TY - JOUR
T1 - Material intelligence by the convergence of artificial intelligence and robotic platforms
AU - Zhang, Xinyu
AU - Chen, Zijian
AU - Chen, Feibei
AU - Fanady, Billy
AU - Wang, Boyuan
AU - Ni, Zongming
AU - Zhou, Shumin
AU - Ye, Junzhi
AU - Chen, GuanHua
AU - Liu, Jie
AU - Hoye, Robert L.Z.
AU - Li, Xiaobo
AU - Chong, Samantha Y.
AU - Feng, Wei
AU - Chung, Chi-yung
AU - Chan, Ching-chuen
AU - Chen, Linjiang
AU - Hao, Han
AU - Aspuru-Guzik, Alán
AU - Jiang, Jun
AU - Zhao, Haitao
PY - 2025/6/30
Y1 - 2025/6/30
N2 - The emerging interdisciplinary research of Material Intelligence through the convergence of artificial intelligence, robotic platforms, and material informatics has revolutionized the field of chemistry and material science. This shift enables precision and intelligence in materials research to avoid the problems of try-and-error synthesis and labour-intensive characterization.The aim of this review is to present a comprehensive methodology that unifies three interlinked domains: data-guided rational design (‘reading’), automation-enabled controllable synthesis (‘doing’), and autonomy-facilitated inverse design (‘thinking’). We critically examine how the integration of materials common discipline (i.e., rational design, controllable synthesis, inverse design) with interdisciplinary research (i.e., data, automation, autonomy), and then emphasize cutting-edge research of artificial intelligence and robotics, collectively shape a closed-loop next paradigm of Material Intelligence, revolutionizing experimental, theoretical, software-driven and data-driven paradigms. Ultimately, this paper outlooks how these insights drive the new paradigm of materials research that seamlessly combine database, robotics, artificial intelligence, and even embodied intelligence to empower the full potential of Material Intelligence.
AB - The emerging interdisciplinary research of Material Intelligence through the convergence of artificial intelligence, robotic platforms, and material informatics has revolutionized the field of chemistry and material science. This shift enables precision and intelligence in materials research to avoid the problems of try-and-error synthesis and labour-intensive characterization.The aim of this review is to present a comprehensive methodology that unifies three interlinked domains: data-guided rational design (‘reading’), automation-enabled controllable synthesis (‘doing’), and autonomy-facilitated inverse design (‘thinking’). We critically examine how the integration of materials common discipline (i.e., rational design, controllable synthesis, inverse design) with interdisciplinary research (i.e., data, automation, autonomy), and then emphasize cutting-edge research of artificial intelligence and robotics, collectively shape a closed-loop next paradigm of Material Intelligence, revolutionizing experimental, theoretical, software-driven and data-driven paradigms. Ultimately, this paper outlooks how these insights drive the new paradigm of materials research that seamlessly combine database, robotics, artificial intelligence, and even embodied intelligence to empower the full potential of Material Intelligence.
UR - http://dx.doi.org/10.1016/j.ynexs.2025.100083
U2 - 10.1016/j.ynexs.2025.100083
DO - 10.1016/j.ynexs.2025.100083
M3 - Article
SN - 2950-1601
JO - Nexus
JF - Nexus
ER -