The importance of the probe in AFM part 1: The tip
The heart of the AFM is really in the cantilever/tip assembly, often referred to as the probe. This probe governs the interaction and ultimately the type and quality of data measured with the instrument. Too often, users just grab probes that are lying around in order to run their instrument. So I figured I would dedicate the next two blogs to explaining the importance of the probe and how it can affect the experiment. The probe really has two parts: the cantilever and the tip.
Image of TR400 probe from olympusprobes.com
So this time we will cover the tip, and next time we will cover the cantilever.
The AFM tip is typically made of silicon or silicon nitride. It does not have to be made of the same material as the cantilever, but each material has its own advantages. A silicon probe can typically be made sharper whereas a silicon nitride probe should wear less than a silicon probe. There are many manufacturers of AFM probes today such as AppNano, Asylum Research, Budget Sensors, Bruker, NanoWorld, Nanosensors, Mikromasch, and Olympus. Probes can typically be purchased directly from the manufacturer or from distributors such as nanoscience and nanoandmore.
Tips made out of diamond are also available commercially from manufacturers such as Adama Innovation, (a recent entry to the market), Bruker, and Nanoworld. There could be several advantages to diamond tips such as wear-resistance and stable shape during imaging, as well as improved and more reliable electrical measurements with a conductive diamond material.
AFM tips also have flexibility to be functionalized or coated. So you can coat your tip with a metal like cobalt or platinum (this is actually needed for electrical/magnetic measurements), or even gold. The AFM tips can be functionalized directly for chemical and biological applications. A gold coating also provides a convenient platform for chemical or biological functionalization by taking advantage of thiol-gold chemistry. The customization possibilities for tips are endless.
The million dollar question with AFM tips is always: what is its shape? Very often when we need to model the AFM probe with contact mechanics in order to extract material properties, and we have a variety of probe geometries that we can select for in the model such as a cone, punch, or sphere. We always show pretty SEM images (like the one above) showing a perfectly pyramidal tip, but sadly this is not always reality! For example, see below SEM images of brand new tips right out of the box showing a variety of tip shapes and sharpnesses:
From Kopycinska-Muller et al., Ultramicroscopy 2006 p. 466
Measuring AFM tip shapes can be tedious. Direct imaging via TEM or field emission SEM is possible but laborious. Another popular way to measure the tip shape is referred to as blind reconstruction. You image a tip with very sharp features that are sharper than the tip (such as Nioprobe sample or Tipcheck sample) so that you get a reverse image of the tip. Then you can use algorithms (commonly available in many SPM softwares such as SPIP Image Metrology or Gwyddion) to reconstruct the tip shape.
Unfortunately, even if you go to a lot of trouble to characterize your tip there is a catch: The tip shape will undoubtedly change during the course of your experiment! In fact, the tip shape is truly an Achilles’ heel of AFM imaging and is the source of a lot of artifacts and unknowns. The shape can either wear down if you are imaging a hard sample, or contaminate if you image a soft or sticky sample like a polymer. In fact, often times you can see the tip change “in real time” as you are imaging as the tip picks up contaminants or more fortuitously, breaks off a piece and maybe even becomes sharper. If knowing the tip shape is that important to your experiment, you simply may have to measure it both before and after your measurement.
Even if you cannot control your tip shape (which you cannot), it is important to understand its variability, how it can affect your imaging, and what your options are. Happy imaging!
Dalia Yablon, PhD