咨询与建议

限定检索结果

文献类型

  • 1 篇 期刊文献

馆藏范围

  • 1 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 1 篇 理学
    • 1 篇 化学
  • 1 篇 工学
    • 1 篇 控制科学与工程
    • 1 篇 计算机科学与技术...
    • 1 篇 化学工程与技术
    • 1 篇 软件工程
  • 1 篇 管理学
    • 1 篇 管理科学与工程(可...

主题

  • 1 篇 co_(2)capture
  • 1 篇 single-atom allo...
  • 1 篇 co_(2)conversion
  • 1 篇 ionic liquids
  • 1 篇 amine
  • 1 篇 high-entropy cat...
  • 1 篇 machine learning

机构

  • 1 篇 department of ma...
  • 1 篇 department of en...
  • 1 篇 mit-ibm watson a...
  • 1 篇 department of nu...

作者

  • 1 篇 ju li
  • 1 篇 sung eun jerng
  • 1 篇 yang jeong park

语言

  • 1 篇 英文
检索条件"主题词=High-entropy catalysts"
1 条 记 录,以下是1-10 订阅
排序:
Machine learning for CO_(2) capture and conversion:A review
收藏 引用
Energy and AI 2024年 第2期16卷 512-527页
作者: Sung Eun Jerng Yang Jeong Park Ju Li Department of Environmental and Energy Engineering The University of Suwon17Wauan-gilBongdam-eupHwaseong-si18323Gyeonggi-doRepublic of Korea Department of Materials Science and Engineering Massachusetts Institute of Technology77 Massachusetts AveCambridge02139MAUnited States of America Department of Nuclear Science and Engineering Massachusetts Institute of Technology77 Massachusetts AveCambridge02139MAUnited States of America MIT-IBM Watson AI Lab 75 Binney StreetCambridge02142MAUnited States of America
Coupled electrochemical systems for the direct capture and conversion of CO have garnered significant attention owing to their potential to enhance energy-and cost-efficiency by circumventing the amine regeneration **... 详细信息
来源: 维普期刊数据库 维普期刊数据库 评论