Data-driven interfacial regulations through molecular additive screening for batteries and electrocatalysis

Molecular additives are widely employed to regulate electrochemical interfaces, but their rational design remains constrained by fragmented mechanistic understanding and the limited transferability of design principles across batteries and electrocatalysis. This review argues that many additive effects in these systems can be interpreted through three shared interfacial mechanisms: coordination remodeling, interfacial adsorption, and competitive inhibition. In batteries, these mechanisms govern metal deposition, electron-transfer-induced interphase engineering, and the management of reactive intermediates. In electrocatalysis, they underlie activity tuning, pathway steering, and selectivity enhancement through interfacial microenvironment regulation, adsorbate and surface-state regulation, and competing-reaction suppression. Building on this framework, we summarize a data-driven route for additive discovery spanning data mining, predictive modeling, screening, closed-loop optimization, and reasoning-guided and data-enabled exploration. Unlike previous reviews that mainly focus on specific battery chemistries, electrocatalytic microenvironments, or ML-assisted molecular discovery, this review extracts common interfacial mechanisms shared by batteries and electrocatalysis. By organizing molecular additives around shared interfacial primitives, this review identifies descriptor transferability as a key opportunity for data-driven additive design and emphasizes the need for cross-system benchmarks to quantitatively assess generalizability beyond individual chemistries. This framework provides a practical basis for the predictive design of multifunctional additives across electrochemical systems.