| 1 | Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set | Computational Materials Science | 1996 | 66,363 |
| 2 | A fast and robust algorithm for Bader decomposition of charge density | Computational Materials Science | 2006 | 9,265 |
| 3 | Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis | Computational Materials Science | 2013 | 3,425 |
| 4 | First-principles computation of material properties: the ABINIT software project | Computational Materials Science | 2002 | 2,723 |
| 5 | Computer graphics and graphical user interfaces as tools in simulations of matter at the atomic scale | Computational Materials Science | 2003 | 1,690 |
| 6 | Pseudopotentials periodic table: From H to Pu | Computational Materials Science | 2014 | 1,633 |
| 7 | MOLCAS: a program package for computational chemistry | Computational Materials Science | 2003 | 1,615 |
| 8 | Pseudopotentials for high-throughput DFT calculations | Computational Materials Science | 2014 | 1,357 |
| 9 | High-throughput electronic band structure calculations: Challenges and tools | Computational Materials Science | 2010 | 1,346 |
| 10 | Systematic analysis of local atomic structure combined with 3D computer graphics | Computational Materials Science | 1994 | 1,231 |
| 11 | A generalized synchronous transit method for transition state location | Computational Materials Science | 2003 | 1,171 |
| 12 | AFLOW: An automatic framework for high-throughput materials discovery | Computational Materials Science | 2012 | 1,163 |
| 13 | Solid state calculations using WIEN2k | Computational Materials Science | 2003 | 1,152 |
| 14 | AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations | Computational Materials Science | 2012 | 921 |
| 15 | A high-throughput infrastructure for density functional theory calculations | Computational Materials Science | 2011 | 884 |
| 16 | Matminer: An open source toolkit for materials data mining | Computational Materials Science | 2018 | 767 |
| 17 | Bulk properties and electronic structure of SrTiO3, BaTiO3, PbTiO3 perovskites: an ab initio HF/DFT study | Computational Materials Science | 2004 | 723 |
| 18 | Molecular dynamics simulations of the elastic properties of polymer/carbon nanotube composites | Computational Materials Science | 2007 | 709 |
| 19 | Band structure diagram paths based on crystallography | Computational Materials Science | 2017 | 669 |
| 20 | An improved prediction of residual stresses and distortion in additive manufacturing | Computational Materials Science | 2017 | 621 |
| 21 | DAMASK – The Düsseldorf Advanced Material Simulation Kit for modeling multi-physics crystal plasticity, thermal, and damage phenomena from the single crystal up to the component scale | Computational Materials Science | 2019 | 621 |
| 22 | Seeing auxetic materials from the mechanics point of view: A structural review on the negative Poisson’s ratio | Computational Materials Science | 2012 | 558 |
| 23 | Constitutive modeling for elevated temperature flow behavior of 42CrMo steel | Computational Materials Science | 2008 | 544 |
| 24 | Elastic constants of cubic crystals | Computational Materials Science | 2014 | 536 |
| 25 | Active learning of linearly parametrized interatomic potentials | Computational Materials Science | 2017 | 530 |
| 26 | Implementation of the projector augmented-wave method in the ABINIT code: Application to the study of iron under pressure | Computational Materials Science | 2008 | 516 |
| 27 | Numerical simulation of temperature field and residual stress in multi-pass welds in stainless steel pipe and comparison with experimental measurements | Computational Materials Science | 2006 | 510 |
| 28 | HOOMD-blue: A Python package for high-performance molecular dynamics and hard particle Monte Carlo simulations | Computational Materials Science | 2020 | 506 |
| 29 | Overcoming the doping bottleneck in semiconductors | Computational Materials Science | 2004 | 499 |
| 30 | Thermo-mechanical analysis of Wire and Arc Additive Layer Manufacturing process on large multi-layer parts | Computational Materials Science | 2011 | 482 |
| 31 | Ring statistics analysis of topological networks: New approach and application to amorphous GeS2 and SiO2 systems | Computational Materials Science | 2010 | 463 |
| 32 | Interatomic potential for Si–O systems using Tersoff parameterization | Computational Materials Science | 2007 | 440 |
| 33 | Theoretical study of the nonlinear conductance of Di-thiol benzene coupled to Au(1 1 1) surfaces via thiol and thiolate bonds | Computational Materials Science | 2003 | 437 |
| 34 | A review on the application of nonlocal elastic models in modeling of carbon nanotubes and graphenes | Computational Materials Science | 2012 | 435 |
| 35 | An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO2 | Computational Materials Science | 2016 | 435 |
| 36 | AiiDA: automated interactive infrastructure and database for computational science | Computational Materials Science | 2016 | 423 |
| 37 | First-principles thermodynamics from phonon and Debye model: Application to Ni and Ni3Al | Computational Materials Science | 2010 | 402 |
| 38 | How to determine composite material properties using numerical homogenization | Computational Materials Science | 2014 | 401 |
| 39 | Mechanical properties of the hexagonal boron nitride monolayer: Ab initio study | Computational Materials Science | 2012 | 392 |
| 40 | Molecular dynamics simulation of ion ranges in the 1–100 keV energy range | Computational Materials Science | 1995 | 391 |
| 41 | Murnaghan’s equation of state for the electronic ground state energy | Computational Materials Science | 2006 | 386 |
| 42 | Ab initio calculations of elastic constants and thermodynamic properties of NiAl under high pressures | Computational Materials Science | 2008 | 382 |
| 43 | High strain rate fracture and C-chain unraveling in carbon nanotubes | Computational Materials Science | 1997 | 381 |
| 44 | Prediction of compressive strength of concrete containing fly ash using artificial neural networks and fuzzy logic | Computational Materials Science | 2008 | 377 |
| 45 | The Materials Application Programming Interface (API): A simple, flexible and efficient API for materials data based on REpresentational State Transfer (REST) principles | Computational Materials Science | 2015 | 375 |
| 46 | Application of the exact muffin-tin orbitals theory: the spherical cell approximation | Computational Materials Science | 2000 | 340 |
| 47 | Density-functional tight-binding for beginners | Computational Materials Science | 2009 | 339 |
| 48 | Graphene-like titanium carbides and nitrides Tin+1Cn, Tin+1Nn (n=1, 2, and 3) from de-intercalated MAX phases: First-principles probing of their structural, electronic properties and relative stability | Computational Materials Science | 2012 | 333 |
| 49 | A comparative study on Johnson Cook, modified Zerilli–Armstrong and Arrhenius-type constitutive models to predict elevated temperature flow behaviour in modified 9Cr–1Mo steel | Computational Materials Science | 2009 | 326 |
| 50 | The AFLOW standard for high-throughput materials science calculations | Computational Materials Science | 2015 | 321 |
