Results 141 to 150 of about 122,744 (306)

Infrared Machine Vision System Based on Te NWs‐Au NPs Plasmonic Optoelectronic Memristor for Motion Detection

Advanced Science, EarlyView.
A plasmonic optoelectronic memristor based on Te nanowires‐Au nanoparticles/ι‐carrageenan enables IR‐programmed and visiblelight‐erased non‐volatile conductance. The all‐photonic write/erase scheme supports in‐sensor logic and real‐time motion detection in darkness.
Jingyao Bian, Yongxing Zhu, Ye Tao, Zhongqiang Wang, Xiaoning Zhao, Ya Lin, Haiyang Xu, Yichun Liu   +7 more
wiley   +1 more source

Model Updating Based on Frequency Response Functions Using A General Finite Element Code [PDF]

, 2003
peer reviewedModel updating techniques using frequency response function (FRF) data are studied in this paper. The numerical techniques are discussed for implementation with a large commercial finite element (FE ) code.
Golinval, Jean-Claude, Yan, Ai-Min
core  

Nanozyme Microrobots: Programmable Spatiotemporal Catalysis for Targeted Therapy and Diagnostics

Advanced Science, EarlyView.
This review presents nanozyme microrobots as emerging catalytic systems that integrate mobility, external actuation, and adaptive reactivity to achieve precise biochemical functions. By examining mobility‐regulated catalysis, spatial targeting, integrated designs, and translational demonstrations, the article highlights how nanozyme robotics enables ...
Hong Huy Tran, Nil Kanatha Pandey, David P. Cormode, Daeyeon Lee, Edward Steager, Hyun Koo   +5 more
wiley   +1 more source

Research on Multi-Alternatives Problem of Finite Element Model Updating Based on IAFSA and Kriging Model. [PDF]

Sensors (Basel), 2020
Kang J, Zhang X, Cao H, Qin S.
europepmc   +1 more source

Study of Resistive Switching Dynamics and Memory States Equilibria in Analog Filamentary Conductive‐Metal‐Oxide/HfOx ReRAM via Compact Modeling

Advanced Electronic Materials, EarlyView.
A physics‐based compact model for Conductive‐Metal‐Oxide/HfOx ReRAM, accounting for ion dynamics, electronic conduction, and thermal effects, is presented. Accurate and versatile simulations of analog non‐volatile conductance modulation and memory state stabilization enable reliable circuit‐level studies, advancing the optimization of neuromorphic and ...
Matteo Galetta, Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Stephan Menzel, Antonio La Porta, Tommaso Stecconi, Folkert Horst, Bert Jan Offrein, Valeria Bragaglia   +9 more
wiley   +1 more source

FE Model Updating of Continuous Beam Bridge Based on Response Surface Method

Buildings
In this paper, A high-order response surface method is proposed for finite element model updating of continuous beam bridges. Firstly, based on visual inspection and environmental vibration testing, the peak picking (PP) method and random subspace ...
Fang Dong, Zhongqi Shi, Rumian Zhong, Nan Jin   +3 more
doaj   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Rethinking Power Solutions for Healthcare Wearables: From Point‐of‐Care and Episodic use to Continuous Monitoring and Therapeutic Platforms

Advanced Energy and Sustainability Research, EarlyView.
This Perspective examines practical power solutions for wearable healthcare systems, highlighting the limits of standard batteries. It categorizes wearables into four domains—point‐of‐care diagnostics, episodic monitoring, continuous long‐term monitoring, and therapeutic platforms—and analyzes their power needs.
Seokheun Choi
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Accelerating Surface Composition Characterization of Thin‐Film Materials Libraries Using Multi‐Output Gaussian Process Regression

Advanced Intelligent Discovery, EarlyView.
To integrate surface analysis into materials discovery workflows, Gaussian process regression is used to accurately predict surface compositions from rapidly acquired volume composition data (obtained by energy‐dispersive X‐ray spectroscopy), drastically reducing the number of required surface measurements on thin‐film materials libraries.
Felix Thelen, Florian Lourens, Alfred Ludwig   +2 more
wiley   +1 more source