My research spans experimental and computational physics, with a focus on thin-film and interfacial materials, advanced materials characterization, structure-property relationships, and scientific data analysis. I am particularly interested in applying these methods to semiconductor materials, thin-film process development, metrology, and materials reliability.
My work combines synchrotron X-ray characterization, scanning electron microscopy (SEM),
computational modeling, statistical analysis, and Python-based automation to understand
how nanoscale structure influences material properties and performance.
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Thin-Film & Interfacial Materials Characterization
- My doctoral research focused on understanding the nanoscale structure and stability of thin-film and interfacial material systems.
- At Argonne National Laboratory's Advanced Photon Source, I worked in cleanroom and controlled laboratory environments while preparing and handling samples for advanced materials characterization.
- I worked with vacuum-based scientific instrumentation and followed established procedures for careful sample handling, contamination awareness, experimental preparation, and measurement reliability.
- I used scanning electron microscopy and advanced X-ray characterization techniques including GIXD, GIXOS, XRD, and XRR to investigate nanoscale structural behavior in thin-film and interfacial material systems.
- I analyzed molecular packing, lattice order, domain size, film thickness, phase transitions, and structural disorder. I also developed Python-based workflows for processing large experimental datasets, peak fitting, extracting structural parameters, and comparing material behavior under different experimental conditions.
- This work provided a strong foundation in cleanroom practices, thin-film metrology, process characterization, experimental troubleshooting, and structure-property analysis, with applications to semiconductor and advanced materials research.
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Computational Materials Science - LaNiO3
- I studied the structural and electronic properties of LaNiO3 using first-principles computational methods.
- Using VASP and Density Functional Theory (DFT+U), I investigated relationships between atomic structure, electronic behavior, and material properties.
- This work developed my experience in electronic-structure calculations, computational materials science, crystal and lattice analysis, Python-based scientific computing, and structure-property relationships.
- These methods are relevant to the study of electronic, oxide, and semiconductor materials.
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Scientific Data Mining & Machine Learning
- I developed a Python-based computational framework to analyze more than 35,000 scientific publications.
- Using Natural Language Processing and Latent Dirichlet Allocation (LDA), I identified emerging research topics and tracked their evolution over time.
- This work resulted in a peer-reviewed publication in Journal of Industrial Ecology.
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Statistical & Computational Physics
- I developed C++ simulations to investigate the structural and statistical behavior of weighted planar stochastic lattices.
- The research involved dynamic scaling, multifractal behavior, statistical mechanics, data collapse, structural disorder, and numerical simulation.
- The work was published in Chaos, Solitons & Fractals.
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Theoretical Physics
- My master's research focused on quantum field theory and the constraint structure of coupled vector and tensor fields.
- This work provided a strong foundation in mathematical physics, analytical modeling, and theoretical problem solving.
Research Interests
• Semiconductor Materials • Cleanroom Processing • Thin-Film Characterization • Materials Metrology • Structure-Property Relationships • Synchrotron X-ray Characterization • Computational Materials Science • Process Development • Scientific Data Analysis • Python Automation