Teachers Notes - Dr Amanda Barnard

Computational physicist

Contents

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Introduction

Dr Amanda Barnard was interviewed in 2010 for the Interviews with Australian scientists series. By viewing the interviews in this series, or reading the transcripts and extracts, your students can begin to appreciate Australia's contribution to the growth of scientific knowledge.

The following summary of Barnard’s career sets the context for the extract chosen for these teachers notes. In the extract, Barnard describes nanoparticles, and how she examines them using computational modelling. Use the focus questions that accompany the extract to promote discussion among your students.

Summary of career

Amanda Barnard was born in 1971. In 2001, she graduated from the Royal Melbourne Institute of Technology (RMIT) University, with a first-class honours science degree, majoring in applied physics. Barnard was awarded a PhD (2003) from RMIT for her computer modelling work, which predicted and explained the various forms of nanocarbon at different sizes.

Barnard then began a distinguished postdoctoral fellowship at the Center for Nanoscale Materials in Argonne National Laboratory, USA (2003-05). During this fellowship, Barnard investigated the different factors that affect the shape of titanium dioxide. From the USA, Barnard’s next position as a senior fellowship took her to Oxford. She was awarded a Violette & Samuel Glasstone Fellowship and an Extraordinary Junior Research Fellowship that allowed her to purse research at the University of Oxford, UK (2005-08). During this time, Barnard was using computer simulations to determine what environments were needed to engineer specific types of nanoparticles. This line of research led her to investigate the potential risks of nanoparticles outside the laboratory environment. This is an ongoing theme in her research. Since 2009, Barnard has been working as a research scientist at CSIRO Material Science and Engineering.

Barnard has been awarded many prestigious awards including; RMIT University Alumnus of the Year (2008), L’Oreal Australia For Women in Science Fellowship (2008), Australian Davos Connection leadership Award (2009), Mercedes-Benz Australian Environmental Research Award (2009), Malcolm McIntosh Prize for Physical Scientist of the Year (2009), Queen Elizabeth II Fellowship (2009), the University of New South Wales Eureka Prize for Scientific Research (2010) and the IEEE South Australia Distinguished Lecturer Award (2010), just to name a few. Barnard received the 2009 JG Russell Award and the 2010 Frederick White prize from the Australian Academy of Science.

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Extract from interview

Teeny tiny nano

For your PhD thesis, you looked at computational modelling of carbon nanostructures. Perhaps you can explain for us, what is a carbon nanostructure?

Yes, of course. First of all, it’s made of carbon and there’s a range of different structures that it can form. One very famous carbon nanostructure is the Buckminsterfullerene, which is 60 carbon atoms in the shape of a soccer ball. There is also a carbon nanotube, which is like a one-dimensional fibre as opposed to a little spherical, zero dimensional structure, with the same kind of chemical bonding. Then, if we change the chemical bonding, we can have a range of other types of carbon nanostructures such as little nanodiamonds, diamond nanorods and other types of hybrid structures. Nanodiamonds are just like the big, beautiful diamonds but millionths of a millimetre in size.

Just how small from carbon nanostructures? Perhaps you could give us a comparison of scale.

A nanometre is a millionth of a millimetre. To give us an idea, the head of a dressmaking pin is about a millimetre across; so that’s a million nanometres that will fit across the diameter of the head of a pin. Now, DNA is roughly about two to 12 nanometres in diameter, and most nanoparticles used in new technologies are about that size. So that’s about 3,000 times smaller than a red blood cell and about 10,000 times smaller than a strand of human hair.

Very small indeed!

Yes. We certainly can’t see them. Actually, the only way that we can see them is not with an optical microscope or with our eyes but with an electron microscope. We have to image them with electrons instead of with light.

Virtual experiments

How do you do your computer experiments? Do you have a special, big computer or is it something that I could do on my home computer?

Interestingly, a little bit of both. Some of the simulation work that I do uses massive super computers, and I need to use tens or thousands of CPUs all working as one to get the job done. The other type of work I do is theoretical, in terms of it being very mathematical, and the equations I can solve on a laptop.

How long does it take to run a computer simulation? Is it done in the click of a button?

Well, it depends upon what kind of structure or what kind of material I’m simulating. Sometimes it can happen in a couple of days or weeks; sometimes it will take months for one simulation to run, and you really don’t want to find that you’ve made a mistake when you get to the end.

No, or have a power failure.

And lose everything!

What can a computational experiment tell us that a wet lab experiment cannot?

There are a couple of different things that we can do in a super computer that we can’t do in a wet lab experiment in a test tube. One is that, in order for us to characterise a wet lab system during a process, we have to stop and then take stock of what’s happened. That is we stop the experiment and test it, stop the experiment and test it. We can’t continuously watch a mechanism or a process in situ throughout the entire evolution of the system. In a super computer, we can actually watch every little step along the way without having to continually stop and check how we’re going.

Another thing that we can do in computational experiments is to look at single particles. In a test tube there are millions and millions and millions of nanoparticles and it’s very difficult to isolate one and just look at its properties; in a super computer we can do that very easily. We can also do one other thing, and that is to look at all kinds of extreme environments that are dangerous for people to work in and dangerous for the lab, and in a super computer they’re perfectly safe; I never get any on me.

Focus questions

  • A coarse human hair is 0.018 millimetres in diameter. Convert this value into metres, centimetres, micrometres and nanometres.

  • What are the advantages of virtual experiments?

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Activities

Select activities that are most appropriate for your lesson plan or add your own. You can also encourage students to identify key issues in the preceding extract and devise their own questions or topics for discussion.

  • Nanoscience – working small, thinking big (Australian Academy of Science)
    This Nova: science in the news topic discusses the chemical and physical property changes of compounds in the nanoscale. Activities, further reading and useful sites sections are included.

  • How Small are Nanotubes? (Nanotechnology Activity Guides, University of Wisconsin, USA)
    In this activity students compare objects on the macro, micro and nano- scale to develop an appreciation for the scale of the nanometre. Student worksheet, handout and overhead transparencies are also available.

  • Build A Buckyball (Schlumberger Excellence in Educational Development, Schlumberger Ltd, USA)
    Instructions for making a paper model of a truncated icosahedron (the shape of the Buckminsterfullerene or buckyball).

  • Slush Rush (American Association for the Advancement of Science, USA)
    In this activity, aimed at children in years 3-5, students explore how computer models help us make decisions and predictions in science and business. Students use three internet based simulations; earthquake and tsunami animations and slushies for aliens, to understand the components and purposes of computer modelling. Student activity sheets are also available.

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Keywords

Buckminsterfullerene (buckyball)
computer modelling
computer simulation
nanoparticle
nanotube
super computer
virtual experiment

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