Machine-Learning-Assisted First-Principles Calculations of Strained InAs1xSbx Alloys for Curved Focal-Plane Arrays

Alexandros Kyrtsos, John Glennon, Andreu Glasmann, Mark R. O’Masta, Binh-Minh Nguyen, and Enrico Bellotti
Phys. Rev. Applied 15, 064008 – Published 3 June 2021
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Abstract

Curved focal-plane arrays offer significant advantages compared with their flat counterparts. However, the curving of the material induces strains which alter its optoelectronic properties. A comprehensive framework is presented for the computational investigation of the band gaps of InAs1xSbx alloys under various strain conditions that are relevant for manufacturing curved focal-plane arrays. The framework consists of both standard and hybrid functional density functional theory (DFT) calculations, finite-element analysis (FEA) calculations, and Gaussian process (GP) regression. The DFT calculations are used for investigating the change of the band gap of the material under various strain conditions. This dataset is then used for training a GP model which is utilized to assess the effects of strain across the device, based on the FEA simulations. The results show excellent predictive capabilities for the machine-learning model at a significantly reduced computational cost and are directly transferable to other device designs.

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  • Received 24 March 2021
  • Revised 29 April 2021
  • Accepted 7 May 2021

DOI:https://doi.org/10.1103/PhysRevApplied.15.064008

© 2021 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied Physics

Authors & Affiliations

Alexandros Kyrtsos1,*, John Glennon2, Andreu Glasmann1, Mark R. O’Masta3, Binh-Minh Nguyen3, and Enrico Bellotti1,2

  • 1Department of Electrical and Computer Engineering, Boston University, Boston, Massachusetts 02215, USA
  • 2Division of Materials Science and Engineering, Boston University, Boston, Massachusetts 02215, USA
  • 3HRL Laboratories, LLC, 3011 Malibu Canyon Road, Malibu, California 90265, USA

  • *akyrtsos@bu.edu

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Vol. 15, Iss. 6 — June 2021

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