At SUNCAT we develop software infrastructure for storing, retrieving and analyzing electronic structure to be used for modeling heterogeneous catalysis reactions. Through the web application CatApp we give web users access to reaction energies and barrieres for surface chemical properties and through CatMAP we provide a framework for microkinetic modeling of catalytic reations integrated with trend studies.

We work on systematic development of exchange correlation functionals for chemical and materials properties relevant in heterogeneous catalysis. Our particular focus for the functional development is moving towards including error estimates in density functional theory, which we have established in the BEEF family of functionals. In our work on improved accurate methods we particular focus on parallelizing the random phase approximation in GPAW on graphical processing units. We also work on non-equilibrium Green's function transport, especially in relation to thermionic emission which we have implemented in the VASP code. All our developments in electronic structure theory is provided through the open-source atomic simulation environment ASE.

For analysis of the atomic scale properties we rely on a number of state-of-the-art electronic structure codes such as GPAW, Quantum Espresso, FHI-aims and VASP, all of which we utilize through the ASE interface.


CatApp is an web application that provides public access to DFT-calculated reaction and activation energies. See the page under outreach: CatApp


Descriptor based analysis is a powerful tool for understanding the trends across various catalysts. The "catmap" Python module seeks to standardize and automate many of the mathematical routines necessary to move from "descriptor space" to reaction rates. The module is designed to be both flexible and powerful.
See more at the CatMAP Github page

Bayesian Error Estimation Functionals

Electronic structure calculations with the Bayesian Error Estimation Functional (BEEF)can be performed using several DFT codes as described below. Error estimates can be obtained with the help of the Atomic Simulation environment (ASE) or using the stand-alone solution in libbeef. The latest version of libbeef can be obtained via:

svn co svn:// beef

and installation is performed using:

./configure [options] 
make install

The DFT codes Quantum Espresso and VASP can be linked against libbeef. For Quantum Espresso, a patched version is available:

svn co --username anonymous

and linking against libbeef is enabled via

./configure BEEF_LIBS="-Lpathtolibbeef -lbeef" [furtheroptions]

The BEEF-vdW functional can then be used by setting input_dft='BEEF'. Error estimates are calculated when in addition ensemble_energies=.true. is set in the &SYSTEM section. For VASP, use version 5.3.5 or later and add -Dlibbeef to CPP and -Lpathtolibbeef -lbeef to LIB in VASP's makefile. To use the BEEF functional, set


in the INCAR file, and add


to calculate error estimates. The error estimates are meaningful for total energy differences and are calculated using the bee utility included with libbeef. To calculate, e.g., the estimated error on the binding energy of H2 one would run:


(for Quantum Espresso, use the corresponding standard output files instead of OUTCAR). The bee utility accepts an arbitrary number of reactants and products, where the factors how to scale the corresponding total energies and the output files have to be specified. Use negative numbers for either reactants or products. For using the BEEF functional in combination with ASE and GPAW, obtain the latest version of GPAW and follow the instructions provided here: Quantum Espresso/BEEF can also be used in combination with the ASE; instructions are provided here:


The Atomic Simulation Environment (ASE) is the common part of the simulation tools developed at CAMd, Technical University of Denmark. ASE provides Python modules for manipulating atoms, analyzing simulations, visualization etc. At SUNCAT we use ASE as our high level simulation environment as a common interface to all the electronic structure codes and to integrate ionic dynamics and optimization. See more here


GPAW is a density-functional theory (DFT) Python code based on the projector-augmented wave (PAW) method and the atomic simulation environment (ASE). It uses real-space uniform grids and multigrid methods or atom-centered basis-functions. At SUNCAT we use GPAW for large systems and as our development code. See more here

Quantum Espresso

Quantum Espresso is an integrated suite of Open-Source computer codes for electronic-structure calculations and materials modeling at the nanoscale. It is based on density-functional theory, plane waves, and pseudopotentials. At SUNCAT we use Quantum Espresso as our primary production code. See more here


Fritz Haber Institute aims is an accurate all-electron, full-potential electronic structure code package for computational materials science. At SUNCAT we use the aims code for detailed electronic structure analysis of small systems and for benchmarking of materials properties. See more here


The Vienna Ab initio Simulation Package (VASP) is a computer program for atomic scale materials modelling, e.g. electronic structure calculations and quantum-mechanical molecular dynamics, from first principles. At SUNCAT we use VASP primarily for testing Bayesian Error Estimation Functionals for extended systems. See more here