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By tuning the composition of the non-solvent bath used in the non-solvent induced phase inversion process for fabricating thick and low-tortuosity battery electrodes, optimal electrochemical performances and compressive modulus were achieved. 

Abstract Texturing the battery electrode to create low‐tortuosity ordered structures can significantly improve the sluggish mass transport in thick electrodes (areal mass loading>20 mg/cm²) during the energy storage electrochemical reactions. In this work, we presented an efficient and effective method to regulate the electrode structure by creating aligned channels throughout the thickness of the electrode. The method combines acoustic manipulation of particles and nonsolvent induced phase inversion and is highly compatible with a wide range of materials used in various battery chemistries. The textured electrodes show better structural integrity compared to electrodes of similar mass loading made with acoustic patterning only and with conventional solution casting. Compared with electrodes made with phase inversion only, it exhibits lower tortuosity, enhanced ion transport/kinetics, better rate capability and cyclic stability. 

Bioorthogonal reactions are powerful tools for studying and manipulating biological systems, yet achieving precise spatial and temporal control remains a major challenge. Here, we introduce cyclopropanol (CPol) as a compact, energy-loaded warhead that remains inert under physiological conditions and is selectively activated by mild electrochemical stimuli. This strategy generates reactive β-haloketone moieties in situ, enabling dual-function bioconjugation for cellular labeling and proteomic analysis. Upon oxidative ring opening, CPol preferentially modifies carboxylic acid-containing residues, such as glutamate and aspartate, rather than the expected tyrosine or tryptophan. The electrochemical activation of CPol is biocompatible in living systems, enabling direct protein labeling, real-time visualization with a fluorogenic CPol probe, and selective targeting of membrane-associated and cytoplasmic proteins with a choline-derived probe through integration into cellular phosphatidylcholine metabolism. Coupling bioorthogonality with electrochemical control, this approach enables precise protein profiling, live-cell imaging, and broader applications in chemical biology. 

An acoustic particle patterning method generated ordered structures in battery electrodes to facilitate lithium-ion diffusion and charge transport kinetics, allowing superior rate capability and cycling stability over conventional electrodes. 

State of health (SOH) estimation of lithium-ion batteries has typically been focused on estimating present cell capacity relative to initial cell capacity. While many successes have been achieved in this area, it is generally more advantageous to not only estimate cell capacity, but also the underlying degradation modes which cause capacity fade because these modes give further insight into maximizing cell usage. There have been some successes in estimating cell degradation modes, however, these methods either require long-term degradation data, are demonstrated solely on artificially constructed cells, or exhibit high error in estimating late-life degradation. To address these shortfalls and alleviate the need for long-term cycling data, we propose a method for estimating the capacity of a battery cell and diagnosing its primary degradation mechanisms using limited early-life degradation data. The proposed method uses simulation data from a physics-based half-cell model and early-life degradation data from 16 cells cycled under two temperatures and C rates to train a machine learning model. Results obtained from a four-fold cross validation study indicate that the proposed physics-informed machine learning method trained with only 60 early life data (five data from each of the 12 training cells) and 30 high-degradation simulated data can decrease estimation error by up to a total of 9.77 root mean square error % when compared to models which were trained only on the early-life experimental data.