Molecular Insights into the Thermal Conductivity of Nanocellulose-Polydopamine Composite Systems von Muthoka, Ruth M., Yoo, Hyeonsuk, Lee, Yongjin

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Machine Learning-based approach for Tailor-Made design of ionic Liquids: Application to CO2 capture von Zhang, Kexin, Wu, Jiasheng, Yoo, Hyeonsuk, Lee, Yongjin

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Machine Learning-Driven Discovery of Metal–Organic Frameworks for Efficient CO2 Capture in Humid Condition von Zhang, Xiangyu, Zhang, Kexin, Yoo, Hyeonsuk, Lee, Yongjin

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In Silico Generation of a Topologically Diverse Zeolite-Templated Carbon Library von Wu, Jiasheng, Zhang, Kexin, Yoo, Hyeonsuk, Lee, Yongjin

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Accelerated Design of Ultra-High-Performance Aramid Copolymers via a High-Throughput Screening Approach von Yoo, Hyeonsuk, Muthoka, Ruth M., Zhang, Xiangyu, Lee, Yongjin

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Enhanced thermal conductivity and mechanical property via improvement of hydrogen bonding between hexagonal boron nitride and aramid copolymer von Jeong, Hwakyung, Lyu, Jaegeun, Choi, Howon, Kim, Min Woo, Kim, Juyoung, Yoo, Hyeonsuk, Lee, Yongjin, Youk, Ji Ho, Chae, Han Gi

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Comprehensive Framework for the Design of High-Performing and Sustainable Polyamides von Muthoka, Ruth M., Park, Jinyoung, Yoo, Hyeonsuk, Suh, Min-ho, Lee, Yongjin

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Machine Learning-Driven Discovery of Metal–Organic Frameworks for Efficient CO 2 Capture in Humid Condition von Zhang, Xiangyu, Zhang, Kexin, Yoo, Hyeonsuk, Lee, Yongjin

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