Cellular Automaton Study of Time-Dynamics of Avalanche Breakdown in IMPATT Diodes

Employing a recently developed efficient cellular automaton technique for solving Boltzmann's transport equation for realistic devices, we present a detailed study of the carrier dynamics in GaAs avalanche p-i-n (IMPATT) diodes. We find that the impact ionization in reverse bias p-i-n diodes with ultrathin (less than 50 nm) intrinsic regions is triggered by Zener tunneling rather than by thermal generation. The impact generation of hot carriers occurs mainly in the low-field junction regions rather than in the high field intrinsic zone. The calculations predict significantly more minority carriers on the n-side than on the p-side

Target‐oriented habitat and wildlife management: estimating forage quantity and quality of semi‐natural grasslands with Sentinel‐1 and Sentinel‐2 data

Semi‐natural grasslands represent ecosystems with high biodiversity. Their conservation depends on the removal of biomass, for example, through grazing by livestock or wildlife. For this, spatially explicit information about grassland forage quantity and quality is a prerequisite for efficient management. The recent advancements of the Sentinel satellite mission offer new possibilities to support the conservation of semi‐natural grasslands. In this study, the combined use of radar (Sentinel‐1) and multispectral (Sentinel‐2) data to predict forage quantity and quality indicators of semi‐natural grassland in Germany was investigated. Field data for organic acid detergent fibre concentration (oADF), crude protein concentration (CP), compressed sward height (CSH) and standing biomass dry weight (DM) collected between 2015 and 2017 were related to remote sensing data using the random forest regression algorithm. In total, 102 optical‐ and radar‐based predictor variables were used to derive an optimized dataset, maximizing the predictive power of the respective model. High R2 values were obtained for the grassland quality indicators oADF (R2 = 0.79, RMSE = 2.29%) and CP (R2 = 0.72, RMSE = 1.70%) using 15 and 8 predictor variables respectively. Lower R2 values were achieved for the quantity indicators CSH (R2 = 0.60, RMSE = 2.77 cm) and DM (R2 = 0.45, RMSE = 90.84 g/m²). A permutation‐based variable importance measure indicated a strong contribution of simple ratio‐based optical indices to the model performance. In particular, the ratios between the narrow near‐infrared and red‐edge region were among the most important variables. The model performance for oADF, CP and CSH was only marginally increased by adding Sentinel‐1 data. For DM, no positive effect on the model performance was observed by combining Sentinel‐1 and Sentinel‐2 data. Thus, optical Sentinel‐2 data might be sufficient to accurately predict forage quality, and to some extent also quantity indicators of semi‐natural grassland

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given

Explaining the Dependences of Electron and Hole Mobilities in Si MOSFETs Inversion Layer

IEEE Catalog Number 99 CH 3631-8, IEEE Publishing Services, New York (1999)

Bands, Bonds, and Polarizations in Nitrides - from Electronic Orbitals to Electronic Devices

A key property of the nitrides is the fact that they possess large spontaneous and piezoelectric polarization fields that allow a significant tailoring of the carrier dynamics and optical properties of nitride devices. In this paper, based on first-principles calculations of structural and electronic properties of bulk nitrides and their heterostructure, we investigate the potential of this novel material class for modern device applications by performing self-consistent Monte Carlo simulations. Our studies reveal that the nitride based electronic devices have characteristics that predispose them for high power and high frequency applications. We demonstrate also that transistor characteristics are favorably influenced by the internal polarization induced electric fields

Midinfrared intersubband electroluminescence of Si/SiGe quantum cascade structures

Unipolar intersubband lasers like quantum cascade laser structures might be realized not only in III–V semiconductors but also in Si/SiGe multiple layer structures since no optical transitions across the indirect band gap are involved. We report on well-defined intersubband electroluminescence emission of Si/SiGe quantum cascade structures with different active quantum wells parameters. The complex valence band structure and a nonradiative relaxation rate of about 400 fs were calculated by multiband k·p formalism including Si/Ge segregation effects. The observed spectral shift of the electroluminescence peak from 146 to 159 meV is described well by quantum confinement of the two lowest heavy hole subbands. The electroluminescence observed reveals transverse magnetic polarization, a spectral line shape that changes with the direction of the current, and low-energy line broadening with an increase in temperature and current. All these features are described well by the k·p model calculation