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CSC@Lunch Seminar Series

We share a weekly seminar series with the Warwick Centre for Predictive Modelling (WCPM). Seminars are held from 1-2 pm on Mondays during the university term. Nominations for speakers are welcome. Please contact James Kermode or Peter Brommer with suggestions.

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  • CSC at Lunch
 
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Mon, Feb 26, '18
13:00 - 14:00
Vikram Gavini (Michigan)
WCPM (D2.02)

Large-scale real-space electronic structure calculations

In this talk, the development of a real-space formulation for Kohn-Sham density functional theory (DFT) and a finite-element discretization of this formulation [1,2], which can handle arbitrary boundary conditions and is amenable to adaptive coarse-graining, will be presented. In particular, the accuracy afforded by using higher-order and enriched finite-element discretizations, and the efficiency and scalability of the Chebyshev filtering algorithm in pseudopotential and all-electron Kohn-Sham DFT calculations will be demonstrated. Further, the development of a subquadratic-scaling approach (in the number of electrons) based on a subspace projection and Fermi-operator expansion will be discussed [3], which will be the basis for the future development of coarse-graining techniques for Kohn-Sham DFT. The developed techniques have enabled, to date, pseudopotential calculations on ~10,000 atoms, as well as all-electron calculations on systems containing ~10,000 electrons.

  • [1] P. Motamarri, M.R. Nowak, K. Leiter, J. Knap, V. Gavini, Higher-order adaptive finite-element methods for Kohn-Sham density functional theory, J. Comp. Phys. 253, 308-343 (2013).
  • [2] B. Kanungo, V. Gavini, Large-scale all-electron density functional theory calculations using an enriched finite element basis, Phys. Rev. B 95, 035112 (2017).
  • [3] P. Motamarri, V. Gavini, A subquadratic-scaling subspace projection method for large-scale Kohn-Sham DFT calculations using spectral finite-element discretization, Phys. Rev. B 90, 115127 (2014).
Mon, Mar 5, '18
13:00 - 14:00
Charlotte Deane (Oxford)
Physical Sciences (PS0.17)

Biologically inspired de novo protein structure prediction

Protein structures can elucidate functional understanding, explain disease mechanisms and inform drug design. However, experimental structure determination is costly, and technically difficult. However, while the three-dimensional structure of proteins is difficult to obtain amino acid sequences are easily available and far outnumber solved structures. There are two main methods for protein structure prediction template based and de novo. Current de novo protein structure prediction methods are heuristics limited by the enormous search space, with successful prediction largely restricted to small, single domain proteins.
The three key components of most de novo methods for protein structure prediction are the fragment library, the “energy” function and the search method. In this talk I will give an overview of my groups work on improving each of these stages. Firstly, describing the development of a novel fragment library Flib that uses predicted secondary structure to determine library generation strategy [1]. Secondly, giving a comparison of the different co-evolution contact predictors in terms of their ability to improve protein structure prediction [2]. Finally demonstrating how sequential prediction approaches using SAINT2 can improve both search heuristics and final model quality [3].

  • [1] Saulo H P de Oliveira, Jiye Shi, Charlotte M Deane, Building a better fragment library for de novo protein structure prediction, Plos One, 2015, 10(4), e0123998
  • [2] Saulo H P de Oliveira, Jiye Shi, Charlotte M Deane, Comparing co-evolution methods and their application to template-free protein structure prediction, Bioinformatics, 2017; 33 (3): 373-381.
  • [3] Saulo H P de Oliveira, Eleanor C. Law, Jiye Shi, Charlotte M. Deane, Sequential search leads to faster, more efficient fragment-based de novo protein structure prediction, Bioinformatics, 2017, btx722
Mon, Mar 12, '18
13:00 - 14:00
Laura de Sousa Oliveira (Warwick Engineering)
WCPM (D2.02)

Atomistic modelling of phonon transport in advanced materials

Heat transfer is ubiquitous in both naturally occurring and engineered materials. In the last few decades, progress has been linked to the ability to manipulate and control materials at increasingly smaller length- and time-scales. It follows that an atomistic-level understanding of thermal transport is often essential in predicting and controlling heat transport in materials and devices. In the work presented, equilibrium classical molecular dynamics and density functional theory are used to investigate phonon transport in defect laden nuclear materials (graphite and UO2) and Si, and in flexible metal–organic frameworks. Finally, I will discuss a new approach to quantify — on-the-fly — the uncertainty on transport properties computed using equilibrium molecular dynamics (i.e. with the Green–Kubo formalism). This method is based on recognizing that the integrated noise of the autocorrelation of the equilibrium fluctuations grows as random walk.