[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 …
Machine learning accelerates the materials discovery
J Fang, M **e, X He, J Zhang, J Hu, Y Chen… - Materials Today …, 2022 - Elsevier
As the big data generated by the development of modern experiments and computing
technology becomes more and more accessible, the material design method based on …
technology becomes more and more accessible, the material design method based on …
[HTML][HTML] Machine learning assisted design of aluminum-lithium alloy with high specific modulus and specific strength
H Li, X Li, Y Li, W **ao, K Wen, Z Li, Y Zhang, B **ong - Materials & Design, 2023 - Elsevier
Advanced aluminum-lithium alloys are the key structural materials urgently needed for the
development of light-weighted aircraft in the aerospace field. In this study, we employ a …
development of light-weighted aircraft in the aerospace field. In this study, we employ a …
[HTML][HTML] Knowledge-aware design of high-strength aviation aluminum alloys via machine learning
J Yong-fei, N Guo-shuai, Y Yang, D Yong-bing… - Journal of Materials …, 2023 - Elsevier
The development of the aviation industry is accompanied by the continuous research of high-
performance aviation aluminum alloys. Stuck in vast untapped composition space and the …
performance aviation aluminum alloys. Stuck in vast untapped composition space and the …
Machine learning elastic constants of multi-component alloys
The present manuscript explores application of machine learning methods for determining
elastic constants and other derived mechanical properties of multi-component alloys. A …
elastic constants and other derived mechanical properties of multi-component alloys. A …
[HTML][HTML] Machine learning-based forward and inverse designs for prediction and optimization of fracture toughness of aluminum alloy
Utilization of machine learning framework to design aluminum alloy with high fracture
toughness is increasing. Nonetheless, before such model can be applied, the …
toughness is increasing. Nonetheless, before such model can be applied, the …
Unsupervised machine learning discovers classes in aluminium alloys
Aluminium (Al) alloys are critical to many applications. Although Al alloys have been
commercially widespread for over a century, their development has predominantly taken a …
commercially widespread for over a century, their development has predominantly taken a …
[HTML][HTML] Data-driven design of biometric composite metamaterials with extremely recoverable and ultrahigh specific energy absorption
The existing mechanical metamaterials are often designed with periodic inter-connected
structs with simple cylindrical or uniform hierarchical geometries, which relies on their parent …
structs with simple cylindrical or uniform hierarchical geometries, which relies on their parent …
[PDF][PDF] Boosting for concept design of casting aluminum alloys driven by combining computational thermodynamics and machine learning techniques
Casting aluminum alloys are commonly used in industries due to their excellent
comprehensive performance. Alloying/microalloying and post-solidification heat treatments …
comprehensive performance. Alloying/microalloying and post-solidification heat treatments …
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 …