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Thermal and Photochemical Electrocyclic Reactions: Overview01:26

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Electrocyclic reactions are reversible reactions. They involve an intramolecular cyclization or ring-opening of a conjugated polyene. Shown below are two examples of electrocyclic reactions. In the first reaction, the formation of the cyclic product is favored. In contrast, in the second reaction, ring-opening is favored due to the high ring strain associated with cyclobutene formation.
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The absorption of UV–visible light by conjugated systems causes the promotion of an electron from the ground state to the excited state. Consequently, photochemical electrocyclic reactions proceed via the excited-state HOMO rather than the ground-state HOMO. Since the ground- and excited-state HOMOs have different symmetries, the stereochemical outcome of electrocyclic reactions depends on the mode of activation; i.e., thermal or photochemical.
Selection Rules: Photochemical Activation
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闭环多目标优化用于Cu-Sb-S光电催化材料的发现.

Yang Bai1, Zi Hui Jonathan Khoo1,2, Riko I Made1

  • 1Institute of Materials Research and Engineering (IMRE), Agency for Science Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore, 138634, Republic of Singapore.

Advanced materials (Deerfield Beach, Fla.)
|September 10, 2023
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概括

铜反硫化物对水分裂催化有很大的潜力. 智能工作流优化了它们的组成,实现了进化的2.3倍更高的活动.

关键词:
高通量实验 高通量实验机器学习是机器学习.光电化学水分离器的使用

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科学领域:

  • 材料科学 材料科学 材料科学
  • 催化剂是一种催化剂.
  • 可再生能源可再生能源是可再生能源.

背景情况:

  • 铜反硫化物是地球上丰富的材料,具有广泛的光吸收能力,这使得它们对光电化学水分有希望.
  • 它们在进化中的催化性能对晶体结构和原子组成高度敏感.

研究的目的:

  • 通过探索其组成空间,优化铜硫化物 (Cu-Sb-S) 的光电催化演变.
  • 开发和实施一个集成的工作流,将高吞吐量实验和机器学习结合起来,以优化催化剂.

主要方法:

  • 采用了结合机器人平台,表征技术和机器学习 (ML) 优化模型的闭环工作流.
  • 多目标优化被用来有效地探索Cu-Sb-S组成空间.
  • 在0V与可逆电极 (RHE) 进行光电测试,以评估催化活性.

主要成果:

  • 综合实验-ML循环仅在9个周期内确定了最佳条件.
  • 在F-doped SnO2 (FTO) 玻璃上的优化Cu-Sb-S成分 (9:45:46比) 实现了 -186 μA cm-2.2的光电流.
  • 这种最佳材料具有1.85 eV的带隙和63.2%的Cu1+/Cu物种含量.
  • 针对性搜索产生了一个非明显的CuSbS成分,其活性比随机抽样高2.3倍.

结论:

  • 智能,闭环工作流可以快速优化复杂的材料系统用于催化.
  • 优化的铜硫化物显示出对进化的显著增强的光电催化活性.
  • 这种方法加速了对可持续能源应用的高效和地球丰富的催化剂的发现.