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Abstract Two-dimensional materials (2DM) and their heterostructures (2D + nD, where n = 0, 1, 2, 3) hold significant promise for electrochemical energy storage systems (EESS), such as batteries. 2DM can act as van der Waals (vdW) slick interfaces between conventional active materials (e.g., silicon) and current collectors, enhancing interfacial adhesion and mitigating stress-induced fractures. They can also serve as alternatives to traditional polymer binders (e.g., MXenes), highlighting the importance of interfacial mechanics between 2DM and active materials. During charge/discharge cycles, intercalation and deintercalation processes substantially affect the mechanical behavior of 2DM used as binders, collectors, or electrodes. For example, porous graphene networks have demonstrated capacities up to five times greater than traditional graphite anodes. However, modeling 2DM in EESS remains challenging due to the complex coupling between electrochemistry and mechanics. Defective graphene, for instance, promotes strong adatom adsorption (e.g., Li⁺), which can hinder desorption during discharge, thereby influencing mechanical properties. Despite the promise of 2DM, most current studies fall short in capturing these critical chemo-mechanical interactions. This perspective provides a comprehensive overview of recent advances in understanding the mechanical behavior of 2DM in EESS. It identifies key modeling challenges and outlines future research directions. Multiscale modeling approaches—including atomistic and molecular simulations, continuum mechanics, machine learning, and generative artificial intelligence—are discussed. This work aims to inspire deeper exploration of the chemo-mechanics of 2DM and offer valuable guidance for experimental design and optimization of 2DM-based EESS for practical applications. 

The development of next-generation energy storage systems relies on discovering new materials that support multivalent-ion transport. Transition metal oxides (TMOs) are promising due to their structural versatility, high ionic conductivity, and ability to accommodate multiple charge carriers. However, their vast compositional and structural diversity makes traditional exploration inefficient. This work presents a generative AI framework combining a crystal diffusion variational autoencoder (CDVAE) and a fine-tuned large language model (LLM) to discover porous oxide materials. Thousands of candidate structures are generated and screened for structural validity, thermodynamic stability, and electronic properties using a graph-based machine learning model and density functional theory (DFT) calculations. CDVAE identifies a broader variety of structures, including five novel TMO-based candidates, while LLM excels in generating highly stable structures near equilibrium. This approach demonstrates the power of generative AI in accelerating the discovery of advanced battery materials for multivalent-ion storage. 

Lithium-ion batteries (LIBs) are ubiquitous in everyday applications. However, Lithium (Li) is a limited resource on the planet and, therefore, not sustainable. As an alternative to lithium, earth-abundant and cheaper multivalent metals such as aluminum (Al) and calcium (Ca) have been actively researched in battery systems. However, finding suitable intercalation hosts for multivalent-ion batteries is urgently needed. Open-tunneled oxides represent a specific category of microparticles distinguished by the presence of integrated one-dimensional channels or nanopores. This work focuses on two promising open-tunnel oxides: Niobium Tungsten Oxide (NTO) and Molybdenum Vanadium Oxide (MoVO). The MoVO structure can accommodate a larger number of multivalent ions than NTO due to its larger surface area and different shapes. Specifically, the MoVO structure can adsorb Ca, Li, and Al ions with adsorption potentials ranging from around 4 to 5 eV. However, the adsorption potential for hexagonal channels of Al ion drops to 1.73 eV due to the limited channel area. The NTO structure exhibits an insertion/adsorption potential of 4.4 eV, 3.4 eV, and 0.9 eV for one Li, Ca, and Al, respectively. Generally, Ca ions are more readily adsorbed than Al ions in both MoVO and NTO structures. Bader charge analysis and charge density plots reveal the role of charge transfer and ion size in the insertion of multivalent ions such as Ca and Al into MoVO and NTO systems. Exploring open-tunnel oxide materials for battery applications is hindered by vast compositional possibilities. The execution of experimental trials and quantum-based simulations is not viable for addressing the challenge of locating a specific item within a large and complex set of possibilities. Therefore, it is imperative to conduct structural stability testing to identify viable combinations with sufficient pore topologies. Data mining and machine learning techniques are employed to discover innovative transitional metal oxide materials. This study compares two machine learning algorithms, one utilizing descriptors and the other employing graphs to predict the synthesizability of new materials inside a laboratory setting. The outcomes of this study offer valuable insights into the exploration of alternative naturally occurring multiscale particles. 

Abstract The development of next-generation batteries, utilizing electrodes with high capacities and power densities requires a comprehensive understanding and precise control of material interfaces and architectures. Electro-chemo-mechanics plays an integral role in the morphological evolution and stability of such complex interfaces. Volume changes in electrode materials and the chemical interactions of electrode/electrolyte interfaces result in nonuniform stress fields and structurally different interphases, fundamentally affecting the underlying transport and reaction kinetics. The origin of this mechanistic coupling and its implications on degradation is uniquely dependent on the interface characteristics. In this review, the distinct nature of chemo–mechanical coupling and failure mechanisms at solid–liquid interfaces and solid–solid interfaces is analyzed. For lithium metal electrodes, the critical role of surface/microstructural heterogeneities on the solid electrolyte interphase (SEI) stability and dendrite growth in liquid electrolytes, and on the onset of contact loss and filament penetration with solid electrolytes is summarized. With respect to composite electrodes, key differences in the microstructure-coupled electro-chemo-mechanical attributes of intercalation- and conversion-based chemistries are delineated. Moving from liquid to solid electrolytes in such cathodes, we highlight the significant impact of solid–solid point contacts on transport/mechanical response, electrochemical performance, and failure modes such as particle cracking and delamination. Finally, we present our perspective on future research directions and opportunities to address the underlying electro-chemo-mechanical challenges for enabling next-generation lithium metal batteries.