Results 111 to 120 of about 26,080 (290)
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
Teaching the Grid: Learning Distributed Computing with the M-grid Framework
A classic challenge within Computer Science is to distribute data and processes so as to take advantage of multiple computers tackling a single problem in a simultaneous and coordinated way.
Bernnett, Philip +6 more
core +1 more source
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
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 +6 more
wiley +1 more source
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Monitoring Cluster on Online Compiler with Ganglia [PDF]
Ganglia is an open source monitoring system for high performance computing (HPC) that collect both a whole cluster and every nodes status and report to the user.
yani, Nur
core
A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle +5 more
wiley +1 more source
Parallel GLRT-Based SAR Tomographic Processing on Distributed Multi-GPU Platforms
This article addresses the development of a multilevel parallel algorithm for detecting single scatterers in SAR tomography, targeted at multinode multi-GPU distributed computational architectures.
Pasquale Imperatore +5 more
doaj +1 more source
Additive Manufacturing of Alumina‐Reinforced Elastomers
Vat‐photopolymerized elastomers reinforced with platelet‐shaped alumina exhibited preferential orientation, reduced porosity, and significantly enhanced mechanical performance. A 3 wt% platelet loading increased tensile strength from 12.4 to 45.7 MPa, highlighting the critical role of filler morphology in elastomeric VPP composites.
Majid Barzegar Keyvani +6 more
wiley +1 more source

