Accelerating discovery of infrared nonlinear optical materials with large shift current via high-throughput screening
Discovering nonlinear optical (NLO) materials with strong shift current response, particularly in the infrared (IR) regime, is essential for next-generation optoelectronics yet remains highly challenging in both experiments and theory, which still largely relies on case-by-case studies. Here, we employ a high-throughput screening strategy, applying a multi-step filter to the Materials Project database (>154,000 materials), which yielded 2519 candidate materials for detailed first-principles evaluation. From these calculations, we identify 32 NLO materials with strong shift current response (σ > 100 μA/V2). Our work reveals that layered structures with C3v symmetry and heavy p-block elements (e.g., Te and Sb) exhibit apparent superiority in enhancing shift current. More importantly, 9 of these compounds show shift current response peaks in the IR region, with the strongest reaching 616 μA/V2, holding significant application potential in fields such as IR photodetection, sensing, and energy harvesting. Beyond identifying promising candidates, this work establishes a comprehensive and high-quality first-principles dataset for NLO response, providing a solid foundation for future AI-driven screening and accelerated discovery of high-performance NLO materials, as demonstrated by a prototype machine-learning application.
Authors
- Qiangqiang Gu (ORCID: https://orcid.org/0000-0002-9438-9883)
- Mingkang Liu (ORCID: https://orcid.org/0000-0003-0786-9561)
- Daye Zheng
- Aiqin Yang
- Dian Jin
- Qi Wang
- Jian-Hua Jiang
Institutions
- University of Science and Technology of China (CN)
- Hong Kong Polytechnic University (HK)
- National University of Singapore (SG)
- Suzhou University of Science and Technology (CN)
- Soochow University (CN)
Publication Details
- Journal
- npj Computational Materials
- Published
- 2026-04-01
- DOI
- https://doi.org/10.1038/s41524-026-02064-3
- Primary Topic
- Crystal Structures and Properties
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Chinese Academy of Sciences
- Government of Jiangsu Province
- Natural Science Foundation of Jiangsu Province
- Priority Academic Program Development of Jiangsu Higher Education Institutions
- National Key Research and Development Program of China