Scholarlink

Abstract <p>Building on Frenkel’s century-old theoretical foundation for understanding defects, modern computational methods for studying defects in semiconductors and insulators have evolved from the initial interpretive tools to predictive approaches capable of guiding technological applications. In this article, we examine the current state and future directions of computational approaches for studying point defects in semiconductors. Density functional theory (DFT)&#xa0;has become the primary tool for defect calculations, with hybrid functionals proving essential for accurately describing electronic structure and charge localization effects that standard DFT cannot capture. We discuss recent advances in treating excited states and calculating experimentally observable properties from first principles. Current methods can predict thermodynamic properties within 0.1&#xa0;eV accuracy and luminescence spectra with meV precision through sophisticated electron–phonon coupling treatments. Emerging techniques include quantum-embedding methods and machine&#xa0;learning interatomic potentials that promise to extend current capabilities while reducing computational costs. Future developments in exchange–correlation functionals and beyond-DFT methods offer exciting possibilities for further advancing computational defect physics.</p> Graphical abstract <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Frontiers of computation for defects in semiconductors and insulators

  • 期刊论文

  • 发表日期：

    2026年5月6日

查看全文
  • Mark E. Turiansky,
  • John L. Lyons,
  • Darshana Wickramaratne,
  • Joel B. Varley,
  • Anderson Janotti

摘要

Abstract

Building on Frenkel’s century-old theoretical foundation for understanding defects, modern computational methods for studying defects in semiconductors and insulators have evolved from the initial interpretive tools to predictive approaches capable of guiding technological applications. In this article, we examine the current state and future directions of computational approaches for studying point defects in semiconductors. Density functional theory (DFT) has become the primary tool for defect calculations, with hybrid functionals proving essential for accurately describing electronic structure and charge localization effects that standard DFT cannot capture. We discuss recent advances in treating excited states and calculating experimentally observable properties from first principles. Current methods can predict thermodynamic properties within 0.1 eV accuracy and luminescence spectra with meV precision through sophisticated electron–phonon coupling treatments. Emerging techniques include quantum-embedding methods and machine learning interatomic potentials that promise to extend current capabilities while reducing computational costs. Future developments in exchange–correlation functionals and beyond-DFT methods offer exciting possibilities for further advancing computational defect physics.

Graphical abstract