Toward Environmentally Friendly Hydrogel‐Based Flexible Intelligent Sensor Systems
This review summarizes environmentally and biologically friendly hydrogel‐based flexible sensor systems focusing on physical, chemical, and physiological sensors. Furthermore, device concepts moving forward for the practical application are discussed about wireless integration, the interface between hydrogel and dry electronics, automatic data analysis
Sudipta Kumar Sarkar, Kuniharu Takei
wiley +1 more source
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam +5 more
wiley +1 more source
Length-dependent quantum interference and high thermoelectric response ferrocene-modified OPE wires. [PDF]
Al-Jobory AA +3 more
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang +3 more
wiley +1 more source
First-principles study of X<sub>2</sub>TlAgCl<sub>6</sub> (X = K, Rb, Cs) double perovskites for high-performance optoelectronic and thermoelectric devices. [PDF]
Shah SH +4 more
europepmc +1 more source
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley +1 more source
Comparative Study of Ni Doping (0-0.3 wt %) in Bi<sub>2</sub>Se<sub>3</sub> Polycrystalline Materials Synthesized via a Solvothermal Method: Structural, Optical, and Thermoelectric Analysis. [PDF]
Zaqa M +8 more
europepmc +1 more source
Doping in Organic Semiconductors: Fundamentals, Materials, and Applications
Advanced Electronic Materials, EarlyView.
Sergi Riera‐Galindo
wiley +1 more source

