Results 51 to 60 of about 20,650,460 (241)

High harmonic generation in two-dimensional Mott insulators

npj Quantum Materials, 2021
With a combination of numerical methods, including quantum Monte Carlo, exact diagonalization, and a simplified dynamical mean-field model, we consider the attosecond charge dynamics of electrons induced by strong-field laser pulses in two-dimensional ...
Christopher Orthodoxou, Amelle Zaïr, George H. Booth   +2 more
doaj   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Numerical determination of the width and shape of the effective string using Stochastic Normalizing Flows

Journal of High Energy Physics
Flow-based architectures have recently proved to be an efficient tool for numerical simulations of Effective String Theories regularized on the lattice that otherwise cannot be efficiently sampled by standard Monte Carlo methods.
Michele Caselle, Elia Cellini, Alessandro Nada   +2 more
doaj   +1 more source

On Estimation of Shannon’s Entropy of Maxwell Distribution Based on Progressively First-Failure Censored Data

Stats
Shannon’s entropy is a fundamental concept in information theory that quantifies the uncertainty or information in a random variable or data set.
Kapil Kumar, Indrajeet Kumar, Hon Keung Tony Ng   +2 more
doaj   +1 more source

Reliability analysis of the triple modular redundancy system under step-partially accelerated life tests using Lomax distribution

Scientific Reports, 2023
Triple modular redundancy (TMR) is a robust technique utilized in safety-critical applications to enhance fault-tolerance and reliability. This article focuses on estimating the distribution parameters of a TMR system under step-stress partially ...
Laila A. Al-Essa, Alaa H. Abdel-Hamid, Tmader Alballa, Atef F. Hashem   +3 more
doaj   +1 more source

Influence of Scan Strategies in Electron Beam Powder Bed Fusion on Solidification, Microstructure, and High‐Temperature Compressive Properties of γ′‐Strengthened Inconel 738LC

Advanced Engineering Materials, EarlyView.
Experiments and thermophysical simulations were conducted to investigate the electron beam powder bed fusion electron beam (PBF‐EB/M) process for the γ′‐strengthened nickel‐based superalloy Inconel 738LC. The results demonstrate the impact of process‐induced microstructural variations on high‐temperature mechanical behavior, providing a basis for ...
Jan Niklas Petenati, Karthik Kumar Banku, Prasanth Bondi, Ivan Zhirnov, Yangyiwei Yang, Gordon Schmidt, Jürgen Christen, Georg Hasemann, Manja Krüger, Bai‐Xiang Xu, Bilal Gökce, Silja‐Katharina Rittinghaus   +11 more
wiley   +1 more source

Review on assessment methodology for hydrothermal resources based on renewable energy attributes

Energy Geoscience
Accurate and effective assessment of hydrothermal resources is crucial in the geothermal industry, given that the global installed capacity for direct use (173 303 MW) significantly exceeds that for geothermal power (16 260 MW).
Yifan Bao, Fengnian Zhao, Li Du, Zhonghe Pang, Yanlong Kong, Fengtian Yang, Chen Yang, Jiachao Huang, Chunhong Ma, Minghui Wu, Peiyao Dong   +10 more
doaj   +1 more source

Toward Full Interoperability in Materials Science: Integrating Workflows With Knowledge Graphs

Advanced Engineering Materials, EarlyView.
The connection of conceptual workflow design, portable execution, and ontology‐based semantics leading to provenance‐rich knowledge graphs are main contributors to interoperability in materials science and a prerequisite to AI‐assisted orchestration and for interoperable Materials Acceleration Platforms.
Jan Janssen, Osamu Waseda, Bernd Bayerlein, Simon Stier, Steffen Brinckmann, Abril Azócar Guzmán, Sarath Menon, Matthias A. Popp, Jesper R. Pedersen, Ivano E. Castelli, Jörg Waitelonis, Wolfgang Wenzel, Jörg Neugebauer, Jörg Schaarschmidt, Tilmann Hickel   +14 more
wiley   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

Pricing methods for American options [PDF]

, 2003
Bibliography: leaves 89-94.This thesis is about the comparison of Pricing models for the valuation of American Options. Three classes of numerical approaches are considered.
Heimo Duvel, Duvel, Heimo
core   +1 more source