ENGLISH
|
JAPANESE
|
CONNECT WITH US:
Home
About
Contact
Log in
*
Home
Press release
Nov 08, 2022 00:00 JST
Source:
Science and Technology of Advanced Materials
New data extracted from old for materials databases
Scientists in Japan have combined two computational models to extract more data on steel alloys from a single test, with implications for the discovery of new materials.
TSUKUBA, Japan, Nov 07, 2022 - (ACN Newswire) - A new approach uses data from one type of test on small metal alloy samples to extract enough information for building databases that can be used to predict the properties and potentials of new materials. The details were published in the journal Science and Technology of Advanced Materials: Methods.
The scientists used computer simulations to build database of material properties.
The Scientists found a way to use topography around indentation impression to predict other properties measured by a tensile or compression test.
The test is called instrumented indentation. It involves driving an indenter tip into a material to probe some of its properties, such as hardness and elastic stiffness. Scientists have been using the data extracted from instrumented indentation to estimate the stress-strain curve of materials using computational simulations. This curve, and the data it provides, is important for understanding a material's properties. That data is also used for building massive materials databases, which can be used, in conjunction with artificial intelligence, for predicting new materials.
A problem scientists face is that this approach for estimating material properties is limited when it comes to materials called 'high work-hardening alloys': metal alloys, like steel, that are strengthened through physical processes like rolling and forging. Only so much information can be estimated from the curve of these materials. To get the necessary additional information needed to determine their properties, more experiments would need to be done, which costs time, effort and money.
Ta-Te Chen of the University of Tsukuba and Ikumu Watanabe of the National Institute for Materials Science in Japan have developed a new computational approach to extract that additional information from instrumented indentation tests on work-hardening alloys.
"Our approach builds on an already-existing model, making it ready for use in industry. It is also applicable to existing data, including hardness," says Watanabe.
The approach involves combining the results from two computational models, the power-law and linear hardening models, which produce their own individual stress-plastic strain curves from information gathered from indentation tests. Combining the data from both curves provides the extra data that, when added to the original stress-strain curve, shows a more holistic picture of the work-hardening alloys' properties.
The scientists validated their approach by using it on a high-work-hardening stainless steel.
We have extended this approach to also evaluate mechanical properties at elevated temperatures, which can contribute to the development of high-temperature alloys," says Chen.
Further information
Ikumu Watanabe
National Institute for Materials Science
Email:
WATANABE.Ikumu@nims.go.jp
About Science and Technology of Advanced Materials: Methods (STAM Methods)
STAM Methods is an open access sister journal of Science and Technology of Advanced Materials (STAM), and focuses on emergent methods and tools for improving and/or accelerating materials developments, such as methodology, apparatus, instrumentation, modeling, high-through put data collection, materials/process informatics, databases, and programming.
https://www.tandfonline.com/STAM-M
Dr. Yasufumi Nakamichi
STAM Methods Publishing Director
Email:
NAKAMICHI.Yasufumi@nims.go.jp
Press release distributed by Asia Research News for Science and Technology of Advanced Materials.
Source: Science and Technology of Advanced Materials
Sectors: Electronics, Materials & Nanotech, Science & Research
Copyright ©2025 ACN Newswire. All rights reserved. A division of Asia Corporate News Network.
Latest Release
CaoCao Inc. (2643.HK) Added to Hang Seng Composite Index, Set to Join Hong Kong Stock Connect on Sept 8
Aug 22, 2025 19:51 JST
CITIC Resources Deepens Dual Driver Development Strategy of "Investment + Trading"
Aug 22, 2025 19:28 JST
China International Development Corporation acquires strategic 20% stake in NVT
Aug 22, 2025 09:22 JST
TANAKA PRECIOUS METAL GROUP and TANAKA MIRAI Lab. Successfully Carries Out Space Protein Crystallization Experiments
Aug 22, 2025 03:00 JST
NEC digital technologies to empower small-scale producers in Africa in partnership with IFAD
Aug 21, 2025 20:32 JST
Sharp Corporation and Sharp Energy Solutions Corporation Sign Memorandum of Understanding with Mitsui O.S.K. Lines, and AAR Japan for Donation of Solar Modules to Kenya
Aug 21, 2025 20:15 JST
Aiming to Build Battery Ecosystem, Toyota and Mazda Start Tests of Energy Storage System Using Electrified Vehicle Batteries
Aug 21, 2025 19:50 JST
NEC signs Memorandum of Cooperation with the Senegalese government, CFPT-SJ, JICA, and four Japan-based companies for vocational training in Senegal
Aug 21, 2025 19:27 JST
Sharp Corporation and Sharp Energy Solutions Corporation Sign Memorandum of Understanding with Mitsui O.S.K. Lines, and IOM to Advance Cooperation through Renewable Energy
Aug 21, 2025 19:07 JST
Kingsoft Announces 2025 Interim and Second Quarter Results
Aug 21, 2025 12:16 JST
NEC develops robot control technology using AI to achieve safe, efficient autonomous movement even at sites with many obstacles
Aug 21, 2025 10:39 JST
Hengdeli Announces 2025 Interim Results
Aug 20, 2025 20:52 JST
Emperor W&J Announces 2025 Interim Results, Revenues from Hong Kong and Mainland China Increase by 9% Respectively
Aug 20, 2025 20:00 JST
Honda Establishes New Subsidiary in India for Retail Financing Services
Aug 20, 2025 18:15 JST
Sharp Introduces Conversational AI Character "Poketomo"
Aug 20, 2025 16:22 JST
Collaborate with BNI, JCB Launch the 1st JCB Corporate Card in Indonesia
Aug 20, 2025 16:00 JST
NEC collaborates with WFP to strengthen cooperative development in Africa
Aug 20, 2025 15:53 JST
Hitachi High-Tech and NOF Metal Coatings use materials informatics to improve the efficiency and sophistication of research and development work
Aug 19, 2025 16:38 JST
NEC and ClimateAi Develop Conceptual Model to Promote Climate Change Adaptation in Agriculture
Aug 19, 2025 11:33 JST
Value Research Center to host The Valuism Conference 2025 on August 28-29 (Hybrid Format)
Aug 19, 2025 11:00 JST
More Latest Release >>
Related Release
Progress towards potassium-ion batteries
July 08 2025 06:48 JST
New method to blend functions for soft electronics
June 23 2025 00:15 JST
New Database of Materials Accelerates Electronics Innovation
May 05 2025 03:20 JST
High-brilliance radiation quickly finds the best composition for half-metal alloys
January 28 2025 08:00 JST
Machine learning used to optimise polymer production
December 03 2024 23:15 JST
Machine learning can predict the mechanical properties of polymers
October 25 2024 23:00 JST
Dual-action therapy shows promise against aggressive oral cancer
July 30 2024 20:00 JST
A new spin on materials analysis
April 17 2024 22:00 JST
Kirigami hydrogels rise from cellulose film
April 12 2024 18:00 JST
Sensing structure without touching
February 27 2024 08:00 JST
More Press release >>