Why is AFM so useful to characterize polymers?

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We know AFM can image a wide variety of surface properties on the nanoscale:   topography, mechanical, electrical, magnetic, and even thermal.  Imaging true topography on the nanoscale is undoubtedly the most widespread application of AFM.  In terms of industrial applications, this is especially true for the semiconductor industry where AFM is a unique tool to measure critical dimensions of a wide array of features in a metrological capacity that are important to this industry.

But in terms of its ability to get material contrast, polymers and the chemicals industry is probably the most widespread application of AFM.  Most R&D facilities in a chemicals company will be equipped with at least one, if not multiple, AFM’s that are used round the clock for imaging the various materials that are being synthesized.   And pretty much anyone who is working with a polymer surface has used AFM to characterize their sample.   Why is it that AFM has emerged as such a useful method to characterize specifically polymer materials?

Before AFM came along, there were certainly other techniques available to scientists to probe nanoscale features in polymers. These techniques are primarily in the electron microscopy toolkit but included several challenges for specifically polymers.  First, these methods operate in vacuum so any ambient studies were not possible and some polymers do not cooperate with vacuum environments. Second, materials composed of light elements and similar densities - such as polymers - require heavy element staining to increase contrast, which can induce its own artifacts.  Third, electrically insulating samples such as polymers can accumulate charge from the electron beam and thus need to be coated with a thin conductive layer for effective imaging and to minimize the charging effect. 

AFM takes care of all these three challenges! It has no problem working in ambient or even fluid environments.  No staining needed to generate contrast between materials. And finally, AFM has no problem handling electrically insulating samples.

It is the second reason though – the contrast mechanism – where AFM really shines with respect to polymers.    Polymers don’t exhibit much chemical variety:  they are primarily composed of carbon, hydrogen, and oxygen, and sometimes with some other elements thrown in like nitrogen or sulfur.  Sure, I’m oversimplifying this incredible class of materials, but from a chemical point of view, there just isn’t a lot of variety.    Polyethylene and polypropylene are commercial commodities in the plastics industry representing a multi –tens of billions of dollars business worldwide.  Their monomers are different by simply 1 carbon, but their properties and applications vary significantly.


Polyethylene structure and isotactic Polypropylene structure

Where there is a lot of variety in polymer materials – and why they are so popular in so many goods and applications – is that they can be designed to exhibit a very wide range of mechanical properties.  Polymers can be really stiff (like a cyclic olefin copolymer) or very squooshy (like an elastomer), or even incorporate elements of both (like an impact copolymer).  Or relating back to our polyolefins, polyethylene is softer and is the most popular plastic available as it is used in grocery bag, food packaging, and milk bottles.  On the other hand, polypropylene is more stiff, rugged, and heat-resistant and used for many different consumer goods such as diapers, health care, appliance parts, and automotive trim parts.   And mechanical properties is where AFM is uniquely powerful due to the inherent mechanical interaction between tip and sample.  Based on this, AFM has no problem distinguishing between PP and PE

Two images of PP and PE showing the differing information available by AFM (courtesy of Anasys Instruments)

AFM even has no problem differentiating different kinds of polyethylene.  Branching can be incorporated into the PE backbone to give it more flexibility resulting in different varieties of polyethylene including high density PE, low density PE, linear low density PE, and ultra high molecular weight PE.  Although chemically very similar, AFM has no problem distinguishing between them. 

There are many different operating modes that AFM can be operated in to generate materials contrast. Probably the two most popular modes today are phase imaging and some kind of force curve imaging.  In phase imaging, the cantilever is oscillated at its resonance frequency and the phase lag (or lead) between the cantilever and its response is mapped as the tip interacts with the surface. While not quantitative, the phase does offer an incredibly useful contrast mechanism based on a convolution of many material properties such as stiffness, adhesion, and dissipation.   The second common mode is based on force curves, where the tip plows in and out of the surface at a given point. Different segments of these force curve can then be analyzed and fit with models to extract useful properties such as modulus and adhesion.  Increasingly, imaging methods that are based on force curves are being developed and used where a force curve is taken at every pixel and analysis is either done on the fly or after the data has been collected.

This blog has just discussed the simplest kinds of polymers and polymer blends.  But polymers are increasingly being formulated with more sophistication in properties and structure including nanocomposites, multiblocks, copolymers, multilayers, branching, thin films – the possibilities are endless.  With its ability to generate mechanical property based contrast on the nanoscale, AFM has really emerged as a unique – and rather widespread tool – for polymer studies. 

Dalia Yablon, Ph.D.

SurfaceChar LLC





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