Science topic

Atoms - Science topic

Explore the latest questions and answers in Atoms, and find Atoms experts.
Questions related to Atoms
  • asked a question related to Atoms
Question
5 answers
Here, a ligand search is done to get the CGENFF force field for serotonin. But the atom type is mismatched.
Relevant answer
Answer
I actually used to have similar issues before.
Simply Open your PDB complex using notepad and locate the atom number indicate here. The old name means what is in the complex initially. The new means what you should change it to. Just simply use notepad to edit and it will be sorted. I hope this helped
  • asked a question related to Atoms
Question
2 answers
Hello,
I hope that my question is not too obvious but I can't find a satisfying answer. I'm studying a very simple box of 8000 Argon atoms in a Lennard-Jones potential. I want to study many different samples to then average over them. I was thinking of using one equilibration of the system (NVT) and then running it for some time, and using this as my second equilibrated system. My question is: how long should I run the equilibration again for them to be decorrelated in time ? I was thinking 50ps, but I would like something optimal. Thank you for your answers.
Relevant answer
Answer
Thank you :) I did that, and it helped me!
  • asked a question related to Atoms
Question
2 answers
I am trying to run MD calculations with an RNA aptamer in Amber. The first step (detachement of hydrogens) occurs fine:
pdb4amber -y -i 7kd1.pdb -o apt-nh.pdb
However, this command gives the message:
"The following residues had alternate locations: U_21"
Than, I go with a command @tleap -f leaprc.RNA.OL3@ which works fine.
Than I print:
rec=loadpdb apt-nh.pdb
which results in:
Created a new atom named: P within residue: .R<G5 1>
Created a new atom named: OP1 within residue: .R<G5 1>
Created a new atom named: OP2 within residue: .R<G5 1>
Created a new atom named: OP3 within residue: .R<G5 1>
total atoms in file: 1914
Leap added 961 missing atoms according to residue templates:
961 H / lone pairs
The file contained 4 atoms not in residue templates
I type:
set default PBRadii mbondi2
Finally, I try to generate a topology file "saveamberparm rec apt.prmtop apt.inpcrd", which results in:
Warning: The unperturbed charge of the unit (-88.000000) is not zero.
FATAL: Atom .R<G5 1>.A<P 33> does not have a type.
FATAL: Atom .R<G5 1>.A<OP1 34> does not have a type.
FATAL: Atom .R<G5 1>.A<OP2 35> does not have a type.
FATAL: Atom .R<G5 1>.A<OP3 36> does not have a type.
Error: Failed to generate parameters
Warning: Parameter file was not saved.
However, when I look through the pdb file I cannot see abnormalities or missing atom types. So what is wrong with my pdb file (attached)?
Relevant answer
Answer
What helped me is to manually delete atoms added by Amber from comp.pdb file produced at the following step:
complex=combine {rec lig}
savepdb complex comp.pdb
The issue is now corrected, everything works fine.
  • asked a question related to Atoms
Question
2 answers
Dear colleagues, I am aware of the differences between the RHF and UHF approximations. In RHF the same orbitals are used for the alpha and beta spin electrons, and the unpaired electron will be at the HOMO orbital, while in the UHF calculations different sets of orbitals are calculated for the alpha and beta spin electrons.
In an RHF calculation the free valence e.g. in an OH radical will be 1 on the oxgen atom and 0 on the hydrogen atom, the spin population will be 1 on the oxygen and 0 on the hydrogen atom. The spin density will be, however, 0 on both atoms, as the same orbitals are used for both spins. In the UHF approximation, however (using 4-31G orbitals, at the optimized UHF geometry the three valences are 1.005 on the oxygen and 0.004 on the hydrogen, the Mulliken spin populations are 1.05988 and -0.05988 on O and H atoms respectively, the spin densities are 0.1954493 and -0.0289111 on the oxygen and hydrogen atoms.
My question is as follows: if, e.g. we want to calculate spin densities for EPR hyperfine constants, is it possible at all to use the RHF approximation, which gives free valence but zero spin density, or only the UHF approximation? I know that RHF calculations are faster and simpler, and I also heard the the UHF functions are "spin contaminated" but I am not quite sure how is it related the above problem?
Looking forward to your comments.
Relevant answer
Answer
  • asked a question related to Atoms
Question
1 answer
Interference between two levels occurs through this contraction that occurs to space-time, and therefore, if we assume that the electron is in the third level, such as the sodium atom, and according to de Broglie’s law, the third level needs 3 ripples, so if a contraction occurs from the higher level until it interferes with the electron level, such as level 4 It is in the form of 3 ripples, and if there is interference from level 6 with the electron level, which is in level 3, it occurs in the form of 3 ripples, but the difference is that level 6 is the ripple amplitude (vibration amplitude) is higher than level 4.
Relevant answer
Answer
The idea that Gravitational changes in Spacetine Geometry occur on an Angstrom scale simply exemplifies not knowing the subject, as is the math. Why not actualy study Theoretical Physics rather than dream about it? I dont understand students who fear the math.
  • asked a question related to Atoms
Question
3 answers
About materials properties of BST (BaSrTiO3) and STO (SrTiO3)
Relevant answer
Answer
There is no theory based equation approach for this. you need a lot of data and build a calibratuon curve.
  • asked a question related to Atoms
Question
1 answer
Hi all,
Thanks for taking the time to help me. I have generated a charged oligomer chain using acepype, as it is the only software I have been able to find to automatically parametrize using the OPLS-AA force field. However, the output file indicates that there are atoms that it could not define. I have attached the files for further clarity. Would it be enough to define these groups by hand, assigning them to the functional groups that suit them best in the topology file with this force field?
Relevant answer
Answer
When generating topology files with acpype (which uses Antechamber and GAFF primarily), encountering undefined atoms or residues when using the OPLS-AA force field is relatively common, especially if acpype cannot match certain groups with the correct parameters in its database. If your output file has unidentified atoms, manually assigning them in the topology file can work, especially if you have a clear understanding of the groups involved and the functional groups they resemble.
Here are some steps and best practices:
  1. Identify and Verify Groups: Look closely at the atoms flagged as undefined. Map these to corresponding functional groups in the OPLS-AA parameter set as accurately as possible. This step ensures that any substitutions you make align with OPLS-AA's parameterizations.
  2. Manual Parameterization: When defining these groups by hand, ensure consistency by consulting OPLS-AA documentation or related literature to confirm the compatibility of force constants, partial charges, and bond parameters with the oligomer’s structure. This manual assignment will involve:Assigning atomic charges and force field types. Ensuring bond, angle, and dihedral parameters align with functional group analogs in OPLS-AA.
  3. Topology File Updates: Modify the topology file by assigning missing parameters directly within it. This approach should be undertaken with caution, as small errors can destabilize simulations. Additionally, test the modified file by running a short minimization to verify stability before running full-scale simulations.
  4. Testing and Validation: Run validation tests, such as energy minimizations and short molecular dynamics simulations, to ensure that the assigned parameters result in stable configurations.
Alternatively, tools like LigParGen or ParamChem might be able to assist with parameterization using OPLS-AA, though these tools may have limitations on specific oligomer types.
  • asked a question related to Atoms
Question
1 answer
I am attempting to repair missing atoms in two protein structures (PI3KR1 and PI3KCA; PDB IDs: 4JPS and 7PG5) using AutoDock Tools for an upcoming molecular docking study. However, I keep encountering an error (see attached image) and have been struggling to resolve this for several days. Can anyone provide assistance?
Relevant answer
Answer
You can use PyMol to add the missing atoms as its more relaible or you can use CHARMM-GUI (online tool).
regards
  • asked a question related to Atoms
Question
2 answers
I want to do xrd rietveld refinement by using X'pert Highscore Plus program.
When execute search and peak, In my quality I don't have 'skip without the structure pattern'.
1. Why my program doesn't have skip without the structure pattern?
2. When doing rietveld refinement using reference, it didn't detect 'no valid atom position available'
X'pert Highscore Plus - v 3.00
I have database, I don't know the problem....
Please help....
Relevant answer
Answer
i have the same problem. i cant see the option "skip pattern without structural data in my highscore plus program.
  • asked a question related to Atoms
Question
3 answers
Dear all
i want to opt my complex with mp2 (6-311++g(d,p)) for C H N O atoms and GenECP (lanl2dz) for Zn atom. but i encounter this error:
Rotational constants (GHZ): 1.2999882 0.4336825 0.3251961
General basis read from cards: (5D, 7F)
QPErr --- A syntax error was detected in the input line.
'
Last state="Top"
TCursr= 927 LCursr= 0
Error reading general basis specification.
Error termination via Lnk1e in /opt/g09/g09/l301.exe at Sat Oct 26 22:20:20 2024.
Job cpu time: 0 days 0 hours 0 minutes 0.3 seconds.
File lengths (MBytes): RWF= 27 Int= 0 D2E= 0 Chk= 2 Scr= 2please
please suggest a solution and just do not link to gaussian error messages since i read it
here i attach the input file.
thanks guys
Relevant answer
Answer
Dear Fatemeh Razavi,
Sometimes empty lines are important in gaussian inputs, try:
C H N O 0
6-311++g(d,p)
****
Zn 0
lanl2dz
****
Zn 0
lanl2dz ECP
Some keys:
- The stars **** indicate the end of input basis. Then an empty line as a good practice.
- Also, in the last line, "ECP" is missing in your input.
- By the way, basis set for Zn is not repeated. The first section of Zn corresponds to the basis set for valence electrons. The second section of Zn are associated with the core electrons, calculated with a pseudopotential.
Best, Pablo
  • asked a question related to Atoms
Question
5 answers
How does the substrate atom hold the sample atoms on the film?
Relevant answer
Answer
Main question:
If you look at the basic structures fcc and hcp, you find that fcc(111) and hcp(001) are both maximum density packed surface structures with triangles. Therefore these two facets match with each other and you can do epitaxy there. Please be aware that, since fcc has an abcabc stacking and hcp just ababab, an fcc-derived layer provides one additional "structure variable" about the stacking direction, so you can expect epitaxial growth without any texture issues of hcp(001) on fcc(111), but if you try it the other way round, you can expect the fcc layer to stack both abcabc and cbacba (symmetry-equivalent to a 60° or 180° rotated domain), so if you check the texture with an XRD pole figure, you can expect twice as many spots as on a single crystal.
Secondary question:
The adatoms can be bound to the substrate by any known kind of bond, be it van der Waals, covalent, ionic, metallic or quite often a mix of them. That's not a question of the crystal structure but more a question of what the specifice atoms prefer when they react with each other.
  • asked a question related to Atoms
Question
1 answer
Hello, everybody. I am an undergraduate student. I have tried calculating the [4Fe-4S] cluster's energy and frequency using the Gaussian program. But the problem is that the program does not recognize sulfur from the cytidine, even though I removed the sulfur to make it an ion. How do I calculate it? How do I make the input structure? How to insert the sulfur atom?
Thank you.
Relevant answer
Answer
Hello! To calculate the energy and frequency of the [4Fe-4S] cluster in Gaussian, you need to pay attention to several key points, especially in the construction of the input structure and the insertion of the sulfur atoms.
Here are some guiding steps:
1. Build the structure:
⦁ First, you can use molecular modeling software (such as Avogadro, Gaussian View, or GaussView) to create your [4Fe-4S] model. In the model, you need to make sure the chemical environments of fluorine and sulfur are correct.
2. Insert sulfur atoms:
⦁ When inserting sulfur atoms in your structure, make sure you use the correct chemical symbol (S) and that the relative position to the iron atom conforms to the geometry of the [4Fe-4S] structure.
⦁ The bond lengths and bond angles of the sulfur atoms should be set according to literature or experimental data.
3. Generate Gaussian input file:
⦁ After creating the model, export it to the Gaussian input file format (usually .gjf or .com file).
⦁ The following key parts need to be included in the input file:
⦁ Calculation method (e.g. DFT, HF) and basis set (e.g. 6-31G*).
⦁ Molecular coordinates: Make sure the coordinates of all atoms (including sulfur) are described properly.
  • asked a question related to Atoms
Question
5 answers
Using Gaussian, I tried to check the Total Energy of the 4-valent atom. I found that the energy of the neutral atom was calculated, but the Total energy of the 4-valent atom was derived as a blank. I don't know why. Which variable should I adjust? I have attached some calculation results to show the situation. I need help.
Relevant answer
Answer
You need to check carefully about the introduction of basis. The question is that when you rise to 4+, there is no electrons left in Sn (I suppose it is Sn).
Here is the link for how SDD basis. Institute for Theoretical Chemistry (uni-koeln.de). I don't know which version it is in Gaussian. It seems to be something like ECP46SDF, which means the first 46 electrons are regarded as potential, and calculate the wavefunction of the left electrons. If it is 4+, there is no electrons left to calculate. Of course there is no electron energy. If you want to make it run, you can try some other basis sets like def2-qzvp.
Another thing to mention, you calculation is very strange. Your method may not give you right answer. Calculation of one atom is rare. And normal method (like b3lyp) can not describe the metal atom well. There maybe also multi-reference questions. Can you tell me what is your aim?
  • asked a question related to Atoms
Question
3 answers
Interference between two levels occurs through this contraction that occurs to space-time, and therefore, if we assume that the electron is in the third level, such as the sodium atom, and according to de Broglie’s law, the third level needs 3 ripples, so if a contraction occurs from the higher level until it interferes with the electron level, such as level 4 It is in the form of 3 ripples, and if there is interference from level 6 with the electron level, which is in level 3, it occurs in the form of 3 ripples, but the difference is that level 6 is the ripple amplitude (vibration amplitude) is higher than level 4.
Relevant answer
Answer
Light emission at a given frequency
Involves 2 levels, not one.
Ie
h nu= E2 -E1
Or E(n+1) -E(n)
The same goes for photon absorption.
  • asked a question related to Atoms
Question
1 answer
I want to simulate polymer in water for that I have confusion in reduce units according my understanding of reduce units if we perform simulation in reduce units means we are make a generalize model because we set sigma , Ellison, mass and other bonding parameters equal to one means we are simulating not real model.
It's like we are doing simulation of ball and spring model.
My confusion is regarding parameter that is equal to one or not for all atoms?
Relevant answer
Answer
Your understanding of reduced units in molecular dynamics simulations is on the right track. Reduced units are a way to scale the physical properties of a system so that certain parameters are set to unity, which can simplify calculations and make the simulation more general. Here’s a clearer explanation of reduced units and how they apply to your polymer in water simulation:
Reduced Units:
In reduced units, the following parameters are often set to 1:
  • Length (σ): The length unit is typically set to the size of a particle, which could be the van der Waals radius or another relevant length scale.
  • Energy (ε): The energy unit is often set to the strength of the pairwise Lennard-Jones interaction between particles.
  • Mass (m): The mass unit is set to the mass of a particle in the system.
These units are defined relative to the system you are studying. For example, in a Lennard-Jones fluid, σ might be the distance at which the interparticle potential is zero, and ε might be the depth of the potential well.
Are All Parameters Equal to One?
No, not all parameters are equal to one. Only the base units (length, energy, and mass) are set to one. Other parameters, such as bond lengths, angles, charges, and force constants, are scaled relative to these base units. Here’s how it works for your polymer in water system:
  • Bond lengths and angles: These are scaled relative to the length unit (σ). For example, if a bond length in your polymer is 0.2 nm, and σ is defined as 0.1 nm, then the bond length in reduced units would be 2σ.
  • Charges: These are scaled relative to the square root of the energy unit (ε) divided by the length unit (σ). This ensures that the electrostatic interaction energy has the correct dimensions.
  • Force constants: For bonded interactions like harmonic bonds and angles, the force constants are scaled relative to the energy unit (ε) and the length or angle unit.
Simulating a Real Model:
When you perform a simulation in reduced units, you are still simulating a real model. The advantage is that the simulation becomes more general and can be applied to a wide range of systems with similar interactions. The parameters you use (like σ, ε, and m) are chosen to reflect the physical properties of the actual system you are studying.
Polymer in Water:
For a polymer in water, you would typically define your reduced units based on the properties of the solvent (water) and the polymer. For example:
  • Length (σ): Could be set to the oxygen-oxygen van der Waals distance in water.
  • Energy (ε): Could be set to the strength of the Lennard-Jones interaction between water molecules.
  • Mass (m): Could be set to the mass of a water molecule.
Then, the polymer’s properties would be scaled accordingly. This does not mean you are simulating a ball and spring model; rather, it’s a way to abstract the physical properties to a set of units that makes the simulation more manageable and computationally efficient.
In summary, using reduced units does not mean you are simulating a non-real model. It is a way to standardize the system so that the simulation can be applied broadly while still reflecting the physical properties of the real system. The choice of what parameters to set to one and how to scale the others depends on the specifics of the system you are simulating.
  • asked a question related to Atoms
Question
1 answer
what is benifit of doing molecular simualiton in reduce units especially if have moleuclar like dna or potein where are so many different atoms??
Relevant answer
I use the program SMOG: Structure-based Models for Biomolecules for this. The benefit of performing molecular simulations in reduced units is the simplification of calculations, which can be especially useful for complex systems like DNA or proteins with many different types of atoms. In reduced units, variables like energy, temperature, pressure, and distance are rescaled to dimensionless values based on characteristic parameters of the system (such as interaction energy and distance). This makes it easier to compare different simulations, regardless of the exact physical properties of the atoms involved.
For large molecules like proteins or DNA, which have many atoms with varying masses and interactions, using reduced units allows you to treat all these atoms in a more generic way, without needing to account for the specific physical constants of each atom type. This can speed up the calculations, making the process more efficient, and allows for clearer analysis of the system's behavior patterns.
  • asked a question related to Atoms
Question
5 answers
There are 4 samples that deposited different process times. Xrd datas of them are different (shows different phases and different atomical rates of elemental compounds). But, Raman analyzes of them stayed same. Is that possible?
Relevant answer
Answer
Elif Özerbaş Yes, it is possible for the XRD (X-ray diffraction) data of the samples to show different phases or elemental compositions, while the Raman analysis remains unchanged. This discrepancy can occur due to several factors related to the sensitivity and mechanisms of each analytical technique:
  1. XRD Sensitivity to Crystalline Structure: XRD is primarily sensitive to the crystalline structure of materials. It detects how atoms are arranged in a periodic lattice, which provides information about different phases, crystal sizes, and lattice parameters. A small change in process time could lead to changes in the crystallinity, phase transitions, or changes in atomic arrangements. Thus, XRD might reveal differences between samples in terms of phase composition or crystallinity.
  2. Raman Sensitivity to Molecular Bonds: Raman spectroscopy, on the other hand, is sensitive to molecular vibrations and the chemical bonds within the sample. If the overall bonding environment or chemical composition remains relatively similar (i.e., no significant change in the bonding of functional groups or major elemental composition), Raman spectra may remain unchanged, despite structural or phase changes detectable by XRD.
  3. Non-Crystalline or Amorphous Phases: XRD is very sensitive to crystalline phases, but if the material is partially amorphous or the Raman-active bonds do not vary significantly between the phases, Raman may not detect these changes. This could explain why XRD shows different phases while Raman data remains the same.
  4. Surface vs. Bulk Sensitivity: XRD and Raman spectroscopy probe different depths in a sample. XRD is more bulk-sensitive, whereas Raman can be surface-sensitive depending on the material and setup. If the changes in crystallinity or phase detected by XRD are primarily in the bulk while the surface properties (such as chemical bonds) remain unchanged, this could lead to the observed discrepancy.
In summary, it is entirely possible for the XRD data to differ due to changes in crystallinity or phase, while the Raman spectra remain the same if the bonding environment or chemical composition has not significantly changed.
  • asked a question related to Atoms
Question
1 answer
2) How is the formation of the universe?
The universe, at its most fundamental level, appears to operate according to the principles of quantum mechanics, where uncertainty and indeterminacy play key roles in shaping its evolution. In classical computational theory, Turing’s Halting Problem demonstrates that it is impossible to predict whether a system will reach a final state or run indefinitely. This raises profound questions about the nature of the universe: could it, too, one day halt, reaching a state where no further evolution is possible? However, the inherent unpredictability of quantum mechanics—through phenomena like superposition, quantum fluctuations, and entanglement—may offer a safeguard against such a scenario. This paper explores the intersection of quantum mechanics and the Halting Problem, suggesting that quantum uncertainty prevents the universe from settling into a static, final state. By continuously introducing randomness and variation into the fabric of reality, quantum processes ensure the universe remains in perpetual motion, avoiding a halting condition. We will examine the scientific and philosophical implications of this theory and its potential to reshape our understanding of cosmology.
Stam Nicolis added a reply:
The evolution of the universe, from the inflationary epoch onwards, is described by classical, not quantum, gravity.
Stam Nicolis added a reply:
Turing's halting problem doesn't have anything to do with the subject of cosmology, or any subject, where the equations that describe the evolution of the system under study are known.
In particular the answer to the question of the evolution of the universe is known: It's described by the de Sitter solution to Einstein's equations, that is its expansion is accelerating, although with a very slow rate. The question, whose answer isn't, yet, known is what happened before the inflationary epoch. It is for this question that a new theory is needed, that can match to classical description of spacetime and the quantum description of matter that emerged from it.
Stam Nicolis added a reply:
That quantum mechanics provides a probabilistic description isn't particular to it. Classical mechanics, also provides a probabilistic description, since classical systems are, typically, chaotic and integrable systems are the exception, not the rule. The only difference between a quantum system and its classical limit is the space of states.
Dale Fulton added a reply:
Turing's Halting Problem comes from computer sciences and the study of such systems. The question is whether nature obeys any of our "halting" knowledge and our myopic perspective of the universe. Likely not.
Javad Fardaei added a reply:
Dear Abbas We must realize that our universe is a complete entity that it is running billions of galaxies and place billions solar systems in each galaxy in most accurate way is not result of accident big bang, or run mechanically as our past icons (quantum mechanics, or any mechanical entanglement) stated it. Our universe like anything else (inside of it) has born and it has a natural journey. If you accept this fact, then we are in right track as far as knowing intelligent atom, not mechanical atom.
Unfortunately science believes someone imagination of collapsing our mechanical physics into nature (atom)
Reading this unprecedented articles might help your view of this magnificent universe of ours.
1-Article Universe's Rotation and Its Benefit:
2-Article Intelligent Atom:
Relevant answer
Answer
Subject: Invitation to Join Dailyplanet.Club and Response to Your Question on Universe Formation
Dear Abbas Kashani,
I hope you are doing well.
I would like to extend an invitation to you to join us at www.Dailyplanet.Club, a community of innovators, researchers, and forward thinkers exploring the boundaries of science, technology, and sustainability. Your interest in quantum mechanics and the formation of the universe aligns perfectly with our mission, and I believe your contributions would be highly valuable.
Regarding your question about the formation of the universe:
  • The Big Bang theory suggests the universe began as a singularity about 13.8 billion years ago, followed by rapid expansion. Quantum mechanics plays a crucial role in explaining early-universe phenomena, especially during the inflationary period when quantum fluctuations may have given rise to the large-scale structure we see today.
  • Quantum mechanics, with its inherent uncertainty and indeterminacy, governs the behavior of particles at the smallest scales, including the primordial particles in the early universe. This uncertainty may have influenced cosmic evolution, leading to the distribution of matter and energy across the cosmos.
  • Beyond classical understanding, theories like quantum gravity and string theory are being explored to unify general relativity with quantum mechanics, giving us deeper insight into how the universe operates at both cosmic and quantum scales.
That said, I believe that Darwin’s theory, while influential, is not entirely accurate when it comes to understanding the formation of the planet and the universe. We have found some amazing results at Dailyplanet.Club, which present a different perspective, showing how the universe and planetary formation could be viewed through a new, intuitive lens. These findings are only shared with our members, as we are building something transformative—not just a place for research, but a platform that makes a tangible difference by producing real-world innovations in factories, infrastructure, and beyond.
I hope this provides some insight, and I look forward to having you join Dailyplanet.Club, where together we can create something truly remarkable.
Best regards, MJ CEO, Dailyplanet.Club MJHSA Ltd.
  • asked a question related to Atoms
Question
1 answer
Question:
I am performing thermochemistry calculations on organic molecules to investigate carbon stability in anoxic systems, focusing on the Gibbs free energy of oxidation per carbon atom (ΔGOx/C) for redox half-reactions. This is based on the work of LaRowe and Van Cappellen (2011) (DOI: 10.1016/j.gca.2011.01.020), and I am using Gaussian with the setup: # B3LYP/6-311+G(2d,p) Opt Freq SCRF=SMD.
My goal is to calculate the Gibbs free energy of oxidation for the redox half-reaction (not the full oxidation) per carbon atom, and I am working with a large dataset of over 4000 molecules. I have been using two different methods to obtain ΔGOx/C, but I am facing significant discrepancies in my results compared to the literature.
Here are the two methods I am using:
  1. Formation Energy Method:Step 1: I calculate the atomization energy of each molecule by summing the computed energies of its constituent atoms and subtracting the total energy of the molecule at 0 K, including zero-point energy (ZPE). Step 2: Using standard tables, I obtain the heats of formation for each atom, and then calculate the heat of formation for the molecule at 0 K. Step 3: I apply enthalpy corrections to adjust these values from 0 K to 298.15 K. Step 4: I compute the entropy for each molecule at 298 K and use this to calculate the Gibbs free energy of formation at 298 K. Step 5: I then apply the oxidation half-reaction equation for organic molecules (where products are HCO3(-), NH4(+), HS(-), HPO4(-2)) and compute the Gibbs free energy of oxidation (ΔGOx) for the redox half-reaction as Σ(ΔGproducts) − Σ(ΔGreactants). Finally, I divide this value by the number of carbon atoms to obtain the Gibbs free energy of oxidation per carbon atom (ΔGOx/C). Problem: Despite following these steps, the ΔGOx/C values I obtain deviate significantly from those reported in the literature. For example, my result for glucose is 90.76 kJ/molC, whereas the literature (LaRowe and Van Cappellen, DOI: 10.1016/j.gca.2011.01.020) reports approximately 65 kJ/molC. This deviation seems to be more prominent for molecules with non-neutral charges.
  2. GIE Method (Gaussian Internal Energy Method):Step 1: For each molecule (both reactants and products in the half-reaction), I perform a DFT geometry optimization and frequency calculation using B3LYP/6-311+G(2d,p) Opt Freq SCRF=SMD. Step 2: I sum the electronic and thermal Gibbs free energies directly from the Gaussian log files. Step 3: I use the same oxidation half-reaction equation as in the Formation Energy Method to calculate ΔGOx. I then divide by the number of carbon atoms to get ΔGOx/C. Example (For glucose):The half-reaction is: C6H12O6 + 12H2O → 6HCO3(-) + 24e(-) + 30H(+). Using the GIE method, I get the following Gibbs free energies from Gaussian:ΔG_HCO3(−) = -264.67 Hartree ΔG_H(+) = -0.41897 Hartree (from literature: DOI: 10.1016/j.molliq.2020.114919) ΔG_H2O = -76.47 Hartree ΔG_C6H12O6 = -687.29 Hartree The total Gibbs free energy for the reaction (ΔGOx) is calculated as: ΔGreaction=([6×(−264.67)+30×(−0.41897)]−[−687.29+12×(−76.47)])×2625.5=11421.3 kJ/mol\Delta G_{\text{reaction}} = \left( [6 \times (-264.67) + 30 \times (-0.41897)] - [-687.29 + 12 \times (-76.47)] \right) \times 2625.5 = 11421.3 \, \text{kJ/mol}ΔGreaction​=([6×(−264.67)+30×(−0.41897)]−[−687.29+12×(−76.47)])×2625.5=11421.3kJ/mol Dividing by 6 (the number of carbon atoms in glucose) gives ΔGOx/C = 1903.55 kJ/molC. Problem: The ΔGOx/C values I obtain using this method are much larger than expected, often about 26.4 times higher. For glucose, my ΔGOx/C = 1903.55 kJ/molC, whereas the literature reports ~65 kJ/molC. Interestingly, when I apply an empirical scaling factor of 26.4, my results align closely with the literature (R² = 0.91), but I cannot explain why this factor is necessary.
Key Issues:
  • Large deviations in the calculated ΔGOx/C for the redox half-reaction using both methods, with GIE method values being consistently about 26.4 times too large.
  • The unexplained empirical scaling factor (26.4) that aligns the GIE results with the literature.
  • Uncertainty about whether B3LYP/6-311+G(2d,p) Opt Freq SCRF=SMD is appropriate for calculating ΔGOx/C for redox half-reactions or if a different method would yield more accurate results.
  • The need for a computationally efficient method, given the large dataset of over 4000 molecules.
Questions:
  1. What could be causing the large discrepancies and the unexplained scaling factor (26.4) in my ΔGOx/C values for the redox half-reaction?
  2. Is there a more appropriate computational method (functional/basis set) for calculating ΔGOx/C in these half-reactions that balances accuracy and computational efficiency?
  3. Could these issues stem from the way I am interpreting and processing the thermodynamic data from Gaussian, or might they be related to the specific setup of the redox half-reaction?
I’ve consulted Gaussian support, but the help they can provide is limited to software usage. I would appreciate any advice or suggestions on how to resolve these discrepancies and improve the accuracy of my calculations.
Thank you for your time and any insights you can offer!
Relevant answer
Answer
The large discrepancies and the unexplained scaling factor (26.4) in your ΔGOx/C values could stem from a combination of several factors related to the computational setup and data processing:
1. Scaling Factor (26.4) and Unit Conversion
  • The factor of 26.4 suggests a possible unit conversion issue, as Hartree to kJ/mol conversion should be around 2625.5 kJ/mol. Double-check the factor and the number of electrons in the reaction, as errors in applying scaling factors for multiple carbon atoms could lead to discrepancies.
  • Ensure that all energy terms are consistently converted between units (Hartree to kJ/mol) and applied correctly across reactants and products.
2. Reference States and Half-Reactions
  • Redox half-reactions can introduce challenges because the free energy of the products and reactants must be referenced accurately to their respective states. Misunderstandings in applying standard states (aqueous, gas-phase, etc.) or interpreting solvation models can lead to large errors.
  • The inclusion of charged species (e.g., HCO3⁻, NH4⁺) might be a source of additional discrepancy. Solvation models like SMD handle these species differently depending on the environment specified, so ensure your solvation models and boundary conditions are appropriate for the redox reaction in question.
3. DFT Method and Basis Set
  • The B3LYP functional with the 6-311+G(2d,p) basis set is widely used but may not be ideal for redox processes, especially when solvation and ionization energies are crucial. B3LYP can sometimes underestimate barrier heights and give inconsistent results for charged species in solvent environments.
  • Consider trying a more robust functional for redox processes like M06-2X or PBE0, which are known to better handle electron correlation and charge distribution, especially in systems involving transition states or ionized products.
  • For large datasets, composite methods like CBS-QB3 or G4, though more expensive computationally, could provide a better trade-off between accuracy and scalability when applied selectively to key molecules for benchmarking.
4. Zero-Point Energy (ZPE) and Thermal Corrections
  • Ensure that the zero-point energy (ZPE) corrections and thermal contributions (enthalpy and entropy) are applied consistently. Gaussian sometimes outputs ZPE separately from thermal corrections, so combining them improperly might be a source of error.
  • Make sure your thermal corrections align with the literature’s method. For example, any slight differences in the calculation temperature (298 K vs. 273 K) or the treatment of ZPE could cause deviations.
5. Reaction Setup and Charge Balancing
  • For redox half-reactions, you must carefully balance electron counts and charges to ensure consistent free energy values. Unintended charge imbalances or incorrect stoichiometric coefficients in the reaction setup could lead to inflated ΔG values.
  • Double-check that your reaction formula for products and reactants is correctly balanced in terms of both mass and charge.
6. Empirical Scaling
  • The empirical scaling factor of 26.4 aligning your GIE results with the literature suggests a consistent systematic issue across the dataset. This factor might represent a combined error from multiple sources: unit conversion, incomplete thermal corrections, or incorrect charge balance in redox reactions.
  • Empirical scaling should not be necessary if the method is fully correct. Identifying the root cause of this consistent error will require examining these different factors systematically.
Recommendations:
  • Unit Check: Double-check the Hartree to kJ/mol conversion and ensure consistent units across your datasets.
  • Benchmark Method: Run a few benchmark calculations using more accurate methods (like M06-2X or a composite method) for a subset of molecules to see if this resolves discrepancies. These results can then help adjust your broader dataset.
  • Thermodynamic Consistency: Carefully reassess your thermodynamic corrections for ZPE and enthalpy, as slight deviations could amplify across larger datasets.
By addressing these potential sources of error, you should be able to reduce the discrepancies and improve the accuracy of your Gibbs free energy calculations for redox half-reactions.
  • asked a question related to Atoms
Question
1 answer
How Penrose - Hameroff theory is crucial to answer this question?
Relevant answer
Answer
AI doesn't have anything to do with consciousness, so there's no bridge to build.
We're not instantly connected to anything, either; ``instantaneous transmission'' of any information (e.g. forces) is an approximation, that's understood for more than a century now.
  • asked a question related to Atoms
Question
4 answers
In an intermetallic phase like Ni3Al, each Al is surrounded by 12 Ni atoms.
So for a dilute Ni alloy with a small concentration of Al atoms, it cannot be nearest neighbour interactions that are responsible for the formation of the phase because in solid solution, each Al is also surrounded by 12 Ni neighbours.
This means that next-nearest neighbour interactions must be responsible for this.
What exactly are these effects? Is it a delocalization of electrons in orbitals that are different when there are Al-Ni-Al chains?
Is it an effect of the density of states, although an intermetallic phase and a solid solution only differ in the fourth moments of the local DOS (4-step hops are the first to be different, with Al-Ni-Al-Ni being possible in the intermetallic, but not in the dilute solution)?
Is there a clear physical picture of this?
Relevant answer
Answer
Well, the different lattice structures of the transition metals canbe explained from the DOS moments theorem (see Pettifor 1987 or the 1993 book by Sutton). That, however, does not explain intermetallics.
  • asked a question related to Atoms
Question
4 answers
Dear researchers,
Very recently, I have downloaded the last version of IGMPlot, version 3.08. I found some new descriptors included in this very nice, complete, and versatile version. One of newly proposed descriptors is "qg" which makes 2-D plots colored based a given scale ranging from 1 (blue color) to 4 (red color). Please let me know the exact and straightforward meaning of these numbers and colors. Indeed, what is the practical usage of "qg" index? or, what is its interpretation when a given inter- or intra-fragment interactions is analyzed? I cannot understand what concept should be taken into account when a 2-D plot of delta_g_inter versus sign (lambda2*Rho) is colored from blue to red (from number 1 to 4). What practical information one can obtain depending on the color type of a given picke. For instance, a taller picke (a larger delta_g value) means a stronger interaction but what statement should be provided for a smaller (blue) or greater (red) value of "qg"? In advance, too many thanks for any help.
Best,
Saeed
Relevant answer
Answer
In IGMPLOT 3.08, the "qg" descriptor is used to indicate the quality of the grid in the plotted data. It helps in evaluating the grid's resolution and accuracy in visualizing the plotted information.
  • asked a question related to Atoms
Question
6 answers
i am currently working on Density of States (DOS) calculations for a nanocluster consisting of 99 atoms and 370 bands using VASP. In my setup, I am using a cluster with 40 cores distributed across 2 nodes, with 20 cores per node. The calculation is configured to run at the gamma point with a 1x1x1 k-point grid. I am executing the job with the following command:(mpirun -np 8 vasp_std)
However, despite these settings, my calculations either get stuck or stop without completing. I am particularly concerned about optimizing the parallelization tags such as NBANDS, NCORE, and others to ensure that the calculation runs efficiently and successfully. Specifically, I am interested in the best approach to parallelize over bands to utilize the available computational resources effectively?
Relevant answer
Answer
VASP has three different executables vasp_std, vasp_ncl, vasp_gam:
vasp_std is standard version of vasp (general use);
vasp_ncl is for non-collinear calculations, for instance to perform fully non-collinear magnetic structure calculations or to include spin-orbit interactions in the calculations;
vasp_gam is the version of vasp working at the Gamma ponit only.
N.B.: 'Definitions' retrieved from Google.
Therefore, using mpirun goes like this (depending on your case):
(1) mpirun -np 40 vasp_std
(2) mpirun -np 40 vasp_ncl
(3) mpirun -np 40 vasp_gam
For example, whenever you want to perform non-collinear calculations, vasp_ncl must be used, and LNONCOLLINEAR must be set to TRUE, along with other tags. This sort of calculation will only run under the vasp_ncl executable. Similarly, although not mandatory as in non-collinear calculations, when running at the Gamma point only (which you are already doing, as set in your KPOINTS file), you can simply use (3). I would say (1) would also work.
Back to the original problem, I don't think it's a matter of vasp_std or vasp_gam, as both can run Gamma-point calculations. I'd say the vasp_gam version is just optimized specifically for Gamma-point-only calc., and you can benefit from this optimization.
Best,
Gabriel Vinicius
  • asked a question related to Atoms
Question
3 answers
As I know how to do refinement of pure sample by Fullprof software, how should done perform the refinement when doping is done into the pure sample, where substitution doping occurs. My concerns are:
1) Whether should I refine the whole doped sample by not incorporating the doped compound in atoms section in the Fullprof software and at last incorporate it (i.e. without adding the doped atoms and just doing a normal refinement of a pure compound)
or
2) When the cif file is added, then in the atoms section should I add them before performing the refinement.(I tried this way but was getting scattering errors).
3) What changes must be done, like in atoms does x,y and z changes or just the occupancy part changes. Say for example the occupancy is 0.4912 of A atoms and one is doing, say 10% of B atoms such that it will replace A atoms, so does A occupancy becomes then 0.44208 and B atoms occupancy as 0.04912 and what about its x y and z parameters?
Relevant answer
Answer
To perform the refinement you should have an idea of the sites on which your dopant ions could be located. If you don't know the exact sites, you can try different models and compare the results (agreement factors and graphical comparison). You need a detailed pattern to have reliable results. Then only the site occupancy changes, not the coordinates. The values of occupancies usually are those of the prepared stoichiometry of the sample, as you wrote in your query. If you want to determine (i.e. refine) the occupancy factors, you should have a sufficient contrast between the atoms occupying the same sites (i.e. to have different atomic scattering factors). You can certainly refine the atomic coordinates, some variations can occur with respect to the undoped phase, but for the dopant ions the coordinates are the same of the original ions.
  • asked a question related to Atoms
Question
2 answers
What happens inside the atom?!
Relevant answer
Answer
Hello Yasmine Mabed.
Octet rule is a theory of chemical bonding. Chemical bonding exist because atoms "want" to be energetically stable. It was found that the atoms of Noble Gases are stable, and generally they don't have to make bonds to be highly stable. This is expressed by the electronic distribution, in which you see that Noble Gases atoms have filled orbitals, like 1s2 2s2 2p6 (Neon), and this is a reference of stability, as Neon atoms exist without bonding with no other atom. Atoms like Carbon have electrons distributed in 1s2 2s2 2p2, therefore they are not stable as Neon, and they must form bonds to be more stable.
The way Carbon forms bonds with hydrogen is called covalent bonding, and they "share" electrons. Carbon has its 2s2 2p2 electrons shared with 4 hydrogens, and 1 electron of each hydrogen is shared with carbon. Now, Carbon has 8 electrons in its valence shell, it reaches the configuration of Neon,
and is much more stable now. This theory works fine for many atoms, however fails to others. When you study the Transition Metals complexes, you see that they don't follow this rule. Then, there are more advanced theories that were proposed to explain them.
Please, reply if this explanation fits answers your questions, and feel free to ask about anything.
Best regards
Ricardo Tadeu
  • asked a question related to Atoms
Question
1 answer
I'm trying to simulate molecular docking with the help of autodocktools. I have added all hydrogens to the protein, computed charges and assigned AD4 type, and the pdbqt file was saved. After that, I adjusted the parameters of grid box and output a gpf file successfully. However, when I run autogrid, the software interface suddenly disappeared and the cmd reported an error: Too many atoms in receptor PDBQT file......the maximum number of atoms, AG_MAX_ATOMS, allowed is 32768...... Sorry, AutoGrid cannot continue. So I want to know whether there is a method to increase the allowed maximum atoms of autodock? Or should I adjust the number of hydrogens or give up this protein? Thanks you!
Relevant answer
Answer
  • asked a question related to Atoms
Question
4 answers
Hi,
I am currently screening more than 2000 compounds virtually on Vina, but I would like to perform covalent docking. Unfortunately, Vina's functionality is limited as its requires manual designation of the reactive atoms on the ligands. Is there any alternative that is free for academic purposes and suited for this sort of task?
Relevant answer
Answer
Use MultiDock Screening Tool
  • asked a question related to Atoms
Question
3 answers
In a supercom with 40 cores/node, normally when I run VASP for a large system with a few hundreds atoms, I set NCORE=20 expecting that 20 cores treat 1 band inside node. Is it OK to apply the same INCAR setting for NEB calculation? When I run with 8 images, I found that all the 8 directories run at the same time. Then, what is happening here? 20 cores for 1 band is applied to 8 calculations at the same time, or do I need to change NCORE if I expect the same performace?
Relevant answer
Answer
I have found this site, https://www.vasp.at/wiki/index.php/Category:Parallelization, where Nnode would be multiple of IMAGES. For example, if I use 20 Nnode, IMAGE=10 where each images run 2 Node. Then NCORE would be set with 80 cores in 2 Nodes such as NCORE=20 or 10, etc.
  • asked a question related to Atoms
Question
1 answer
After performing the molecular docking of ligands containing chlorine atoms, the .pdb files of the complex of the conformers of interest and the respective receptor were generated from the .dlg.pdb output file using the Maestro program. When trying to visualize ligand-receptor interactions, Discovery Studio shows alkyl-type interactions with the chlorine atom.
Does anyone know how this error can be fixed?
Relevant answer
Answer
Open your AutoDock complex file then go to detail description of ligand click on chlorine atom then go to chemistry >element>chlorine. After that check interaction.
  • asked a question related to Atoms
Question
3 answers
Dear All,
I have come across something strange while doing RMSD calculation.
I calculated the RMSD of a mutated protein using the .tpr file generated from Wild type and it does the calculation without any error. Both the systems have different number of atoms and I was anticipating an error, but that didnt happen. Infact, I tried the calculation using totally unrelated .tpr from a different protein and yet it prints some values.
Now I'm totally confused about whats happening. I tried the calculation using two versions of gromacs:2020.2 and 2022 as well.
Can anyone explain what might have gone wrong here ? Or am I making some mistake in understanding.
Thanks and Regards
Relevant answer
Answer
Kindly check the contents of both the tpr files using the 'gmx check' function. Maybe the mutation is not applied correctly in the WT.
  • asked a question related to Atoms
Question
1 answer
I'm trying to cyclise the molecule attached and am having trouble when using methods described for similar looking things. I ran a computational model that suggested that at their closest point, the 2 carbons I am trying to form a bond between are 6 Å apart, which is obviously quite far. So I have 2 questions really, 1) how close would the carbons need to be to each other to be able to form a bond (is it just around 1.54 Å, the bond length of a C-C bond)?
2) Are there ways to force these closer together together?
Relevant answer
Answer
The thing is, computational models usually show the most stable state, but at any temperature above 0K there will be some activated state that has alternate geometry. In organic synthesis the usual way to build this cycle would be to use some metal catalyst that will form a complex with both double bonds in suitable positions and then oxidize it.
  • asked a question related to Atoms
Question
1 answer
I am trying to find the thermal conductivity of a material with 3 atoms kinds through the Green-Kubo method. I could find the LJ pair coefficients of the material in any literature or database. I tried to estimate the values with Lorentz-Berthelot mixing rules but the obtained thermal conductivity with those parameters is much less than the experimental values.
Relevant answer
Answer
Dear Subham,
finding the correct LJ pair coefficients for materials, especially those with multiple atom types, can be challenging when such parameters are not readily available in the literature or databases. When the Lorentz-Berthelot mixing rules are applied and the results still fall short of experimental thermal conductivity values, several factors could be contributing to the discrepancy.
Potential Reasons for Discrepancy - Limitations of the mixing rulkes:
LB mixing rules are an approximation and may not always yield accurate parameters for interactions between different types of atoms, especially in complex materials. This can lead to an underestimation of the interaction strength, affecting thermal conductivity calculations.
Accuracy of Lj parameters - LJ potential might not fully capture the interactions in your material, especially for materials with complex bonding, directional interactions, or significant electronic effects. LJ parameters are often fitted for specific systems, and they might need refinement or alternative potentials like EAM, MEAM, Tersoff etc. to better represent the interactions.
Take into account cuttoff. If the cutoff distances in your simulations are not appropriately chosen, it can lead to inaccuracies in the calculated forces, and hence, the thermal conductivity. Simulation box&time as well - the size of the simulation box and the length of the simulation time can significantly impact the accuracy of the Green-Kubo results. Insufficiently large systems or short simulation times can lead to poor convergence.
At low temperatures, quantum effects might need to be considered, which classical MD using the LJ potential cannot capture.
If the atoms in the material are polarizable or the interactions are anisotropic, the LJ potential may not capture these effects adequately. This can also lead to discrepancies in calculated thermal conductivity.
Consider fitting the LJ parameters (ε and σ) to reproduce known thermodynamic or mechanical properties (e.g., lattice constants, elastic constants) from experiments or quantum mechanical calculations.
Explore using more sophisticated potentials like EAM, MEAM, S-W .... potentials if they exist for your material.
Perform first-principles calculations like DFT to obtain interatomic potentials or directly calculate thermal conductivity using methods like the Boltzmann Transport Equation or MD with ab initio forces.
Search for experimentally fitted L-J parameters or force fields specifically developed for your material in the literature. Materials Project, OpenKIM, or other similar databases might have data relevant to your material.
Apply corrective scaling to the obtained thermal conductivity based on known discrepancies between experimental and calculated values. This should be done carefully and with an understanding of the underlying causes.
Hope it helps.
  • asked a question related to Atoms
Question
3 answers
Hello,
I'm trying to create parameter and coordinate files for a drug (PRG-A01) found on the following page:
I used the guide made by Michael Barton and Tyler Luchko at the following link: https://ambermd.org/tutorials/basic/tutorial4b/index.php
At first, I obtained the sdf structure thanks to the PDB Chemical sketch tool and converted into pdb using MOE (I simply did a quick prep and saved as pdb):
HEADER
REMARK 99
REMARK 99 MOE v2022.02 (Chemical Computing Group ULC) Thu Jul 18 15:08:13 2024
HETATM 1 O1 * 0 -16.219 1.636 -1.486 1.00 0.00 O1-
HETATM 2 C2 * 0 -16.359 1.987 0.839 1.00 0.00 C
HETATM 3 C3 * 0 -15.215 1.727 1.387 1.00 0.00 C
HETATM 4 C4 * 0 -14.286 1.316 0.345 1.00 0.00 C
HETATM 5 C5 * 0 -14.732 1.265 -1.013 1.00 0.00 C
HETATM 6 O6 * 0 -18.237 2.364 -0.412 1.00 0.00 O1-
HETATM 7 C7 * 0 -13.868 0.878 -2.019 1.00 0.00 C
HETATM 8 C8 * 0 -12.967 0.968 0.644 1.00 0.00 C
HETATM 9 C9 * 0 -12.095 0.571 -0.368 1.00 0.00 C
HETATM 10 C10 * 0 -12.557 0.538 -1.694 1.00 0.00 C
HETATM 11 O11 * 0 -11.720 0.155 -2.719 1.00 0.00 O
HETATM 12 C12 * 0 -10.666 0.191 -0.042 1.00 0.00 C
HETATM 13 C13 * 0 -10.048 -0.656 -1.169 1.00 0.00 C
HETATM 14 C14 * 0 -10.295 -0.012 -2.565 1.00 0.00 C
HETATM 15 O15 * 0 -8.647 -1.082 -0.914 1.00 0.00 O
HETATM 16 C16 * 0 -7.582 -0.324 -0.570 1.00 0.00 C
HETATM 17 C17 * 0 -3.884 -0.967 0.266 1.00 0.00 C
HETATM 18 C18 * 0 -2.759 -0.142 0.425 1.00 0.00 C
HETATM 19 C19 * 0 -3.711 -2.361 0.368 1.00 0.00 C
HETATM 20 C20 * 0 -2.456 -2.913 0.611 1.00 0.00 C
HETATM 21 C21 * 0 -1.348 -2.080 0.760 1.00 0.00 C
HETATM 22 C22 * 0 -1.503 -0.685 0.667 1.00 0.00 C
HETATM 23 C23 * 0 -17.053 2.034 -0.313 1.00 0.00 C2+
HETATM 24 O24 * 0 -0.472 0.237 0.803 1.00 0.00 O
HETATM 25 C25 * 0 0.938 -0.002 1.045 1.00 0.00 C
HETATM 26 O26 * 0 -0.128 -2.662 0.996 1.00 0.00 O
HETATM 27 O27 * 0 -7.741 0.878 -0.488 1.00 0.00 O
HETATM 28 C28 * 0 -6.328 -1.001 -0.330 1.00 0.00 C
HETATM 29 C29 * 0 -5.180 -0.349 0.009 1.00 0.00 C
HETATM 30 C30 * 0 -9.657 1.367 -2.812 1.00 0.00 C
HETATM 31 C31 * 0 -9.841 -0.960 -3.684 1.00 0.00 C
HETATM 32 H1 * 0 -15.058 1.822 2.431 1.00 0.00 H
HETATM 33 H2 * 0 -14.215 0.846 -3.017 1.00 0.00 H
HETATM 34 H3 * 0 -12.658 1.015 1.655 1.00 0.00 H
HETATM 35 H4 * 0 -10.648 -0.384 0.884 1.00 0.00 H
HETATM 36 H5 * 0 -10.104 1.111 0.115 1.00 0.00 H
HETATM 37 H6 * 0 -10.621 -1.586 -1.176 1.00 0.00 H
HETATM 38 H7 * 0 -2.853 0.911 0.359 1.00 0.00 H
HETATM 39 H8 * 0 -4.540 -3.012 0.267 1.00 0.00 H
HETATM 40 H9 * 0 -2.348 -3.965 0.684 1.00 0.00 H
HETATM 41 H10 * 0 1.472 0.947 1.100 1.00 0.00 H
HETATM 42 H11 * 0 1.369 -0.595 0.238 1.00 0.00 H
HETATM 43 H12 * 0 1.079 -0.533 1.988 1.00 0.00 H
HETATM 44 H13 * 0 -0.168 -3.639 1.036 1.00 0.00 H
HETATM 45 H14 * 0 -6.360 -2.051 -0.440 1.00 0.00 H
HETATM 46 H15 * 0 -5.204 0.711 0.095 1.00 0.00 H
HETATM 47 H16 * 0 -9.951 2.073 -2.035 1.00 0.00 H
HETATM 48 H17 * 0 -10.009 1.765 -3.764 1.00 0.00 H
HETATM 49 H18 * 0 -8.571 1.298 -2.846 1.00 0.00 H
HETATM 50 H19 * 0 -8.762 -1.107 -3.654 1.00 0.00 H
HETATM 51 H20 * 0 -10.117 -0.544 -4.654 1.00 0.00 H
HETATM 52 H21 * 0 -10.340 -1.924 -3.580 1.00 0.00 H
CONECT 1 5 23
CONECT 2 3 3 23
CONECT 3 2 2 4 32
CONECT 4 3 5 5 8
CONECT 5 1 4 4 7
CONECT 6 23
CONECT 7 5 10 10 33
CONECT 8 4 9 9 34
CONECT 9 8 8 10 12
CONECT 10 7 7 9 11
CONECT 11 10 14
CONECT 12 9 13 35 36
CONECT 13 12 14 15 37
CONECT 14 11 13 30 31
CONECT 15 13 16
CONECT 16 15 27 27 28
CONECT 17 18 19 19 29
CONECT 18 17 22 22 38
CONECT 19 17 17 20 39
CONECT 20 19 21 21 40
CONECT 21 20 20 22 26
CONECT 22 18 18 21 24
CONECT 23 1 2 6
CONECT 24 22 25
CONECT 25 24 41 42 43
CONECT 26 21 44
CONECT 27 16 16
CONECT 28 16 29 29 45
CONECT 29 17 28 28 46
CONECT 30 14 47 48 49
CONECT 31 14 50 51 52
CONECT 32 3
CONECT 33 7
CONECT 34 8
CONECT 35 12
CONECT 36 12
CONECT 37 13
CONECT 38 18
CONECT 39 19
CONECT 40 20
CONECT 41 25
CONECT 42 25
CONECT 43 25
CONECT 44 26
CONECT 45 28
CONECT 46 29
CONECT 47 30
CONECT 48 30
CONECT 49 30
CONECT 50 31
CONECT 51 31
CONECT 52 31
END
Then I used the following instructions adapted from the guide:
obabel PRG_A01.pdb -O PRG_A01_h.pdb -h
antechamber -i PRG_A01_h.pdb -fi pdb -o PRG_A01.mol2 -fo mol2 -c bcc -s 2
parmchk2 -i PRG_A01.mol2 -f mol2 -o PRG_A01.frcmod
tleap
source leaprc.protein.ff19SB
source leaprc.gaff
PRG = loadmol2 PRG_A01.mol2
loadamberparams PRG_A01.frcmod
saveoff PRG PRG_A01.lib
saveamberparm PRG PRG_A01.prmtop PRG_A01.rst7
The PRG_A01.frcmod file when opened gives:
"Remark line goes here
MASS
BOND
ANGLE
DIHE
IMPROPER
NONBON"
So I don't know if the line of instruction "parmchk2 -i PRG_A01.mol2 -f mol2 -o PRG_A01.frcmod" did properly its job.
Furthermore this is what each instruction returned.
[marco99@narval2 PRG_A01 preparation]$ obabel PRG_A01.pdb -O PRG_A01_h.pdb -h
[mii] Please select a module to run obabel:
MODULE PARENT(S)
1 openbabel/3.1.1 StdEnv/2023 gcc/12.3
2 openbabel-omp/3.1.1 StdEnv/2023 gcc/12.3
3 openbabel/3.1.1 StdEnv/2020 intel/2020.1.217
4 openbabel-omp/3.1.1 StdEnv/2020 intel/2020.1.217
5 gnina/1.0.1 StdEnv/2020 gcc/9.3.0 cuda/11.0
6 openbabel/3.1.1 StdEnv/2020 gcc/9.3.0
7 openbabel-omp/3.1.1 StdEnv/2020 gcc/9.3.0
Make a selection (1-7, q aborts) [1]: 1
[mii] loading StdEnv/2023 gcc/12.3 openbabel/3.1.1 ...
Lmod is automatically replacing "boost-mpi/1.82.0" with "boost/1.82.0".
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
The following dependent module(s) are not currently loaded: boost-mpi/1.82.0 (required by: amber/22.5-23.5)
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1 molecule converted
[marco99@narval2 PRG_A01 preparation]$ antechamber -i PRG_A01_h.pdb -fi pdb -o PRG_A01.mol2 -fo mol2 -c bcc -s 2
Welcome to antechamber 22.0: molecular input file processor.
Info: acdoctor mode is on: check and diagnose problems in the input file.
Info: The atom type is set to gaff; the options available to the -at flag are
gaff, gaff2, amber, bcc, and sybyl.
-- Check Format for pdb File --
Status: pass
Info: Determining atomic numbers from atomic symbols which are case sensitive.
-- Check Unusual Elements --
Status: pass
-- Check Open Valences --
Status: pass
-- Check Geometry --
for those bonded
for those not bonded
Status: pass
-- Check Weird Bonds --
Status: pass
-- Check Number of Units --
Status: pass
acdoctor mode has completed checking the input file.
Running: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/bin/bondtype -j full -i ANTECHAMBER_BOND_TYPE.AC0 -o ANTECHAMBER_BOND_TYPE.AC -f ac
Running: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/bin/atomtype -i ANTECHAMBER_AC.AC0 -o ANTECHAMBER_AC.AC -p gaff
Info: Total number of electrons: 222; net charge: 0
Running: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/bin/sqm -O -i sqm.in -o sqm.out
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 0, Name: O1).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 1, Name: C2).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 2, Name: C3).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 5, Name: O6).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 5, Name: O6).
Automatically increasing to 15000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 5, Name: O6).
Automatically increasing to 20000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 17, Name: C18).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 17, Name: C18).
Automatically increasing to 15000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 18, Name: C19).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 19, Name: C20).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 20, Name: C21).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 21, Name: C22).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 22, Name: C23).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 23, Name: O24).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 24, Name: C25).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 25, Name: O26).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 31, Name: H1).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 37, Name: H7).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 37, Name: H7).
Automatically increasing to 15000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 38, Name: H8).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 39, Name: H9).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 40, Name: H10).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 41, Name: H11).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 42, Name: H12).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 43, Name: H13).
Automatically increasing to 10000.
Info: The number of path atoms exceeded MAXPATHATOMNUM for atom (ID: 52, Name: H).
Automatically increasing to 10000.
Running: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/bin/am1bcc -i ANTECHAMBER_AM1BCC_PRE.AC -o ANTECHAMBER_AM1BCC.AC -f ac -p /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/antechamber/BCCPARM.DAT -s 2 -j 1
Running: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/bin/atomtype -f ac -p bcc -o ANTECHAMBER_AM1BCC.AC -i ANTECHAMBER_AM1BCC_PRE.AC
[marco99@narval2 PRG_A01 preparation]$ ^C
[marco99@narval2 PRG_A01 preparation]$ parmchk2 -i PRG_A01.mol2 -f mol2 -o PRG_A01.frcmod
[marco99@narval2 PRG_A01 preparation]$ tleap
-I: Adding /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/prep to search path.
-I: Adding /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/lib to search path.
-I: Adding /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/parm to search path.
-I: Adding /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/cmd to search path.
Welcome to LEaP!
(no leaprc in search path)
> source leaprc.protein.ff19SB
----- Source: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/cmd/leaprc.protein.ff19SB
----- Source of /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/cmd/leaprc.protein.ff19SB done
Log file: ./leap.log
Loading parameters: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/parm/parm19.dat
Reading title:
PARM99 + frcmod.ff99SB + frcmod.parmbsc0 + OL3 for RNA + ff19SB
Loading parameters: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/parm/frcmod.ff19SB
Reading force field modification type file (frcmod)
Reading title:
ff19SB AA-specific backbone CMAPs for protein 07/25/2019
Loading library: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/lib/amino19.lib
Loading library: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/lib/aminoct12.lib
Loading library: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/lib/aminont12.lib
> source leaprc.gaff
----- Source: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/cmd/leaprc.gaff
----- Source of /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/cmd/leaprc.gaff done
Log file: ./leap.log
Loading parameters: /cvmfs/restricted.computecanada.ca/easybuild/software/2023/x86-64-v3/CUDA/gcc12/openmpi4/cuda12.2/amber/22.5-23.5/dat/leap/parm/gaff.dat
Reading title:
AMBER General Force Field for organic molecules (Version 1.81, May 2017)
> PRG = loadmol2 PRG_A01.mol2
Loading Mol2 file: ./PRG_A01.mol2
Reading MOLECULE named *
> loadamberparams PRG_A01.frcmod
Loading parameters: ./PRG_A01.frcmod
Reading force field modification type file (frcmod)
Reading title:
Remark line goes here
> saveoff PRG PRG_A01.lib
Creating PRG_A01.lib
Building topology.
Building atom parameters.
> saveamberparm PRG PRG_A01.prmtop PRG_A01.rst7
Checking Unit.
Building topology.
Building atom parameters.
Building bond parameters.
Building angle parameters.
Building proper torsion parameters.
!FATAL ERROR----------------------------------------
!FATAL: In file [/tmp/ebuser/avx2/Amber/22.5-23.5/gofbc-2023a/AmberTools/src/leap/src/leap/unitio.c], line 1955
!FATAL: Message: 1-4: cannot add bond 2 3
This may be caused by duplicate bond specifications;
for example, explicit bond commands in addition to PDB conect records.
!
!ABORTING.
The last instruction "saveamberparm PRG PRG_A01.prmtop PRG_A01.rst7" gives the fatal error I'm worried about:
!FATAL ERROR----------------------------------------
!FATAL: In file [/tmp/ebuser/avx2/Amber/22.5-23.5/gofbc-2023a/AmberTools/src/leap/src/leap/unitio.c], line 1955
!FATAL: Message: 1-4: cannot add bond 2 3
This may be caused by duplicate bond specifications;
for example, explicit bond commands in addition to PDB conect records.
!
I tried to remove the conects and remarks from the PDB file of the structure (which MOE added), resulting in the same error.
Is there a ways to face this obstacle?
Thank you very much
Relevant answer
Answer
I will try it, thank you very much!!!
  • asked a question related to Atoms
Question
1 answer
Suppose i have two compounds H2O and H2O2 or CO and CO2, i want to make crystal how can i make in material studio?
Relevant answer
Answer
Here's a general approach to making crystals of these compounds:
Start by building the individual molecules using the Builder module in Materials Studio.
Go to Sketch > Insert > Molecule, and then either choose a pre-built molecule or build it manually using the atomic fragments available in the builder.
Adjust the geometry to make sure bond lengths and angles are realistic (use literature values or typical bond lengths and angles).
Once the molecule is built, you'll need to create a crystal structure.
Go to Modules > Build > 3D Atomistic.
Choose Space Group from the available options. For example, you can choose a common space group like P1 if you're unsure about the symmetry requirements, or select a space group that matches your desired crystal symmetry (e.g., P21/c for monoclinic symmetry, etc.).
After defining the space group, you can place the molecule inside the unit cell.
Go to Edit > Symmetry > Add Molecule to Symmetry. This will add the molecule according to the symmetry operations of the chosen space group.
Adjust the positioning, orientation, and packing of the molecule within the unit cell using the Transform tool if needed.
I hope this can help
Good luck
  • asked a question related to Atoms
Question
2 answers
I am using Materials Studio and the CASTEP software package. I would like to apply Hubbard U corrections to a model that includes transition metals. Should I directly adjust the Hubbard U values for the atoms in the "Electronic Configuration" section, and do I need to enable the LDA+U option during the calculations?
If I don't use LDA+U, will the system be unable to recognize the Hubbard U correction values?
Relevant answer
Answer
You must enable the LDA+U option during the calculations. This is because the Hubbard 𝑈 correction is specifically applied within the LDA+U (or GGA+U) framework. Without enabling LDA+U, the system will not recognize or apply the Hubbard 𝑈 values you have set. The LDA+U method modifies the exchange-correlation functional to account for the on-site Coulomb interactions for localized 𝑑 or 𝑓 electrons, which is crucial for transition metals.
After enabling LDA+U, you should indeed adjust the Hubbard 𝑈 values in the Electronic Configuration section of CASTEP. This is where you specify the 𝑈 parameters for the specific orbitals of the transition metal atoms in your system. These values are typically determined from literature or by fitting to experimental data.
  • asked a question related to Atoms
Question
2 answers
Hello all,
I am trying to determine the dependence of the energy gap of silicon as a function of temperature. In the literature, it is stated that the decrease in the energy gap of silicon with increasing temperature can be explained by thermal expansion and electron-phonon interaction.
First, I used the thermo_pw library (which uses the QHA approximation) to determine the lattice parameter of silicon as a function of temperature. Then, I ran the following calculations: SCF, NSCF, DOS, band, and finally plotband. I performed these calculations using the lattice parameters of Si corresponding to temperatures in a range from 4K to 800K. For this simulation, I am using PBE pseudopotentials, an ecutwfc of 25 Ry, and a unit cell with 2 atoms.
The problem is that the gap increases with temperature instead of decreasing. I obtained a gap of 0.6187 eV at 4K and 0.6315 eV at 800K.
I also tried calculating the band structure considering electron-phonon coupling using the EPW library, but the gap still increases with temperature.
Has anyone already tried to calculate the silicon gap as a function of temperature? What am I doing wrong?
Relevant answer
Answer
I found that to account for phonon effects, I needed to consider lattice vibrations. I performed MD calculations at different temperatures using a supercell of 512 atoms with PBE pseudopotentials, an energy cutoff of 25 Ry, and calculations at the gamma point only. Once the temperature was stabilized, I extracted 160 structures at each temperature.
For each structure, I ran an SCF calculation, and now I observe that the energy gap decreases with temperature. I am still waiting for all the SCF calculations to be completed, but currently, the average band gap is 0.54624 eV at 250K and 0.65271 eV at 4K.
Once all the calculations are done, I will correct the band gap using the GW method to obtain a better approximation.
  • asked a question related to Atoms
Question
2 answers
Hi all, my experimental XPS results shown that my C3N5 sample consists of N-H bond, hence in this case I should incorporate the N-H bond into my DFT modelling. However, I do notice several papers report N-H bond from their XPS results too but did not incorporate it into their modelling while some did include the N-H bond.
This confuses me, logically I feel like it should include the N-H bond so that the modelling is closer to the experimental case. However, is there any specific reason they do not include H-bond for modelling?
Relevant answer
Answer
Dear Zi, where do you exactly want to add N-H bonds?
For modelling n-dimensional carbon or carbon/nitrogen structures we usually add dangling H bonds at the edges. For example, C-H at the edge of a carbon nanotube, C-H at the edge of a graphene sheet, etc... This make sure all atoms will contain their octet completed (i.e., four bonds or 8 electrons in the valence shell of carbon).
In your case, I assume dangling H bonds should be added to amine or triazole terminals, check your system, and complete the octet in N as needed.
Please take into account that protonating the triazine rings or imine is a different situation, so you should consider it carefully. You are probably interested in the neutral system; but some experimental observations might be explained with the protonated system.
Best, Pablo
  • asked a question related to Atoms
Question
4 answers
If we map as a continuous motion an ionising electron (beginning its journey at n=1) in an H atom, a hyperbolic spiral emerges (see animation). When we solve this spiral formula, we find that at regular intervals the spiral angles will cancel to give integer radius values (360°=4r, 360+120°=9r, 360+180°=16r, 360+216°=25r ... 720°=∞ ... formulas below).
As the orbital levels corresponding to the principal quantum number n^2 (4, 9, 16, 25 ...) naturally occur via this spiral geometry, then at those points where the angles cancel to give integer radii (360°, 360+120°, 360+180°, 360+216° ...) we can use the spiral perimeter (r = Bohr radius) to derive the transition frequency for that integer (n^2) level ......, thus equating these energy levels directly to pi, the question then becomes, could quantization in the atom have geometrical origins?
In the animation the radius is mapped (during ionization), as the electron reaches each integer level, it completes 1 orbit (for illustration) then continues outward (actual velocity will become slower as radius increases).
Relevant answer
Answer
Does your one-dimension static equation recognize three-dimension, color, taste, smells, temperature, pressure.....?
Reading this might help.
  • asked a question related to Atoms
Question
1 answer
I have face this problem anyone help me how to solve this issue ?which is below
Fatal error:
There are inconsistent shifts over periodic boundaries in a molecule type
consisting of 78 atoms. The longest distance involved in such interactions is
4.894 nm which is above half the box length. Either you have excessively large
distances between atoms in bonded interactions or your system is exploding.
For more information and tips for troubleshooting, please check the GROMACS
Relevant answer
Answer
It seems like your box size might be too small compared to your short-range interaction cutoff, leading to issues with periodic boundary conditions.
Here are some key points to consider:
1. For short-range non-bonded interactions, only the nearest image of each particle is considered among all those generated by PBC.
2. A spherical cutoff is applied to limit the number of interactions calculated.
3. The cutoff radius shouldn’t be more than half the shortest box vector, or multiple images of a particle might fall within the cutoff distance.
4. Ideally, a solvent molecule shouldn’t interact with both sides of your macromolecule. Therefore, each box vector should be longer than the macromolecule by at least twice the cutoff radius.
To fix this error, you can adjust your box size using the GROMACS command to ensure there’s at least 1 nm between your protein and the box edge. Also, set your short-range cutoff to 9 or 10 Å in the MDP file.
  • asked a question related to Atoms
Question
3 answers
If from a geometric perspective the non-halogens, non-noble gases have more empty spots in their valence shell, and the filling/exiting of any of the empty spots in the shell constitutes a chemical rxn, shouldn't non-halogens and non-noble-gases be more reactive? (AFAIK) Just from a probability perspective, the probability of hitting the empty spot in the electron shell which is crowded by 7 electrons already is just less likely when you can hit any of the >1 empty places in the shell of the electron accepting atom. I'm aware electrons are non-stagnant.
Relevant answer
Answer
First, what do you mean by reactivity? All kinetic data indicates the rate of a reaction depends on the collision probability of reactants with sufficient kinetic energy, and the energy difference between ground and activated state. The energy difference depends on a number of things but as a generalization it depends on the energy of the valence electron on whatever state it is in. The bond energies DO depend on the number of empty orbitals, but not in the way you think. If an electron from atom B pairs with an electron from atom A, it takes the energy of atom A in then region of atom A, and vice versa. If the space available to the electron in atom A is reduced, the energy is increased. The reason the halogens are so reactive is because an electron entering their valence shell gains more kinetic energy because the space available to it is reduced. (That the nuclear charge appears greater arises from the same reason, but is more complicated to explain.) That fluorine is the most reactive is because it is the smallest, and an electron entering its valence shell has the least room to move and is closer to the nucleus.
  • asked a question related to Atoms
Question
3 answers
If you think of electrons with spin as bar magnets, you know bar magnets of opposite polarity as long as they're not occupying the same spatial location don't cancel out each other's magnetic field.
So what's a more apt analogy/or math reason, or explanation for all electron paired atoms have no magnetic field?
Relevant answer
Answer
They do. Instead of asking questions like these it would be better to learn electromagnetism, there are so many resources now available, for instance https://www.feynmanlectures.caltech.edu/.
  • asked a question related to Atoms
Question
1 answer
I don't even know what the central atom of a isoprene is. Does the rule above work when you don't have an odd number of carbons on the longest not necessarily straight backbone?
Relevant answer
Answer
Isoprene received its trivial name before IUPAC was a thing, so don't try to apply current systematics there.
Coined (1860) by British chemist C. G. Williams, from iso- (“equal; different, isomeric”) + prop- (“three carbon prefix”) + -ene (“alkene suffix”).
  • asked a question related to Atoms
Question
1 answer
Hello,, The metal complex ligand appears incomplete in the screen of the discovery studio visualizer
Relevant answer
Answer
Hello Nisreen Meiqal, To draw a coordinate bond between a metal and a donor atom in Discovery Studio Visualizer, first ensure both the metal and the ligand are loaded and properly visualized in the workspace. Select the "Bond" tool from the toolbar and click on the metal atom followed by the donor atom (e.g., nitrogen or oxygen in the ligand). This action will create a bond between the two atoms. If the ligand appears incomplete, check for missing atoms or improper connectivity. Use the "Build" tool to add any missing atoms or correct the structure. Additionally, ensure that the valence and geometry are appropriate for the coordination chemistry context, adjusting bond lengths and angles if necessary. This process should result in a complete and accurate representation of the metal-ligand coordination complex.
  • asked a question related to Atoms
Question
1 answer
i m interested in pca analysis of c-alpha atoms in gromacs for that i used the following
gmx_mpi covar -s mdca.tpr -f mdca.xtc -o eigenvalca.xvg -v eigenvecca.trr -av average.pdb -n index.ndx
but i am getting the error
Range checking error (possible bug):
The provided structure file only contains 10 coordinates, but coordinate index
147 was requested for fitting. Make sure to update structure files and index
files if you store only a part of your system.
how should i prepare the md.tpr file for only c-alpha atom
Relevant answer
Answer
To perform PCA analysis on the C-alpha atoms of a protein using GROMACS, you need to prepare the necessary files and use the appropriate commands. Here are the steps you can follow:
  1. Prepare the System: Make sure you have the necessary files, including the protein structure file (e.g., PDB format) and the trajectory file (e.g., XTC format) containing the coordinates of the C-alpha atoms.
  2. Create an Index File: Create an index file (e.g., index.ndx) that specifies the C-alpha atoms. This file will be used to select the C-alpha atoms for the analysis.
  3. Replace md.mdp with the appropriate name of your MD parameter file, system.gro with the name of your system coordinate file, and topol.top with the name of your topology file.
  4. Generate the TPR File: Use the grompp command to generate the TPR file, which contains the necessary information about the system and the simulation parameters. The command may look like this:javascriptgmx_mpi grompp -f md.mdp -c system.gro -p topol.top -n index.ndx -o md.tpr Replace md.xtc with the name of your trajectory file.The -o option specifies the output file for eigenvalues, -v for eigenvectors, -av for the average structure, and -n for the index file.
  5. Perform Covariance Analysis: Use the gmx_mpi covar command to perform the covariance analysis. Specify the TPR file, trajectory file, and output files. The command may look like this:javascriptgmx_mpi covar -s md.tpr -f md.xtc -o eigenval.xvg -v eigenvec.trr -av average.pdb -n index.ndx
  6. Interpreting the Results: Once the analysis is complete, you can analyze the eigenvalues and eigenvectors obtained from the covariance analysis. These can provide insights into the principal components and the motions of the C-alpha atoms.
It is important to note that the error you encountered may be due to an issue with the structure file or index file. Make sure that your structure file contains all the necessary coordinates and that the index file correctly selects the C-alpha atoms.For further guidance and troubleshooting, you may find it helpful to consult the GROMACS documentation, user forums, or research papers that discuss PCA analysis in GROMACS.
  • asked a question related to Atoms
Question
3 answers
Can someone verify me whether its right or wrong the number of atoms displayed in Burai using same cif created by vesta?
Relevant answer
Answer
yes, phenomenologically they are same, but some times when doing magnetic calculations when we want to do calculation for different spin structure calculations more number of atomic sites becomes useful.
  • asked a question related to Atoms
Question
6 answers
We are currently trying to calculate the lattice thermal conductivity of several metals (Ni, Cu, Pd, Ag, Pt and Au) using the non-equilibrium Müller-Plathe method in LAMMPS. We are considering big supercells (20x20x20 unit cells, 70k+ atoms) for each elemental metal separately. The interactions between atoms are mediated by the well-known MEAM potential. The heat flux is tallied using the fix thermal/conductivity command, and temperature profiles are recorded using the compute chunk/atom and fix ave/chunk commands. Please find attached the typical input run for reference. We have successfully run this for other systems (molecular liquids governed by OPLS-AA), but for MEAM metals we found that the temperature profiles are basically erratic noise. While the lattice thermal conductivity of metals should low, we do not expect it to be completely negligible.
Is anyone aware of existing problems with the application of the Müller-Plathe method together with the MEAM potential? Is there particular requirements for such a case? We have played with the Nevery and Nswap parameters in the fix thermal/conductivity command with no success.
Thank you in advance for your attention.
*****
include "system.in.init"
read_data "system.data"
include "system.in.settings"
include "system.in.charges"
neigh_modify every 1 delay 0 check yes
variable t equal 0.001
variable T equal 298.0
variable P equal 1.013
variable s equal 5
variable c equal 10000
variable d equal $s*$c
variable kB equal 8.617333262E−5
minimize 1.0e-6 1.0e-8 1000 100000
reset_timestep 0
timestep $t
thermo_style custom step etotal temp press lx ly lz density
thermo 1000
fix 1 all nvt temp $T $T 10.0
run 500000
unfix 1
fix 2 all npt temp $T $T 10.0 iso $P $P 100.0
run 2000000
unfix 2
reset_timestep 0
thermo_style custom step etotal epair ke temp press
thermo 1000
fix 3 all nvt temp $T $T 10.0
run 10000000
unfix 3
reset_timestep 0
fix 4 all nve
fix 5 all thermal/conductivity 100 z 50
compute ke all ke/atom
variable temp atom c_ke/(1.5*${kB})
compute layers all chunk/atom bin/1d z lower 0.02 units reduced
fix MP all ave/chunk $s $c $d layers v_temp file temp.profile ave one
thermo_style custom step etotal epair ke temp press f_5
thermo 1000
run 10000000
unfix MP
unfix 5
unfix 4
Relevant answer
Answer
Dear Iván Carrillo-Berdugo,
Thank you for the answer.
Actually, I am a new user of LAMMPS, and I am trying to test thermal conductivity calculations on metals that already have defects in the lattice. For this, I am using the SNAP potential (though I can try EAM as well), but the problem remains the same. I am using the input script provided in the LAMMPS example for the Müller-Plathe method, making changes according to my metal. The variable tdiff is defined in this script.
I have the error :ERROR: Variable tdiff: Fix in variable not computed at a compatible time (src/variable.cpp:1854)
Last command: run 20000
{# sample LAMMPS input script for thermal conductivity of liquid LJ
# Muller-Plathe method via fix thermal_conductivity
# settings
variable x equal 10
variable y equal 10
variable z equal 20
variable rho equal 0.6
variable t equal 1.35
variable rc equal 2.5
#variable rho equal 0.85
#variable t equal 0.7
#variable rc equal 3.0
# setup problem
units lj
atom_style atomic
lattice fcc ${rho}
region box block 0 $x 0 $y 0 $z
create_box 1 box
create_atoms 1 box
mass 1 1.0
velocity all create $t 87287
pair_style lj/cut ${rc}
pair_coeff 1 1 1.0 1.0
neighbor 0.3 bin
neigh_modify delay 0 every 1
# 1st equilibration run
fix 1 all nvt temp $t $t 0.5
thermo 100
run 1000
velocity all scale $t
unfix 1
# 2nd equilibration run
compute ke all ke/atom
variable temp atom c_ke/1.5
fix 1 all nve
compute layers all chunk/atom bin/1d z lower 0.05 units reduced
fix 2 all ave/chunk 10 100 1000 layers v_temp file profile.mp
fix 3 all thermal/conductivity 10 z 20
variable tdiff equal f_2[11][3]-f_2[1][3]
thermo_style custom step temp epair etotal f_3 v_tdiff
thermo_modify colname f_3 E_delta colname v_tdiff dTemp_step
thermo 1000
run 20000
# thermal conductivity calculation
# reset fix thermal/conductivity to zero energy accumulation
fix 3 all thermal/conductivity 10 z 20
variable start_time equal time
variable kappa equal (f_3/(time-${start_time})/(lx*ly)/2.0)*(lz/2.0)/f_ave
fix ave all ave/time 1 1 1000 v_tdiff ave running
thermo_style custom step temp epair etotal f_3 v_tdiff f_ave
thermo_modify colname f_3 E_delta colname v_tdiff dTemp_step colname f_ave dTemp
run 20000
print "Running average thermal conductivity: $(v_kappa:%.2f)"}
  • asked a question related to Atoms
Question
1 answer
Can we calculate the friction coefficient of an interface by only knowing the atom types and geometry forming it, without performing any experiment or simulations? We think yes, and discuss a possible route to get there in our recently published review - download it with this free access link
Relevant answer
Answer
Jeff Sokoloff has articles in this topic.
An incommensurate intermediste layer will lower friction.
  • asked a question related to Atoms
Question
6 answers
During the preparation of a ligand molecule in autodock or openbabel Cl atom is not showing in the .pdbqt file whereas it was present in the pdb and sdf file. Due to this Cl atom is not showing in the docked complex as well. How do we resolve this issue? I am attaching two images for your reference.
Thanks in advance
Relevant answer
Answer
Thank you very much Annemarie Honegger for your help.
  • asked a question related to Atoms
Question
3 answers
Hi, my research involves in ZnO synthesis. I have performed rietveld refinement of my samples and obtain a good fit using Fullprof suite software. However to obtain the crystallite size, the IRF file is required which often generated from the standards as LaB6, Si etc.,,, . May i know whether others standards (in my case, pure ZnO) be used to generate the IRF file since I have analyzed the pure ZnO sample with the same XRD instrument. I also have performed the rietveld refinement on the pure ZnO and obtain pretty much similar crystal parameter (lattice constants,...atom occupancies..etc.,,) with the standard ZnO sample from the cif files. Therefore, can i used the pure ZnO XRD pattern to generate the IRF file ?
Relevant answer
Answer
Although Joshua's answer is very nice, and demonstrates skill in using Chat GPT or Open AI, that answer was not written by a human.
Notice that the requirements for the standard mean that are somewhat vague but properly applied mean that you must have compared your local standard, such as ZnO, to a certified NIST SRM, or equivalent.
Notice the Validation point under considerations means that you must compare your local, secondar, standard to a well characterized primary standard! So, you really need NIST SRM 660 or 640.
If you have compared your ZnO to NIST SRM 660x or 640x and find identical peak widths (interpolated to the same angles), then sure, use your ZnO, but without that comparison, don't! (As I said more briefly, above.)
The point from Joshua about Consistency is very important: acquire your sample data and reference data using same settings and acquisition parameters (except possibly count time).
  • asked a question related to Atoms
Question
3 answers
My ligand is a metal complex conatining Ag (Silver). So when i tried to run Molecular docking using Autodock vina as well as PyRx, it shows error as
"Parse error on line 15 in file "Methioninesilver.pdbqt": ATOM syntax incorrect: "Ag" is not a valid AutoDock type. Note that AutoDock atom types are case-sensitive."
Any necessary recommendation to overcome this error.
Relevant answer
Answer
Hi Suraj, you will have to the edit the 'atom_constants.h' file in the vina install directory (given that you have installed vina from source). You will have to add the parameters of Ag in 'atom_constants.h' .
Adding new atom type in atom_constant.h is tricky.
To make things easy, you can rename Ag in your ligand to any metal which is recognized by vina (say, Zn, Mg, Fe etc.). Then you can change the parameter values of these metals in atom_constant.h file with that of Ag. The docking should then work fine. This is quite like dummy-atom approach.
  • asked a question related to Atoms
Question
3 answers
The error message is "Angle parameter for atoms42-45-15 (cf-nu-ns) not found in the force field. Initialization is not possible, check atoms for incorrect bonds, then update the force field's angle parameter section".
What should I do to run the simulation after error correction
Relevant answer
Answer
1. How did you perform the optimization and docking? Did you use YASARA for these steps?
2. What simulation are you now trying to do on the ligand-receptor complex?
  • asked a question related to Atoms
Question
4 answers
I am trying for the structure optimization via Gaussian16 DFT calculation, for a system consisting of C,H, N, O and Ce atoms. Where I am using B3LYP/ 6,311G(d,p) C, H, N and O and B3LYP/SDD for Ce. I am having error termination Error termination via Lnk1e in /share/apps/gaussian/g16/l502.exe
Any suggestion for normal termination?
Relevant answer
Answer
Greetings!
Copying an answer I wrote a couple days ago to another question:
"Error in L502 means that the SCF failed to converge for a geometry. It happens because the default settings for gaussian is to do at maximum 128 SCF cycles, if your convergence requires more than that the job will fail at the 129th." https://www.researchgate.net/post/How_to_rectify_the_error_l502_in_gaussian
Also, considering your system has Ce, you will, most likely, need to employ a vshift, damping and maxcycles > 500 for your SCF to converge. Also, I'd employ more modern basis sets than 6-311G(d,p), since Pople's basis sets are not fit for lanthanides. And lastly, please employ relativistic corrections, they are necessary for, lets say, Z > 38.
Hope I was of any help.
  • asked a question related to Atoms
Question
8 answers
Hello dear researchers, I hope you are doing well.
I want to ask you a question. I have a unit cell with 24 atoms (4 A, 4 B and 16 X) and I want to substitute X atom by another atom (for example changing one X by other element).
My question is, can I substitute it within the unit cell without making supercell?? or should I make a supercell??
Relevant answer
Answer
A novel variable into game theory could indeed be a valuable contribution to the field, potentially offering new insights or enhancing existing models. Here’s how you might conceptualize and present such a "present" to science:
Conceptualizing a Novel Variable in Game Theory
  1. Identify a Gap or Enhancement Opportunity:Review existing game theory models and literature to identify areas where a new variable could provide deeper insights or improve predictive accuracy. Consider aspects such as behavioral psychology, environmental factors, or dynamic variables that current models may not fully capture.
  2. Define the Novel Variable:Clearly define the new variable and its potential impact on decision-making within game scenarios. Examples could include introducing time-dependent variables, emotional states, resource constraints, or adaptive learning capabilities of players.
  3. Integration with Existing Models:Demonstrate how the novel variable can be integrated into existing game theory frameworks (e.g., Nash equilibrium, evolutionary game theory) to refine predictions or outcomes. Illustrate through mathematical formulations or simulations how the variable interacts with traditional game theory concepts.
Presenting Your Contribution
  1. Research Paper or Article:Write a research paper detailing the rationale, methodology, and findings related to introducing the novel variable. Structure the paper to include background on game theory, a clear description of the variable, its theoretical implications, and practical applications.
  2. Simulation or Case Study:Conduct simulations or case studies to illustrate the impact of the novel variable in various game scenarios. Provide quantitative results and qualitative insights to support your theoretical propositions.
  3. Discussion and Implications:Discuss how the novel variable addresses existing limitations in game theory and enhances the understanding of decision-making processes. Explore potential real-world applications and policy implications based on your findings.
  4. Peer Review and Publication:Submit your paper to peer-reviewed journals specializing in game theory, economics, or behavioral sciences. Respond to reviewer feedback to strengthen the rigor and relevance of your contribution.
  5. Presentation and Dissemination:Present your findings at academic conferences, workshops, or seminars to solicit feedback and engage with other researchers in the field. Consider creating visual aids or demonstrations to effectively communicate the novelty and impact of your variable.
Example Scenario: Introducing Emotional State as a Variable
  • Variable Definition: Introduce emotional state (e.g., happiness, stress) as a dynamic variable influencing decision-making in game interactions.
  • Model Integration: Modify traditional game theory models to incorporate emotional states as parameters affecting strategy choices and outcomes.
  • Applications: Explore how emotional variability among players affects cooperation, competition, and equilibrium states in social dilemmas or economic negotiations.
By presenting a novel variable in game theory, you contribute not only to theoretical advancements but also potentially to practical applications in fields ranging from economics to social sciences. Your "present" to science could pave the way for deeper insights into human behavior and decision-making dynamics.
3.5
Doping/Substitution of an element in QE
ChatGPT
In the context of quantum mechanics and materials science, "QE" typically refers to Quantum Espresso, which is an integrated suite of open-source computer codes for electronic-structure calculations and materials modeling. Doping or substitution of an element within Quantum Espresso involves simulating the introduction of foreign atoms (dopants) into a material to study its electronic and structural properties. Here’s how this process is generally approached:
Doping/Substitution in Quantum Espresso (QE)
  1. Setup and Structure Initialization:Input File Preparation: Define the crystal structure of the material of interest using Quantum Espresso's input format (typically based on atomic positions and unit cell parameters). Specify Dopant Positions: Identify the specific sites where dopant atoms will replace or occupy lattice positions within the crystal structure.
  2. Electronic Structure Calculation:Density Functional Theory (DFT): Utilize DFT calculations to compute the electronic structure and ground-state properties of the doped material. Exchange-Correlation Functional: Choose an appropriate functional (e.g., LDA, GGA) to describe the electron exchange and correlation interactions accurately. Pseudopotentials: Select suitable pseudopotentials for the elements involved to approximate the atomic cores and reduce computational complexity.
  3. Simulation Parameters and Convergence:K-Points and Energy Cutoff: Define the Brillouin zone sampling (k-points) and energy cutoff for plane-wave expansions to achieve converged results. Relaxation and Optimization: Optionally, perform structural relaxation to minimize atomic forces and optimize the lattice parameters around the doped atoms.
  4. Analysis and Visualization:Electronic Properties: Analyze the band structure, density of states (DOS), and charge distribution to understand how doping affects the material's electronic properties. Structural Properties: Evaluate changes in lattice parameters, bond lengths, and atomic positions due to doping.
  5. Interpretation and Applications:Dopant Effects: Assess how the introduced dopants alter the material's behavior, such as its conductivity, magnetic properties, or catalytic activity. Comparison with Experimental Data: Validate computational findings against experimental observations to refine theoretical models and predictions.
Example Scenario: Doping Silicon with Phosphorus
  • Objective: Study the effects of phosphorus doping on silicon's electronic properties using Quantum Espresso.
  • Steps:Prepare the crystal structure of silicon (Si) and specify the substitutional positions for phosphorus (P) atoms. Perform DFT calculations with appropriate pseudopotentials and exchange-correlation functionals. Calculate the band structure and DOS to analyze how P doping modifies Si's electronic bandgap and carrier concentration. Compare results with experimental data on doped silicon to validate computational predictions and insights.
Impression
Doping or substitution of elements within Quantum Espresso allows researchers to explore how the introduction of foreign atoms influences the electronic and structural characteristics of materials. This approach is fundamental in materials science for understanding doping mechanisms, predicting material behaviors, and designing novel materials with tailored properties for various applications.
3.5
  • asked a question related to Atoms
Question
2 answers
Hello everyone, I am currently working on miRNA- mRNA interaction study. Further, I would like to do MD simulations for the miRNA-mRNA models.
For the Simulation, I have modelled this complex using the Alphafold server. But when I try to use AlphaFold models for the Gromacs MD simulations, it gives some error when I apply the force field (Amber - 2010).
The error is "Atom OP3 in residue U 1 was not found in rtp entry RU5 with 28 atoms while sorting atoms."
If I change the atom name, it shows another atom is missing (attached the screen shot with this Q&A)
Is there any updated force field or modelling algorithm?
Kindly help me to solve this issue.
Relevant answer
Answer
I removed all the OP3, P, OP1, and OP2 atoms from the file. Now, The Amber force field is working for the model. Thank you for the suggestion.
  • asked a question related to Atoms
Question
3 answers
I am trying to run a md stimulation in gromacs for HDAC2 inhibitor and ligand. The protein is metalo protein, contain a Zn atom. Now I am facing problem while converting the pbd to gmx, i.e., in the time of applying forcefield. I have attached the error details. It will be very helpful if anyone can solve this error.
Relevant answer
Answer
Thank you everyone for helping me to solve the issue.
  • asked a question related to Atoms
Question
1 answer
I encounter an issue in Vista; the system fails when determining the atoms ?
Relevant answer
Answer
Admittedly you should be add more pieces of information for this message to be of any use. At the same time, while for sure here there are people using (I assume Vesta, not Vista) VESTA, I would recommend you send your message to the developers rather than the user community.
Regards,
Roberto
  • asked a question related to Atoms
Question
3 answers
Suppose a lab experiment gave evidence that the DNA or RNA code for bacteria are stored in radioactive chemical atoms, because the atomic decays are followed by the appearance of protozoa in a test tube of sterile chemical building blocks. Would this be an evidence for a cosmic mind that formed the atoms containing these genetic codes?
Relevant answer
Answer
"Can the existence of God be supported by the results of a lab experiment?": No.
The probability that somethinig born in a dreamu or in pure fantasy can be can be supported by a lab experiment approachs zero. Do not waste time with metaphysics.
  • asked a question related to Atoms
Question
6 answers
I am working on a molecular dynamics simulation in protein-ligand system, using NAMD software, and I got the following error.
"FATAL ERROR: UNABLE TO FIND ANGLE PARAMETERS FOR HGA1 CG3C51 SG311 (ATOMS 1753 1752 1770)"
The atoms mentioned above belong to the ligand structure. The .str and topology files for the ligand were generated using Charmm-gui. Can someone help me to solve this failure? Thank you in advance.
Relevant answer
Answer
Any solution to this please? I'm facing similar problems