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openprotein

A PyTorch framework for prediction of tertiary protein structure

optical-modeling

Optical Modeling (Transfer Matrix): Modeling the light propogation, light absorption, transmission, and reflection in a multi-layer thin-film stack and current in solar cells.

p4vasp

p4vasp, the VASP Visualization Tool

pdielec

PDielec is a Python package for post-processing solid state QM and MM calculations of Infrared Spectra

phasefield

PRISMS Finite Element Phase Field Code

phono3py

A simulation package of phonon-phonon interaction related properties

phonolammps

LAMMPS interface for phonon calculations using phonopy

phonon_bandplot

This script would fix the band ordering problem in phonopy-bandplot.

phonons

A collection of structures, force constants and phonon data obtained from first-principles calculations

phonopy

Phonon code

phonopy-spectroscopy

A collection of tools for simulating vibrational spectra, which interfaces with the Phonopy package.

photonic-radiative-cooler

Data files and Matlab codes for analyzing a multilayer thin-film photonic radiative cooler

plasticity

PRISMS Crystal Plasticity and Continuum Plasticity FEM code

preisach_model_matlab

prophet

PROPhet is a code to integrate machine learning techniques with first-principles quantum chemistry approaches

prospr

ProSPr: Protein Structure Prediction

pulse

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

pyband

band plot using python matplotlib

pycp2k

Python Cp2k interface

pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project.

pymatgen-db

Pymatgen-db provides an addon to the Python Materials Genomics (pymatgen) library (https://pypi.python.org/pypi/pymatgen) that allows the creation of Materials Project-style databases for management of materials data.

pyprism

A framework for conducting polymer reference interaction site model (PRISM) calculations

pyprocar

A python package for analyzing PROCAR files obtained from VASP and Abinit

q-e_schrodinger

Quantum ESPRESSO package for integration into Schrödinger’s Materials Science Suite

qe-tddft

Time-Dependent Density Functional Theory Integration Schemes

qstem

STEM/TEM/Coherent CBED image simulations

random-exchange-atoms

In this package, you can exchange atoms in crystal structures randomly with pymatgen.

revealing-ferroelectric-switching-character-using-deep-recurrent-neural-networks

The ability to manipulate domains and domain walls underpins function in a range of next-generation applications of ferroelectrics. While there have been demonstrations of controlled nanoscale manipulation of domain structures to drive emergent properties, such approaches lack an internal feedback loop required for automation. Here, using a deep sequence-to-sequence autoencoder we automate the extraction of features of nanoscale ferroelectric switching from multichannel hyperspectral band-excitation piezoresponse force microscopy of tensile-strained PbZr0.2Ti0.8O3 with a hierarchical domain structure. Using this approach, we identify characteristic behavior in the piezoresponse and cantilever resonance hysteresis loops, which allows for the classification and quantification of nanoscale-switching mechanisms. Specifically, we are able to identify elastic hardening events which are associated with the nucleation and growth of charged domain walls. This work demonstrates the efficacy of unsupervised neural networks in learning features of the physical response of a material from nanoscale multichannel hyperspectral imagery and provides new capabilities in leveraging multimodal in operando spectroscopies and automated control for the manipulation of nanoscale structures in materials.

rvasp

Tools for loading, manipulating and plotting VASP files within R

scriptsforvasp

Making life easier using scripting languages (Bash and Python) to facilitate multiple VASP simulation jobs preparation, submission and analysis.