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Volume 4, Issue 1 (2024) – 4 articles

Cover Picture: We have developed a Local Environment Interaction-based Machine Learning Framework (LEI-Framework) that utilizes graph algorithms and fingerprint descriptors to capture and extract the important local information. This enables fast and accurate predictions of molecular adsorption across extensive and diverse material surfaces. Our work presents an effective and universal machine learning tool for a wide range of applications in molecular adsorption, such as electrocatalysis, molecular gas sensors, carbon capture, energy storage, and drug design/delivery.
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Journal of Materials Informatics
ISSN 2770-372X (Online)
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