Application of quantitative mobility-spectrum analysis to multilayer HgCdTe structures

Abstract

For modern semiconductor heterostructures containing multiple populations of distinct carrier species, conventional Hall and resistivity data acquired at a single magnetic field provide far less information than measurements as a function of magnetic field. However, the extraction of reliable and accurate carrier densities and mobilities from the field-dependent data can present a number of difficult challenges, which were never fully overcome by earlier methods, such as the multicarrier fit, the mobility-spectrum analysis of Beck and Anderson, and the hybrid mixed-conduction analysis. More recently, to overcome the limitations of those methods, several research groups have contributed to development of the quantitative mobility-spectrum analysis (QMSA), which is now available as a commercial product. The algorithm is analogous to a fast Fourier transform in that it transforms from the magneticfield (B) domain to the mobility (µ) domain. The QMSA converts the fielddependent Hall and resistivity data into a visually meaningful transformed output, comprising the conductivity density of electrons and holes in the mobility domain. In this article, we apply QMSA to both synthetic and real experimental data that are representative of modern multilayer HgCdTe structures. We discuss such features as the accuracy of the extraction of individual layer conductivities and average mobilities, reconstruction of the carrier mobility distribution within a particular layer, the resolution of two carriers with similar mobilities, and limits of the sensitivity.

Double subband occupation of the two-dimensional electron gas in InxAl1−xN/AlN/GaN/AlN heterostructures with a low indium content (0.064≤x≤0.140) barrier

“…The QMSA method is widely used in many studies to extract the mobilities and carrier densities of different carriers in semiconductor materials, including bulk samples, thin films, quantum wells, and multilayer device structures [14][15][16][17]. In addition, the mobilities and carrier densities of individual 2D and 3D electrons and holes in GaN-based heterostructures are reported with the implementation of the QMSA method [18,19].…”

Characterization and Simulation of Semiconductor Thin Films Using Quantitative Mobility Spectrum Analysis (QMSA)

“…Such analysis are generally consisted of a multi-carrier fit (MCF) to the experimental Hall data under the applied magnetic field which is not unique since the starting parameters such as number and type of carriers, and corresponding mobilities and concentrations need to be assumed [3]. Based on all the previous attempts like MCF, MSA [4], Dziuba and Gorska Iterative procedure of obtaining an accurate MS, an approach described by Antoszewski and Faraone et al [5], and known as quantitative mobility spectrum analysis (QMSA), has been developed and then systematically tested and improved [6][7][8][9]. By using the MS of Beck and Anderson as an initial function for a modified Gauss Seidel iterative procedure, the inherent instability of previous iterative procedures during the convergence process is removed and a good fit to the experimental data is obtained.…”

A Model of Numerical Calculation of Conductivity for III-V MBE Epilayers Using a Hall Device

“…To this end, other methods, such as the maximum entropy approach [22] or the application of Bryan's algorithm [23], must be considered. The concept most often used in the ii , dp , po , pie , sc , disl ii , disl ii , disl characterisation of mobility spectra has been described in many papers by Antoszewski and collaborators [12,24,25]. The main features of the above-mentioned methods are as follows.…”

“…(3) The mentioned authors [6,12,24,25] used different mathematical approaches to obtain mobility spectra from mobility and conductivity data.…”

“…Many experimental results have been analysed using this method [8-12, 24, 25]. Antoszewski et al concluded that a major advantage of mobility spectrum analysis (MSA) and quantitative mobility spectrum analysis (QMSA) over other methods is that these procedures are inherent not arbitrary that is, no prior assumptions are required [24,25]. These investigators suggested that their improved (QMSA) method has sufficient reliability, versatility, and sensitivity for their proposed analysis which is fully computer-automated, using magnetic field dependence data as input.…”