FHI/SG15/PseudoDojo potentials provided for almost all elements of the periodic table, including semi-core potentials for many elements
PseudoDojo and SG15 potentials are fully relativistic
Around 400 LDA/GGA/MGGA exchange-correlation functionals via libXC
Possibility to add custom DFT functionals
MetaGGA SCAN functional for significant improvements for energetics over GGA and LDA
Methods for accurate band gap calculations of semiconductors and insulators
MetaGGA (TB09)
DFT+1/2 method (DFT: LDA, GGA, MetaGGA SCAN)
Shell DFT-1/2 method enabling scripting of GGA-1/2 parameters
Empirical "pseudopotential projector shift" method (parameters provided for Si and Ge)
Hybrid functionals for accurate electronic properties of bulk materials, interfaces and gate stack structures
HSE06, B3LYP, B3LYP5, PBE0
Dielectric dependent hybrid functional HSE06-DDH, based on using improved material-specific and position-dependent fractions of exact exchange, automatically calculated from density
Works for semiconductors, insulators, and metals
Large-scale simulations with modest computational resources: LCAO basis sets enable linear scaling with the system size and number of k-points
2-20X speed-up by using Auxiliary Density Matrix Method (ADMM) to obtain large basis set quality results at small basis sets costs
Van der Waals models (DFT-D2 and DFT-D3) for LDA, GGA and hybrid DFT functionals
Non-collinear, restricted and unrestricted (spin-polarized) calculations
Spin-orbit coupling
Hubbard U term in both LDA and GGA (also spin-dependent)
"Dual", "on-site", and "shell-wise" models
Counterpoise correction for basis set superposition errors (BSSE) for bulk, surface and device (NEGF) configurations
Ghost atoms (vacuum basis sets) for higher accuracy in the description of surfaces and vacancies
FHI/SG15/PseudoDojo potentials provided for almost all elements of the periodic table, including semi-core potentials for many elements
PseudoDojo and SG15 potentials are fully relativistic
Projector-augmented wave (PAW) pseudopotentials
GPAW data set for LDA/GGA
JTH data set for LDA/GGA (includes lanthanides)
Around 400 LDA/GGA/MGGA exchange-correlation functionals via libXC
Possibility to add custom DFT functionals
MetaGGA SCAN functional for significant improvements for energetics over GGA and LDA
Methods for accurate band gap calculations of semiconductors and insulators
MetaGGA (TB09)
Empirical "pseudopotential projector shift" method (parameters provided for Si and Ge)
Hybrid functionals for accurate electronic properties of bulk materials, interfaces and gate stack structures
HSE06, B3LYP, B3LYP5, PBEO (Implemented using the ACE algorithm)
Van der Waals models (DFT-D2 and DFT-D3) for LDA, GGA and hybrid DFT functionals
1D and 3D k·p methods for much faster plane-wave bandstructure, density of states, eigenvalues, and optical spectrum calculations without loss of precision, in particular, with plane-wave HSE
Non-collinear, restricted and unrestricted (spin-polarized) calculations
Spin-orbit coupling
Eigensolvers
Generalized Davidson method – stable and robust method
Universal Force Field (UFF) containing parameters for every element in the periodic table
Bonded DREIDING, OPLS-AA, OPLS-Min and UFF for polymer, battery electrolyte and organic molecule simulations
Automatic potential generation, atom type assignment, and possibility to edit all terms of bonded potentials
Possibility to incorporate partial charges into potentials from different sources, to account for (long-range) electrostatic interactions
These can be calculated to replicate electrostatic interactions from DFT calculations, estimated by QEq or manually assigned
GPU acceleration for organic and oxide potentials (only available in Linux, preview version)
BYOP (Bring Your Own Potential)
Python and GUI interface for adding your own or literature potential of any of the supported types
GUI to easily set up organic force fields (OPLS, UFF, Dreiding) and combine it with inorganic force fields for surfaces and non-particles.
Support for custom combinations of potentials
E.g. combine a Stillinger-Weber potential with a Lennard-Jones term to account for van der Waals interaction
Several such potentials from literature are already provided: Pedone, Guillot-Sator, Marian-Gastreich, Feuston-Garofalini, Matsui, Leinenweber, and more
Machine-Learned Force Fields
Machine-Learned Force Fields, Moment Tensor Potentials (MTPs), calculate interactions (energy, forces, stress) in an atomic configuration at nearly the same accuracy as ab initio (e.g., DFT), but 1,000-10,000 times more efficient
Use Machine-Learned Force Fields (ML-FFs) when no conventional Force Fields exist to describe complex materials accurately and ab initio simulations are too expensive, i.e., for large-scale systems (10,000 – 100,000+ atoms)/long-timescale dynamical simulations:
Realistic structure generation of complex multi-element crystalline and amorphous materials, alloys, interfaces, and multilayer stacks
Multilayer Builder GUI for building high-k metal gate stacks (HKMGs)
Defect and dopant migration barriers
Crystallization and amorphization
Thermal transport
Mechanical properties
Surface processes, such as thermal ALD and ALE
With a given parameter set ML FFs can be used for molecular dynamics/time-stamped force-bias Monte Carlo/geometry optimization like any other QuantumATK force field
Available pre-trained ML FFs in the QuantumATK library:
Bulk crystal and amorphous: Si, SiO2, HfO2, TiN, TiSi, TiNAlO
Crystal/amorphous and amorphous/amorphous interfaces: TiN|AlO, Si|SiO2, SiO2|HfO2, HfO2|TiN, Ag|SiO2, Si|Ti|TiSi
Surface process simulations: HfCl4 depositionon HfO2 surfaces (ALD)
Automated and efficient generation of ML FFs enabling users to develop, systematically improve, and use ML FFs for new materials
Framework for automatically generating training configurations, computing training data with DFT, such as energy, forces, stress, fitting to the training data, validating and optimizing hyperparameters
Active Learning method to improve initial ML FFs by actively adding training configurations and DFT training data during MD simulations
Recommended for amorphous systems, interfaces, systems at high temperatures, surface processes
Automatic ML FFs training tools and GUI templates, ensuring minimal amount of training data and time needed, for:
Possibility to combine ML FFs with conventional FFs, DFT and Semi-empirical methods to include additional interactions and improve overall accuracy in specific applications, such as, for example:
Long-range D3 dispersion correction: can be important for molecules, molecule-solid interfaces, and solid-liquid interfaces
Long-range electrostatic interactions: can help to improve accuracy in the presence of ionic species interacting over large distances beyond the ML FF cutoff
Short-range repulsion: can improve the stability in simulations when atoms come too close to each other
Supports OpenMP and massively-parallel MPI parallelization
Ion Dynamics for LCAO, PlaneWave, Semi Empirical and ForceField
Quasi-Newton LBFGS and FIRE methods for geometry and unit cell optimization (forces and stress)
Quick initial optimization using available force fields
Simultaneous optimization of forces and stress
Optimize structure to specified target stress (hydrostatic or tensor)
Pre/post step hooks for custom on-the-fly analysis
Constant volume optimization
Interrupt a calculation by saving the most recent state
Automatic restart
Geometry optimization of device structures (also under finite source–drain bias)
Computation of dynamical matrix
Compute phonon band structure, DOS, and thermal transport
Compute and visualize phonon vibration modes
Compute the Seebeck coefficient, ZT, and other thermal transport properties by combining ionic and electronic results
Zero-point energy and free lattice energy can be obtained from the PhononDensityOfStates
Analysis object (vibrational free energy in quasi-harmonic approximation of molecules and bulk)
Based on weighting calculated phonon modes, obtaining displacement vectors of the atomic coordinates and displacing atoms accordingly at various temperatures
Calculation of transition states, reaction pathways, and energies
Nudged Elastic Bands (NEB) method
Support for varying cell shape and size, to simulate e.g. phase changes
Alternative to molecular dynamics for long time-scale equilibration, deposition, amorphization, diffusion, sampling of rare events, etc., either at constant temperature with a linear heating/cooling ramp or constant pressure
Possibility to use hooks for customs on-the-fly analysis or custom constraints
Metropolis Monte Carlo Method
Generate realistic fully-coordinated defect-free amorphous/crystalline interface structures using the continuous random network (CRN) method.
Efficiently build high-quality polymer melt or composite structures without long brute-force equilibration MD.
Crosslinking reaction tool for building thermoset polymers which form cross-linked or 3D network structures, as well as rubber-like network structures
Homo- and co-polymers, and polymer blends
Include additive molecules, surfaces, nanoparticles, or any nanostructure
Create your own monomers or use provided monomers from monomer database, add monomers in forward or reverse orientations
Automatic assignment of connectivity tags to define monomer linking reactions
Automatic potential generation for DREIDING, UFF and OPLS-AA
Polymer equilibration methods, such as force-capped-equilibration for initial equilibration, singe-chain mean-field (SCMF) equilibration, energy minimization for relaxing the polymer system, 21 step polymer equilibration automatic workflow
Simulation methods, such as MD in the NVE, NVT and NPT ensembles, time-stamped force-biased Monte Carlo, non-equilibrium momentum exchange for modeling heat transfer in polymer systems, and advanced custom techniques via hook functions
Support for united atoms and coarse-grained polymers to significantly speed up simulations
Analysis tools for plotting end-to-end distances, free-volume, characteristic ratio, molecular order parameters, radius of gyration
Set up and analysis tools to provide atomic-level insight into surface processes and to study the impact of incoming kinetic energy, incident angle, the time between impacts, surface temperature, and thermostat layer thickness
Calculate sputtering yield, sticking coefficient, and precursor coverage needed for feature scale and reactor scale models
Use specifically trained Machine-Learned Force Fields (ML FFs) to efficiently simulate thermal ALD and ALE processes with ab initio accuracy
Available pre-trained ML FF in the QuantumATK library for HfCl4 depositionon HfO2 surfaces (ALD)
Employ a special ML FF training protocol to generate ML FFs for other processes and materials
Flexible and intuitive API to set up custom sequences of events or set up more complex workflows
Hybrid MD/Force-bias Monte Carlo (FBMC) simulations to increase accessible time-scale and enhance equilibration between two deposition events
Poisson Equation Solvers for LCAO, PlaneWave and Semi Empirical
FFT (for periodic systems)
Solvers for systems including metallic/dielectric regions:
Multigrid
Conjugate gradient method (parallelized in memory and execution)
“Direct" solver for large-scale calculations (parallelized in memory)
Non-uniform grid solver for bulk systems and devices with vacuum/dielectrics regions in one or both transverse directions
FFT2D solver for device configurations that have no metallic and dielectric regions.
Metallic gate electrodes and dielectric screening regions
Allows for computation of transistor characteristics (gated structures) as well as charge stability diagrams of single-electron transistors
Multipole expansion for molecules
Dirichlet, von Neumann, or periodic boundary conditions can be specified independently in each direction
Performance Options for LCAO, PlaneWave and Semi Empirical
Consistent use of "best in class" standard libraries/algorithms like Intel MKL, ELPA, PETSc, SLEPc, ZMUMPS and FEAST
Proprietary sparse matrix library
Parallel memory distribution of e.g. the mixing history
Automatic adjustment of number of bands above the Fermi level to include
Multilevel parallelism
Over images in NEB and similarly for other complex tasks
Over k-points
Over basis functions (using multiple processes per k-point)
Also for band structure, DOS etc.
Automatic algorithm to determine the default (optimal) number of processes per k-point
Caching of data for higher memory usage vs. faster performance - or opposite
Use disk space instead of RAM to store grids for Poisson solver
PEXSI solver for O(N) calculations of very large systems (10,000+ atoms in DFT);
Automatic threading intelligence to optimize efficiency when using hybrid MPI/OpenMP parallelization
Electronic Structure Analysis for LCAO, PlaneWave and SemiEmpirical
Band structure
User defined Brillouin zone path through selection of high symmetry points
Fat bandstructure, shows projection onto atoms, spin, orbitals or angular momenta, in any desired combination
Effective bandstructure, i.e. unfolding of bandstructure for alloys and other supercells (no constraints on defect location, defect types, element), option to choose projections
Local bandstructure
Molecular spectrum
One-electron spectrum of molecules
Projected Gamma-point molecular spectrum for periodic systems
Density of states (DOS)
Calculated using the tetrahedron method of Gaussian smearing
Projection onto atoms, spin, orbitals or angular momenta, in any desired combination
Local density of states (can be used to simulate STM images within the Tersoff-Hamann approximation or bulk DOS)
Normalize DOS with respect to volume, area, length or a number of atoms in the cell
Calculation of carrier concentration from DOS and Fermi distribution
Projections of band structure and DOS onto atoms, spin, orbitals or angular momenta, in any desired combination
Mulliken populations of atoms, bonds and orbitals
Real-space 3D grid quantities as Python objects allowing for manipulations, evaluation at points,
Electron density
Partial electron density (simulate STM images within the Tersoff-Hamman approximation)
Effective potential
Full Hartree or Hartree difference potential
Exchange-correlation potential
Full electrostatic or electrostatic difference potential
Electron localization function (ELF)
Molecular orbitals
Bloch functions, complex wavefunction with phase information
A framework for studying the properties of a defect in a host material (formation energies, trap levels, migration paths and energies), by setting up and running all the calculations required for a comprehensive study
Type of defects: vacancies, substitutionals, interstitials, pairs & larger clusters
FNV correction scheme for charged defects with automatic Gaussian model charge fitting
Possibility to include vibrational corrections and modify atomic chemical potentials
Elastic correction to account for the spurious residual stress caused by a defect centre in a finite supercell of the host material
Band gap correction scheme to obtain accurate band gaps for defect trap levels at significantly lower computational cost
Possibility to apply constraints and point defect symmetry to reduce computational cost
Use friendly script generation for linking simulation outputs to TCAD Sentaurus KMC for further defect characterization
Additional Electronic Structure Analysis for LCAO and Semi Empirical
Empirical approach to study various magnetic properties (Heisenberg exchange coupling, exchange stiffness, Curie temperature) at finite temperatures, e.g., to understand phase diagrams, phase transitions, and magnetization dynamics of the magnetic system
Spin life time
At technologically relevant temperatures (>100 K) the spin life time will be limited by electron-phonon interactions, mediated by spin-orbit coupling (Elliot-Yafet mechanism)
Calculate the phonon-limited spin life time from an ElectronPhononCoupling object (if computed with noncollinear spin and spin-orbit coupling)
Gilbert damping for spin dynamics of magnetic systems (with LCAO)
Gilbert damping constant, damping rate, and damping tensor for different life-time broadenings
Based on Kamberskys torque-torque correlation model (Lorentzian)
Raman tensor, phonon mode intensities and polarization dependent or averaged Raman spectra for incoming light scattered in bulk and 2D materials or nanowires
Optical properties, such as refractive indices, extinction coefficients, reflectivity in the THz regime
Infrared spectrum
Includes both, electronic and ionic contributions, i.e., coupling with vibrations for low frequency
Phonon contributions to the results
Vibrational spectra for liquids and amorphous materials above their glass transition temperatures can be also obtained from molecular dynamics trajectory
Total, electronic and ionic tensors, and also ionic part for different modes
Optical spectrum (with LCAO and PlaneWave)
Both contributions, interband and intraband (dominating in metals due to plasmons)
Linear electronic susceptibility, refractive indices, absorption from the Kubo-Greenwood formalism (no ionic contribution)
Second harmonics generation (SHG) susceptibility (with LCAO and PlaneWave)
Spin up/spin down, real, imaginary and absolute values for different tensor components
Polar LO-TO phonon splitting of phonon bandstructure
NEGF for LCAO and Semi Empirical
Non-equilibrium Green's function (NEGF) method for two-probe systems
NEGF description of the electron distribution in the scattering region, with self-energy coupling to two semi-infinite leads (source/drain electrodes)
Open boundary conditions (Dirichlet/Dirichlet, Dirichlet/Neumann or Neumann/Neumann) allows application of finite bias between source and drain for calculation of I-V curve
Includes all spill-in contributions for density and matrix elements
Use of electronic free energy instead of total energy, as appropriate for open systems
Ability to treat two-probe systems with different electrodes (enables studies of single interfaces like metal-semiconductor or p-n junctions, for instance)
Ability to add electrostatic gates for transistor characteristics
Works with LDA, GGA, MGGA (TB09) and hybrid (HSE06, HSE06-DDH) DFT functionals
Surface Green's function method for single surfaces
NEGF description of the surface layers, with self-energy coupling to a semi-infinite substrate (replaces the slab approximation with a more physically correct description of surfaces)
Appropriate boundary conditions for infinite substrate and infinite vacuum above the surface, both for zero and finite applied bias on the surface
Compute surface bandstructure – device density of states evaluated along a k-point route
Works with LDA, GGA, MGGA (TB09) and hybrid (HSE06) DFT functionals
Performance and stability options
Scattering states method for fast contour integration in non-equilibrium (finite bias)
O(N) Green’s function calculation and sparse matrix description of central region
Double or single semi-circle contour integration for maximum stability at finite bias
Ozaki contour integration to capture deep states
Sparse self-energy methods to save memory
Options to store self-energies to disk, either during calculation (instead of RAM) or permanently, to reuse in other calculations
Adaptive (non-regular) k-point integration for transmission coefficients
Parallelization:
Over left/right electrode self-energies
Over contour points (combination of transverse k-points and energy points)
Inside the calculation of each contour point
Minimal Electrode Concept
Reduced electrode - automatically repeated for computing self-energies
Works for electrodes that are pure repetitions in the lateral A and B directions and/or in the transport direction C
Saves time in the electrode calculation which is O(N3)
Set-up and simulation of GB reflection coefficients for a large set of GBs and GB resistivity as a function of average grain size using Mayadas Shatzkes Model
Analysis tools for a large set of different grain boundaries
User-friendly script generation for linking simulation outputs to TCAD Raphael FX for interconnect simulations
Special Features for LCAO, PlaneWave, Semi Empirical and NEGF
Initialization of a new calculation via the self-consistent density matrix of a converged one (with automatic spin realignment)
Initialization of noncollinear spin calculations from collinear or spin-unpolarized ones for improved convergence
Custom initial spin-filling schemes
Odd/even k-point grids (Monkhorst-Pack or edge-to-edge zone filling), Gamma-centered or with custom shifts
Fractional hydrogen pseudopotentials and basis sets (for surface passivation)
Low-level interface to extract Green's function, Hamiltonian, overlap matrices, self-energies, etc.
Delta test module for benchmark of pseudopotential/basis set accuracy
Flexible and customizable verbosity framework to control the level of output to the log files
Electron-Phonon Interaction for LCAO and Semi Empirical
Extract electron-phonon coupling matrix elements
Compute deformation potentials and conductivity/mobility tensors from the Boltzmann equation, with constant, full k-point dependent and/or only energy-dependent relaxation times
Compute Seebeck coefficients and thermoelectric ZT (and underlying first moment and thermal conductance tensors)
Compute Hall coefficient and Hall conductivity tensors
Calculate phonon-limited momentum- and spin lifetimes for different temperatures, broadenings and bands, resolve different phonon modes contributions
Automated workflows for dynamical matrix (D) and Hamiltonian derivatives (dH/dR), with a possibility to utilize a Wigner-Seitz scheme for speeding up calculations of large systems and improving accuracy of calculated dynamical matrix
k-space symmetries of the Brillouin zone (BZ) can be taken into account for the k-point sampling to significantly reduce computational time
Tetrahedron integration method for calculating mobility and resistivity of nontrivial Fermi-surfaces or direct integrations for clever selections of BZ areas
Approximate methods for calculating phonon-limited resistivity: constant mean-free path (for nanostructures) and constant relaxation time method (for bulk), postponing the heavy calculation of the full scattering rate or use known rate from experiments
Thermal velocity of electrons and holes
Multiscale QuantumATK-Sentaurus Device Workflow for 2D FET Engineering
QuantumATK - Sentaurus Device QTX - Sentaurus Device workflow to investigate the impact of various parameters on the 2D material-based FET performance (Id-Vg, Id-Vd, and C-V characteristics)
Different 2D materials and number of layers for channel
Source/drain materials and orientations
Gate stack material parameters
Device architecture and dimensions
Doping concentrations and interface trap distribution
Interactive GUI for setting up and analyzing the workflow results
NanoLab (Graphical User Interface)
Atomic geometry builder for molecules, crystals, nanostructures and devices
1st party plugins for setting up interfaces, multilayer stacks, nanowires, nanoparticles, polycrystals, alloys, cleave surfaces, etc.
Interface builder
Analyze strain for different supercell sizes and crystal rotations
Generate good starting interface geometries quickly using classical force fields
Optimize interface geometry
Multilayer Builder
Automatically build nearly defect-free multilayer stacks of amorphous and crystalline layers of desired thicknesses between these materials: Si, SiO2, HfO2, and TiN for high-k metal gate stack (HKMG) applications
Pre-trained provided Machine-Learned Force Fields (ML FFs) with MD are automatically used to
generate amorphous layers using the melt-quench methodology
anneal and optimize/relax each interface
In order to build multilayer stacks of other materials and stoichiometries, use Python scripting to add layers and the automatic ML FF training workflow to generate ML FFs for these materials
Surface cleaver
Select Miller indices, surface Bravais Lattices and cleavage planes
Create slabs or supercell geometries
Passivation tool for surfaces to remove bonds
Grain boundary builder
Build grain boundaries based on the coincidence site lattice theory, which is used to match the two grains at the grain boundary
Choose between different grain boundary planes and types of grain boundaries (tilt, twist or mixed)
Create bulk or device structures
Device tool for setting up device structures for transport calculations
Add gate electrodes and dielectric screening regions
Dope semiconductors
Molecular builder
Add atoms and build structures through point and click-and-drag interface
Supports cut, copy, paste and unlimited undo
Edit bond lengths, angles and dihedrals
Bonds plug-in for finding, adding or deleting static bonds
Perform quick optimization with classical force fields
Builder plugin for adsorbing molecules to a surface
Define specific sites on the surface where molecules can be attached, at what distance above a surface and orientation
Set a number of molecules either by setting a count or the coverage of sites of the selected site type
Add different molecule types to the same surface
Scripting support to automate adsorption simulations
Nanostructures builders
Icosahedron builder plugin for building icosahedron nanoparticles
Wulff construction tool for building nanoparticles with minimal surface energy
Builders for nanostructures like graphene, nanotubes, nanowires, and nanoparticles
Polycrystalline builder
Builders for amorphous structures
Amorphous pre-builder to create a rough initial guess for an amorphous structure
Packmol builder plugin for creating amorphous configurations
Alloy builders
Special Quasi-random Structures (SQS) algorithm for generating random alloys
SQS uses a genetic algorithm (unlike other codes that perform an open-ended Monte Carlo simulation, which can be very slow)
Supports two-component systems like SixGe1-x or InxGa1-xAs
Any type of geometry, also nanowires etc.
Generic alloy builder
Heusler alloy builder
Substitutional alloy builder
NEB tools
Set up path
Edit images collectively or individually
Pre-optimize NEB path with Image Dependent Pair Potentials (IDPP)
Access interpolation algorithms (LI-LinearInterpolation, HLC-HalgrenLipscomb, and IDDP-ImageDependentPairPotential) in Python scripts for easier automation of NEB path generation
Interactive control of structure, select, edit, move (translate, rotate, align), by atom, fragment, etc.
Symmetry information tool with the option to symmetrize crystal structures based on approximate space groups
Supercells
Import/export of most common atomic-scale modeling file formats (extendable by plugins; embedded version of OpenBabel)
Pre-defined and custom isotopes
Python Console
Provides direct Python access to interact with the configurations in the Builder
Maps (some) operations in the Builder to Python commands
Create pre-defined scripts (”snippets”) to automate repeated tasks
Databases
Internal structure library with several hundred basic molecules and crystal structures
Support for custom, internal databases based on MongoDB or MySQL
Easy setup of calculations, even advanced workflows
Full range of functionality for LCAO, PlaneWave, SemiEmpirical and ForceField
Framework for setting up and submitting a large number of simulations at once for high-throughput material screening
Set up calculations of electronic, optical, thermal, magnetic, mechanical, electron-phonon coupling, piezoelectric, thermoelectric, and other material properties of nanostructures, bulk materials and surfaces
Use specialized interface to set up independent tasks for obtaining I-V characteristics, magnetic anisotropy energy, defect formation energies and transition levels
Set up molecular dynamics simulations using basic ensembles (NVE, NVT, NPT), more advanced stress-strain, thermal transport techniques or surface process simulations (deposition, etching, sputtering)
Use the specialized interface for relaxation of devices and interfaces
Edit input files (Python scripts) using the NanoLab built-in editor
Customizable script generator
Plugin framework for building your own script blocks
Save your calculator (LCAO, PlaneWave, SemiEmpirical, ForceField) settings to a preset file, and reuse it in future calculations or ship them to your colleagues
Save your workflows including analysis objects as templates and reuse them in future calculations or ship them to your colleagues
Editor
Search-and-replace
Syntax highlighting
Python code completion
Select font
Job Manager
Submit and run multiple jobs from the GUI in serial, using threading, and in parallel using MPI, or OpenMP and MPI together
Edit job settings on the fly, on (re)submit
Advanced machine setup enabling good control of MPIs vs threading and setting maximum number of jobs per queue
Submit jobs from the GUI to local machines
Submit jobs from the GUI to remote machines
A variety of queue types: Torque/PBS, PBSPro, LSF, SLURM, SGE, and direct execution (no queue)
Additional queue types can be added by plugins
Requires only SSH access from client to server (no server-side daemon is required, all is controlled by the client)
Automatically copies input and output files to/from remote resources
Built-in SSH key generation and transfer to remote host (no need of 3rd party programs)
Diagnostics tool checks that added machine settings are correct
Overview currently running tasks for easier control of running jobs
Viewer for 3D data
High-performance shader-based rendering engine for very large data sets (1M+ atoms and bonds)
Isosurfaces, isolines, and contour plots, with graphical repetition and data range control
Control atom color, size, transparency, etc.
Color atoms by computed quantities, like forces, velocities and by molecules
Also works in movies, e.g. MD trajectories
Polyhedral rendering of crystals
Voxel plot (point cloud) rendering of 3D grids
Vector field plots
3D extrusion of contour plans
3D scene camera and lighting control
Brillouin zone explorer
Export images in most common graphical formats
Export (and import) CUBE or simple xyz data files for external plotting
Export movies of MD trajectories, phonon vibrations, NEB paths, etc
Auto-rotated views can be exported as animated GIFs
Interactive 3D measurement tool for distances and angles
2D plot framework
Perform advanced editing of plots, such as changing color, line width, etc. of multiple items (several bands for instance) at once, changing title axes, legend, etc., editing grid layout, and adding annotations like arrows and labels
Use dual axes: logarithmic and linear scale, and color code the data to match the particular axis
Save customized plots for further analysis and reuse plot setups with new data
Link and combine plots, e.g. band structure and DOS, for more insightful analysis
Fit data to linear and other models, apply smooth rolling or macroscopic averaging transform lines, adjust plot data range for analysis and measure directly in graphs
Plot quantities along with the animation using a movie tool
Data Plot plugin to easily plot chosen physical quantities and measurements
Export plot data to text and import data from a text file to visualize imported data
Manipulate plots in scripts, build your own custom plots (Plot Framework API), and apply the same plot settings to multiple calculations
Overview all data in a project, or focus on particular subsets, then combine data sets from different files for advanced analysis
Easily transfer projects between computers, or share with other users
Report generator tool high-throughput material screening
Extract selected data from multiple calculations and perform analysis by expecting data in a table, grouping results, and visualizing extracted data
Create and reuse research protocols, i.e. collection of predefined measurements with visualization, to save time when analyzing data from multiple sets of simulations
Save results (in hdf5, csv or excel format) after extracting data
GUI interface to external simulation engines
Generate input files and plot some of the data obtained with VASP, QuantumESPRESSO, GPAW, Orca, and LAMMPS
Import/export structures in external file formats
Write addons and plugins in Python using our API to add new functionality to NanoLab
Python Scripting and Automatization
QuantumATK is based on Python
Python Scripting is the component that binds all the calculators together in a common interface and allows them to synergistically work together
All input scripts for setting up simulations use native Python commands together with QuantumATK Python functions
Write your own custom scripts in Python or edit the scripts created with the NanoLab GUI Scripter
Can run in an interactive mode and in a batch mode
QuantumATK Python functions for:
Structure generation
Define molecule, bulk, surface and device geometries
Define Bravais lattices
Build special geometries like nanowires, graphene sheets, nanotubes
Reproduce workflows from the NanoLab builder using builder Python commands
Add new features to the Builder (anything from simple operations to fully interactive widgets)
Simulation Setup
Define simulation setup for QuantumATK DFT-LCAO, DFT-PlaneWave, Semi-empirical or ForceField
Define workflows which combine simulation engines
Add post or pre-hooks to Molecular Dynamics simulations, thereby tailoring the MD simulation algorithm
Post Analysis
Automate analysis and plotting
Access internal QuantumATK variables for specialized analyses
Add new data analysis capabilities and plot types
Batch processing of analyses
Combined analysis of different simulations
Write addons and plugins in Python, using our API, to add new functionality to NanoLab
There are more than 400 QuantumATK classes and functions available to the user, see list here
Add-on manager for installing plugins written by Synopsys QuantumATK team or users
Variables are defined with physical units and QuantumATK allows for conversion between different units
A variety of Physical Constants available
3rd party Python modules available from atk python
Platform Support
Self-contained binary installer - no compilation needed, no external library dependencies beyond standard operating system packages
Provides a complete Python environment with precompiled optimized libraries like numpy/scipy/ScaLAPACK (based on MKL), matplotlib/pylab, MPI4Py, SSL bindings, Qt/PyQt, etc.
Parallelization (Windows/Linux)
QuantumATK is compiled against Intel MPI and the Intel Math Kernel Library (MKL) which in combination automatically provide an optimized balance between OpenMP threading and MPI
Intel MPI is included in the shipment
Support for MPICH2/MPICH3 (Ethernet), MVAPICH2 (Infiniband), and other MPICH-compatible libraries
Floating license system (SCL from Synopsys)
Learn more about QuantumATK products
Interested in applying QuantumATK software to your research? Test our software or contact us at [email protected] to get more information on QuantumATK platform for atomic-scale modeling.