Results 111 to 120 of about 6,454,505 (250)

Fiber‐Based Wearable Electronics as Adaptive Biointerfaces for Healthcare Applications

Advanced Functional Materials, EarlyView.
Fiber‐based wearable electronics have been extensively studied as adaptive healthcare biointerfaces. In this review, we classify and introduce fiber‐based systems according to biointerface design, conductive materials, transduction mechanisms, and healthcare applications, and provide a perspective on their translation toward reliable, continuous ...
Sangwoo Hong, Jinsol Kim, Yoonjae Jeong, Sejong Kang, Daeho Lee, Seung Hwan Ko   +5 more
wiley   +1 more source

Analog Classification of Human Hand Gestures Exploiting Dendritic Integration With an Organic Artificial Soma

Advanced Functional Materials, EarlyView.
An organic neuromorphic architecture for the classification of human motor behavior is presented and validated. It performs somatic integration by linearly combining the activity from three muscles. An investigation of synaptic weights is presented and discussed in relationship with the classification performance.
Ilenia Sergi, Federico Rondelli, Francesco Torricelli, Federica Velluto, Anna De Salvo, Michele Di Lauro, Luciano Fadiga, Fabio Biscarini   +7 more
wiley   +1 more source

Physics-Informed Neural Networks and Extensions [PDF]

In this paper, we review the new method Physics-Informed Neural Networks (PINNs) that has become the main pillar in scientific machine learning, we present recent practical extensions, and provide a specific example in data-driven discovery of governing ...
Karniadakis, George Em, Perdikaris, Paris, Ahmadi, Nazanin, Raissi, Maziar   +3 more
core  

Degradable, Skin‐Conformal Nanocomposite‐Based Bioelectronic Patches for High‐Fidelity Electrophysiology and Gesture‐Controlled Robotics

Advanced Functional Materials, EarlyView.
A degradable, skin‐conformal bioelectronic patch combines a starch‐dominated nanocomposite conductor with a gelatin substrate to enable sensitive strain sensing, high‐fidelity electrocardiography, electromyography, electrooculography, and machine‐learning‐assisted gesture control.
Ming Dong, Hongna Yuan, Shubo Liu, Abdulkadir Sanli, Emiliano Bilotti, Han Zhang, Pietro Cataldi, Karin Hing, Oliver Fenwick, Colin J. Humphreys, Dimitrios G. Papageorgiou   +10 more
wiley   +1 more source

Computation of waveguide eigenmodes by physics-informed neural networks

Machine Learning. Engineering
Physics-informed neural networks (PINNs) have emerged as powerful deep-learning frameworks for solving partial differential equations by directly embedding physical laws into the learning process.
Geetanjli, Kirankumar R Hiremath
doaj   +1 more source

Atomic‐Scale Visualization of Topotactic Resistive Switching in Epitaxial La0.5Sr0.5CoOx Neuromorphic Memristors

Advanced Functional Materials, EarlyView.
Forming‐free epitaxial Pt/La0.5Sr0.5CoOx (LSCO)/La0.5Sr0.5MnO3 (LSMO) memristors exhibit heterogeneous and partially reversible topotactic switching involving brownmillerite (BM)‐, Grenier (GN)‐like‐, and perovskite (PV)‐like configurations. Atomic‐resolution scanning transmission electron microscopy and in situ transmission electron microscopy resolve
Zi‐Qin Hong, Yen‐Jung Chen, Shih‐Chao Chang, Jui‐yuan Chen, Jan‐Chi Yang, Wen‐Wei Wu   +5 more
wiley   +1 more source

Physics-Informed Neural Networks for Heat Pump Load Prediction

Energies
Heat pumps are promising solutions for managing the increasing heating demand of residential houses, reducing the environmental impact when used with renewable energy.
Viorica Rozina Chifu, Tudor Cioara, Cristina Bianca Pop, Ionut Anghel, Andrei Pelle   +4 more
doaj   +1 more source

Learning strategies for physics-informed neural networks

Physics-informed neural networks (PINNs) are at the forefront of scientific machine learning, making possible the creation of machine intelligence that is cognizant of physical laws and able to accurately simulate them. This thesis studies the challenges
Wong, Jian Cheng
core   +1 more source

Role of Structural Disorder on Phonon Transport and Thermal Conductivity in Li6PS5Br

Advanced Functional Materials, EarlyView.
Solid electrolytes are fast ion and slow heat conductors. Although both transport properties are governed by lattice dynamics and atomic structure, their interplay remains poorly understood. Here, we study this interrelation in anion‐ordered and disordered Li6PS5Br.
Lukas Ketter, Ryoma Sasaki, Kyra Strotmann, Wolfgang G. Zeier, Yoshitaka Tateyama   +4 more
wiley   +1 more source

Unraveling particle dark matter with Physics-Informed Neural Networks

Physics Letters B
We parametrically solve the Boltzmann equations (BEs) governing freeze-in dark matter (DM) in alternative cosmologies with Physics-Informed Neural Networks (PINNs), a mesh-free method.
M.P. Bento, H.B. Câmara, J.F. Seabra
doaj   +1 more source