[HTML][HTML] Making sustainable aluminum by recycling scrap: The science of “dirty” alloys
There are several facets of aluminum when it comes to sustainability. While it helps to save
fuel due to its low density, producing it from ores is very energy-intensive. Recycling it shifts …
fuel due to its low density, producing it from ores is very energy-intensive. Recycling it shifts …
Recent applications of machine learning in alloy design: A review
The history of machine learning (ML) can be traced back to the 1950 s, and its application in
alloy design has recently begun to flourish and expand rapidly. The driving force behind this …
alloy design has recently begun to flourish and expand rapidly. The driving force behind this …
Data analytics approach for melt-pool geometries in metal additive manufacturing
S Lee, J Peng, D Shin, YS Choi - Science and technology of …, 2019 - Taylor & Francis
Modern data analytics was employed to understand and predict physics-based melt-pool
formation by fabricating Ni alloy single tracks using powder bed fusion. An extensive …
formation by fabricating Ni alloy single tracks using powder bed fusion. An extensive …
Machine learning approach for the prediction and optimization of thermal transport properties
Y Ouyang, C Yu, G Yan, J Chen - Frontiers of Physics, 2021 - Springer
Traditional simulation methods have made prominent progress in aiding experiments for
understanding thermal transport properties of materials, and in predicting thermal …
understanding thermal transport properties of materials, and in predicting thermal …
Prediction of mechanical properties of wrought aluminium alloys using feature engineering assisted machine learning approach
Data-mining based machine learning (ML) method is emerging as a strategy to predict
aluminium (Al) alloy properties with the promise of less intensive experimental work …
aluminium (Al) alloy properties with the promise of less intensive experimental work …
A data-driven framework to predict the morphology of interfacial Cu6Sn5 IMC in SAC/Cu system during laser soldering
A data-driven approach combining together the experimental laser soldering, finite element
analysis and machine learning, has been utilized to predict the morphology of interfacial …
analysis and machine learning, has been utilized to predict the morphology of interfacial …
Recent Progress in Creep-Resistant Aluminum Alloys for Diesel Engine Applications: A Review
RI Arriaga-Benitez, M Pekguleryuz - Materials, 2024 - mdpi.com
Diesel engines in heavy-duty vehicles are predicted to maintain a stable presence in the
future due to the difficulty of electrifying heavy trucks, mine equipment, and railway cars. This …
future due to the difficulty of electrifying heavy trucks, mine equipment, and railway cars. This …
Combining multi-phase field simulation with neural network analysis to unravel thermomigration accelerated growth behavior of Cu6Sn5 IMC at cold side Cu–Sn …
In Pb-free solder alloys used in solder balls of diameter of 50 µm or smaller, larger
proportion of Cu 6 Sn 5 intermetallics formation is a major reliability concern, and this is …
proportion of Cu 6 Sn 5 intermetallics formation is a major reliability concern, and this is …
Predicting diffusion coefficients of binary and ternary supercritical water mixtures via machine and transfer learning with deep neural network
Prediction for diffusion coefficients of multicomponent supercritical water (SCW) mixtures is
crucial for the system design and industrial application of SCW-related technologies, such …
crucial for the system design and industrial application of SCW-related technologies, such …
[HTML][HTML] Machine learning approach for prediction of hydrogen environment embrittlement in austenitic steels
This study introduces a machine learning approach to predict the effect of alloying elements
and test conditions on the hydrogen environment embrittlement (HEE) index of austenitic …
and test conditions on the hydrogen environment embrittlement (HEE) index of austenitic …