Photo © Alban Kakulya
Nicola Marzari, who joined EPFL in 2011, does just that, by developing and applying to materials science powerful computational modeling techniques based on the fundamental principles of quantum mechanics. These "first-principles" calculations allow one to solve, rather than model, the exact behavior of materials starting from the atomic scale up, and thus do not require any prior knowledge or experimental input.
Materials at the centre of our daily lives
A
lmost every aspect of modern life involves materials and benefits from advances in materials modelling. Mobile phones, aircraft, power stations, fuels, medications, and much else that we now take for granted, all rely on materials.
In addition, many processes in the natural world, ranging from the growth of ice in the upper atmosphere all the way to diseases caused by protein mis-folding also involve the properties of materials. Many of today's challenges, such as climate change, energy production and healthcare, demand powerful methods for probing the properties of a vast range of materials.
Predictive modelling has now become a powerful tool, which can also deliver real value through application and innovation to the nano, chemical and process industries. It forms an essential part of the research and development effort of many of the world’s leading organisations and can be incredibly valuable for businesses. Simulation methods can be routinely used across industry to accelerate product development, increase efficiency, and provide fundamental understanding.
Quantum-mechanical simulations have become dominant and widely used tools for scientific discovery and technological advancement; since they are performed without any experimental input or parameter they can streamline, accelerate, or replace actual physical experiments. This is a far-reaching paradigm shift, substituting the cost- and time-scaling of brick-and-mortar facilities, equipment, and personnel with those, very different, of computing engines.
Nevertheless, computational science remains anchored to a renaissance model of individual artisans gathered in a workshop, under the guidance of an established practitioner. Great benefits could follow from rethinking such model, while adopting concepts and tools from computer science for the automation, management, preservation, analytics, and dissemination of these computational efforts.
N. Marzari, Materials modelling: The Frontiers and the challenges, Nature Materials 15, 381 (2016)
N. Nosengo, "The Material Code", Feature Story, Nature 533, 22 (2016).
The conference
During this conference, Nicola Marzari will present her point of view on the current state of knowledge in the field, its power and limitations, as well as the role and possibilities of high throughput computing (HTC, rather than HPC), open-source codes and workflows, and large data available on demand.
Free registration requested by email before 16 May 2018 via email address: IL.Piperakis@uliege.be
Biography
"Nicola Marzari has a "Laurea" degree in Physics from the University of Trieste (1992), and a PhD in physics from the University of Cambridge (1996).
He moved to the US as an NSF postdoctoral fellow (Rutgers University, 1996-98), and then as a research scientist first at the Naval Research Laboratory (1998-99) and Princeton University (1999-01).
In 2001, he was named assistant professor in computational material science at the Massachusetts Institute of Technology, where he was promoted to associate professor in 2005, and named Toyota Chair of Materials Engineering in 2009. After 10 years at MIT, Nicola Marzari joined the University of Oxford, as its first Statutory (University) Professor of Materials Modelling, and as Director of the Materials Modeling Laboratory.
He joined EPFL in 2011, where he heads the laboratory for Theory and Simulation of Materials."
Sources
