Toward artificial intelligence and machine learning-enabled frameworks for improved predictions of lifecycle environmental impacts of functional materials and devices

被引：0
|
作者：
T. Ibn-Mohammed
K. B. Mustapha
M. Abdulkareem
A. Ucles Fuensanta
V. Pecunia
C. E. J. Dancer
机构：
[1] WMG,Department of Mechanical, Materials and Manufacturing Engineering
[2] The University of Warwick,School of Sustainable Energy Engineering
[3] University of Nottingham (Malaysia Campus),undefined
[4] William Harvey Research Institute,undefined
[5] Queen Mary University,undefined
[6] Simon Fraser University,undefined
来源：
MRS Communications | 2023年 / 13卷 / 5期
关键词：
Artificial intelligence; Machine learning; Life cycle assessment; Environmental impact; Functional ceramic; Critical materials;
D O I：
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中图分类号：
学科分类号：
摘要：
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页码：795 / 811
页数：16
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