Results 141 to 150 of about 2,452 (216)

Realization of Kagome Kondo lattice. [PDF]

Nat Commun
Song B, Xie Y, Li WJ, Liu H, Chen J, Tian S, Zhang X, Wang Q, Li X, Lei H, Zhang Q, Guo JG, Zhao L, Yu SL, Zhou X, Chen X, Ying T.   +16 more
europepmc   +1 more source

Investigation Into the Electrochemical Performance of Micron‐ and Nanosized Tin in Diglyme and Carbonate Electrolytes in Sodium Ion Batteries

Advanced Energy Materials, EarlyView.
This study compares Sn particles of different sizes in NIBs using carbonate‐ and diglyme‐based electrolytes. Diglyme electrolytes enable stable cycling despite large volume changes, while carbonate electrolytes degrade rapidly, especially with nanoparticles.
Chinnasamy Murugesan, Aaron B. Naden, Paul A. Connor, A. Robert Armstrong, John T. S. Irvine   +4 more
wiley   +1 more source

Imaging the flat bands of magic-angle graphene reshaped by interactions. [PDF]

Nature
Xiao J, Inbar A, Birkbeck J, Gershon N, Zamir Y, Vituri Y, Taniguchi T, Watanabe K, Berg E, Ilani S.   +9 more
europepmc   +1 more source

Organic Photoelectrochemical Cells Beyond Performance: Interface and Catalyst Engineering for Durability

Advanced Energy Materials, EarlyView.
Organic photoelectrochemical cells based on π‐conjugated semiconductors offer a versatile platform for solar fuel generation. This review outlines operating principles, device architectures, and key metrics, and highlights advances in p‐ and n‐type photoelectrodes, interfacial engineering, and catalyst integration.
Jaehyeong Kim, Jung Min Ha, Yeonjeong Lee, Seung Won Oh, Wangyeon Lee, Munsu Kwon, Soonyong Lee, Jin Young Kim, Han Young Woo   +8 more
wiley   +1 more source

Cavity-mediated charge and pair-density waves in a unitary Fermi gas. [PDF]

Nat Commun
Zwettler T, Marijanovic F, Bühler T, Chattopadhyay S, Del Pace G, Skolc L, Helson V, Uchino S, Demler E, Brantut JP.   +9 more
europepmc   +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

Linking DSC/TGA to Cell Levels: Energetics, Evolved Gases, and Thermal Safety of NMC811‐Graphite Micro‐Cell

Advanced Energy Materials, EarlyView.
A bottom‐up, component‐resolved framework combining DSC/TGA, evolved gas analysis, and in situ XRD reveals how decomposition pathways control energy release in partial and micro‐cell configurations. Separator‐free assemblies are dominated by cathode‐O2${\rm O}_2$/anode‐Li reactions, while the separator restricts oxygen transport, reshapes the reaction ...
Ayrton M. Yanyachi, Lingmin Lin, Siddhartha Nanda, Wenlong Li, Yijin Liu, Steven Swinnea, Hadi Khani, Donal Finegan, Ofodike A. Ezekoye   +8 more
wiley   +1 more source

Hund's flat band in a frustrated spinel oxide. [PDF]

Proc Natl Acad Sci U S A
Oh D, Hampel A, Wakefield JP, Moen PC, Smit S, Luo X, Zonno M, Gorovikov S, Leandersson M, Polley C, Kundu AK, Rajapitamahuni A, Vescovo E, Jozwiak C, Bostwick A, Rotenberg E, Isobe M, Verma M, Crispino M, Grundner M, Kugler FB, Parcollet O, Schollwöck U, Takagi H, Damascelli A, Sangiovanni G, Checkelsky JG, Georges A, Comin R.   +28 more
europepmc   +1 more source

Three-dimensional numerical analysis of switching properties of high-speed and non-volatile nanoelectromechanical memory

, 2007
Mizuta, Hiroshi, Tadashi Arai, Shunri Oda, Momo, N., Oda, S., Shimada, T., Yoshishige Tsuchiya, Tsuchiya, Yoshishige, Arai, T., Saito, S., Nagami, T., Tasuku Nagami, Nobuyuki Momo, Shin-ichi Saito, Hiroshi Mizuta, Toshikazu Shimada   +15 more
core   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source