Author Correction: Ab-initio calculations of shallow dopant qubits in silicon from pseudopotential and all-electron mixed approach

Ma, Hongyang; Hsueh, Yu‐Ling; Monir, Serajum; Jiang, Yue; Rahman, Rajib

doi:10.1038/s42005-022-01014-x

Cited by 1 publication

(4 citation statements)

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“…Calculated hyperfine parameters for shallow dopant systems using the PP-PAW method in VASP , and AE and PP-AE in CP2K were compared. However, unlike the linear fitting scheme employed by Swift et al, Ma et al opted instead for a quadratic fit yielding extrapolated hyperfine values of 56.7, 115.5, and 112.5 MHz (exp = 117 MHz) for the PP-PAW, AE, and PP-AE approaches, respectively. Of note is the decreased computational scaling of the atom-centered approach in CP2K, enabling calculations on supercells up to 4096 atoms versus 1000 atoms for the PP-PAW approach .…”

Section: Designing Robust Computational Modelsmentioning

confidence: 99%

“…However, unlike the linear fitting scheme employed by Swift et al, Ma et al opted instead for a quadratic fit yielding extrapolated hyperfine values of 56.7, 115.5, and 112.5 MHz (exp = 117 MHz) for the PP-PAW, AE, and PP-AE approaches, respectively. Of note is the decreased computational scaling of the atom-centered approach in CP2K, enabling calculations on supercells up to 4096 atoms versus 1000 atoms for the PP-PAW approach . Clearly, the discrepancies in expense and predicted properties between the two approaches warrant further benchmarking to understand the ability of each to describe different material types and particular material properties.…”

Section: Designing Robust Computational Modelsmentioning

confidence: 99%

“…23 From a more practical standpoint, constructing the allelectron charge density from PPs using the projector augmented wave (PAW) method has been shown to be successful in calculating the hyperfine parameters of some transition-metal-doped systems. 24 A comparison between the different approaches was attempted by Ma et al 25 in 2022. Calculated hyperfine parameters for shallow dopant systems using the PP-PAW method in VASP 26,27 and AE and PP-AE in CP2K 28 were compared.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Of note is the decreased computational scaling of the atom-centered approach in CP2K, enabling calculations on supercells up to 4096 atoms versus 1000 atoms for the PP-PAW approach. 25 Clearly, the discrepancies in expense and predicted properties between the two approaches warrant further benchmarking to understand the ability of each to describe different material types and particular material properties.…”

Section: ■ Introductionmentioning

confidence: 99%

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Lessons Learned from Catalysis to Qubits: General Strategies to Build Accessible and Accurate First-Principles Models of Point Defects

Repa,

Fredin

2023

J. Phys. Chem. C

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Defects and dopants play critical roles in defining the properties of a material. Achieving a mechanistic understanding of how such properties arise is challenging with current experimental methods, and computational approaches suffer from significant modeling limitations that frequently require a posteriori fitting. Consequently, the pace of dopant discovery as a means of tuning material properties for a particular application has been slow. However, recent advances in computation have enabled researchers to move away from semiempirical schemes to reposition density functional theory as a predictive tool and improve the accessibility of highly accurate first-principles methods to all researchers. This Perspective discusses some of these recent achievements that provide more accurate first-principles geometric, thermodynamic, optical, and electronic properties simultaneously. Advancements related to supercells, basis sets, functionals, and optimization protocols, as well as suggestions for evaluating the quality of a computational model through comparison to experimental data, are discussed. Moreover, recent computational results in the fields of energy materials, heterogeneous catalysis, and quantum informatics are reviewed along with an evaluation of current frontiers and opportunities in the field of computational materials chemistry.

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