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Combining machine learning and metal–organic frameworks research: Novel modeling, performance prediction, and materials discovery
C Li, L Bao, Y Ji, Z Tian, M Cui, Y Shi, Z Zhao… - Coordination Chemistry …, 2024 - Elsevier
Abstract Machine learning (ML) is the science of making computers learn and behave like
humans, autonomously improving their learning by providing them with data and information …
humans, autonomously improving their learning by providing them with data and information …
Accelerated Discovery of Metal–Organic Frameworks for CO2 Capture by Artificial Intelligence
The existence of a very large number of porous materials is a great opportunity to develop
innovative technologies for carbon dioxide (CO2) capture to address the climate change …
innovative technologies for carbon dioxide (CO2) capture to address the climate change …
High‐Throughput Computational Screening‐Driven Porous Material Discovery for Benchmark Propylene/Propane Separation
T Zhang, JJ Lv, Y Dang, Z Gao, H Wang… - Advanced Functional …, 2025 - Wiley Online Library
Abstract Separating propylene (C3H6) from propylene/propane (C3H6/C3H8) mixture using
energy‐efficient adsorption is industrially important, but due to the lack of universal pore …
energy‐efficient adsorption is industrially important, but due to the lack of universal pore …