EPSRC Centre for Doctoral Training in Computational Methods for Materials Science

Lead Research Organisation: University of Cambridge
Department Name: Physics

Abstract

Moore's Law states that the number of active components on an microchip doubles every 18 months. Variants of this Law can be applied to many measures of computer performance, such as memory and hard disk capacity, and to reductions in the cost of computations. Remarkably, Moore's Law has applied for over 50 years during which time computer speeds have increased by a factor of more than 1 billion!

This remarkable rise of computational power has affected all of our lives in profound ways, through the widespread usage of computers, the internet and portable electronic devices, such as smartphones and tablets. Unfortunately, Moore's Law is not a fundamental law of nature, and sustaining this extraordinary rate of progress requires continuous hard work and investment in new technologies most of which relate to advances in our understanding and ability to control the properties of materials.

Computer software plays an important role in enhancing computational performance and in many cases it has been found that for every factor of 10 increase in computational performance achieved by faster hardware, improved software has further increased computational performance by a factor of 100. Furthermore, improved software is also essential for extending the range of physical properties and processes which can be studied computationally. Our EPSRC Centre for Doctoral Training in Computational Methods for Materials Science aims to provide training in numerical methods and modern software development techniques so that the students in the CDT are capable of developing innovative new software which can be used, for instance, to help design new materials and understand the complex processes that occur in materials. The UK, and in particular Cambridge, has been a pioneer in both software and hardware since the earliest programmable computers, and through this strategic investment we aim to ensure that this lead is sustained well into the future.

Planned Impact

Computing, data and communications infrastructure have transformed modern life. They all require software, security and trained personnel to work effectively and it has become common to use the term e-Infrastructure to refer to the whole of this interconnected ecosystem. E-Infrastructure has become a major contributor to advances in science and technology and it is clear that no industry will be able to compete internationally unless it exploits e-Infrastructure at highest level. The proposed EPSRC Centre for Doctoral Training in Computational Methods for Materials Science is focused on the development of new functionality in existing software, and even entirely new codes that will address challenges in materials that cannot presently be addressed. The UK is making large capital investments in e-Infrastructure but these investments will only achieve a fraction of their potential impact unless investments are also made in software development. The CDT will primarily focus on software development for materials science, which is itself, of course, extremely broad. However, the training provided in numerical methods, modern software development techniques and the exposure to present and emerging computational hardware means that the students will have the skilled set to work in any area of software after their PhDs. Given the universally acknowledge lack of highly trained personnel in software development one of our most important impacts will be in providing nearly 80 people who can apply this training in industry, including the very large number of UK software-based SMEs, or academia. The emphasis of the training and subsequent research project in the CDT is on development of innovative new methods for materials modelling and these will have impact in both academia and industry in further expanding the capability of materials simulation and the range of phenomena and processes that can be simulated and/or the amount of information that can be extracted from experiments. Thus we expect the CDT to have a significant impact across a very broad spectrum of disciplines.

Publications

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