Dept. of Production Systems Engineering

National Institute of Technology, Hakodate College

AI& Deep Learning for New Material Research

研究内容：Name

Kazu-masa YAMADA

StatusDr. Professor, Mr.

Affiliations

E-mailyama@hakodate-ct.ac.jp/ Supervisor for Advanced Course , HNCTDept. of Production Systems Engineering(Dept. of Electrical and Electronic Engineering)

Keywords

Materials science, Iron system materials, molecular dynamics method, diffusion coefficient,information processing materials, amorphous materials, relaxation phenomena

Technical
Support Skills・・・Research Contents

Measurement of the diffusion coefficient of atoms
Numerical processing in Python and deep learning
Fundamentals and applications of materials related to phonon and magnetism

New Material Development and Visualized Atomic Diffusion Studies Using IoT Deep Learning

IoT Deep Learning for New Material Development
3D AVS Player Research on numerical processing for automated video visualization,
especially visualization of atomic diffusion in Iron-based materials by molecular dynamics method

The focus is on information processing of materials science. The convenient 3D AVS Player can play back 4D
animations of AVS/Express and MicroAVS visualization results (viewpoint can be changed during playback), and is beingdeployed in new materials development using IoT deep learning.
The 3D AVS Player is currently available in Japanese, English, and Chinese, and is distributed free of charge inMS-Windows 32-bit and 64-bit versions.
In this study, we apply Python open source libraries to deep learning for new material development, especially forvisualization of atomic diffusion in iron-based materials by molecular dynamics. The data used are not limited tomechanics; a wide variety of data can be used. In addition, we will especially focus on the greatest advantage of moleculardynamics, which is the ability to numerically explore the diffusion coefficient of atoms by the only means available, andapply the results, both quantitatively and qualitatively, especially to atomic diffusion in iron-based materials, to develop
new functions for materials closely related to both optical and magnetic aspects, such as high-density magnetic recording
materials.
The application of visualization techniques to the structural results of the above materials provides a broader
perspective to the discussion of the thermal stability of materials.
The following (left) is a time-tracking and visualization of thermal diffusion of atoms in a multilayer in an iron-basedmaterial, which may lead to new structural and magnetic materials. The following (right) is a time-tracking andvisualization of hydration in a carbon-based material, which is expected to be used, for example, for the application of amechanism to efficiently transport drugs into the body.

Left: An example of Fe multilayer in a 4D movie
in which all atomic positions are calculated fromthe computer and the viewpoint can be changed
flexibly. Right: A time-dependent hydration ina carbon-based graphene material is visualized
and applied, for example, to a mechanism for
efficient drug delivery into the body.
Available Facilities and Equipment
Scientific Plot PDF Creation Software Operating Env.

3D Scientific Diagram Python Operating Environments

4D Movie Automatic Generation Operating Environments

Differential Scanning Material Property , Calorimetry

GMR, Giant type Magneto-Resistance Sensors

Hall-type Giant type Magneto-flow Sensors

Real-time Facial Surface Geometry from Video on GPUs

Real-time Facial Surface Geometry from Monocular Camera

Real-t-Hand/Body Geometry from Monocular Video GPUs

Real-time music acrostic spectrum analyzer from on GPUs