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2023 Fiscal Year Annual Research Report

Development of Collaborative Intelligence System and Application in Energy Materials

Research Project

Project/Area Number 22KJ0780
Allocation TypeMulti-year Fund
Research InstitutionThe University of Tokyo

Principal Investigator

ZHANG YUCHENG  東京大学, 工学系研究科, 特別研究員(DC2)

Project Period (FY) 2023-03-08 – 2024-03-31
Keywordselectret material / CYTOP / deep learning / molecule optimization / PCM / DFT
Outline of Annual Research Achievements

Density functional theory (DFT) with polarizable continuum model (PCM) is introduced to analyze the charge trapping mechanism of CYTOP-based electrets. It is found that the computational cost of PCM-DFT is 16 times smaller than that of MD-DFT and requires no manual intervention. Thereafter, a quantum chemical dataset consisted of 10k molecules is built via high-throughput PCM-DFT computations.
ChemTS-based de novo molecule generation algorithm has been employed to design new molecules. To avoid the huge computational cost and the difficulty in the chemical synthesis, graph neural networks such as MEGNET have been used to screen amine end groups and to predict the charging performance of CYTOP electrets. Functional group enrichment analysis is made to extract interpretable knowledge from abundant data where hydroxyl group and piperazine substructure are found effective. Thereafter, quantum chemical formula, deep reinforcement learning and expert knowledge are coupled for successfully building an automatic collaborative intelligence system.
Brand-new superior electrets such as CTX-A/APDEA, DHPEDA, BAPP, APPCA are proposed and synthesized based on the proposed simulation methods and AI-based algorithms. Taking the developed CTX-A/BAPP as an example. It can retain the surface potential of over +/- 3kV after 2135 hours under room temperature. Its TSD peak temperature is around 236 °C, while the previously developed CTX-A/APDEA is around 180 °C. Its lifetime is estimated as 146 years at 80 ℃, which is much better than previously commercialized CTYOP-EGG (12.4 years).

  • Research Products

    (1 results)

All 2023

All Journal Article (1 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 1 results,  Open Access: 1 results)

  • [Journal Article] AI‐Driven Discovery of Amorphous Fluorinated Polymer Electret with Improved Charge Stability for Energy Harvesting2023

    • Author(s)
      Mao Zetian、Chen Chi、Zhang Yucheng、Suzuki Kuniko、Suzuki Yuji
    • Journal Title

      Advanced Materials

      Volume: / Pages: /

    • DOI

      10.1002/adma.202303827

    • Peer Reviewed / Open Access / Int'l Joint Research

URL: 

Published: 2024-12-25  

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