Results 121 to 130 of about 18,090,481 (292)

NeuroVisio SyncPatch: A Skin‐Conformal Multimodal EMG–Motion Sensing Platform for Quantitative Neuromuscular Rehabilitation and Performance Monitoring

Advanced Healthcare Materials, EarlyView.
NeuroVisio SyncPatch integrates skin‐conformal electromyography (EMG) electrodes with camera‐tracked markers to jointly assess muscle activity and three‐dimensional knee kinematics during rehabilitation. Parallel feedback pathways provide real‐time kinematic guidance during movement and post‐trial neuromuscular feedback.
Bohyung Choi, Yoo‐Jin Jun, Heewon Choee, Kun‐Do Lee, Heesoo Kim, Yu Seok Hwang, Choong Yeon Kim, Seongok Chae, Juhyun Lee, Minkyu Je, Jae‐Woong Jeong, Hyung‐Soon Park   +11 more
wiley   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Set-to-set iterative learning control

Automatica
This work introduces a novel set-to-set (STS) iterative learning control (ILC) framework which generalizes the ideas of point-to-point ILC (PTP ILC) and region-to-region (RTR ILC) techniques. The existing ILC frameworks are extended by tracking both sets and points at desired times within an iteration.
Reid D. Smith, Andrew G. Alleyne
openaire   +3 more sources

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

Advanced 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

Learning of Iterative Learning Control for Flexible Manufacturing of Batch Processes. [PDF]

ACS Omega, 2022
Xu L, Zhong W, Lu J, Gao F, Qian F, Cao Z.   +5 more
europepmc   +1 more source

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

Advanced 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, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

A Hybrid Controller for a Soft Pneumatic Manipulator Based on Model Predictive Control and Iterative Learning Control. [PDF]

Sensors (Basel), 2023
Dai Y, Deng Z, Wang X, Yuan H.
europepmc   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Physiologic Data-Driven Iterative Learning Control for Left Ventricular Assist Devices. [PDF]

Front Cardiovasc Med, 2022
Magkoutas K, Arm P, Meboldt M, Schmid Daners M.   +3 more
europepmc   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source