Results 61 to 70 of about 2,027,139 (291)

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

QCD heat kernel in covariant gauge [PDF]

Journal of Physics A: Mathematical and General, 1996
6 pages + title page, standart ...
Guendelman, E. I., Leonidov, A. V., Nechitailo, V. A., Owen, D. A.   +3 more
openaire   +3 more sources

Rapidly Solidified High‐Strength Invar 36 Prepared by Planar‐Flow Melt Spinning

Advanced Engineering Materials, EarlyView.
The Invar 36 alloy was rapidly solidified using the planar‐flow melt‐spinning technique. Ribbon samples with thicknesses ranging from 20 to 160 mm were produced. As the grain size of the ribbon decreased to sub‐micron levels, the hardness increased by more than 2 times.
Bekir Akgül, Mehmet Kul
wiley   +1 more source

Intrinsic Functional Partially Linear Poisson Regression Model for Count Data

Axioms
Poisson regression is a statistical method specifically designed for analyzing count data. Considering the case where the functional and vector-valued covariates exhibit a linear relationship with the log-transformed Poisson mean, while the covariates in
Jiaqi Xu, Yu Lu, Yuanshen Su, Tao Liu, Yunfei Qi, Wu Xie   +5 more
doaj   +1 more source

An estimate on the hessian of the heat kernel [PDF]

Journées équations aux dérivées partielles, 1995
Summary: Let \(M\) be a compact, connected Riemannian manifold, and let \(p_t(x,y)\) denote the fundamental solution to Cauchy initial value problem for the heat equation \({\partial u\over\partial t}={1\over 2} \Delta u\), where \(\Delta\) is the Levi-Civita Laplacian.
openaire   +2 more sources

High‐Entropy Alloy Interlayers Toward Advanced Joining for High‐Performance Structural Applications: Current Progress and Emerging Challenges

Advanced Engineering Materials, EarlyView.
HEA interlayers offer a versatile route for joining high‐performance structural materials. Their compositional and structural design regulates interfacial reactions, suppresses brittle IMCs, and improves metallurgical bonding. Sandwich interlayers further integrate defect healing with precipitation strengthening, enabling improved strength–ductility ...
Lin Yuan, Jiafen Song, Jinglong Li, Jiangtao Xiong, Tao Yang   +4 more
wiley   +1 more source

Asymptotics of a modified holomorphic analytic torsion

Complex Manifolds
We prove a formula for the first few terms of the asymptotic expansion of the holomorphic analytic torsion of the Dirac operator modified by the Clifford action of a real and closed three-form.
Larraín-Hubach Andrés
doaj   +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

Heat Kernel Estimate Along Ricci-Harmonic Flow

Mathematics
In this paper, we study the Ricci-harmonic flow under the assumption that the scalar curvature is bounded. First, we establish a time-derivative bound for solutions to the heat equation along the flow.
Chen Wang, Guoqiang Wu
doaj   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source