About Me
Nikhil Komalla (Ph.D. Candidate)
With over seven years deeply immersed in the potential of hydrogen energy and catalysis, I am a Ph.D. Candidate at Penn State specializing in Energy & Mineral Engineering with a minor in Computational Materials. My core passion lies in harnessing advanced computational methods—including Density Functional Theory (DFT), Molecular Dynamics (MD), and cutting-edge AI/Machine Learning techniques—to design and discover novel materials for a sustainable energy landscape.
My research targets the heart of green energy challenges, particularly in developing efficient electrocatalysts and photocatalysts. I am enthusiastic about pushing the boundaries of computational materials design to accelerate the transition to cleaner energy systems, with a keen focus on energy materials and advanced functional materials.
Education
Ph.D. in Energy and Mineral Engineering
The Pennsylvania State University, USA (Expected Aug 2026)
Minor: Computational Materials | GPA: 3.54/4.0
B.Tech. in Chemical Engineering
Osmania University, India (May 2021)
GPA: 8.17/10.0
Professional Journey
Graduate Researcher
The Pennsylvania State University, USA (Aug 2022 – Present)
- Designing Fe-Ni Sulfide & SrNb2O6 catalysts for green H2 via DFT (VASP) & METADISE.
- Explored 130+ active sites, mapped diffusion pathways, developed reaction mechanisms.
- Integrating experimental-theoretical approaches for accelerated catalyst discovery.
Graduate Teaching Assistant
The Pennsylvania State University, USA (Aug 2022 – Present)
- Mentored 90+ undergraduates in Thermodynamics & Solar Energy Conversion projects.
Process (R&D) Engineer
Krest Engineering, India (Sep 2021 – Dec 2021)
- Techno-economic analyses for Fuel Cells & Electrolysers; CSP feasibility for DRDO.
- Developed green energy transition roadmaps for Refining/Petrochemical sectors.
Technical Toolkit
Computational Methods
- Density Functional Theory (DFT)
- Molecular Dynamics (MD)
- Quantum Chemistry
- Computational Thermodynamics
Programming & Software
- Python, Matlab
- Scripting, Git
- VASP, Quantum ESPRESSO
- Matlab, Aspen, ANSYS
AI & Machine Learning
- ML Models
- TensorFlow, Keras
- Data Analysis & Visualization
Domain Expertise
- Catalysis
- Hydrogen Technologies
- Electrochemistry
- Materials Science
Research Contributions
Loading publications...
For a comprehensive list, please visit my Google Scholar Profile.
Let's Connect
I'm always open to discussing new research, collaborations, or opportunities in computational materials science and sustainable energy. Feel free to reach out!