Webinar: Surface energy analysis for measuring physicochemical properties of materials

Hello everyone and thank you for joining us for today's webinar with surface measurement systems. The title of today's session is Surface Energy Analysis for Measuring Physicochemical Properties of Materials. Today's session is being delivered by our very own Application Scientist, Dr. Sabiyeh Ahmed. Dr. Ahmed is the Application Scientist for both DBS and IDC SCA at Service Material Systems. She gained her Master's Degree in Pharmaceutical Chemistry at the Queen Mary University of London and her PhD in chemical engineering at the Imperial College of London. After her PhD, she started working for Surface Measurement systems as our application scientist and as mentioned, has worked extensively on both our solution systems, the ITCSEA and our DDS range. Just before we kick off today, I'd like to remind everyone, as well as today's presentation, you will have an opportunity to engage Dr. Sebiyeh in a live Q and A session. So if at any point during today's presentation you have a question for the doctor, please feel free to submit it through the questions panel and we will ask the question directly to the doctor in the live Q and A session at the end of the presentation. Or alternatively, if you have maybe a slightly long question or you would like to ask the question yourself for any other reason, go into a bit more detail with the doctor. Please feel free to raise your hand at the end of the presentation and we will let you know when you can unmute your microphone so that you can ask the question yourself and get your response from Sebiyya. So without further ado, I would like to hand over to Dr. Sabiyeh Ahmed for today's presentation. Thank you everyone.

Thanks John for the introduction. I'm just sharing my screen now, so I hope you all can see it. Lovely, thank you. So in today's presentation, what I'll be discussing is what's called inverse gas chromatography Surface Energy analyzer. So that's igcsea. So I'll be going through a bit of the introduction and what the system looks like and what it does, and then I'll go through a few case studies of some results. So INFOS gas Chromatography was first developed in the 1950s. It used gas phase molecules as a separation technique and in 2009 surface measurement systems developed what's called an sea. This is a surface energy analyzer. This is designed to determine the surface energy and heterogeneity. But alongside this we can also understand other properties of our sample, such as adsorption, isotherms, heat absorption, glass transitions, temperature and a few others which I will go through too. So just comparing with standard analytical gas chromatography, usually in this case, we have a mixture of gas phase probes which we would then inject into a column. And depending on interaction with the column, these would then separate out. And as a result, on the detector end, what you're left with is peaks at different retention times. However, an inverse gas cometography is a little bit different. So what we're doing is packing the column with your sample of interest and then injecting individually a few probes of known properties. On the detector end, we will end up with peaks based on different retention times. And this is a result of the interaction between the probe molecules and the sample of interest. So this is what the typical IGC SCA system looks like. It has two drawers on either side and a drawer in the middle. When you open up each of the drawers, what you'll see is six cases where you put your solvents. These are the reservoirs. So this is where you choose which solvents you wish to use for your experiment. The system comes with either a helium or nitrogen carrier gas. And when you open the door in the middle, what you'll find is where you put your columns. So we have a two position column one and two, and this is surrounded by a column oven. The column oven goes from 20 degrees to 150 degrees. We can also offer a background humidity controller. So in this case, what we're doing is applying humidity on the surface of your sample, then running your experiments. In this case, one of our reservoirs will have to be water. The detector we use is a flame ionization detector and this is really useful for measuring accurate concentrations of organic vapours. We also have some safety features as well. So we have hydrogen leak detectors and organic vapor leak detectors. The hydrogen leak detector is necessary for igniting. Our system is quite versatile in terms of the different types of materials that we can analyze. So at the bottom I have some examples such as cotton, carbon fibre, hairs, granules and even medical metal implants. To prepare a sample for IGC sca. It's very different from the standard GC column. It's much more straightforward. So what we have is some silo lines, glass columns, and what we effectively do is plug in some silanised glass wall. And in this case we then funnel in our sample of interest and close off with some more siloised glass wall. So in this case we don't have any of our material going into the lines of the system. So before starting an experiment, there's a few things you need to do first is to pack a column with the sample of interest, then go ahead and choose some probe molecules. So the most common property measured by IGCSEA is surface energy. In this case, we need a few non polar probes. This gives rise to the dispersive interactions. We also need some polar probes as well. And this gives rise to specific interactions. We can then choose how to inject them. So we can inject them at very small concentrations, infinite dilution or much larger concentrations. We then start our experiment on the software. And depending on the interaction between the probe molecules and the sample, we would obtain different peaks based on different retention times, which we can go ahead and analyze. So the system comes with a variety of different pro molecules. Here we have some standard ones. We have in our system a mixture of some non polar and polar probe molecules. Alternatively, if you wish to add one of your own solvents as well, we just need, it's relatively quite straightforward to calibrate onto the system. You just need a few physical properties and then you're good to go. We also offer another way to analyze samples. So instead of packing a sample in a column, you may have samples that are more planar. In this case we have a film cell. So a film cell looks something like this. And you would place your planar sample in between these panels here, close off your film cell and these lines here, they are directly linked to the IGCSEA where your columns would go inside the door. And your probe molecules would be injected along this panel here. In this case, you need a sample that's big enough to cover this space. And because with this film cell we it would sit beside the idcse. So you may not necessarily have the temperature control, but you will have the humidity control and you will be able to carry out exactly the same experiments. There's two different softwares we have of the system. One is a control software. So in this case, this is where you would manage and create your experiments. After you run your experiments, we can move on to the analysis software. This is where you would have a look at your raw data and your different peaks and analyze those peaks and obtain different properties. So peak analysis is relatively quite straightforward. In this example here, we've injected a few lines nonpolar molecules. We've also injected some methane. So this is to calculate the dead volume. This is as a result of one of our hexane peaks. What you do is simply select the beginning and the end of the peak and click calculate. In this case, as you can see, all these parameters here will start filling up. So analysis is automatic. However, if you did want to kind of export some raw data and do some back calculations, that's also a possibility too. So there's a few things that we can measure with IGCSE 1. The most common one is surface energy. And because we are injecting polar probes, we are able to understand acid base interactions in terms of Ka and kb. We are also able to understand and obtain isotherms. And as a result we can then calculate the BET specific surface area. Other things we can measure work of adhesion and cohesion. And also because we are able to inject multiple concentrations, we are also able to obtain heterogeneity map on the surface of the sample. So like I mentioned before, surface energy is the most common property measured by the IGC technique. And what it is is analogous to the surface tension of liquids. Thus the ability of the surface to react compared to the bulk. And in this case we need dependent on two different probes components. One is a dispersive component and this is in the form of with some N alkanes, this gives rise to long physical long range interactions. We also have need Lewis acid base components. And this is in the form of your polar probes. And this gives rise to chemical short range interactions. So before we start a surface energy experiment, there's a few things we need to know. So one of which is the obesity surface area. So we can calculate the BT surface area using our igcsea. Alternatively, if you do have the value at hand using other methods, we can also just plug in that value too. What we also need to know is the size of our probe molecules. So as I showed before, we have like a nice database of the probe molecules available calibrated in our system, and we also have their physical properties. So these are the two things we need to know. So what we then can go ahead and do is use the software to calculate the amount of moles or percentage of the probes that we need to obtain and achieve a certain coverage of the surface of your sample. Then we can go ahead and start the experiment. And as a result of the interaction between the probe molecule and the sample of interest, you will have different interactions based on the different types of probes probe molecules, and as a result different retention times and volumes, which we can then go ahead and analyze. So surface energy is quite an interesting property because it actually can be related to other properties, one of which is wettability. So increasing surface energy you would also get increase invertibility, you also get an increase of cohesion. This Is how likely the particles are likely to interact with itself. Because we can inject multiple concentrations, we can have an understanding of the heterogeneity or the homogeneity of the surface of the sample. So if you have any defects or surface porosity, we can. It's useful for analyzing these surfaces. We can also calculate work of adhesion. This is two unlike materials that you'd wish to go ahead and calculate the work of adhesion between the two. I'm going to go through a few case studies, one of which is looking at analysis of dmannitol and understanding its heterogeneity. So this, for this example we have D mannitol and we have silanized D mannitol. And this is the resulting plot that we obtain using the IGCSEA system. This is looking at the dispersive surface energy. So this is a result of our non polar probes interacting with the surface of the sample. And on the x axis we have surface coverage, increasing the surface coverage across the sample. There's a few things that we can see here, one of which is that our silanide sample has a much more lower surface energy compared to our untreated D Mannitol. What we can also see is the shape of the profile. For sinolides mannitol we have a very linear profile, and for the untreated demonitol we have quite a curved profile, especially in this region here. So what this is telling us is that at infinite dilution and very small concentrations, the molecules are actually small enough to interact with high energy sites in the sample. And as a result we have a high surface energy for untreated D mannitol. However, when we start to silonize the material, silization has caused these areas to be blocked. In this case, we lose this area of surface energy, and that's why we have a more linear plot in this case. Another way that we can understand the sample is by taking a point by point integration and plotting that. And as a result, we obtain a dispersive surface energy distribution. So looking at the minimum, the maximum and the Gamma D50, what we can interpret from this plot is that the wider the peak width, the more heterogeneous the sample. The more narrower the peak width, the more homogeneous the sample. So you can see that silinization has actually changed the material to something that's very heterogeneous to something that's very homogeneous. We can also relate this to flowability properties. So with the as received D mannitol, what we're looking at seeing Is that we have very unstable flow behavior. In this case we're looking at different air velocities. And at very low air velocities we have very unstable flow here behavior for the amanitol, which we don't see for the cyanised material. And this is due to the higher surface energy correlating to higher work of cohesion. And this can have effects poor effect of flowability. However, as you increase the air velocity, you're actually overcoming this cohesive effect and therefore have a much more stable flow. With the silanized D mannitol, the silinization has actually caused to have a quite constant and quite reliable flowability across the sample. In the next case study, we're looking at some pharmaceutical drugs and excipient. So we're looking at drugs budesonide and salbutamyl sulfate. The excipient we're looking at is alpha lactose monohydrate. We wanted to use the IGCSEA to understand kind of content uniformity of the individual components, the drugs and the lactose. So this is a result of the dispersive surface energy of each of our materials. And what we can see that the budethonnet has a higher squares of surface energy than the other two components. What we can also plot is the work of cohesion and adhesion. In this case we want to understand the affinity between the excipient and the jug molecules. So what we have is if we want to look at the blending for the lactose and budesonide, what we first can look at is the lactose cohesive properties of itself and the budesonage cohesive properties of itself. What we can see when we compare these two is that budesonide has a stronger affinity to interact with itself and this will cause higher aggregation compared to our lactose and lactose. So in this case we would have a weak affinity between the drug and the carrier. We would expect quite poor blending performance. However, when we looked at the lactose and subbutamyl sulfate, we actually see that the work of cohesion for the salbutanol sulfate with itself much lower compared to the lactose and subbutamyl sulfate, which is quite higher. So this again is suggesting that we may have a stronger affinity between the drug and the carrier and much more blending performance with amolactose and subbutamyl sulfate. The next example here is looking at the influence of bleach conditions on some hair samples. In this case, the different hair samples that we're looking at are untreated. Chemically bleached samples, UV treated samples. We've preconditioned the samples for five hours. The experimental temperature was 303 Kelvin. We didn't, we didn't apply any relative humidity and we had a stable flow rate of 10 mil per minute. So in this case, to calculate the dispersive surface energy, we injected alkanes from tridocane to heptidecane. And this we also had a look at from other probe molecules to calculate the free energy with a hexanal probe and a butyl acetate probe as well. So this is the results obtained. And as you can see here, by looking at the dispersive surface energy for the untreated hair sample, we have quite a lower dispersive surface energy. So this is indicating a more homogeneous sample. However, when we start to bleach the hair or treat it with uv, you get quite a higher dispersive surface energy. So this indicates introducing a bit more heterogeneity to the surface of the sample, which is what you would expect if we are treating hair with quite harsh conditions. We can also understand the free energy between the samples and the hexanembutel acetate. And again, what we can see is that we have a smaller interaction with our untreated sample and a high interaction with our bleached and UV treated samples. What's also interesting is that the different types of treatments, so we have bleached and uv. However, what we're seeing is that the interactions and the set energies are actually quite similar. So they actually have quite similar effects to each other. So the next example I'm looking at is going to talk about the characterization of a drug and a PLA material. So that's polylactic acid material. So this was used to characterise 3D printing for drug loaded implants. And we're looking at disulfiram drug and the polylactic acid acid. So polylactic acid is quite useful as it can offer formulation, drug release over a duration of days. And in this case we're looking at two processing conditions. So the PLA plus the drug which has been cooled during formulation and the PLA and the drug which has been non cooled. We want to understand the differences of these two processing conditions. So what we have here is the dispersive surface energy with our increasing of surface coverage of our cooled and non cooled samples. So what we can see first is that we have quite curved profile. This is telling us that our sample is quite heterogeneous. We can also see how similar these two are. So in terms of heterogeneity and dispersiveness of synergy, these are quite two samples are quite similar. This plot looks at the specific surface energy across increasing surface coverage. So in this case what we can see first of all is that it's a lot lower than our dispersive surface energy. So our dispersive surface energy contributes to a much more major part of surface energy. What we can see is that the cooled material has a slightly higher specific surface energy than our non cooled material. What we've also then gone and done is calculate this specific free energy. We've injected dichloromethane, ethyl acetate, chloroform and toluene in this case. And what you can see is in the interaction of our non cooled material and our cooled material with all these probe molecules. So what we can see is that for both samples, the dichloromethane has much more stronger interaction with the samples. And in this case what we can understand from this is that there must be some labile functional groups on the surface of the samples are responsible for a stronger interaction with dichloromethane. What we can then also do is calculate the Ka and KB for the surface of the samples. And what we can see is that the cooled sample, we can see a general trend of smaller Ka and KB Ka compared to kb. And we can see that the cooled sample has higher Kb. We can say that this is more basic in nature than our non cooled sample. It has more electron donating groups on the surface of the sample. So in this next case study we're looking at the surface energy heterogeneity of carbon fibers. In this case we're looking at sized fibres and unsized fibres. We are also looking at the pre treatment conditions at 30 degrees and 120 degrees. So in the IGCSE system we can purge the material prior to any experimental analysis. And this would be the preconditioning step. So we can precondition the samples directly before we start an experiment. And in this case we've appreciated at 30 degrees and 120 degrees. We just want to understand if this makes a difference and if the size and unsized carbon fibers contribute to a difference in surface energy. So this plot is looking at the dispersive surface energy with increasing coverage. So what we can first see here is that our size material compared to unsized material has a lower dispersive surface energy. Our unsized material has a much higher surface energy, especially at this region here. Looking at dilution region, and this is suggesting that small concentrations we're able to access higher energy sites which are only available in the unsized carbon. But once we increase the injections over higher surface coverages, these tend to clatter out. So this is suggesting much that the unsized material are much more heterogeneous compared to our size material. We've also done a point by point integration to obtain the dispersive dispersive surface energy distribution. What we can see is that the wider the peak width, the more heterogeneous and the more narrower the peak, the more homogeneous. In this case, if we have a look at the temperature differences, we can see that once we increase the temperature of our carbon fibers to 120, what this is doing is actually removing any kind of adsorbates or anything blocking high energy sites, exposing these energy sites. When we do our experiment at 30 degrees, this isn't enough energy input onto the surface of samples and cannot remove these adsorbates. And as a result, if you look at these two peaks here, we have a much more wider peak with 120 degrees and a much narrower peak width of 30 degrees. We can also have a look at the effects of surface treatment. So an oxidized sample, oxidized and sized with epoxy agents and comparing it to an unoxidised and unsized material, and this is the resulting KA and KB plots. So what you can see is due to oxidation we have a higher KA for our material. And this is of course what you would expect compared to our reference material. And our reference material has a much higher kb, more electron donating groups on this sample here. We can also see the effects of different types of oxidation as well. So the final case study that I'm going to go through is looking at the interaction with a polymer matrix. So in this case, what we have is carbon nanotubes. So we have as received carbon nanotubes. We have carbon nanotubes oxidized with carboxylic acid functional groups. We also have some nanoclay has received nanoclay and nanoclay functionalize with isocyanate groups. We also have our polymer matrix. So this is polyurethane matrix. So this is looking at the total surface energy of each of our components. And what we can see is that we have a higher total surface energy of our as received nanoclay and our carbon nanotubes with carboxylic acid groups. So this can give an indication of these two samples having a higher particle particle interaction and this is quite important because once we start to blend into the polyurethane matrix and give an indication of these two materials having a much more poorer dispersion into the polyurethane matrix due to this higher total surface energy contribution, we've also calculated the work of adhesion and cohesion and calculated the adhesion cohesion ratio. So in this case it's good indication of the balance of forces between the adhesion and forces of cohesion. And this is quite important in formulation studies because if you have too weak or too strong particle particle interactions, this can either lead to like segregation or aggregation of the material. And this can lead to maybe poor dispersion into the polymer matrix. So it can be used as a formulation tool prior to making any final products. And we can develop and optimize the work of adhesion and cohesion ratio. We've also coupled this with another technique to understand the mechanical performance. And it's showing that with the higher work of cohesion we have higher tensile strength. So it's very useful to correlate the data from the surface energy to work of adhesion and cohesion to other mechanical properties. So just to summarize, the surface Energy analyzer is a very versatile technique, can be used to understand several different properties of your sample. It's a vapour absorption technique and we can characterize a variety of materials such as powders, fibers, films, and we can also understand subtle differences in surface chemistry and use it as a formulation tool as well. So I hope this has been useful for you and if you do have any questions, I'm happy to answer them.

Thank you very much. Sebea. Yes, just a reminder to our audience, you can submit your questions through the questions panel or if you would like to unmute your MIC and ask the question yourself, please raise your hand and we'll pass it to you. Time to ask. So just the first question here, someone asks, is it possible to use some other solvents with the ICC system, apart from the ones in the solvent database list, for example, some fragments like Alpha P9?

Yes, we can do that. So with the SCA, apart from the list that I've shown, to accommodate any other solvent, really you would need to fill out a few of these properties here. So molecular weight and liquid density, if you have the Gutman exception number and donor number as well available, will be very useful. We have calibrated some fragrance molecules into our system and the calibration is relatively quite straightforward if you have the known properties at hand.

Great question from Michelle Padrigi. They ask how much is this technique sensitive to the differences in column packing.

So with regards to column packing we do have on our control software a pressure drop. So if you, if you do are packing the sample quite tightly before the experiment, you would be able to see that when once you put the column into the column position, it will then flow through the carrier gas and you'll give an indication if the pressure is okay. Or if you do need to maybe use a slightly larger column or separate out the sample within your column. And if you do choose to separate out the sample, we have done some column to column reproducibility studies and it doesn't affect the results. If you do use maybe some silanised, maybe some silanised glass wall in between to adjust the pressure. So we have done some column to column studies and this doesn't affect the results.

Great, thank you. A question here from Ocean Gao. They ask how much sample should you be using for an ITC experiment?

So the sample is typically based on the BT surface area of your material. So if you have quite a low surface area material, about 1 meter squared per gram, you may need about 5, 600 milligrams of your sample. However, if you have a sample which has a slightly higher beauty surface area, so about 100 meters squared per gram would need roughly about 10 milligrams. So it does depend on the rough estimate of the beauty surface area.

Great. Another question we have here is what is this? What are the mass requirements?

Sorry John, we were breaking up there, couldn't hear you.

Apologies. The question is what are the mass requirements for sample analysis?

Yeah, so similar to what I said before, it does depend on the BT surface area of your sample. You need more mass for a low surface area sample and high mass or.

A.

A high mass for. Sorry, a high mass for a low surface area sample and a low mass for a high surface area sample.

Great, thank you. We did have a Jack Nottingham, he lowered his hand so might be we addressed what he was going to ask already. But while I ask another question. Jack, if you would like to ask a question, please raise your hand again and go to after this.

Next.

So before that our next question is how does this technique pair with other techniques that measure surface entropy? For example the contact angle technique.

So with regards to contact angle you can compare the surface energy results as long as you're using the same types of probes. So the same polar probes and non polar probes. However, with the contact angle experiment you're kind of limited to the probe molecules and Also, you're only looking at localized areas of the surface of your sample. Whereas with the IGCSCA we can actually inject different percentages across the surface of your sample. So we are able to look at the whole sample rather than small localized areas. So it's much more representative of how energetically stable the surface energy is on your sample compared to contact angle.

Great. A question here from Claudia and they may have. We may have covered this before, but I think this goes into a bit more detail. So we've covered before that the sensitive to column packing differences. But this question asks, does the packing density pressure drop along the column influence the results? Can you correct for it or is it necessary to achieve a certain pressure drop when preparing the column?

Sure. So when preparing the column, once you prepare the column and you place it into the column position before running your experiment, the system will run a constant flow of your carrier gas. And if you do see quite a large pressure drop around 800 torr, then the system will you have a message on your system telling you that you need to pack the sample more loosely. So in this case a few ways to overcome this. We have different column sizes. We have 2, 3, 4 and a 10 millimeter column. You can increase the column size. Alternatively, if you have quite already a quite high larger column size, what you can do is insert some silanised glass for between your sample packing. So this will reduce the pressure and because it is silanized glassware, it doesn't interact with any of your experiments. And then we have a nice separation between your sample and yet. So once you do run your experiments, we've done some studies from column to column reproducibility studies and we haven't seen any difference in the results. Okay, great.

And I think we have time for a question here. Jack Nottingham has kindly typed his question in. Now just an advanced apology if I don't get this question right because I am not quite most of the people listening to this. So you need to read this yourself as well. After relatively severe how do you get dispersive Gibbs free energy from the retention time and peak area? I assume you are calculating Gibbs free energy from the surface tension using DJ equals yda, which is surface energy.

Surface tension?

Yes, surface and surface tension, which assumes the adsorbent is forming a thin film. Can you elaborate on how energy is calculated?

So with the dispersive surface energy we inject different non polar probe molecules. And in this case we have we create a linear plot. If I go down to this slide here, we have an RTL and V plot and based on this linear plot we are able to calculate the surface energy and regards to delta G of the specific probe molecules. We take this linear plot and we plot the delta G based on relative points along this plot here. So that's the way that we calculate the dispersive surface energy as well as the Gibbs free energy. If it's useful as well, we can also send you a nice PDF of how we go into detail on the equations that we use to go ahead and calculate as well.

Thank you Sabiyeh. I think that's all the questions today and that takes us quite neatly up to the end of our time. So thank you once again so much for giving this presentation, sharing those insights with our audience. Do you have any final thoughts before we go? Doesn't sound like it. So that brings us to the end of today. So again, a big thank you to all of our attendees and another big thank you to Sophia for being here today to share her insights with us. So thank you all for joining us today. We do have a full range of events being posted on our website later this week, so we invite you to check backsystems.com later this week to see more of the virtual webinars and workshops we have coming up in the next month or so. So thank you all once again for joining us. I hope that wherever you are, you have a wonderful morning, evening or night. Thank you.

Thank you. Sa Sam.