2026-06-25 ローレンス・バークレー国立研究所（LBNL）
＜関連情報＞
- https://newscenter.lbl.gov/2026/06/25/scientists-develop-predictive-roadmap-to-boost-performance-in-next-gen-spintronics/
- https://www.cell.com/matter/abstract/S2590-2385(26)00039-1
吸収非対称性因子の増強：キラル2次元ペロブスカイトの合成メカニズムを解明するためのデータ駆動型アプローチ Absorption dissymmetry factor enhancement: A data-driven approach to unravel the synthesis knobs of chiral 2D perovskites
Raphael F. Moral ∙ Maher B. Alghalayini ∙ Raushan N. Nurdillayeva ∙ … ∙ Marcus M. Noack ∙ Craig P. Schwartz ∙ Carolin M. Sutter-Fella
Matter Published: March 19, 2026
DOI:https://doi.org/10.1016/j.matt.2026.102676
Highlights
- Data-driven framework identifies key synthesis “knobs” for chiral 2D perovskites
- Solvent choice is the primary factor governing dissymmetry factor variability
- Acetonitrile provides superior reproducibility and higher chiroptical response
- GPR reveals thickness, annealing temperature, and texture as gabs predictors
Summary
Chiral 2D metal halide perovskites (MHPs) are promising for spin-optoelectronic applications, yet their absorption dissymmetry factor (gabs) exhibits significant variability due to complex, co-dependent structural and experimental factors. We established a data-driven framework using Pearson’s correlation, ANOVA, and Gaussian process regression to identify and model key synthesis “knobs” governing these properties. The analysis revealed that solvent choice is the primary factor driving variability. For acetonitrile-based films, gabs was maximized by optimizing annealing temperature and film thickness. Conversely, films from higher boiling point solvents showed complex dependencies on annealing temperature, excitonic integral intensity, and film texture. These statistical correlations provide a roadmap for the rational design of high-performance chiral MHPs and establish a foundation for future machine learning-driven material exploration.
