CONNECT WITH US:
Aug 01, 2020 04:00 JST
Science and Technology of Advanced Materials
Using AI to predict new materials with desired properties
An artificial intelligence approach extracts how an aluminum alloy's contents and manufacturing process are related to specific mechanical properties.
Tsukuba, Japan, Aug 01, 2020 - (ACN Newswire) - Scientists in Japan have developed a machine learning approach that can predict the elements and manufacturing processes needed to obtain an aluminum alloy with specific, desired mechanical properties. The approach, published in the journal Science and Technology of Advanced Materials, could facilitate the discovery of new materials.
Aluminum alloys are lightweight, energy-saving materials which are used for various purposes, from welding materials for buildings to bicycle frames. (Credit: Jozef Polc via123rf)
Aluminum alloys are lightweight, energy-saving materials made predominantly from aluminum, but also contain other elements, such as magnesium, manganese, silicon, zinc and copper. The combination of elements and manufacturing process determines how resilient the alloys are to various stresses. For example, 5000 series aluminum alloys contain magnesium and several other elements and are used as a welding material in buildings, cars, and pressurized vessels. 7000 series aluminum alloys contain zinc, and usually magnesium and copper, and are most commonly used in bicycle frames.
Experimenting with various combinations of elements and manufacturing processes to fabricate aluminum alloys is time-consuming and expensive. To overcome this, Ryo Tamura and colleagues at Japan's National Institute for Materials Science and Toyota Motor Corporation developed a materials informatics technique that feeds known data from aluminum alloy databases into a machine learning model. This trains the model to understand relationships between alloys' mechanical properties and the different elements they are made of, as well as the type of heat treatment applied during manufacturing. Once the model is provided enough data, it can then predict what is required to manufacture a new alloy with specific mechanical properties. All this without the need for input or supervision from a human.
The model found, for example, 5000 series aluminum alloys that are highly resistant to stress and deformation can be made by increasing the manganese and magnesium content and reducing the aluminum content. "This sort of information could be useful for developing new materials, including alloys, that meet the needs of industry," says Tamura.
The model employs a statistical method, called Markov chain Monte Carlo, which uses algorithms to obtain information and then represent the results in graphs that facilitate the visualization of how the different variables relate. The machine learning approach can be made more reliable by inputting a larger dataset during the training process.
National Institute for Materials Science
About Science and Technology of Advanced Materials Journal
Open access journal STAM publishes outstanding research articles across all aspects of materials science, including functional and structural materials, theoretical analyses, and properties of materials.
STAM Publishing Director
Press release distributed by ResearchSEA for Science and Technology of Advanced Materials.
Source: Science and Technology of Advanced Materials
Sectors: Metals & Mining, Nanotechnology, Science & Research, Artificial Intel [AI]
Copyright ©2020 ACN Newswire. All rights reserved. A division of Asia Corporate News Network.
Related Press Release
Let the robot swarms begin!
June 21 2020 18:00 JST
Bringing the green revolution to electronics
February 28 2020 16:00 JST
Gaining more control over fuel cell membranes
February 21 2020 08:00 JST
Using bone's natural electricity to promote regeneration
February 13 2020 01:00 JST
Combined data approach could accelerate development of new materials
February 11 2020 16:00 JST
Measuring the wear and tear of metals
February 06 2020 13:00 JST
Quantum dot imaging advances
April 16 2019 16:00 JST
Electronics at the nanoscale: challenges and opportunities for making metal nanowires
March 26 2019 04:00 JST
The Future of Stretchable Electronics
March 24 2019 16:00 JST
Progress in Self-assembling Nanomaterials
February 07 2019 20:00 JST
More Press release >>
Latest Press Release
Toyota's Global Sales and Production Up Year-on-Year in September
Oct 29, 2020 13:57 JST
DENSO Announces First-half Financial Results
Oct 29, 2020 12:57 JST
MITSUBISHI MOTORS Starts Production of XPANDER in Malaysia
Oct 29, 2020 09:03 JST
Trials of Jointly Developed Compact LNG Filling System to Commence in Hokkaido
Oct 28, 2020 10:30 JST
Eisai to Present Latest Data on Pipeline Assets in the Area of Alzheimer's Disease and Dementia at the 13th Clinical Trials on Alzheimer's Disease Conference
Oct 28, 2020 10:07 JST
Eisai and JD Health Establish JV Company in China to Implement Health Service Platform
Oct 28, 2020 09:01 JST
SDK to Split Its Optical Semiconductor Business
Oct 27, 2020 16:00 JST
Hitachi: "Paperless & Office" Innovations to Achieve New Workstyles in the New Normal
Oct 27, 2020 12:59 JST
Mitsubishi Corporation: Cross-Industry Investment by Seven Enterprises in New TradeWaltz Platform
Oct 27, 2020 12:25 JST
MHI Opens "Yokohama Hardtech Hub"
Oct 27, 2020 11:19 JST
Hitachi Named a Leader in 2020 Gartner Magic Quadrant for Industrial IoT Platforms
Oct 27, 2020 10:59 JST
Hitachi ABB Power Grids Wins Major Order to Support Sub-Saharan Africa's Largest Solar Venture in Angola
Oct 27, 2020 08:51 JST
Eisai and Cogstate Expand Agreement for Global Development and Commercialization of Digital Cognitive Assessment Technologies
Oct 26, 2020 16:52 JST
NEC and Realeyes Jointly Develop Emotion Analysis Service in Support of Video Communications
Oct 26, 2020 10:05 JST
NEC and Analog Devices Collaborate to provide a 5G O-RAN Massive MIMO Radio for Rakuten Mobile
Oct 23, 2020 17:31 JST
Mitsubishi Power Receives Follow-up Order from Serbia for Two Sets of World's Largest Flue Gas Desulfurization Systems
Oct 22, 2020 18:24 JST
MHI Thermal Systems Opens New Development and Testing Facility for Commercial-Use Air Conditioning & Refrigeration Systems
Oct 22, 2020 18:13 JST
MHI Again Receives EcoVadis Silver Rating for Overall Sustainability
Oct 20, 2020 15:54 JST
Vodafone and NEC Start Trialing Open RAN Technology
Oct 20, 2020 11:09 JST
Mitsubishi Shipbuilding Receives Approval in Principle for LNG Fuel Gas Supply System from Bureau Veritas
Oct 19, 2020 19:07 JST
More Latest Release >>