Simple intrinsic defects in InP : numerical predictions.

Schultz, Peter A.

doi:10.2172/1051733

Cited by 4 publications

(25 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As previously [1], defect formation energies are quoted in the phosphorus-rich limit. The chemical potential of the phosphorus atom is set to the computed energy of the phosphorus in the elemental bulk A7 structure, and the chemical potential of the indium atom is set to be that required to make the formation energy of perfect InP equal to zero.…”

Section: Methodsmentioning

confidence: 99%

“…The details of the computational methods are the same as comprehensively described previously [1], and will only be summarized here.…”

Section: Methodsmentioning

confidence: 99%

“…The comparison of LDA and PBE results is a partial assessment of the physical uncertainties within DFT functionals [5]. The pseudopotentials [6] (PP) for In and P are the same used for intrinsic defects calculations [1] and carefully verified. The close correspondence between the 3d-core and 3d-valence PP for the indium atom are evidence for a good transferability of the 3d-core PP for In.…”

Section: Methodsmentioning

confidence: 99%

“…Calculations for silicon-containing InP defects are all done with 3d-core pseudopotentials (total valence charge Z=3) for the In atom, and not repeated with 3d-valence (Z=13) PP. We had determined that the PP construction for the In atom, the 3d-core vs. 3d-valence, had only modest effect on computed defect properties, the physical uncertainties in the DFT results being dominated by the difference between the physical approximations of LDA and PBE [1]. If deemed necessary, the current calculations could be straightforwardly repeated using the more rigorous 3d-core PP for In.…”

Section: Methodsmentioning

confidence: 99%

“…This Report focuses on silicon-containing defects in InP. Numerical results for density functional theory (DFT) calculations of properties of simple intrinsic defects in indium phosphide have been presented in a previous SAND Report: 2012-3313, "Simple intrinsic defects in InP: Numerical predictions" [1]. That Report contains detailed tables of intrinsic defect properties-charge transition defect level energies, formation energies, diffusionpredicted with converged DFT.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Defect reaction network in Si-doped InP : numerical predictions.

Schultz¹

2013

Self Cite

View full text Add to dashboard Cite

This Report characterizes the defects in the defect reaction network in silicon-doped, n-type InP deduced from first principles density functional theory. The reaction network is deduced by following exothermic defect reactions starting with the initially mobile interstitial defects reacting with common displacement damage defects in Si-doped InP until culminating in immobile reaction products. The defect reactions and reaction energies are tabulated, along with the properties of all the silicon-related defects in the reaction network. This Report serves to extend the results for intrinsic defects in SAND 2012-3313: "Simple intrinsic defects in InP: Numerical predictions" to include Si-containing simple defects likely to be present in a radiation-induced defect reaction sequence.

show abstract

Section: Methodsmentioning

confidence: 99%

“…The details of the computational methods are the same as comprehensively described previously [1], and will only be summarized here.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Defect reaction network in Si-doped InP : numerical predictions.

Schultz¹

2013

Self Cite

View full text Add to dashboard Cite

show abstract

Simple intrinsic defects in InAs :

Schultz¹

2013

Self Cite

View full text Add to dashboard Cite

show abstract

Automated Algorithms for Quantum-Level Accuracy in Atomistic Simulations: LDRD Final Report.

Thompson¹,

Schultz²,

Moore³

et al. 2014

Self Cite

View full text Add to dashboard Cite

This report summarizes the result of LDRD project 12-0395, titled "Automated Algorithms for Quantum-level Accuracy in Atomistic Simulations." During the course of this LDRD, we have developed an interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected on to a basis of hyperspherical harmonics in four dimensions. The SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. Global optimization methods in the DAKOTA software package are used to seek out good choices of hyperparameters that define the overall structure of the SNAP potential. FitSnap.py, a Python-based software package interfacing to both LAMMPS and DAKOTA is used to formulate the linear regression problem, solve it, and analyze the accuracy of the resultant SNAP potential. We describe a SNAP potential for tantalum that accurately reproduces a variety of solid and liquid properties. Most significantly, in contrast to existing tantalum potentials, SNAP correctly predicts the Peierls barrier for screw dislocation motion. We also present results from SNAP potentials generated for indium phosphide (InP) and silica (SiO 2). We describe efficient algorithms for calculating SNAP forces and energies in molecular dynamics simulations using massively parallel computers and advanced processor architectures. Finally, we briefly describe the MSM method for efficient calculation of electrostatic interactions on massively parallel computers.

show abstract

Simple intrinsic defects in InP : numerical predictions.

Cited by 4 publications

References 14 publications

Defect reaction network in Si-doped InP : numerical predictions.

Defect reaction network in Si-doped InP : numerical predictions.

Simple intrinsic defects in InAs :

Automated Algorithms for Quantum-Level Accuracy in Atomistic Simulations: LDRD Final Report.

Contact Info

Product

Resources

About