Results 111 to 120 of about 5,576 (252)

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

Solution Synthesis of Actinide Chalcogenide and Oxychalcogenide Nanoparticles

Angewandte Chemie, EarlyView.
We report the synthesis of UOS, UOSe, and US2 nanoparticles under colloidal conditions. The magnetic properties were measured of all three materials and compared to prior studies of UO2 nanoparticles. Nanoparticle phases were determined using powder diffraction, and size by transmission electron microscopy.
Cheyenne Orozco, Orlando C. Stewart Jr., Nicole Vanagas, Greg Morrison, Hans‐Conrad zur Loye, Hope E. Smith, Karah Knope, Sarah L. Stoll   +7 more
wiley   +2 more sources

Correction to: Memristive Devices Based on Two-Dimensional Transition Metal Chalcogenides for Neuromorphic Computing. [PDF]

Nanomicro Lett, 2022
Kwon KC, Baek JH, Hong K, Kim SY, Jang HW.   +4 more
europepmc   +1 more source

Design Principles of Electrocatalysts for Industrial‐Scale Water Electrolysis

Advanced Energy Materials, EarlyView.
This Review distills electrocatalyst design for industrial‐scale water electrolysis into integrated principles linking active‐site engineering, phase and lattice modulation, interfacial microenvironment regulation and mass‐transport control. By connecting catalyst families with HER/OER mechanisms and practical operating demands, it outlines pathways ...
Hong Tang, Cui Ce, John Wang
wiley   +1 more source

Functionalization‐Mediated Synthesis of Bridge‐Coordinated Fe Atoms on MoS2 Nanosheets for PEM Water Electrolyzers

Angewandte Chemie, EarlyView.
We report a functionalization‐mediated strategy to synthesize robust iron (Fe) atoms selectively coordinated at bridge sites on molybdenum disulfide (MoS2) nanosheets. The resulting b‐Fe‐MoS2 catalyst exhibits enhanced activity and durability for the hydrogen evolution reaction in proton exchange membrane water electrolyzers compared to atop ...
Zakaria Anfar, Haitham Maslouh, Yuwei Yang, Mathilde Moderne, Jiefeng Liu, Loïc Assaud, Mikhael Bechelany, Chrystelle Salameh, Kun Qi, Yuying Meng, Huali Wu, Ji Li, Nicholas M. Bedford, Damien Voiry   +13 more
wiley   +2 more sources

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

Advanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz, Gisya Abdi, Andrzej Sławek, Marlena Gryl, Konrad Szaciłowski   +4 more
wiley   +1 more source

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Synthesis and Electrocatalytic Applications of Noble Metal Chalcogenides Nanomaterials

ChemElectroChem
In this review, we first focus on summarizing recent advances in effective and facile strategies for the ration synthesis of noble metal chalcogenide nanomaterials (NMCNs), and then, we systematically introduce their applications in catalyzing typical ...
Zhenya Hu, Li Huang, Lin Xu, Dr. Hui Liu, Dr. Shaonan Tian, Prof. Jun Yang   +5 more
doaj   +1 more source

Opening the pathway towards a scalable electrochemical semi-hydrogenation of alkynols via earth-abundant metal chalcogenides. [PDF]

Chem Sci, 2022
Pellumbi K, Wickert L, Kleinhaus JT, Wolf J, Wolf J, Leonard A, Tetzlaff D, Goy R, Medlock JA, Junge Puring K, Cao R, Siegmund D, Apfel UP.   +12 more
europepmc   +1 more source