Digital Transformation in Materials Science 2026

Language:
Japanese
Product Code No:
C67121000
Issued In:
2026/01
#of Pages:
152
Publication Cycle:
  
Format:
PDF
Geographic Coverage:
Global , Japan
Industry:
Jump to the Japanese Page:

Price

180,000 yen ($1,138.74)
(excluding consumption tax)
360,000 yen ($2,277.47)
(excluding consumption tax)
540,000 yen ($3,416.21)
(excluding consumption tax)
* Equivalent value in US$ (Today's rate : $1= 158.07 yen , 2026/01/20 Japan)
*Scope of Each License Type

Coverage: (Product/service)

Digital Transformation in Materials Science

Research Target:

Companies and research Institutions studying digital transformation for materials science

Research Content:

This report provides the trend of digital transformation in material science, including key trends and key players pertaining to Process Informatics (PI), computational science and simulation technology, use of AI and machine learning, and Organic and Inorganic Materials Informatics (MI).

This market report is recommended for:

  • Strategic Leaders & Analysts: Professionals seeking to synthesize broader market dynamics, digital transformation (DX) trends in material science, and competitive intelligence into a cohesive market outlook.
  • Product Managers & Business Developers: Those responsible for defining target metrics and establishing data-driven frameworks for new product launches or developmental phases.
  • DX Specialists & Innovators: Individuals looking for actionable insights into the product landscape and a deeper understanding of competitor positioning and emerging industry shifts regarding DX in material science

 

Q: What years' performance data and forecasts are included?
A: Actual figures for 2025 and market size forecasts from 2030 to 2050.

Q: What are the key topics/keywords discussed in the report?
A: While traditional Materials Informatics (MI) primarily focused on the relationship between material composition and physical properties, PI aims to elucidate the correlation between manufacturing process parameters and final product characteristics. Digital Transformation (DX) in material science has entered a new phase, advancing the development of digital twin of entire manufacturing processes. By modeling the complex interactions between process variables and material properties using AI, technologies enable rapid identification of optimal manufacturing conditions.

Q: Can I find market player trends in this report?
A: You can explore the business trends of companies and research institutions advancing initiatives toward commercializing DX-related technologies in material science segment.

TOC:

Chapter 1: Process Informatics

Chapter 2: Computational Science and Simulation Technology

Chapter 3: Material Design Using AI and Machine Learning

Chapter 4: Organic Materials Informatics

Chapter 5: Inorganic Materials Informatics

Price

written in Japanese
180,000 yen ($1,138.74)
(excluding consumption tax)
360,000 yen ($2,277.47)
(excluding consumption tax)
540,000 yen ($3,416.21)
(excluding consumption tax)
* Equivalent value in US$ (Today's rate : $1= 158.07 yen , 2026/01/20 Japan)
*Scope of Each License Type