symbolic collective variable definitions and automation of metadynamics
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Updated
Nov 2, 2020 - Python
symbolic collective variable definitions and automation of metadynamics
This repository contains all material related to the project done as a part of the course Computational Systems Biology (BT5240) in the Spring 2020 semester.
Hop.jl has been renamed to HopTB.jl and moved to https://github.com/HopTB/HopTB.jl
A Modern DFT + DMFT Computation Framework
A Julia package that provides operations of a database with pseudopotential datasets
Study of molecular motion of Glycerol using NMR modeling and simulations
VASP input files required to conduct ab initio MD simulation of a short polyurethane chain.
The command-line interface of Express.jl
Provides basic data structures and helpful functions for manipulating structures, generating input files, pre-running error checks, etc.
SHRY (Suite for High-throughput generation of models with atomic substitutions implemented by python) is a tool for generating unique ordered structures corresponding to a given disordered structure.
Python wrappers for TurboRVB
Neural network class for molecular dynamics to predict potential energy, forces and non-adiabatic couplings.
Open-source first-principles computational toolkit for the efficient calculation of the strength of materials in 1D, 2D, and 3D materials at both zero and finite temperatures
Extended DeepH (xDeepH) method for magnetic materials.
Quantum Monte Carlo package, TurboRVB
Tight-binding package written in Julia
Quantum Visualization Interacting Toolkit for Ab-initio Simulations
Sparse Gaussian Process Potentials
A solver for the coupled and decoupled electron and phonon Boltzmann transport equations.
Deep neural networks for density functional theory Hamiltonian.
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