팝업레이어 알림

 연구실 인턴십


 MII 연구실의 인턴십 프로그램에 관심이 있으신 분께서는 

 아래 이메일을 통해 교수님께 직접 문의하시기 바랍니다.

 인턴십은 온라인으로 진행되며, 기간은 3개월입니다.


 If you are interested in participating in an internship at this 

 laboratory, please contact the professor via the email 

 address below. The internship will be conducted online 

 for a period of 3 months.



 Email Address: seungbum@kaist.ac.kr

  • Materials Imaging & Integration

  • We are the masters of “structure-property relationship” via materials imaging and
    the innovators of “materials design” via materials integration.

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Materials Imaging & Integration

APPLICATIONS

  • Battery
    Electro-mechanical Analysis
    and Characterization
  • Memory
    Piezoelectrics and
    Ferroelectrics
  • Bio
    Structural and
    Functional Biomaterials
Materials Imaging & Integration

TOOLS

  • AI/ML
    Materials Informatics
  • AFM
    Imaging and
    Property Analysis
  • Synthesis
    Processing and
    Optimization
Materials Imaging & Integration

TOOLS

  • AI/ML
    Materials Informatics
  • AFM
    Imaging and
    Property Analysis
  • Synthesis
    Processing and
    Optimization
Materials Imaging & Integration

APPLICATIONS

  • Battery
    Electro-mechanical Analysis
    and Characterization
  • Memory
    Piezoelectrics and
    Ferroelectrics
  • Bio
    Structural and
    Functional Biomaterials

Project

  • 1On-going

    일자리 창출을 위한 뉴제너레이션 지역특화형 산학연협력 모형 개발 및 확산에 관한 연구 : 공공기술 기반 기술사업화와 창업을 중심으로

    2021.09.01~2024.12.31

  • 1On-going

    차세대 배터리(Na-ion 배터리) 개발을 위한 초민감소재 분석기법 고도화

    2024.03.01~2025.02.28

  • 1On-going

    다각도-멀티스케일 데이터 융합형 리튬이차전지 설계 인공지능 플랫폼 개발

    2023.04.01~2027.12.31

  • 1On-going

    다중모드 원자간력 현미경 이미징 기반 반응 맞춤형 전극 표면의 젖음성 및 표면 에너지 분석 기술 개발

    2023.07.29~2024.07.28

  • 1On-going

    반도체-이차전지 인터페이싱 분석 및 평가 플랫폼 기술개발

    2023.01.01~2027.12.31

Gallery

  • 2025.05.12 Advanced Materials Editor Visit

    2025.05.19

Lab Video

VIEM
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Materials Imaging & Integration

publication

  • 6Selected Publications

    Uncertainty-Quantified Primary Particle Size Prediction in Li-Rich NCM Materials via Machine Learning and Chemistry-Aware Imputation

  • 6Selected Publications

    Lateral Piezoelectricity of Alzheimer's Aβ Aggregates

  • 6Selected Publications

    Unveiling the Nanoscale Dielectric Gap and Its Influence on Ferroelectric Polarization Switching in Scanning Probe Microscopy

  • 6Selected Publications

    Switchable tribology of ferroelectrics

  • 6Selected Publications

    Composition and state prediction of lithium-ion cathode via convolutional neural network trained on scanning electron microscopy images

  • 6Selected Publications

    Spatially Uniform Lithiation Enabled by Single-Walled Carbon Nanotubes

  • 6Selected Publications

    Machine learning assisted synthesis of lithium-ion batteries cathode materials

  • 6Selected Publications

    Segmentation of experimental datasets via convolutional neural networks trained on phase field simulations

  • 6Selected Publications

    Reducing Time to Discovery: Materials and Molecular Modeling

  • 6Selected Publications

    Breaking the elastic limit of piezoelectric ceramics using nanostructures: A case study using ZnO

  • 6Selected Publications

    Intrinsically stretchable multi-functional fiber with energy harvesting and strain sensing capability

  • 6Selected Publications

    Room-temperature relaxor ferroelectricity and photovoltaic effects in tin titanate directly deposited on Si substrate

  • 6Selected Publications

    Flexible Ferroelectric Organic Crystals

  • 6Selected Publications

    Screening Mechanisms at Polar Oxide Heterointerfaces

  • 6Selected Publications

    Enhancement of Local Piezoresponse in Polymer Ferroelectrics via Nanoscale Control of Microstructure

  • 6Selected Publications

    Charge gradient microscopy

  • 6Selected Publications

    X-ray Irradiation Induced Reversible Resistance Change in Pt/TiO2/Pt Cells

  • 6Selected Publications

    High Resolution Field Effect Sensing of Ferroelectric Charges

  • 6Selected Publications

    Principle of Ferroelectric Domain Imaging using Atomic Force Microscope