Results 81 to 90 of about 289,279 (277)

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

open access: yesAdvanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Superionic Amorphous Li2ZrCl6 and Li2HfCl6

open access: yesAdvanced Materials, EarlyView.
Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
wiley   +1 more source

Bayesian Functional Optimization

open access: yesProceedings of the AAAI Conference on Artificial Intelligence, 2018
Bayesian optimization (BayesOpt) is a derivative-free ap-proach for sequentially optimizing stochastic black-box functions. Standard BayesOpt, which has shown many successesin machine learning applications, assumes a finite dimen-sional domain which often is a parametric space.
Vien, Ngo Anh   +2 more
openaire   +2 more sources

Bayesian Optimization Of NeuroStimulation (BOONStim)

open access: yesBrain Stimulation
AbstractBackgroundTranscranial magnetic stimulation (TMS) treatment response is influenced by individual variability in brain structure and function. Sophisticated, user-friendly approaches, incorporating both established functional magnetic resonance imaging (fMRI) and TMS simulation tools, to identify TMS targets are needed.ObjectiveThe current study
Lindsay D. Oliver   +10 more
openaire   +4 more sources

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

open access: yesAdvanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj   +8 more
wiley   +1 more source

Laser material processing optimization using bayesian optimization: a generic tool

open access: yesLight: Advanced Manufacturing
Optimizing laser processes is historically challenging, requiring extensive and costly experimentation. To solve this issue, we apply Bayesian optimization for process parameter optimization to laser cutting, welding, and polishing.
Tobias Menold   +5 more
doaj   +1 more source

Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets

open access: yes, 2017
Bayesian optimization has become a successful tool for hyperparameter optimization of machine learning algorithms, such as support vector machines or deep neural networks.
Bartels, Simon   +4 more
core  

Hydrogel‐Based Functional Materials: Classifications, Properties, and Applications

open access: yesAdvanced Materials Technologies, EarlyView.
Conductive hydrogels have emerged as promising materials for smart wearable devices due to their outstanding flexibility, multifunctionality, and biocompatibility. This review systematically summarizes recent progress in their design strategies, focusing on monomer systems and conductive components, and highlights key multifunctional properties such as
Zeyu Zhang, Zao Cheng, Patrizio Raffa
wiley   +1 more source

Optimize Gate-All-Around Devices Using Wide Neural Network-Enhanced Bayesian Optimization

open access: yesIEEE Journal of the Electron Devices Society
Device design processes based on manual design experience require numerous experiments and simulations. As transistors continue to shrink, complex physical effects, such as quantum effects intensify, making the design process increasingly costly, whether
Jiaye Shen, Zhiqiang Li, Zhenjie Yao
doaj   +1 more source

Magnetic Textiles: A Review of Materials, Fabrication, Properties, and Applications

open access: yesAdvanced Materials Technologies, EarlyView.
Magnetic textiles (M‐textiles) are emerging as a programmable materials platform that merges magnetic matter with hierarchical textile structures. This article consolidates magnetic material classes, textile architectures, and fabrication and magnetization strategies, revealing structure–property–function relationships that govern magneto‐mechanical ...
Li Ke   +3 more
wiley   +1 more source

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