Clay Characterization & Water Vapor Sorption—Moving Beyond Atterberg Limits

Dr. Bill Likos shows why vapor sorption is superior to conventional methods for quantifying clay properties.

This webinar summarizes recent research related to geotechnical characterization of clays and clayey soils using measurements of water vapor sorption behavior. Dr. Likos evaluates testing equipment for determining water vapor sorption isotherms.  He also illustrates applications of sorption measurements toward understanding interlayer swelling behavior, classifying expansive clays, and estimating fundamental surface properties such as specific surface area (SSA) and cation exchange capacity (CEC). Dr. Likos advocates sorption-based soil characterization as an alternative to conventional clay characterization approaches commonly used in geotechnical engineering practice such as Atterberg limits. Sorption-based clay characterization is more firmly rooted in fundamental clay compositional properties and relies on measurement techniques that are potentially more systematic, economical, and readily automated.

Topics covered:

  • Fundamentals of mineral-water interactions
  • Techniques for measuring water vapor sorption isotherms
  • Connections between sorption isotherms and clay properties
  • Characterizing specific surface area and cation exchange capacity

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Our scientists have decades of experience helping researchers and growers measure the soil-plant-atmosphere continuum.


Dr. Bill Likos, Professor in the Department of Civil and Environmental Engineering and Chair of the Geological Engineering Program at University of Wisconsin, has been mining the high-resolution isotherms generated by METER’s Vapor Sorption Analyzer (VSA) to revolutionize clay soil characterization.


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Hello everyone, my name is Bill Likos, I’m faculty in the Department of Civil Environmental Engineering at the University of Wisconsin in Madison. And I’m chair of the geological engineering program there. My background is in engineering. And so this seminar is going to be coming at clay characterization kind of from an engineering context. And one of the things that I’ll be advocating is that, you know, currently used methods for classifying particularly fine grained soils really don’t get at fundamental clay properties that really control engineering behavior of clay, things like cation exchange capacity and surface area. And so what we’re advocating here are using water vapor sorption as an alternative way to characterize in particular clay materials. And so we’ll get into that as we move forward.

One of the primary applications for you know why one might want to classify soil or in particular clays has to do with expansive clays. And so I wanted to spend just a little bit of time looking at these images here. This map in the upper left here is a map of essentially plasticity. And so the color bar here, these red areas indicate areas of high plasticity clays, whereas the brown areas indicate, you know, less occurrence of high plasticity clays. And so you can see, you know, these major deposits of what is essentially pure smectite clays up in the Dakotas, Wyoming area, some deposits in Texas, Louisiana. And so these are areas where there’s been significant damage to engineering infrastructure that’s founded on these materials. And so, of course, this is an engineering problem, this is something that we’re very interested in mitigating and part of that expansive soil mitigation problem is identifying where expansive clays are present, identifying the severity of swelling potential. And so the traditional ways of doing this again, one of the things that I’m trying to advocate here don’t necessarily get at you know the fundamental properties of clay that caused them to be expansive.

Just a few more photos, this one in the lower left here is a photo from Louisiana that you can see this very large crack occurring in this longitudinal fashion along a roadway here. This is a fairly common looking distressed pattern for a pavement system founded on expansive clays and it develops for very specific reason. You can imagine that when we put an impervious barrier over clay, really what happens is the underlying soil wets up with time. And so we have you know, relatively constant moisture condition under the centerline of this pavement, but near the edges that are exposed to the atmosphere, that soil experiences fluctuations, wetting and drying. And so you can imagine that if that’s an expansive clay that swells when the soil wets up and shrinks when it dries out, there’s gonna be movement, cyclical movement of that material, that’s really focused near the the edge of this pavement, and that’s what leads to this longitudinal cracking is that pavement heaves and then settles back down, heaves and settles back down. And you know, this crack changes the moisture infiltration boundary conditions and so, this is a problem that precedes with time. Moving to the upper right here, this is an image from the front range of the Colorado Rockies in here somewhere outside Denver, the expansive clay problem there is very interesting from a geologic engineering standpoint. The formations there particularly right along the front range are steeply dipping. So these are sedimentary layers that have been upturned to near vertical. This is an example of an upturned highly expansive bentonite layer that has weathered from volcanic ash. And so the interesting problem here is that, you know, this is a fairly, very highly expansive layer that is sandwiched between, you know, moderately to low, expansive layers. And so, this layer is probably only eight to 20 centimeters wide, so very, very small, the, you know, the footprint of a house, or certainly a road would span that area. And this leads to differential movements. If this system were to wet up, for example, that the heave experienced by the structure overlying these multiple deposits, each with a different swelling potential, the heat would be very differential. Portions of the house, for example, would move a lot more than other portions of the house that are founded on less expansive material. And it’s that differential movement that’s really disruptive to overlying structures. And so again, we would be very interested in classifying you know how expansive this material is. We can’t come up with a mitigation plan until we know what we’re dealing with. And so this presentation is about classifying materials like this.

A few other photos, this is a photo of a house, also in the Colorado Front Range area that experienced very severe distress from underlying expansive clays, a little bit hard to see, but particularly over this, within this garage area, which is very lightly loaded. I mean, there’s probably just a four to six inch concrete slab overlying the natural material. So it’s these lightly loaded structures, things like you know, small storey houses, pavements that really experienced the most damage because there’s not enough downforce to resist the upward heaving that’s occurring. And then finally, this photo in the lower right, is a fairly typical distress pattern in an area that’s underlined by the steeply dipping layers as we were talking about earlier. And so you know, these heave features along this roadway here really look like speed bumps, and you know, these correspond to underlying thin beds that have been upturned to a steeply dipping angle that are causing this very severe differential movement. So again, how do we classify these materials? A few thoughts on expansive soil class characterization from the literature, and the point here, as you read these is that there’s really not a standard way to do this. A lot of what’s done in practice is very much based on empiricism. There’s not really a standard approach for identifying expansive clays, for trying to quantify how much expansive clays might heave. And so it’s very much a part of engineering that is very much uncertain. And so I wanted to share a few of these quotes that you can read on your own to really communicate the fact that there’s not one way to do this. Another important thing to communicate is a very subtle difference between what we might refer to as swelling potential and potential swell. And so here, swelling potential is really the classification component of you know, mitigating something like an expansive clay. And so swelling potential is a qualitative descriptor, something like low, moderate, higher, or very high, that’s really a classification. It’s not a quantification of how much heave we might get under certain conditions. So swelling potential, we typically will use tools like Atterberg limits, which I’ll describe in a moment here. Percent clay which we might measure from hydrometer analysis, activity, which is really a combination of Atterberg limits and percent clay, and there are a few approaches that we can use to classify expansive soils using soil suction. Potential swell on the other hand is a quantitative measurement of you know, how much either pressure or volume change we might expect under certain environmental conditions, certain confining conditions, certain moisture conditions, and so here we use direct measurements. This is an image of a typical looking one dimensional swell test where we would take an undisturbed sample of clay that we probably had identified as potentially expansive using you know, an initial qualitative screening approach and then would measure how much the specimen heaves, usually just by fully inundating it with water, either measuring how much volume change we get under free swell or perhaps how much pressure is required to maintain zero volume change conditions. So this we might call a potential swell classification or quantification, whereas something here is a very common approach right here that’s summarized in this table to classify an expansive soil based on plasticity index.

So again, a qualitative descriptor ranging from something like low to very high. And so again, what this talk is about today is you know, rather than using tools like plasticity index or Atterberg limits, let’s advocate using approaches or clay properties that are more fundamentally related to why they’re expansive. Things like mineralogy, things like surface area, things like having exchange capacity. And so we’re working on using water vapor absorption isotherms to quantify these things. The purpose of soil classification, I’ve touched on this already, again in engineering practice, we use things like grain size distribution, and Atterberg limits.

Grain size distribution is often enough to classify coarse grain materials like sands or gravels or aggregate that we might use in a structural fill application. With that information, you know, we actually can generate a language. You know, we can take the output from index tests like this, and classify perhaps using a unified soil classification system, which I’ll describe here to actually say for example that we have a high plasticity clay or a silty sand or something like that. So these indices or these measurements become input into a system that we can use to generate a language. Once we have the soil classified, we can, you know, empirically, or you know, using accumulated experience have some idea of how that soil is going to behave or how that particular class of soil might behave, and estimate engineering properties to achieve engineering purposes. And of course, there’s gonna be direct measurements of engineering properties along the way, shear strength, hydraulic conductivity, but we can use soil classification as a starting point to, you know, to anticipate a range of engineering properties that we might actually measure.

There are a number of different classification systems of course, and so I’m summarizing three of them here. This textural triangle triangle here in the upper right is really the basis of the USDA classification system based on grain size percent clay, percent silt, percent sand. Two of the more engineering oriented classification systems, one of them is the AASHTO system. AASHTO is responsible for specifications for transportation related construction, things like highways, airport, tarmacs, and things like this. That AASHTO classification relies on again two input parameters, grain size distribution using sieve analysis, and then Atterberg limits. You can see here that an AASHTO classification will result in some sort of designation, A1 through A8 and there are various subgroups within that designation. But the standard in geotechnical engineering practice is the unified soil classification system, where again the input to this system is the same as the AASHTO system grain size based on sieve analysis and Atterberg limits. And the output of a unified soil classification system is as I mentioned before, a designation for that particular soil type and SP for example, is a poorly graded sand and ML is a low plasticity silt. Okay, and so it’s this Atterberg limits input that that I’m really addressing today and advocating water vapor absorption as an alternative way to classify soils.

Here’s a summary of those two tools. I think most of the listeners here are familiar with these methods. So sieve analysis for generation of grain size distribution curve as well as parameters that can quantify the general shape of that curve. This is the coefficient of curvature, coefficient of uniformity, which again effectively describe or quantify the breadth of the grain size distribution curve and can be used to to identify limits on whether a particular soil is well graded or poorly graded. For the fine grain portion, so for materials that are less than 75 microns, so that would include silts and clays in an engineering context, we use hydrometer analysis or some other sedimentation technique to measure or to separate particle sizes in that fine grained fraction. In an engineering context, we would define a clay particle as that less than two microns. So that’s just a size based classification, nothing to do with whether or not that’s an actual clay mineral. And here are Atterberg limits, at least the two that we most commonly use in practice, the liquid limit, and so this is a photograph of a coarse-grained percussion cup that we would use to measure liquid limit, so that really the moisture content that quantifies or that defines the boundary between the consistency of this clay between a liquid and a semi plastic state. And then we have the plastic limit, I think everybody’s probably familiar with this, where we define the water content between a semi solid and a plastic state. The results of liquid limit and plastic limit or the difference between these two is the plasticity index. And so when we classify soils using the unified soil classification system, we would plot the results of Atterberg limits in this space, plasticity index versus liquid limit. And there are various zones within this plasticity chart. You can see here as MH or high plasticity, silt, we’ve got clay materials above this a line, the liquid limit of 50% differentiates low plasticity materials from high plasticity materials. So again, we see these, what are certainly very archaic methods that we use to classify clays that are really only indirectly linked to the things that are actually controlling whether or not that clay is plastic, or whether or not it absorbs water. And those things are mineralogy, surface area cation exchange capacity. And so our intent here is to get a little bit closer to those fundamental clay properties. Again, just a short description of Atterberg limits, so these are water content values that quantify the boundaries between consistency states of fine grained material as it changes with water content. So again, this boundary between the plastic state and the liquid state which we arbitrarily define or arbitrarily identify using this Casa Grande method or other method, Falcone methods and other approaches that we can use, that’s the liquid limit. So essentially, the higher that water content, the more that clay is capable of absorbing the more water that clay is capable of absorbing before it begins to behave like a liquid. The plastic limit, which we measure using this thread rolling approach, generally, again defines the water content between the semi solid and plastic state. And so again, there’s that difference the plasticity index, the larger that number, the broader the range between the water contents at the plastic limit state and the liquid limit state. So again, the plasticity index is really a direct measure of, you know, how much water that particular soil is capable of absorbing before it’s sheer strength essentially is affected by taking on additional water. Activity, which we mentioned earlier is defined as plasticity index over percent clay, which we would measure from a hydrometer, or some other type of approach. And then a liquidity index really is used to quantify where the natural water content of a particular clay is relative to its liquid limit and plastic limit. So what is the consistency of a clay sample from the field relative to these two bounds?

The next slide I really like, this is a sort of a timeline of major milestones in soil mechanics history and that the intent of this slide is to point out how long Atterberg limits have been around. And so you can see back in the 19th century, a lot of the Darcy’s work with fluid flow a lot of the early mechanic’s work and here’s Atterberg limits 1911. So, over 100 years ago, the system has been around for classifying consistency of clay materials, K. V. Terzaghi’s work in the 20s through 40s really formalized if you will soil mechanics as a with the addition of the effect of stress principle. And, again, I just to point out a few you know, very specific events in our history, including the fact I used to live in St. Louis and growing up in St. Louis, you are obligated to be a Cardinals fan for the rest of your life. And I had to point out that this large disparity of when the Cubs won the World Series and when the Cardinals won the World Series. And so that’s almost as long as Atterberg limits have been around. And so how do we move beyond Atterberg limits?

That’s what this this presentation is about. And so we’re advocating sorption of water vapor as a way to classify expansive clays. And this slide really summarizes why we think this is a good approach to do that, when you think about, you know, when water is absorbed by clay, we’re really talking about a change in the potential or a change in the energy state that that water goes through. And so if we think of some, you know, free water conditions, some reference condition and think of this as a relatively high energy state, and then we, if we were to add that to dry clay, and so this little rectangle here is a little clay particle with a net negative charge there, exchangeable cat ions to balance that net negative charge. When that water hydrates this clay, there’s a change in energy, we’re going from this free water state to an adsorbed water state which is at a much lower potential or much lower energy state. And so there’s work that’s done during that adsorption process. And that work comes out either as heat there is some heat of absorption when we mix clay with water. For an expansive clay mineral, there’s work that’s done as volume change, if that expansive clay is confined, there’s work that’s done as swelling pressure. And so this absorption of water by clay is directly linked really to the swelling behavior of clay and so directly linked to surface area. And the amount of water absorbed for given water potential is going to be related to the surface area, it’s directly linked to the amount and type of cat ions that are associated with that clay. And so things like cat ion exchange capacity, specific surface area, mineralogy to some extent, swelling potential, these aspects of clay properties and clay behavior are all going to be linked to how that clay absorbs water. And so that’s really what we’re pursuing here. And this slide addresses some of those points as well.

What we’re looking at here on the left are water vapor sorption isotherms for several different types of clay. So again, the sorption isotherm. In this space, that gravimetric water content of this particular clay as a function of relative humidities so our vapor pressure. And we’re looking if you look at this green one down here, this is for a kaolinite clay along a absorption path and then a subsequent desorption path and there’s a couple observations that we can make here. One is that kaolinite because it has a relatively low surface area, maybe 10 to 20 meters squared per gram and so it doesn’t absorb a lot of water relative to these other clays. We also see if particularly when we compare that to this blue one, which is a sodium smectite that there’s much less hysteresis in the response for this kaolinite clay, a great deal more for this sodium smectite here that’s also related to the swelling. The fact that the sodium smectite swells as it absorbs and subsequently desorbs water and water is released from the interlayer space. Okay, so mineralogy clearly linked to sorption behavior, what type of clay mineral do we have? Specific surface area we’ll look later at how we can back out surface area from these measurements. Cat ion exchange capacity I’ll show some results where we can back out cat ion exchange capacity from water vapor sorption behavior as well as the type of cat ion that is associated with that cat ion exchange population. These are results on the right that illustrate for you know various, the same smectite or bentonite here exchange with different home ionic species we get an entirely different sorption response and so, the type of cat ion, the amount of charge associated with that cat ion population, all that information is buried in the water vapor sorption isotherm. So if these are if surface area, mineralogy, CEC, if these are the things that really control macroscopic you know, engineering behavior of clay, and if those properties are buried within the sorption isotherm, the idea with this talk is to explore the link between water vapor absorption and engineering behavior. And so what we’ll talk about for the next few slides is how we might measure these.

This is a slide summarizing some of the earlier work we did measuring sorption isotherms using a steady state approach, just to sort of summarize the schematic over here. Basically, this is a way to control relative humidity in a small chamber and then measure how much moisture a clay sample picks up in that controlled humidity environment. And so we had an air canister that was split into two separate gas streams using these mass flow controllers. And so one of those gas streams was bubbled through water to create pretty close to a saturated gas stream closer to maybe about 95% relative humidity. The second gas stream is routed through a desiccant column which isn’t shown here. You can see it in this photograph over here to produce a gas stream probably somewhere around 2% humidity or so and then we could mix those two gas streams together in this mixing flask at a ratio that would have produced a gas stream with some target humidity or some desired humidity, that we would then route into this environmental chamber, measure the humidity and use that as a feedback to control these two valves. And that the specimen that’s in here, a couple of grams, maybe three or four grams of clay sitting on electronic balance, and so we could measure the absorption or desorption responses, we control the humidity in that environment. This is just these data here are responsive. Just to give you some idea of you know how long at least for the volume of chamber that we were using, the flow rates that we were using to reach steady state humidity in that environment. We could ramp up and ramp back down. And that the clay response would be superimposed on this. The response of the clay, you know, depends on the geometry in the mass of clay that we’re dealing with. But you know, within a week or so, which is a fairly long time, we could reach steady state moisture content at each of these increments. So that’s one of the ways to do this.

Other ways to do this, these dynamic dewpoint methods that are the two figures up here on the left are an earlier generation device developed by Decagon here to measure water vapor sorption isotherms in a dynamic fashion where again, the idea is similar where circulating a gas stream through a chamber containing a powdered specimen of let’s say clay in this case, and really taking snapshots of the humidity or the vapor pressure and the mass of the clay during this dynamic sorption process. And so this is the current generation VSA system that accomplishes that as well, we did quite a bit of work looking at comparing the results of a system like this to that steady state system that I was just describing. And so this is a comparison of for a pure kaolinite. These close circles here are, you know, steady state measurements of the sorption isotherm at these you know fairly coarse increments in vapor pressure. And these open symbols here are that dynamic measurement. So that’s where a pure kaolinite. For a 10% kaolinite, 90% bentonite mixture again, really good comparison, most notably at lower humidities for between these two methods. This is a comparison of how we might back out surface area or related monolayer coverage from sorption isotherms. I’ll talk about that in a moment. And so, the point here is that sorption isotherms are pretty easy to measure, you know, this these dynamic methods can develop sorption isotherms for clay along wetting and drying paths, you know, within 24 hours or so, and so, very, very efficient way to make a measurement.

The next sort of step in, you know, using water vapor sorption as a classification tool, at least as I saw it in and my colleagues saw it was to try and establish links between indices that we can obtain from sorption measurement. And so that’s what this w 75 is down here. This is from a measured sorption isotherm using water vapor that gravimetric water content of, in this case clay or natural soil at 75% humidity, and we specifically identified 75% humidity because that’s sort of the upper limit between water sorption that occurs for most soils as a you know short ranged hydratation mechanism. And at higher humidities greater than 80, 85%. Typically, where water starts to be absorbed under capillary mechanisms which are sensitive to disturbance and fabric. And so we wanted to identify an index that was measurable and so that the closer we could be to kind of the endpoint of the hydration regime that the larger that value is going to be, and therefore, the less important noise in the measurement is going to be. But we also wanted to stay within this hydration regime. And so what this plot is, is a comparison for several natural materials from, in this case, Missouri and Colorado as well as a few artificial mixtures of different types of soils, w 75 versus plasticity index. So it’s sort of a conventional classification approach here on the vertical axis, and then this proposed classification index here on the horizontal axis. And so, what these shaded boxes are, we looked at earlier. These are those different categories of summarized again, down here, different categories of swelling potential based on plasticity index. So between zero and 15, we would, you know, using this, in this case, the Chen classification system based on plasticity index, correspond to a non expansive or low expansive material 10 to 35%. Or rather 10 to 35 PI moderate. And so, by sort of bounding corresponding widths of these boxes to accommodate these data, we could identify ranges of w 75, that were in this paper at least proposing as an alternative way to classify expansive clays that’s directly linked to at least one of the ways that practitioners are doing this now. Other things that we’re working on, as I’ll show you in a moment here is how to extract surface area or cat ion exchange capacity from sorption measurements. And then ultimately, how do we establish links between surface properties like surface area and cat ion exchange capacity to engineer behavior, things like compressibility, or shear strength or other things that we might be interested in from an engineering standpoint. We talked about surface area for a moment.

So if we quantify specific surface areas, so meters squared per gram, typical values for kaolinite, as I mentioned before, maybe between 10 and 20 meters squared per gram. Smectite, depending on whether we’re talking about internal or total surface area may be up to 800 meters squared per gram. There’s been a number of studies that have been done just sort of empirically correlating surface area to a variety of engineering properties, certainly plasticity, cat ion exchange capacity, some of these correlations are better than others, as well as engineering behavior things like compressibility, dispersion behavior, frost heave susceptibility, and swelling behavior. So there is motivation to try and identify not only these links between surface area and engineering behavior, but also to identify and refine approaches for measuring surface areas. It’s one of these approaches that can really have a wide range depending on what approach is used to measure it. Ways that surface area can be measured, not very commonly done, at least in my circle is using XRD to identify crystallographic information or morphology by imaging. More commonly those sorption methods are used using, you know, a variety of different probe molecules, nitrogen EGME, methylene blue, and so here we’re talking about using water vapor as a probe molecule for measuring surface area. This isn’t a new approach. This has been around for a long time, there’s been a number of challenges that are identified using water as a probe molecule, particularly when we’re dealing with clay and this image over here intends to communicate some of that and you know, the idea with a surface area measurement is to identify an amount of this sorbent that corresponds to monolayer coverage and so, the idea of or the concept of monolayer coverage particularly with a clay cat ion system is a little bit arbitrary. You know, we have preferential adsorption initially, by the cat ions, we have adsorption directly onto the of water directly onto the clay surface and it becomes challenging to differentiate when and if monolayer is present. I’ll point you to some of the work that my colleague at the Colorado School of Mines Professor Ningaloo is currently doing to really identify systematically sort of these boundaries between, you know, when cat ion hydration is satisfied when surface adsorption is satisfied, when capillary condensation begins to occur. But again, if we’re using water to identify a monolayer coverage, there are challenges associated with this. One of the common ways to do this is using BET analysis.

This equation is at the heart of BET analysis. And essentially what this allows us to do is to plot results of sorption isotherm in space that we can use to back calculate monolayer coverage, which we’re ultimately looking for, to calculate a surface area. This C is an energetic constant, there’s information in here about sorption capacity. And so what we’re looking at here is a comparison between specific surface area calculating using water vapor and multipoint BET analysis versus an alternative approach using a different EGME molecule and we can see that we get fairly good correspondence between these methods for you know relatively low surface area materials maybe less than about 100 meters squared per gram. For expansive materials in particular higher surface area materials, where we have inner layer swelling, water being adsorbed on, you know, two layers within an inner layer of space, we do see this divergence between the the EGME method and a method based on water vapor sorption. We see you know, no deviations based on cat ions that are associated with this as well.

In terms of cat ion exchange capacity, first of all again, what is this? This is really a measure of the cat ion charge required to balance that negative charge associated with the clay mineral surface. And so, that’s again related to you know, the sorption capacity of the clay, you know, if there is a great deal of net negative surface charge counteract, counterbalanced by these, by a large population of cat ions, the water vapor sorption behavior is going to be influenced by that. CEC also varies widely with mineralogy, maybe between three and 15 meq per 100 grams or something like kaolinite, much higher for smectite. Commonly, this is used using displacement methods, it will displace the natural cat ion exchange complex with an index species and then measure essentially what was kicked out of that natural complex. And so the question here becomes, can we use water vapor sorption rather than a displacement method to quantify CEC? And so we’ve been working in this area for some time. A couple different ways to do this and this is one approach is to simply empirically relate CEC to other things that we might measure and perhaps surface area.

And so, you know, correlations between surface area and cat ion exchange capacity there tends to be some correlation, but they can be all over the place. And so there’s some uncertainty associated with that, but it’s not surprising probably that there is some relation between surface area and CEC. Another approach that seems to be showing some promises is using water vapor sorption to do this. And so just to kind of illustrate this point, in the upper right here, these are sorption isotherms for kaolinite. This is sort of an end member of pure kaolinite, down here and an end member, sodium smectite up here, and then mixtures between. Not surprisingly, the sorption responses is systematically related to the percent smectite if you will, in the mixture. And the interesting thing is that if we normalize this water content, if we normalize it by the CEC of these mixtures, within this range, where surface hydration is dominating the sorption, these normalized isotherms really collapsed to what we might call a master curve. And so the idea here is that if there is a master curve, and we don’t know the cat ion exchange capacity, can we use that master curve to back calculate what the CEC would be for that material? These results here are sort of results from a few years ago where we were working with you know, homoionic species and you know, well controlled mixtures within some of the work that’s happening now. We’re able to not only calculate cat ion change capacity from sorption behavior, but actually identify specific cat ion types, differentiate major cat ions within that overall population.

And then finally, just, you know, we’ve been talking about clay. But we’ve been also looking at water vapor sorption to characterize other materials. And one of which is why this is sodium bentonite up here, this is a geosynthetic clay liner that might be used in a landfill application or something like that. So again, this is a very thin layer, maybe seven to 10 millimeter thick layer of what is essentially sodium smectite that is used to create a low hydraulic conductivity barrier to contain lead shade within let’s say, a municipal solid waste landfill or a disposal site for coal combustion products, something like that. One of the things that we’ve been working with recently is bentonites that have been modified or amended with polymer, super absorbent polymers to really deal with aggressive chemical environments, maybe really high salinity, lead shade that might be generated, really extreme pH environments that are not compatible with conventional sodium bentonite that would collapse double layers and open up pathways to increase hydraulic conductivity. By incorporating polymers into this blend, really what the polymer is doing, you can see in these images is really even if the clay clusters within this system collapse, the polymer is available to fill up that that larger scale pore space, create a hydrogel that reduces hydraulic conductivity. But the question becomes, you know, how can we do quality control for these materials? How can we classify or predict the engineering hydraulic conductivity of a polymer amended clay and so we’ve been looking at using water vapor sorption to do that, and we just look at these results over here where we see this is a constant that falls out of a fit to a friendly isotherm for the water vapor sorption. And we see that that’s clearly correlated to polymer content. The idea is to be able to use water vapor sorption as a screening tool basically. If this is a manufactured product, heterogeneity of the polymer within this, you know, within this system becomes extremely important. You know, we don’t want spots where there’s not enough polymer perhaps from a assembly limitation where the homogeneity of the polymer within this mixture is not homogeneous. And so it becomes a way to do spot checks, basically, on the on the polymer content. Can we use water vapor sorption to do that, for example? And so, these are some of the things that we’re looking at.

Finally, just to summarize, the goal of soil characterization, ultimately, is to predict engineering behavior. The tools that we’re using to do this in engineering practice Atterberg limits, these are certainly archaic. These are sort of arbitrary index tests that we use to define these consistency limits. They’re over 100 years old, and they’re only indirectly related to the basic properties that control soil behavior, clay soil behavior, so surface area, cat ion exchange capacity, cat ion type, these are the things that really controls soil fabric. And soil fabric is what really controls essentially behavior. So can we get closer to direct measurements of these? And so what we’re advocating here is are ways to use water vapor sorption to do that. One application is swelling soils, you know, water vapor sorption is you know, this process, is associated with a change in potential of that water phase. You know, is that change potential directly related to work done as that material swells? Is water vapor sorption directly correlated to mineralogy surface area, cat ion exchange capacity type of cat ion? And so these are the things that we’re working on to try and establish these relations. Water vapor sorption is an approach that’s relatively easily measured. We looked at a few different ways to do this using this mixed flow system that I pointed out, dynamic dewpoint methods that can obtain sorption isotherms for clays or other materials in 24 hours or so. And then finally, we looked at some of the things that need to be done to implement this idea of replacing Atterberg limits. You know, can we establish links between existing classification tools, maybe plasticity based tools to sorption based tools? And can we resolve some of these challenges with extracting things like surface area and cat ion exchange capacity from sorption measurements. And so these are the things that we’re continuing to work on and making progress on. And then finally, I’ll just leave with a few references. There are a number of other references as I pointed out. I’m aware that we’ll have a question and answer session after this. And so we can talk then if you’d like about some other references. Some of the more recent work that’s been done to get at cat ion exchange capacity and surface area. And finally, just to acknowledge NSF funding for this work, this work is falling out of a grant entitled A new framework for fine-grained soil characterization (moving beyond Atterberg limits) so with that, I’ll close. Thank you very much.

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