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Shailaja Keyur Sampat

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Review Aug 2026

MXenes From Fundamentals to Market: Structural Characteristics, Emerging Synthesis Routes, Applications, and AI‐Accelerated Innovations

MXenes, a rapidly growing family of two‐dimensional transition‐metal carbides, nitrides, and carbonitrides have attracted significant attention because of their layered structures, metallic conductivity, and tunable surface chemistry. These unique characteristics allow precise control of their physical, and chemical properties, making them promising materials for diverse advanced applications. This review provides an overview of recent progress in MXene research, covering their structure, synthesis, properties, and applications. The structural characteristics of MXenes, including atomic arrangements, surface terminations, and interlayer interactions, are discussed to explain their influence on electrical, thermal, optical, and electrochemical behavior. Recent advances in synthesis methods are then examined, including conventional top‐down etching techniques and emerging fluoride‐free, hydrothermal, and scalable approaches that aim to improve safety, reproducibility, and industrial applicability. The review further highlights important structure–property relationships, emphasizing the roles of compositional tuning, surface functionalization, and hybridization in controlling charge transport, ion diffusion, mechanical flexibility, and stability. Finally, recent MXene applications in energy storage, smart textiles, healthcare, environmental remediation, and electromagnetic interference shielding are reviewed, together with the growing role of artificial intelligence in materials design and performance optimization.

Vaibhav Jain, Bhavya Jain, Ashish Kalkal et al. · 0 citations
Preprint Jul 2026

Data Analysis in the Wild: Benchmarking Large Language Models Against Real-World Data Complexities

DataGovBench is introduced, a benchmark derived from governmental open data designed to evaluate LLMs in practical scenarios that includes two tasks: Table QA that requires solving complex decomposable questions and producing textual answers or visualizations, and Table Insight that evaluates the ability of models to generate expert-level findings through exploratory data analysis.

So Hasegawa, Shailaja Keyur Sampat, Lei Liu et al. · 0 citations