High‑throughput screening of Sr_(x)A_(1−x)Fe_(y)B_(1−y)O_(3) perovskites for low‑temperature chemical looping air separation using graph neural networksOA
Low‑temperature Chemical Looping Air Separation(CLAS)is a promising technology for producing oxygen‑enriched gas streams.It utilizes the redox properties of solid oxygen carriers to selectively capture and release oxygen from the air.Oxygen vacancy formation energy(E_(ovf))can be used to evaluate the ease of oxygen release by the oxides.In this study,the applicable range of E_(ovf)for CLAS oxygen carriers was determined to be<2.3 eV using the thermodynamic calculations.A graph neural network(GNN)was trained and used to predict the E_(ovf).By predicting E_(ovf)with the GNN model,a screening from the 3649 compositions of Sr_(x)A_(1−x)Fe_(y)B_(1−y)O_(3)perovskites was conducted to discover the CLAS oxygen carriers.The prediction results indicate that the doping of Ba and Ca ions at the A site and Co ions at the B‑site can effectively reduce the E_(ovf)of the perovskite structure.The feasibility of screening the CLAS oxygen carriers using the E_(ovf)method was validated through the rediscovery of some known materials.These results support the effectiveness of GNNs in accelerating the discovery of CLAS oxygen carriers.
ZHAO Jie;DONG Changqing;XUE Junjie;HU Xiaoying;ZHANG Junjiao
National Engineering Laboratory for Biomass Power Generation Equipment(NCEPU),School of New Energy,North China Electric Power University,Beijing 102206,ChinaNational Engineering Laboratory for Biomass Power Generation Equipment(NCEPU),School of New Energy,North China Electric Power University,Beijing 102206,China New Energy Generation National Engineering Research Center(NCEPU),School of New Energy,North China Electric Power University,Beijing 102206,ChinaNational Engineering Laboratory for Biomass Power Generation Equipment(NCEPU),School of New Energy,North China Electric Power University,Beijing 102206,ChinaNational Engineering Laboratory for Biomass Power Generation Equipment(NCEPU),School of New Energy,North China Electric Power University,Beijing 102206,ChinaSchool of Energy Power and Mechanical Engineering,North China Electric Power University,Beijing 102206,China
能源科技
chemical looping air separationoxygen vacancy formation energygraph neural networkmaterial discovery
《燃料化学学报(中英文)》 2026 (7)
P.270-282,13
Supported by National Natural Science Foundation of China(50976032,51776070)。
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