Big Data and Quantum Mechanics
Goals
Leverage advances in machine learning and data analytics to enable faster and more accurate calculations of chemical properties using quantum-mechanical techniques such as density functional theory (DFT).
Students will learn about applications of quantum-mechanical simulations in photocatalysis and electrocatalysis, with particular focus on nitrogen fixation and water oxidation. These reactions have the potential to help alleviate global hunger by enabling distributed fertilizer production and helping to provide clean energy based on hydrogen fuel derived from water.
Issues Involved or Addressed
Simulation of molecular and surface systems using DFT calculations on high-performance computing resources; Training and testing of neural network models designed to predict energies of molecular and surface structures; Software development of tools for training, testing, and visualizing machine learning models for molecular systems.
Note: This course does not involve any quantum computing or development of quantum-mechanical theories.
For a detailed overview of topics covered in the training semester, please review the course Jupyter Book via the link below.
Methods and Technologies
- Density Functional Theory
- Automation
- Bayesian Statistics
- Visualization
- Databases
- Neural Networks
- High-performance Computing
- User Interface Design
Majors Sought
Engineering: Chemical and Biomolecular Engineering, Computer Engineering, Materials Science and Engineering
Sciences: Chemistry, Mathematics, Physics, Statistics
Preferred Interests and Preparation
ChBE, Chem, MSE, Physics – Background/interest in quantum mechanics, computational materials science, computational chemistry. Curiosity about machine learning, data science, and big data. Programming skills would be helpful but are not required.
CS, Applied Math, Stats, CSE – Background/interest in machine learning, uncertainty quantification, data-driven methods. Interest in the intersection of machine learning and physics. Programming skills encouraged but not required.
CS – Interest in software architecture, database design, schema-free data models, functional programming, interactive visualization. Programming experience and skills are strongly encouraged.
Advisor
Andrew Medford
Andrew Medford
Andrew.medford@chbe.gatech.edu
Day, Time & Location
Full Team Meeting:
2:00pm-2:50pm Wednesday
BlueJeans
Subteam meetings scheduled after classes begin.