Results 121 to 130 of about 116,582 (263)

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

open access: yesAdvanced Engineering Materials, EarlyView.
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

The PRIMA Thesaurus for Materials Science and Engineering

open access: yesAdvanced Engineering Materials, EarlyView.
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa   +8 more
wiley   +1 more source

High‐Temperature Nanoindentation of Metals: Assessing Thermal Drift, Frame Compliance, and Chemical Composition Effects on the Reported Mechanical Properties

open access: yesAdvanced Engineering Materials, EarlyView.
Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova   +2 more
wiley   +1 more source

A deep-learning-based early warning system for abnormal eye conditions in chickens. [PDF]

open access: yesPoult Sci
Chen YC   +6 more
europepmc   +1 more source

Additive Manufacturing of Alumina‐Reinforced Elastomers

open access: yesAdvanced Engineering Materials, EarlyView.
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

Foundational Machine‐Learning Interatomic Potential for Simulating Chemically Complex Ni‐Based Superalloys

open access: yesAdvanced Engineering Materials, EarlyView.
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

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