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Microstructure Control Lab
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The lab predicts the microstructure of materials through computation and creates it exactly as intended.
AboutAbout the lab
Controlling nano- and microscale microstructures through computation.
The Microstructure Control Lab aims to create materials with excellent properties by controlling the nano- and microscale microstructures that make up metallic materials.
To bring out the properties of a metal, the microstructure must be shaped as intended during processes such as solidification, precipitation, and grain growth.
The lab's main approach is computational materials science, combined with theory, experiments, and data science.
By advancing the science of microstructure, the lab works toward developing new high-quality, high-performance materials.
Key terms
- Microstructure
- The fine structure, invisible to the naked eye, formed by crystal grains and precipitates inside a metal
- Solidification
- The process in which molten, liquid metal cools and becomes solid
- Molecular dynamics
- A method that calculates the motion of each individual atom to study the behavior of matter
NewsLab news
A master's student received an Outstanding Presentation Award at the Joint Winter Meeting of the Hokkaido Branches of the Japan Institute of Metals and related societies
A student received the Aragane Award at the graduation thesis presentations of the Applied Materials Engineering Course
A master's student received a Silver Poster Award at the international conference CMSTF2023
ResearchResearch themes
The lab aims to create materials with excellent properties by controlling the nano- and microscale microstructures that make up metallic materials. Using computational materials science as its main approach, together with theory, experiments, and data science, it works to advance the science of microstructure.
*Illustrative imageMicrostructure simulation
To predict and freely control the microstructures that form in metal manufacturing processes, the lab investigates how microstructures evolve using mathematical models and computer simulation. Targets include dendrite growth during solidification and precipitation during heat treatment.
*Illustrative imageEstimating parameters with data assimilation
The lab estimates the input values that simulations require using data assimilation, a data science method. From only a cooling curve measured in the mold, it can estimate how heat is transferred between the molten metal and the mold.
*Illustrative imageFaster, more accurate macrosegregation calculations
To reduce the large compositional variations that form in ingots, the lab improves the accuracy and speed of simulations. It incorporates microscale segregation behavior using machine learning and speeds up flow calculations with the lattice Boltzmann method.
*Illustrative imageSeeing from the atomic level with molecular dynamics
To understand atomic-level details that microstructure simulations cannot handle, the lab calculates the motion of atoms using molecular dynamics. Its work includes calculating the physical properties of solid-liquid interfaces and analyzing how nuclei form.
MembersFaculty
The members of the Microstructure Control Lab are faculty, master's and undergraduate students, and administrative assistants.As of 2026
- ProfessorMunekazu Ohno
- Assistant ProfessorGeunwoo Kim
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Crystal dendrides - 02” Ivan Bachev / CC BY 4.0 (cropped)
- Microstructure simulation: “Pleiades two row” NASA Ames Research Center / Public domain (cropped)
- Estimating parameters with data assimilation: “Huta Pokój walcownia 2019 (2)” Adrian Tync / CC BY-SA 4.0 (cropped)
- Faster, more accurate macrosegregation calculations: “Continuous casting die” Swoolverton / CC BY-SA 3.0 (cropped)
- Seeing from the atomic level with molecular dynamics: “Close-packed spheres” Greg L / CC BY-SA 3.0 (cropped)
- Related lab (Strength System Design Lab): “Turbine blade with wax pattern” Olivier Cleynen / CC BY-SA 3.0 (cropped)
- Related lab (Condensed Matter Physics Engineering Lab): “CdTe quantum dots” Ruslan.Ka / CC BY 4.0 (cropped)
- Related lab (Optical Quantum Physics Lab): “532nm” Netweb01 / CC BY-SA 3.0 (cropped)
- Related lab (Multiscale Functional Integration Lab): “Scanning transmission electron microscopy la07sr03mno” Magnunor / CC BY-SA 4.0 (cropped)
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