Results 111 to 120 of about 41,374 (268)

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

Enhanced Performance of Optoelectronic Devices Using Metal Chalcogenide Complex Ligands‐Capped InAs/ZnSe Quantum Dots as Electron Transport Layers

Advanced Energy Materials, EarlyView.
Thin‐shell InAs/ZnSe quantum dots functionalized with metal chalcogenide ligands were employed as electron transport layers in organic optoelectronic devices, yielding optimized conduction band alignment and film morphology. Consequently, the devices achieved enhanced charge transport, a detectivity of ∼1013 Jones, and a power conversion efficiency of ...
Yonghoon Choi, Seyeong Song, Dain Choi, Jinho Shin, Yeonjeong Lee, Jaehyeong Kim, Jeongmin Son, Jin Young Kim, Jongnam Park   +8 more
wiley   +1 more source

Donor–Acceptor Covalent Organic Framework Enables Ambipolar Charge Storage in Aluminum‐Ion Energy Storage

Advanced Energy Materials, EarlyView.
A donor–acceptor covalent organic framework is designed as an ambipolar cathode for aluminum‐ion energy storage. The crystalline, microporous architecture enables intrinsic charge transport without conductive additives. Multi‐electron redox activity at donor and acceptor sites supports high capacity, excellent stability, and efficient reversible ...
Cataldo Valentini, Verónica Montes‐García, Wojciech Kukułka, Saira Sarwar, Michał Bielejewski, Mateusz Wlazło, Rossella Greco, Viktorija Pankratova, Ignacio Pérez‐Juste, Dawid Pakulski, Paolo Samorì, Artur Ciesielski   +11 more
wiley   +1 more source

Modulation of Local Environment for Selective Bicarbonate Conversion to Multi‐Carbon Products

Advanced Energy Materials, EarlyView.
Highly porous Cu electrode partially coated with an ionomer/carbon composite enables efficient conversion of bicarbonate to multi‐carbon products. By regulating the local reaction microenvironment, this strategy overcomes selectivity and reaction‐rate limitations, achieving Faradaic efficiencies of 43% for ethylene and 60% for total multi‐carbon ...
Tai Nguyen, Anh N. Nguyen, Guorui Gao, Jackson Crane, Thành Trần‐Phú, Gelson Tavares da Silva, Aldo Gonzalez‐Lopez, Hung Lai, Khac Huy Dinh, Duc‐Minh Phan‐Pham, Martin Guay, Carlos Escobedo, Rosalie K. Hocking, Jonathan Raisin, Lucia H. Mascaro, Cao‐Thang Dinh   +15 more
wiley   +1 more source

FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

Advanced Intelligent Discovery, EarlyView.
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker, Enzo Raffaele Moretti, Jin Hyun Chang, Tejs Vegge   +3 more
wiley   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

Improved active current limiting control for flexible DC power grid to consider the effects of selective and higher fault resistance. [PDF]

Sci Rep
Qin X, Hou J, Fan Y, Song G, Wu X.
europepmc   +1 more source

Autonomous X‐Ray Fluorescence Mapping for Nanoscale Chemical Speciation of Fine Particulate Matter

Advanced Intelligent Discovery, EarlyView.
We present X‐AutoMap, an autonomous X‐ray fluorescence mapping framework that integrates real‐time analysis with rule‐based computer vision to selectively target chemically relevant regions. By avoiding background‐dominated areas, the method reduces acquisition time by fourfold while enabling accurate particle‐level speciation.
Carlos Deleon, Dmitri Gavrilov, Peggy O’Day, Ajith Pattammattel   +3 more
wiley   +1 more source

Enhancing grid stability using dynamic reserve power point tracking techniques. [PDF]

PLoS One
Kumar S, Venkatakrishnan GR, Rengaraj R, Kumar A, Kumar P.   +4 more
europepmc   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source