Resources

Useful software tools and online references related to what we do in our lab (Link last updated on April 2024)

Databases and Scripts for Materials, Molecules, and Proteins

• CoRE MOF

• QMOF

• UMOF

• ARC-MOF

• CSD MOF subset

• ToBaCCo MOF

• CURATED-COF

• 2D Zeolite Slabs

• Porous Amorphous Materials

• 2D Perovskites

• OQMD

• NIST JARVIS

• NREL MatDB

• NOMAD

• SMACT

• Materials Cloud

• MaterialsProject

• ZINC15 (dataset for commercially available compounds)

• Surge (molecular-graph based chemical structure generator)

• AlphaFold Protein Structure Database (200 million predicted protein structures)

General Atomistic Simulation Software

• RASPA

• PorousMaterials.jl

• BRICK-CFCMC

• GROMACS

• LAMMPS

• VASP

• CP2K

• Quantum Espresso, QE

• pySCF

• DFTB+ (periodic solids, molecule)

• ORCA

• Gaussian16

• xTB

• xTB-CREST

Visualizer and Editors

• VMD (visualizer for MD trajectories)

• Avogadro (free Molecular Editor and Visualization)

• Gabedit (free GUI for computational chemistry)

• VESTA (free crystal structure visualizer)

• Carbon Dot Builder (carbon dot builder)

• CYLview (Visualization and analysis software for computational chemistry)

• PoreMatMod.jl (code to modify crystal structures)

• Online Molecule File Converter

Workflow Softwares

• AFLOW suite

• AiiDA

• pySIMM (python-based program for polymer simulation)

• polymatic (python-based porous polymer structure generation)

• MosDEF (python-based program for soft matter simulation)

• Ogre (python-based slab model construction)

• MolSimplify (organometallic system construction)

• QE input generator (QE input generator)

• PackMol (prepares input geometry for MD simulations)

• Layerd Materials Setup with GROMACS

• stk: Supramolecular Toolkit

• MAZE (Multiscale Atomistic Zeotype Environment)

Software and Datasets for Adsorption Science

• Zeo++ (high-throughput script for porous materials properties)

• SESAMI (a script to estimate surface areas of materials from their isotherms)

• SESAMI-ML (SESAMI with machine learning implementation to more accurately estimate the monolayer coverage)

• SESAMI-APP (a website for SESAMI tools)

• raw2aif (adsorption information format for standardizing adsorption data)

• pyGAPS (adsorption data analysis and fitting)

• ISAACS (analysis tool for amourphous materials)

• pyIAST (python-based IAST program)

• IAST++ (user-friendly IAST program)

• MOFid (script to identify MOF)

• MOF Adsorbate Initializer (adsorbate initializer for quantum calculations)

• pyIsoP (isotherm prediction based on energy-grids)

• SorbNet (deep neural network for complex binary sorption equilibria)

• pyMOFscreen (script for HT QM screening of MOFs)

• NIST Data Repository for Adsorption Science and Technology

• MemPy (simulation software for gas separation using spiral-wound membrane modules)

• OMS detector (script to detect open metal sites in MOF dataset)

• MAPLE (Machine-assisted Adsorption Process Learner and Emulator)

• BAAM (BATCH ADSORBER ANALOGUE MODEL)

• PSA (MATLAB-based PSA simulation code)

Partial Atomic Charges and Force fields

• TraPPE (force field bench-marked against experimental VLE)

• LAMMPS-Interface (assigns bonded FF parameters for MOFs)

• QuickFF (MOF force field from ab initio data)

• EQeq (Extended Charge Equilibrium method for partial atomic charges)

• EQeq+c (EQeq with correction for high-oxidation-state transition metal atoms)

• DDEC (DFT-derived partial atomic charges)

• REPEAT (DFT-derived partial atomic charges)

• m-CBAC (atom-typing partial atomic charges)

• MPNN Charges (Neural Network-derived partial atomic charges)

• LigParGen (automated OPLS force field parameter generator for small molecules)

• PACMOF (Partial Atomic Charges in Metal-Organic Frameworks (PACMOF) from Machine Learning)

Machine Learning for Materials and Synthesis

• Crystals.ai

• QML (ML for molecules and solids)

• DeepChem

• Chemical VAE (variational autoencoder (VAE) for use with molecular SMILES)

• SynCoFinder (synthesis condition finder using ML)

Crystal Structure Predictions and Analysis

• AIRSS

• CALYPSO

• USPEX

• TopCryst (crystal topology determination)

• ELATE (mechanical properties analysis)

• pyWindow (Cage window size analysis)

• DiffPy (Atomic Structure Analysis in Python)

• CrystalNets.jl (crystal topology analysis tool)

Software and Tools for Electronic Structure Calculations

• kgrid (k-point density calculation from the input geometry for periodic quantum chemistry calculations)

• Setupkpoints (band structure diagram for crystal structure)

• phonopy (python code for phonon calculations)

• WulffPack (python code to create Wulff constructions)

• GPView (visualize orbitals)

• LOBSTER (Crystal Orbital Hamilton Populations)

• CGCNN (Crystal Graph Convolutional Neural Networks)

• VASPKIT (Scrip-based Vasp calculation helper)

• VTST (code to find saddlbe point and evaluate TST rate constant with VASP)

• py4vasp (python interface to VASP outputs)

• CENSO (Sorting program for CREST outputs based on energetics)

• QCxMS (Mass spectra using Born-Oppenheimer MD)

Computational Chemistry Scripts and Tutorials

• Pymatgen

• ASE (tools and Python modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations)

• DFT-book by John Kitchin (density functional theory book)

Python, AI and Scientific Visualization

• ACMM MolSim-2020 (intro to molecular simulation)

• Data Camp (free python tutorial)

• Jupyter (on-line app for Julia, Python)

• Pyomo (optimization language)

• AI Hub

• Scikit-learn

• Data Visualization (data viz info book – recommended by Tyler Josephson, Univ. Maryland - Baltimore County)

Tools for Diagrams, Graphs, Equations

• tikzit (a simple GUI editor for graphs and string diagrams)

• Math (online mathematics editor for fast writing and sharing mathematics)

• Omnigraffle (diagram, rapid-prototype, and design)

• sumoplot (a python script for plotting and analysis for solid-state calculation data)

Machine and Statistical Learning Books

• Mathematics for Machine Learning (math book for ML)

• Computational and Inference Thinking (math book – recommended by Cory M. Simon, Oregon State Univ.)

• Deep Learning for Molecules & Materials (by Andrew White @ Univ. Rochester USA)

MISC

• Markdown Guide

• CSD Access Structure

• Matplotlib Cheatsheet

• LaTex Table Generator

• GROMACS MD Tutorial

• Materials Exchange

• WebPlotDigitizer (extracting data from figure plots)

• KISTI Supercomputing Blog (KSC blog to get started with supercomputing, written in Korean)