Results 91 to 100 of about 1,662 (257)
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 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
Fatigue Crack Initiation and Growth in Nanocrystalline Ni at Multiple Length‐Scales
Overview of miniaturized in situ SEM fatigue setup and resultant fatigue crack growth data for nanocrystalline Ni. The presented study focuses on the analysis of fatigue crack growth rate (FCGR) in focused ion beam‐notched microcantilevers prepared from nanocrystalline (NC) Ni as a model material.
Igor Moravcik +7 more
wiley +1 more source
Optimization of the Production of Rubber Compounds Using Mathematical Models
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle +7 more
wiley +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
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
This study aims to analyze how religious moderation values are systematically integrated into Islamic Religious Education at NU Elementary School 10 Wuluhan, Jember, Indonesia, and to examine the pedagogical strategies, challenges, and institutional ...
Ahmad Ilmi Aslam A’lawi +1 more
doaj +1 more source
During creep of a single‐crystal Ni‐based superalloy, the overall crystal orientation is observed to remain constant while the microstructure evolves. Despite the lack of macroscopic rotation, small (<1°) rotations are observed on the submicron size scale and are accommodated by counteracting rotations over the scale of several micrometers.
E. J. Payton +3 more
wiley +1 more source
We apply a foundational machine‐learning interatomic potential based on the graph atomic cluster expansion (GRACE) to simulate the commercial Ni‐based single‐crystal superalloy CMSX‐4. Hybrid Monte‐Carlo/molecular dynamics sampling resolves short‐range order in the γ phase and L12 sublattice occupancies in the γ’ phase and connects them to stacking ...
Aditya Vishwakarma +4 more
wiley +1 more source
Laser‐Induced Graphene from Waste Almond Shells
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova +9 more
wiley +1 more source

