Amanda Barnard

Dr. Amanda S. Barnard is a theoretical physicist working in predicting the real world behavior of nanoparticles using analytical models and supercomputer simulations. Barnard is a pioneer in the thermodynamic cartography of nanomaterials, creating nanoscale phase diagrams relevant to different environmental conditions, and relating these to structure/property maps. Her current research involves developing and applying statistical methods and machine/deep learning in nanoscience and nanotechnology, and materials and molecular informatics. In 2014 she became the first person in the southern hemisphere, and the first woman, to win the Feynman Prize in Nanotechnology, which she won for her work on diamond nanoparticles.

Contents

• Biography
• Qualifications
• Career highlights awards fellowships and grants
• Research highlights
• References

Dr. Barnard is currently based in Australia as Office of the Chief Executive (OCE) Science Leader at the Commonwealth Scientific and Industrial Research Organisation (CSIRO), based at Data61.

Biography

In 2001, she graduated with a first-class honours science degree from the Royal Melbourne Institute of Technology (RMIT), majoring in applied physics. Barnard received a PhD in 2003 from RMIT for her computer modelling work predicting and explaining various forms of nanocarbon at different sizes. Following her PhD, Barnard served as a Distinguished Postdoctoral Fellow in the Center for Nanoscale Materials at Argonne National Laboratory (USA). She also held a senior research position as Violette & Samuel Glasstone Fellow at the University of Oxford (UK) with an Extraordinary Research Fellowship at The Queen's College. Dr Barnard has been with CSIRO since 2009.

Qualifications

2003 Doctor of Philosophy (Physics), RMIT University

2001 Bachelor of Science, First Class Honours (Applied Physics), RMIT University

Career highlights, awards, fellowships and grants

2017 Woman of Achievement, Black & White Foundation, Australia

2014 Feynman Prize in Nanotechnology (Theory)

2014 ACS Nano Lectureship (Asia/Pacific), American Chemical Society, USA

2010 IEEE Distinguished Lecturer Award, IEEE, South Australia

2010 UNSW Eureka Prize for Scientific Research, Australian Museum

2010 Frederick White Prize, Australian Academy of Science

2009 Malcolm McIntosh Prize for Physical Scientist of the Year

2009– Leader of the Virtual Nanoscience Laboratory, CSIRO Materials Science and Engineering

2009— Queen Elizabeth II Fellowship, Australian Research Council

2009 Mercedes-Benz Australian Environmental Research Award, Banksia Environmental Foundation

2009 Young Scientist Prize in Computational Physics, International Union of Pure and Applied Physics

2009 JG Russell Award, Australian Academy of Science

2009 Future Summit Leadership Award, Australian Davos Connection

2008 L'Oréal Australia For Women in Science Fellowship

2008 Alumnus of the Year, RMIT University

2008 Inaugural Future Generation Fellowship, School of Chemistry, University of Melbourne

2005–2008 Extraordinary Junior Research Fellowship, Queen's College, Oxford, UK

2005–2008 Violette & Samuel Glasstone Fellowship, Department of Materials, University of Oxford, UK

2004 Innovation Award (Student Category), RMIT University

2004 University Research Prize, RMIT University

2003–2005 Distinguished Postdoctoral Fellowship, Center for Nanoscale Materials, Argonne National Laboratory, USA

Research highlights

Identified the link between nanomorphology and the environmental stability of nanomaterials, and how it influences reactivity and potential "nano-hazards"

Developed a new technique for investigating the shape of nanomaterials as a function of size, temperature or chemical potential, able to include experimentally realistic structures and chemical environments

First researcher to report investigations into the effect of shape on size-dependent phase transitions in nanomaterials

Discovered the first example of anisotropic (facet-dependent) surface electrostatic potential in a homoelemental nanomaterial, resulting in dipolar or multipolar interactions in a non-polar material

Leader in statistical nanoscience and the use of statistical analysis and machine learning to predict the properties of diverse and complex ensembles of nanoscale materials.