Results 111 to 120 of about 7,015,125 (284)
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 +7 more
wiley +1 more source
Performance evaluation of the high resolution small animal PET scanner
[[abstract]]Molecular imaging is an important technology to clarify biological and medical uncertainties in the 21th century. This is best realized via in vivo imaging of biological processes in small animals.
Mok, Seng-Peng;Wang, Chao-Hsing;Chen, Jyh-Cheng;Liu, Ren-Shyan
core
Effects of Mg on Microstructure and Solidification of a Hypereutectic Zn–8 wt.%Al Alloy
An appreciable set of results involving thermal data, microstructure, chemical composition, and microstructural growth laws is reported for ZnAlMg alloys. Such results demonstrate that ZnAlMg alloys have high potential for applications in automotive self‐lubricating components, batteries, and electrical systems.
Raí B. de Sousa +6 more
wiley +1 more source
FastNano Liquid: An Automated Platform for Small‐Angle X‐ray Scattering‐Based Materials Discovery
We present FastNano Liquid, an automated small‐ and wide‐angle X‐ray scattering platform for the combined synthesis and characterization of (nano)materials. The platform is coupled to varied reactor workflows for both in situ studies of reaction kinetics and ex situ screening of synthesis conditions to support machine learning‐guided exploration ...
Pierre‐Baptiste Flandrin +16 more
wiley +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
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 +14 more
wiley +1 more source
Additive manufacturing introduces pronounced microstructural and crystallographic anisotropy in Ni‐based superalloys, resulting in orientation‐dependent creep deformation and damage. This review identifies the key microstructural origins of creep anisotropy, examines their influence on dominant deformation mechanisms, and highlights processing ...
Chandan Kumar +3 more
wiley +1 more source
Conventional imaging techniques such as SPECT and PET cannot directly identify the positions of individual decaying nuclei. As such, they heavily rely on statistical backprojection for image point reconstruction.
Leonid Leopold Nkuba +1 more
doaj +1 more source
Microstructural evolution of premium rail steel during flash butt welding (FBW), comparing physically simulated heat‐affected zones with actual weld regions. Thermal cycles induce phase transformations and microstructural heterogeneity that influence weld quality and mechanical performance. These findings provide insights into optimizing FBW parameters
Emmanoelle Cintra da Cunha Araújo +15 more
wiley +1 more source
Electrospun Wood‐Derived Biopolymers as Electrodes in Electrochemical Energy Storage Technologies
Electrospinning transforms wood‐derived cellulose and lignin into architecturally defined, binder‐free carbon electrodes with tuneable porosity and functionality. This review shows how fibre design enables decoupled charge and mass transport, enhancing performance across battery systems, while identifying key challenges in spinnability, scalability ...
Michael W. Thielke +3 more
wiley +1 more source
The spline reconstruction technique (SRT) is a fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform.
Alexandros Vrachliotis +4 more
doaj +1 more source

