Multimodal metrology for sustainable lithium-ion battery formation: From baseline electrical measurements to intelligent, adaptive process control

Lithium-ion battery formation is a critical yet poorly observable stage in cell manufacturing, governing the development of interphases, electrolyte wetting, and defect evolution that ultimately determines performance, safety, and cell lifetime. Traditionally treated as an empirical process, formation is increasingly being redefined through research and advances in metrology, modelling and data science. In this Review, we present for the first time, a comprehensive framework for evaluating and controlling lithium-ion battery formation through multimodal diagnostics, spanning electrical, impedance, mechanical, thermal, acoustic, and spectroscopic measurements. We show how each modality captures distinct yet complementary aspects of the underpinning formation physics, from charge-transfer kinetics and interphase growth through to gas evolution, wetting heterogeneity, and thermal dissipation. We further highlight the emergence of quantitative formation metrics—derived from raw measurement signals such as voltage relaxation, impedance spectra, ultrasound attenuation, and calorimetric heat flow—that potentially enable a direct link between early-stage formation behaviour and long-term cell degradation pathways. By integrating these heterogeneous data streams, we review recent studies that collectively are moving toward the derivation of predictive models capable of identifying defects, optimizing protocols, and enabling real-time decision-making. Finally, we discuss the transition from passive diagnostics to active closed-loop control, where machine learning and multimodal data fusion enables the use of closed-loop formation strategies. Remaining challenges—including data standardization, cross-platform generalizability, and scalability—are outlined, alongside research opportunities to transform battery manufacturing into a predictive, adaptive, and digitally controlled process.