Polarity - Science topic

Yes, asymmetric EDLC supercapacitors have polarity due to different electrode materials, which create an uneven voltage distribution. Reversing polarity can cause degradation or failure, so they must be used with the correct orientation.

I can't find the article either. If you found the article, could you send it to me?

Hi,

Various developing solvents can be used, or separation can be carried out using recrystallization, HPLC, or reduced pressure distillation.

Never encountered problems: rinse the column using a gradient starting at 20% ACN in water to 100% ACN in 30 minutes. Store the column in 100% ACN. Our system contained also PEEK tubing: no problem.

This is not a simple topic. However it is completely understandable and calculable. An internet search turns up all kinds of information, references, even online calculators. See if something like this helps:

Dear Homasadat Esfahani

You stumble on the short coming of every individual hydrophobicity scale (which is behind every bioinformatics method that can predict the hydrophobicity).

In general the overall 'consensus is that cysteine is (moderate) hydrophobic.

See for example:

where a comparison between some of the most frequently used scales is made.

keller3biotech2015suppl.docx

See also https://en.wikipedia.org/wiki/Cysteine (scroll to "Roles in protein structure") which indicates quite accurately the nuanced view on this matter (there is for example a big difference whether you consider the individual AA or look at the amino acid in the context of protein and/or the protein in its 'natural environment').

Best regards.

That´s okay I´d say.

If it doesn´t work, you could also use the Mitsunobu reaction. This way, you activate the alcohol for the nucleophilic attack of the acid, which in your case I think could be more appropriate.

Good luck!

CASTEP, as many DFT codes, calculates the band structure and thus evaluates the difference between the last occupied state and the first un-occupied state. The establishment of selection rules to determine if a transition if forbidden or not is another step. You could plot the spin resolved bands or spin resolved DOs, for example, and obtain such information.

Anyway, if you believe this is a bug, I am confident people at CASTEP would be happy to hear your comments and eventually take action. Commenting on a general purpose research website might not be leading to a solution.

Regards,

Roberto

Changing the excitation variables in "Edit Sources" will only affect the field results and not the S-parameters. By exciting both modes with the 90 degrees phase shift you will generate a CP wave and can look at the metasurface response in any of the field results.

I am not sure if looking at the combined effect in the S-parameters is useful in a unit cell simulation, especially if the unit cell is circularly symmetric, but it can be done. If you want to look at the effect on the S-parameters when you excite both you need to post process the TE and TM S-parameters. Look up the S-matrix of an ideal 3 dB hybrid coupler, you can use it to transform the two linear and orthogonal polarizations of TE and TM into circular polarization. You can probably do this calculation directly in the calculator window of the results on HFSS.

Xiao Songmao Thanks for the suggestion I will try.

Malcolm White and Shrivastav a.k.

First thank you for your response. I still try to measure the polarizer correctly. In my research I found a blog post. You may see it via link --> https://www.ainfoinc.com/blog/blog-how-to-measure-the-axial-ratio-of-the-circular-polarizer.html

In there the method is similar as Malcolm White said. And it looks more simpler and quicker to do for me. You both may see the pictures of my measurement setup. I put two 4 port OMT's back to back. Each OMT has 2 TX and 2 RX ports for vertical (V) and horizantal (H) polarizations. In this first setup I did the measurements S21-VV and S21HH. Then I put the polarizer between the OMT's as in picture at 45degree alinged and measure S21-VV and S21HH again. So it's like in blog post ILV1 ILH1 and ILV2 ILH2 I assume. Then I took amplitude division in linear scale;

Delta-V=ILV2/ILV1 and Delta-H=ILH2/ILH1

So if it's true so far Delta-V and Delta-H would be my polarizer's vertical and horizantal results in linear scale. Then I also took their amplitudes division to find Axial ratio --> AR= Delta-V/Delta-H

Then using this formula I calculated cross polar discrimination --> XPD=20*log10((AR+1)/(AR-1))

The results I had from those calculations in Matlab seems so perfect but also unrealistic beacause I've never seen a polarizer that has these kind of perfect XPD results. So I beleive I had made a mistake because I also couldn't see 90 degree phase difference between measurements. But I can't find where. If you have any idea please tell.

To extract a wide range of polar and non-polar compounds, such as antibiotics, from large aqueous samples (e.g., 500 mL), the most suitable solid-phase extraction (SPE) cartridge is one that offers both high capacity and versatility across different compound polarities. Based on recent studies, the hydrophilic-lipophilic balance (HLB) SPE cartridge is highly effective for this purpose.

Cartridge Selection

The Oasis HLB cartridge is one of the best choices for handling large-volume extractions of both polar and non-polar compounds. This cartridge contains a polymeric sorbent that integrates both hydrophilic and lipophilic components, providing the flexibility to retain analytes with a wide range of polarities. This balance is crucial when dealing with mixed compound classes like antibiotics, which may have varying polarities depending on their chemical structures.

The versatility of HLB cartridges has been demonstrated in multiple studies. For example, Yi et al. (2015) showed that optimizing the pH of the sample can significantly improve the extraction efficiency of antibiotics with low and high pKa values when using HLB cartridges (Yi et al., 2015). Their study highlighted how HLB materials can capture a broad spectrum of antibiotic compounds from environmental water samples, making them an ideal choice for mixed polarity analytes. Additionally, Köke et al. (2018) demonstrated that HLB cartridges outperform traditional methods for both polar and non-polar analytes in aqueous environments, ensuring higher recovery rates (Köke et al., 2018).

Protocol for Large-Volume Extraction (500 mL)

1. Preconditioning the Cartridge:

Start by conditioning the Oasis HLB cartridge with 5 mL of methanol to activate the sorbent material. Follow this by rinsing with 5 mL of ultrapure water to equilibrate the cartridge for sample introduction. This step is necessary to remove any contaminants and prepare the sorbent for efficient binding of both polar and non-polar analytes.

2. Sample Loading:

The pH of the sample should be adjusted depending on the pKa values of the target antibiotics. Antibiotics with lower pKa values (<7) are better extracted under slightly acidic conditions, while those with higher pKa values (>7) require neutral conditions. Studies, including those by Yi et al. (2015), have shown that adjusting the pH can lead to significantly improved extraction efficiencies, especially for polar compounds (Yi et al., 2015).

Pass the 500 mL aqueous sample through the cartridge at a controlled flow rate (10-20 mL/min). This ensures that both polar and non-polar compounds have sufficient time to interact with the sorbent, optimizing retention.

3. Washing:

After sample loading, wash the cartridge with 5-10 mL of water or a weak solvent (such as 5% methanol in water). This step removes any residual matrix interferences while ensuring that the target analytes remain bound to the sorbent.

The study by Wang et al. (2023) emphasized the importance of using sequential extraction methods to reduce competition between analytes and to prevent matrix effects that could displace polar compounds during extraction (Wang et al., 2023).

4. Elution:

For the elution of polar compounds, use 5-10 mL of methanol. This solvent has been shown to effectively elute hydrophilic analytes, while maintaining the integrity of the extraction. For non-polar compounds, a stronger solvent, such as acetonitrile or a methanol-acetonitrile (1:1) mixture, should be used. This ensures maximum recovery of both polar and non-polar compounds, as noted in the work of Sajid & Basheer (2016) on SPE methods (Sajid & Basheer, 2016).

Ensure complete elution by passing the solvent slowly and thoroughly through the cartridge.

5. Post-Elution Concentration:

The eluted fractions should be evaporated to dryness using a gentle stream of nitrogen or a vacuum concentrator. This step concentrates the analytes, preparing them for further analysis, such as liquid chromatography-mass spectrometry (LC-MS).

Reconstitute the dried extract in a small volume (1-2 mL) of methanol or a similar solvent before analysis.

pH Optimization for Efficient Extraction

As mentioned earlier, optimizing the sample pH is critical for maximizing the recovery of both polar and non-polar compounds. Antibiotics with different pKa values respond differently to extraction conditions. Yi et al. (2015) demonstrated that adjusting pH for polar compounds significantly enhances recovery rates. Polar antibiotics, particularly those with lower pKa values, are best extracted at acidic pH, while non-polar compounds are better captured at neutral to slightly alkaline pH (Yi et al., 2015).

Conclusion

For extracting a wide variety of polar and non-polar antibiotics from large aqueous samples, the Oasis HLB cartridge is highly recommended due to its hydrophilic-lipophilic balance, which ensures broad-spectrum retention of analytes. By using the outlined protocol, including steps such as pH optimization, precise washing, and tailored elution, you can maximize the efficiency of your extractions. The results from Yi et al. (2015) and Köke et al. (2018) provide robust evidence for the effectiveness of this approach in handling both polar and non-polar compounds across diverse matrices (Yi et al., 2015), (Köke et al., 2018).

Here are the references:

1. Köke, N., Zahn, D., Knepper, T., & Frömel, T. (2018). Multi-layer solid-phase extraction and evaporation—enrichment methods for polar organic chemicals from aqueous matrices. Analytical and Bioanalytical Chemistry, 410(10), 2403-2411. https://doi.org/10.1007/s00216-018-0921-1

2. Sajid, M., & Basheer, C. (2016). Stir-bar supported micro-solid-phase extraction for the determination of polychlorinated biphenyl congeners in serum samples. Journal of Chromatography A, 1455, 37-44. https://doi.org/10.1016/j.chroma.2016.05.084

3. Wang, Y., Zhou, W., & Pawliszyn, J. (2023). Sequential solid-phase microextraction with biocompatible coating materials to address displacement effects in the quantitative analysis. Analytical Chemistry. https://doi.org/10.1021/acs.analchem.3c00508

4. Yi, X., Bayen, S., Kelly, B., Li, X., & Zhou, Z. (2015). Improved detection of multiple environmental antibiotics through an optimized sample extraction strategy in liquid chromatography-mass spectrometry analysis. Analytical and Bioanalytical Chemistry, 407(30), 9071-9083. https://doi.org/10.1007/s00216-015-9074-7

I hope that helps you if you have another question just ask.

Dear Dr. Vahinipriya Manoharan

Macrophages become strongly adherent to the culture dish, making it difficult to detach them. It would not be proper to leave them in trypsin for 30 minutes. Instead, there are other alternatives that I have listed below which you could incorporate in your protocol.

1. Macrophages can be lifted by incubating them in cold PBS (without Ca2+ and Mg2+) and 5 mM EDTA for 45 min at 4 °C.

2. Incubate the cells in ice-cold PBS (50% of media volume) for 5 min. Detach the cells from the plate with gentle scraping or repeated pipetting. Or

3. Make use of temperature-responsive culture dish coated with poly-(N-isopropylacrylamide). On lowering to room temperature, the culture surfaces change from hydrophobic to hydrophilic, and this weakens the cells' attachment to the dish. For more information on temperature-responsive culture dish coated with poly-(N-isopropylacrylamide), you may want to refer to the papers attached below.

Good Luck!

Regards,

Malcolm Nobre

thank u dear Bintu Kumar

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/.

Dear Haejin Woo

It has to do with the solvent (mobile phase) used. If the mobile phase is more polar than the silica on the TLC plate then this explains your observation. Since both DPG and PG are both polar lipids, the choice will always be inclusion of (most likely) methanol and a bit of water. See for example

Best regards.

PS. There are numerous scales and ways to express the polarity of solvents but see for an example here https://research.cbc.osu.edu/turro.1/wp-content/uploads/2017/02/PolarityofSolvents.pdf

Methanol and sulfuric acid are used in the analysis of polyhydroxyalkanoates (PHA) methyl esters by GC-MS to facilitate methanolysis, converting PHAs into volatile methyl esters suitable for analysis. Sulfuric acid acts as a catalyst, enhancing the reaction efficiency. Non-polar solvents are preferred in GC-MS because they improve the separation and detection of non-polar analytes, ensuring clearer results.

Hello Protsan Dhungana

Try using "#P freq=raman polar b3lyp/6-311g(d,p)" if you use Gaussian 16 software.

The choice of DFT functional and basis set ( b3lyp/6-311g(d,p) ) depends upon the nature of your work and its benchmark level.

The above input line will give the Dipole polarizability (Alpha), the First hyperpolarizability (Beta), and its components.

Feel free to reach out.

I hope this helps!

I think it is not straightforward to calculate these using GROMACS. Instead, you can use other tools, such as "freesasa", it wil give you total as well as each type of surface area. For this, you need pdb files that can be extracted and later using bash (or WSL), you can do it.

Just an example:

#!/bin/bash

set -e

for i in $(ls -1v ../S176P/packing/pdbs/*.pdb); do

freesasa --select "NLS, resi 87-95" $i -w -n 100 >> output.txt

done

Here, NLS used as title, and resi for residue index, like calculate accessible surface for 87-95 residues. You can use your own index.

Google it, and and you find its help as well. Pretty good tool.

The melting of polar ice caps, particularly in the Arctic and Antarctic regions, has significant implications for global sea levels and climate patterns. Here are the potential effects:

In conclusion, the melting of polar ice caps has far-reaching consequences for global sea levels, climate patterns, and ecosystems. These effects highlight the interconnectedness of Earth's systems and underscore the urgency of mitigating climate change to reduce further ice loss and its impacts on the planet and human societies.

You

From the SDK docs provided by Polar: "Electrocardiography (ECG) data in µV with sample rate 130Hz" Source: https://github.com/polarofficial/polar-ble-sdk

There is a whole chapter on effects of solvents on florescence emission spectra in Joseph Lakowicz's textbook "Principles of Fluorescence Spectroscopy" (Chapter 7 in the 1st edition). He divides solvent effects into general and specific types. The following is an excerpt from p. 189.

"By general solvent effects we mean those which result from the refractive index (n) and dielectric constant (epsilon)....Specific solvent effects refer to specific chemical interactions between the fluorophore and the solvent molecule, such as hydrogen bonding and complexation."

The rest of the chapter goes into details.

Have you found the answer? I want to know the same, If you know could you please share with me. Thank you

The difference in docking results between alpha-glucosidase and established inhibitors such as miglitol and acarbose is a complex issue that involves computational limitations, the intrinsic characteristics of the enzyme, and the physicochemical properties of the compounds. The unexpected superior performance of long-chain lipids highlights this issue. Molecular docking algorithms, such as GOLD and DOCK6, use scoring functions to predict the affinity between ligands and target proteins. These functions, although sophisticated, may not fully capture the complexities of molecular interactions, especially non-polar interactions and solvation effects. These effects are crucial for accurately modeling the behavior of lipid molecules. If interactions with long-chain lipids are not adequately accounted for, binding affinities may be overestimated.

Additionally, the active site of alpha-glucosidase is dynamic and can accommodate a wide range of substrates and inhibitors through substantial conformational adjustments, adding another layer of complexity. Docking algorithms that do not adequately model molecular flexibility may inaccurately predict the binding modes and affinities of relatively rigid molecules such as miglitol and acarbose, compared to more adaptable long-chain lipids. Furthermore, the hydrophobic nature of long-chain lipids drives them to interact with non-polar regions of proteins, reducing their exposure to water. If the docking algorithm gives too much weight to hydrophobic interactions, it may lead to incorrect predictions of higher affinities for certain molecules. This is especially true if the modeled alpha-glucosidase contains inaccurately depicted or overrepresented hydrophobic pockets.

To address these discrepancies, a comprehensive approach is necessary. This includes using enhanced sampling methods to better account for ligand and enzyme flexibility, utilizing improved scoring functions or empirical corrections that more accurately model hydrophobic interactions and solvation effects, and integrating experimental validation to corroborate computational predictions. Induced fit docking or ensemble docking techniques can provide a more realistic model of the ligand-enzyme interaction. Advanced scoring functions can offer a more nuanced understanding of the energetics involved. Ultimately, a synergy of computational refinement and empirical verification will be essential to resolve the apparent paradox in the alpha-glucosidase docking results and to advance our understanding of this enzymatic target.

Try using Isopropanol alcohol in your mobile phase and a C18 HPLC column with a UV detector.

Surface energy can be determinedfrom surface angle measurement. You can find allthe detail on the internet by interrogating contact angle and durface enrgy

Hi, I am struggling with the vibrational contribution to SFG hyperpolarizability

calculated on small molecule such as water or CO in vacuum .

I read that vibrational contribution are usually negligible for organic molecule with covalent bonds, is it the case also of VIS-IR SFG where one of the frequency can be resonant with the vibrational modes?

Because my vibrational contributions (calculated by Gaussian16 by differentiation)are in the order of 10-4 with respect to the electronic hyperpolarizability (obtained with the Multiwavefunction software thanks by a Sum over state method).

I know that usually IR SFG experiment are performed enhancing the signal with surfaces,so could be this justify my low vibrational contribution?

If a Metamaterial has circular polarization features this already means that it is sensitive to polarization of light. For example it transmits only right-handed circular polarization and blocks a left handed one.

Polarization insensitive metamaterial in opposite has a property to interact with any polarization state in the same way.

Hey there Igor Lavrentev! Using a silver wire as a pseudo reference electrode for cyclic voltammetry (CV) on the IKA ElectraSyn 2.0 is a feasible option. Silver is commonly employed as a reference material due to its stable and reproducible potential.

When recording a CV for the first time, it's essential to follow established protocols. I'd recommend checking out literature like "Electroanalytical Chemistry: A Series of Advances" by Allen J. Bard for comprehensive insights into CV techniques. Additionally, "Modern Techniques in Electroanalysis" by Pedro Gomez-Romero provides practical guidance.

Understanding how the potential (U) is determined when using a pseudo reference electrode involves considering the reference electrode's potential against a known standard. The potential of the pseudo reference electrode is typically stable and known, allowing for accurate measurements.

Feel free to explore these references for a deeper understanding of CV techniques, and let me know if you Igor Lavrentev have more specific questions!

Thank you for your reply.

Your question isn't very clear, but the short answer is that it uses the LSDA for the spin-polarised exchange-correlation functional, and a Hubbard U for any of the atomic orbitals you specified a Hubbard U value for. This is the basis for the "DFT+U" approach, almost always used to reduce the effects of self-interaction on atomic d- or f-states.

Once you have the Phi or Theta vs magnitude values then you can directly plot using Polar r(X) Theta (Y) option in Origin pro.

Before clicking on the polar option select the two columns (Phi or Theta vs magnitude values)

The following formula can be performed to calculate an ellipse's polar moment of inertia, sometimes recognized as the polar second moment of area:

I_p​=1/4*​πa³b

Where:

· I_p​ is the polar moment of inertia.

· a is the semi-major axis of the ellipse.

· b is the semi-minor axis of the ellipse.

One-pot synthesis of block copolymer dispersant by ICAR ATRP with ppm copper catalyst and the dispersibility on pigment

Author links open overlay panel

, , , , , ,

https://doi.org/10.1016/j.porgcoat.2022.106914Get rights and content

Abstract

The controlled / living polymerization mechanisms have advantages on synthesizing the dispersant with defined structures and compositions, while encountering with individual drawbacks in industrial application. Based on the initiators for continuous activator regeneration atom transfer radical polymerization (ICAR ATRP) of oligo(ethylene oxide)methyl ether methacrylate (OEEMA) and glycidyl methacrylate (GMA) monomers, the diblock copolymers POEOMA-b-P(OEOEMA-co-GMA) were prepared. The GMA units were further modified with 3-mercaptopropionic acid (MPA) agent. The polymerization and modification procedure can be readily realized in a one-pot technology with complete monomer conversion (~100%) and high ring-opening efficiency (~100%), as well as low concentration copper catalyst (100 ppm). Using the MPA modified P(OEOEMA-co-GMA) as anchoring block, POEOMA as stabilizing block, the obtained block copolymers can be used as dispersant to disperse and stabilize the pigment yellow 14. The standing experiment, optical microscope (OM) and dynamic light scattering (DLS) measurements reached to a consistent conclusion that the absolute number of carboxyl groups on each chain modulate the dispersibility of the dispersions, rather than the relative content of carboxyl groups. This work provided a feasible one-pot technology to efficient dispersants.

Graphical abstract

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Introduction

The dispersants, acting as indispensable additives, have been widely used in various fields in industry due to the unique property of dispersing and stabilizing particles. For example, the dispersant can be used to disperse the pesticide, [1], [2], [3], [4] the additives in food, [5] the pigment in paint and ink, etc. Up to now, the low molecular weight dispersants have been well studied and extensively used due to the simple preparation and low cost. However, because of the limited anchoring groups and short stabilizing moiety, the application of low molecular weight dispersants was always limited. Alternatively, the polymeric dispersants with high molecular weight and random, block, or graft structures were welcomed. The dispersants with block and graft structures were especially focused due to the excellent dispersibility brought by the well-defined structures, controlled compositions and site-specific functionality. [6], [7], [8], [9] Typically, such copolymers can be synthesized by controlled / living polymerization mechanisms, such as living anionic polymerization (LAP), [10], [11], [12], [13], [14], [15] atom transfer radical polymerization (ATRP), [16], [17], [18], [19], [20] nitroxide mediated radical polymerization (NMRP), [21] reversible addition-fragmentation chain transfer (RAFT) polymerization, [22], [23], [24] group transfer polymerization (GTP), [25], [26] and so on.For example, using the normal ATRP, Auschra et al. prepared the diblock copolymer poly(butylacrylate)-b-poly(dimethylamino ethylacrylate) (PBA-b-PDMAEA) and studied their dispersibility on opaque or transparent pigments. [16] Similarly, Monteiro et al. synthesized the amphiphilic block copolymer methoxy poly(ethylene glycol)-b-poly(4-vinyl pyridine) (mPEG-b-P4VP) by normal ATRP. [17] Comparing with the sodium salt of polyacrylic acid (Na-PAA), the diblock copolymer mPEG-b-P4VP showed excellent dispersibility on TiO2 nanoparticles. The normal ATRP was also used to synthesize the amphiphilic block copolymer poly(acrylic acid)-b-poly(4-vinylpyridine) (PAA-b-P4VP) and poly(acrylic acid)-b-poly(2-(dimethylamino)ethyl methacrylate) (PAA-b-PDMAEMA) by Costa et al., [18] and their application on stabilizing the TiO2 particles was compared. Aiming to meet the requirement for the pigment dispersion in LCD color filters, the block copolymer poly[(2-dimethylamino)ethyl methacrylate]-b-poly[oligo(ethylene oxide)methyl ether methacrylate] (PDMAEMA-b-POEOMA) was designed and synthesized by normal ATRP, [19] and the improved dispersibility on copper phthalocyanine pigment was achieved. Alternatively, using the reverse ATRP, Lokhande et al. synthesized the diblock copolymer poly(butyl methacrylate)-b-poly(glycidyl methacrylate) (PBMA-b-PGMA) and further modified the GMA units with methyl ethanol amine. [20] The generated block copolymers also showed excellent dispersibility on pigments.With versatility on polymerizing plenty of functional monomers, the RAFT mechanism was also widely used to synthesize the dispersants with expected structures and compositions. For example, North et al. prepared the zwitterionic diblock copolymer poly(methacrylic acid)-b-poly(2-(dimethylamino)ethyl methacrylate) (PMAA-b-PDMA) using an atom-efficient, wholly aqueous one-pot technology. [22] The obtained zwitterionic diblock copolymers can be served as highly effective dispersants for transparent yellow iron oxide nanoparticles. Using the RAFT based alcoholic dispersion polymerization, they also synthesized the nano-objects with poly(2-(dimethylamino)ethyl methacrylate) (PDMA) as steric stabilizer block and poly(benzyl methacrylate) (PBzMA) as core-forming block. [23] The nano-objects can be used to disperse the model pigment of silica. Using the RAFT mechanism, Saindane et al. prepared the amphiphilic diblock copolymer poly (ethyl acrylate)-b-poly (acrylic acid) (PEA-b-PAA) and introduced it into water borne coating formulation. [24]With powerful control on the structures and composition of copolymers, the LAP mechanism was also found extensive application in preparing the dispersants. For example, via sequential LAP in tetrahydrofuran (THF) solvent, the block copolymer poly(2-vinylpyridine)-b-poly(ε-caprolactone) (P4VP-b-PCL) was realized and used for dispersing the TiO2 nanoparticle. [10], [11], [12] Using the LAP mechanism, the diblock, triblock and tapered copolymers based on tert-butyl methacrylate (tBMA), ethylene oxide (EO), 4VP, and DMAEMA monomers were synthesized by Creutz et al. [13], [14], [15] By transformation of the tBMA units into sodium methacrylate (MANa) units, the generated copolymers can be employed as effective dispersants for TiO2. The triblock copolymers consisting of PMANa as outer blocks cannot stabilize the dispersion, and the triblock copolymers with the reverse structure form poorly stable dispersions due to partial particle bridging. The stabilization capability was even lost in the case for non-blocky distribution of the DMAEMA and MANa comonomers. Furthermore, they confirmed that the blockiness of comonomer distribution was a prerequisite for expected dispersibility. The tapered diblock with a regular change in composition from one block to the other one has better dispersibility than that for the pure diblock copolymer. The analysis on these model copolymers actually confirmed that the molecular composition of the block copolymers showed important effect on the dispersion stability.Obviously, the above examples illustrated that the block copolymers had been confirmed with excellent dispersibility in pigment formulations. However, the employed mechanisms were always limited with individual drawbacks, such as the deep color of copper catalyst in ATRP, expensive chain transfer agent in RAFT, tedious or strict operation conditions in GTP or LAP mechanisms. In most cases, the complex operations for purification should be accompanied, which increased the cost and lowered the possibility in an industrial application. Thus, the practical application of the block dispersant is still encountering with much challenge and less feasibility. In the past several years, employing a reversible activation and deactivation equilibrium catalyzed by transition-metal redox-active complexes, [27], [28], [29], [30], [31], [32], [33], [34], [35] the normal ATRP process has been updated by using lower concentration (ppm) of copper catalyst, such as initiators for continuous activator regeneration (ICAR) ATRP, [36] activators regenerated by electron-transfer (ARGET) ATRP, [37] supplemental activators and reducing agent (SARA) ATRP, [38] electrochemically mediated ATRP (eATRP), [39], [40] and photo-induced ATRP. [41], [42], [43] With the advantages of ppm copper catalyst, cheap catalyst and initiators, versatile monomers and convenient operations, these techniques are finding with potential application in industry with large scale.In this contribution, aiming to seeking an effective dispersant and exploring a versatile route to their industrial production, the ICAR ATRP with ppm copper catalyst was attempted to target the model diblock copolymer POEOMA-b-P(OEOMA-co-GMA). The carboxyl groups were subsequently introduced by modifying GMA units with 3-mercaptopropanoic acid (MPA) agent via ring-opening reaction (Scheme 1). Especially, a one-pot technology was developed, which was featured with high monomer conversion, simple operations and correspondingly low cost in practical applications. The application of the generated block copolymers as dispersants was comprehensively compared and analyzed.

Section snippets

Materials Glycidyl methacrylate (GMA, 99%, Adamas), and oligo(ethylene oxide) methyl ether methacrylate(OEOMA300, average molecular weight 300, Aldrich) were purchased and passed over a column of basic alumina to remove inhibitor prior to use. Tris(2-pyridylmethyl)amine (TPMA) was synthesized by following the previously reported procedure [44]. Toluene (99%, Greagent), ethanol (99.7%, Greagent), copper(II) bromide (99%, Adamas), ethyl 2-bromoisobutyrate (EBiB, 98%, Adamas), 3-mercaptopropionic acid (MPA,

Synthesis and characterization of MPA modified POEOMA-b-P(OEOEMA-co-GMA) Aiming to prepare the dispersant for yellow 14 in aqueous formulation, the stabilizing block of POEOMA was selected due to the excellent solubility in water. [36], [37], [45] According to the principle for dispersants, [6], [7], [8], [9], [46] the anchoring block containing amine or carboxyl groups was always preferred. However, the acrylic monomer with functional groups, such as amine or carboxyl groups, were difficult to polymerize in an ATRP system, especially in an ATRP system with ppm

Conclusion Using the ICAR ATRP technique, the diblock copolymer POEOMA-b-P(OEOEMA-co-GMA) can be readily synthesized in a one-pot technology in the presence of ppm coper catalyst. The GMA units can be further modified with MPA agent to introduce the carboxyl groups. The polymerization and modification procedure can be performed with complete monomer conversion (~100%) and high efficiency (~100%). No any additional purification procedure is required and the operations is largely simplified. Thus, the

CRediT authorship contribution statement Conceptualization: Meng Luan, Guowei Wang.Methodology: Meng Luan, Ding Shen, Peng Zhou.Software: Meng Luan, Penghan Li, Boyang Shi.Validation: Meng Luan.Formal analysis: Meng Luan, Ding Shen, Di Li.Investigation: Meng Luan, Ding Shen, Peng Zhou, Di Li.Resources: Meng Luan, Ding Shen, Di Li.Data Curation: Meng Luan, Peng Zhou, Boyang Shi.Writing-Original draft: Meng Luan.Writing-Review & editing: Meng Luan, Guowei Wang.Supervision: Guowei Wang.Visualization: Meng Luan, Peng Han, Guowei Wang.

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement We appreciate the financial support of this research by the National Natural Science Foundation of China (21774022).

References (51)

I think you can try something like this

Though the purpose behind the experiment is not clear but purging isnecessary in electrochemistry to get rid of oxygen. If the experiment target is reduction of CO2 then the solution must be saturated with CO2. In all cases the scan must be performed in a stagnant solution because cyclic voltammetry theory is based on diffusion as the mode of mass transfer.

According to our limited understanding and practical experience, the connection between TPSA and thermal stability is not significant.

Gwyddion can do that automatically:

It is still okay, however use dichloromethane first.

script that demonstrates how to create a polar plot:

```python

import numpy as np

import matplotlib.pyplot as plt

# Sample data for Young's modulus and Poisson's ratio

theta = np.linspace(0, 2*np.pi, 100) # Angular values

young_modulus = np.random.rand(100) # Young's modulus values (replace with your own data)

poissons_ratio = np.random.rand(100) # Poisson's ratio values (replace with your own data)

# Create the polar plot

fig = plt.figure()

ax = fig.add_subplot(111, polar=True)

# Plot Young's modulus

ax.plot(theta, young_modulus, label="Young's Modulus")

ax.fill(theta, young_modulus, alpha=0.25)

# Plot Poisson's ratio

ax.plot(theta, poissons_ratio, label="Poisson's Ratio")

ax.fill(theta, poissons_ratio, alpha=0.25)

# Set the labels and title

ax.set_xticklabels([])

ax.set_yticklabels([])

ax.set_title("Polar Diagram for Young's Modulus and Poisson's Ratio")

# Add a legend

ax.legend()

# Show the plot

plt.show()

```

matplotlib library should been installed (`pip install matplotlib`) before running this script. You can replace the sample data (`young_modulus` and `poissons_ratio`) with your own data accordingly.

This script generates a polar plot with Young's modulus and Poisson's ratio represented as two separate curves. Each data point is plotted at a specific angle (`theta`) around the polar axis. The `fill` function is used to fill the area enclosed by the curves.

Good luck

Yes. The keywords in Gaussian are 'EmpiricalDispersion=GD3BJ' or 'em=gd3bj'. One should write 'B3LYP-D3(BJ)' in a paper. 'B3LYP-D3BJ' is not strict but can be understood.

I have some extra suggestions on your question:

(1) The full name of 'DES' should be given. Abbreviations 'DES' may make some readers confused since they come from different research fields.

(2) It is possible that you can firstly perform the geometry optimization with no diffuse functions, to save the computational time and avoid possible convergence problems. And secondly perform a single-point calculation with diffuse functions, e.g. to calculate the polarizability. This depends on your studied molecules.

Definitely no. For versatile derivatization, you should perform the reaction under alkaline conditions. For this borate or carbonate buffers are needed and there is not any problem in your setup. I suggest you use FA at the end of the derivatization reaction as a stopping reagent. By lowering the pH after the experimentally defined incubation period, FMOC affinity is restricted, and formation of the further products or by-products is prevented. This will return as reproducible derivates. You may refer to my research which was conducted with a similar strategy but the target was aminoglycoside. It may be helpful for clarifying...Here is the link;

When performing mass spectrometry analysis of lipid classes using a lipidomics standard like the EQUISPLASH product from Avanti Polar Lipids, adding the standard to your test sample serves as an internal standard for quantification. This approach helps account for variations that can occur during sample preparation, extraction, and analysis. Here's how it works:

1. Internal Standard Principle:An internal standard is a compound that is added to both your standard samples and your test samples in a known amount. It's chemically similar to the analytes of interest but should be easily distinguishable in the mass spectrometry analysis. By adding a known amount of the internal standard, you can correct for variations that might occur during sample preparation and analysis.

2. Adding the Internal Standard:When you add the EQUISPLASH lipidomics standard to your test sample during the extraction process, it becomes a reference compound with a known concentration that you control. This internal standard will undergo the same extraction and analysis steps as your sample, which helps compensate for any losses, variations, or biases introduced during these steps.

3. Quantitative Data Analysis:To obtain quantitative data from your mass spectrometry analysis, you'll follow these steps:

The rationale behind this is that the internal standard's known concentration serves as a reference point. If the extraction and analysis are consistent, the ratio of the analyte's peak area to the internal standard's peak area should be proportional to the ratio of their concentrations.

4. Calibration Curve:To convert the peak area ratio to quantitative concentration, you'll need to create a calibration curve. This involves analyzing a series of standard solutions with known concentrations of the lipid classes using the same extraction and analysis procedures. The calibration curve plots the concentration of the internal standard against the measured peak area ratio.

5. Quantification:Using the calibration curve, you can then determine the concentration of your lipid classes in your test samples based on the peak area ratio. The formula to calculate the concentration is derived from the linear relationship shown in the calibration curve.

By adding the internal standard and utilizing a calibration curve, you can obtain quantitative data for your lipid classes in your test samples, even considering any variations introduced during sample preparation and analysis. This internal standard approach enhances the accuracy and reliability of your quantitative results. Subhadip Kundu

Greetings, for availing its softcopy the webpage libgen helps you with it.

you can get mor information in the manual of multiwfn in this manual explain about polarizability and hyper

Sriram Srinivasan

Toluene can be classified as a polar hydrocarbon with a dipole moment of 0.41 D compared to hexane, which has no dipole moment. Тhey mix with each other in any ratio. Surfactants for mixing (formation of emulsions) are used when the substances do not mix and form an interface between them.

Another potential scenario is that the DCM and Acetonitrile do not have the capability to create a hydrogen bond, while DMSO can form a hydrogen bond depending on the structure of your solute. If there is a complex formed in the ground state, it is likely that you will observe multiple lifetimes.

Of course it is best to have pure reference standards. In the real world, it is understood that this is not always possible. For a qualitative result, you may be able to make an educated guess using a properly developed HPLC method with MS and DAD detection modes, in-line (compound has chromophores that can be detected AND it must also ionize well under the analysis conditions used). MS/MS would add more information, and another orthogonal dimension of analysis. The quality of the HPLC method is the key as the results will only be as good as the method used.

We try to use as many different orthogonal methods of analysis as possible (combine detection methods which use different chemical or physical properties) with or without standards to come up with a proposed ID. That is what leads to a good QUALITATIVE ID.

Monoclinic and triclinic crystals are much more complicated, because in the general case light becomes elliptically polarized. If you want to have nice plots, use a uniaxial or an orthorhombic crystal and arrange it in a way that the polarization directions are parallel to the crystallographic axis to preserve linear polarization. For a monoclinic crystal linear polarization is definitely preserved for light that is polarized parallel to the crystallographic b-axis, but in a 90° geometry this does not help.

Hi Pratyasha Bhowal ,

In general, each software calculates the distance differently.

I'm not sure about PyMol but you can change the preference in LigPlot.

As long as you have the specifics from PyMol, input them in the LigPlot's preferences and you should get similar results.

Hope this help all the best.

Bianca Maria thank you!

See method M1.5

10.1016/j.bcab.2021.102270

Please refer this paper

This will help you

You can try, especially if the amount of water that needs to be absorbed is relatively small (as opposed to a reaction that generates water stoichiometrically). However, be prepared for surprises because activated silica catalyzes various reactions and may also interfere with your reaction by preferentially adsorbing an intermediate etc.

From datasheet of respective pin diode you may find the dimensions.

Hi Refik,

Thanks so much for your response, it was really helpful.

Best,

Randy

Hello Lisa Jen

Macrophages are capable of displaying very different and even opposing phenotypes, depending on the microenvironment they are embedded in. Activated macrophages are often classified into M1 (classical-activated macrophages) and M2 (alternative-activated macrophages) phenotype. In general, M1 macrophages foster inflammation response against invading pathogens and tumor cells, whereas M2 macrophages tend to exert an immune suppressive phenotype, favoring tissue repair and tumor progression. These two types of macrophages are distinct in their different markers, metabolic characteristics, and gene expression profiles.

Under normal conditions, naïve M0 macrophages get energy by efficiently employing OXPHOS. Whereas, polarized macrophages (M1 and M2) rely more on their characteristic metabolic signatures for energy prerequisite within the tissue microenvironment.

To uphold dramatic pro-inflammatory functions, M1 macrophages trigger energy expenditure by the magnified aerobic glycolysis and Pentose Phosphate Pathway (PPP) in conjunction with decreased OXPHOS and fatty acid oxidation (FAO). Glycolysis and PPP are fundamental for macrophage functional adjustments and preventing the body from harmful events within an exigent time.

On the other hand, M2 macrophages preferentially utilize FAO and OXPHOS to execute cellular behaviors and activities. Although some evidence demonstrated that FAO is typical for M2 polarization, researchers believe that M2 macrophages retain the same dependence on glycolysis and exhibit modest glucose consumption. Glucose can fuel fatty acid synthesis to support increased FAO in M2 macrophages, linking glycolysis, fatty acid synthesis, and FAO.

What are you referring to, are the TAMs (Tumor-Associated Macrophages). Macrophages infiltrating tumor tissues or populated in the microenvironment of solid tumors are defined as tumor-associated macrophages (TAMs). As a critical component of tumor microenvironment, TAMs affect tumor growth, tumor angiogenesis, immune regulation, metastasis, and chemoresistance. By producing growth factors, proteolytic enzymes, and various inhibitory immune checkpoint proteins in T cells, TAMs display implicated functions in regulating metastasis.

Researches have revealed that TAMs actually have higher glucose uptake and a high level of glycolytic metabolism similar to M1 macrophages to support their cytokine profiles and functions. Simultaneously, lactic acid released by glycolytic cancer cells into the tumor microenvironment also upregulates HIF-1α expression in TAMs responsible for increased glycolysis and M2-like state.

You may want to refer to the articles attached below. They may be helpful.

https://jhoonline.biomedcentral.com/articles/10.1186/s13045-019-0760-3#:~:text=Tumor%2Dassociated%20macrophages%20(TAMs),proteins%20release%20in%20T%20cells.

Best.

There are several possible reasons why you may have obtained a significantly larger hyperpolarizability value for urea compared to the values reported in the literature:

1. Basis set: The choice of basis set can have a significant effect on the calculated hyperpolarizability value. Make sure that you have used a basis set that is appropriate for the size and complexity of the molecule. You may want to try using a larger basis set or a different basis set altogether to see if that affects your results.

2. Method: The choice of computational method can also affect the calculated hyperpolarizability value. Make sure that you have used a method that is appropriate for the level of theory that you are interested in. You may want to try using a different method, such as a different density functional theory (DFT) method or a different post-Hartree-Fock method, to see if that affects your results.

3. Convergence: Ensure that your calculations have converged by checking that the total energy, dipole moment, and other relevant properties have converged with respect to basis set and level of theory. You may need to increase the size of your basis set, increase the level of theory, or adjust other computational parameters to achieve convergence.

4. Experimental conditions: The reported hyperpolarizability values in the literature may have been measured under different experimental conditions than those used in your calculation. Make sure that you have accounted for any differences in experimental conditions, such as the wavelength of the incident radiation.

5. Errors in implementation: It is possible that there may be errors in the implementation of the polar=dcshg keyword or in the Gaussian software itself. You may want to consult the Gaussian documentation, check your input file for errors, or contact the Gaussian support team for assistance.

It is important to note that hyperpolarizability values are highly sensitive to computational parameters and can vary significantly between different methods and basis sets. Therefore, it is recommended to perform a thorough validation of the computational method and basis set before making any conclusions about the accuracy of the calculated hyperpolarizability value.

I got the same problem recently, I always measured around 200 ohm from day 1 to day 15. I performed immunofluorescence, I can see the cell stained by DAPI and ZO-1 expression, however, there are some small holes.

Now, I suspect that the cells are mycoplasma contaminated. I am going to check it soon...

Seismic refraction surveys may have polarity inversions for a variety of reasons. The existence of near-surface layers with low velocity and high attenuation is one of the most frequent reasons. The signal may experience a phase change when a seismic wave passes through these layers, which results in polarity inversion.

Incorrect geophone orientation may also result in polarity inversion in seismic refraction investigations. Geophones may create inverted signals if they are not oriented correctly since they are sensitive to the direction of the incoming wave. For instance, if the geophones are not correctly aligned with the anticipated direction of the oncoming wave, this may occur.

Incorrect wiring or defective amplifiers are only two examples of equipment issues that might result in polarity inversion. Polarity inversion may occur if the geophone signal is improperly amplified or handled.

Finally, mistakes in data processing may potentially result in polarity inversion. There are many approaches to analyse seismic data to enhance the signal quality and eliminate unwanted noise. Polarity inversion, however, may occur if the processing is not done properly.

To handle polarity inversions in seismic refraction surveys, it is critical to thoroughly analyse the data and pinpoint the source of the issue. This might include reorienting the geophones, modifying the equipment settings, or switching data processing techniques. The quality and accuracy of seismic data may be enhanced by appropriately treating polarity inversions, resulting to more trustworthy interpretations and better exploration results.

Depends on whether the bulk polarity or the local polarity is wanted. Reichardt's polarity scale is a measure of local polarity, although it tends to include hydrogen bonding as well, so it's not just polarity. There are other solvatochromic probes that will also give a measure of local polarity. Bulk polarity is best measured by dielectric constant of the mixture using a capacitor.

In one hand using polarizing beam splitter is the best way recombine beams with low losses. On the other hand beams with orthogonal polarisations will NOT interfere. So if you want to do collinear interferometry, you must use non-polarizing beam splitters. Both Michelson and Mach-Zehnder interferometers have 2 outputs. If you have constructive interference in one output, you will have destructive one in the other. Therefore the power split ratio between the outputs depends on the phase difference between your two beams.

It is better to to communicate service engineer.

Dear Bahha Habeeb ,

Both answers are both right and, in a way, wrong as well. It is a matter of a somewhat ‘sloppy’ description. Indeed here https://www.genome.gov/genetics-glossary/Cell-Membrane they state, “The cell membrane consists of a lipid bilayer that is semipermeable.”

A way better description is “The cell membrane consists of a lipid bilayer, made up of two layers of phospholipids with cholesterols (a lipid component) ... The membrane also contains membrane proteins, including integral proteins that span the membrane and serve as membrane transporters, and peripheral proteins …” and (one of the functions is) “The cell membrane controls the movement of substances in and out of cells and organelles, being selectively permeable to ions and organic molecules.” https://en.wikipedia.org/wiki/Cell_membrane

So, a bilayer of (phospho-)lipids is the main ‘principle’ of how the cell membrane is built and this a whole world by itself, see for example https://en.wikipedia.org/wiki/Lipid_bilayer Again, in a way both answers tell a part of the whole story but it is essential to be fully clear where they refer to: either the cell membrane (with proteins included) or a (pure) lipid bilayer.

By the way the world famous “fluid mosaic model” by Singer and Nicolson: Singer, S. J., & Nicolson, G. L. (1972). The Fluid Mosaic Model of the Structure of Cell Membranes: Cell membranes are viewed as two-dimensional solutions of oriented globular proteins and lipids. Science, 175(4023), 720-731 remains useful as basic concept but new experimental findings/phenomena like the asymmetry of the bilayer, lipid rafts etc. reveals that the cell membrane is way more complex, see for example: Bernardino de la Serna, J., Schütz, G. J., Eggeling, C., & Cebecauer, M. (2016). There is no simple model of the plasma membrane organization. Frontiers in cell and developmental biology, 4, 106.

So, the seemingly simply question is way more complicated to answer correctly.

Best regards.

Yes, it is possible to change the polarity of a nanoparticle suspension by adding a surfactant or other polar molecule to the suspension. These molecules can interact with the nanoparticles, altering their surface charges and thus the overall polarity of the suspension.

Without knowing the unique properties of the compounds such as LogP values, pKa, and ionic nature...it is hard to say a spot-on methodology. Since you are targeting the simultaneous extraction of the hydrophobic and polar compounds in a single pot, you may perform SPE (bi-modal or sequential) as sample pretreatment. Protein precipitation plates may also be beneficial at this stage. Extracted compounds should be analyzed by using a mix-mode column or polar embedded RP columns (e.g. aqua-c18) depending upon the molecule characteristic as I indicated above. It is typically hard work to combine two distinct-natured compounds into a single analysis platform. MS must be employed for sensitive analysis and besides chromatography, it is also arduous to adjust the best conditions for each compound.

Definitely, we should know more...We may narrow down the subject if you share some additional information regarding the molecules...

It depends upon the oil composition eg. saturated fatty acid or unsaturated fatty acid. Oil turns rancid upon heating if they have unsaturated fatty acids, resulting aldehydes and ketone and other acids. The extent of rancidity can be measured by Acid Value, Peroxide value, Iodine value and Anisidine value. Refer USP for these estimations.

Vitamin B12 analysis in tablets using HPLC is certainly possible because concentrations are relatively high and the matrix is not compicated. However, determination in food products can be very difficult, because at very low concentrations it is "sticky". Difficult to liberate from the matrix and it also tends to stick to components of your HPLC system (e.g. tubing and column)

I do not know much about the topic, but something tells me it is a space group of a given solid crystalline material.

This problem is caused mainly by cable and instrument. It's usually very diffculty to measure IP respone by an ERT instrument. You may get differeny result if you use an IP instrument. In order to measure a reliable IP response, not only the measuring electrode and the power supply electrode need to be separated, but also the measurement electrode and the power supply electrode need to be connected separately with different cables.

I have done a lot of IP projects in recent years. Since the SSIP instrument I used was separated from the measuring electrode and the power supply electrode, and different cables were used to connect the measurement electrode and the power supply electrode, we successfully obtained the induced electrical response in all projects, and the maximum exploration depth exceeded 1000 meters.Please find one of our result in page 41-43 in the attached files.

Try Raman spectroscopy that can distinguish a few layer graphene and expanded graphite. Even SEM would show you the difference.

Yujie Cao it is the transmittanse of a material for a polarized radiation. I have saw that spectroscopy using polarized light is useful to study the polarization ability of a material. Here additional information:

Polarizer Selection Guide | Edmund Optics

(PDF) Optical rewritable liquid-crystal-alignment technology (researchgate.net)