Condensed Matter Physicist / Computational Material Scientist
📍 Merced, CA, USA
📧 rafaeldgrande@gmail.com
🔗 LinkedIn | GitHub | Google Scholar

I am deeply interested in condensed matter physics and computational material science. I have experience in computational simulations (DFT, GW/BSE, classical MD, tight binding), and more recently I started learning machine learning methods to be applied in my research.

At UC Merced, I am working with excited-state forces that combine exciton coefficients from GWBSE and electron-phonon interactions from DFPT. I implemented the code that calculates those forces and studied different workflows for excited-state relaxations considering computational cost and precision. Using those forces I am performing the relaxation of excited states, studying self-trapped excitons, polaronic excitons and calculating Huang-Rhys factors at diverse systems such as transition metal dichalcogenides, perovskites and alkyl halides. In the near future I will extend the excited-state forces code to deal with spin-flip BSE and developed deep learning force fields trained with the excited-state forces.

During my PhD I worked with carbon nanomaterials. I studied the shear and layer breathing modes in multilayer graphene and reconstruction in twisted 4 and 6 layer graphene. I also studied the local collapse mechanism in carbon nanotubes and self trapped excitons in carbon nanotubes with sp3 covalent defects.

During my internship at IBM research, I performed classical molecular dynamics simulations of liquid-liquid interfaces with silica nanoparticles and worked on the development of coarse grained models in order to perform simulations at scales closer to experimental data.