# A design methodology of crystal growth furnace and process aided by two-step optimization using machine learning models and genetic algorithm

https://mdr.nims.go.jp/datasets/0bfe60fa-8ad3-424d-9e8a-48d84b8392f8

## File

- [A design methodology of crystal growth furnace and process aided by two-step optimization using machine learning models and genetic algorithm (1).pdf](https://mdr.nims.go.jp/filesets/03d4ac33-5aa5-4e99-9653-a1e859702936/download) ([Detail](https://mdr.nims.go.jp/filesets/03d4ac33-5aa5-4e99-9653-a1e859702936.md))
- [Supplemental.pdf](https://mdr.nims.go.jp/filesets/9be7e110-77e4-4e9d-90fe-11aa262b688a/download) ([Detail](https://mdr.nims.go.jp/filesets/9be7e110-77e4-4e9d-90fe-11aa262b688a.md))
- [TSTM-2025-0008_data.zip](https://mdr.nims.go.jp/filesets/fe5a6101-8c5f-42fd-9aaf-0ed9a7e353fa/download) ([Detail](https://mdr.nims.go.jp/filesets/fe5a6101-8c5f-42fd-9aaf-0ed9a7e353fa.md))
- [Figure3b.txt](https://mdr.nims.go.jp/filesets/e50e9bed-0694-407d-9ffd-92b0379f0394/download) ([Detail](https://mdr.nims.go.jp/filesets/e50e9bed-0694-407d-9ffd-92b0379f0394.md))
- [Figure14.txt](https://mdr.nims.go.jp/filesets/0b45422d-2b07-4dd6-84f9-4cd53c416e15/download) ([Detail](https://mdr.nims.go.jp/filesets/0b45422d-2b07-4dd6-84f9-4cd53c416e15.md))
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## Id

0bfe60fa-8ad3-424d-9e8a-48d84b8392f8

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2026-02-26T04:22:51.907456Z

## Updated at

2026-02-27T03:30:07.753807Z

## Published at

2026-02-27T00:51:39.066090Z

## Doi

https://doi.org/10.48505/nims.6191

## First published url

https://doi.org/10.1080/27660400.2025.2581358

## Date published

2025-12-31

## Recorded date published

2025-12-31

## Resource type

journal_article

## Manuscript type

accepted_manuscript

## Collection



## Title

- title: A design methodology of crystal growth furnace and process aided by two-step
    optimization using machine learning models and genetic algorithm
  title_type: original
  lang: en

## Description

- description: We have developed an innovative design method for crystal growth furnaces
    and processes involving two-step optimization. The first step focuses on finding
    the ideal temperature transition around the crucible without assuming a specific
    crystal growth furnace. The design of the crystal growth furnace and process is
    then optimized to replicate the ideal temperature transition. We utilized a deep
    neural network model in each optimization step to substitute crystal growth simulation
    and genetic algorithm. A proof-of-concept optimization is performed for the directional
    solidification of a crystalline silicon ingot in a crucible. Since our method
    does not rely on a predetermined furnace, we can achieve more flexible temperature
    distribution transitions than conventional approaches by implementing adaptable
    temperature boundary conditions. This allows us to refine the design of the crystal
    growth furnace and process, which has significant potential to advance the production
    of a wide range of materials and improve materials production environments and
    equipment design.
  description_type: abstract
  lang: en

## Creator

- name: Hiroyuki Tanaka
  role: author
  organization: Nagoya University
  department: a Graduate School of Engineering
- name: Kentaro Kutsukake
  role: author
- name: Kota Asakura
  role: author
- name: Takuto Kojima
  role: author
- name: Xin Liu
  role: author
- name: Noritaka Usami
  role: author

## Contact agent



## Publisher

organization: Taylor & Francis

## Managing organization



## Keyword

- subject: Optimization
  schema: not_defined
- subject: machine learning
  schema: not_defined
- subject: genetic algorithm
  schema: not_defined
- subject: crystal growth
  schema: not_defined
- subject: process informatics
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Science and Technology of Advanced Materials
  issn: '27660400'
  volume: '5'
  issue: '1'
  article_number: '2581358'

## Conference



## Related item



## Funding



## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



## Energy level/transition state



## Software



## Custom property



## Fileset

- id: 03d4ac33-5aa5-4e99-9653-a1e859702936
  filename: A design methodology of crystal growth furnace and process aided by two-step
    optimization using machine learning models and genetic algorithm (1).pdf
  content_type: application/pdf
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- id: 9be7e110-77e4-4e9d-90fe-11aa262b688a
  filename: Supplemental.pdf
  content_type: application/pdf
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- id: e50e9bed-0694-407d-9ffd-92b0379f0394
  filename: Figure3b.txt
  content_type: text/plain
  size: 42364
  md5: c4a419d924ed719d545e85a513323e33
- id: 0b45422d-2b07-4dd6-84f9-4cd53c416e15
  filename: Figure14.txt
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- id: 80cc4fe2-90d1-496b-8157-7a51e2f87356
  filename: Note_about_fig3b_and 14.txt
  content_type: text/plain
  size: 127
  md5: 36d2914bbc667f396b80c962a0295041

## Thumbnail