2024
DOI: 10.1002/smll.202401214
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Machine Learning‐Guided Prediction of Desalination Capacity and Rate of Porous Carbons for Capacitive Deionization

Hao Wang,
Mingxi Jiang,
Guangsheng Xu
et al.

Abstract: Nowadays, capacitive deionization (CDI) has emerged as a prominent technology in the desalination field, typically utilizing porous carbons as electrodes. However, the precise significance of electrode properties and operational conditions in shaping desalination performance remains blurry, necessitating numerous time‐consuming and resource‐intensive CDI experiments. Machine learning (ML) presents an emerging solution, offering the prospect of predicting CDI performance with minimal investment in electrode mat… Show more

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Cited by 8 publications
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