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Register a new userImproved predictions of the physical properties of Zn- and Cd-based wide band-gap semiconductors: a validation of the ACBN0 functional
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We study the physical properties of Zn$X$ ($X$=O, S, Se, Te) and Cd$X$ ($X$=O, S, Se, Te) in the zinc-blende, rock-salt, and wurtzite structures using the recently developed fully $ab$ $initio$ pseudo-hybrid Hubbard density functional ACBN0. We find that both the electronic and vibrational properties of these wide-band gap semiconductors are systematically improved over the PBE values and reproduce closely the experimental measurements. Similar accuracy is found for the structural parameters, especially the bulk modulus. ACBN0 results compare well with hybrid functional calculations at a fraction of the computational cost.
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Wide band gap semiconductors are essential for todays electronic devices and energy applications due to their high optical transparency, as well as controllable carrier concentration and electrical conductivity. There are many categories of materials that can be defined as wide band gap semiconductors. The most intensively investigated are transparent conductive oxides (TCOs) such as ITO and IGZO used in displays, carbides and nitrides used in power electronics, as well as emerging halides (e.g. CuI) and 2D electronic materials used in various optoelectronic devices. Chalcogen-based (S, Se, Te) wide band gap semiconductors are less heavily investigated but stand out due to their propensity for p-type doping, high mobilities, high valence band positions (i.e. low ionization potentials), and broad applications in electronic devices such as CdTe solar cells. This manuscript provides a review of wide band gap chalcogenide semiconductors. First, we outline general materials design parameters of high performing transparent conductors. We proceed to summarize progress in wide band gap (Eg > 2 eV) chalcogenide materials, such as II-VI MCh binaries, CuMCh2 chalcopyrites, Cu3MCh4 sulvanites, mixed anion layered CuMCh(O,F), and 2D materials, among others, and discuss computational predictions of potential new candidates in this family, highlighting their optical and electrical properties. We finally review applications of chalcogenide wide band gap semiconductors, e.g. photovoltaic and photoelectrochemical solar cells, transparent transistors, and diodes, that employ wide band gap chalcogenides as either an active or passive layer. By examining, categorizing, and discussing prospective directions in wide band gap chalcogenides, this review aims to inspire continued research on this emerging class of transparent conductors and to enable future innovations for optoelectronic devices.
Optical properties of ZnMnO layers grown at low temperature by Atomic Layer Deposition and Metalorganic Vapor Phase Epitaxy are discussed and compared to results obtained for ZnMnS samples. Present results suggest a double valence of Mn ions in ZnO lattice. Strong absorption, with onset at about 2.1 eV, is tentatively related to Mn 2+ to 3+ photoionization. Mechanism of emission deactivation in ZnMnO is discussed and is explained by the processes following the assumed Mn 2+ to 3+ recharging.
Ultrawide-band-gap (UWBG) semiconductors are promising for fast, compact, and energy-efficient power-electronics devices. Their wider band gaps result in higher breakdown electric fields that enable high-power switching with a lower energy loss. Yet, the leading UWBG semiconductors suffer from intrinsic materials limitations with regards to their doping asymmetry that impedes their adoption in CMOS technology. Improvements in the ambipolar doping of UWBG materials will enable a wider range of applications in power electronics as well as deep- UV optoelectronics. These advances can be accomplished through theoretical insights on the limitations of current UWBG materials coupled with the computational prediction and experimental demonstration of alternative UWBG semiconductor materials with improved doping and transport properties. As an example, we discuss the case of rutile GeO$_2$ (r-GeO$_2$), a water-insoluble GeO$_2$ polytype which is theoretically predicted to combine an ultra-wide gap with ambipolar dopability, high carrier mobilities, and a higher thermal conductivity than b{eta}-Ga$_2$O$_3$. The subsequent realization of single-crystalline r-GeO$_2$ thin films by molecular beam epitaxy provides the opportunity to realize r-GeO$_2$ for electronic applications. Future efforts towards the predictive discovery and design of new UWBG semiconductors include advances in first-principles theory and high-performance computing software, as well as the demonstration of controlled doping in high-quality thin films with lower dislocation densities and optimized film properties.
The ability to predict the likelihood of impurity incorporation and their electronic energy levels in semiconductors is crucial for controlling its conductivity, and thus the semiconductors performance in solar cells, photodiodes, and optoelectronics. The difficulty and expense of experimental and computational determination of impurity levels makes a data-driven machine learning approach appropriate. In this work, we show that a density functional theory-generated dataset of impurities in Cd-based chalcogenides CdTe, CdSe, and CdS can lead to accurate and generalizable predictive models of defect properties. By converting any semiconductor + impurity system into a set of numerical descriptors, regression models are developed for the impurity formation enthalpy and charge transition levels. These regression models can subsequently predict impurity properties in mixed anion CdX compounds (where X is a combination of Te, Se and S) fairly accurately, proving that although trained only on the end points, they are applicable to intermediate compositions. We make machine-learned predictions of the Fermi-level dependent formation energies of hundreds of possible impurities in 5 chalcogenide compounds, and suggest a list of impurities which can shift the equilibrium Fermi level in the semiconductor as determined by the dominant intrinsic defects. These dominating impurities as predicted by machine learning compare well with DFT predictions, revealing the power of machine-learned models in the quick screening of impurities likely to affect the optoelectronic behavior of semiconductors.
We have investigated the Vanadium- (V) substituted Ni-Zn-Co ferrites where the samples were prepared using solid-state reaction technique. The impact of V5+ substitution on the structural, magnetic, dielectric and electrical properties of Ni-Zn-Co ferrites has been studied. XRD analysis confirmed the formation of a single-phase cubic spinel structure. The lattice constants have been calculated both theoretically and experimentally along with other structural parameters such as bulk density, X-ray density and porosity. The FESEM images are taken to study the surface morphology. FTIR measurement is also performed which confirms spinel structure formation. The saturation magnetization (Ms), coercive field (Hc) and Bohr magneton (B) were calculated from the obtained M-H loops. The temperature dependent permeability is studied to obtain the Curie temperature. Frequency and composition dependence of permeability was also analyzed. Dielectric behavior and ac resistivity are also subjected to investigate the frequency dependency. An inverse relationship was observed between the composition dependence of dielectric constant and ac resistivity. The obtained results such as the electrical resistivity, dielectric constants and magnetic properties suggest the appropriateness of the studied ferrites in microwave device applications.
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