Results 151 to 160 of about 1,629,210 (315)

Emergent Spin‐Glass Behavior in an Iron(II)‐Based Metal–Organic Framework Glass

Advanced Functional Materials, EarlyView.
A one‐pot, solvent‐free synthesis yields an Fe2+‐based metal‐organic framework (MOF) glass featuring a continuous random network structure. The material exhibits spin‐glass freezing at 14 K, driven by topological‐disorder and short‐range magnetic frustration, showcasing the potential of MOF glasses as a plattform for cooperative magnetic phenomena in ...
Chinmoy Das, Soma Salamon, Joachim Landers, Jan‐Benedikt Weiß, Wen‐Long Xue, Pascal Kolodzeiski, Roman Pallach, Heiko Wende, Sebastian Henke   +8 more
wiley   +1 more source

Thickness‐Dependent Skyrmion Evolution in Fe3GeTe2 During Magnetization Reversal

Advanced Functional Materials, EarlyView.
Thickness‐ and field‐dependent magnetic domain behavior in 2D van der Waals Fe3GeTe2 is studied using Lorentz TEM and micromagnetic simulations. A patch‐like domain phase evolves from skyrmions during magnetization reversal, and step edges between thickness regions act as pinning sites.
Jennifer Garland, John Fullerton, PeiYu Cai, Rabindra Basnet, Santosh Karki Chhetri, Jin Hu, Elton J. G. Santos, Yue Li, Charudatta Phatak, Amanda Petford‐Long   +9 more
wiley   +1 more source

Towards Deep Q-Network Based Resource Allocation in Industrial Internet of Things. [PDF]

IEEE Internet Things J, 2022
Liang F, Yu W, Liu X, Griffith D, Golmie N.   +4 more
europepmc   +1 more source

Solving the spike feature information vanishing problem in spiking deep Q network with potential based normalization. [PDF]

Front Neurosci, 2022
Sun Y, Zeng Y, Li Y.
europepmc   +1 more source

Enhancing Molecular Docking with Deep Q-Networks

, 2022
El descubrimiento de fármacos es un proceso largo y costoso que suele durar entre 10 y 15 años, desde la evaluación inicial de candidatos farmacológicos hasta la aprobación final por parte de los organismos reguladores correspondientes. Por este motivo, simulaciones moleculares por computador, conocidas como Virtual Screening (VS) (o Cribado Virtual ...
openaire   +1 more source

Microgrid energy management using deep Q-network reinforcement learning

Alexandria Engineering Journal, 2022
Mohammed H. Alabdullah, M. A. Abido
semanticscholar   +1 more source

A Smart Magnetically Actuated Flip‐Disc Programmable Metasurface with Ultralow Power Consumption for Real‐Time Channel Control

Advanced Functional Materials, EarlyView.
The study proposes a 1‐bit programmable metasurface based on flip‐disc display, named flip‐disc metasurface (FD‐MTS). This new design enables ultralow energy consumption while maintaining coding patterns. It also exhibits high scalability and multifunctional flexibility.
Jiang Han Bao, Che Liu, Jia Cheng Li, Zhen Hao Fu, Yi Su Huang, Si Qi Huang, Lei Zhang, Jian Wei You, Tie Jun Cui   +8 more
wiley   +1 more source

Optimal Energy-Storage Configuration for Microgrids Based on SOH Estimation and Deep Q-Network. [PDF]

Entropy (Basel), 2022
Chen S, Li J, Jiang C, Xiao W.
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

DAQN: Deep Auto-encoder and Q-Network

, 2018
The deep reinforcement learning method usually requires a large number of training images and executing actions to obtain sufficient results. When it is extended a real-task in the real environment with an actual robot, the method will be required more training images due to complexities or noises of the input images, and executing a lot of actions on ...
openaire   +2 more sources