Results 131 to 140 of about 1,786,533 (325)

A Self-Taught Artificial Agent for Multi-Physics Computational Model\n Personalization [PDF]

, 2016
Dominik Neumann, Tommaso Mansi, Lucian Itu, Bogdan Georgescu, Elham Kayvanpour, Farbod Sedaghat‐Hamedani, Ali Amr, Jan Haas, Hugo A. Katus, Benjamin Meder, Stefan Steidl, Joachim Hornegger, Dorin Comaniciu   +12 more
openalex   +1 more source

Computational Essays: An Avenue for Scientific Creativity in Physics [PDF]

, 2020
Tor Ole B. Odden, Marcos D. Caballero
openalex   +1 more source

Composition and Resulting Band Alignment at the TiO2/InP Heterointerface: A Fundamental Study Combining Photoemission Spectroscopy and Theory

Advanced Functional Materials, EarlyView.
The chemical composition and band alignment are systematically investigated at the TiO2/InP heterointerface. Thin TiO2 films are deposited by ALD on atomically ordered, P‐terminated p‐InP(100). By combining UPS, XPS, and ab initio molecular dynamics, the atomistic structure and electronic alignment are revealed.
Mohammad Amin Zare Pour, Muhammad Nawaz Qaisrani, Christian Höhn, Johannes Laurenz Wolf, Negin Mogharehabed, Jennifer Velazquez Rojas, Wolfram Jaegermann, Erich Runge, Roel van de Krol, Thomas Hannappel, Christian Dreßler, Agnieszka Paszuk   +11 more
wiley   +1 more source

Multi-physics computation and deformation testing of a shell-type 1.5-GHz cavity

, 2019
Ming-Chyuan Lin, Meng‐Kao Yeh, Ming-Fu Lu, C. H. Lo   +3 more
openalex   +1 more source

Information theoretic and neural computational tools for meta-analysis of cumulative databases in the age of Big Physics experiments [PDF]

, 2022
A. Murari, M. Lungaroni, L. Spolladore, E. Peluso, Riccardo Rossi, M. Gelfusa   +5 more
openalex   +1 more source

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

Advanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic Junior, Nicholas Sandor, Alexander Hart, Yuki Haruta, Magdalena Bazalova‐Carter, Marcos J. L. Santos, Makhsud I. Saidaminov   +8 more
wiley   +1 more source

Advanced Numerical Modeling of Powder Bed Fusion: From Physics-Based Simulations to AI-Augmented Digital Twins. [PDF]

Materials (Basel)
Łach Ł, Svyetlichnyy D.
europepmc   +1 more source

Bimetallic Nanoparticles as Cocatalysts for Photocatalytic Hydrogen Production

Advanced Functional Materials, EarlyView.
Recent developments have introduced bimetallic nanoparticles as effective cocatalysts for photocatalytic systems. This review explores the rapidly expanding research on bimetallic cocatalysts for photocatalytic production of hydrogen, emphasizing the creation of carrier‐selective contacts, localized surface plasmon resonance effects, methodologies for ...
Yufen Chen, Asier Agrelo‐Lestón, Ignasi Burgués‐Ceballos, Jordi Llorca, Lluís Soler   +4 more
wiley   +1 more source

OrientationNN: a physics-informed lightweight neural network for real-time joint kinematics estimation from IMU data. [PDF]

Front Bioeng Biotechnol
Bian Q, Wang H, Alsayed K, Ding Z.
europepmc   +1 more source

Computational electron–phonon superconductivity: from theoretical physics to material science

Shiya Chen, Feng Zheng, Zhen Zhang, Shunqing Wu, Kai‐Ming Ho, Vladimir Antropov, Yang Sun   +6 more
openalex   +2 more sources