Atomic Force Microscopy (AFM) for Polymer Characterization and Analysis
February 14, 2017
Presenter: Dalia Yablon, Ph.D., Founder, SurfaceChar, LLC
Atomic force microscopy (AFM) is uniquely suited to characterize polymer materials on the nanoscale revealing structures and morphology without the need for extensive sample prep or vacuum environment. Unlike its electron microscopy counterparts, the interaction between probe and sample in AFM is mechanical-based making it especially suited to provide contrast on polymeric type samples. This webinar reviews the application of AFM to study different polymer materials, including thermoplastics, elastomers, blends, and high resolution studies. 30 minutes.
Charles Zona (CZ): Welcome to another McCrone Group webinar. My name is Charles Zona, and today our presenter is Dalia Yablon. Dalia is going to talk to us today about the application of atomic force microscopy to polymer characterization and analysis. Before we get started, I would like to give you a bit of Dalia’s background.
Dalia is the founder of SurfaceChar, an AFM consulting firm located in the Boston area. SurfaceChar specializes in surface and interface characterization and measurement, along with education and training, focusing on scanning probe microscopy. Prior to SurfaceChar, Dalia spent a good portion of her career at ExxonMobil Research and Engineering working with the chemicals division to develop new AFM-based imaging methods. Dalia is also the editor of the book Scanning Probe Microscopy in Industrial Applications published by Wiley Publishing in 2013.
Dalia will field questions from the audience immediately following today’s presentation. This webinar is being recorded and will be available on the McCrone Group website under the Webinars tab. Now, I will hand the program over to Dalia.
Dalia Yablon (DY): Hey everyone, good afternoon, and thanks for joining us. This afternoon I will provide a brief overview of the technology of AFM and give some examples of the power of its capabilities when applied to characterizing polymeric materials.
So what are some of the most common measurements AFM conducts on polymers? Probably the most common data polymer scientists ask for from AFM is topography and morphology. AFM is unique in that provides true measurement of z, or height. This enables any measurements that requires the sample height such as thickness or roughness to be measured accurately and with very high resolution. The AFM can provide a true three-dimensional map of the surface like the one shown here which is very useful for certain applications.
The morphology is also a very useful measurement. Morphology refers to features like particle and domain size and distribution, geometry and size of features, and other size-based descriptions of the surface. AFM is uniquely suited to provide morphology on polymer samples, since the mechanism for contrast is mechanical—based on a mechanical interaction between the tip and sample. This is very different than the contrast mechanism between electrons and the sample in SEM or TEM. The kind of contrast required for SEM and TEM can be hard to obtain for polymer samples, since there might not be much chemical differentiation between the materials. Very often, in those cases, the AFM mechanism of contrast is superior and very easy to obtain.
There are a number of different AFM modes that can be operated to obtain images based on mechanical contrast, with the most common mode called phase imaging. Here is an AFM image showing the topography and phase of alternating sets of high and low density polyethylene. The topography image on the left shows little contrast, but the material-based contrast of the phase image on the right shows unambiguous contrast between the two components.
Finally, AFM can be used to make semiquantitative, or, in some cases, even quantitative, measurements of mechanical properties of a material, including stiffness or modulus, adhesion, and viscoelasticity. And all of these measurements can be made with impressive nanometer lateral resolution and sub-nanometer vertical resolution. I’m not going to be showing applications of these quantitative mechanical measurement even though they are quite polymer for polymer applications and that is because they are more complicated than the imaging methods I have time to describe today.
Now that we have a little bit of background on AFM, I wanted to explain a little bit on the operating principle of the instrument. Shown here is a schematic of how the AFM works. The heart of the AFM is shown right here in the cantilever/tip assembly that I will refer to as the AFM probe. An SEM image is shown here in the top left is an example of a probe. You can see the long cantilever here with a sharp tip hanging off of it. The cantilever has dimensions similar to those of a human hair—typically hundreds of microns in length, tens of microns in width, and a few microns thick. The very sharp tip at the end of the cantilever is what will interact with the sample as it is raster scanned under the tip. The diameter of commercial tips is typically 5-10 nm.
As the probe interacts with the surface, a laser is reflected off the back end of the cantilever and directed towards a two- or four-quadrant position-sensitive detector that can monitor both the up/down motion, and in the case of a four-quadrant detector, also the side-to-side or lateral motion of the cantilever as it raster scans across the surface.
Finally, showing a sample scanning configuration here, we have a piezo that will move the sample under the cantilever in a raster scan to collect the image.
The key to AFM is, again, the interaction between the very sharp probe and the sample. There are a number of ways the probe can interact with the sample, including methods that are both static, or non-resonant, and those that are dynamic, or resonant. These resonant methods take advantage of oscillating the cantilever at resonance through this shake piezo, shown here, in order to interact with the surface.
Now that we hopefully understand a little about how the AFM works, let’s discuss some applications of AFM to imaging polymer materials.
The most common AFM mode to get contrast based on materials properties is called phase imaging. Phase imaging is a dynamic or resonant method where we oscillate the cantilever at resonance and measure the phase lag between the drive and response. This phase lag is due to a convolution of material properties including adhesion, stiffness, dissipation, and viscoelasticity, resulting in very useful, albeit qualitative, images providing material contrast.
A couple of slides ago, we showed a phase image differentiating the layers of low and high density polyethylene, where the topography image did not.
On this slide, we have a 10 µm x 5 µm image of a tire tread with topography on top and phase on bottom. In the topography image, features that are bright or yellow/white are topographically high, and features that are dark/purple are topographically low.
In the topography image on top, we see a high density of particles in the yellow dotted regions shown. In the phase image shown below, we see a much richer picture of this material. Those little yellow particles are now showing up dark purple in the phase image, consistent with the interpretation of these particles as being stiffer than the other components in this surface. As an aside, interpretation of phase images is tricky, and is dependent on collecting the image under appropriate and consistent imaging conditions, so the interpretation of the phase images that I will be describing here and in the rest of the webinar are based on these images being collected under what we refer to as net-repulsive imaging conditions. In addition to stiff particles, the phase image shows multiple components, which are differentiated based on their materials properties. We will look more closely at these components on the next slide. And then here on the right, reflecting the impressive capability of the AFM to provide multiple channels of information on a surface at the nanoscale, we have image of the phase painted onto the three-dimensional topography. This visualization enables us to correlate the material property contrast from the phase channel with the topography in order to provide us with a more complete picture—no pun intended—of the surface.
This next slide shows an important material used in consumer products, termed an impact copolymer. It consists of a matrix of thermoplastic, in this case, polypropylene, that has been impregnated with micron-sized rubber domains. In this way, this material delivers the stiffness of the thermoplastic and the impact toughness from the rubber. These materials are commonly used for a wide variety of consumer applications, including car bumpers and appliance linings, where these performance attributes are necessary. The size, morphology, and dispersion of the rubber domains is critical to determining the ultimate mechanical performance of these materials. The AFM is the ideal tool to characterize such materials. On the left here, we have a 10 µm x 10 µm phase image, where the rubber domains are clearly showing up in the bright yellow regions among the purple thermoplastic. On the right is a zoom-in showing a 5 µm x 5 µm image, where we can see some of the rubber domains up close, including inclusions within the rubber domain. With this type of information, AFM is an indispensable characterization tool for quality control during product formulation.
We can also do a quantitative analysis to further describe the structures in this particular sample. Here we have conducted a domain sizing analysis where we can easily threshold out the rubber domains based on their phase value. We could also use sophisticated algorithms to help select out domains if necessary, but in this case, a manual thresholding based on the z value of phase did the job nicely. Once these domains are selected, we can then analyze a number of different parameters of their size, geometry, proximity, etc., then tabulate it in graphs and measure statistics, so, for example, in the image on the left, we have color-coded the rubber domains by radius so that rubber particles of similar radius have been outlined in the same color. On the right are shown histograms of some of the parameters, including radius, length, area, and aspect ratio, all of which can be used to quantify the structure-property relationships of this particular sample.
Another area where AFM is popular and takes advantage of its nanoscale resolution is its imaging of block copolymers, which are made up of blocks of different polymerized monomers and can be compromised of two blocks (diblocks), three blocks (triblocks), etc. Typically, these polymers will micro-phase segregate to form pretty periodic nanostructures. Here on the left are examples of high resolution AFM images of a popular block copolymer, SEBS (styrene-ethylene-butylene-styrene), and on the right, an AFM image of poly (3-hexylthiophene)-block-perylene-bisimide acrylate copolymer, where P3HT is a conductive polymer with application to photovoltaic devices.
One of the strengths of AFM is that it is capable of a wide variety of in situ measurements because of the flexibility of the platform. One such measurement is shown here, where the impact copolymer is being stretched under tensile stress, and the AFM is imaging it in situ while it is being stretched. The direction of the white arrow reflects the direction of stretching. On the left is a 10 µm x 6 µm phase image of the stretched impact copolymer. In the region circled in white, we can see a craze, or fracture, appear within the PP matrix as the material is pulled apart. On the right is a 5 µm x 5 µm image focusing on the rubber domain. We can see stretching of the rubber in a direction perpendicular to the stretching direction as the rubber tries to compensate for the tensile stress.
Another theme of in situ measurements is the AFM as a powerful tool for studying polymer crystallization. Thanks to the key AFM advantages of resolution, minimal sample prep, and non-destructive imaging, AFM has contributed many insights into crystallization, melting, and re-ordering processes at the lamellar and sub-lamellar scale. In situ measurements of polymer crystallization using heating stages—where the surface can be heated, cooled, and imaged at temperature—is an area where AFM has contributed a lot of insights. Here is an example I pulled from a paper published in August of last year dealing with the crystallization of poly(ethylene terephthalate), or PET. The thin film of PET was held for two hours at each temperature as the temperature was slowly increased; so, first we see an amorphous surface at 65°C. As the temperature is raised to 75°C, surface crystals begin to grow. As the temperature continues to rise to 85°C, an intermediate structure is formed, in which the surface crystallinity has not yet fully broken up; then, finally, we see onset of bulk crystallization. There are also ultra-fast scanning capabilities that have come to the AFM market within the past five years, where the imaging speeds have been significantly increased, combined with the ability to image at temperature, such that kinetics of crystallization process can be visualized in real time. There is a lot of exciting work—and beautiful videos—that have resulted from this research.
Continuing our theme of in situ measurements of polymer kinetics and dynamics, here is some work exploring ultra-thin polyethylene films on graphite. At 120°C, a semi-crystalline PE layer is covered by molten droplets shown by the bright yellow patches that measure at about 5 nm in height. Structure in the semi-crystalline layer can be seen here in the background. By manipulating the AFM imaging parameters, the authors then penetrate through the molten droplet in order to detect the interfacial layer, which they find is ordered. By gently tapping on the surface, they visualize the liquid droplet shown here; then by changing the parameters of the AFM, they are able to poke through the droplet to take a peek under it and see that, in fact, there is order underneath the droplet. The color scale on the height image of bright to dark is only 4 nm here.
Finally, being microscopists, we are always intrigued by the limits of the resolution of the instrument. AFM is continuing to push the limits on its resolution with sophisticated techniques and hardware that have achieved molecular, and even sub-molecular, resolution. I will tantalize you here with an example—pushing resolution that is relevant to the polymer community. Here they imaged a sheared PE film revealing a 110 surface of a crystalline PE lamella where you can see the single chains. When they zoom in to different regions on the surface, they landed on an area shown here, where they captured an interface between an amorphous region (shown in the dashed box) and a crystalline region, showing chains in the 010 surface of the crystal. Free loops emanating from the fold surface project into the amorphous region, as shown where one is marked by the arrow. The loops project about 5 nm into the amorphous material.
Because this is a time-constrained webinar intended to give you a flavor of AFMs capabilities for characterizing and analyzing polymers, I want to conclude with a taste of some more advanced AFM methods that are commonly used to study polymers. So far, I have focused on the imaging modes, but as I have been stressing throughout this webinar, because we have a mechanical interaction between the AFM probe and sample, the AFM can do much more than just image.
On the left, I have some examples of force curve measurements. These are single point measurements where we use the AFM probe to poke the sample; so we bring the probe in, poke, and then retract it. We can plot the force exerted by the cantilever as we poke, as a function of tip-sample separation. Here, I have plotted the force curves measured on two samples: in blue is on a smooth metallic film, and in red is a force curve on a rubber sample; we can see these force curves look very different. Some of the attributes that we would focus on are the slopes of what we call the repulsive wall of the curve (highlighted by black arrows), and the adhesion dip (marked in the red curve with the star). We can use contact mechanics models to model the interaction between the tip and sample to get further information on the mechanical properties, such as modulus and adhesion of our sample.
On the right is an example of an advanced dynamic contact method used to quantitatively measure the loss modulus and loss tangent of a material. This sample is a blend of three polymers – PP, PE, and PS, and we have a quantitative measurement of these viscoelastic properties loss modulus and loss tangent here.
In terms of information from our images, there are also advanced modes that are providing more powerful capabilities as advances in hardware and software improve the technology. Multi-frequency methods where we oscillate the cantilever at more than one eigenmode have emerged, with improved results for multi-component, heterogeneous samples. Here on the top, on the left, is a conventional phase image of a multi-component material. On the right, is a multi-frequency image collected simultaneously, revealing this bright yellow component that was not visible in the single mode image.
On the bottom is an example combining AFM and chemical information. I alluded it to such methods earlier in the webinar. This is an example of a technique that combines AFM with IR spectroscopy, where the IR spectroscopy is now at the resolution of a couple hundred nanometers. In this image, the AFM topography of a blend of rubber and nylon was collected. Then, IR images at 3300 wavenumbers—a dominant stretch in nylon and colored in green, and 2956 wavenumbers—a dominant stretch in the rubber and colored in blue, was mapped and superimposed onto the AFM topography, revealing an image where the two components are identified unambiguously.
In summary, I hope I have been able to show you that AFM is a powerful tool in our nanoscale toolkit, where its primary advantage comes from a mechanical interaction and the ability to operate in flexible environments. For polymers, AFM is especially useful, because it provides a unique contrast mechanism based on mechanical or materials properties. It also requires minimal sample prep. I have shown a number of examples of using AFM to characterize a wide variety of polymers. Most of the applications I showed today are using basic AFM methods. The last couple of examples of the ultrathin PE films on graphite and the high resolution imaging of individual PE chains were more advanced methods, but the rest of the images were done with conventional modes. Finally, the ability of the AFM to take advantage of the environmental flexibility to image in fluidic environments, at temperature, and with tensile stages, expand the utility of the tool to further explore polymer chemistry and engineering.
I’m going to conclude with a brief plug for a course we are holding next month at Hooke College of Applied Sciences in Westmont, Illinois. If you are interested in learning more about the AFM and learning the basics of operation and even getting running the instrument yourself, I encourage you to consider this course. It is a three-day, intensive, laboratory-based course, where we will be working with AFMs from Bruker and Asylum Research, as well as cryomicrotomy tools from Leica, provided by Mager Scientific. In this course, we will cover topics such as modes of operation, overview of hardware, image processing, imaging artifacts, advanced imaging modes, nanomechanical modes to measure mechanical properties, hybrid AFM/spectroscopy methods such as AFM Raman and AFM IR, and much more. It really is a very thorough and comprehensive hands-on introduction to AFM, and please don’t hesitate to contact either myself or Hooke College with any questions.
CZ: Okay, great. We do have some questions rolling in. The first one is from Chris, and she asks, “Are there any requirements or constraints on the kind of sample that can be studied with AFM?”
DY: Yes. That is an excellent question, and the good news is, not really. There is certainly no material requirements on the samples, so there are no electrical, conducting, or insulating requirements, or mechanical properties. It can pretty much image it all. The only two practical requirements on the sample are: one, it has to fit into your instrument. AFMs fall into two categories: there are the large sample instruments, and small sample instruments. Different instruments are designed to handle different kinds of samples. In general, if it fits into the instrument, you go for it. When I was at Exxon Mobil, I was sticking in engine parts and imaging those, so that is fine. That is constraint number one. The other constraint is the smoothness constraint, and that has to do with the limits of the piezzos that are in the instrument, so typically you have to check what the z-range is of your instrument. Typically, the z-range is not huge, we are talking about 5 microns in z over hundred microns in x and y are typically the type of dimensions the instrument can handle.
Okay, I see some more questions and I think I am going to start going through them one-by-one.
CZ: Yes, go ahead, Dalia.
DY: Great. I see a question here. “What is net repulsive condition?” Net repulsive condition refers to operation in tapping or dynamic mode. It refers to the interaction between your tip and sample. When you set up your AFM experiment—when you’re setting up those parameters—if you’re not careful, which to be honest, most users probably aren’t even aware of this and are not careful, you will set up a condition where your tip, sample, and traction will toggle between what is called repulsive and attractive interaction. Again, that refers to how the tip is interacting with the sample, and that causes a lot of confusion, a lot of artifacts, and a lot of problems in phase imaging. It is probably the number one cause of artifacts and misinterpretation of phase imaging when users are not careful to set up there parameters such that they are imaging consistently in the correct regime.
Okay, next question. “How does AFM IR/ AFM Raman work in general?”
Sorry, that is a two-and-one-half hour module in the course. It is pretty involved explanation. They are separate in terms of how they work. AFM IR is one system, AFM Raman is totally different system, and it is beyond the scope of the ability to answer here and go into in more detail.
Next question: “Is it possible to get a force distance curve for soft matter?” Certainly. I think that is one of the biggest applications of force curve is polymeric samples, even biological samples. You have to be very careful how you set that up, and use the right kind of cantilevers with the right kind of spring constant, but a very popular application of these force distance curves.
CZ: Does that do it, Dalia, for the questions?
DY: Yes, I think so.
CZ: Okay. I would just like to thank Dalia again for the presentation, and thank everybody for attending today’s webinar. If you have any questions about the upcoming course, feel free to contact Dalia or Chris. Our next webinar is with Bill Chapin, Senior Research Scientist at McCrone Associates. Bill will talk to us about various light sources and techniques as applied to the stereomicroscope, and why this powerful instrument is the beginning point for nearly all of his analysis.