Workshop: Vapour Sorption Techniques for Fuel Cell Research

Hello everyone and a massive thank you to all of you for joining us here for today's Surface Measurement Systems webinar Organizing coordination with zsw. The title of today's session is Vapor Sorption Techniques for Fuel Cell Research. And we are very, very lucky and grateful to have Dr. Florian Wilhelm from ZSW here to speak on this topic today along with our very own Meishan Gao. So before we go ahead, I just wanted to go through a few housekeeping rules. We do ask that everyone keeps their microphones muted for the duration of the presentations just to avoid any background noise or feedback that could reduce the audio quality of the presentation for anyone else listening. And you can of course also take part in today's presentation through our live Q&As. So at the end of each presentation from each of our two speakers, you will have an opportunity to submit your question in writing through the questions panel, at which point I will ask the speaker your question. Or if you would like to ask the question yourself, we invite you to raise your hand and unmute your microphone and we will let you know. Sorry, raise your hand and we will.

Let you know when you can unmute.

Your microphone to ask the speaker your question. So once again, you can submit the question in writing for me to ask during the presentation through the questions panel or you can raise your hand and I will let you know when you can unmute your microphone to ask the question yourself. Now, before we get onto the main presentations, just to give everyone a grounding of understanding in some of the techniques we'll be discussing, we'll be going now to surface measurement systems to MAS Schmidt are dark cells representative for the dark region. And he'll just give us a quick introduction to surface measurement systems and some of our techniques. Passing over to you Thomas.

Thank you. Thank you, John. So as John said, I would like to give you a small an overview of service measurement system where we are coming from and what we are providing and how we can support you customers. A lot of customers know us, some of you don't know us and I will keep it short. All right. Sorry for the delay. As John said, I'm sales manager for Germany, Switzerland and Austria. So your direct contact in all that region. And yeah, as I said I give you a short, short intro. So about about our our products we have dynamic vapor absorption instruments. We have inverse gas chromatography. It's mainly for surface energy, a surface energy analyzer but can do much more. We have in the program the vapor pressure analyzer for solid vapor pressure measurements and The DVS vacuum system which is more for porous, microporous and mesoporous software. We are doing development of the software in house and at the end we'll have a summary. So Surface Measurement System is really a company expert in vapors option with the DVS and the igc. And our range of instruments helps characterization of materials in very different industry and especially more difficult problem. The pharmaceutical biomaterials, polymers, catalysts, porous materials of course membranes and in that fuel cells, cosmetics and food. So it's a broad range. We are covering worldw and industry and also universities or research institutes. So we have 30 years of experience in that area and we are pioneer in that area. What makes our strength or the strength of surface measurement systems is the application support and the scientific expertise we have. That's on the one hand side. On the other side is dedicated instruments for vapor vapor absorption instrumentation. And yeah, we have all research and development in house. But we are working closely with you all. With customers, customers of industry and customers at university doing also together some publication. So that's important part of our work working together with customers. The company was established by Professor Daryl Williams. So he moved from different university, was born in Australia, went to the us was after the university Australia and is for many years now also at Imperial College. So he's the owner of surface Measurement System. But he has two careers and has the insight of what is research and development at university and industry. He has published a lot of papers, 70 and more papers and has different patents. And it started in 1991. It was. There were no automatic vapor gravimetric vapor absorption instrument of the market. He was asked if he could build such an instruments. That was at this time for Pfizer for pharmaceutical industry who were searching for a gravimetric system which is automatic and which is very sensitive and reliant for the pharmaceutical industry. And yeah, with the year moving on from a range of different DVs. So that stands for gravimetric dynamic vapor absorption instruments for measurement of water vapor absorption. But also organic vapors and gases. As I said, Surface energy analyzer. It's based on the inverse gas chromatography. It allows you the characterization of surface properties. We'll see which one. But also some bulk properties of powders and solid materials can be also films. And we have the vapor pressure analyzer that's typically for measurement of vapor pressure, solid vapor pressure, a liquid vapor pressure over the Knudsen effusion cell which is compliant with the current regulation. And the DVS vacuum for microporous and Basoporous materials here. See in a few words, the range the DVS intrinsics. That's yeah, our small small guy. That's for water vapor absorption between 20 and 40 degree here that would be more for the fuel cells market. The DVS adventure, who covers a broader temperature range 5 to 85 even over 5 to 85 degree for water absorption measurements are the DVS resolution we can do, which can do also organic. And for all that instruments adventure and resolution, you have a choice of options, which is a video microscope, Raman spectroscopy, nir, IR and all that measurement are done in situ during the vapor absorption measurements. We'll see a lot of examples later under DVS vacuum for membranes and porous materials, zeolites, MOFs, etc. DVS endeavor. That's our last system, not the last, but it came last week. But it allows to measure five samples at the same time under exactly the same conditions. Water or organic absorption or both. So mixtures are also possible with some of our systems. So in a few words, what does VVS do? For me, that's just to put some ideas. So it allows to show how the material interacts with moisture or different solvents. It allows you to know more about the stability of the product. For example, if an adsorption is reversible or irreversible, it allows to create moisture absorption isotherms. So what is the uptake in equilibrium of the sample over humidity or vapor pressure range between 0 and 95%. It allows you to say you something about the homogeneity of the sample. An important point is the kinetics. How fast does things happen? How fast is the adsorption? What you need also for diffusion experiments, how strongly moisture or other vapors are bounded to a material allows to identify phase transitions. For example, glass transition in function of.

Humidity.

Iteration and solvate formation drying analysis for the DVS vacuum diffusion, permeation measurements and activation, energy, heat absorption and of course moisture uptake, moisture content, all that value. So here you see the surface energy analyzer. It is based on this GC or inverse gas chromatograph. So what you see on the right side in the instruments, in the middle you have an oven where you get your samples and you put different liquids and organic molecules in that reservoir and also water and organic molecules. And what you're looking about is about the retention time. So you are generating a vapor from the liquids and you measure the retention time when you flow your IG here, your samples. How long does it take for the different organic molecules to get to fid? Flame ionization detector and that retention time is proportional with the surface energy. With the interaction of your material with the different organic molecules. Vapor vapor molecules. What can you do with that? You can measure the non polar dispersive or polar surface energy, the heat absorption. You can see something about the acid base interaction and the acid base ratio on on your surface. You can measure for low surface areas, especially the BT surface area. You can measure some phase transitions, though the GC is very sensitive to measure some some changes on on the surface of of your membrane of your sample. You can measure absorption either terms at low concentration. At higher concentration for polymers it's possible to measure solubility parameters. And finally, with the value of surface energy, you can calculate the work of cohesion and addition. Last but not least is to measure the homogeneity of your surface. And to do that homogeneity or heterogeneity mapping. All that of course is driven with a software. So I would just take the most important points is we have software development in house so it allows to have very comprehensive software, intuitive software. So a software specially designed for that kind of measurements. It's user friendly. That's what we heard from most of our customers and users. This is step by step software. It's reliable over time and it is compatible with latest operating system. And you can do ask for all software data export if you do want to do further analysis. So let's summary. We aim to expand the frontiers of particles, material and surfaces by developing unique methods and instruments. Our customers are in research and development, but also in quality control. And we position us as a leader, as an innovator, presenting new methods and new capabilities for dynamic aption. Yeah, for the support we are supporting you with very experienced support and service Technica. We have a new service engineer in Germany to service you here on site and with the Brexit and development with a pandemic, we will have Shortly also a GmbH in Germany to be able to support you even better on site. So that's what I wanted to say to introduce surface measurement systems. And yes, now we are coming to the main talk from Dr. Wilhelm from ZSV. I thank you for your attention and if you have any question, the stage is open for that.

Thank you to Thomas for that introduction to surface measurement systems. Without further ado, we'll move on to our first full presentation from our guest speaker than Dr. Florian Wilhelm from ZSW. Now we'd like to take a special moment to thank Dr. Wilhelm for taking the time to be here with us today and for helping us organize this workshop and for sharing his findings with us. So he will be exploring the title Water management in PEM fuel cells and characterization of relevant component properties. So just to remind everyone, we will have a Q and A session at the end of the Florian's presentation. So just submit any questions you have in the questions panel or raise your hand at the end and we will let you know when to unmute. So Dr. Wilhelm, I will pass over to you now.

Thank you very much for the kind introduction. I'm going to share my screen in a minute. One moment. So also from my side. Welcome to this workshop and welcome to my talk. Good morning everybody. My name is Florian Wilhelm and I'm going to present you some results on water management in PAM fuel cells and characterization of relevant component properties. What I'm going to do is to introduce in very short few slides PAM fuel cells and the topic of water management. Just that everybody has the same basis to start from and then describe two example applications. One is characterizing wetability properties, the other one is membrane sorption properties with a special focus on PEMFC simulation models, how to use the results there. And finally summary and outlook. But before starting, please allow me two minutes to introduce my employer. That is zsw, an institute working on all fields of renewable energies. And just at a glance. We are a non profit organization of about 300 employees. Our budget is made up of 85% of external funding. External funding meaning here both direct orders from industry and publicly funded projects. So that's a larger share than usually for institutions like ours. We're working on applied research and development on new energy technologies and that's specifically batteries and super capacitors. We are working on materials production technologies, systems qualification. That's fuel cells, as you will hear today. We're working on technology systems, production technologies. We are operating a test center. We are developing stacks, photovoltaics here we're especially working on film thin film technologies and application systems and the field of renewable fuels where we're working on the power to gas technology, biomass gasification. So that's a real broad range of topics all related to renewable energies and I would say all of them hot topics as of today and for our future to go a little bit into detail for hydrogen and fuel cells. What are we doing there? We do research on catalysts and membrane electrode assemblies. As mentioned, we're developing stack technology as tools for this. We are employing modeling and simulation. We're working on stack integration. We are operating a fuel cell test center and fuel cell systems Both for ourselves and customers. We're working on electrolyzers and hydrogen for mobility and we're investigating new energy storage concepts. On the right side you see two logos. One is the hilab, that's laboratory for hydrogen quality we are operating today. This is specifically important for mobility applications because the question how pure does hydrogen need to be to be appropriate for being used in automotive applications? Is quite important one. So that's a laboratory dedicated to that. And the Second one, the HiFab, that's the. Yeah, production technology part of our work. Here we are at the moment, we're building a new building to support industry with introducing production technology related to fuel cells. But now we're coming to the main topic of today. That is what is water management in PAM fuel cells and what can be done to characterize this, to model this, to understand this. First of all, what is a PEM fuel cell? Now I guess for most of you this will be just very familiar, but as I said, to bring everybody to the same basis, I would like to introduce it in short. So starting from the anode over here we have, for example, we have hydrogen gas coming into the cell being distributed via those channels of the so called bipolar plate. Then the gas diffusion layer GDL serves to further distribute these gases from the gdl. Or they are transported through the GDL onto the catalyst layer of the anode side where the hydrogen is split into two protons and two electrons. The protons are transported over the PEM membrane to the cathode catalyst side, whereas the electrons are transported via the outer electric circuit. And here the electrical work can be performed by the fuel cell at the cathode side. Same principle. Oxygen, usually as oxygen in air, is distributed over the cell area via those channels, further distributed by the gas diffusion layer and then transported to the catalyst layer. And at the catalyst layer, the oxygen and the PROT react to water. This reaction takes place again combining the electrons into the molecule. And so the electrical circuit is also closed here. The water is then transported via the gas diffusion layers and the channels to the outlet of the cell. Maybe some abbreviations I'm going to use in the further slides. Bipolar plate is usually called BPP as an abbreviation. Gas diffusion layer is mentioned. GDL membrane electron assembly or CCM catalyst coated membrane are often used for the same layers. This is the three layer mea. Some people also understand the five layer MEA including both GDL layers as an mea, whereas CCM is only used for these three layers in here. So that's the membrane with the two Catalyst layers, that's the, so to say, core component of a fuel cell. Yeah, maybe that for the basic functionality, the components, how do they look like Here you can see a gas diffusion layer on the right side. It is usually made up out of two layers. One is the fiber substrate you can see on top in the SEM picture, and one is the so called microporous layer you can see below the fibers. Microporous layer is actually not completely correct. These are not micropores. They are rather in the range of, let's say 15 nanometers around. That is the maximum of the pore radius distribution. Overall, the thickness of this material is maybe 150 to 200 microns. And it serves to distribute the gases over the complete area of the cells. So even under the ribs of the flow you have sufficient gas supply for direction to take place. And yeah, that's the most important functionality. Of course, transporting the electrons is required, transporting heat. So a lot of functionality in one material. The CCM on the left side, you can see it consists of the three layers as mentioned. Anode catalyst layer, membrane cathode catalyst layer, the stripe you can see in the middle of the membrane, that's a mechanical support. That's state of the art today, that the membrane consists of several layers. As you can see, the sizes here are much smaller. So we are talking about let's say 10 micrometers for the membrane, for example, and also very thin catalyst layers usually. So that's state of the art today. So why is it important and interesting to investigate the water management in a PAM fuel cell? On one hand, if you have no water or not enough water, dry membranes just feature very poor proton conductivity that results in a high proton conductivity resistance. And this means poor cell performance in the end. On the other hand, too much liquid water within the catalyst layer or GDL pores or bipolar plate channels will block the reactant transport. And this will also lead to poor performance. So a well balanced water management is essential for high and stable soil performance. This means that there is a high need to characterize, model and understand the membrane water uptake, for example, and the gas diffusion layer wetability. Just taking two examples, one, so to say from the right side picture, one from the left side picture, what properties are relevant with regards to water management in the respective components of the cell? Okay, so how can we do that? Regarding surface energy and surface heterogeneity, Thomas Schmidt, already introduced to you a very versatile instrument that is the sea surface energy analyzer, which works according to the principle of Inverse gas chromatography. This is a gas phase method and it's called inverse gas chromatography because the solid sample is the stationary phase in this kind of chromatography. So what is usually called the column. This you can see in the two sketches on top of the slide. For standard analytical gas chromatography, the sample is usually in the gas phase and it will be absorbed to the stationary phase, the column, and by different absorption times on the stationary phase, it will be separated into its components. Whereas for inverse gas chromatography we employ a single probe, gas pulse, this will be absorbed on the sample. And what we measure, as Thomas mentioned before, is a single peak with the retention time that belongs to this single probe and to the surface coverage value that we're aiming for with this single injection. So we can probe the interaction with the surface for different polar and non polar solvents and for a range of surface coverage values, practical values, for example, maybe 1 to 25% coverage of the surface, meaning a monomolecular layer which is formed. So not a complete one, but 1 to 25% of such a layer. This can be more, this can be less. Depends on the material and on the practical requirements of the measurement. What we can evaluate is the distribution and expectation values for the dispersive or non polar. Sorry. Here the automated correction apparently changed something which I did not want and the specific, that is Polar portion of the surface energy of total surface energy. Details on this will be shown in the following talk. So you can go deeper into method and theory with the slides that Meijan is going to show to you later. So what we did here, we performed a study on artificially aged GDL samples. We employed state of the art commercial GDL samples which were immersed into 30% of hydrogen peroxide at 90 degrees Celsius for a defined time that was 4 hours, 8 hours and 12 hours. And you can see here just some photos of the apparatus. So in principle, on the top left side, you see how the sample is immersed into the solution and then the vessel is closed and it is integrated into, of course, the monitoring and analysis devices that we need to understand what is exactly going on during the artificial aging. So this is, so to say, going one step back, not employing material directly from fuel cell testing, because there are many, many factors that, yeah, so to say, induce changes in the material that may influence our results. With this, we just have, so to say, the time that is changing in between. And we have a very controlled experiment. What we measured is the CO2 release. So as a measure of what is the amount of material that is, so to say, destroyed by the hydrogen peroxide, or at least affected. And as you can see for the different duration, the first experiment ends here after four hours. The second one here after eight hours, the third one after 12 hours. And of course, we measured as a reference what the sensor is doing. If we do the same measurement just with an empty sample holder. That was our measurement of CO2 for this experiment. And what we did is characterizing the wettability of the sample after the experiment. A very simple method that is the sessile drop measurement of contact angle. You can see an example picture. On the right side, you see a drop sitting on the surface. And this picture is taken by a camera. And then a computer can be used to evaluate the contact angle between the surface and the drop. On the left side, you can see the evolution of the contact angle over the duration of the artificial aging. And this is the substrate side of the gdl. We start with values which are quite common for such material, 150 degrees. And then the artificial aging shows a clear effect. After four hours, we're a little above 135, then going down even to 130 degrees as the lowest value for the contact angle. So there is a change in wettability. The samples become more hydrophilic. Now, okay, you could wonder, that's it, that's the answer. This is what happens. Why do you need any more investigations from now on? Yeah, that's part of the answer. Let's say, of course, this is a nice qualitative tool to see what is happening with the sample. But the first drawback is we can just see the surfaces. So you can measure the same on the MPL surface. This I didn't show you will give very similar behavior. But you just see the surfaces, you don't see the inside, and you have no idea what actually changes. I mean, from the underlying physics, it's clear that something with the surface energies of the sample has to change. But the second influence could be also, of course, some changes in geometry. Just as background information. This contact angle you see here with the Cecil drop method has a strong impact of the surface geometry. So the so called Lotus effect describing the phenomenon that you get much higher contact angles than for pure flat material once you measure on corrugated surfaces also comes into play here. Pure PTFE with a flat surface would have around 113 degrees of contact angle. So 150 and above is much higher than the value for pure ptfe. And PTFE is usually employed as A hydrophobia agent in gdls that shows you that we have a really high impact of the surface roughness of the sample in addition to the surface chemistry. And so it is very interesting to find out what and how the surface chemistry of this sample changed. And for this we employ the technique of inverse gas chromatography. So what is the result we can get from inverse gas chromatography? We can assess the contributions to total surface energy with igc maybe let's start from the right. The specific surface energy. This is the polar or this is due to the polar surface functions. And as you can see, going from the fresh sample, which is shown in Black, to the 4 hour aged sample in red, the 8 hour aged sample in green and the 12 hour aged sample in blue, we have a clear trend. There's an overall increase of the mean value of the specific surface energy and the distribution is shifted to higher energies and broadened. So that's a really clear trend for the polar surface functions. We see that this artificial aging method increases the fraction of polar surface functions. And with this the corresponding surface energy rises the dispersive surface energy in the middle. This is representative for the non polar surface functions. And as you can see, we only see small changes in the expectation value. We can detect a more narrow distribution and the less share of the area by the non polar functions. So that's also some change, even if not that clear, but some change in the non polar surface energy distribution. For total surface energy as composed of both components, of course it increases and the distribution is broadened in the end. So what I wanted to show to you today is that IGC can be used to assess the contributions to total surface energy. Clear overall trends can be observed. We have an increase of the polar component of surface energy. We have a more heterogeneous composition of the surface. Evidently we can expect that this surface will show more hydrophilic behavior. And as you've seen before from the sessile drop measurements, this is what we actually can confirm. Of course it would be nice to calculate the contact angle directly out of these values that we have here of the surface energy. This is a little difficult because the scales used here, what I showed to you is the Van Oss scale. Yeah, they are not perfectly absolute or transferable. So that is still something that we're investigating and we're working on. But as you could see, we are able to gain some valuable additional information on the contributions to surface energy. This is to be continued for different GDL types and of course materials stemming also from fuel cell testing to be compared with those values from artificial aging. Okay, now we are coming to the second component I wanted to focus on today. That is the membrane and here especially the sorption properties and their relation to PEMFC models. For this we're employing dynamic vaporsorption instrument as presented by Thomas before. Now in short, what can it do? It can measure the water uptake of the sample from gas phase employing a sub microgram resolution balance. During the experiment the relative humidity and temperature can be precisely controlled and this makes both dynamical and equilibrium measurements feasible. What I'm going to show you is some examples for equilibrium measurements. But also dynamical measurements are very interesting if we want to gain some information on rates of adsorption and other properties. The details on methods and theory will also be shown in the following talk. So I'm not going to go too deep into detail here, so don't be frightened because now it's going to start with a few formula and this is always the case when you start with modeling. But I'm going to keep this really brief just to show you where for which aspects of modeling do we need results from this technique? So, one characteristic quantity that is commonly used in fuel cell modeling is the water content of the membrane. And this is described as the quantity lambda which is given in moles of water per mole of sulfonic acid group. The water uptake from the water vapor as measured in the DBS can be modeled by a third order polynomial fit for example, and this is a function of the relative humidity as written below. So basically that's just an analytical fit to the experimental behavior. You can also employ different functional forms here. Tangents Hypopolicus is also one of the functions that are employed here for example in literature. So I'm just stating the most commonly used one. And how does this go into the modeling of the membrane? So what I'm showing here is that equation from the full cell model in CFD to be more precise in the ANSYS fuel cell module for ANSYS fluent cfd. And you can see different contributions here in this equation, one is from the electro osmotic DAG drag that's here. So that's the phenomenon that water is transported by the drag caused by the protons which are transported over the membrane or through the membrane. Better then there is a term describing diffusion because we may have concentration difference between the anode and the cathode side of the membrane. And this of course also induces diffusion. These two electro osmotic drag in diffusion usually go to opposite directions. And then we have some source terms, one related to the reaction. This is S lambda in this case, this is the water produced by the reaction. In this specific model by Ansys, this water is directly injected, so to say, into the face dissolved in the membrane. But this can be dealt with in a different way also in other models. So that's not mandatory, so to say, to formulate it like this. But what is mandatory is the source term for the phase change. So that's gas dissolved and liquid dissolved. That is the phase change from going from the gas phase into the dissolved phase in the membrane and going from the liquid phase into the dissolved phase in the membrane. Now you could already see some lambda terms up here, but there is even more dependence on lambda lambda because the electro osmotic direct term ND is usually a function of lambda. The diffusion coefficients is a function of lambda within the membrane and the source terms are also functions of lambda. This means that the whole equation is a highly implicit equation for the water content lambda. Sorry. So this water content lambda is a very important property that we need to describe in a realistic way if our modeling should be successful. Just to show a little bit from the side or the point of view of results why this is important. This is now a current density distribution over typical area of automotive flow field, just showing the active area. And as you can see coming from the right side, where you have the hydrogen inlet and the oxygen outlet, there is a quite low current density and values increase towards the left. And the highest current density values can be seen at the oxygen entry into the flow field or the air entry. So that's result here from modeling that can also be found in experiment. This is mainly dependent on the oxygen depletion over the flow field. But the water balance is also an important influence factor to this, as can be shown here, because the water balance does not follow this linear trend. Here you can see the water content in the membrane, that is this parameter lambda here ranging from values say from 10 to 14. Roughly as you can see in the scale bar here, and as you can easily see in the middle of the cell, we find the highest values of lambda. This corresponds to a relatively high current density and wet gases at a time. Whereas on the right side where the dry anode gas, relatively dry anode gas enters, we see low water content of the membrane. And on the left side as well, we see a lower water content. And now it really depends on the specific design of the cell and the properties of the material whether the current Density has the shape as shown here, so linear decrease, so to say from left to right. Or if it follows a different shape that may be then determined by the membrane properties. Okay, now how is this described in literature? The most well known paper on this was published by Sprenger and colleagues beginning of the 90s of the last century and they measured isotherms of water uptake here shown with reference to the dry membrane mass. This is the direct result of the measurement and what you can see here is the fit of the experimental results they obtained with some third order polynomial as shown before. Sprenger and colleagues employed their measurement setup at 30 degrees Celsius and as mentioned use this Nafion 117, a well known outdated membrane. There is a second publication which is quite often cited for this subject, I.e. hinatsu and colleagues, they measured also the membrane water uptake a few years later employing the same material. And as you can see they obtained at 80 degrees Celsius, much flatter curve. So for the low RH values both curves agree quite well. But for high RH you see some significant deviation between both measurements. Springer and colleagues assumed that their measurement for 30 degrees Celsius would also be valid for 80 degrees Celsius. That is what they write in text of their paper. So maybe that is not perfectly true that you can simply transfer these results, but this is what is quite often used in modeling. Now calculating the water content. So that is lambda as before from the water uptake results in this diagram as shown here. So this is now just calculating the moles of water per mole of sulfonic acid group as defined before. And then the typical fits third order polynomial are shown here. What is the result? The parameters found by the two groups. So these values you can most often find in even today's PEMFC models, at least if you take the standard values offered to you, so to say the generic model. How does it look like if we measure a little bit more recent material at different temperatures? So this is the first task we so to say wanted to perform for us. Is this something that is relevant to measure at different temperatures or is the assumption of Springer valid that you can just use the 30 degrees value for 80 degrees and as you can see here, the 80 degrees curves for another material because we don't have Nafion 117 anymore. So we employed Nafion 112 which is very common still in laboratories today. So it's like 10 years old from point of view of development or more. So this material is thicker than Fuel cell material today, but still often used as a reference. And as you can see there is a real clear difference between 80 degrees and 25 degrees, whereas 65 degrees, so to say an intermediate temperature here the difference between the curves the isotherms measured is not that big. Maybe a second remark, always the desorption curve is slightly above the sorption curve. But this is not a very huge effect. So the hysteresis here is not very big for other material. You may see a lot of hysteresis effects in these typical isotherm curves, but not for these fuel cell membranes, at least not for the ones we measured so far. The reproducibility, as you can see we also showed several measurements is really good. So that is a really reliable method to characterize these materials. Okay, again we tried to fit this to the analytical functions shown before. So third order polynomial and as you can see the fit is really good. We obtain a very high R square values very close to one here for all temperature values. And what one has to say is the fit at 65 degrees Celsius is rather similar to the original parameters of Hinatsu and colleagues. Whereas at 80 degrees Celsius. Yeah, it starts to get a little different throw. Hinatsu also measured at 80 degrees Celsius but with much older material, so older generation of material. One more remark, you can see here that in the beginning, so below 0.1 fraction of relative humidity, so that's 10% the curves disagree somehow the 80 degrees curve goes down very steeply going to 5% of RH. Whereas for the other temperatures we have a shape which is more this s like third order polynomial shape. As this region is not very relevant for fuel cell operation. This does not really affect the validity of the fit for modeling for practical purposes in fusel research. But nevertheless it's interesting to characterize what is happening here and why this different behavior for different temperatures. Okay, so this gives you an overview of the isotherm measured and also from literature. So in red you can see the Nafion 117 as measured by Hinatsu and colleagues at 80 degrees Celsius. In blue the same curve from the springer paper at 30 degrees Celsius. And in comparison to this the curves we measured N1, 112 at 80 degrees Celsius and two other membranes, we call them membrane A and B also measured at 80 degrees Celsius. Membrane A and B are really state of the art as of today. So thin automotive membranes as would be used in automotive fuel cell applications today and as you can see, there are quite some distinct differences for the NAFEON112. Also, our measurements fit, or let's say the curves from literature for the N117 fit the measurement for the N112 at least for the trends and the low RH values quite nicely. For the high RH values, you see some deviation, especially for the Springer case. But going to the more modern membranes, the state of the art material, you can clearly see that the behavior is different. And modeling with the, so to say, old parameters for the N117 will not result in the right quantitative answer that we are aiming at just a few differences between the materials. The N117 and N112 are quite thick, so 170 micrometers of thickness for the 117 roughly and 50 micrometers for the N117.12 membrane A and B, as mentioned, state of the art in fin, so around 10 micrometers of thickness. Okay, so, coming to the summary of my talk, we saw that the IJC is a versatile method to characterize surface energy and the distribution of its components, or polar and non polar contributions to the surface energy. This is important for understanding of processes related to aging. The DVS is an adequate characterization tool for membrane and ionomer properties related to water uptake. As we could see, the generic parameterization of the membrane water content as commonly applied in fuel cell models is not so far from reality. Let's say, maybe better than could be expected if you take into account that these values were measured beginning of the 90s with material which is 17 times thicker than material today. And of course also the chemistry is different. This mechanical support material in the middle of the membrane was not common at this time. So these membranes were really different. And taking into account all this, it's surprising how realistic this description is. But still, for a precise description of the cell water management for state of the art material, it is required to reparametrize the models. And here the DVS results can contribute really a crucial part of this reparametrization. Of course you need further data. You need the membrane equivalent weight. You need, for example, the membrane proton conductivity resistance as a function of the humidity. This needs to be measured with different instruments and different setups. So overall we're developing and maintaining a material database which is to be filled and constantly extended to improve modeling and understanding of the material properties. Finally, acknowledgement, we wish to thank Troop, the German Federal Ministry for Economic affairs and Energy and FCHJU for funding two projects which allowed us to Measure the results or part of the results that we show today. And with that I would like to thank you for your kind attention. If you should have any questions after the talk, please feel free to contact me by email. The email address is written on this slide and with that, yeah, thank you very much and I'm looking forward to your questions.

That was brilliant. Thank you, Dr. Wilhelm. Yes, just to remind everyone, you can submit your questions now in a written format in the questions panel or you can raise your hand and have us come around to you, give you a chance to unmute your microphone. So we have Saman Hossainpour who has already raised their hand to ask a question. So Saman, if you would like to unmute your microphone, I will unmute you from our side and you can ask Florian your question.

Hello.

Thank you.

This is someone from University of Erlangen in Germany. Thank you Florian for nice presentation and giving nice overview. You very nicely showed that there is a distinction between the water uptake at 30 degrees and 80 degrees. And I guess that is kind of obvious, but what is your take on that? What happens from the molecular point of view?

Why is that so?

Is it just because of the higher activity at 80 degree or it is really a structural change in, let's say the naphy membrane?

Well, I would say the highest contribution to this will be given by the higher value of the vapor pressure. As the vapor pressure curve rises steeply between let's say 60 and 80 degrees, you see a very big difference between the values measured at 65 and 80 degrees. So that's probably the main contribution. Further changes in within the membrane, of course there could be also some changes, but. But I would say the major contribution should come from water vapor pressure.

Thanks. And if I may, as a follow up on that, do you think that there is like a gradient within this membrane thickness in the term of the water content or it is uniformly distributed.

Especially at the interface, let's say with.

Electrode or at the surfaces of the membrane. Do we have such gradients? And if yes, is that even important?

Thank you very much for the interesting question. Now I have to split this or the answer to this into two parts. One is the DBS measurement. For the DBS measurement we are really taking care to reach an equilibrium value. That means there should not be any gradients anymore. Basically and especially for the thin material, the 10 micrometers, I would say we can so 10 micrometers orders of magnitude. It's not the exact value, but we can be quite sure that the distribution will be Uniform and really representative for, so to say, the bulk material going to modeling, of course there is a difference. The gradient there will be determined first of all by the fact that we're in a dynamic system. So the equilibrium value is just part of the answer there. One needs to describe also the rates of water uptake and water release. This can also be done, let's say, or it can be calibrated employing inter alia, some values measured with the dbs. But that's the dynamic side, so to say. And the second point is that on the anode and cathode side, or anode and cathode interfaces to the membrane, we will also have different surrounding different boundary conditions, so to say, because the heat is mainly produced on the cathode side, the water is produced on the cathode side, so the RH will be different from the anode side. And of course this induces a gradient of this lambda value over the membrane thickness. And this is exactly what you can see in simulations when you employ a 3D resolved model of the membrane.

Okay, cool. Thank you.

You're welcome.

Thank you very much, Saman. That was a great question. We have another question here from Victoria Servi and she asks how useful did you find the IGC technique and how easy was it to interpret the results?

Well, I would say it's a very useful technique, as I mentioned on my slides. Of course, the final goal would be to be really able to calculate also the values of the contact angle that you could directly insert into modeling and which you could directly use to to feed your models. That is not feasible with the values of the surface energy and this distribution, as I showed today. Nevertheless, to understand what is happening, which contributions to the surface energy are modified by the aging processes for this, the IGC technique delivered really useful and valuable results for us. And as also mentioned, we're working on the correlation to the, so to say, application, especially with regards to contact angle. Maybe if I can state that the surface contact angle measurement with the Cecil Drop method, as I showed it, is one of the most commonly employed ones for these properties for this kind of material. And as I explained, one of the drawbacks of this method is that you always have the combination of the geometry factor, the surface roughness and the surface chemistry. And IGC allows you to separate surface chemistry from the geometry because it is a method working in gas phase. And this is really an important advantage also if you wanted to determine the sorption properties inside the material. If you do this employing sorption techniques from the liquid phase you can do that, for example, with a tensiometer. Again, you have a huge influence of the properties of the pore space, the geometric properties, which is in most cases much larger than the influence by the surface chemistry. And so gas based methods are really promising here and I hope that future research will finally give the correlation to the contact demo.

Thank you. Thank you, Florian. We have another hand raised and I think this is. We have time for one last question, so we'll have to make this our last question before we move on. But this question is hand raised by Edward Nuremberg. So Edward, I have unmuted you from our side if you would like to do the same and ask your question.

Hello.

Hello.

Yes, we can. Yeah, thank you very much.

Edward Nuremberg from CellPT. So you showed the aging tests of the GD GDL. Do you also, is there a procedure to age the membrane and what is the effect on the water uptake after aging if there's such a procedure? Yeah, thank you for this interesting question. Yes, we did experiments on that, for example, by investigating GDLs that were aged in this way with imaging techniques and we could see that they tend to retain water to a much greater extent than fresh material. So the artificial aging at least qualitatively reproduces the effect of the aging in the fuel cell. So that to the last part of your question, coming to the first part of the question. Yes. In the past we also worked with techniques for artificial aging of for example, membrane material that can be done with the so called MERA technique that is in principle a spray technique. You also employ hydrogen peroxide solution, but much lower concentration and you can also get significant aging effect on the membrane. But that was not my work, so I cannot comment on the very, very detailed level here. I hope it answers your question. Thank you very much. Thank you.

Thank you Edu, for your question. Thank you to Florian for taking questions from the audience. So I think we'll now move on just to make sure we have enough time for our last speaker to go through their presentation and so we don't overrun it all. But I'd like to give another massive thank you to Dr. Florian Wilhelm for taking the time to be with us here today. And once again, as he mentioned, I'm sure he'd be happy to take any more questions you have if you want to send them directly to him or to us here at science and servicemeasurementsystems.com we'll make sure he gets them.

Thank you very much. Also from my side for the opportunity to present our Results.

Thank you Florian. So onto our last presentation of today and this is being presented discussed by our very own Meishan Gao from Surface Measurement Systems, our very own application scientist and Meishan will be exploring the topic measuring water vapor flux and diffusion kinetics on proton exchange membranes using the DVS technique. So without further ado, I will hand over to Mei Xian to give her presentation.

Good morning everyone and Mei Shen. Firstly I would like to thank Florin again for the really nice and informative talk about the applications in the film cell. And for my presentation here I will just focus in more of the basic part about the techniques we're using for the characterization of the film cell. So I will first introduce about the two techniques. So the DBS dynamic wave absorption and inverse gas chromatography and I have some case studies really similar to what Florian introduced just now in his presentation. But hopefully I can give some different or further ideas about those kind of characterization based techniques. So the two techniques we are introducing today are both the vapor sorption techniques that we are using molecules as the probe for the characterization of the solid material. So when we talk about the molecules interact with the solids, it will be either absorbed on the surface of the material or absorbed into the bulk of the material. So based on the kinetics of the absorption and desorption, we can easily predict some kind of behavior of this solid material in the bottom here at certain temperatures. So for example the properties related to the surface like surface area, surface energy or the properties related to the bulk such as the diffusion coefficient and the permeability constant permeability parameter. So first let's talk about the dynamic vapors option which is basically a gravimetric method to measure the change of mass for the sample at different concentrations of moisture or organic vapor. So the system is based on a really sensitive balance based resolution of 0.1 microgram. So we just need to use very small amount of the sample for the analysis, typically just around 10-20mg of the sample for depending on the uptake of different samples and compared to the static method. The DBS method has a continuous flow of the probe molecule to the sample constantly in a dynamic mode. So we can achieve a much faster equilibrium compared to the static method. And the experiment can be performed at real world condition at ambient temperature and pressure, which means we can simulate the conditions during the application of the product to get some more practical result for the research and development. And here's just an example with one of our system the DBS resolution which can measure the Sorption of both water and organic vapor as well as the competitive solption of two different components. So in the middle of the system here we have the micro balance. It's connected to both the sample pan and the reference pen. Then we will put the sample of interest into the sample pan here. And as you can see, there are two bottles at the back of the system. So one bottle is for the water and the other bottle for the organic vapors. The carrier gas for the system could be nitrogen or dry air. And the mass flow controllers in the system will control the flow of the carrier gas and the saturated vapor in ratio to get a certain level of relative humidity or pressure pressure. And then this mixture will be detected by the sensor here, the rotronic probe for water and the speed of sound sensor for the organic vapors. And the sensor will make sure the actual generation is matching with the target value we want to generate it. And then this mixture with certain level of concentration will flow to both the sample chamber and the reference chamber at a constant rate. And the sample inside this chamber here will pick up the moisture and the mass change will be recorded by the high sensitivity balance and the whole stent. This one will sit in incubator with the temperature range from 5 to 85 degree. Which means we can perform the experiment within this temperature range with excellent performance on the temperature and humidity stability. And there is also an option that you can add a preheater under the sample chamber at this location that allows you to precondition the sample in situ before the experiment up to 200 degree to remove any kind of moisture content or the contaminant in the original sample. And the system could also be integrated with some other accessories, for example some camera that or some Raman spectra. That means if DVS plus with a video camera we can take the sample images while we running the DBS experiment. So for example, here with the cellulose particular sample that at different humidity stages, as shown in the legend here, 25 degree. We can see a clear fact about the swelling behavior of the sample as well as the shrinking behavior during the desorption step. So the video function is a really useful tool to see any change in the nature or change in the color, for example, along with changing with the humidity. And another option is DBS integrated with Raman spectroscopy that we can take the spectra at the end of each humidity stage when the sample is reaching equilibrium. Then we can get both the DVS data and the Raman data as well as the video sample images at the same time running A full DBS experiment. So for example here with the amorphous lactose sample at 25 degree, we perform the water sorption experiment from 0 to 95% RH with 10% intervals as indicating as the blue line here. So from 0, 10, 20 and 60 and the red line is the change of mass for the sample. So at each stage the sample is picking up, the moisture is reaching equilibrium and then jump to the next stage automatically. And as you can see there is a significant mass decrease at 60% RH here. And this is due to the amorphous to the crystalline phase change because the crystalline state has smaller surface area as well as less object capacity. And this phase change is irreversible one that it doesn't happen in the second stage, second cycle. So the random spectra we taking while we run in this experiment. So at lower humidity range it shows the broad peaks showing the amorphous state. And exactly above 60% RH some new peaks showing up here indicating the crystalline state. So the Raman spectra just confirming with our observation in the DBS Data that at 60% RH the sample will go through a phase change. So this combination setup just give you a full idea about the solid characterization for different kind of materials. And for a typical DBS experiment we will first change the concentration of water or organic vapor inside the chamber. And then the sample inside the chamber will pick up those molecules and the mass change will be recorded. Then we can reach equilibrium at each humidity stage and generating this kind of mass plot for the kinetics information. And if we have the equilibrium mass at each stage and we can plot against the relative humidity, then we can give, then you will give this isotherm plot with both sorption and desorption. And the gap between sorption and desorption is called the hysteresis gap. Also giving some kind of information about the solid behavior. We can also calculate some other properties from the isotherm. For example the BET surface area. If the shape of the isotherm is a typical type 2 or type 4 isotherm. We can also calculate the porosity or the heat of surface from the DBS data as well. But today I'd just like to focus on the diffusion and the permeability measurement with the thin film sample. So to measure the diffusion constant of something film sample, we basically have two different ways of performing the experiment. So we can either put the whole piece of film directly on our sample pen, or we can make a hole in the middle of this film and put it directly on The Honda wire like this one. So in this case both sides of this film sample will be exposed to the vapor molecules. And we can perform this two sided diffusion experiment on the sample. So we can start the experiment from 0% RH and then expose the sample to certain relative humidity. So for example here is 20% RH. So according to the fixed theory and with this equation, we have the thickness of this sample, the film sample as well as the mass at equilibrium state. Then we can do a fitting line for this curve and from the slope of this curve we can get diffusion coefficient of this film sample at certain relative humidity. So it's very easy to marry the diffusion constant with the DBS technique just by setting up the moisture absorption with the step method. So here we have a very simple case study about the fuel cell research is we have three different naftium based film sample. So the same as what Florian introduced before is the 117112. Those two film sample with different thickness are the excluded film sample. And we also have a dispersion cast film sample, the NR112 sample with the same thickness as the N112 sample. So we want to measure the diffusion constant of these samples at different temperatures with the thickness of the film sample ready for the calculation. So the experiment is rather simple. We just did the water absorption from 0 to 90% RH with 30% intervals. And we did two cycles of the experiment on each sample to check the sample history effects. And we perform a series of experiments at 30, 50 and 70 degree to study the temperature effect on this moisture absorption. So here's the moisture absorption kinetics for the 117 sample at 30 degree. The blue line is the target relative humidity at each side. So from 0 to 90 for sorption back to 0 for desorption and then the second cycle and the right line is the change of mass for the sample. So this sample has a very rapid response to the humidity changes. So it can reach a perfect equilibrium at very beginning of changing the humidity and then stay for the equilibrium for another two hours. And then the humidity will change to the next step. And the total water uptake for this sample is quite high. It's more than 10% change in the mass at 90% RH, which means the water molecules are not only on the surface, but also go to the bulk structure of these membrane samples. And the second cycle here just exactly the same as the first cycle. So the same uptake as well as the same kinetics, which means the water sorption desorption is a completely reversible process. So we can get the mass at equilibrium state at each humidity stage and plotting against the target rel humidity. Then we can get this isotherm and with the relationship between the target RH with the change of mass. So here the right and the blue line are for the first cycle and the green and the pink line for the second cycle. So the two cycles are completely overlapping with each other. So there is almost no hysteresis gap between the sorption and desorption isotherm which indicates the watersorption on the same sample is perfectly reversible. And there are no hysteresis effect. There are no sample history effect on all related at all for all the sample related to the watersorption on this NAFN117 sample at 30 degree. So this is just one degree result. And we perform the same experiment at three different temperature, 30, 50 and 70 degree. So the solid line for the soption isotherm and the dashed line for the desorption process. So here the sample shows higher uptake with higher temperature, which is probably due to that higher temperature will increase the molecular mobility within the sample that allow more water molecules to diffuse and absorb into the bulk structure of the film. And the hysteresis gap is also becoming slightly smaller or almost no hysteresis at higher temperature, which also confirms that watersorption is not diffusion limited with increasing temperature. So the next slide is we summarize all three different samples at three different temperature. So 30, 50 and 70 degree. So the blue line for the 112 sample, the green line for the NR 112 sample and the red line for the 117 sample. So at 30 degree the three samples show the greatest differences for the water capacity but this difference becomes less significant with the increasing of the temperatures. So among the two excluded samples, the N112 and N117 sample, the thinner the sample seems to have a better water capacity with the higher water uptake at 90% RH. And as for the sample with the same thickness, the extruded N112 sample has slightly higher water uptake than the dispersion cast NR112 sample at 30°, which suggests the excluded sample may allow improved water diffusion into the bulk. So with the exclusion method and then we also calculated the diffusion constant for the N112 sample at different temperatures. So within the same line for a different temperature, the higher the temperature the larger the diffusion constant which is also due to the increased molecular mobility within the sample at higher temperature and in case of the same column. So at the same temperature the diffusion constant decreases as the starting humidity increases, which is probably due to that higher humidity range. The sample is partially saturated with the water molecules. Therefore the smaller water vapor concentration gradients give less driving force for the diffusion. And this will lead to the lower diffusion coefficient at the same temperature but with increasing of humidity. So this case study just demonstrate the potential of DVs for the characterization of the moisture sorption behavior of the PEM membranes in the film cell. We also have the accessory called Pincel to measure the vapor transmission rate of the membrane with only one side of the membrane exposed to the vapor molecules. So if you're interested, please feel free to contact us after the meeting for the further discussion. And the next technique I'd like to introduce is the inverse gas chromatography. And actually Thomas and Florin already gave a really nice introduction for the theoretical background about idc. So I'm not going in details, I will just focusing on the method as well as the instruments we are using today. So we will pack the sample of interest into the column and what we do is we inject a series of different organic vapors at different concentration to determine different energy sites on the surface. From the retention volume and retention time of this peak, then we can calculate the surface property of the solid compound inside the column. So the procedure of doing an IGC experiment is we first pack the sample of interest into the column. The amount of the sample will depending on the surface of the area for the sample. So for the porous material we just need to use maybe 10 milligram or several 50 milligrams of the sample. But for the low surface area material we might need to use hundreds milligram of the sample or even one gram of the sample. Then we can inject the silatic probe molecules at different concentration. So we have the non polar probes for the dispersive surface energy and we have the specific the polar probe for the specific surface energy. We inject them at different concentration for the heterogeneity surface energy on the surface. And from the detective signal we can calculate those kind of property on the surface. And here's the example with our instrument. So we have totally 12 solvents inside the reservoir here which are injected directly from the gas phase. So it's more accurate to control the very small concentration of the vapor inside the injection. So the carrier gas for the system could be helium or nitrogen. And the blue door in the front is our column oven raised the temperature range from 20 to 150. And we have two positions allow you to put two samples at the same time and you can run the method in sequence. The detector for the system is the FID detector. It's very sensitive for the organic vapors. And we also have the option that you can equip a background humidity controller inside the system that allow you to do the experiment at different humidities to simulate the conditions in the real application. So you will find some interesting results about the humidity effect on the surface property. For example, how the surface property is increasing with the humidity or how the surface energy will changes based increasing of humidity. And apart from our column, we also have the accessory tool especially designed for the film sample that you can place a kind of film directly on this film cell and it can be external connected to the system to mirror the film heterogeneity within just one side exposed to the vapor molecules. And if you can put your films directly in the column, then we more recommend to use the column to perform the experiment. And in this case both side of the film will be exposed to the vapor molecules. And we have a series of different size of the column for different nature of the sample. So for example, we can put our film or the fiber sample in the 4 millimeter column, or we can put some powder sample in the 2 or 3 millimeter column. And the sample preparation for the IGC column is rather simple. You can do just within 5 minutes for sample preparation. And we also have a video on YouTube telling you about how to do the sample preparation. So you can have a look later after the meeting if you're interested. And here are some of the property could be measured with the IGC technique. So for example, we can inject different polar and non polar probe for different components on the surface energy. And from the polar probe we can also calculate the acid base property on the surface, giving some surface chemistry about the solid material. And from the absorption isotherm we can easily calculate the bet surface area of the material with very good reproducibility, especially for some low surface area materials. And if we inject the PRO molecule at different concentrations, then we can get the heterogeneity mapping on the surface with different level of energy size on the surface. And from the surface energy we can also calculate the work of cohesion and adhesion, which are very two important parameters in the multi component system for the quality between different for the affinity between different components in the composite systems. And here I also have a case study about the fuel cell membranes. So this time we have two different PEM samples, the Naft 1135 sample and the BPSH 30 sample. We would like to study the background humidity effect on the surface energies of these samples. So we use a series of non polar probes to determine the dispersive surface energy including hexane, heptane, octane, nonane and dikane. And then we will use a series of polar probes for the specific surface energy. So we use dichromethane, isoacetate, ethanol and acetone, sorry, acetyl. We perform the experiment at 30 degree with the background humidity varying from 10, 50 and 90% RH. So first for the dispersive surface energy results the two membrane samples shows very similar values at 10% RH, but this dispersive surface energy becomes smaller with increasing of background humidity. So at 90% RH the dispersive surface energy of BPSH sample drops almost 30% while the Naphthene sample is probably just about 10% dropping and it's a constantly trend for the decreasing of dispersive surface energy of the BPSH sample which indicating this sample is more humidity dependent. And this is for the dispersive surface energy only counts for the van der Waals interaction with the non polar probes. And as for the specific surface energy it shows an opposite trend. So the values are increasing with increasing humidity which is probably due to the interaction of the polar probe molecules with the water content on the PEM surfaces. So the BPSH membrane is Fairly stable below 50% RH in case of the specific component. So the values for 10% and 50% is almost the same but it has a significant change in the high humidity environment which could be a consideration if you want to apply this kind of membrane at high humidity environment. And we also apply the DBS method to measure the water sorption isotherms for both of the samples. So it shows both sample absorb a significantly more water as the humidity increase. So for example at 90% RH the water uptake for both samples are around 13%. Change in the mass and the relatively high mass increases indicate the water uptake is dominated by the bulk sorption into the structure of the material and coupled with the changes in the surface energy with humidity. So the higher water uptake indicates the membrane properties are greatly affected by the amount of the water present in the material which should be a consideration in the real application for the fuel cell and the water supply. Result indicates the BPSH sample is more hydrophilic than the naphthene sample causing a greater RH Dependence in the surface energy result for the BPSH membrane. And some further work for this study could be that we can measure some other mechanical properties or some even other properties for these membranes that we can try to correlate the surface energy to with the mechanical properties and give some more idea about the research and development for the fuel cell membranes. And we do have some other applications for the battery materials. For example, we have different treatment on the gas diffusion layer and we want to study the humidity effect on the surface energy. And recently we're going to publish another case study about the anode and cathode material in the lithium battery for the temperature effect on the surface energy. And if you're interested we are happy to share those kind of publications or the case studies with you after the meeting. And that's probably all for my presentation. So for summary, DBS and IGC could be used for the characterization in the fuel cell membranes with a really good performance for the reproducibility and study the effect on the temperature and relative humidity. So I hope the presentation is clear for you and thank you very much for listening and let me know if you have any questions. Thank you.

Thank you Moshan for a great talk. Yes, we invite our audience now to take part in our live Q and A. So please submit your questions through the questions panel or raise your hand to have your to have the opportunity to unmute your microphone and ask a question yourself. So we'll give you a few moments to submit any questions you may have for me.

Perhaps I may start. Thank you. Please I'm Thomas Yah from sms Maishan, can you tell us more about the heterogeneity mapping of the igc? What does it tell you?

So basically what we perform in the experiment is we inject those kind of probe molecules at different concentrations so it will give a correlation of the surface energy with the surface coverages so it will be decreasing like a high surface energy site when you inject very small amount of the polar molecules and non polar molecules and then it will occupy all the low energy sites. So here we'll give you different levels of energies on the surface and this heterogeneity mapping this surface energy profile will give you idea about the sample is homogeneous in the nature with all the surface size the same level or heterogeneous with nature with a variation in the energy size on the surface just exactly as the distribution curve in Florence presentation that those kind of peak the wider or the broader the peak that means the sample is more heterogeneous and if It's a very narrow peak or even a straight line. That means the sample is really homogeneous. All the energy site on the surface is the same level. And this heterogeneity will also affect some properties of the sample. For example, the flowability of the material for the powder material, or is the sample is stable with the variation in different energy that will affect the other mechanical performance of the sample as well.

Okay, thank you.

Thank you, Tomas. We'll just give everyone else a minute or two to submit any questions they may have.

So I think, John, perhaps you can open all the. All the microphones. Those who. Who want to switch on the camera, of course, can. Can do it. Or any question either to. To Maishan or to Florian. Sure.

I've been unmuting anyone. So anyone who would like to ask a question can unmute their microphone, or anyone who has a comment in general, can unmute. It doesn't look like we have any questions coming from us, so we're approaching the end of our time, so maybe best to wrap up there.

Yeah. So let's wait for a few questions. So I would like also to thank you, Florian, for the nice presentation and the nice results about the last membranes and that.