Computational Mesoscale Science and Open Software for Quantum Materials

Objectives: This project integrates computational simulation, software development, and experimental validation to accelerate the insertion of quantum materials into devices. The key to advance the understanding of materials is to predict their properties and responses on various time and length scales. The ability to predict, understand, and control the spatiotemporal evolution of materials at the mesoscale — that is, the scale between the atomistic and macroscopic lengths — is critical to translating novel quantum observations into practical technologies. The specific objectives of the proposed program are to: (1) explore and understand the thermodynamic stability of mesoscale structures and their responses to external thermal, mechanical, electric, and magnetic stimuli; (2) develop mesoscale computational models and innovative numerical algorithms to expand these algorithms towards exascale computations, and implement them into a corresponding open-source software for understanding, discovering and manipulating emergent mesoscale architectures and phenomena in quantum materials, and (3) experimentally validate and then refine the theory and computational tools using atom-resolution materials synthesis in tandem with cutting-edge quantum characterization methods.Description of methods: This project will leverage and further develop the predictive ability of the phase-field method, which has emerged as a powerful approach to model and simulate hierarchical mesoscale structures between the elementary atoms and the macroscopic continuum. The essential physics of strongly correlated electrons, topologically driven spin, charge, orbital and lattice textures, and their dynamical response to ultrafast signals and applied fields will be incorporated into the computational phase-field method that can predict emergent mesoscale quantum orders and pattern formations from the femtosecond (a millionth of a trillionth of a second) to long time scales of seconds or more. This proposal is based on nearly three decades of work by the lead PI in developing state-of-the-art phase-field simulation tools and software and in collaborating with experimental groups to model strongly correlated electron systems, topologically nontrivial polar vortex and bubble states, magnetic skyrmions, and multiferroic spin devices. Their collaborative computational and experimental efforts have recently led to the first dynamical phase-field model for predicting and understanding ultrafast phenomena in optical pump-probe experiments. The project brings together an interdisciplinary team of experts in mesoscale phase-field modeling (Chen), advanced numerical algorithms and high-performance computing (Xu), materials thermodynamic database development based on electronic structure calculations (Dabo), and experimental validation using finite-temperature measurements involving nonlinear optical microscopy, scanning probe microscopy and diffraction imaging (Gopalan), as well as cutting-edge materials synthesis using molecular beam epitaxy (Engel-Herbert). The project will involve extensive collaborations with other experts on dynamical mean field theory, crystal growth, and experimental characterization of mesoscale structures of quantum materials at several DOE Labs and a number of academic institutions.Potential impacts: One of the primary outcomes of the proposed project is an experimentally validated open source software package, open Q-µ-PRO, parallelized to enable peta- and exascale computing for understanding and predicting quantum materials and their mesoscale responses to external thermal, chemical, electrical, magnetic, and mechanical stimuli towards designing device architectures for harnessing these functionalities. The open source software Q-µ-PRO will harness the full potential of DOE leadership computing facilities. The proposed open software package will not only become a powerful tool for understanding the mesoscale phenomena in strongly correlated electronic materials but also accelerate materials insertion into quantum devices, such as strongly correlated materials for next generation field effect transistors, novel spin textures for spintronics, and superconducting qubits for quantum computing.