AUSTRALIAN FRONTIERS OF SCIENCE, 2003
Canberra, 31 July to 1 August 2003
Advanced
materials synthesis
by Professor Marcela Bilek
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Marcela Bilek was appointed Professor of Applied Physics at the University of Sydney in November 2000. She holds a PhD in Engineering from the University of Cambridge, UK, a BSc (Hons) in Physics from the University of Sydney and an MBA degree from the Rochester Institute of Technolgy, USA. Prior to her present appointment she held a visiting professorship at the Technische Universitat Hamburg-Harburg in Germany and a research fellowship at Emmanuel College, University of Cambridge, UK. She also worked for a number of years as a visiting research scientist at the Lawrence Berkeley Laboratory, University of California, USA. Aside from her academic experience, Marcela has also spent time working in industry as a research scientist at Comalco Research Centre, Melbourne, and at the IBM Asia Pacifc Group Headquarters in Tokyo. Her main research interest is in plasma-based thin film deposition and surface modification. She was awarded the Malcolm McIntosh Prize for Physical Scientist of the Year in 2002. |
This first session is on advanced materials. Essentially, the field that I work in is often labelled materials science, and to some extent it is already an interdisciplinary field. It involves some chemistry, some engineering and also some physics. I am from the physics side, and in particular I work with plasmas, using them to modify materials and to create new materials.
I am just going to walk you through what has been going on in that field a very little bit of the history and then what is current research and also where it is going. There have been some interesting developments.
An outline for the presentation goes something like this. First of all we have some traditional approaches of what has been done in the past with materials. We have always created them by simple alloying, just mixing of materials that already exist and by chemical methods.
More recently there have been some advances in computer technology and also in the algorithms that allow us now to compute structures of materials and their properties in computers. That has been a tremendous advance for the field. In fact, there have been many new materials predicted in that way which we have then had the challenge of manufacturing or fabricating in the lab.
Another exciting area is that we have developed techniques now and this is work that is currently under way in our group to stabilise new phases, phases that do not exist at the sorts of pressures and temperatures in our normal environment, but we have developed mechanisms for stabilising those and being able to then utilise them. So I will talk a little bit about that.
Finally and this is, I think, the cutting edge at the moment in the materials game people are realising that there are special properties associated with not just the chemistry of a material, as in what elements are in there, but the way that it is structured. With this very fine structure, if you go down to the nanoscale, you start accessing effects which involve quantum mechanics and they produce quite different behaviours to the same materials unstructured in this way. So this structure is what we are now looking at, and we are trying to develop techniques of creating materials that have this fine structure and understanding how that structure leads to special properties. So I will try and walk you through a little bit of that as well.
The traditional approaches have just been blending materials, and the means of doing that have been both physical and chemical. The applications of interest in my particular field are, particularly, coatings to modify surfaces. Examples of applications there are materials that we implant into the body in, say, biomedical devices you want to put a coating on that: if it is in contact with blood, for example, you want a low-friction coating that does not cause clotting; it should also be biocompatible and in an industry, for example, for cutting tools you need a coating that will not wear.
Even though I call this 'traditional approaches', it is certainly not over yet. There are a lot of new alloys that we have not even looked at and have not explored, so there is still work ongoing in that field, in this area.
Click on image for a larger version of figure 1
Computer prediction of materials has really enhanced what we can do, and also in predicting what alloys might be interesting to look at that we haven't yet looked at. Techniques such as density functional theory (DFT) enable us to simulate down to the quantum mechanical behaviour of the electrons. The picture at the bottom, in the colours, shows you a simulation done at our university showing electron clouds, or electron density patterns the hotter the colour, the higher the density. There is a carbon atom in the centre of this orange circle, and a silicon one in the blue circles. The green stuff is the electron clouds that form the bond. So we can actually visualise chemical bonds in the computer now. The accuracy of techniques like this DFT, however, make it quite slow if you want to do large systems or any long timescale effects, so there is a trade-off there.
We have also developed quite a lot of computer codes which do not go down to the quantum mechanical calculation of actually calculating the electron clouds, but using the predictions of these models we have developed empirical potentials which are much faster and enable us to simulate long timescale events like the growth of a thin film material you can see that happening on the screen now from a plasma. You can see each of the atoms coming in. We are growing amorphous carbon on diamond in this particular simulation.
You can see we are growing diamond for a little distance through, and now it is starting to change over to the green colour coding, which is the amorphous or disordered carbon phase. That is quite an interesting thing, because we could grow epitaxially, so the system grew epitaxially to some point, until the amount of defects gets to a certain level and then the lowest energy configuration is no longer the epitaxial bonding, or the diamond-like bonding, and it flips over to the amorphous carbon. You find that if you change the temperature and this again perfectly simulates reality if you go higher with temperature you can continuously grow epitaxial diamond. So we are quite happy with that simulation. It turns out that it predicts reality very accurately.
This is really an important development for us in this field: the ability to simulate things in the computer, and actually simulate them very accurately down to the quantum mechanics of the electronic bonding.
There is still progress happening there, and the way forward there lies not only in waiting for the computer scientists to increase the speed of the machines, but also in ourselves developing algorithms that can access the longer timescales. That is very important as well, because the computer speed itself will not enable us to get to the sort of phenomena that are interesting over long timescales, like diffusion, for example, in materials.
Click on image for a larger version of figure 2
This is a slide to try and give you a bit of an idea of what I mean by stabilisation of metastable phases. In the system of boron nitride, the hexagonal phase which is this one over here, similar to graphite, except you have boron as well as nitrogen atoms in the structure is the stable phase at low temperatures and pressures that we are used to. If you go to higher pressures you find that this cubic boron nitride and the analogue there for carbon is diamond is stable. So this is what we call the metastable phase.
Now, if we use a plasma to grow the material as a thin film, we can actually generate something called compressive stress, or intrinsic stress. The way to think of that is that as you are growing the material, you push in more atoms than would like to be there at this low pressure. By doing that and then cooling it rapidly, you force them to stay there. So you have actually built up a system that is under a high pressure, the pressure sustained by the substrate that is the material that you are growing it on, because the substrate applies a force that pushes these atoms together. And so the material grown as this thin film thinks it is under a high pressure. It then decides to go into the stable phase at that high pressure.
You can see that here [at right of slide]. This is an experimental curve that was taken with my colleagues in Germany, where I have just been for two months, and you can see that initially, when we start the growth, what we have here is the stress this is the stress characteristic of the hBN phase. As the stress increases a little bit, we nucleate cubic boron nitride that is the diamond-like material and here at the very high-stress regime, so this is equivalent to a material that thinks it is under very high pressure, we can fabricate this very hard, diamond-like material called cubic boron nitride (cBN). So that is the stabilisation of metastable phases.
Click on image for a larger version of figure 3
This is a very exciting and, I think, the most interdisciplinary of the areas in materials science at the moment: exploring the structure at the nanoscale and what effect that has on materials properties. This is an example from Nature. Nature is actually very good at this, as you will see in a lot of biological examples if you look closely. I will show two here. The first one is the abalone shell. You find that the structure is actually made up of some very fine layers in this case they are little plate-like layers that are stacked together. This is essentially a ceramic-like material, but in between those layers there are very, very fine protein layers which you cannot see clearly in this diagram or even here in between all these layers. Scientists still do not fully understand how this structure works, because you have a very brittle material interfaced with this very soft material, and it turns out to be extremely tough. If you had the hard, brittle material on its own, you could easily crack it. But with the soft material as well, it becomes very, very tough.
On examination of the fine structure this is electron diffraction patterns, and Dougal will talk a bit more about those and the electron microscopy used to get these results if you look closely you can see that the interface between the layers has fine asperities on it. They seem to play a key role in that toughness, in that they limit the sliding of the platelets, one over the other.
So looking at Nature's structures like this and trying to understand what it is about the way they are put together that gives them these incredible properties in this case the hardness and the toughness will enable us, hopefully, to manufacture similar things in cysteinic form that provide the same sort of properties for us.
Click on image for a larger version of figure 4
Another example from Nature is the photonic crystal. In this case it comes from a butterfly's wing. This is a butterfly that has a green colour in this portion of its wing, and if you look at the wing scales from this butterfly this is again an electron microscope picture here, and here it is enlarged from this region here [at right] what you find is this section here that you see is a crystal, a photonic crystal, and it is made up of structures that repeat. It interacts with light in such a way that it reflects just the green light, and that is why it looks green. The other light passes through. So that is another very interesting biological example.
We would like to make structures like this, but first of all we need to understand them, we need to understand how they work, and so that is part of the work that is currently under way. And then we need to develop methods for making them.
Broadly speaking, there are two ways that you can go to try and make this kind of a nanostructured material. One is the way that the electronics industry has been perfecting, going down to smaller and smaller scales over the past decades. I have just called that nanomachining, for want of a better term. What I mean there is that you start with a large system like a silicon wafer and then you etch holes in it and you dig pits and you draw lines and you put little bits of deposited material on it, and wires and so on. That is the traditional way we think of building things. That is an option, and I will talk a little bit about some of the things that are happening in research there. Generally, to try and get to those very fine scales, we use energetic ions instead of machining drills and so on. So ions do the drilling, the creation of the pits and so on, and they are energetic ions. We use a process called sputtering to remove material. Chemical etching is another way to do it in a wet form. You can remove material if you mask off certain areas and then etch pits.
But actually, if you try and push this to smaller limits, you find that it becomes more and more impractical. To try and go to the nanoscale you end up having to manipulate single atoms. This could be quite an expensive way of constructing something that you might want to be a consumer item. So let's look at the other alternative.
This is called self-assembly. We want to set up the constituents of the system in such a way that when we put them together they interact so that they naturally build the system that we are looking for. They just combine automatically. Essentially, in physics terminology I hope this doesn't confuse too many people; we can have some explanations in question time but I am sure you are all familiar with this concept the idea is that these particles interact with each other in such a way as to minimise the energy of that system, under constraints. These constraints are something that we can apply externally to manipulate the system. We can put some constraints on and then the system will form in a slightly different way. I will show an example of that.
Here are a few examples that happen quite naturally and that we are probably quite used to: segregation in multielement alloys that is an attempt of the system to minimise its energy and development of pores and voids in some materials, again a surface energy versus volume energy trade-off. Multilayered thin films are another, and that is because the constraints are changed by changing the composition during the growth; and growth of nanoparticles and nanoclusters in, say for example, a plasma, are also a result of energy minimisation.
Click on image for a larger version of figure 5
Here are some examples of the nanomachining concept. In these three examples we get a solid piece of silicon and we cut and drill holes in it, using a masking technique to protect the areas we do not want to drill into and then energetic ion beams or plasmas to drill out, for example, these deep pits. Then we can also use a plasma to apply some coatings on the surface. We can actually put on a material that condenses. A lot of research goes into making these so deep and filling them.
Here [in the third picture] you can also see that you can make quite complex structures, down to very fine scales. This is a pollen grain, and a gear wheel. This is done in silicon as well.
Click on image for a larger version of figure 6
If you want to push this kind of approach to the limits, you can do this sort of thing using an atomic force microscope. You can actually pick up atoms off a silicon surface here they are, you can see them and move them, atom by atom. Here somebody has written a monogram, doing just that. It is kind of a painful process, though, if you want to try and make materials for consumer devices that are fairly cheap to buy. So let's look at the other approach, self-assembly.
In this one we are looking for components that interact with each other and with their environment, and we want to set it up so that when the system minimises its energy we get the structure that we want. Here are some examples.
Click on image for a larger version of figure 7
This is a simple one, just to illustrate the concept. Here we have three magnets. This system will self-organise when there is no magnetic field present I am assuming that they are also fixed in the centre, so they are going to rotate about this axis. This is what happens: they line up, because their magnet fields interact with each other and the minimum-energy configuration is north-south for these poles. What happens if I change the external constraints, if I put on a magnetic field here? North is upwards. Well, now the system will line up with the external magnetic field. So that is an example that you are all quite familiar with, just knowing what fridge magnets do, I guess, and that you can relate to, illustrating what we mean by self-organisation.
Click on image for a larger version of figure 8
Here are some examples that we are hoping to apply to technology. This one shows carbon nanotubes. These are grown from a plasma, a simple DC discharge, and they are grown in these patterns. You can see here this is from Cambridge. They have written CNT@Cambridge [i.e. Carbon nanotubes @ Cambridge]. These are all oriented nanotubes, standing up. The way they have done that is using a nickel catalyst, and they have patterned the catalyst onto the silicon substrate. The nanotubes grow it is energetically favourable for them to grow with this catalyst, or at the location of the catalyst. You can control the width and the length of them by simply changing the thickness of the nickel layer that you use to initiate the growth.
Click on image for a larger version of figure 9
Here is an example from our own laboratory. This is multilayered film, very fine layers 17nm for every pair. It is a titanium/titanium nitride stack, a soft layer/hard layer stack, grown on a silicon substrate. Dougal McCulloch will talk a bit about the imaging techniques that we used to get these maps to show you the layers. These formed by simply changing the plasma composition periodically and letting the system grow its layers and minimise the energy. The interesting thing about them is looking at the interfaces and trying to understand what goes on there, and how that structure depends on what is going on in the plasma system at the time of growth.
Click on image for a larger version of figure 10
Here is another example, from my German colleagues. What they have done is to use an energetic ion beam on angle to the silicon substrate, and it is etching into the substrate. At the same time, they rotate the substrate. The idea here is you can imagine the wind blowing on the sand dunes, you get waves. Well, if you rotate the sand dunes at the same time, you can make some very interesting self-organised patterns. And with temperature there are significant changes here. We do not understand all of them, but this is also a self-organisation phenomenon.
Click on image for a larger version of figure 11
Finally, we are getting very interested in interfacing a lot more with the biologists, because there are a lot of interesting things that we think we can contribute to biology. Here is an example from my colleagues at Lawrence Berkeley Laboratory. What we have done here is to put a special type of carbon onto a silicon wafer. We find that we can grow neurons; if we put neurons onto this surface they grow preferentially on that carbon and they stay right away from the substrate material. You can see that they have done an LBNL pattern with the neurons. So there are some interesting things that we think we can do with the biological materials. This [at bottom right] is an example for a DNA array. The idea here is that you put material onto the surface in this case it will be biological material that specifically interacts with the DNA that you are looking for. Each of the spots means a certain DNA in the system.
The most interesting and promising systems at the moment are the complex ones, the ones that we are looking at self-organising and with the fine structure. The processes involved there are chemical and physical, as well as biological if we are looking at ones that involve biomolecules. The inputs and understanding from all these fields are going to be required, so there is a real need for interdisciplinary work there. Also, let's not leave out the engineers and the computer scientists, because that technology has played a crucial role in the past and I think will continue to do so in our field.