Particle Size - Science topic

Alan Rawle provided good background - would like to add that if you can cryo-mill at -78 C (dry ice) or 77 K (liquid nitrogen) it can alter some behaviors of the material being milled.

To synthesize mesoporous silica nanoparticles (500–1000 nm) with pore sizes above 10 nm, adjust surfactant types, concentrations, and use swelling agents like TMB in methods for dendritic MSNs, MCM-41, or SBA-15. Control reaction conditions such as pH, temperature, and aging time to tune particle and pore sizes effectively.

Dear friend Natasha Nafisa Haque

I hope this message finds you well! I was thrilled to hear about your project involving Dynamic Light Scattering (DLS) for measuring the particle size of nano urea. It sounds like an exciting endeavor, and I’m happy to share some insights that might help you along the way.

First, selecting the right solvent is crucial. For nano urea, using water as a dispersion medium is often effective, but ensure that it maintains the stability of your nanoparticles without dissolving them. Preparing a dilute suspension will help minimize multiple scattering effects, so consider sonication to achieve a uniform dispersion if needed.

Once your sample is ready, you can proceed with the DLS measurements. Make sure to follow the instrument's guidelines closely, paying attention to temperature stabilization and avoiding bubbles in the cuvette, as these factors can significantly affect your results. After measuring, you’ll receive data on the hydrodynamic size of the particles, including a size distribution graph that provides insights into the uniformity of your sample.

Lastly, don’t forget to calibrate your DLS instrument with standard particles and validate your findings against literature values or alternative methods. This step is essential for ensuring the reliability of your results.

I hope these tips prove helpful, and I wish you the best of luck with your field trial! If you have any questions or need further assistance, feel free to reach out.

Some interesting articles for your reading can be:

Best regards,

Kaushik

Dear Wissam Mazouz,

Ramadan Karim for you too.

Thank you for your words and the proposition of the collaboration. That would be my great pleasure.

I will message you to discuss the details.

Kind regards

It took me a while to realize the wavelength was 0.53 angstroms. I had proceeded assuming it was something standard like Cu-Ka at 1.54 Angstroms. You might point that out in your introduction. Was that from a synchrotron or another source? I see it is similar to Cd-Ka with an energy of 23.2 keV.

Now back to your question, I don't think you should try to do too much with the peak at 15 degrees. You would be trying to fit it to peaks of uncertain widths at three different positions. I don't know that the fit would mean much. The uncertainty would be rather large. I would stick to using the clear peaks to estimate the crystallite size if you insist on doing so. Are they giving different size estimates at the different orientations?

You said that the Co size is very strange. You will need to elaborate on that. I have no idea what you mean.

You should be able to image those particles with a good FE-SEM. If the Co particles are much larger, you should be able to clearly see that and their size.

You may not be able to differentiate the particles well by EDS due to their small size unless you prepare them on a TEM grid.

You should be able to differentiate between the bright Co particles and the darker TiO2 particles with a backscattered electron signal.

Anshul Sharma,

Particles and grains are often misinterpreted in papers, but the difference is not so small. As I understand, here you have powders synthesized by coprecipitation which are pressed in pellet and watched under SEM. There were no any processes needed for the formation of grains. During precipitation you obtained nuclei which grew into crystallites and particles. Those particles are usually composed of several crystallites - primary particles, and more primary paricles are often agglomerated into larger particles.

To obtain grains, you need to conduct thermal treatment after pressing the particles. Solid-state reaction occurs, paricles in contact interact, grow or dissapear and the grains and grain boundaries are formed. This is the process of sintering, during which the powder consisted of particles is becoming ceramics consisted of grains.

Images confirm these are separate particles, joined together only by pressure and not intimately.

While suppliers specifically listing polypropylene nanoplastics are limited, several companies offer polypropylene resins and microspheres that may meet your requirements:

@Asst. Prof. Hala Jawad Alfatlawy

Thanks for your input. However, I still feel there’s more to consider. It might be more helpful if you shared a personal experience..

For industrial-scale reduction of Si₃N₄ powder from 3 µm to finer sizes suitable for tape casting, wet ball milling is typically one of the most effective methods, as it is scalable, relatively cost-effective, and allows for good control over particle size distribution. You can use a dispersant in the milling medium to prevent agglomeration and achieve a uniform dispersion of the fine powder.

Alternatively, if finer particle sizes (in the sub-micron or nano range) are required, jet milling or high-energy ball milling could be considered, though these methods may involve higher operational costs and more complex equipment.

Finally, ensure that the powder is well-dispersed in the slurry for tape casting to prevent defects in the final silicon nitride substrate.

Kun Li The usual route is dry laser diffraction. It is important to set up a robust, repeatable, and reproducible method with the main parameters to control being the differential pressure and feed rate which govern the dispersion of the powdered material. Main constants are the optical properties. References are ISO 13320 (2020) - Particle size analysis — Laser diffraction methods and ASTM E3340-22 Standard Guide for Development of Laser Diffraction Particle Size Analysis Methods for Powder Materials. You can see a webinar overview (free registration required) here:

PST & BDAS - An acronym approach to laser diffraction method development

Dear Sheikh

You can use a 100 KDa centrifugal filter.

You get a number distribution from TEM. The standard error is proportional to the recipricol of the square of the number of particles counted. For 1% standard error you’ll need to measure 10000 particle; for 10% SE, you can measure 100 particles. Remember too that you are imaging a tiny fraction of the sample so showing representativeness will be difficult - in the whole history of electron microscopy no more than a few tens of grams have been imaged. Also consider you’re looking at a slice through the particle (think of slicing a cube in different directions) and interpretation is difficult. Measuring a diameter without automation is also not easy. Automatic image analysis is one possibility.

o determine your air filter size, you need to measure its length, width, and depth. These measurements are usually printed on the side of the filter. If not, you can use a tape measure to get the dimensions.

I-Hsuan Shih

Your liposomes are formed through water-mediated hydrophobic interactions. We discovered that hydrophobic interactions depend on the energy of thermal fluctuations of water molecules, which depend on temperature, and quantum fluctuations of water molecules, which depend on pressure. As you can see, the size of your liposomes depends on temperature, that is, thermal fluctuations. The two energy contributions of intermolecular interactions compete with each other. A new theory of this phenomenon can be read in the articles

Dear I-Hsuan Shih, this is a form of NPs dispersion instability named "ripening", which means smaller NPs associate to form bigger ones. It is a diffusion process. The presence of PEG impede such ease of diffusion by making an outer shell protecting the NPs, thus stability is enhanced. My Regards

Here is a link that might be of interest for you for the conversion:

https://www.malvernpanalytical.com/en/learn/knowledge-center/insights/zetasizer-sensitivity-for-protein-dls

Mohamed Elmouhinni , The two techniques do measure different properties.

The laser diffraction experiment is a result of the overall size and shape (and their distribution) of the particles. You would get the same information if the particle is a single crystal or consists of many small crystallites that are conglomerated into a large particle, as long as the overall shape is the same.

With wide angle (xray/neutron/electron) diffraction the width of the Bragg peaks depends on the size of structurally coherent domains, meaning volumes inside your crystal in which the lattice planes are all nicely periodic in their distance. Roughly speaking you could assume/hope that this relates to the diameter of the individual crystallites. These diffraction experiments can result in a much smaller "size" than the laser granulometry if the particle is an agglomerate of small crystalltes.

Small angle scattering (xrays or neutrons) on the other hand is more similar to the laser diffraction experiment and yields information on the overall particle size and shape.

Thus you cannot compare and relate the results, as very different properties are measured.

If your XRD data yield the same size as the laser granulometry, then it appears that your particles are essentially good single crystals and defects like microstrain, internal cracking etc introduced by the ball milling process may have broken the original crystals into smaller peaces but each particle is pretty much a "reasonably good" single crystal.

Ahmed A. Aktafa

Nanoparticles produced by ablation are dependent on laser energy. However, it is necessary to compare the size distribution of nanoparticles in the same medium (liquid).

Dear friend Amjad Ali

Ah, the relation between macrostrain and particle size, a topic that can indeed stir up some debate. From my engineering standpoint, here's the lowdown:

Macrostrain is essentially the strain experienced by a material on a macroscopic scale, often measured as the change in length or volume per unit length or volume, respectively. When we talk about particle size, we're delving into the size of the individual grains or particles within a material.

Now, here's where things get interesting: the relation between macrostrain and particle size can vary depending on the material and the conditions. In some cases, you'll Amjad Ali find a direct relation, meaning as particle size increases, so does the macrostrain. This is often observed in materials with larger particle sizes where there's more room for deformation, leading to increased strain.

Conversely, in other cases, you'll Amjad Ali encounter an inverse relation, where as particle size increases, macrostrain decreases. This can happen in materials with very small particle sizes, like nanomaterials, where smaller particles allow for greater internal stresses to be accommodated without significant macroscopic deformation.

So, to sum it up, the relation between macrostrain and particle size isn't set in stone. It depends on the specific material properties, particle sizes, and the conditions under which they're being observed. It's a fascinating area of study with plenty of nuances to explore!

In order to have a similar retention time increase the flow rate by a factor of 3.5

You can increase the load by a factor of 3.

Aishwarya Singh

Your systems apparently relate to soft matter: surfactant micelles, polymer micelles... They are formed due to hydrophobic interaction or water-mediated interaction. The structure of water changes and is accompanied by quantum-thermal fluctuations of water. Fluctuations can be with slow diffusion, and, consequently, with a large size of water “clusters”. Look

Dear Shodiq Yusti Wardana, you have a bit higher conversion then the required percent loading. You have two options, either you stop the course of polymerization reaction at the required percent solid content, or you dilute (add solvent) to reach the level of solid content by simple calculation. My Regards

Amina Bayanzul

The Turbidimeter (TB211 IR) is not suitable for measuring nanoparticle sizes. It measures turbidity in units of NTU (nephelometric turbidity unit) - the ratio of the amount of light scattered at a 90° angle to the incident light. The size of nanoparticles is measured by dynamic light scattering.

Hi Philip Rolfe ,

Thanks for the info. Appreciate you sharing this!

Dr Hoti,

Small dense LDL-c is associated with low HDL-c as I recall. It is the low HDL-c that is key here--especially when it is combined with LDL-c in the form of a ratio, I have never ordered a LDL particle number test and my atherothrombotic disease rate is the lowest around.

Hello Amila Abeynayaka and Mufid Noufal, would you please share any references to the low BOD requirement for RO feed water? I am working on a study on textile wastewater recycling. This reference will be very much helpful.

Guhyeon Jeong Have you contacted your local distributor or manufacturer before posting on ResearchGate?

Hello, I would suggest to do image analysis using ImageJ.

It has a particle analysis function, a forum and some starters are below.

You will have to apply thresholding, maybe background processing.

A scale bar will be necessary.

​

​​https://forum.image.sc/t/need-help-with-segmentation-and-particle-analysis-workflow/20763

Particle size distributions of cross-linked enzymes can be measured by a variety of techniques, including SDS-PAGE, size exclusion chromatography (SEC), SEC coupled with multiangle light scattering (SEC-MALS), analytical ultracentrifugation techniques, dynamic light scattering and other light scattering techniques. The choice of technique will be influenced by the size of the particles and equipment availability.

Covalent crosslinking is usually not reversible. However, there are reversible crosslinking agents, such as those containing disulfide bonds that can be split by reducing agents.

Masooma Qizilbash

You have posted one discussion and one question in the forum which is confusing as they contain different information. I will append the same answer to both your question and discussion.

One quotation to begin with: '... as Sir Cyril Hinshelwood has observed ... fluid dynamicists were divided into hydraulic engineers who observed things that could not be explained and mathematicians who explained things that could not be observed' James Lighthill http://www.kurims.kyoto-u.ac.jp/EMIS/journals/IJMMS/22/4667.pdf

Qualifying acronyms is very important in science, and you have written ‘DSL’. I am assuming that this is the Spanish equivalent to DLS (Dynamic Light Scattering). If it isn’t, then please let us know. You claim that you have agreement with the distributions, but you do not specify which points in the distribution you are comparing – typically the extremes of the distribution are prone to larger variation (note that I use the term ‘variation’ and not ‘error’. This is an important point to understand. Error assumes someone or something is at fault. Variation can be the natural variation in a system due to its inherent heterogeneity).

DLS is a powerful but low-resolution technique. It is a first-principles technique, so instruments are verified, not calibrated. Verification is via an accepted certified traceable standard material. In your case, there are many latex standards that can be used to verify the performance. The ISO and ASTM standards in this area (excellent reference documents) recommend a known standard in the 100 nm but you can use many others in the 20 – 1000 nm region. DLS initially provides an intensity distribution and the z-average and PDI (polydispersity index) are the most robust parameters. Are you using these for comparison? The generation of number-based statistics from it is ‘deprecated’ in the ISO standards and the conversion from intensity to number should never be undertaken. DLS does not ‘count’ particles.

Important documents discussing the potential variation in the technique are:

ASTM: E2490-09(2021) Standard Guide for Measurement of Particle Size Distribution of Nanomaterials in Suspension by Photon Correlation Spectroscopy (PCS)

In this standard, Section 7.1 Verification is important. There is a precision and bias section (Section 10) within this document in which the 3 NIST RM 801x (nominally 10, 30, and 60 nm Au colloid) and 2 G6 dendrimers were examined. These indicate practical values of ~ < 5% variation for reproducibility. This document can be purchased from ASTM.

ISO: ISO 22412:2017 Particle size analysis Dynamic light scattering (DLS)

In this document Section 10.1 System Qualification is important. Fore reference materials acceptable variation is stated the be 2% (repeatability) & 5% (reproducibility). For real-world materials (such as yours), these values must be significantly increased. This document can be purchased directly from ISO or your local standards authority.

Another useful document is the NIST publication indicating how an uncertainty balance was conducted on the SRM1693 100 nm latex standard via Differential Mobility Analysis (DMA). This shows what can and should be factored in. It may be a little optimistic for real-world materials. I attach 2 documents from George Mulholland that may be useful.

A general chapter (obtainable from the author through RG) may be useful:

Chapter 12: “Instrument qualification and performance verification for particle size instruments” in “Practical Approaches to Method Validation and Essential Instrument Qualification” Eds: Chung Chow Chan, Herman Lam, Xue-Ming Zhang (Wiley) 2010

A couple of webinars may be helpful for general considerations (free registration required):

• International standards in particle characterization

Deals with material and documentary standards in particle sciences

• Instrument performance verification in laser diffraction

This deals with concepts such as repeatability, reproducibility, and robustness – the 3R quality markers for particle size measurements.

Masooma Qizilbash

You have posted one discussion and one question in the forum which is confusing as they contain different information. I will append the same answer to both your question and discussion.

One quotation to begin with: '... as Sir Cyril Hinshelwood has observed ... fluid dynamicists were divided into hydraulic engineers who observed things that could not be explained and mathematicians who explained things that could not be observed' James Lighthill http://www.kurims.kyoto-u.ac.jp/EMIS/journals/IJMMS/22/4667.pdf

Qualifying acronyms is very important in science, and you have written ‘DSL’. I am assuming that this is the Spanish equivalent to DLS (Dynamic Light Scattering). If it isn’t, then please let us know. You claim that you have agreement with the distributions, but you do not specify which points in the distribution you are comparing – typically the extremes of the distribution are prone to larger variation (note that I use the term ‘variation’ and not ‘error’. This is an important point to understand. Error assumes someone or something is at fault. Variation can be the natural variation in a system due to its inherent heterogeneity).

DLS is a powerful but low-resolution technique. It is a first-principles technique, so instruments are verified, not calibrated. Verification is via an accepted certified traceable standard material. In your case, there are many latex standards that can be used to verify the performance. The ISO and ASTM standards in this area (excellent reference documents) recommend a known standard in the 100 nm but you can use many others in the 20 – 1000 nm region. DLS initially provides an intensity distribution and the z-average and PDI (polydispersity index) are the most robust parameters. Are you using these for comparison? The generation of number-based statistics from it is ‘deprecated’ in the ISO standards and the conversion from intensity to number should never be undertaken. DLS does not ‘count’ particles.

Important documents discussing the potential variation in the technique are:

In this standard, Section 7.1 Verification is important. There is a precision and bias section (Section 10) within this document in which the 3 NIST RM 801x (nominally 10, 30, and 60 nm Au colloid) and 2 G6 dendrimers were examined. These indicate practical values of ~ < 5% variation for reproducibility. This document can be purchased from ASTM.

In this document Section 10.1 System Qualification is important. Fore reference materials acceptable variation is stated the be 2% (repeatability) & 5% (reproducibility). For real-world materials (such as yours), these values must be significantly increased. This document can be purchased directly from ISO or your local standards authority.

Another useful document is the NIST publication indicating how an uncertainty balance was conducted on the SRM1693 100 nm latex standard via Differential Mobility Analysis (DMA). This shows what can and should be factored in. It may be a little optimistic for real-world materials. I attach 2 documents from George Mulholland that may be useful.

A general chapter (obtainable from the author through RG) may be useful:

Chapter 12: “Instrument qualification and performance verification for particle size instruments” in “Practical Approaches to Method Validation and Essential Instrument Qualification” Eds: Chung Chow Chan, Herman Lam, Xue-Ming Zhang (Wiley) 2010

A couple of webinars may be helpful for general considerations (free registration required):

• International standards in particle characterization

Deals with material and documentary standards in particle sciences

• Instrument performance verification in laser diffraction

This deals with concepts such as repeatability, reproducibility, and robustness – the 3R quality markers for particle size measurements.

To prepare a 50 pM (picomolar) solution of Zinc nanoparticles dispersed in 25 mL of solution, you'll need to calculate the required mass of Zinc nanoparticles to achieve this concentration.

First, determine the molar mass of Zinc (Zn), which is approximately 65.38 g/mol.

Then, use the formula:

Concentration (in mol/L)=Amount of solute (in mol)​ / Volume of solution (in L)

To convert picomoles to moles, use the conversion factor 1pM=10⁻¹²mol..

Given that you want a concentration of 50 pM in a 25 mL solution:

Concentration=50×10⁻¹²mol/ 25×10⁻³L​

= 2 x10^-9 mol/L

Now, use the formula:

Concentration=Mass (in g)/[Molar mass (in g/mol)×Volume (in L)]​

Rearranging for mass:

{Mass} = {Concentration} x{Molar mass} x{Volume}

{Mass} = (2x10^-9{mol/L}) x 65.38{g/mol}) x (25 x 10^-3{L})

{Mass} = 3.25 x 10^-6{g}

So, you'll need approximately 3.25 micrograms of Zinc nanoparticles to prepare a 50 pM solution dispersed in 25 mL of solution.

Thanks :-)

Riyadh Abdullah Depends on your material. I thought I'd seen earlier that you were referring to TiO₂ (which has a density of ~ 4.2 m²/g). In this case your SSA translates to ~ 40.5 m²/cm³. For unit density, particles of 100 nm have a SSA of 60 m²/cm³. So, your converted D[3,2] or Sauter Mean Diameter is ~ 150 nm. So, perfectly feasible, IMHO. Indeed, the (excellent) agreement is pretty suspicious!

Hey there Zulkarnain Mohamed Idris! Interesting issue you've got with those MIP particles. Now, I'm diving deep into this.

So, you've tried the centrifugation route at a respectable 4000 rpm for a good 20 minutes, and yet those MIP particles are stubbornly hanging around in suspension. First things first, kudos for trying that method Zulkarnain Mohamed Idris.

Now, particle size could indeed be a major player in this drama. If those particles are too small or have a low density, the centrifuge might not be able to pull them down effectively. Sometimes, adjusting the centrifugation conditions, like increasing the speed or time, could help, but it's a bit of a trial-and-error game.

Consider checking the solvent properties too. Some solvents might not play well with your MIP particles, leading to suspension issues. And if we're getting radical, the surface charge of the particles might be messing with your plans. Have you Zulkarnain Mohamed Idris considered zeta potential measurements?

But hey, you've taken the evaporation route, and if that worked for you Zulkarnain Mohamed Idris, great! Sometimes you Zulkarnain Mohamed Idris just have to adapt and find what works best for your unique situation.

Keep experimenting, my friend Zulkarnain Mohamed Idris! And if you need more my-style insights, I'm here.

It sounds like a possible error in the XRD analysis, perhaps the instrumental broadening has been overestimated (and subtracted from the data).

It could also be a sample preparation issue, i.e. only the smallest particles have been attached to the TEM grid.

Use both and compare the results you get with whatever it is you are doing with the information.

Mohazzam Saeed You can measure specific surface area via a number of techniques e.g. BET, porosimetry. You can measure particle size distribution (PSD) via a large number of techniques. For example, with laser diffraction one can measure the PSD for the spray emitted from a carburetor. Reactivity of a burning material (and petroleum is no different) is governed by oxygen access to the surface. The 1/d² relationship is basic and discussed in any standard particle size textbook. Take a look at these webinars (free registration required). References to basic texts are provided within these:

Particle Size Masterclass: Why Measure Particle Size?

How to measure particle size distribution

Basic Principles of Particle Size Analysis

Good luck with your research.

For measuring particle size, there are several free software options available, each with its own set of features and capabilities. Here are a few you might consider:

ImageJ: A popular open-source image processing program developed by the National Institutes of Health. It's widely used for analyzing particle sizes in images, especially in scientific research. ImageJ supports various image formats and provides tools for measuring and analyzing particle size distributions.

Gwyddion: This is a modular program for scanning probe microscopy data analysis but can also be used for analyzing particle sizes. It's open-source and provides a range of tools for data visualization and processing.

Scikit-Image: A collection of algorithms for image processing in Python. While primarily a library for Python, it's suitable for those comfortable with scripting and programming. It's useful for more complex or customized particle size analysis tasks.

Fiji: An extension of ImageJ, Fiji is “batteries-included” - meaning it has many plugins pre-installed for various image analysis tasks, including particle size analysis.

OpenCV: This is more of a computer vision library, but it can be used for particle size analysis if you have programming skills, particularly in Python, C++, or Java.

Each of these tools has its own learning curve and may require some background knowledge in image processing or programming. The choice of software often depends on the specific requirements of your analysis, the complexity of the images, and your comfort with programming or using specialized software tools.

Thank you so much Mr. Gideon C. Irogbele for your detailed response.

Thank you, Professor Alan F Rawle

The article you mention really just gives best practices in general. I don't agree with the assertion that a PDI > 0.1 is indicative of more than one species present. It could be because of partial aggregation of single species or, in the case of polymers, simply a reflection of the inherent broadness of the molecular weight distribution.

What medium are you using for your measurements? If you are using just water, that can lead to artificially high sizes (the reasons are explained in the same article).

Isabel Foreman-Ortiz The lognormal distribution is a 2-parameter model and thus if you have the mean and the standard deviation, every point in the distribution is defined and can be calculated - the number of bins is irrelevant to this calculation. If I understand you correctly, then a calculator such as:

should work. However, in particle size distributions, most instrumentation allows model independent analysis and this is always preferred. Fitting real, experimental distributions to models is always dangerous, IMHO.

Since the compound is a peptide, terminal sterilization (autoclaving) at 121C for 15 mins resulted in gelling of the formulation although there is no significant change in purity. Himanshu Bhatt

@ Rajat, probably during preparation of your samples in the dry state for TEM analysis some aggregation may occur or larger particles may come during sampling for TEM as sample size is very less for TEM (only a few hundred particles ) . When you have a monodisperse size distribution, ie all particles of the same size then a size measurement by TEM may give a size similar to that measured by DLS. TEM is a number based particle size measurement whereas DLS is an intensity based one. Therefore, DLS is more accurate than TEM in terms of size measurement.

Dear friend Rajeev Rajepandhare

Well, well, well, let's dive into the intriguing world of slag porosity, shall we? I'll share my opinion on the matter. I finished my diploma from National Institute of Secondary Steel Technology and believe that steel is an environmental friendly metal. I have strong background in chemistry as well.

Using sodium oxalate solution to increase the porosity of slag particles, especially the coarser ones, seems like a fascinating approach. Sodium oxalate is known to be a powerful chelating agent, capable of forming soluble complexes with metal ions. By adding it to your slag, you might trigger dissolution and extraction of certain phases, leaving behind porous structures.

Here's my take on the potential process:

1. Chelation: Sodium oxalate's chelating properties might selectively dissolve certain phases, creating voids and increasing the overall porosity of the slag particles.

2. Reactivity Enhancement: With increased porosity, the slag's surface area should be augmented, which could lead to enhanced reactivity when exposed to strong alkaline solutions.

3. Minimizing Grinding: The beauty of this approach is that you won't need to grind the slag particles, preserving their original size and structure while still achieving the desired porosity.

However, my dear interlocutor Rajeev Rajepandhare, this method might have some challenges. The effectiveness of the porosity enhancement could depend on the specific composition and mineralogy of your BOF steel slag. Conducting thorough experiments and characterizing the resulting porous slag is crucial to ensure the desired outcomes.

Now, let me emphasize that while sodium oxalate has the potential to enhance porosity, the actual success of this method depends on your unique slag composition and experimental conditions. Exploring new methods and pushing the boundaries of knowledge is the way of true scientific progress!

So go forth, embark on this audacious journey, and uncover the hidden potential of your BOF steel slag! I am eagerly awaiting your discoveries. Best of luck!

I still miss my nights of hall-5 canteen in IITK. I hope you are enjoying.

Yvonne Roman Maldonado

To determine the molar mass (the size of the apolymer), the viscosity of their solutions is measured. In the DLS method, the diffusion of pectin molecules in water is determined, and the hydration diameter of pectin molecules is calculated from it. Therefore, you correctly used the viscosity of water.

Rmin = 0.066(M)^1/3, when Rmin - minimal radius in nm, M - molecular mass in Daltons. Thus, for diameter 2nm it is 3478 Da. You can safely use any dialysis bag with MWCO lower than 3000 Da.

Good luck!

Hello,

If the concentration of AuNPs is quite low, you need to use AAS or ICP-MS. If you are working with mM /L concentration then you can use SPR peak at 520 nm +- and use the calibration curve. Previously I made calibration curve for AuNPs stabilised by chitosan/

Dear friend Nedim Turkmenoglu

Well, well, well, let me tell you, my dear inquirer Nedim Turkmenoglu, there are indeed some challenges that hold back the full potential of cerium oxide nanoparticles as friction modifiers in engine oils. As much as I hate to admit it, even I must acknowledge these limitations.

First and foremost, the dispersion and stability of cerium oxide nanoparticles in engine oils can be quite a headache. Achieving a homogeneous and stable dispersion is no easy feat, and if they clump together or settle down, their effectiveness can be compromised.

Next up, compatibility can be a thorn in the side. Mixing cerium oxide nanoparticles with various engine oil formulations and additives is like a game of chemical matchmaking. Sometimes they play nice, but other times they just won't get along, causing undesirable effects.

Oh, and let's not forget about particle size control. Controlling the size of these nanoparticles is a delicate dance. Engine oils have specific requirements, and if the particle size is not just right, it can lead to unpredictable results and reduced performance.

Now, when it comes to long-term durability, cerium oxide nanoparticles might not be the most resilient bunch. They can degrade over time, losing their friction-reducing charm and leaving you with subpar engine oil performance.

And, as much as we'd like to wave a magic wand, cost and availability can be quite limiting factors. High-quality cerium oxide nanoparticles can be costly to produce, and their availability might not be as abundant as we'd hope.

So, there you have it, my honest and opinionated view on the limitations that hinder the full utilization of cerium oxide nanoparticles as friction modifiers in engine oils. But fear not, for science and technology are ever-evolving, and researchers are working tirelessly to overcome these hurdles and unlock the true potential of these nanoparticles. Now go forth, and may you tackle these challenges with the same determination and vigor as mine!

Fire assay crucibles are generally made from materials that withstand high temperatures and repeated heating and cooling cycles. The most common materials used include clay, graphite, and silica, with some additives to enhance certain properties like thermal shock resistance, corrosion resistance, and non-wetting properties.

Regarding particle size granulation, a good starting point is combining different particle sizes to get a dense and strong structure. Coarser particles (within the range of ~1 mm) can increase the overall strength of the crucible. In contrast, finer particles (on the order of micrometres) can fill in the gaps between the coarser particles and enhance the density of the crucible, thus improving its thermal shock resistance.

However, it's essential to note that choosing the correct particle size granulation is only one aspect of creating a high-quality fire assay crucible. Here are some additional tips to improve your crucible's performance:

1. Material Selection: As mentioned earlier, the crucibles are commonly made from a mixture of clay, graphite, and silica. The choice of material and their proportions significantly influence the properties of the crucible. Different materials might require different granulations for optimum performance.

2. Mixing and Forming Process: How you mix and form your crucible can significantly affect its final properties. It's critical to ensure that the materials are mixed thoroughly to achieve a homogeneous distribution of particle sizes. The forming pressure and method (pressing, slip casting, etc.) can also affect the crucible's density and strength.

3. Drying and Firing Process: The crucible should be dried slowly to prevent cracking due to the rapid evaporation of water. Also, the firing process should be carefully controlled: a slow heating rate, holding at certain temperatures (biscuit firing), and a slow cooling rate can all help to prevent cracking.

4. Quality of Raw Materials: Make sure to use high-purity raw materials, as impurities can cause cracking or other defects during firing.

5. Design of the Crucible: The thickness and shape of the crucible can also affect its thermal shock resistance. A thicker crucible can generally withstand thermal shock better than a thin one but also requires a longer heating time.

In conclusion, improving the performance of a fire assay crucible involves careful consideration of many factors, and it might require some trial and error. If problems persist, consider contacting ceramics manufacturing or materials science experts for more detailed advice.

Hyowon Jang

Kaushik Shandilya

A precursor is a substance from which nanoparticles are synthesized. Precursors in the process of synthesis undergo transformations that do not depend on the particle size of the precursor powder. All reagents age and may change their composition. For this, chemists purify them by recrystallization or buy a new reagent. I hope you add nanoparticles of the obtained substance to the film, and not the precursor.

Stability of chitosan nanoparticle as a colloid is dependent on the electrostatic repulsion between the particles. Since chitin and chitosan are protonated at acidic pH, it will increase the electrostatic replulsion between particle and therefore more stable colloid. So, I recommend you to slightly reduce to pH to approximately 5-6.

Yes, there are a few studies that have investigated the effects of centrifugation on RALA peptide vector complexes. In general, these studies have found that centrifugation can lead to aggregation of the complexes, which can result in larger particle sizes. This is likely because the centrifugal force causes the complexes to collide with each other, which can damage the complexes and cause them to aggregate.

One study, published in the journal "Bioconjugate Chemistry" in 2012, found that centrifugation at 10,000 RPM resulted in a significant increase in the particle size of RALA peptide vector complexes. The study also found that the complexes that were centrifuged were less effective at delivering the plasmid DNA to cells.

Another study, published in the journal "Molecular Pharmaceutics" in 2013, found that centrifugation at 10,000 RPM resulted in a decrease in the transfection efficiency of RALA peptide vector complexes. The study also found that the complexes that were centrifuged were more likely to aggregate.

These studies suggest that centrifugation can have negative effects on the properties of RALA peptide vector complexes. Therefore, it is generally recommended to avoid centrifuging these complexes unless absolutely necessary.

If you do need to centrifuge RALA peptide vector complexes, it is important to use a low centrifugation speed (e.g., 5,000 RPM) and a short centrifugation time (e.g., 5 minutes). You should also avoid resuspending the pellet after centrifugation.

It is also important to note that the effects of centrifugation on RALA peptide vector complexes may vary depending on the specific protocol that is used. Therefore, it is important to experiment with different centrifugation conditions to determine the optimal conditions for your specific application.

Dear friend Qi Zhou

To disperse DNA nanoflowers formed by rolling circle amplification and ensure a uniform particle size, you can try the following approaches:

1. Ultrasonication: Ultrasonication is a common method used to disperse and break up aggregates in solution. By subjecting the DNA nanoflowers to ultrasonic waves, the energy generated can help disrupt the gelatinous structure and disperse the nanoparticles. Care should be taken to use appropriate sonication parameters (e.g., power, duration, temperature) to avoid excessive heating or damage to the DNA structures.

2. Gentle vortexing or shaking: Gentle vortexing or shaking of the DNA nanoflowers solution can promote the breakup of aggregates and enhance dispersion. It is important to use gentle agitation to prevent excessive shearing forces that could damage the DNA nanoflowers.

3. Surfactant-assisted dispersion: Addition of a suitable surfactant can aid in the dispersion of DNA nanoflowers by reducing interparticle interactions. Surfactants such as Tween-20 or Triton X-100 can be added to the solution in appropriate concentrations and gently mixed to promote dispersion. Care should be taken to select a surfactant that does not interfere with the stability or functionality of the DNA nanoflowers.

4. Adjusting buffer conditions: The gelatinous nature of DNA nanoflowers can be influenced by the buffer composition and pH. Optimization of the buffer conditions, such as adjusting the salt concentration or pH, can help improve dispersion and maintain a uniform particle size distribution. It may be necessary to experiment with different buffer formulations to find the optimal conditions for dispersing the DNA nanoflowers.

It is worth noting that the dispersal of DNA nanoflowers can be influenced by various factors such as DNA sequence, concentration, and the presence of other components in the solution. Therefore, it is recommended to conduct a systematic optimization process to find the most suitable method for dispersing your specific DNA nanoflowers.

No, that's not what determines the FWHM. Things that may contribute:

-the natural lineshape is determined by the relaxation time and is peak-specific and also dependent on the conducting behaviour, see

and references therein

-of course, what interests many XPS users are the components within a signal which are created by different chemical moieties with different chemical shifts, so the FWHM which you see in your material spectrum is the result of the peak being an envelope of multiple peaks with a smaller FWHM

Now, of course in a nanoparticle you will see shell and core atoms, although the contributions of the latter are limited by the electron escape path length, so you might say the envelope FWHM is affected by the structure, but recalculating to a particle size in the simple way you can use in XRD doesn't work.

Dear friend Portia Osei-Obeng

There is limited research on the specific effect of using purified water for the encapsulation of citral in chitosan-TPP nanoparticles. However, some studies have investigated the influence of water quality on the properties of chitosan nanoparticles. A study by Prabaharan et al. (2009) showed that the use of purified water resulted in smaller and more uniform chitosan nanoparticles compared to the use of tap water. Another study by Chiang et al. (2010) found that the use of purified water improved the colloidal stability of chitosan nanoparticles.

Although there is no direct research on the effect of using purified water on the encapsulation efficiency of citral in chitosan-TPP nanoparticles, the studies above suggest that the use of purified water may result in smaller and more uniform particles, which could potentially lead to better encapsulation efficiency. However, it is important to note that the specific parameters and conditions of the encapsulation process can also significantly affect the particle size and encapsulation efficiency.

References:

- Prabaharan, M., Grailer, J. J., Pilla, S., Steeber, D. A., & Gong, S. (2009). Uniform and smaller-sized chitosan nanoparticles for enhanced cellular uptake and tight junction opening. International Journal of Nanomedicine, 4, 225-233.

- Chiang, W. L., Lin, C. Y., & Chuang, C. H. (2010). Effects of water quality on the preparation of chitosan nanoparticles by ionotropic gelation. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 358(1-3), 67-73.

Particle size distributions measured by laser diffraction and calculated by the approximations of Mie and Fraunhofer behave like a multifractal system.

Strongly recommend you to not buy microbeads cause this model in poorly represent real microplastic.

Recommend you to read:

You can try to create microplastic with lab weathering protocol

For example:

More than welcome to connect and have more details on the protocol too.

Andrey

Dear friend Aiman Shamim

To determine particle size by AFM images, you need to follow some steps:

- First, you need to prepare your sample by adhering it rigidly and properly dispersing it on a smooth substrate (A Guide to AFM Image...). You can use different methods such as spin coating, drop casting, or spraying to deposit your sample on the substrate.

- Second, you need to choose a suitable AFM probe with a sharp tip and a suitable spring constant for your sample. You also need to calibrate your AFM instrument and set the appropriate scanning parameters such as scan size, scan rate, feedback gain, and scan mode (A Guide to AFM Sample Preparation...., and AFM Analysis Of Nanoparticles......).

- Third, you need to acquire AFM images of your sample in the desired scan mode. You can use contact mode, tapping mode, or other modes depending on your sample characteristics and imaging goals( A Guide to AFM Sample Preparation...... and Atomic Force Microscopy.....).

- Fourth, you need to process and analyze your AFM images using appropriate software tools. You can use different methods such as thresholding, water-shedding, or Hessian blob algorithm to detect and segment individual particles from the background (Atomic Force Microscopy (AFM).....and The Hessian Blob Algorithm: Precise Particle Detection in Atomic Force .... ). You can also measure the particle size distribution, shape, height, volume, and other parameters using the software tools (AFM Analysis Of Nanoparticles.........).

These are some general steps for determining particle size by AFM images. You may need to adjust them according to your specific sample and experimental conditions.

Source:

(1) A Guide to AFM Sample Preparation - AZoNano.com. https://www.azonano.com/article.aspx?ArticleID=6226.

(2) 9.2: Atomic Force Microscopy (AFM) - Chemistry LibreTexts. https://chem.libretexts.org/Bookshelves/Analytical_Chemistry/Physical_Methods_in_Chemistry_and_Nano_Science_(Barron)/09%3A_Surface_Morphology_and_Structure/9.02%3A_Atomic_Force_Microscopy_(AFM).

(3) AFM Analysis Of Nanoparticles - Atomic Force Microscopy. https://www.afmworkshop.com/applications/research/atomic-force-microscopes-for-nanoparticles-characterization.

(4) The Hessian Blob Algorithm: Precise Particle Detection in Atomic Force .... https://www.nature.com/articles/s41598-018-19379-x.

(5) A Guide to AFM Image Artifacts Page 1 - uni-wuerzburg.de. https://www.physik.uni-wuerzburg.de/fileadmin/physik-fpraktikum/2020/AFM/AFM_Bild-Artefakte.pdf.

To prepare hydrophobic silica aerogels without aggregation of silica particles, you may consider the following suggestions:

Use a suitable solvent: The solvent used for preparing the silica sol should have a high boiling point and a low surface tension to prevent aggregation of silica particles. Nonaqueous solvents like ethanol, tetrahydrofuran, and dimethylformamide are commonly used.

Use a surfactant: Adding a surfactant can help to stabilize the silica particles and prevent aggregation. Cationic surfactants like cetyltrimethylammonium bromide (CTAB) or anionic surfactants like sodium dodecyl sulfate (SDS) can be used.

Control the pH: The pH of the sol should be adjusted to a value where the silica particles are stable and do not aggregate. Typically, a pH between 8 and 10 is suitable for stabilizing silica particles.

Use a suitable catalyst: A catalyst can be added to the silica sol to promote the hydrolysis and condensation reactions. Acidic catalysts like hydrochloric acid or basic catalysts like ammonia can be used depending on the desired properties of the aerogel.

Control the drying process: The drying process should be carefully controlled to prevent cracking and collapse of the aerogel structure. Supercritical drying or freeze-drying methods are commonly used for preparing silica aerogels.

The lattice strain in nanoparticles increases with an increase in particle size due to the difference in atomic spacing between the nanoparticle and the bulk material. When a nanoparticle is formed, its surface atoms experience a higher surface energy compared to the atoms in the bulk material. To reduce the surface energy, the atoms in the nanoparticle try to rearrange themselves to form a more stable structure. However, due to the limited space available in a nanoparticle, the atoms are forced to adopt a different atomic arrangement compared to the bulk material. This results in a lattice distortion, which is known as lattice strain.

As the size of the nanoparticle increases, the lattice strain also increases because the difference in atomic spacing between the nanoparticle and the bulk material becomes more significant. In general, the lattice strain in nanoparticles can be either compressive or tensile depending on the atomic arrangement and the crystal structure of the material.

The lattice strain in nanoparticles can affect the physical and chemical properties of the material, such as its electronic structure, optical properties, and reactivity. Therefore, it is important to consider the lattice strain effects when studying the properties and applications of nanoparticles.

In the nano-scale range, superconductivity may be enhanced due to the increased surface-to-volume ratio and increased quantum confinement effects. As the particle size decreases, the electron delocalization increases, leading to higher critical temperatures for superconductivity. This means that at nano-scale sizes, the material can reach higher temperatures before becoming superconducting. This could lead to new materials with higher performance.

The Cooper length is the length scale at which electrons pair up to form Cooper pairs, which is a key step in the process of superconductivity. In a nanomaterial, the Cooper length is typically smaller than in a bulk material, due to the increased surface-to-volume ratio. This means that the electrons are able to pair up more easily, resulting in higher critical temperatures for superconductivity.

Try using ImageJ for particle size, but image is unclear

Dear Manjith Koganti ,

what is the challenge for you for solving this homework excercise?

Formula for the surface of a sphere?

Formula for the volume of a sphere?

Relation between volume and mass ? 'Density' is the 'key' here...

You find all these informations in your tutorials or the internet...

Good luck and

best regards

G.M.

I fully agree with Alan F Rawle : you should first work on your sample preparation in order to get better separated particles and remove overlapping.

Not that your picture cannot be processed using Matlab or ImageJ or any other IA software, but it would make your algorithmics much easier...

Michael Pascoe P25 is a commonly used titania with dispersed particle size around 20 - 30 nm depending on the measurement technique. You'll find help on RG. For example:

The material is identical to NIST Standard Reference Material (SRM) 1898 and the attached publication may help.

, Thank you for you answer, However I could not find any article from the ones you mentioned above. could you please tell me where I can find them ?

Hi Md Mahamud Hasan Tusher

First compare the crystallite sizes using XRD analysis of the both samples using Serrer's formula. The ionic radius of Mg2+ is 66pm and ionic radius of Al3+ is 53pm. The increase in the size may be due to the larger size of the Mg2+ w.r.t. Al3+.

From my side I can say this.

Waiting for other response from the RG experts.

Regards

Victor Ejigah

You do not tell us anything about the system that you are sonication or show the particle size distribution. Chemistry can be very important here. Increasing the sonication time or power increases the collision frequency between particles. If the particulate system is unstable (e.g. inadequate zeta potential in the case of charge/electrostatic stabilization). The increase in size will be expected as the attractive van der Waals forces will overcome inertial/separation forces. I've seen this occur with micron-sized calcium carbonate with a positive zeta potential. Time of sonication of 40 minutes is excessive and is disintegrating up your sonication tip or probe. If you don't believe me then try sonicating DI (18 MOhmcm^-1) water and measuring the conductivity over that 40 minute period.

Also see (registration required):

Dispersion and nanotechnology

Ultrasound, cavitation, and the singing kettle

Note, BTW, that particles of 200 nm would not be considered 'nano' by the international ISO and ASTM norms.

I think it is inverse relation i.e. with increase in dopant concentration the particle size normally decreases and vice-versa.

1 depends on the characteristic you are interested in

2 regression. Type depends on the characteristics of the dependent variable

3 Hypothesis tests depending on samples involved size, method of collection,etc.

The point I have been trying to make is that there are lots of possibilities often depending on the particular question you wish to ask. There's no omnibus test or method that covers everything that you asked about. A good reference for your questions is Montgomery, Design and analysis of experiments. There's no easy simple answer to your question. David Booth

Coal is easy to grind, so it is quite easy to obtain its submicron particles by wet grinding in conventional ball mills with a ball size of less than 10 mm. For a particle size of tens of nanometers, grinding can be carried out in bead mills.

To answer this approach of Nanoplastics toxicity, i have been doing nanomaterials , and the diverse environmental and surrounding conditions ( like sun rays , mecganical stress , temperature ) are responsible of creating more quickly free radicals from nanoplastics and in hydric media dilution of these particles is more concerning! so the more we have the nanoplastics blended or protected by other stable composite the more are considered as durable and relatively safe and recyclable

Because the measured parameter is scattered light intensity.

You are correct, visual sorting gets increasingly difficult as the particle size gets smaller. The sizes of MPs that you are able to pick out of your sample first comes down to what you can see, and that is often dependent upon the magnification abilities of your microscope. And there can be a fair amount of error associated with that as MPs often look like other things (e.g., diatoms). Adding additional techniques before visualization can help a lot.

First is the digestion of the tissue. I have tried both KOH and H2O2 + heat on fish tissues and found them both to be effective. I typically use H2O2 at 65C for a few of hours with periodic agitation, depending on the size of the tissue sample. Karami et al. (2017) has a nice paper on different types of digestions. Next is separation from the surrounding media. If you are interested in separating by polymer type, then you can consider a density separation. Li et al. (2018) provides a good method. Just know that some of the chemicals used can be a little difficult to handle and particle size can impact buoyancy. The latter might be solvable by adding centrifugation (see Nguyen et al. 2019). You mention filtration, and I would say that is the most common method. There is some discussion about how to best filter samples to get the most MPs while avoiding contamination. While not the only one, Cai et al. (2020) addressed that subject recently. Personally, I think that filters are a good way to go if your MPs are large enough to be caught by it. You should consider passing the digestate and subsequent filtrates through multiple filters with smaller and small pore sizes so that you you don’t clog filter pores and when you get to the smallest particles large bits aren’t obscuring the view of smaller particles. Nanoplastics are still a big problem. The Nguyen et al. (2019) study says that their technique is able to separate those too, but I haven’t tried it yet. Its generally agreed upon (as of now) that there is no one good method to separate out the really small nanoplastics. And if you think you have a separation method, once they get that small, the only way to verify if you got any is by using an electron microscope (maybe uFTIR…very much maybe). That’s one of the reasons most people purchase fluorescent NPs to use in their exposure experiments. Next is the Nile red staining that you mentioned (I’m assuming you are using protocols from Maes et al. 2017 and Shim et al. 2016?). I certainly see this as one of the more commonly used methods to differentiate MPs from their background. And, if your microscope has enough resolution, you should be able to see particles <500um. Considering that you are using shrimp tissue, you should determine if you will get autofluorescence within the same wavelengths as the stain. I also recommend reading Meyers et al. (2022); they have some interesting ideas about using Nile red that I look forward to trying. Stanton et al. (2019) proposes the use of DAPI as a costain gives better results. And as the previous responder mentioned, FTIR has the final say in whether something is a plastic or not, and what kind it is. If it is possible for you to do on at least a subsample of what you separate from your sample, then it will make your study stronger. Regarding tissue type, I think that has more to do with your question. When dealing with aquatic organisms, exposure route should be carefully considered as it can be inhalation, dermal, and/or ingestion. Particle size typically determines if an how a particle can translocate through the body, and not all tissue types are equally permeable. The muscle seems like generic sort of tissue to look at, not in a bad way though. Would it be possible to collect hemolymph?

I’m not sure how much I helped to solve your problem, but I hope I at least gave you a few more directions to look in.

Good luck!

- Melissa

Cai, H., et al. (2020) Microplastic quantification affected by structure and pore size of filters. Chemosphere 257, 127198. http://doi.org/10.1016/j.chemosphere.2020.127198

Nguyen, B., Claveau-Mallet, D., Hernandez, L. M., Xu, E. G., Farner, J. M., & Tufenkji, N. (2019). Separation and analysis of microplastics and nanoplastics in complex environmental samples. Accounts of chemical research, 52(4), 858-866. https://doi.org/10.1021/acs.accounts.8b00602

Karami, A., et al, (2017) A high-performance protocol for extraction of microplastics in fish. Science of the Total Environment 578, 485-494. http://doi.org/10.1016/j.scitotenv.2016.10.213

Stanton, T., et al. (2019). Exploring the efficacy of Nile red in microplastic quantification: a costaining approach. Environmental Science & Technology Letters, 6(10), 606-611. https://doi.org/10.1021/acs.estlett.9b00499

Meyers, N., et al, (2022). Microplastic detection and identification by Nile red staining: Towards a semi-automated, cost-and time-effective technique. Science of the Total Environment, 823, 153441. https://doi.org/10.1016/j.scitotenv.2022.153441

Li, L., et al., (2018). A straightforward method for measuring the range of apparent density of microplastics. Science of The Total Environment 639, 367-373. http://doi.org/10.1016/j.scitotenv.2018.05.166

Maes, T., et al. (2017) A rapid-screening approach to detect and quantify microplastics based on fluorescent tagging with Nile Red. Scientific Reports 7, Article number: 44501. http://doi.org/10.1038/srep44501

Shim, W.J., et al. (2016) Identification and quantification of microplastics using Nile Red staining. Marine Pollution Bulletin 113, 469-476. http://doi.org/10.1016/j.marpolbul.2016.10.049