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Orchestrating explainable AI, ChatGPT, and human expertise: a framework for extracting polymer design guidelines
Yin Kan Phua, Nana Terasoba, Manabu Tanaka, Tsuyohiko Fujigaya, Koichiro Kato
Kyushu University Tokyo Metropolitan University
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Orchestrating XAI, ChatGPT, and expert knowledge to extract actionable and chemically intuitive guidelines for designing high-performance functional polymers.
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学术脉络
学科主题
材料 / 化学Machine Learning in Materials Science
Artificial Intelligence in Healthcare and Education · Explainable Artificial Intelligence (XAI)
参考文献 129
A mini-review on anion exchange membranes for fuel cell applications: Stability issue and addressing strategies
被引 313Jie Cheng, Gaohong He, Fengxiang Zhang · International Journal of Hydrogen Energy · 2015
Anion exchange membranes based on carbazole-containing polyolefin for direct methanol fuel cells
被引 57Ao Nan Lai, Ke Zhou, Yizhi Zhuo · Journal of Membrane Science · 2015
Prediction of nanoparticle transport behavior from physicochemical properties: machine learning provides insights to guide the next generation of transport models
被引 59Eli Goldberg, Martin Scheringer, Thomas D. Bucheli · Environmental Science Nano · 2015
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