It is most likely that I told you to come here, instead you are probably here because I told you to come here to find the information that you need.
Computational Materials Science Bootcamp. These notes have evolved over the years, starting with my personal notes when I got started in the field at the University of Florida to get my PhD, I have updated to train undergraduate and graduate students in the field. It assumes that you do not have experience with a UNIX style environment or programming experience. Since this is a document which I use to train people, it usually reflect the environment that I currently work in.
LaTeX template
DFT and VASP bootcamp
I am currently a postdoc at the Ohio State University. My research area is computational materials, which is the simulation of materials to predict material properties and behavior. Secondarily, I am interested in machine learning topics, although I am getting more acquainted with the field. This is likely a likely a personal topic of discovery for me. My professional background is quite eclectic, since I have had careers in finance, technology, secondary education, and the military. If you want to know more about me, you can check my online curriculum vitae.
I am currently a postdoc at the Ohio State University. My research area is computational materials, which is the simulation of materials to predict material properties and behavior. I have a specific interest in the thermal properties of materials, phonon behavior, material thermodynamics, and transport properties.
Monte Carlo simulation methods for the calculation of computational phase diagrams. (see software package developed for this pymatmc2)
Novel approaches to the development of analytical interatomic potentials (see software package pypospack)
Software for the management of computational resources and processes (see software package mexm)
Verification, validation and uncertainty quantification (VVUQ) of atomistic simulations.
Bridging atomistic level simulations to the mesoscale. I am not an expert here, but any notes contained here are more personal notes.
Unique to computational materials science is the use of specific tools used to calculate material properties and characterize behavior.
Density Functional Theory. The focus of my research has used the code VASP. The notes posted here are primarily apply particularly for VASP code.
Molecular Dynamics. The focus of my research has used the code LAMMPS.
Lattice Dynamics. Lattice dynamics have been analyzed by both using LAMMPS, GULP, and PhonTS.
Previous Projects:
The effect of anion intrinsic defects of Raman spectra on fluorite-structure materials with a particular focus on CaF2, CeO2, and UO2. Since CeO2 and UO2 require DFT+U corrections perturbational methods aren't available to calculate Raman signatures. Instead the derivatives of the polarization tensor is calculated through the application of finite electric fields. DFT+U has the problem of creating metastable states which need to be resolved to find the ground state energy requiring the use of techniques such as occupation matrix control, +U ramping, and annealing. The value of this research for experimental researchers to resolve changes in Raman signatures to particular point defects. For computational scientists, this research will also explore techniques for resolving metastable states to the ground state, particuarly with the application of an electric field to the calculations.
Self-diffusion behavior in niobium carbide (particularly Nb2C). The interest in self-diffusion behavior in Nb2C is driven by the need to create cladding materials that provide an oxygen diffusion behavior in zircalloy cladding materials in nuclear fuel rods. During plant coolant failure, the zirconium oxide layer is no longer passivizing which causes the zirconium alloy to react with water causing the the release of hydrogen gas which is an ignition risk in nuclear power plants.
Verification, Validation, and Uncertainity Quantification in EAM potentials. The purpose of this research is to develop tools and techniques for uncertainty quantification to explore how VVUQ techinques can be used to improve the transparency of the fitting process as well as explore error propagation due to uncertainity in the training set used to fit empirical potentials for molecular dynamics.
I spent the summer of 2014 at Idaho National Laboratory studying ZrSi oxidation behavior with a particular focus on oxygen transport in ZrSiO4 using both molecular dynamics and density functional theory tools to study self-diffusion behavior by particularly looking at possible intrinsic defect (oxygen interstititals and oxygen vacancies) as well as the impact of strain on them.
So I have a couple active software projects in various states of preparation:
projectkoios (Project Koios). One of my interests is small scale cluster computing. In particular, I am working with commodity low voltage computers (e.g. Intel NUC, Raspberry Pi, NVIDIA jetson nano).
mexm-base. (Materials Ex Machina). This is a refactor of my work at the University of Florida (pyflamestk, pypospack), which I am developing as a general toolkit for computational materials simulation.
mexm-cluster. (Materials Ex Machina). This is a rudimentary job-submission manager for SLURM and TORQUE (although the SLURM functionality maybe a little outdated, since my computational clusters are currently SLURM). In addition, I am interested in the possibility of using cloud computing resources (such as Amazon AWS and Google Cloud).
pymatmc2 (python material multi-cell monte carlo). This is computational rewrite of the MC2 code.
pyflamestk. This is software for modelling materials using LAMMPS, DAKOTA, and DFT as computational calculators. It was originally written to support VVUQ and the calculation of Raman spectra, but I hope to write more.
pypospack. This is a refactor of some pyflamestk code to support the development of interatomic potentials.
This section is just links to stuff I want to check out
Automation of band structure (for both phonons and electronic structure calculations)
aflowlib (Setyawan, Curtarolo)
Setyawan, Wahyu, and Stefano Curtarolo. "High-throughput electronic band structure calculations: Challenges and tools." Computational Materials Science 49.2 (2010): 299-312. Link
explore SeeK-path
Y. Hinuma, G. Pizzi, Y. Kumagai, F. Oba, I. Tanaka, Band structure diagram paths based on crystallography, Comp. Mat. Sci. 128, 140 (2017). link
For crystal symmetries (spglib for python)
ragasa_tutorials. This is some personal code which I have written to understand a variety of python software and is presented as a set of programming idioms which may or may not be useful for other people.
https://aws-parallelcluster.readthedocs.io/en/latest/getting_started.html
IBM quantum computing framework
Scala Programming Language: https://scala-lang.org/files/archive/spec/2.12/12-the-scala-standard-library.html
Julia with MPI: http://www.claudiobellei.com/2018/09/30/julia-mpi/