Results 241 to 250 of about 12,455,841 (338)

A comprehensive benchmark of active learning strategies with AutoML for small-sample regression in materials science. [PDF]

Sci Rep
Bi J, Xu Y, Conrad F, Wiemer H, Ihlenfeldt S.   +4 more
europepmc   +1 more source

Bias Free Multiobjective Active Learning for Materials Design and Discovery

, 2020
Kevin Maik Jablonka, Giriprasad Melpatti Jothiappan, Shefang Wang, Berend Smit, Brian Yoo   +4 more
openalex   +1 more source

Solvent‐Free Bonding Mechanisms and Microstructure Engineering in Dry Electrode Technology for Lithium‐Ion Batteries

Advanced Functional Materials, EarlyView.
Dry electrode technology revolutionizes battery manufacturing by eliminating toxic solvents and energy‐intensive drying. This work details two promising techniques: dry spray deposition and polymer fibrillation. How their unique solvent‐free bonding mechanisms create uniform microstructures for thicker, denser electrodes, boosting energy density and ...
Yuhao Liang, Hao Long, Zimo Huang, Ting He, Xueming Chen, Meng Li, Hao Chen, Shanqing Zhang   +7 more
wiley   +1 more source

Innovative Approaches to Dental Education: Active Learning for Erosive Tooth Wear Diagnosis in Online and Face-to-Face Settings. [PDF]

Cureus
Ionta F, Martins D, Bueno G, Tosta W, Ferreira A, Ferreira E, Boteon AP, Braga M, Rios D.   +8 more
europepmc   +1 more source

Molecular Cross‐Linking of MXenes: Tunable Interfaces and Chemiresistive Sensing

Advanced Functional Materials, EarlyView.
In this study, Ti3C2Tx MXenes are initially functionalized using oleylamine ligands to form stable dispersions in an organic solvent. Subsequently ligand exchange with α,ω‐diaminoalkanes enables cross‐linking, along with precise tuning of interfaces. This structural control translates into tunable charge transport and responsive VOC sensing, showing ...
Yudhajit Bhattacharjee, Lukas Mielke, Mahmoud Al‐Hussein, Shivam Singh, Karen Schaefer, Borja Rodriguez‐Barea, Qiong Li, Anik Kumar Ghosh, Artur Erbe, Carmen Herrmann, Yana Vaynzof, Andreas Fery, Hendrik Schlicke   +12 more
wiley   +1 more source

Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction. [PDF]

NPJ Comput Mater
Bhatia N, Rinke P, Krejčí O.
europepmc   +1 more source

Naturally Derived Donor‐π‐Acceptor Compounds for Efficient Long‐Wavelength LEDs/Sunlight‐Induced Polymerization and High‐Precision Multiple 3D Printing

Advanced Functional Materials, EarlyView.
Two novel donor–π–acceptor photoinitiators enable ultrafast long‐wavelength photopolymerization under blue/green LEDs and sunlight. Effective at low intensities and concentrations, they overcome slow kinetics and permit rapid 3D printing via DLW, DLP, and LCD methods.
Ji Feng, Tong Gao, Fabrice Morlet‐Savary, Michael Schmitt, Céline Dietlin, Jing Zhang, Pu Xiao, Frédéric Dumur, Jean‐Patrick Joly, Jacques Lalevée   +9 more
wiley   +1 more source

Active Learning [PDF]

Al Ameen Journal of Medical Sciences, 2010
M. Nasir Afzal
doaj  

Automated Alzheimer's disease detection using active learning model with reinforcement learning and scope loss function. [PDF]

Npj Ment Health Res
He Z, Govindarajan V, Yang J, Abdel-Salam M, Shaikh ZA, Por LY, Alizadehsani R, Tan RS, Rajendra Acharya U.   +8 more
europepmc   +1 more source

‘Oxygen Bound to Magnesium’ as High Voltage Redox Center Causes Sloping of the Potential Profile in Mg‐Doped Layered Oxides for Na‐Ion Batteries

Advanced Functional Materials, EarlyView.
Na‐ion batteries ‐ Impact of doping on the oxygen redox: The sloping potential of NaMg0.1Ni0.4Mn0.5O2 above 4.0 V is caused by a new redox center (arising from the ‘O bound to Mg’), having a higher potential but being more irreversible compared to the ‘O bound to Ni’.
Yongchun Li, Konstantin Köster, Katherine A. Mazzio, Yanan Sun, Annica I. Freytag, Deniz Wong, Christian Schulz, Götz Schuck, Volodymyr Baran, Alba San Jose Mendez, Marcin Zając, Payam Kaghazchi, Philipp Adelhelm   +12 more
wiley   +1 more source