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Kentaro Kutsukake

Nagoya University

Research Interests

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Articles (20)

Collaborators (10)

Yasuyoshi Kurokawa

Kansai University

Keisuke Ohdaira

Japan Advanced Institute of Science and Technology

Tatsuya Yokoi

Nagoya University

Ryoji Katsube

Nagoya University

Xin Liu

Associate Professor

Nagoya University

Yutaka Ohno

Tohoku University

Miho Tagawa

Nagoya University

Atsuhiko Fukuyama

Yuki Tokumoto

The Univeristy of Tokyo

Noritaka Usami

Nagoya University

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Kentaro Kutsukake

Research Interests

Make your next move.

Explore related searches

Articles (20)

Collaborators (10)

Yasuyoshi Kurokawa

Keisuke Ohdaira

Tatsuya Yokoi

Ryoji Katsube

Xin Liu

Yutaka Ohno

Miho Tagawa

Atsuhiko Fukuyama

Yuki Tokumoto

Noritaka Usami

Make your next move.

Kentaro Kutsukake

Research Interests

Make your next move.

Explore related searches

Articles (20)

Bayesian Optimization–Driven Design of Hydrogen Concentration in A-Si/H Multilayers for Silicon Heterojunction Solar Cells

Regression framework incorporating intermediate parameters for improved prediction accuracy in multilayer thin films for silicon heterojunction solar cells with high efficiency

Edge facets and twins in highly impurity-doped Czochralski-Si: A question on twin generation in semiconductors

Transfer of Optimized Crystal-Growth Environments between Different Furnace Configurations via a Latent Space

Dynamic deformation modeling for the interfaces of growth, etching, and deposition under switching flow in TSSG-SiC growth

A design methodology of crystal growth furnace and process aided by two-step optimization using machine learning models and genetic algorithm

Dislocation cluster generation behavior in multicrystalline silicon investigated using twin network analysis

Two‐Stage GAN‐Based Generation of Virtual 3D Multicrystalline Silicon Reproducing Nucleation and Crystal Growth Processes Using Crystallographic Information from Real Ingots

A machine learning approach to reveal microstructures contributing to dislocation clusters in multicrystalline silicon

Stress analysis and dislocation cluster generation in silicon crystal with artificial grain boundaries

Numerical Simulation of the Formation Process of Overhanging Structures in SiC Solution Growth to Suppress Solvent Inclusion

Machine learning-based laser heterodyne photothermal displacement method: simultaneous estimation of silicon thermal diffusivity and carrier lifetime

Effect of Solution Components on Solvent Inclusion in SiC Solution Growth

Multicrystalline informatics: a methodology to advance materials science by unraveling complex phenomena

Multicrystalline Informatics Applied to Multicrystalline Silicon for Unraveling the Microscopic Root Cause of Dislocation Generation

High Passivation Performance of Cat-CVD i-a-Si:H Derived from Bayesian Optimization with Practical Constraints

Feature extraction and spatial imaging of synchrotron radiation X-ray diffraction patterns using unsupervised machine learning

Thermal boundary conductance of artificially and systematically designed grain boundaries of Silicon measured by laser heterodyne photothermal displacement method

Review of machine learning applications for crystal growth research

3D CNN and grad-CAM based visualization for predicting generation of dislocation clusters in multicrystalline silicon

Collaborators (10)

Yasuyoshi Kurokawa

Keisuke Ohdaira

Tatsuya Yokoi

Ryoji Katsube

Xin Liu

Yutaka Ohno

Miho Tagawa

Atsuhiko Fukuyama

Yuki Tokumoto

Noritaka Usami

Make your next move.