Results 101 to 110 of about 26,748 (250)

Triboelectric Tactile Transducers for Neuromorphic Sensing and Synaptic Emulation: Materials, Architectures, and Interfaces

Advanced Energy and Sustainability Research, EarlyView.
Triboelectric nanogenerators are vital for sustainable energy in future technologies such as wearables, implants, AI, ML, sensors and medical systems. This review highlights improved TENG neuromorphic devices with higher energy output, better stability, reduced power demands, scalable designs and lower costs.
Ruthran Rameshkumar, Arunkumar Chandrasekhar, Poongundran Selvaprabhu   +2 more
wiley   +1 more source

A chaotic parallel hash engine with dynamic stochastic diffusion for blockchain and cloud security. [PDF]

Sci Rep
Wang Q, Yang Y, Zhao M, Wan H, Li B, Yan X.   +5 more
europepmc   +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

Multi-texture synthesis through signal responsive neural cellular automata. [PDF]

Sci Rep
Catrina MM, Plajer IC, Băicoianu A.
europepmc   +1 more source

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Supervised and Unsupervised Learning with Numerical Computation for the Wolfram Cellular Automata. [PDF]

Entropy (Basel)
Tuo K, Deng S, Yang Y, Wang Y, Wang Q, Li W, Zhang W.   +6 more
europepmc   +1 more source

Information Dense and Industry Scalable Accelerated Formation

Advanced Intelligent Discovery, EarlyView.
Pulsed formation can reduce lithium‐ion battery formation time by over 50% while maintaining or enhancing performance. Validated on 25 Ah prismatic cells, this industry‐scalable method yields thinner, more homogeneous solid electrolyte interphases (SEIs).
Leon Merker, Markus Blessing, Bojing Zhang, Helge Sören Stein   +3 more
wiley   +1 more source

A new digital watermarking model using honey encryption and reversible cellular automata. [PDF]

Sci Rep
Xiong J, Zhou Z, Dubrovskiy VV, Lee S.
europepmc   +1 more source

Magnetic QCA Design: Modeling, Simulations and Circuits [PDF]

, 2011
Graziano, Mariagrazia, Vacca, Marco, Zamboni, Maurizio   +2 more
core  

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