上下併記パターン.png
JSOL
Booth
3S-G09
Zone
Data-driven R&D zone

Materials R&D in the AI era: physics, simulation and data

We will showcase three complementary technologies for materials R&D: the simulation-integrated materials informatics platform “MI-Suite,” the multiscale materials simulation platform “J-OCTA,” and “ASAP/ASAP-PRO” for first-principles calculations and machine-learning force fields. Together, they connect electronic and atomic-scale physics, molecular and mesoscale simulation, and experimental and simulation data analysis to support materials development in the age of AI.


Inquiry Chat

New Product
PDF
Demo
Stage Presentation
Product / Technology Information

New Product
PDF

MI-Suite is a materials informatics platform that integrates experimental and simulation data for materials R&D. It supports data management, preprocessing, analysis, machine learning, property prediction and materials exploration. Physics-based information obtained from simulations, including molecular interactions, interfaces, free volume, structural features and dynamics, can also be incorporated into the analysis. MI-Suite is designed to connect data-driven prediction with physical information that can support the next decision in materials design.

MI-Suite-banner.png
Download PDF
Product/Technology Category
Nano Evaluation & Measurement / Analysis Technology & Tool
Materials informatics Simulation software / Supercomputer Process informatics
Application Field
Materials
Functional hybrid material Lightweight/ high-strength material Thermic-functional material (heat resistance/storage/conduction/insulation etc) Electric material (superconductors/dielectrics/semiconductors etc) Photonic material (EL/ LED/ Liquid crystal/ Optical disk etc) Magnetic-functional material Biocompatible material Catalyst Coating material Paint/ink Precision plating Biodegradable plastic Film/sheet
IT & Electoronics
5G/6G related techniques Photonic device Display Virtual reality/ augmented reality technology Artificial intelligence(AI)/ deep learning MEMS/Micromachine Advanced semiconductor (Logic semiconductors) Wide Band Gap power semiconductor Three-dimensional circuit device Robotic Wearable device
Automobile
Solid-state battery Lithium ion battery Fuel cell / Air battery Lightening material Vehicle sensor Display Emission control system Thermal management
Environment & Energy
Fuel cell Solar battery Perovskite Secondary battery Hydrogen Energy Photo catalyst Environment evaluation, monitoring, sensor Biomass Water / soil clean-up technology PFAS-free
Biotechnology
Antibacterial / antiviral material Regenerative medicine material DDS(Drug Delivery System) Health care Biosensor Medicinal product Medical/diagnostic device Wearable device Cosmetic material Cosmetic processing technology Functional food
Others
Agriculture Textile Sporting goods Construction Aerospace Information and telecommunications equipment Biomimetics
Solutions
Digital Transformation Artificial Intelligence

PDF
Demo

J-OCTA is a multiscale simulation platform for studying materials phenomena from atomic and molecular scales to the mesoscale. It provides modeling and analysis capabilities for molecular interactions, interfaces, diffusion, phase separation, dispersion, viscoelasticity and other structure–property relationships. Building on more than two decades of research and development originating from the OCTA project, J-OCTA is also evolving as a physics-based simulation platform that can be combined with AI and materials informatics.

J-OCTA_banner.png
Download PDF
Product/Technology Category
Nano Evaluation & Measurement / Analysis Technology & Tool
Materials informatics Simulation software / Supercomputer Process informatics
Application Field
Materials
Functional hybrid material Lightweight/ high-strength material Thermic-functional material (heat resistance/storage/conduction/insulation etc) Electric material (superconductors/dielectrics/semiconductors etc) Photonic material (EL/ LED/ Liquid crystal/ Optical disk etc) Magnetic-functional material Biocompatible material Catalyst Coating material Paint/ink Precision plating Biodegradable plastic Film/sheet
IT & Electoronics
5G/6G related techniques Photonic device Display Virtual reality/ augmented reality technology Artificial intelligence(AI)/ deep learning MEMS/Micromachine Advanced semiconductor (Logic semiconductors) Wide Band Gap power semiconductor Three-dimensional circuit device Robotic Wearable device
Automobile
Solid-state battery Lithium ion battery Fuel cell / Air battery Lightening material Vehicle sensor Display Emission control system Thermal management
Environment & Energy
Fuel cell Solar battery Perovskite Secondary battery Hydrogen Energy Photo catalyst Environment evaluation, monitoring, sensor Biomass Water / soil clean-up technology PFAS-free
Biotechnology
Antibacterial / antiviral material Regenerative medicine material DDS(Drug Delivery System) Health care Biosensor Medicinal product Medical/diagnostic device Wearable device Cosmetic material Cosmetic processing technology Functional food
Others
Agriculture Textile Sporting goods Construction Aerospace Information and telecommunications equipment Biomimetics
Solutions
Digital Transformation Artificial Intelligence

ASAP / ASAP-PRO provides atomic-scale materials simulation based on first-principles calculations for studying electronic structures, defects, interfaces, reactions and diffusion. Machine-learning force fields can extend atomistic simulations beyond the size and time scales that are practical with DFT alone. ASAP can also be combined with J-OCTA and MI-Suite to connect electronic- and atomic-scale information with multiscale simulation and materials data analysis. ASAP-PRO also supports workflows based on MACE machine-learning force fields, with DFT reference calculations and validation used to assess applicability to target materials.

ASAP_banner.png
Product/Technology Category
Nano Evaluation & Measurement / Analysis Technology & Tool
Simulation software / Supercomputer
Application Field
Materials
Functional hybrid material Lightweight/ high-strength material Thermic-functional material (heat resistance/storage/conduction/insulation etc) Electric material (superconductors/dielectrics/semiconductors etc) Photonic material (EL/ LED/ Liquid crystal/ Optical disk etc) Magnetic-functional material Biocompatible material Catalyst Coating material Paint/ink Precision plating Biodegradable plastic Film/sheet
IT & Electoronics
5G/6G related techniques Photonic device Display Virtual reality/ augmented reality technology Artificial intelligence(AI)/ deep learning MEMS/Micromachine Advanced semiconductor (Logic semiconductors) Wide Band Gap power semiconductor Three-dimensional circuit device Robotic Wearable device
Automobile
Solid-state battery Lithium ion battery Fuel cell / Air battery Lightening material Vehicle sensor Display Emission control system Thermal management
Environment & Energy
Fuel cell Solar battery Perovskite Secondary battery Hydrogen Energy Photo catalyst Environment evaluation, monitoring, sensor Biomass Water / soil clean-up technology PFAS-free
Biotechnology
Antibacterial / antiviral material Regenerative medicine material DDS(Drug Delivery System) Health care Biosensor Medicinal product Medical/diagnostic device Wearable device Cosmetic material Cosmetic processing technology Functional food
Others
Agriculture Textile Sporting goods Construction Aerospace Information and telecommunications equipment Biomimetics
Solutions
Digital Transformation Artificial Intelligence
Seminar Information

  • 2026/12/18 13:00 ~ 13:30
    Venue:Seeds & Needs Seminar A(South hall 3)
    nanotech.png
    Select this
    session
    【Abstract】

    Rapid advances in artificial intelligence (AI) and machine learning are transforming materials development through data-driven prediction, materials exploration, and accelerated simulation. However, the properties of real materials are affected not only by their chemical composition but also by hierarchical structures spanning atomic, molecular, mesoscopic, and macroscopic scales, together with processing history. Physics-based simulation therefore continues to play an important role in materials design. This presentation reviews research on multiscale modeling accumulated through OCTA/J-OCTA and discusses its recent integration with AI, including structure recognition, surrogate modeling, and optimization. We also introduce MI-Suite, which aims to integrate experimental and simulation data for analysis and materials exploration. Through these examples, we discuss how multiscale simulation can evolve and complement AI in future materials development.

    Dr. Taku Ozawa
    JSOL CORPORATION
    Engineering Technology Business Unit
    General Manager
    【Profile】

    Taku Ozawa is engaged in the development and commercialization of materials simulation software at JSOL Corporation, including OCTA/J-OCTA. His interests include multiscale simulation from molecular to mesoscopic and continuum scales, materials informatics, and the integration of simulation with AI. He holds a Ph.D. and serves on a computational science research group within the Society of Polymer Science, Japan.

Contact

*The following information is provided to enable inquiries to exhibitors.
Unauthorized use and reproduction for any other purpose is prohibited.

Exhibitor Name
JSOL
Engineering Technology Business Unit
Address
KUDAN-KAIKAN TERRACE 1-6-5,Kudanminami,Chiyoda-ku,Tokyo 102-0074, Japan 102-0074
TEL
03-6261-7168
URL
Corporate's Handling of personal information URL
0 seminar(s) selected
Apply for seminar
Loading...

Updating data...

Please wait, this will only take a moment.

Inquiry
Booth No.
Exhibit Booth