Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Magnesium-based thermoelectric materials and modules for low-temperature applications (below 300°C). [PDF]
MRS BullHe R, Ying P, Chen S, Ren Z, Nielsch K.
europepmc +1 more source
Toward Environmentally Friendly Hydrogel‐Based Flexible Intelligent Sensor Systems
Advanced Intelligent Discovery, EarlyView.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
Characterization and Preparation of Nanostructured Al<sub>2</sub>Fe<sub>3</sub>Si<sub>3</sub> Thermoelectric Materials. [PDF]
Materials (Basel)Zhao Z, Ikeda T.
europepmc +1 more source
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
Advanced Intelligent Discovery, EarlyView.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
The Design of Intrinsically Conductive Metal-Organic Frameworks for Thermoelectric Materials. [PDF]
Small SciMcVea M +3 more
europepmc +1 more source
Advancing Thermoelectric Materials: A Comprehensive Review Exploring the Significance of One-Dimensional Nano Structuring. [PDF]
Nanomaterials (Basel), 2023 Al-Fartoos MMR +3 more
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.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
Nano-engineered thin-film thermoelectric materials enable practical solid-state refrigeration. [PDF]
Nat CommunBallard J +9 more
europepmc +1 more source