Results 141 to 150 of about 11,198,121 (288)

Sincronización de vehículos autónomos en Platoon con Physics-Informed Machine Learning

Important code available at https://github.com/mjcharria/PIML.Physics-Informed Machine Learning (PIML) consiste en un método de Machine Learning que combina la información de datos con conocimiento físico.
Charria Macias, María José
core  

Advancing deformation calculation: a physics-informed deep graph learning framework for hyperelastic materials

Advanced Modeling and Simulation in Engineering Sciences
In elastohydrodynamic lubrication (EHL) simulations, classical numerical methods like the finite difference method (FDM) and the finite element method (FEM) are commonly employed. While PINNs have proven to be a suitable alternative for fluid simulation,
Faras Brumand-Poor, Matthias Trautmann, Katharina Schmitz   +2 more
doaj   +1 more source

Photochromic Artificial Synapses for Neuromorphic Electronics: Mechanisms, Device Architectures, and Emerging Applications

Advanced Functional Materials, EarlyView.
Photochromic materials offer a promising route toward light‐programmable neuromorphic electronics through reversible, multilevel, and nonvolatile state modulation. This review establishes links between photochromic switching mechanisms, device architectures, and neuromorphic functions, spanning diverse materials and platforms.
Debdatta Panigrahi, Dong Hyun Lee, Jihyun Shin, Sten Gebel, Parham Derakhshanfar, Hocheon Yoo, Ulrike Kraft   +6 more
wiley   +1 more source

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains.
Paulson, Joel A., Nagy, Zoltan, Schwan, Roland, Di Cairano, Stefano, Cortez, Wenceslao Shaw, Carron, Andrea, Jones, Colin, Drgona, Jan, Nghiem, Truong X., Vrabie, Draguna L., Dey, Biswadip, Zeilinger, Melanie N., Chakrabarty, Ankush   +12 more
core   +1 more source

Physics-informed machine learning modelling of hydrokinetic energy harvester

Discover Energy
Hydrokinetic energy converters are environmentally friendly and hold significant potential for bridging the energy gap in remote villages where mainstream electrical grid infrastructure is unavailable.
Kombo Theophilus-Johnson, Ebughni Okoria Nangi, John Ndaa Samson   +2 more
doaj   +1 more source

High‐Throughput DNA Sequence Space Exploration for Carbon Nanotube Biosensor Design

Advanced Functional Materials, EarlyView.
For the screening of next‐generation biosensors, we developed a high‐throughput nanotube platform using covalent DNA‐anchor chemistry to recruit ssDNA motifs via hybridization. Automated liquid handling and spectroscopy enable synthesis of 180 unique sensors and testing of over 540 sensor/analyte conditions in three days.
Magdalena Theresia Kuom, Phillip Galonska, Sayantani Chakraborty, Simon van Impel, Lela Vukovic, Sebastian Kruss   +5 more
wiley   +1 more source

Advancing Human Skin Equivalents: The Crucial Role of Neurovascular Integration

Advanced Healthcare Materials, EarlyView.
This review discusses the importance of integrating vascular and peripheral nerve systems into human skin equivalents (HSEs) to better recapitulate native skin physiology. Recent advances in vascularized, innervated, and neurovascularized HSEs are highlighted, together with emerging bioengineering strategies, current challenges, and future ...
Hao Wu, Lorenzo Moroni, Nicolas Lebonvallet, Vincent Flacher, Paul Wieringa   +4 more
wiley   +1 more source

Physics-Informed Machine Learning in Subsurface Multiphysics Flow Modeling: Integrating Physical Constraints for Accelerated Simulation

Buildings
Subsurface thermo-hydro-mechanical (THM) coupled processes are fundamental to geomechanics, yet conventional mesh-based methods face high computational costs and limited efficiency in strongly nonlinear simulations and inverse problems.
Linchao Wang, Fei Xiong, Faning Dang, Lin Zhu, Yi Xue   +4 more
doaj   +1 more source

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source