Electronic Structure: Basic Theory and Practical Methods

By Richard M. Martin. 2004

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Citations in the corpus

Machine learning bandgaps of double perovskites (2016, methodology): “Finally, we would also like to note that despite its significantly low computational cost compared to the GW approach, the GLLB-SC functional is about twice as expensive as compared to a conventional DFT calculation employing a local or semi-local functional.”
Accelerating materials property predictions using machine learning (2013, methodology): “The quantum mechanical computations were performed using density functional theory (DFT) 23,24 as implemented in the Vienna ab initio software package 34,35 .”
Evaluation of Half‐Heusler Compounds as Thermoelectric Materials Based on the Calculated Electrical Transport Properties (2008, unknown): “Even though much progress has been made to solve this intrinsic problem of density functional methods, most of the advanced methods and algorithms([45]) are still in their infancy and are hardly used for real complex materials simulations.”
Electron-phonon interactions from first principles (2016, background): “(23) Here the potential V KS is the sum of the nuclear (or ionic) contribution V en, the Hartree electronic screening V H, and the exchange and correlation potential V xc (Martin, 2004): V KS = V en + V H + V xc. (24) The potentials appearing in Eq.”
Crystal structure representations for machine learning models of formation energies (2015, background): “One resolution is given by the Ewald sum [33–35].”
ABINIT: First-principles approach to material and nanosystem properties (2009, methodology): “…Operating System: All systems with a Fortran95 compiler RAM: ranges from a few Mbytes to several hundred Gbytes, depending on the input file Number of processors used: sequential, or parallel with proven speed-up up to one thousand processors Email address: xavier.gonze@uclouvain.be (X. Gonze?).”
BoltzWann: A code for the evaluation of thermoelectric and electronic transport properties with a maximally-localized Wannier functions basis (2013, methodology): “We use ultrasoft pseudopo-tentials for Co and S atoms, and norm-conserving pseudopotentials for Sb and Ge, publicly available at www.quantum-espresso.org [51, 52, 6].”
Error Estimates for Solid-State Density-Functional Theory Predictions: An Overview by Means of the Ground-State Elemental Crystals (2012, background): “They are: (1) alkali and alkaline earth metals; (2) nonmagnetic transition metals; (3) magnetic materials; (4) correlation-dominated materials; (5) high-coordination p block compounds; (6) low-coordination”
Metal Oxide Semi-Conductor Gas Sensors in Environmental Monitoring (2010, background): “The separation between these two bands is a function of energy, particularly the Fermi level, defined as the highest available electron energy levels at a temperature [7].”
BerkeleyGW: A massively parallel computer package for the calculation of the quasiparticle and optical properties of materials and nanostructures (2011, methodology): “…is intended to be used on top of a number of mean-ﬁeld (DFT and other) codes that focus on ground-state properties, such as PARATEC [11], Quantum ESPRESSO [12], SIESTA [13], PARSEC [14,15], Octopus [49,50] and an empirical pseudopotential code (EPM) included in the package (based on TBPW [16 ).”
Emergence of magnetism in graphene materials and nanostructures (2010, background): “This approach is now implemented in a large number of public computer codes and well described in a variety of graduate-level textbooks (for instance, see (Koch and Holthausen, 2002; Martin, 2004; Marx and Hutter, 2009)).”
Electronic properties of graphene antidot lattices (2009, background): “DFT is a widely used standard for electronic structure calculations and we shall here only briefly outline the underlying theory [41].”