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2018 Fiscal Year Research-status Report

Inverse materials design by integrating transfer learning techniques into a Bayesian framework

Research Project

Project/Area Number 18K18017
Research InstitutionThe Institute of Statistical Mathematics

Principal Investigator

Wu Stephen  統計数理研究所, データ科学研究系, 助教 (70804186)

Project Period (FY) 2018-04-01 – 2021-03-31
KeywordsTransfer learning / Materials informatics / Polymer design / Open source software
Outline of Annual Research Achievements

In 2018, I have successfully completed an open Python package, called XenonPy, that can perform Bayesian inverse design for organic molecules, as originally planned in my proposal. Moreover, a case study of designing high thermal conductivity polymer was completed, with a peer-reviewed paper conditionally accepted by npj Computational Materials under minor revision. One transfer learning algorithm, called Frozen-featurizer, was also implemented in XenonPy. I am now starting a series of simulation and experiment regarding the use of this algorithm. Meanwhile, more variety of the transfer learning algorithm will be developed and analyzed to understand the best way to exploit transfer learning for material design with small data.

Current Status of Research Progress
Current Status of Research Progress

1: Research has progressed more than it was originally planned.

Reason

The basic functionality of the open software for material design, including the Bayesian inverse design and one transfer learning method, was finished as planned. One paper is conditionally accepted along with a patent submitted for approval. Furthermore, the developed methodology on transfer learning has been extended to other applications outside of materials science as well, showing the great potential of our algorithm. I have given a presentation on this subject in four Japanese conferences and one international conference, as well as being an invited speaker at four international workshops. Despite the great success on the software development and application, I think the experimental work in this project needs to be improved in the next year.

Strategy for Future Research Activity

With the basic infrastructure (the open package) completely ready for sure, I will continue on the development and experiment of transfer learning algorithms, as planned in the proposal. Furthermore, more collaboration with the experimental group at Tokyo Institute of Technology is expected to speed up the experimental progress. At least one more paper is expected to be published next year along with 3 or more conference participations. The major challenge is expected to the on the generalization and automation of the transfer learning algorithm to efficiently produce reliable predictive models for thermal conductivity of polymers with limited data. I expect that more effort will be spent on understanding the underlying mechanism of successful knowledge transfer in the next year.

Causes of Carryover

N/A

  • Research Products

    (10 results)

All 2018

All Presentation (9 results) (of which Int'l Joint Research: 4 results,  Invited: 4 results) Patent(Industrial Property Rights) (1 results)

  • [Presentation] A Bayesian molecular Design Framework for Searching High Thermal Conductivity Polymers2018

    • Author(s)
      Stephen Wu
    • Organizer
      統数研・流体研・AIMR合同Workshop
  • [Presentation] Accelerated Discovery of High Thermal Conductivity Polymers with a Bayesian Molecular Design Method2018

    • Author(s)
      Stephen Wu
    • Organizer
      第67回高分子学会年次大会
  • [Presentation] 機械学習に基づくポリマー設計: 合成の壁を超えるには ~ 高熱伝導率ポリマーの設計事例2018

    • Author(s)
      Stephen Wu
    • Organizer
      The 39th Japan Symposium on Thermophysical Properties
  • [Presentation] Bayesian Inverse Material Design for High Thermal Conductivity Polymers2018

    • Author(s)
      Stephen Wu
    • Organizer
      I-URICフロンティアコロキウム
  • [Presentation] Engineering applications of transfer learning2018

    • Author(s)
      Stephen Wu
    • Organizer
      Asia-Pacific-Euro Summer School on Smart Structures Technology 2018
    • Int'l Joint Research / Invited
  • [Presentation] Engineering applications of the Bayesian problem solving framework2018

    • Author(s)
      Stephen Wu
    • Organizer
      Workshop on the Frontier of Applied Bayesian Inference and Computation
    • Int'l Joint Research / Invited
  • [Presentation] Potential of transfer learning in engineering applications2018

    • Author(s)
      Stephen Wu
    • Organizer
      Big data forum on Big Data in Civil Engineering
    • Invited
  • [Presentation] Applications of transfer learning in materials science2018

    • Author(s)
      Stephen Wu
    • Organizer
      ISI-ISM-ISSAS Joint Conference 2019
    • Int'l Joint Research
  • [Presentation] Potential of applying transfer learning to engineering applications: an example in materials science2018

    • Author(s)
      Stephen Wu
    • Organizer
      信頼性工学分野におけるデータサイエンス技術の活用に関する講演会
    • Int'l Joint Research / Invited
  • [Patent(Industrial Property Rights)] ベイズ推論による高熱電導高分子の設計と合成2018

    • Inventor(s)
      森川淳子, 吉田亮, Stephen Wu, 等
    • Industrial Property Rights Holder
      森川淳子, 吉田亮, Stephen Wu, 等
    • Industrial Property Rights Type
      特許
    • Industrial Property Number
      A00386JP01

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Published: 2019-12-27  

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