Results 111 to 120 of about 154,891 (246)

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

The Role of Active Learning in Modern Machine Learning

Even though Active Learning (AL) is widely studied, it is rarely applied in contexts outside its own scientific literature. We posit that the reason for this is AL's high computational cost coupled with the comparatively small lifts it is typically able to generate in scenarios with few labeled points.
Werner, Thorben, Schmidt-Thieme, Lars, Yalavarthi, Vijaya Krishna   +2 more
openaire   +2 more sources

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

Conductance‐Dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing

Advanced Functional Materials, EarlyView.
A nanoscale SrTiO3 memristor is shown to exhibit dynamic synaptic behavior through the interaction of local electrical and global optical signals. Its photoresponse depends quantitatively on the conductance state, which evolves and decays over tunable timescales, enabling ultralow‐power, biorealistic learning mechanisms for advanced in‐memory and ...
Christoph Weilenmann, Hanglin He, Marko Mladenović, Till Zellweger, Kevin Portner, Klemens Bauer, Guillaume Bellec, Mathieu Luisier, Alexandros Emboras   +8 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

Liquid Phase Transmission Electron Microscopy: A Window into the Early Stages of Complex Material Formation

Advanced Functional Materials, EarlyView.
Liquid‐phase transmission electron microscopy enables direct observation of nucleation and growth processes in solution. This review is dedicated to the remembrance of Helmut Cölfen and highlights recent studies on complex materials—oxides, biominerals, organic–inorganic crystals—which were central to his research activity. It summarizes key milestones,
Charles Sidhoum, Vinavadini Ramnarain, Nathaly Ortiz Peña, Dris Ihiawakrim, Clément Sanchez, Ovidiu Ersen   +5 more
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

HAML-IRL: Overcoming the Imbalanced Record Linkage Problem Using Hybrid Active Machine Learning

Jordanian Journal of Computers and Information Technology
Traditional active machine learning (AML) methods employed in Record Linkage (RL) or Entity Resolution (ER) tasks often struggle with model stability, slow convergence, and handling imbalanced data.
Mourad Jabrane, Mouad JBEL, Imad HAFIDI, Yassir ROCHD   +3 more
doaj   +1 more source