Abstract Developing safe, high‑energy‑density energy storage systems is a central goal in electrochemistry. Silicon (Si) delivers a high theoretical specific capacity of 4200 mAh g-1, yet it suffers from severe volume expansion and interfacial degradation. Solid-state electrolytes (SSEs) can exert mechanical confinement and enable the formation of self-limited interfaces, rendering silicon-carbon (Si-C)/SSEs composite a highly promising anode system. This paper first analyzes the failure mechanisms in liquid-electrolyte systems, followed by an elaboration on the distinctive merits of Si-C-based solid-state anodes. Meanwhile, it identifies the core challenges confronting this system, including rigid interfacial contact, dynamic stress, and process compatibility issues. Recent research advances are reviewed from three critical perspectives: intrinsic material modification, interface engineering, and fabrication process optimization, covering diverse modification strategies at both the material and electrode levels. Finally, future research directions are prospected, with emphases on integrated material-device design, advanced in-situ characterization techniques, and artificial intelligence-empowered research and development, aiming to accelerate the practical deployment of low-voltage, high-energy-density solid-state batteries.
Investigating how experienced developers use agents in building software, including their motivations, strategies, task suitability, and sentiments finds that while experienced developers value agents as a productivity boost, they retain their agency in software design and implementation out of insistence on fundamental software quality attributes.
An adaptive surrogate modeling method for problems with very high-dimensional spatio-temporal outputs is developed that combines exploration and exploitation to improve the surrogate model accuracy with the fewest possible runs of the expensive physics-based model.
B. Kapusuzoglu, S. Mahadevan, Shunsaku Matsumoto et al.· Structural And Multidiscipli...· 17 citations
An adaptive jailbreak attack framework for systematic evaluation of both cascaded pipelines and end-to-end large audio-language models under a unified experimental setting that achieves consistently higher attack success rates across diverse audio-based LLM systems.
Linghan Huang, Bo Li, Huaming Chen et al.· 12 citations· ⚡2
This review provides a systematic literature review of LLM-based Verilog code generation, analyzing 102 papers (70 published and 32 high-quality preprints) from SE, AI, and EDA venues and outlines a roadmap highlighting potential opportunities in LLM-assisted hardware design.
This work introduces Behavior-Outcome Freedom (F), a pre-synthesis diagnostic of signed behavior-outcome rank mismatch, and formalizes its candidate-conditional role through Signed Anchor-Rank Transfer, which preserves validated capability resources, removes runtime orchestration, and conditionally inherits pipeline guidance using a calibrated rule over F.
Binyan Xu, Dong Fang, Haitao Li et al.· arXiv.org· 10 citations
Simulation results confirm the effectiveness and benefits of DMs in generating neighbor velocity estimates in a four-UAV swarm coordination task using Deep Reinforcement Learning (DRL), and explore the integration of DMs with RL and DT.