Triply periodic minimal surfaces have become ideal templates for fabricating porous materials with customized properties owing to excellent geometric tunability. Herein, a novel nonuniform Gyroid lattice with an innovative “X”‐shaped reinforced domain is proposed to improve the quasi‐static compressive performance of uniform Gyroid lattices. Uniform Gyroid (UG) and nonuniform reinforced Gyroid (XG) lattices made of Ti─6Al─4V are fabricated by selective laser melting, and their quasi‐static mechanical properties are comprehensively characterized and analyzed via experiments and numerical simulations. The experimental results demonstrate that properly designed XG configurations achieve superior comprehensive mechanical performance compared with the UG lattice. Adjusting the width of the reinforced domain exerts significant effects on specific elastic modulus, specific initial peak stress, and specific plateau stress, while rotating the reinforced domain obviously affects specific energy absorption (SEA). Further numerical investigations reveal that within the range of the investigated structural parameters, the optimal reinforced domain width and rotation angle are 9/40 and 45°, respectively, to achieve maximum SEA. These findings can provide valuable insights and design guidance for developing high‐performance triply periodic minimal surfaces lattice structures.
While fluorine‐free superhydrophobic (SH) coatings and phase change material (PCM)‐integrated SH systems have been reported independently, no prior work has combined natural nanoclay‐reinforced epoxy with fluorine‐free sol–gel chemistry to deliver both SH wettability and high latent heat storage capacity within a single scalable framework. Building on previously established flow‐resistant SH architectures, this work fabricates state‐dependent dual‐functional nanocomposite coatings—superhydrophobic in their native state (contact angles ≈150° and sliding angles ≈3°) and active thermal energy storage materials upon PCM incorporation—using an epoxy matrix reinforced with naturally abundant Halloysite and Sepiolite nanoclays. Reduction of work of adhesion and contact angle hysteresis is achieved through Polysilsesquioxane (PSQ) sol–gel modification using either a conventional fluorosilane or a fluorine‐free alkylsilane alternative, validating trimethoxyoctylsilane as an effective fluorosilane replacement. Systematic variation of formulation demonstrates iluentsy of the porous reentrant architecture leading to paraffin PCM uptake control, with most compositions approaching 50 wt% and the optimized case yielding ≈63 wt% for latent heat storage. Halloysite/alkylsilane composites enhance 10% the PCM loading relative to Halloysite/fluorosilane counterparts; conversely, fluorosilane‐modified formulations exhibit lower work of adhesion. Compositional and synthetic control thus emerges as the key design lever for navigating competing functional demands.
The growing availability of structured battery databases opens new opportunities for data‐driven quality control in battery manufacturing. Efficient identification of anomalous cells is critical for ensuring safety, performance, and longevity. In this work, we present a machine‐learning‐based framework for detecting anomalous cell behavior using rate‐test data and electrochemical impedance spectroscopy (EIS) measurements. A curated battery database serves as a reference and filter, enabling systematic comparison across 29 distinct coin cell configurations, each comprising 4–14 nominally identical cells. Rate‐test anomaly prediction using a support vector classifier (SVC) with a radial basis function (RBF) kernel yields a test accuracy of 90%, whereas anomaly detection based on EIS data with a convolutional variational autoencoder (CNN‐VAE) achieves an accuracy of 83.3%. Overall, these findings demonstrate the promise of combining structured battery datasets with advanced machine‐learning techniques to enable automated, accurate, and scalable diagnostic pipelines for next‐generation energy storage systems.
