FridayAFM - Frankenstein's monsters

Héctor here, your AFM expert at Nanosurf calling out for people to share their Friday afternoon experiments. Today I will teach you how to recognize tip artefacts in your images.

If I trained you on how to use an AFM, you probably heard me more than once repeating:

"if you want to obtain good images and get the most out of your research time, before capturing an image, you should know how it should look like, maybe not at 100%, because why doing research then?, but at least, have a good idea how it should look like, otherwise you will be easy to trick"

Well, maybe not that long all the times, and not exactly those words, but you get my point. The more you know how something should be, the easier it is to detect when something is off.

So, in order to help you with that, I'm going to show you what happens when you have different tip artefacts, so you will be able to quickly identify them, and save research time (or reputation if you go as far as publishing).

First of all, you need to understand that the images you get out of an AFM depend on the interaction between your probe and your sample, and thus, they will be a combination of tip geometry and sample geometry.

The fact that on an AFM the generated image is a convolution of tip and surface geometry (and feedback parameters, but we are going to asume them ideal here), means that you will always need to interpret the result to reconstruct the original surface. Using a sharp tip means less interpretation, but still there will be cases where the tip sidewalls are convoluting with vertical steps, or where overhanging structures create a shadow. If your tip is blunted or if it is contaminated or broken (usually referred as "double tip"), then the effort to reconstruct the original image will be significant or plain simply impossible.

,Can I learn how these artefacts look like without having to image all types of surfaces and without having to blunt tips?

Yes, using Gwyddion. You can generate artificial surfaces similar to your samples, you can also generate different tip shapes, and most important, you can simulate the image resulting from the tip-sample interaction.

How to generate surfaces? We showed how to do that in:

FridayAFM - Particle detection

FridayAFM - Neural networks and Gwyddion

How to generate tips to use with the generated images?

1. You generated the surface.

2. Click on the image to select it (this will dictate the pixel size and pixel count on the image of the generated tip). Then navigate to the model tip menu Data Process>SPM Modes>Tip>Model Tip.

3.  The tip modeling menu is quite simple, it lets you select a geometry for the the tip and preview it. Usually a conical shape is a good approximation, as even triangular tips tend to end in a conical shape. If you are not sure of which parameters to use, check the AFM probe manufacturer website, they tend to include geometrical information about the probes they sell.

4. After generating the tip shape, to simulate how it will interact with your surface, click on the surface image and then navigate to 

Data Process>SPM Modes>Tip>Dilation.

5. The dilation menu is simple, it lets you choose an image to act as a tip shape. The list include only images compatible with your selected surface. This means that the pixel size match, and that the tip image is smaller than the surface image.

6. If your generated tip is not on the menu, it might mean that you need to resample your tip image to match the pixel size of your surface (Data Process>Basic Operations>Resample). Or that you need to generate a completely new tip image because it is larger than your surface image. Note that you can use the dilation menu with real surface data and see what will happen when your tip gets blunted on the surfaces you typically image.

7. The new image generated will be the result of your tip-sample interaction.

So. Lets see how this tip convolution process affects several different surfaces (I choose a range of surfaces which I think are a good representation of what you might have in your samples).

The first image I choose (see below) is a porous surface, typical of etching process. This is a sample that easily blunts tips, hence identifying tip-blunting here is very useful.

Using a conical shape tip and varying its radius we can see that at the beginning there isn't too much difference with the original data, but as the radius increases the holes become smaller and circular, until eventually the tip can no longer penetrate into the holes and the image looks like formed of bumps.

In general, sharpness and roundness of holes could be a good indicator of tip artefact in this case.

What will happen if the tip is triangular?

The answer is not too much more (see below). Because of the geometry of this sample (and this might not be true to other samples), there is not much difference between a triangular or a blunted tip. In this case the "radius" parameter is almost equivalent but not completely, thus wh for the same value the triangular tip images seem sharper.

Notice that once the tip can no longer enter the holes, the images are identical.

Ok, and what if the tip is contaminated or broken? What we will see? Generating a contaminated tip has more variables, because it can have 2, 3 apexes, one can be sharp, the other not, they can be close together, they can be far, one conical, the other triangular, one can be taller than the other...

So, I generated 3 contaminated tips and hopefully they will give you a glimpse of what might happen in a case of "double tip", but results here might vary dramatically (see below).

The "double tip" result (top part of the image below), shows what is a typical image of a broken and large tip, the image consists in repetitions of the image of the probe itself. In general this is easy to spot because the  same structure repeats over and over with the same dimensions and orientation. This is extremely rare unless the surface was specifically built that way.

The contaminated tip results (bottom of the image below), demonstrate that if the tip size is smaller or comparable to the features seen in the sample, the resulting image could (to certain point), resemble the original. Here in this case, without knowing the original image, could be difficult to identify the artefacts (we will see cases where it is not the case). 

The second image I choose (see below) is a flat surface, typical of glass, silica, lenses... It is one sample where it is hard to identify artefacts because if you blunt your tip when landing on the surface, then the blunted tip image shows no especial distinctive features (at least for conical tips).

However, (see below), the situation changes with a triangular tip. In this case a blunted tip produces images of itself that are triangular and oriented, which is a quite unnatural surface texture and thus easy to identify.

Similar with "double tips" (see below), the resulting images show features that are hard to encounter in nature and have all the same size and same orientation.

The porous silica case is a good example to explain a good way to identify if the tip is blunted, broken or contaminated. If you rotate the sample (physically in respect to the scanner), the artefacts remain with the same orientation, meaning that are due to the tip (which didn't rotated), not to the sample, which rotated.

The third image I choose (see below) is a flat surface with holes, typically these are the type of features you will encounter on a reference grid, which most AFM systems have included among the tools delivered with the system.

Here the blunting of the tip is not very obvious, however, if the dimensions of the features are known, it is a sample where measuring the sharpness of the tip is relatively easy. Unfortunately, this is one of the cases where conical and triangular tips produce very similar results (both difficult to grade the level of tip blunting).

On the other hand(see below), tip contamination generates double steps making the image like double or "shaded". This is a very easy to identify artefact, and thus in most situations it is recommended to image the reference grid if there are doubts about the state of the tip.

The fourth image I choose (see below) is covered in nanoparticles, typically spherical is the most common feature seen in AFM images, for instance contamination on the sample surface usually comes as small nanoparticles. Unfortunately, blunting of conical tips is hard to identify as the nanoparticles are also round, so unless the size of the nanoparticles is well known in advance, there is no way of telling if the tip has been blunted.

On the other hand (see below), triangular tips tend to make the spheres look non spherical when blunted, and the additional features are all aligned along the same direction.

The case of contaminated or double tips (below) is similar to the triangular, they introduce additional features all aligned along the same direction. In the case of double tips the identification might be more difficult, but can also be described as a repeating pattern aligned along a specific direction.

The fifth image I choose (see below) is composed of staked flakes, typically flakes are found in 2D materials. In this case, both conical and triangular tip blunting are difficult to identify.

As mentioned, same for triangular tips (below).

However, luckily for us, tip contamination or double tips are easy to spot as they produce steps only on certain edges (see below).

The sixth image I choose (see below) is composed of rings, this pretends to resemble self assembled proteins, such as DNA origami. Usually these objects have one well defined dimension, which can be used to track tip sharpness, as otherwise, there are no clear indicators of tip blunting for either conical or triangular tips.

As mentioned, no clear indicator for triangular tips either (see below), unless a critical dimension is known.

But in the case of double tips (see below) there are shadows, and contaminated tips produce double images along specific directions, making the identification of artefacts very easy (of course assuming one knows the shape of the self assembled structure)

The seventh, and last image, I choose (see below) is composed of fibers, this can represent collagen, but also certain nanolithography structures. The most visible artefact is that the tip sidewalls create a halo around the fibers.

This is the same for triangular tips (see below).

For contaminated and double tips the result is different, but also easy to identify. Parallel fibers are extremely rara, and thus have to be artefact. Sidewalls tend to be more pronounced in one direction, but identifiable.

Let's recap. Being able to grade properly the quality of the acquired data is extremely important, it might mean the difference between having material for a publication or walk away from the instrument empty handed. Here I showed you how to use Gwyddion to simulate several different tip artefacts so you are trained for when they occur. Is this enough? Absolutely not, there is always something you will not be prepared for, but the example surfaces we covered here are the most common types of surfaces, so it is a good start (specially if you think about the combination of several features). Also remember that the fact that parts of your image have artefacts doesn't mean the image is not valid, depends on which part of the image is relevant and where are the artefacts.

I hope you find this useful, entertaining, and try it yourselves. Please let me know if you use some of this, and as usual, if you have suggestions or requests, don't hesitate to contact me.