Yun Yihan, Wu Mengfan, Yang Zhihua, Li Guangmao, Pan Shilie
Research Center for Crystal Materials; State Key Laboratory of Functional Materials and Devices for Special Environmental Conditions; Xinjiang Key Laboratory of Functional Crystal Materials; Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, 40-1 South Beijing Road, Urumqi, 830011, China.
Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China.
Adv Sci (Weinh). 2025 Jun;12(23):e2417851. doi: 10.1002/advs.202417851. Epub 2025 Apr 26.
Discovering novel infrared functional materials (IRFMs) hold tremendous significance for laser industry. Incorporating artificial intelligence into material discovery has been recognized as a pivotal trend driving advancements in materials science. In this work, an IRFM predictor based on machine learning (ML) is developed for the pre-selection of the most promising candidates, in which interpretable analyses reveal the prior domain knowledge of IRFMs. Under the guidance of this IRFM predictor, a series of selenoborates, ABa(BSe)X (A = Rb, Cs; X = Cl, Br, I) are successfully predicted and synthesized. Comprehensive characterizations together with first-principles analyses reveal that these materials exhibit preferred properties of wide bandgaps (2.92 - 3.04 eV), moderate birefringence (0.145 - 0.170 at 1064 nm), high laser-induced damage thresholds (LIDTs) (4 - 6 Ý AGS) and large second harmonic generation (SHG) responses (0.9 - 1 × AGS). Structure-property relationship analyses indicate that the [BSe] unit can be regarded as a potential gene for exploring novel IRFMs. This work may open an avenue for exploring high-performance materials.
发现新型红外功能材料（IRFMs）对激光产业具有重大意义。将人工智能融入材料发现过程已被视为推动材料科学进步的关键趋势。在这项工作中，开发了一种基于机器学习（ML）的IRFM预测器，用于预选最有前景的候选材料，其中可解释分析揭示了IRFMs的先验领域知识。在该IRFM预测器的指导下，成功预测并合成了一系列硒硼酸盐ABa(BSe)X（A = Rb、Cs；X = Cl、Br、I）。综合表征以及第一性原理分析表明，这些材料具有宽带隙（2.92 - 3.04 eV）、适度双折射（在1064 nm处为0.145 - 0.170）、高激光诱导损伤阈值（LIDTs）（4 - 6 Ý AGS）和大二阶谐波产生（SHG）响应（0.9 - 1 × AGS）等优良特性。结构 - 性能关系分析表明，[BSe]单元可被视为探索新型IRFMs的潜在基因。这项工作可能为探索高性能材料开辟一条途径。
