Results 151 to 160 of about 29,946 (302)

Physics-Informed Neural Networks for Structural Health Monitoring of Cross-Ply Laminates

embargoed_20270703La tesi propone l'utilizzo di reti neurali physics-informed per predire in funzione della variazione della resistenza elettrica, l'elasticità di un componente realizzato in materiale laminato polimerico-fibroso cross-ply.
AMBROSI, FILIPPO
core  

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 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

Adaptive Physics-informed Neural Networks: A Survey

CoRR
https://openreview.net/forum?id ...
Edgar Torres, Jonathan Schiefer, Mathias Niepert   +2 more
openaire   +2 more sources

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

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

Intelligent Acousto‐Electrical Metamaterials (IAM) for Sound Source Detection

Advanced Materials, EarlyView.
Our proposed metamaterial concept enables sound source detection using a single material, in contrast to conventional arrays that require dozens or even hundreds of transducers. We show that the coupled acoustic–vibrational–electrical responses in piezoelectric metamaterials give rise to topology‐governed charge transport, producing distinct voltage ...
Victor Couëdel, Haotian Lu, Jiayan Zhang, Desheng Yao, Ananya Bhardwaj, Ramiro Contreras, Karim Sabra, Xiaoyu (Rayne) Zheng   +7 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

Physics-informed Neural Networks for Biopharma Applications

, 2021
Physics-Informed Neural Networks (PINNs) are hybrid models that incorporate differential equations into the training of neural networks, with the aim of bringing the best of both worlds.
Cedergren, Linnéa
core  

Mechanically Programmable DNA Hydrogel Microparticles for 3D Cellular Systems

Advanced Materials, EarlyView.
DNA hydrogel microparticles are designed to exhibit controllable viscoelasticity and stiffness across three orders of magnitude from 30Pa$30 \,\mathrm{Pa}$ to 6.5kPa$6.5 \,\mathrm{kPa}$. They are uptaken into fibroblast spheroids where they are actively remodeled by cellular forces depending on their mechanical properties.
Tobias Walther, Eleni Dalaka, Gotthold Fläschner, Manuel Gómez‐González, Ilia Platzman, Sadaf Pashapour, Michelle Emmert, Pere Roca‐Cusachs, Xavier Trepat, Kerstin Göpfrich   +9 more
wiley   +1 more source