Shell - Science topic

Merkez atoma bakılır.

Doping quantum dots (QDs) with plasmonic core/shell structures is primarily intended to improve their optical and electrical properties via a coupling effect between the plasmonic core and quantum dot. The plasmonic core (usually a metal such as gold or silver) can amplify the local electromagnetic field near the QD, resulting in an increased fluorescence signal. Which is especially beneficial in applications that require great sensitivity, such as bioimaging and sensing. The plasmonic core's resonance frequency can be adjusted to match the QD's emission or absorption spectra, allowing for controlled energy transfer (Förster resonance energy transfer, or FRET) between the core and QD. This tunability allows for customizable emission qualities, which is useful in optoelectronics and photonic devices.

Foton bombardımanı sırasında onların enerjilerini korumak için yapılır. Au ve Cd iyi bir iletkendir. Fotonun enerjisi yüksektir. Bunun için iyi bir iletkenle yalıtım yapılır.

Thanks, Douaa Arrouk . I really appreciate! If I run into trouble when it comes trying these analyses in R, could I send you a message for help? I plan to start these projects sometime next summer.

Thanks again!

Regards,

Miguel

I found this error Error at k-point 33 ndimwin 30 num_wann 32.

Check if this works...

Step 1: Define the Point Load

Step 2: Implement Frequency Dependency

Step 3: Assign Location for Point Load

Step 4: Implementing Displacement Dependency

Park Ayoung Can you share your .stl file?

Aashish Bhatt , thank you for your response. I will certainly try this software and method.

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.

Hello Debopam Acharjee.

A core shell or "non core shell" CdSe have the same unit cell, and consequently the same XRD peaks position. Could you explain what exactly is this CdSe ZnS structure?

Mr Ladhari, thank you for your valuable contribution

Would your acrylic intermediate binder be effective in binding the microcapsule to the fabric under normal room temperature conditions?

Or are special conditions also required?

Ahmed G. Rahma Can you share your .stl file?

hahaha....., I see. You can refer this paper “Enhanced Electrocatalytic CO2 Reduction to C2+ Products by Adjusting the Local Reaction Environment with Polymer Binders”，in which it mentioned three polymers with different hydrophilicities (i.e., polyacrylic acid (PAA), Nafion, and fluorinated ethylene propylene (FEP)) are selected as binders for catalysts.

Fluid Flow in Helically Coiled Pipes

📷

MDPI

https://www.mdpi.com › ...

by LDG Sigalotti · 2023 · Cited by 3 — The most notable feature of flow in helical pipes is the secondary flow (i.e., the cross-sectional circulatory motion) caused by centrifugal forces due to the ...

COMPUTATIONAL FLUID ANALYSIS OF TRIPLE ...

📷

SSRN

https://papers.ssrn.com › sol3 › Delivery.cfm › S...

PDF

... of 1000 mm length of all three tubes. The theoretical and computational fluid dynamics analysis of triple copper tube heat exchanger results showed better ...

Dear Sir,

Thanks for the mentioned papers, which are really within the study on the egg shell thickness of parasitic birds. Unfortunately, there's no information on cuckoo finch egg shell there.

Dear friend Antonio Ilderlânio de Sousa Leite

Surface area and amorphization degree in high-energy ball-milled activated carbon can indeed be related, and the main source can influence this relationship. When milling activated carbons from different sources, such as shell nut and bituminous coal, variations in surface area and amorphization can occur due to differences in their intrinsic properties.

Regarding your Antonio Ilderlânio de Sousa Leite observation, it's intriguing that while the shell nut activated carbon didn't increase in surface area, it exhibited some degree of amorphization post-milling. Conversely, the bituminous coal activated carbon maintained its graphitic structure but showed a doubling in surface area.

Firstly, changes in surface structure can indeed impact the surface area measured by the BET method. Amorphization, characterized by the disruption of the ordered carbon structure, can lead to the creation of new surface sites and defects, potentially increasing the measured surface area despite a reduction in crystallinity.

Secondly, it's plausible that amorphization could remove micropores, especially if the milling process is severe. Micropores are inherently part of the porous structure of activated carbon and contribute significantly to its surface area. Therefore, their removal could result in a decrease in measured surface area.

The influence of the main carbon source on these results is multifaceted. Differences in precursor materials can lead to variations in the initial structure and composition of the activated carbon. This variance can affect how the carbon responds to the milling process, impacting factors such as the extent of amorphization and the preservation of micropores. For instance, bituminous coal may have a more robust crystalline structure that resists amorphization, while shell nut-derived activated carbon may be more prone to structural changes.

In conclusion, the relationship between surface area and amorphization in high-energy ball-milled activated carbon is complex and influenced by factors such as the carbon source and the milling conditions. Understanding these relationships is crucial for tailoring activated carbon properties for specific applications.

Shiyao Lin as per my understanding, shell elements primarily capture in-plane stresses (membrane behavior) and bending moments. Initial stress definitions in ABAQUS are typically for normal and shear stresses. Directly applying these to shells might not translate well to the bending behavior that shells are often designed for. I am not sure, let's wait for the expert reviews further.

Those mollusks that have shells, have only a single shell. Bivalves do not have "two shells", they have two valves or...BIvalvia. Thus gastropods were considered UNIvalvia (univalves). The clams, mussels, scallops are all bivalves or Bivalvia. The shelled shails are univalves but you are correct that snails are not taxonomically "univalvia" but are Gastropoda.

Carlos Francisco Lucena Gonzalez Thank you sir, for your clear explanation.

The stiffness coefficient for a shell element is determined based on the shell's geometry, such as its thickness, and the material properties, such as the Young's modulus and Poisson's ratio. Unlike beam elements, shell elements have additional degrees of freedom and exhibit different deformation characteristics, which impact the stiffness coefficient calculation.

Physiologically egg White and yolk are liquids. Between yolk and White these is a membrane and between White and shell ( the Ca fraction) there is also a (protein containing) membrane . Check any textbook or Wikipedia for more details.

Little late, but add a very thin ply at the top and bottom. Just pull that thickness of the next plies.

Thank you Haobam. Much appreciated!

Follow these steps:

1. Import the Geometry: Load the pelvis and sacrum bone geometry file into a 3D modeling software or a CAD program capable of handling complex geometries. Ensure that the file format is compatible with the software you are using.

2. Duplicate the Bone Geometry: Create a duplicate copy of the original bone geometry to work on. This will allow you to preserve the original bone geometry while creating the cortical bone shell.

3. Scale the Duplicate Geometry: Scale up the duplicate bone geometry uniformly by 4mm in all directions. This will create a larger version of the bone geometry, which will serve as the outer boundary for the cortical bone shell.

4. Offset the Duplicate Geometry: In the CAD software, use the "offset" or "shell" feature to create a new surface that is 2mm away from the outer surface of the scaled duplicate bone geometry. This will generate the cortical bone shell with the desired thickness.

5. Boolean Operation: Perform a Boolean subtraction operation between the original bone geometry and the cortical bone shell geometry. This will remove the original bone geometry from the cortical bone shell, leaving behind the shell itself.

6. Clean and Refine the Geometry: After the Boolean operation, you may need to clean and refine the resulting geometry. Check for any overlapping or intersecting surfaces and make necessary adjustments to ensure a watertight and smooth cortical bone shell.

7. Create Holes for Screw Insertion: Identify the locations where you want to insert screws and create holes in the cortical bone shell geometry accordingly. The size and shape of the holes will depend on the specifications of the screws you intend to use.

8. Export the Final Geometry: Once you have completed the cortical bone shell and added the necessary holes, export the final geometry in a suitable file format (such as STL) that can be imported into a finite element analysis (FEA) software.

I am NOT a doctor, it should be used only for models.

Hope it helps: partial credit AI

Yes! Thanks!

Akila Dulanjalee Wijethunge Can you share your Abaqus models (.inp format)?

Mohammad Vahdani, this will help; https://classes.engineering.wustl.edu/2009/spring/mase5513/abaqus/docs/v6.6/books/usb/default.htm?startat=pt08ch28s02aus105.html

Shijie Zhang, Have you studied section 12.11.4 of ABAQUS/CAE Analyses user manual? https://classes.engineering.wustl.edu/2009/spring/mase5513/abaqus/docs/v6.6/books/usi/default.htm?startat=pt03ch12s11s02.html

Actually this is not possible. The shell thickness differs from one particle to another particle. Using XPS spectrum, you can deduce an average approximate value.

To estimate fluid velocity in a heat exchanger without knowing the surface area, you can make assumptions and employ simplified methods. Assuming a known heat transfer rate (Q) and overall heat transfer coefficient (U), rearrange the heat exchanger equation to solve for surface area (A). Although the surface area cannot be directly determined without more information, you can estimate fluid velocity by assuming a velocity profile, using the cross-sectional area of the exchanger, or relying on known inlet or outlet velocities. These approaches involve simplifications and assumptions about fluid behavior within the exchanger, emphasizing the need for detailed design specifications or manufacturer information for more accurate calculations.

read this

1-s2.0-S0001868618303208-am.pdf

I suggest reviewing the following paper:

Hello there Afsana Mimi! I'd be happy to help you with your research endeavors. It's great that you're working on core-shell structured nanoparticles. Achieving uniform and reproducible results can be a bit challenging, but there are several key factors to consider when working on the formation of complete shell structures:

1. **Precursor Concentrations**: Ensure that you are using the correct concentrations of your precursor materials, both for the core (Au NPs) and the shell (HEPES/HAuCl4). Precise control of concentrations is crucial for achieving uniform shell formation.

2. **Reaction Conditions**: Pay close attention to the reaction conditions such as temperature, pH, and reaction time. Variations in these parameters can significantly impact shell formation. Be consistent in your experimental conditions for reproducibility.

3. **Stirring and Mixing**: Proper mixing and stirring of your reaction mixture can promote uniform shell growth. Ensure that your solutions are well-mixed to allow for even distribution of shell material.

4. **Reduction Agent**: In the case of HEPES/HAuCl4, the reduction agent plays a vital role in reducing Au ions to form the shell. Ensure that the reduction agent is added in the right amount and at the right time during the reaction.

5. **Core Size and Shape**: The size and shape of the core nanoparticles can influence shell formation. Make sure your Au NPs are uniform in size and shape to facilitate consistent shell growth.

6. **Purification and Washing**: Thoroughly purify and wash your synthesized nanoparticles to remove any unreacted or byproduct materials. Proper purification helps in obtaining pure core-shell nanoparticles.

7. **Characterization**: Regularly characterize your nanoparticles using techniques like TEM, SEM, XRD, UV-Vis spectroscopy, and FTIR spectroscopy to monitor the shell formation and confirm the presence of a shell.

8. **Seed-Mediated Growth**: Consider using a seed-mediated growth approach. This involves the initial growth of small Au nanoparticles (seeds) followed by the addition of your shell material. This method can yield more controlled shell growth.

9. **Literature Review**: Examine the literature for your specific core-shell system. Research papers from other scientists who have successfully synthesized similar nanoparticles can provide valuable insights and protocols.

10. **Consultation**: If possible, consult with experienced researchers or your supervisor. They may have insights and troubleshooting tips specific to your lab setup and materials. I will provide as much assistance I can.

Remember that nanoparticle synthesis can be sensitive, and small variations in any of these factors can affect the outcome. Don't be discouraged by initial challenges; scientific research often involves iterative optimization. Keep meticulous records of your experiments, and with patience and persistence, you'll likely achieve the uniform and reproducible core-shell nanoparticles you desire. Good luck with your research!

Hello, my friend Anjali Krishna G! It's great to help out a fellow researcher. Let's talk about the synthesis of magneto-electric core-shell (CoFe2O4/BaTiO3) nanoparticles using the layer-by-layer deposition technique.

The layer-by-layer (LbL) deposition method is a versatile and precise way to control the thickness and composition of coatings on nanoparticles. In your case, you Anjali Krishna G want to achieve a partial coating of BaTiO3 on CoFe2O4 nanoparticles. Here's a general procedure:

**Materials You'll Need:**

1. CoFe2O4 nanoparticles (the core material).

2. BaTiO3 precursor solution.

3. Solvents (typically water or a suitable solvent for the BaTiO3 precursor).

4. pH adjustment solutions if needed.

5. Centrifuge for separating particles.

6. Characterization tools (e.g., TEM, SEM, XRD) to monitor the coating process.

**Procedure:**

1. **Prepare the Core Nanoparticles:** Start with your CoFe2O4 nanoparticles. Ensure they are well-dispersed in a solvent. You may need to sonicate them to break up any agglomerates.

2. **Prepare the BaTiO3 Precursor Solution:** Dissolve your BaTiO3 precursor (usually a salt like barium acetate and titanium isopropoxide) in an appropriate solvent. This solution will contain the material that forms the shell.

3. **Layer-by-Layer Deposition:** Here's where the layer-by-layer magic happens:

- Immerse your core nanoparticles in the BaTiO3 precursor solution.

- Allow the nanoparticles to adsorb BaTiO3 precursor onto their surfaces. This can be influenced by factors like pH, temperature, and the nature of the core nanoparticle's surface.

- After a suitable adsorption time, remove the nanoparticles from the solution.

- Optionally, you can wash and centrifuge them to remove excess precursor solution.

- Repeat these steps for as many cycles as needed to achieve the desired shell thickness. Each cycle adds another layer of the shell material.

4. **Characterization:** Throughout the process, use characterization techniques like TEM or SEM to monitor the growth of the shell on the core nanoparticles. Also, you can use XRD to confirm the crystal structure.

5. **Adjust Parameters:** You may need to adjust parameters such as the concentration of the BaTiO3 precursor, the pH of the solution, and the deposition time to control the thickness and composition of the shell.

6. **Final Treatment:** After reaching the desired shell thickness, you may want to perform final treatments like annealing to crystallize the shell material if needed.

Remember that the exact procedure can vary depending on the specific nanoparticles and materials you Anjali Krishna G are using, so it's important to consult the literature and potentially perform some preliminary experiments to optimize the process for your particular case. Good luck with your research, and feel free to ask if you have more questions!

Hello Anjali Krishna G!

It's great to help you out with your research. Layer-by-layer (LbL) deposition is a versatile technique used to create core-shell structures with precise control over the thickness of each layer. It's commonly used for applications like drug delivery where you want to encapsulate a core material within a shell.

Here's a general procedure for employing the layer-by-layer diffusion method to create partial coatings of a shell over the core:

**Materials Needed:**

1. **Core Particles**: These are the nanoparticles you want to coat with a shell.

2. **Shell Material**: The material that will form the shell. This can be a polymer, a charged molecule, or another material suitable for your application.

3. **Solvent**: A solvent that's compatible with both the core and shell materials.

4. **pH Buffer Solutions**: If your materials are pH-sensitive, you may need buffer solutions to control the pH during the process.

5. **Centrifuge**: To separate coated particles from uncoated ones.

6. **Ultrasonicator**: To aid in dispersion and mixing.

7. **Layer-by-Layer Deposition Equipment**: This can be a simple setup, like vials and a centrifuge, or more complex systems.

**Procedure:**

1. **Prepare Core Suspension**: Disperse your core particles in the solvent. You might need to use an ultrasonicator to ensure a uniform suspension.

2. **Prepare Shell Solution**: Prepare a solution of your shell material in the same solvent. The concentration will depend on the desired thickness of the shell layer.

3. **Deposition**: This is where the layer-by-layer part comes in. Here's a simplified version of the process:

- **Dip the Core Particles**: Immerse your core particle suspension into the shell solution. Allow the shell material to adsorb onto the core particles.

- **Wash**: After a certain amount of time, remove the core particles from the shell solution, and wash them with the solvent to remove any unbound shell material.

- **Repeat**: Repeat the dipping and washing steps for the desired number of layers. The number of layers determines the shell thickness.

4. **Characterization**: After the desired number of layers, characterize your core-shell nanoparticles. This can include measuring size, zeta potential, and shell thickness using techniques like dynamic light scattering (DLS) or electron microscopy.

The expected size range of the core-shell nanoparticles will depend on the specific materials and deposition conditions. Typically, you Anjali Krishna G can control the thickness of the shell and, to some extent, the size of the core particles by adjusting factors like the concentration of the shell material and the dipping time.

Remember that LbL deposition is a highly customizable technique, and the exact conditions will vary based on your specific core and shell materials and your desired outcomes. It's essential to consult the literature, perform preliminary experiments, and optimize the process for your application. Good luck with your drug delivery research!

Draw it in BIM, import .ifc.

You may read my publicatIon in JMBA UK (1990) 70, 441-457. Age determination, growth rate and pop structure of the horse mussel.Mofiolus mofiolus.

Tutorial on how to incorporate easily a custom AD4 parameter file when using Autodock4

Hai Dr OLADIRAN., how are you? I am attracted to your question as I have some information on it. Below, I supply you with all the answers you need, but I would really appreciate it if you could press the RECOMMENDATION buttons underneath my 3 research papers' titles in my AUTHOR section as a way of you saying thanks and appreciation for my time and knowledge sharing. Thank you in advance and please read my answers below :

When modeling the Dielectrophoresis (DEP) force on a particle with multiple shells in COMSOL Multiphysics, the order of modeling the shells can impact the accuracy and complexity of your simulation. Here's a suggested approach:

1. Core Particle (Cytoplasm):Start by modeling the core particle, which in this case is the cytoplasm of the T-lymphocyte. Define the material properties, geometry, and initial conditions for the core particle.

2. First Shell (Cell Membrane):Model the first shell, which is the cell membrane. Apply appropriate material properties, thickness, and boundary conditions to simulate the behavior of the cell membrane.

3. Second Shell (Nuclear Membrane):Model the second shell, which represents the nuclear membrane. Apply similar steps as for the cell membrane, considering the material properties, thickness, and interactions between the nuclear membrane and cytoplasm.

4. Core of Second Shell (Nucleus):Model the core of the second shell, which represents the nucleus itself. Define its material properties, geometry, and any relevant parameters.

5. Third Shell (Nucleus Membrane):Model the third shell, which is the nuclear membrane. Apply similar steps as for the cell membrane and nuclear membrane to define its properties.

6. DEP Force Modeling:Once you've modeled the particle with multiple shells, you can proceed to incorporate the DEP force. Apply appropriate physics interfaces, such as Electric Currents or Electrostatics, to simulate the DEP effect on each shell based on their respective dielectric properties.

7. Boundary Conditions and Excitation:Define the boundary conditions and excitation methods (e.g., electric field) that will induce the DEP forces on the various shells. Consider the interactions between the shells and how they respond to the applied field.

8. Coupling and Multiphysics:If there are interactions between the shells or if their behavior affects each other, you may need to set up multiphysics coupling between different physics interfaces.

9. Meshing and Simulation:Create a suitable mesh for the entire model and perform simulations to observe the behavior of the particle with multiple shells under DEP forces.

When it comes to the order of modeling the shells, it's generally advisable to start from the core and work outward. This helps ensure that the interactions and physics of each shell are properly accounted for. In the case of the T-lymphocyte, you would start with the cytoplasm as the core, then model the cell membrane, followed by the nucleus, nuclear membrane, and any additional layers.

Remember to validate your model using experimental data or existing literature to ensure its accuracy and reliability. The order of modeling the shells should follow the logical progression of the particle's structure, from the innermost core outward to the outermost layers.

Cautions: It is recommended to limit the number of extractions and to follow ethical guidelines for animal research.

Extracting haemolymph from snails can be a delicate procedure, and it is important to minimize stress and injury to the snail during the process. Here is a general outline of the procedure for extracting haemolymph from snails:

1. Prepare the materials: You will need a small container to collect the haemolymph, a sterile syringe and needle (typically 21-25 gauge), and a clean, flat surface to work on.

2. Anesthetize the snail: To minimize stress and injury to the snail, it is recommended to anesthetize it first. You can place the snail in a container with a damp paper towel for a few minutes to relax it.

3. Position the snail: Carefully remove the snail from the container and place it on the flat surface with the opening of the shell facing up.

4. Sterilize the injection site: Using a sterile alcohol pad, clean the area around the injection site (usually near the head or foot) to prevent infection.

5. Insert the needle: Holding the syringe and needle at a 45-degree angle to the injection site, slowly insert the needle into the haemocoel (body cavity) of the snail. Be careful not to insert the needle too far, as this can cause injury to internal organs.

6. Collect the haemolymph: Slowly draw back on the plunger of the syringe to collect the haemolymph into the syringe. Be careful not to apply too much suction, as this can damage the cells in the haemolymph.

7. Remove the needle: Once you have collected the desired amount of haemolymph, carefully remove the needle from the injection site. Apply gentle pressure to the injection site with a sterile cotton ball to stop any bleeding.

8. Release the snail: Carefully return the snail to its container and monitor it for any signs of distress or injury.

It is important to note that extracting haemolymph can be stressful for the snail, and repeated extractions can cause harm or even death.

Hope it helps!!

Credit Mainly AI Tools

Did you figure this out? I am trying to model some wedges which are partially in contact, after applying a load I will force the wedges to bend down and come in contact with a substrate (Master or slave surface). I am getting this error:

slave nodes for surface pair (assembly_surf-glass,assembly_surf-wedges) are reverted back to type node-to-surface. This case may happen if type surface-to-surface cannot find some nodes to form the constraint. Some of reasons are: the slave is coarser or larger than the master surface, the slave is not flat relative to the master surface, or slave nodes that are beyond the extent of the master surface.

6162 slave nodes either found no intersection with a master surface or outside the adjust zone.

Dear Professor Wenbin Yu,

Thank you so much for your suggesstion.

It is very useful for me and of course I will have a look at "Mechanics of structure genome (MSG)".

Just for your information, my main issue is that Gyroid does not have materials at corners C4 and C6. To overcome this issue, I just created additional nodes at these locations and then I can apply PBC to the unit cell.

Best regards,

You can check in with Allschoolabs scientific. Equipped with some of Nigeria's Best equipment currently . See Details - analysis.allschoolabs.com

Dear Kaushik Shandilya

Thank you so much for your detailed answer and your effort.

I haven't found a specific procedure yet or an expert in this field that I can consult. But I hope I will find a way in the light of these papers you suggested.

Regards,

Aylin

Your are modelling on ASPEN PLUS?

Modeling the effects of Na2CO3 as a catalyst for hydrogen production through the gasification of peanut shells in supercritical water conditions involves considering several factors. Here's a step-by-step guide on how you can approach this:

Remember that modeling chemical reactions is a complex task, and the effectiveness of the model heavily relies on the quality and comprehensiveness of the experimental data. It is recommended to consult with experts in the field and refer to existing literature on gasification and catalyst effects to enhance your understanding and improve the accuracy of the model.

Kindly let me know if you get the solution to your problem

Von Mises is a nonlinear function of stress components, which are the output averaged.

The average of von Mises is, in general, not equal to the von Mises of average stresses.

Aung Nyein Soe , your code is not correct and it is likely that your fortran compiler is not able to compile it. Indeed, according to Fortran 77 standards, all Fortran statements must be written in columns 7 to 72, which is not the case in your code (e.g. lines 20, 21 and 28).

Also, lines 56 to 61 do not make sense as you are trying to assign a value to an array, which is not possible for Fortran 77 (and also probably not what you want to do). The indexes of S11, S22... arrays are likely missing.

Before running an abaqus simulation, you should first try compiling your code to make sure no obvious programming mistake is present.

Charles

See also these discussions:

The conventions used in Abaqus for shell elements are as follows.

13 should be 'efferent' not 'afferent' as it takes oxygenated haemolymph away from the ctenidium.

Just to expand on what Giovanni Zucco has said and to clarify a couple of common misconceptions. There is no "issue" in what Riks is doing; in fact, it is behaving exactly as it should. The Riks arc-length method is a Newton solver for tracing solutions to a system of equations with the ability of passing a limit point, i.e. a maximum or minimum, in the driving parameter. At a limit point the number of negative eigenvalues of the tangent stiffness matrix will always change, i.e. if a limit point corresponds to a loss of stability the change is from 0 to 1 negative eigenvalues. But a limit point isn't the only way a system can lose stability. The second possible instability for a single changing parameter is a bifurcation point, where a second equilibrium path intersects your current one. Depending on the nature of this bifurcation point (super- or supercritical) and depending on which path of the bifurcation manifold the solver is currently on, the number of negative eigenvalues may change or may not change. In structural applications when we start at zero load, the solver will generally be on some fundamental path with 0 negative eigenvalues and if it passes a bifurcation point before reaching a limit point will then show a change from zero to one negative eigenvalue. At this point you have reached an instability and the structure will buckle if modelled dynamically rather than quasi-statically. There is nothing "wrong" with Riks in continuing on the fundamental path, however, because its purpose is to follow an equilibrium branch in a direction tangential to the current path. To perturb the solver onto the bifurcated path one could (i) keep the structure perfect and push the Riks solver onto the bifurcated path (branch switching), e.g. using a secondary force or changing the predictor, or (ii) embed an imperfection which breaks the perfect bifurcation such that the imperfect prebuckling and imperfect postbuckling curves are connected. The second option is the more straightforward in commercial FE packages but has significant limitations when mutliple bifurcation points are nearly coincident as different imperfections will trigger different buckling modes. As such the Riks solver doesn't give a "false" buckling load, because one should always be looking at the number of negative eigenvalues while path-following.

see this

Thank you very much for your help!

It seems more and more likely, that the structures acutally might be eggs.

Reverse image search did not produce any helpful output unfortunatley.

It´s indeed a beautiful area, yes! - I will keep you updated in case I find out more!

DDA is much more applied technique to determine the purity of chitosan indeed but you can try CPMAS C13 NMR also.

Mohsin Ali Marwat

As I have gone through some papers on this hybridization modes, I have found that there is a simple equation that can give modes for a hollow shell.

some groups have also carried out for multishelll and even for core-shell. For that first they have calculated modes of different shells and then found out the interaction.

But no where I have found the formulation to get particular wavelength.

I want to know how to get that equations which will give wavelengths of different coupled modes after interaction. I know the equation to calculate modes of plasmon for single hollow nanoparticle.

Hi Hanieh, The issue you are experiencing may be due to the synthesis conditions or the properties of the AuNSs. It's possible that the AuNSs are aggregating or clustering together during the coating process, which could result in multiple nanostars being coated with silica instead of individual nanostars.

One potential solution to this problem is to try modifying the synthesis conditions to prevent aggregation or clustering of the AuNSs. This could involve optimizing the pH, temperature, or reaction time of the coating process to promote the formation of individual nanostars. Another solution could be to modify the surface of the AuNSs prior to coating to make them less likely to aggregate or cluster.

It may also be helpful to consult with other researchers or experts in the field who have experience with similar coating processes to gather additional insights and suggestions for optimizing your coating process.

If you're ever in need of more personalized research support, our services (e.g. consulting, data analysis, editing, technical writing, and scientific illustration) can provide tailored solutions to help you achieve your academic goals and save you valuable time. If you're interested in learning more about our services, please feel free to send me a message.