Sequential construction of stable nitrogen–oxygen compounds using high-throughput quantum mechanical calculations and customized machine learning model
Chenyue WangSchool of Materials Science & Engineering, Beijing Institute of Technology, Beijing 100081, ChinaLei ZhangSchool of Materials Science & Engineering, Beijing Institute of Technology, Beijing 100081, ChinaChuanyue ChenSchool of Materials Science & Engineering, Beijing Institute of Technology, Beijing 100081, ChinaKaile DouSchool of Materials Science & Engineering, Beijing Institute of Technology, Beijing 100081, ChinaJinya ZhangSchool of Materials Science & Engineering, Beijing Institute of Technology, Beijing 100081, ChinaChongyang LiCollege of Mechanical Engineering and Automation, Chongqing Industry Polytechnic College, Chongqing 401120, ChinaMichael GozinCenter for Advanced Combustion Science, Tel Aviv University, Tel Aviv 69978, IsraelWeibo ZhaoAlibaba Group, Beijing 100102, ChinaChunlin HeSchool of Materials Science & Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSiping PangSchool of Materials Science & Engineering, Beijing Institute of Technology, Beijing 100081, China
2025en
ABI
Аннотация
The machine learning-driven approach and sequential construction strategy enabled the design of 168 nitrogen–oxygen compounds. High-throughput calculations identified 106 stable candidates, some rivaling N 2 O 4 , with potential for space exploration.
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