Results 21 to 30 of about 1,095 (107)

Emerging Materials and Future Strategies for Solid Oxide Electrochemical Cells

Advanced Energy Materials, EarlyView.
Solid oxide electrochemical cells operate under strongly coupled electrochemical and thermodynamic conditions, where performance is constrained by interactions among crystal structure, defect chemistry, and interfacial evolution. This review, based on a structure‐defect‐property‐durability framework, reveals the roles of lattice symmetry and defect ...
Qiuchun Lu, Yufei Zhang, Han Zhao, Pooi See Lee, Daniel H.C. Chua   +4 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

First‐Principles Study of Structural, Mechanical, Electronic, Thermodynamical, and Optical Properties of XGaO2 (X = Rb and Cs): Unlocking Its Green Energy Potential

Advanced Physics Research, EarlyView.
This study employs density functional theory (DFT) to investigate the structural, mechanical, electronic, optical, and thermodynamic properties of RbGaO2 and CsGaO2. The calculated band structures and band‐edge positions indicate semiconducting behavior and favorable alignment for photocatalytic dye degradation and hydrogen evolution, highlighting ...
Md. Zuel Rana, Md. Saiful Islam, Jahid Hasan, Abdul Barik, Mahamud Hasan Reedoy, Afroza Khatun, Md. Abde Mannaf, Ehesanul Hoq, Neelufar Panna, M. S. Alam   +9 more
wiley   +1 more source

Ab‐Initio Study of Structural, Magnetic, Optoelectronic and Thermophysical Properties of Heusler Compound HoPdBi

Advanced Physics Research, EarlyView.
The top panel shows the electronic band structure, which illustrates how the electronic energy varies with momentum along different high‐symmetry directions within the first Brillouin zone. Band structure determines the electronic character of a crystalline solid.
Tanvir Khan, F. Parvin, S. H. Naqib
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Beyond Activity: The Unified Framework of the Sabatier Principle to Guide Rational Design of Durable and Active Electrocatalysts

Carbon Energy, EarlyView.
In this review, a unified framework of the Sabatier principle is applied to a diverse range of catalytic and electrocatalytic systems for advanced clean energy technologies, with a particular focus on the oxygen reduction reaction (ORR). This approach will guide the design and development of highly active and stable catalysts for fuel cells ...
Wanying Zhang, Quan Zhou, Xuanxuan Bi, Luo Luo, Yunxiang Cheng, Rongyue Wang, Zhongwei Chen   +6 more
wiley   +1 more source

Heterogeneous Single/Dual‐Atom Electrocatalysts in Lithium–Sulfur Batteries

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This review summarizes recent advances in single‐atom and dual‐atom electrocatalysts for high‐performance lithium–sulfur batteries. The text systematically covers the classification of catalysts by active metal centers, key synthesis methods, in situ characterization for mechanistic insights, and electrocatalytic mechanisms.
Wenbin Li, Ying Xin, Zhaoliang Zhang, Jin Wang   +3 more
wiley   +1 more source

Generative Models in Inorganic Crystals Discovery and Inverse Design

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Generative inverse‐design samples from the vast inorganic crystal design space by starting from target properties such as band gap, stability, and ion transport. This Review examines the representations, generative models, and validation workflows needed to translate candidate structures into stable, potentially synthesizable materials for applications
Tao Li, Xiaolin Liu, Fei Wang, Yan Xiong, Yu Chen, Yan Zhao   +5 more
wiley   +1 more source