Results 111 to 120 of about 6,454,315 (251)

Covalent Functionalization of 2D Semiconductors: A Roadmap to Advanced Electronic Devices

Advanced Functional Materials, EarlyView.
This Review presents recent advances in the covalent functionalization strategies for two‐dimensional semiconductors and their implementation in modern technologies. Layered materials are modified through diverse molecular chemistries (e.g., thiols, diazonium salts, alkyl halides, and electron‐deficient species) to tailor their surface properties ...
Ramiro Quirós‐Ovies, Bin Han, Paolo Samorì   +2 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

Forecasting seasonal influenza epidemics with physics-informed neural networks

Epidemics
Accurate epidemic forecasting is critical for informing public health decisions and timely interventions. While physics-informed neural networks have shown promise in various scientific domains, their potential application to real-time epidemic ...
Martina Rama, Gabriele Santin, Giulia Cencetti, Michele Tizzoni, Bruno Lepri   +4 more
doaj   +1 more source

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

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  

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

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

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

GeS as an Emerging OTS Material: Atomic Structure and Modeling of ON/OFF Switching

Advanced Functional Materials, EarlyView.
The structural puzzle of glassy GeS, an advanced memory‐selector material, has finally been disentangled, revealing a patchwork of mixed tetrahedral and trigonal species. Under a high electric field, over‐ and under‐coordinated Ge and S defects, together with three‐membered rings, form an interconnected network associated with localized and extended ...
Andrey Tverjanovich, Jörg C. Neuefeind, Chris J. Benmore, Daniele Fontanari, Anton Sokolov, Maxim Khomenko, Shinji Kohara, Aleksei Bytchkov, Takeshi Usuki, Maria Bokova, Mohammad Kassem, Pascal Masselin, Mariana Milochova, Eugene Bychkov   +13 more
wiley   +1 more source

Convergence of Physics-Informed Neural Networks for Fully Nonlinear PDE\u27s

The present work is focused on exploring convergence of Physics-informed Neural Networks (PINNs) when applied to a specific class of second-order fully nonlinear Partial Differential Equations (PDEs).
Arakelyan, Avetik, Barkhudaryan, Rafayel
core   +1 more source