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| ONETEP | |
|---|---|
| Name | ONETEP |
| Developer | University of Cambridge; The University of York; University of Nottingham |
| Released | 2009 |
| Programming language | Fortran, C |
| Operating system | Linux, macOS |
| Genre | Computational chemistry, Materials science |
| License | Proprietary / academic |
ONETEP is a linear-scaling electronic structure package designed for large-scale ab initio simulations of molecules, solids and nanostructures. It targets systems with thousands of atoms by combining density functional theory with localized, variationally optimized orbitals and systematic basis sets, enabling calculations that bridge between detailed quantum chemistry methods and large-scale materials modeling. The project emerged from collaborations among researchers at University of Cambridge, University of York, and University of Nottingham, and has been applied in studies related to surfaces, biomolecules, nanoclusters, and defects.
ONETEP implements a linear-scaling formulation of Kohn–Sham equations within density functional theory frameworks developed for periodic and aperiodic systems. The code emphasizes systematic convergence of total energies and forces via a basis of localized nonorthogonal generalized Wannier functions optimized in situ, aiming to combine the accuracy associated with plane-wave methods used at Culham Centre for Fusion Energy and Diamond Light Source with computational costs more typical of localized-basis packages used at Oak Ridge National Laboratory and Lawrence Berkeley National Laboratory. Its methodology connects to foundational work by Walter Kohn and later implementations by researchers at Harwell and groups associated with Max Planck Society.
The theoretical foundation rests on linear-scaling (O(N)) algorithms that exploit electronic nearsightedness for systems with a band gap, building on concepts introduced by Niels Bohr and formalized by Walter Kohn and Lars Onsager-adjacent literature. ONETEP represents the single-particle density matrix using a separable form composed of localized, nonorthogonal generalized Wannier functions and a sparse density kernel, analogous to strategies used in codes developed at SIESTA-related groups and contrasted with plane-wave approaches at VASP and CASTEP. The basis employs psinc functions, which are closely related to plane-wave expansions and provide systematic convergence similar to techniques employed at CERN in computational materials efforts. Variational optimization of both the localized orbitals and the kernel is performed under constraints to maintain idempotency and electron number, integrating techniques from constrained optimization research at University of Oxford and matrix purification approaches used in high-performance libraries at Argonne National Laboratory.
ONETEP is implemented in high-performance Fortran with performance-critical sections in C, and leverages parallelization strategies compatible with message-passing standards developed at Los Alamos National Laboratory and Argonne National Laboratory. Key features include systematic basis control via kinetic energy cutoff parameters analogous to plane-wave codes used at Brookhaven National Laboratory, support for norm-conserving pseudopotentials similar to those from projects at PSI (Swiss research groups), and linear-scaling exact exchange and dispersion-correction modules informed by methods advanced at Kolya Sleny-adjacent theoretical groups. ONETEP interfaces with pseudopotential libraries and can perform geometry optimization and molecular dynamics for extended systems, using thermostats and algorithms related to approaches developed at Princeton University and California Institute of Technology.
Benchmark studies demonstrate ONETEP's capability to treat systems with thousands of atoms with favorable scaling compared to conventional cubic-scaling plane-wave codes such as VASP and Quantum ESPRESSO. Comparative performance assessments have been conducted on high-performance computing platforms at ARCHER and PRACE-hosted facilities, and reported speed and memory advantages for insulating systems with localized electronic structure—benchmarks that echo scaling improvements reported by teams at IBM Research and Cray Research. Accuracy benchmarks against all-electron methods and hybrid functional calculations reference validation efforts similar to those performed at Los Alamos National Laboratory and Harvard University, highlighting systematic convergence of total energies, forces and band gaps when increasing the psinc kinetic energy cutoff.
ONETEP has been applied across a wide range of problems in Materials science and Computational chemistry including studies of semiconductor nanocrystals investigated in collaborations with researchers at Bell Labs and NREL, surface and defect energetics relevant to work at MIT and ETH Zurich, adsorption on catalysts related to investigations at Imperial College London and Max Planck Institute for Chemical Physics of Solids, and biomolecular electronic structure problems tied to projects at European Molecular Biology Laboratory and Wellcome Sanger Institute. Specific applications include modeling charge transfer in organic photovoltaics similar to research at University of Cambridge Materials Science Department, investigation of point defects in oxides in the spirit of studies from Oak Ridge National Laboratory, and exploration of van der Waals interactions in layered materials as pursued by groups at University of Manchester.
ONETEP's development is rooted in academic research initiatives funded by agencies such as Engineering and Physical Sciences Research Council, with contributions from researchers affiliated with University of Cambridge and partner institutions. The code follows a mixed licensing model oriented toward academic use, with access arrangements coordinated through collaboration agreements similar to distribution practices at European research consortia. Development practices incorporate version control and testing frameworks inspired by workflows at GitHub-hosted scientific projects and continuous integration paradigms used at Lawrence Livermore National Laboratory.
The user base comprises academic groups in computational materials and theoretical chemistry across institutions including University of Oxford, University of Cambridge, University College London, University of York, University of Nottingham, and international collaborators at Max Planck Society and Lawrence Berkeley National Laboratory. Training and dissemination have occurred via workshops and tutorials analogous to events hosted by CECAM and MaX (European Centre of Excellence), and adoption is often driven by needs for large-scale, high-accuracy simulations in fields represented by research groups at Imperial College London and ETH Zurich.
Category:Computational chemistry software