Results 151 to 160 of about 12,756 (264)

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Achieving Phonon‐Glass Electron‐Crystal Behavior in Fully Organic Flexible Thermoelectrics

Advanced Energy Materials, EarlyView.
Phonon‐glass Electron‐crystal (PGEC) behavior is demonstrated in fully organic composites consisting of conductive polymers (PEDOT:PSS) and soft polymeric fillers (PVA). The optimized PEDOT:PSS–PVA composite concurrently reveals delocalized transport and thermal conductivity close to its theoretical minimum, yielding a superior thermoelectric figure of
Jeong Han Song, Seunghwan Lee, Sunwoo Cho, Beomsoo Chun, Hyejin Jang, Jeonghun Kwak   +5 more
wiley   +1 more source

Structural heterogeneity-induced enhancement of transverse magneto-thermoelectric conversion revealed by thermoelectric imaging in functionally graded materials. [PDF]

Sci Technol Adv Mater
Park SJ, Gautam R, Yagi T, Modak R, Sepehri-Amin H, Uchida KI.   +5 more
europepmc   +1 more source

Redox‐Mediated Aluminum–Air Fuel Cells With Suppressed Hydrogen Evolution for Durable Power Generation

Advanced Energy Materials, EarlyView.
The redox‐mediated aluminum–air fuel cell (RM‐AAFC) integrates a soluble redox mediator, 7,8‐dihydroxy‐2‐phenazine sulfonic acid (DHPS), to facilitate the oxidation of aluminum and inhibit hydrogen evolution reaction (HER) through competitive reactions between DHPS reduction and HER on the Al surface.
Yuxi Song, Hang Zhang, Zhongheng Fu, Zeyun Gu, Lingchao Xia, Haoyang Guo, Jiahao Zhuang, Yizhuo He, Linghang Meng, Zhi Wei Javier Ang, Qing Wang   +10 more
wiley   +1 more source

Towards the practical realization of high-performance Ag₂Se-based thermoelectric coolers. [PDF]

Sci Technol Adv Mater
Jiang F, Wang Z, Zhong W, Zhou Y, Zhou Z, Wu L, Chen J, Xu Y, Wang X, Cao F, Zhang Q, Mao J.   +11 more
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

Synergistically Optimizing the Thermoelectric Performance of n-Type SnS through an Integrated Systematic Approach. [PDF]

ACS Appl Mater Interfaces
Duraisamy S, Chen YY, Chen KH, Wu MK, Peramaiyan G, Ranganayakulu VK, Wollele MB, Ou MN.   +7 more
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, Ogheneyoma Aghoghovbia, Mohammed Al‐Fahdi, Lingyu Kong, Victor Fung, Ming Hu   +5 more
wiley   +1 more source

A microwave-programmable abiotic/biotic hybrid system for integrated tumor eradication, immune activation, and bone regeneration. [PDF]

Mater Today Bio
Deng X, Ze R, Li J, Hong P, Li J, Wang W, Tan L, Chen C.   +7 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, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source