High-performance computing for materials design to advance energy science

Abstract

The development of new materials typically requires an iterative sequence of synthesis and characterization, but high-performance computing (HPC) adds another dimension to the process: materials can be synthesized and/or characterized virtually as well, and it is often an overlapping quilt of data from these four aspects of design that is used to develop a new material. This is made possible, in large measure, by the algorithms and hardware collectively referred to as HPC. Prominent within this developing approach to materials design is the increasingly important role that quantum mechanical analysis techniques have come to play. These techniques are reviewed with an emphasis on their application to materials design. This issue of MRS Bulletin highlights specifi c examples of how such HPC tools are used to advance energy science research in the areas of nuclear fi ssion, electrochemical batteries, photovoltaic energy conversion, hydrocarbon catalysis, hydrogen storage, clathrate hydrates, and nuclear fusion.

Minimization Principles for the Linear Response Eigenvalue Problem I: Theory

“…In computational quantum chemistry and physics, the excitation states are described by the random phase approximation (RPA), a linear response perturbation analysis in the time-dependent density functional theory. There has been a great deal of recent work on and interest in developing efficient numerical algorithms and simulation techniques for excitation response calculations of molecules for materials design in energy science [9,21,28,29].…”

Trace minimization method via penalty for linear response eigenvalue problems

“…Consequently, traditional algorithms for the Hamiltonian eigenvalue problem (e.g., [4,9]) would be ineffective, as they are usually designed for small-scale problems. A large number of recent studies (e.g., [1,2,8,13,16,17,18,19,21]) have been concerned with the development of efficient numerical algorithms and simulation techniques for excitation-response calculations of molecules for materials design in energy science. These algorithms have been reported to be efficient for (1) (e.g., [2]).…”

Density functional theory calculations of electronic structure and thermoelectric properties of K‐based double perovskite materials

“…By changing one material of the system, we can affect the material properties and materials often exhibit novel crystal phases and new behaviors. Computational methods have made a substantial impact on physics of the materials 13–16 . This has provided important complementary data to experiment.…”