Results 101 to 110 of about 1,892,477 (294)

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, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Characterization of the Dimensional Precision, Physical Bonding, and Tensile Performance of 3D-Printed PLA Parts with Different Printing Temperature

Journal of Manufacturing and Materials Processing
In this study, tensile test specimens were fabricated using a material extrusion 3D-printer at various printing temperatures to evaluate the development of physical bonds within the same layer as well as in between previous layers.
Rayson Pang, Mun Kou Lai, Khairul Izwan Ismail, Tze Chuen Yap   +3 more
doaj   +1 more source

Studies on Dimensional Accuracy of Working Casts Made by Various Impression Techniques. Influence of Undercuts on Dimensional Accuracy.

THE JOURNAL OF THE STOMATOLOGICAL SOCIETY,JAPAN, 1992
The purpose of this research was to evaluate the clinical acceptability of various impression techniques by comparing the dimensional accuracy of their working casts. An original metallic model was designed for this experiment. It has reference points to overlap and compare the master model and the working casts for measuring their dimensional accuracy
openaire   +3 more sources

On the Lightweight Potential of Laser Additive Manufactured NiTi Triply Periodic Minimal Sheet Lattices

Advanced Engineering Materials, EarlyView.
This study explores the lightweight potential of laser additive‐manufactured NiTi triply periodic minimal surface sheet lattices. It systematically investigates the effects of relative density and unit cell size on surface quality, deformation recovery, compression behavior, and energy absorption.
Haoming Mo, Shuo Qu, Shiming Gao, Xu Song   +3 more
wiley   +1 more source

Optimal Control of a Parabolic Distributed Parameter System Using a Barycentric Shifted Gegenbauer Pseudospectral Method

, 2016
In this paper, we introduce a novel pseudospectral method for the numerical solution of optimal control problems governed by a parabolic distributed parameter system.
Elgindy, Kareem T.
core  

Innovative Processing of Compacted Waste Aluminum Alloy Powders via Controlled Remelting and Solidification

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, Marcella Gaute Cavalcante Xavier, Abdoul‐Aziz Bogno, Piter Gargarella, José Eduardo Spinelli   +4 more
wiley   +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, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

A Thermodynamic 3D Model for the Simulation of Diffusion‐Controlled Alloying Processes in Heterogeneous Material Structures

Advanced Engineering Materials, EarlyView.
A numerical model resulting from irreversible thermodynamics for describing transport processes is introduced, focusing on thermodynamic activity gradients as the actual driving force for diffusion. Implemented in CUDA C++ and using CalPhaD methods for determining the necessary activity data, the model accurately simulates interdiffusion in aluminum ...
Ulrich Holländer, Leonhard Holländer, André Langohr, Hans Jürgen Maier   +3 more
wiley   +1 more source

Exploring the Effects of Thermal Cycling on the Precision of 3D-Printed Parts: A Comprehensive Analysis

Applied Sciences
This study investigates the dimensional stability of FDM-printed Z-ULTRAT components subjected to repeated thermal cycling between −20 °C and 80 °C. Dimensional measurements (height and width) were collected before cycling and after 1, 5, and 10 cycles ...
Gina-Mihaela Sicoe, Abdelhakim Dorbane, Daniel-Constantin Anghel   +2 more
doaj   +1 more source