Research
Research Interests
Machine Learning-Driven Materials Discovery for Energy and Biomedical Applications
- Design of Active Learning Workflow and Algorithm
- Programming and Analyzing Machine Learning Models
- Training Dataset Generation by Experimentation and Theoretical Calculation
- Materials Synthesis, Structural and Electrochemical Characterizations
- Machine Learning Model Training and Screening
- Statistical Analysis for Model Predictions
- Experimental Validation of the Best-Performing Materials Predicted by Machine Learning
- Applications in Catalysis, Batteries, Biomedicine, and Beyond!
Research Expertise
Machine Learning-Driven Materials Discovery
- Design of Closed-loop Protocol and Active Learning Strategy
- Programming Deep Learning Models (Graph Neural Networks, Computer Vision, Natural Language Processing)
- Programming and Analyzing Models (Bayesian Optimization, Model Uncertainty Quantification)
- Generation of Model Training Datasets via Own Experimentation
- Explainable Artificial Intelligence (Shapley Additive Explanations, Feature Importance Analysis)
- Visualization of Exploring Chemical Spaces (t-distributed Stochastic Neighbor Embedding)
Synthesis of Inorganic Functional Materials
- Synthesis of Inorganic Bulk/Nanomaterials (Sol-Gel, Solid-State, Wet Impregnation, Hydrothermal, Heat-Up)
- Synthesis of Metal Oxides (High-Entropy Oxides, Multi-Metallic Perovskite, Spinel, and Rutile Oxides)
- Synthesis of Metal Halides (Lithium Metal Halides)
- Synthesis of Metal Alloys (Platinum-Group-Metal Alloys, High-Entropy Alloys)
- Synthesis of Single-Atom Catalysts (M−N−C Materials, Single-Atom Catalysts on Oxides)
- Synthesis of Metal-Organic-Frameworks
- Controlling Defect of Nanomaterials (Metal Oxides, M−N−C Materials)
- Surface and Bulk Modification of Nanomaterials (Facet Control, Composition and Phase Tuning)
Structural Characterization of Nanomaterials
- Analyzing Geometric and Electronic Structure of Nanomaterials
- Discovering Structure-Property Relationships using Machine Learning and Statistics
- Synchrotron-based X-ray Characterization Techniques
Electrochemical Characterization of Nanomaterials
- Catalytic Performance Measurements for Electrochemical Reactions (Activity, Stability)
- Setting-Up Half-Cell and Single-Cell Devices
- Analysis of Material Structure Changes Before and After Reactions
Applications of Nanomaterials in Energy Applications
- Electrochemical and Photochemical Catalysis (Oxygen Evolution, Hydrogen Evolution, Oxygen Reduction, CO2 Reduction)
- Batteries (Electrolytes for All-Solid-State Batteries, Cathode Materials for Lithium-Ion and Sodium-Ion Batteries, Anode-Free Batteries)
- Biomedicine (mRNA Delivery using Nanoparticles)
Technical Skills (Self-Operating)
Machine Learning
- Design of Materials Discovery Protocols
- Python Programming (Keras, PyTorch)
- Model Construction and Analysis (Graph Neural Network, Convolutional Neural Network, Recurrent Neural Network, Reinforcement Learning, Random Forest, Gaussian)
- Text Mining (Natural Language Processing, Term Frequency-Inverse Document Frequency)
- Explainable Chatbot Development (GPT-4.1, FAISS)
Synthesis and Structural Characterization
- Various Techniques for Inorganic Functional Materials Synthesis (Sol-Gel, Solid-State, Wet Impregnation, Hydrothermal, Heat-Up Process)
- Air-free Schlenk Techniques for Inorganic Functional Materials Synthesis
- Glove Box Techniques for Inorganic Functional Materials Synthesis
- Ball Milling Techniques for Inorganic Functional Materials Synthesis
- Transmission Electron Microscope (JEOL JEM-2020, JEM-2100)
- Synchrotron X-ray Absorption Spectroscopy
- UV-Vis Spectrophotometer
- BET analysis (Micromeritics)
- X-ray Photoelectron Spectroscopy
- Powder X-Ray Diffraction (Rigaku D/Max-3C)
Electrochemical Characterization
- Setting-Up Devices (PGSTAT302N)
- Catalyst Ink Preparation and Electrolyte Purification
- Catalytic Activity and Stability Measurements (Oxygen Evolution, Hydrogen Evolution, Oxygen Reduction)
- Conductivity Measurements (Electrolytes for All-Solid-State Batteries)