COFAP: A Universal Framework for COFs Adsorption Prediction through Designed Multi-Modal Extraction and Cross-Modal Synergy

• URL: http://arxiv.org/abs/2511.01946v1
• Date: Mon, 03 Nov 2025 10:11:33 GMT
• Title: COFAP: A Universal Framework for COFs Adsorption Prediction through Designed Multi-Modal Extraction and Cross-Modal Synergy
• Authors: Zihan Li, Mingyang Wan, Mingyu Gao, Zhongshan Chen, Xiangke Wang, Feifan Zhang,
• Abstract summary: Covalent organic frameworks (COFs) are promising adsorbents for gas adsorbing and separation.<n>A universal COFs adsorbing prediction framework (COFAP) is proposed, which can extract multi-modal structural and chemical features through deep learning.<n>A weight-adjustable prioritization scheme is also developed to enable flexible, application-specific ranking of candidate COFs for researchers.
• Score: 15.886563559077507
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Covalent organic frameworks (COFs) are promising adsorbents for gas adsorption and separation, while identifying the optimal structures among their vast design space requires efficient high-throughput screening. Conventional machine-learning predictors rely heavily on specific gas-related features. However, these features are time-consuming and limit scalability, leading to inefficiency and labor-intensive processes. Herein, a universal COFs adsorption prediction framework (COFAP) is proposed, which can extract multi-modal structural and chemical features through deep learning, and fuse these complementary features via cross-modal attention mechanism. Without Henry coefficients or adsorption heat, COFAP sets a new SOTA by outperforming previous approaches on hypoCOFs dataset. Based on COFAP, we also found that high-performing COFs for separation concentrate within a narrow range of pore size and surface area. A weight-adjustable prioritization scheme is also developed to enable flexible, application-specific ranking of candidate COFs for researchers. Superior efficiency and accuracy render COFAP directly deployable in crystalline porous materials.

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