Results 101 to 110 of about 279,520 (289)

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

Machine learning in the identification of native species from seed image analysis

Journal of Seed Science
: The identification of seeds from native species is a complex assessment due to the high Brazilian biodiversity and varied characteristics between species.
Francival Cardoso Felix, Dagma Kratz, Richardson Ribeiro, Antônio Carlos Nogueira   +3 more
doaj   +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

From Wafers to Electrodes: Transferring Automatic Optical Inspection (AOI) for Multiscale Characterization of Smart Battery Manufacturing

Advanced Functional Materials, EarlyView.
Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley   +1 more source

Frontier Advances of Emerging High‐Entropy Anodes in Alkali Metal‐Ion Batteries

Advanced Functional Materials, EarlyView.
Recent advances in microscopic morphology control of high‐entropy anode materials for alkali metal‐ion batteries. Abstract With the growing demand for sustainable energy, portable energy storage systems have become increasingly critical. Among them, the development of rechargeable batteries is primarily driven by breakthroughs in electrode materials ...
Liang Du, Kaidi Zhang, Liang Wang, Di Zhao, Mengqing Hu, Mingli Li, Ming Zhou, Zhenzhen Wu, Mengyang Dong, Bo Fu, Porun Liu, Yun Wang, Hongxia Wang, Yuantong Gu, Lei Zhang   +14 more
wiley   +1 more source

On robustness properties of convex risk minimization methods for pattern recognition [PDF]

The paper brings together methods from two disciplines: machine learning theory and robust statistics. Robustness properties of machine learning methods based on convex risk minimization are investigated for the problem of pattern recognition ...
Christmann, Andreas, Steinwart, Ingo
core  

Additive Manufacturing of NiTi Shape Memory Alloys for Elastocaloric Applications: A Review

Advanced Functional Materials, EarlyView.
Additive manufacturing enables complex NiTi architectures that overcome key limitations in elastocaloric refrigeration, including poor heat transfer and high mechanical work input. This review surveys recent advances in LPBF‐ and DED‐fabricated NiTi shape memory alloys for elastocaloric applications, highlighting process–structure–performance ...
Ignatius Andre Setiawan, Mohammad Mehrali, Jaka Tušek, Shiva Mohajerani, Xiebin Wang, Dermot Brabazon, Mohammad Elahinia, Mehrshad Mehrpouya   +7 more
wiley   +1 more source

Handwritten Amharic Character Recognition Through Transfer Learning: Integrating CNN Models and Machine Learning Classifiers

IEEE Access
Handwritten Amharic character recognition presents significant challenges due to the script’s syllabic nature and variations in handwriting styles. This study investigates a hybrid approach that integrates convolutional neural networks (CNNs) with
Natenaile Asmamaw Shiferaw, Zefree Lazarus Mayaluri, Prabodh Kumar Sahoo, Ganapati Panda, Prince Jain, Adyasha Rath, Md. Shabiul Islam, Mohammad Tariqul Islam   +7 more
doaj   +1 more source

Molecularly Engineered Highly Stable Memristors with Ultra‐Low Operational Voltage: Integrating Synthetic DNA with Quasi‐2D Perovskites

Advanced Functional Materials, EarlyView.
Molecularly engineered memristors integrating Ag nanoparticle–embedded synthetic DNA with quasi‐2D halide perovskites enable ultra‐low‐operational voltage, forming‐free resistive switching, and record‐low power density. This synergistic integration of customized DNA and 2D OHP in bio‐hybrid architecture enhances charge transport, reduces variability ...
Kavya S. Keremane, Abhinav Gorthy, Luyao Zheng, Chiranth C Ravi, Haodong Wu, Jiamao Zheng, Neela H. Yennawar, Shashank Priya, Rashmi Jha, Bed Poudel   +9 more
wiley   +1 more source

The Cuttlebone Blueprint for Multifunctional Metamaterials: Design Taxonomy, Functional Decoupling, and Future Horizons

Advanced Functional Materials, EarlyView.
Cuttlebone‐inspired metamaterials exploit a septum‐wall architecture to achieve excellent mechanical and functional properties. This review classifies existing designs into direct biomimetic, honeycomb‐type, and strut‐type architectures, summarizes governing design principles, and presents a decoupled design framework for interpreting multiphysical ...
Xinwei Li, Zhendong Li
wiley   +1 more source