Results 121 to 130 of about 1,256,985 (257)

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing

Advanced Functional Materials, EarlyView.
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy, Chuan‐En Lu, Kai Liu, Audrey Gallud   +3 more
wiley   +1 more source

Universal Electronic‐Structure Relationship Governing Intrinsic Magnetic Properties in Permanent Magnets

Advanced Functional Materials, EarlyView.
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley   +1 more source

Data-Driven Knowledge Fusion for Deep Multi-Instance Learning

IEEE Transactions on Neural Networks and Learning Systems
Multi-instance learning (MIL) is a widely-applied technique in practical applications that involve complex data structures. MIL can be broadly categorized into two types: traditional methods and those based on deep learning. These approaches have yielded significant results, especially with regards to their problem-solving strategies and experimental ...
Yu-Xuan Zhang, Zhengchun Zhou, Xingxing He, Avik Ranjan Adhikary, Bapi Dutta   +4 more
openaire   +3 more sources

Intermediate Resistive State in Wafer‐Scale Vertical MoS2 Memristors Through Lateral Silver Filament Growth for Artificial Synapse Applications

Advanced Functional Materials, EarlyView.
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa, Milan Buttberg, Ke Ran, Rana Walied Ahmad, Dennis Braun, Lukas Völkel, Jimin Lee, Sofía Cruces, Bart Macco, Bárbara Canto, Holger Lerch, Thorsten Wahlbrink, Holger Kalisch, Michael Heuken, Andrei Vescan, Joachim Mayer, Zhenxing Wang, Ilia Valov, Stephan Menzel, Max C. Lemme   +19 more
wiley   +1 more source

Bio‐Inspired Molecular Events in Poly(Ionic Liquids)

Advanced Functional Materials, EarlyView.
Originating from dipolar and polar inter‐ and intra‐chain interactions of the building blocks, the topologies and morphologies of poly(ionic liquids) (PIL) govern their nano‐ and micro‐processibility. Modulating the interactions of cation‐anion pairs with aliphatic dipolar components enables the tunability of properties, facilitated by “bottom‐up ...
Jiahui Liu, Marek W. Urban
wiley   +1 more source

Pixelation‐Free, Monolithic Iontronic Pressure Sensors Enabling Large‐Area Simultaneous Pressure and Position Recognition via Machine Learning

Advanced Functional Materials, EarlyView.
A pixelation‐free, monolithic iontronic pressure sensor enables simultaneous pressure and position sensing over large areas. AC‐driven ion release generates spatially varying impedance pathways depending on the pressure. Machine learning algorithms effectively decouple overlapping pressure–position signals from the multichannel outputs, achieving high ...
Juhui Kim, Junseo Lee, Kwang‐Hun Choi, Seongil Im, Jae Hong Kim, Changsoon Choi, Junghwan Byun, Changhwan Shin, Ho Won Jang, Hyunsu Ju, Jung Ah Lim   +10 more
wiley   +1 more source

From Wafers to Electrodes: Transferring Automatic Optical Inspection (AOI) for Multiscale Characterization of Smart Battery Manufacturing

Advanced Functional Materials, EarlyView.
Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley   +1 more source

Accelerated Discovery of High Performance Ni3S4/Ni3Mo HER Catalysts via Bayesian Optimization

Advanced Functional Materials, EarlyView.
Integrated workflow accelerates the catalyst discovery of hydrogen evolution reaction via Bayesian optimization. An experiment‐trained surrogate model proposes synthesis conditions, guiding iterative refinement using electrochemical performance metrics.
Namuersaihan Namuersaihan, Zhiqiang Zhao, Oliver J. Conquest, Ying Shu, Haoyue Sun, Chunjing Su, Qi Cheng, Aloysius Soon, Catherine Stampfl, Jun Huang   +9 more
wiley   +1 more source

Uncertainty Ordinal Multi-Instance Learning for Breast Cancer Diagnosis. [PDF]

Healthcare (Basel), 2022
Xu X, Guo Q, Li Z, Li D.
europepmc   +1 more source