Structural optimization in fingerprint space

ORAL

Abstract

Structural optimization has been a crucial component in computational materials research, and structure predictions have relied heavily on this technique in particular. By introducing an extra fingerprint space, we propose a new structural optimization approach that prevents configurations from being stranded in low-symmetry, high-energy conformations. Using this strategy, the chance of achieving low-energy designs has been significantly increased. This performance boost is anticipated to be advantageous for structure search methods that rely on the local optimization of structures. Therefore, the work provides a path toward the objective of predicting the crystal structure of complex systems.

*This work was supported by the National Science Foundation, Division of Materials Research (NSF-DMR) under Grant No. 2226700, and startup funds of the office of the Dean of SASN of Rutgers University-Newark. The authors acknowledge the Office of Advanced Research Computing (OARC) at Rutgers for providing access to the Amarel cluster and associated research computing resources.

Presenters

  • Li Zhu

    • Physics Department, Rutgers University-Newark
    • Rutgers University
    • Rutgers University-Newark

Authors

  • Li Zhu

    • Physics Department, Rutgers University-Newark
    • Rutgers University
    • Rutgers University-Newark
  • Shuo Tao

    • Rutgers University - Newark
  • Rishi Rao

    • Rutgers-Newark
  • Xuecheng Shao

    • Rutgers University - Newark