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浏览/检索结果: 共6条，第1-6条 帮助 限定条件 发表日期：2019    专题：金属研究所    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Low Temperature Oxidation of Ethane to Oxygenates by Oxygen over Iridium-Cluster Catalysts 期刊论文 JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, 2019, 卷号: 141, 期号: 48, 页码: 18921-18925 作者:  Jin, Renxi;  Peng, Mi;  Li, Ang;  Deng, Yuchen;  Jia, Zhimin 收藏  |  浏览/下载：10/0  |  提交时间：2021/02/02 Anchoring Cu-1 species over nanodiamond-graphene for semi-hydrogenation of acetylene 期刊论文 NATURE COMMUNICATIONS, 2019, 卷号: 10, 页码: 7 作者:  Huang, Fei;  Deng, Yuchen;  Chen, Yunlei;  Cai, Xiangbin;  Peng, Mi 收藏  |  浏览/下载：159/0  |  提交时间：2021/02/02 Tin-Assisted Fully Exposed Platinum Clusters Stabilized on Defect-Rich Graphene for Dehydrogenation Reaction 期刊论文 ACS CATALYSIS, 2019, 卷号: 9, 期号: 7, 页码: 5998-6005 作者:  Zhang, Jiayun;  Deng, Yuchen;  Cai, Xiangbin;  Chen, Yunlei;  Peng, Mi 收藏  |  浏览/下载：39/0  |  提交时间：2021/02/02 atomic dispersion  defect-rich graphene  Pt nanocluster  dehydrogenation  heterogeneous catalysis   Modeling the corrosion behavior of Ni-Cr-Mo-V high strength steel in the simulated deep sea environments using design of experiment and artificial neural network 期刊论文 JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY, 2019, 卷号: 35, 期号: 1, 页码: 168-175 作者:  Hu, Qiangfei;  Liu, Yuchen;  Zhang, Tao;  Geng, Shujiang;  Wang, Fuhui 收藏  |  浏览/下载：1/0  |  提交时间：2021/02/02 Ni-Cr-Mo-V steel  Deep sea corrosion  Design of experiment  Artificial neural network   Modeling the corrosion behavior of Ni-Cr-Mo-V high strength steel in the simulated deep sea environments using design of experiment and artificial neural network 期刊论文 JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY, 2019, 卷号: 35, 期号: 1, 页码: 168-175 作者:  Hu, Qiangfei;  Liu, Yuchen;  Zhang, Tao;  Geng, Shujiang;  Wang, Fuhui 收藏  |  浏览/下载：2/0  |  提交时间：2021/02/02 Ni-Cr-Mo-V steel  Deep sea corrosion  Design of experiment  Artificial neural network   Modeling the corrosion behavior of Ni-Cr-Mo-V high strength steel in the simulated deep sea environments using design of experiment and artificial neural network 期刊论文 JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY, 2019, 卷号: 35, 期号: 1, 页码: 168-175 作者:  Hu, Qiangfei;  Liu, Yuchen;  Zhang, Tao;  Geng, Shujiang;  Wang, Fuhui 收藏  |  浏览/下载：1/0  |  提交时间：2021/02/02 Ni-Cr-Mo-V steel  Deep sea corrosion  Design of experiment  Artificial neural network