Results 131 to 140 of about 1,714,603 (291)
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
A Regularized Regression Thermal Error Modeling Method for CNC Machine Tools under Different Ambient Temperatures and Spindle Speeds. [PDF]
Sensors (Basel), 2023 Wei X, Ye H, Zhou J, Pan S, Qian M.
europepmc +1 more source
Advanced Engineering Materials, EarlyView.The corrosion performance of AlSi7Mg and AlSi10Mg alloys produced through selective laser melting (SLM) was examined under compressive stress in a chloride environment. Electrochemical analyses, including open‐circuit potential (OCP), potentiodynamic polarization (CPP), and electrochemical impedance spectroscopy (EIS), were complemented by scanning ...
Femi John Akinfolarin +2 more
wiley +1 more source
An Energy Data-Driven Approach for Operating Status Recognition of Machine Tools Based on Deep Learning. [PDF]
Sensors (Basel), 2022 Yan W, Lu C, Liu Y, Zhang X, Zhang H.
europepmc +1 more source
, 2019 Machine learning research depends on objectively interpretable, comparable, and reproducible algorithm benchmarks. Therefore, we advocate the use of curated, comprehensive suites of machine learning tasks to standardize the setup, execution, and ...
Bischl, Bernd +7 more
core
Advanced Engineering Materials, EarlyView.This study demonstrates an efficient recycling route for out‐of‐spec AlSi10Mg atomized powders through compaction and arc remelting followed by suction casting. By correlating compaction load, cooling rate, and resulting microstructure, we show that intermediate pressures (50–80 kN) and rapid cooling refine dendrites, reduce porosity, and enhance ...
Mila Christy de Oliveira +4 more
wiley +1 more source
Kinematics and geometric features of the s-cone test piece: identifying the performance of five-axis machine tools using a new test piece. [PDF]
Int J Adv Manuf Technol, 2023 Osei S, Wang W, Ding Q.
europepmc +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Year-Round Thermal Error Modeling and Compensation for the Spindle of Machine Tools Based on Ambient Temperature Intervals. [PDF]
Sensors (Basel), 2022 Wei X, Ye H, Feng X.
europepmc +1 more source
Advanced Engineering Materials, EarlyView.This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source