Machine-Learning-Assisted Selective Synthesis of a Semiconductive Silver Thiolate Coordination Polymer with Segregated Paths for Holes and Electrons
Machine-Learning-Assisted Selective Synthesis of a Semiconductive Silver Thiolate Coordination Polymer with Segregated Paths for Holes and Electrons
复制标题
机器学习辅助选择性合成空穴和电子路径分离的半导体硫醇银配位聚合物
DOI：
10.1002/anie.202110629
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
and Daisuke Tanaka
中科院分区：
文献类型：
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作者：
Takuma Wakiya;Yoshinobu Kamakura;Hiroki Shibahara;Kazuyoshi Ogasawara;Akinori Saeki;Ryosuke Nishikubo;Akihiro Inokuchi;Hirofumi Yoshikawa;and Daisuke Tanaka
具有无限金属硫键网络的配位聚合物具有独特的导电性和光学性质。然而，新的（-M-S-）n-结构CP的发展受到其结晶困难的阻碍。在本文中，我们描述了使用机器学习来优化具有无限Ag−S键网络的三硫代氰尿酸（H3 ttc）基双硫代CPs的合成，报告了三种CP晶体结构，并揭示了异构体选择性主要由反应介质中的质子浓度决定。其中一种CP，[Ag 2 Httc]n，具有3D扩展的无限Ag−S键网络，具有堆叠的三嗪环的1D柱，根据第一性原理计算，为空穴和电子提供单独的路径。时间分辨的微波电导率实验表明[Ag 2 Httc]具有很高的光电导性（φ μmax=1.6×10− 4cm 2 V − 1 s −1）。因此，我们的方法促进了新的CP与选择性的拓扑结构，难以结晶的发现。
Coordination polymers (CPs) with infinite metal–sulfur bond networks have unique electrical conductivities and optical properties. However, the development of new (‐M‐S‐)n‐structured CPs is hindered by difficulties with their crystallization. Herein, we describe the use of machine learning to optimize the synthesis of trithiocyanuric acid (H3ttc)‐based semiconductive CPs with infinite Ag−S bond networks, report three CP crystal structures, and reveal that isomer selectivity is mainly determined by proton concentration in the reaction medium. One of the CPs, [Ag2Httc]n, features a 3D‐extended infinite Ag−S bond network with 1D columns of stacked triazine rings, which, according to first‐principle calculations, provide separate paths for holes and electrons. Time‐resolved microwave conductivity experiments show that [Ag2Httc]nis highly photoconductive (φΣμmax=1.6×10−4cm2V−1s−1). Thus, our method promotes the discovery of novel CPs with selective topologies that are difficult to crystallize.