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Quantifying Steric–Electrostatic Coupling in Nanofiltration via Explainable Machine Learning
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DOI：10.1016/j.memsci.2026.125775.png)
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Abstract
En 中文
• Quantified coupling between steric and electrostatic effects in NF • Discovered a steric transition threshold governing rejection behavior • Revealed compensatory electrostatic effects under weak steric exclusion • Established an interpretable ML framework for mechanism resolution • Bridged data-driven modeling with classical membrane transport theory
Journal
IF:
9
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2.1W
Citations:
9.4W