Deep Learning Guided Exploration of Transition Metal Oxide Catalysts in Acetylene Selective Hydrogenation.

Journal: Journal of the American Chemical Society
Published Date: Dec 20, 2025

Abstract

The development of empirical materials, hindered by the complex interplay between material properties and reaction mechanisms, typically necessitates an extensive trial-and-error process to identify optimal catalysts. In our study, we integrate density functional theory (DFT) predictions to generate mappings of electronic and molecular adsorption properties, which are then employed to identify novel materials using deep learning algorithms. These newly identified materials were synthesized and assessed for their catalytic performance in the selective hydrogenation of acetylene. Notably, CuTiO3 catalysts demonstrated exceptional performance, achieving acetylene conversion exceeding 99% and ethylene selectivity greater than 99% at a relatively low temperature of 75 °C. Additionally, CuO-doped TiO2 was observed to form strong acetylene adsorption sites and weaker ethylene adsorption sites (Cu-O-Ti). The p-π hybridized coupling between the oxygen p-orbitals and the π-electrons of acetylene in the Cu-O-Ti structure was found to play a critical role in facilitating the conversion of acetylene to ethylene.

Authors

  • Chong Yao
    Key Laboratory of Industrial Dust Prevention and Control and Occupational Health and Safety, Ministry of Education, Huainan, China.
  • Qianjun Zhang
    Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-Xiangya, Changsha, 410008, Hunan, China; National Engineering and Research Center of Human Stem Cells, Changsha 410006, China; Institute of Reproductive and Stem Cell Engineering, NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Xiangya School of Basic Medical Science, Central South University, Changsha 410008, China.
  • Hao Lu
    Huazhong University of Science and Technology, Wuhan, China.
  • Xinhui Zhang
    Center of Hepatobiliary Pancreatic Disease, XuZhou Central Hospital, Jiangsu, People's Republic of China. [email protected].
  • Yuanjing Fan
    State Key Laboratory of Green Chemical Synthesis and Conversion, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China.
  • Jie Luo
  • Rubo Fang
    State Key Laboratory of Green Chemical Synthesis and Conversion, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China.
  • Hao Liu
    Key Laboratory of Development and Maternal and Child Diseases of Sichuan Province, Department of Pediatrics, Sichuan University, Chengdu, China.
  • Jinghui Lyu
    State Key Laboratory of Green Chemical Synthesis and Conversion, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China.
  • Feng Feng
    Department of Microbiology, Boston University, Boston, MA 02118, USA.
  • Lili Lin
    State Key Laboratory of Green Chemical Synthesis and Conversion, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China.
  • Chunshan Lu
    State Key Laboratory of Green Chemical Synthesis and Conversion, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China.
  • Ying Zheng
    Department of Ultrasound, Beijing Youan Hospital, Capital Medical University, Beijing 100000, China. Electronic address: [email protected].
  • Jianguo Wang
  • Qingtao Wang
    Department of Laboratory Medicine, Beijing Chao-yang Hospital, Capital Medical University, Beijing, P.R. China.
  • Qunfeng Zhang
    Institute of Bioengineering, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
  • Xiaonian Li
    State Key Laboratory of Green Chemical Synthesis and Conversion, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, China.

Keywords

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