Identifying Rashba–Dresselhaus splittings from first-principle calculations: A brief overview

Abstract

The present review is aimed to understand the Rashba and Dresselhaus effects from the first-principle calculations. A brief overview of first-principle density functional theory (DFT) and its global acceptance have been discussed. The discussions of the Rashba–Dresselhaus splittings, spin textures and understanding the effects from first-principle DFT calculations have been highlighted. Rashba and Dresselhaus effects have gained much attention in recent era for their highly promising applications in spintronics. In the presence of spin-orbit coupling and inherent non-centrosymmetry, while BiTeCl, TiS2Se, rhombohedral CsPbF3 and BiCoO3 compounds show large values of Rashba parameter ([Formula: see text] of [Formula: see text], 1.10, 1.05 and 0.74[Formula: see text]eVÅ, respectively, the single-layered semiconductor nanostructure InSb, rhombohedral BiFeO3 and Ag2BiO3 systems however depict promising values of Dresselhaus parameter ([Formula: see text] of [Formula: see text], 0.50 and 0.15[Formula: see text]eVÅ, respectively. The future of Rashba–Dresselhaus effects and their advancements in spintronics have also been enlightened in this paper. We believe that this study will not only help to understand the Rashba–Dresselhaus effects from first-principle calculations, but can also augment their applications in next generation spintronic devices.

Predicting band gaps of ABN3 perovskites: an account from machine learning and first-principle DFT studies

“…Presence of indirect band gaps with gap openings in the range 0.94–1.81 eV may render their applications in photovoltaics. 92–96 In this connection it may be relevant to mention that while the PBE functional is known to underestimate the E g values of the systems in general, 14,33–36,40,41,43 the HSE06 functional on the other hand can predict the E g values of the compounds in close agreement with the experimental observations. 14,33,40,45,97 The HSE06 XC energy functional ( E HSE06 XC ) is mathematically expressed as: 98 E HSE06 XC = 1/4 E HF, SR X ( ω ) + 3/4 E PBE, SR X ( ω ) + E PBE, LR X ( ω ) + E PBE C where “X”, “C”, “SR” and “LR” symbolize the exchange, correlation, short range and long range terms respectively in the energy functional.…”

“…The selective choice of G 0 W 0 @HSE06 level of theory in the DFT calculation as input for the prediction of band gaps is thus meaningful, given its efficacy in reproducing the experimental band gaps of many such compounds as reported elsewhere. 14,101–103…”

“…1–10 Moreover, perovskites containing heavy fermionic elements, that show Rashba splittings, find promising applications in spintronics. 11–14…”

“…[1][2][3][4][5][6][7][8][9][10] Moreover, perovskites containing heavy fermionic elements, that show Rashba splittings, nd promising applications in spintronics. [11][12][13][14] Despite considerable successes of oxide and halide perovskites, recently much attention has been focused on the synthesis and rst-principle calculations of nitride perovskites having general formula ABN 3 . [15][16][17][18][19] Of late, ABN 3 nd potential applications as topological insulators, photovoltaic cells and are being successfully used as optical luminescent materials.…”

“…[37][38][39] In this regard DFT calculations, as accomplished from single-shot GW (G 0 W 0 ) approximation using hybrid exchange-correlation (XC) functionals such as Heyd-Scuseria-Ernzerhof (HSE), Becke-3-parameter-Lee-Yang-Parr (B3LYP) and B3PW91 are known to predict the E g values of the compounds close to the experimental results. 14,33,[40][41][42][43][44][45][46][47][48] The major pitfalls of such calculations are that they are computationally demanding and need high end servers to run them. In this context, the machine learning (ML) is now considered as an effective alternative route to avoid the inherent computational costs linked with DFT calculations and helps in establishing a simple model between the characteristics features of materials and the target variable (here E g ).…”