Close Menu
    Facebook X (Twitter) Instagram
    Facebook X (Twitter) Instagram
    BusinessNewsAsia.comBusinessNewsAsia.com
    Subscribe
    • Home
    • Top Stories
    • Business
    • Tech
    • Companies
    • Events
    • Announcements
    BusinessNewsAsia.comBusinessNewsAsia.com
    Home»Electronics»Showa Denko, AIST, NEDO and ADMAT Prove AI Speeds up Development of Flexible Transparent Film
    Electronics

    Showa Denko, AIST, NEDO and ADMAT Prove AI Speeds up Development of Flexible Transparent Film

    Marie JonesBy Marie JonesApril 13, 2020No Comments6 Mins Read
    Share
    Facebook Twitter LinkedIn Pinterest Email

    Low_sdk2004131TOKYO, Apr 13, 2020 – (JCN Newswire) – Showa Denko (“Showa Denko”; TSE: 4004), National Institute of Advanced Industrial Science and Technology (AIST), New Energy and Industrial Technology Development Organization (NEDO) and Research Association of High-Throughput Design and Development for Advanced Functional Materials (ADMAT) have cooperatively proved that introduction of artificial intelligence (AI) into the process to develop flexible transparent film[1] can reduce the numbers of times of experiment to produce film that satisfies required properties to one-twenty-fifth (1/25) or less of those conventional development methods require.

    This development work has been subcontracted by NEDO’s “Ultra High-Throughput Design and Prototyping Technology for Ultra Advanced Materials Development Project” (Ultra-Ultra PJ) to the consortium. By fully utilizing AI and multiscale simulation[2], Ultra-Ultra PJ aims to reduce substantially the numbers of times of experiment and development period required for the development of flexible transparent film from those conventional ways of material development require.

    Researchers of SDK, AIST and ADMAT have been conducting AI-based searches for polymers that satisfy properties required for designing of flexible transparent film, which is essential for development of mobile devices. As the first step of this research, skilled researchers produced 27 types of films. Then researchers incorporated chemical information including molecular structures and mole ratios into explanatory variables[3] with a special method named Extended Connectivity Circular Fingerprints (ECFP4), and chose converted transmissivity[5], braking stress and stretch as objective variables[6]. These three objective variables have trade-off relations and are incompatible among them. Then, researchers made the AI learn actual values of these variables.

    Following these steps, researchers prepared data including comprehensively dispersed explanatory variables, made the AI learn concept of the deviation value[7] and estimate several combinations of materials for films that would maximize the three objective variables with the same ratio. Then researchers manufactured three types of films based on the recommendation AI made. Concurrently, as a comparative experiment, the skilled researchers who prepared the 27 sample films at the first step also made 25 types of films based on their own knowledge and experience. Next, we compared properties of the three types of films based on combination of materials recommended by the AI and 25 types of films prepared by the skilled researchers who made the 27 types of films in the first step of the research.

    As a result, physical properties of all of the three types of films made from combinations of raw materials recommended by the AI showed superiority over those of the 25 types of films made by the skilled researchers. We obtained films with physical properties superior to those developed by skilled researchers through one-twenty-fifth times of experiments or less compared to the development process conducted by the skilled researchers. Thus, we proved that we can substantially shorten the period of development of flexible transparent films by utilizing AI, and that it is possible for us to develop films with physical properties superior to those of films made by researches based on their knowledge and experience

    Hereafter, we will improve this technology further, and develop a system in which the AI can suggest ratios of combinations of raw materials that can produce target products with even better physical properties while satisfying required characteristics. Today, we also announced the detail of this development work on the Website reporting results of the Ultra High-Throughput Design and Prototyping Technology for Ultra Advanced Materials Development Project (Ultra-Ultra PJ).

    Notes:

    [1] Flexible transparent film: This is a bendable transparent film. Flexible transparent film is applicable to wide-ranging use such as electroconductive transparent base for touch panel, base for flexible electronic circuit and base for flexible display panel.

    [2] Multiscale simulation: This simulation connects material density, flux density and energy density in an interactive way and as common languages. It simulates behavior of various matters ranging from atoms and molecules in micro fields to fluids and continuums in macro fields. For detail, please access the following URLs.

    URL: https://www.admat.or.jp/technology

    URL: https://tinyurl.com/ujkkndy

    [3] Explanatory variables: These are variables that lead to estimates, including mole ratio and kind of functional group of raw materials to make polymers

    [4] Extended Connectivity Circular Fingerprints (ECFP): This is a way to describe characteristics of molecules by quantifying kinds and numbers of partial structures including functional groups. For detail, please refer to the following theses.

    1. Rogers, M. Hahn, J. Chem. Inf. Model. 50, 742 (2010).
    2. Minami, et al., MRS Advances, 3(49), 2975 (2018)

    URL: https://bit.ly/3a4leov

    [5] Converted transmissivity: In this experiment, researchers converted refractive index measured by skilled researchers into transmissivity.

    [6] Objective variables: These are variables to be estimated, such as physical properties of polymers.

    [7] Concept of the deviation value: Converted value of variable by setting the mean value as 50 and standard deviation as 10. In this development work, we calculated deviation values by converting the three objective variables (converted transmissivity, braking stress and stretch).

     

    Outline of organizations

    Showa Denko K.K. (SDK)

    Location: 13-9, Shiba Daimon 1-chome, Minato-ku, Tokyo

    Establishment: June 1939

    President: Kohei Morikawa

    Scope of business: Manufacture and sale of organic/inorganic chemicals, ceramics, electronic materials, aluminum, etc.

    URL: https://www.sdk.co.jp/

     

    National Institute of Advanced Industrial Science and Technology (AIST)

    Location: 1-3-1, Kasumigaseki, Chiyoda-ku, Tokyo

    Establishment: April 2001

    President: Kazuhiko Ishimura

    Scope of business: Research and development concerning industrial technology

    URL: https://www.aist.go.jp/

     

    New Energy and Industrial Technology Development Organization (NEDO)

    Location: Muza Kawasaki Central Tower, 1310 Omiya-cho, Saiwai-ku, Kawasaki-city, Kanagawa

    Establishment: October 2003

    Chairman: Hiroaki Ishizuka

    Scope of business: Management of technological development and related matters

    URL: https://www.nedo.go.jp/

     

    Research Association of High-Throughput Design and Development for Advanced Functional Materials (ADMAT)

    Location: Central 5-1, 1-1-1 Higashi, Tsukuba, Ibaraki (at the premises of AIST Tsukuba Center)

    Establishment: July 2016

    Chief Director: Kunihiro Koshizuka

    Scope of business: R&D work to reduce drastically the number of prototypes and length of time required to develop functional materials

    URL: http://www.admat.or.jp/

     

    For further information, contact:

    SDK

    CSR & Corporate Communication Office

    Phone: 81-3-5470-3235

    Fax: 81-3-3431-6215

     

    AIST

    Media Relations Office, Planning Headquarters

    Phone: 81-29-862-6216

    Fax: 81-29-862-6212

    E-mail: press-ml@aist.go.jp

     

    NEDO

    Miyake or Hara

    Materials Technology and Nanotechnology Department

    Phone: 81-44-520-5220

    E-mail: mkyakemsm@nedo.go.jp

     

    ADMAT

    Yukito Matsuda

    Phone: 81-29-856-3580

    Fax: 81-29-856-3582

    E-mail: y-matsuda@admat.or.jp

    SDK
    Share. Facebook Twitter Pinterest LinkedIn Tumblr Telegram Email
    Previous ArticleZhengTong Auto Appointed Mr. Tian Sheng as Chief Operating Officer
    Next Article The Executive Talk: Global Green Chemicals PCL (SET:GGC)

    Related Posts

    C.banner to Acquire Controlling Stake in Benyuan Zhishu to Establish Dual-core Businesses: Footwear + AI Data

    June 8, 2026

    Alltronics Officially Opens Malaysia Facility

    June 5, 2026

    Mint and Rice Robotics Launch Joint Venture to Expand AI Companion Robot Business with HK$15M in funding

    June 2, 2026
    Add A Comment

    Comments are closed.

    © 2026 BusinessNewsAsia.com
    • About Us
    • Contact Us
    • BusinessNews.ph
    • AsiaPEVC.com
    • DevFiNews.com
    • RenewableEnergy.ph

    Type above and press Enter to search. Press Esc to cancel.