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DE-SC0020129: Toward exascale computing of electron-phonon couplings for finite-temperature materials design

Award Status: Active
  • Institution: The University of Texas at Austin, Austin, TX
  • UEI: V6AFQPN18437
  • DUNS: 170230239
  • Most Recent Award Date: 09/26/2023
  • Number of Support Periods: 5
  • PM: Graf, Matthias
  • Current Budget Period: 09/01/2023 - 07/31/2024
  • Current Project Period: 09/01/2023 - 07/31/2026
  • PI: Giustino, Feliciano
  • Supplement Budget Period: N/A
 

Public Abstract

Toward Exascale Computing of Electron-Phonon Couplings for Finite-Temperature Materials Design

F. Giustino, The University of Texas at Austin (Principal Investigator)

E. Kioupakis, University of Michigan at Ann Arbor (Co-Investigator)

E. R. Margine, Binghamton University-SUNY (Co-Investigator)

The overarching aim of this effort is to enable accurate, fast, scalable, and reproducible ab initio calculations of electron-phonon couplings for the design of advanced functional materials, and to make these tools widely accessible to the computational materials science community.

In semiconductors, metals, insulators, and superconductors, the vibrations of the crystal lattice can have a significant impact on their electronic properties. For example, under standard operating conditions, the electrical resistivity of semiconductors in microelectronic devices increases with temperature because electrons experience increased scattering from thermal vibrations of the atoms. This phenomenon leads to electronic devices heating up when performing intensive compute tasks, something that we are all very familiar with. At the microscopic scale, these processes can be understood in terms of electrons exchanging energy with the crystalline lattice in the form of vibration quanta called phonons. Beyond semiconductor devices, the coupling between electrons and phonons influences myriad other materials properties and functionalities, including the absorption of light in solar cells, the emission of light in LEDs, the dissipation of excess heat by thermal conductors, and even the entanglement of qubits in quantum computers. Therefore, the ability to compute electron-phonon couplings with predictive accuracy is key to design and develop a variety of advanced materials and devices for applications in energy conversion and storage, solid-state lighting, energy-efficient electronics, and quantum technologies.

Here, we will develop innovative ab initio methods, algorithms, and software to investigate an array of materials properties that are beyond the reach of existing computational methods; we will consolidate and expand the EPW code, a large open-source software project for calculating electron-phonon couplings and related materials properties; and we will progress toward exascale computing by harnessing the power of leadership-class DOE supercomputers. We will push the frontiers of high-performance computing of electron-phonon couplings for predictive materials design. We will develop advanced many-body approaches to investigate the formation, energetics, and dynamics of small and large polarons. We will develop Monte Carlo simulators and real-time solvers to predict the carrier transport properties of semiconductors under high-field and out-of-equilibrium conditions, as well as methods to investigate magneto-transport in topological materials. Furthermore, we will continue refactoring the EPW code to leverage many-core architectures and GPU acceleration on DOE supercomputers, and we will simplify the calculation workflows to enable more systematic investigations of electron-phonon couplings. We will strive to increase accessibility, transparency, and reproducibility of these calculations by making all new developments fully and promptly available to the scientific community, through a six-months release cycle under GPL open-source license. To support the growth of data-driven materials research, we will adopt portable, descriptive, and AI-ready data formats, and we will invest into training of users and developers of ab initio electronic structure software.

Overall, this project will accelerate the pace of discovery in materials research by making advanced ab initio many-body calculations of electronic, optical, and transport properties of materials more widely accessible, by leveraging the power of DOE exascale supercomputers, and by enabling predictive design of materials for energy, microelectronics, and quantum technologies.


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