Abdullah Bin Faheem

Ionic transport in solid‐state electrolytes is governed by interfacial disorder and local chemical environments, yet their microscopic design principles remain challenging because large‐scale interfacial kinetics are simulated using molecular dynamics (MD), where predictive design requires quantum‐level accuracy. Here, we use an actively learned machine learning interatomic potential (MLIP) to bridge this scale‐accuracy gap in halide‐tunable antiperovskite solid electrolytes. By varying the local Cl ⁻ /Br ⁻ ratio and quantifying interfacial amorphicity and ion flux, we identify an MLIP‐driven volcano relationship between structural disorder and ionic transport. Cl‐enriched grain boundaries remain overly ordered, whereas Br ⁻ enrichment induces excessive disorder that disrupts migration. Intermediate halide compositions maximize ionic transport through moderately amorphous environments. Guided by this relationship, we design an anion‐engineered grain boundary through selective halide tuning. These results establish controlled anion segregation as a strategy for reducing interfacial resistance and highlight MLIP‐enhanced MD as a predictive framework for transport and disorder engineering in solid‐state materials.

This review presents a comprehensive perspective on how AI and big data strategies can transform the understanding and design of the electrode–electrolyte interphases (EEI) in rechargeable batteries, highlighting their pivotal role in battery performance and longevity. Through uniting high‐throughput experimentation and high‐throughput computation (HTC), which includes automated cell fabrication, advanced characterization, large‐scale HTC screening, and reaction network modeling, diverse datasets can be generated to reveal the mechanistic foundations of interfacial processes. The integration of these datasets with artificial intelligence‐orchestrated workflows and machine learning models, such as closed‐loop optimization and large language model‐assisted hypothesis generation, enables the prediction of interphase behavior, linking molecular‐level EEI understanding and macroscale device performance, and data‐driven discovery of optimal material combinations. Critically, the review identifies persistent challenges, including limited data standardization, a shortage of high‐quality interoperable datasets, the gap between optimization and generalizable understanding, the limits of currently available self‐driving labs, and outlines mitigation strategies for building intelligent, data‐centric frameworks for rational engineering of next‐generation battery systems.

Despite the reported benefits of lithium difluorophosphate (LiDFP), studies on its physical and electrochemical properties remain limited. This work systematically investigates LiDFP and its potential for lithium metal battery (LMB) electrolytes using a combined experimental and theoretical approach. Solubility, ionic conductivity, viscosity, lithium‐ion transference number, diffusion coefficient, and contact angle are experimentally evaluated to provide a comprehensive understanding of its behavior. A key finding is the decoupling of ionic conductivity and viscosity at high concentrations. Additionally, Raman and nuclear magnetic resonance spectroscopy, along with molecular dynamics simulations, reveal the formation of large cation–anion aggregates at high concentrations, which facilitate lithium‐ion transport and contribute to the stabilization of the solid electrolyte interphase. The results reported herein emphasize the potential of LiDFP as an attractive component for advanced electrolyte formulations in energy storage, providing new insights into optimizing LMB performance.

Lithium metal batteries (LMBs) have the potential to significantly increase the energy density of advanced batteries in the future. Nonetheless, the dendritic lithium structures and low Coulombic efficiency (CE) of LMBs currently impede their applied implementation. Herein, a sulfite‐based electrolyte (SBE/FEC), including 1.0 m lithium bis(fluorosulfonyl)imide in a blend of ethylene sulfite and diethyl sulfite, and 5 wt% fluoroethylene carbonate is proposed. SBE/FEC is a highly efficient inhibitor against the growth of lithium dendrites through the formation of robust solid electrolyte interphase (SEI) layer. Raman spectroscopy and theoretical calculation indicate that in SBE/FEC, a significant portion of FSI⁻ exists in associated complexes, playing a vital role in the creation of LiF‐rich passivation. Besides, the sulfite solvents decompose and yield polysulfide complexes in the SEI layer. A direct correlation between the proportion of cation–anion complexes and the contact angle between electrolyte and separator is elucidated through molecular dynamics simulations. The SBE/FEC system exhibits high CEs (98.3%) with Li||Cu cells, along with a steady discharge capacity of ≈137 mA h g⁻¹ in Li||LiFePO₄ cell. This study presents an effective approach for enhancing LMBs with sulfite‐based electrolytes, which can lead to high‐energy‐density next‐generation rechargeable batteries.

Li-metal batteries (LMBs) are regarded as next generation storage devices for applications in a wide range of fields, such as electric vehicles and grid-scale energy storage. Unfortunately, their practical applications have been restricted by some defects including safety hazards, low coulombic efficiency (CE), and lithium dendrite growth. Inspired by the low-cost electrolytes in industrial applications, a low concentration bisalt electrolyte (LBE) for practical LMBs is proposed in this work. The synergistic effect of bisalt (0.3 M lithium bis(fluorosulfonyl)imide (LiFSI) and 0.2 M lithium bis(trifluoromethanesulfonyl)imide (LiTFSI)) and weakly solvating solvent (1,4-dioxane (DX)), provides robust and conductive solid/cathode electrolyte interphase (SEI/CEI) layers on the Li metal anode and LiFePO₄ (LFP) cathode, respectively. The majority of salt anions exist in associated states, such as contact ion pairs (CIPs) and aggregates (AGGs), as observed in highly concentrated electrolytes. These ion associates are involved in the formation of stable and LiF-rich SEI and CEI layers which suppress the dendrite growth on the Li anode and prevent parasitic reactions on the LFP cathode. The average CE of the Li‖Cu cells in the LBE was 99.2%. Furthermore, LBE also improved the cycling stability of a Li‖LiFP cell, with a capacity retention of 78.5% after 400 cycles. These results demonstrate the benefits of LBE, paving way for the industrial application of LCE.