Advanced numerical modeling of avalanche infrared photodetectors

Infrared detectors are critical for a variety of applications within the commercial, scientific, and defense communities. Applications such as commercial LiDAR systems or the James Webb Space Telescope rely on infrared detectors with high sensitivity and fast response times to achieve their missions. The avalanche photodiode is a class of detectors with high bandwidth and internal signal amplification which can improve the sensitivity of a detector by overcoming the noise associated with readout electronics. The transport and multiplication properties of avalanche photodiodes are predicated on large electric fields in the device significantly shifting the distribution of the particles to higher energies, where the transport properties change. The modeling of these effects requires simulation tools which accurately incorporate the microscopic processes affecting the energy distribution within the device. In this work, a general-purpose three-dimensional Monte Carlo simulation tool, FBMC3D, is developed and subsequently employed to study infrared avalanche photodiode detectors. The software can employ both analytic and numerically computed descriptions of the semiconductor band structure, and real space is discretized using an unstructured tetrahedral mesh suited to the description of modern semiconductor devices with irregular geometries, doping profiles, and compositional gradients. FBMC3D combines and extends the steady advancements of the Monte Carlo technique of the previous decades and allows for the simulation of devices on a scale that has traditionally been restricted to drift-diffusion packages. This tool is then applied to the study of HgCdTe infrared avalanche photodetectors. Monte Carlo transport parameters are determined for a compositional range of HgCdTe corresponding to much of the infrared spectrum. The parameter model is able to fit the multiplication properties of a number of devices of varying architectures and compositions in the range. Finally, the assembled transport models are used to design a long wavelength infrared avalanche photodiode with significantly improved performance with respect to what has been reported in literature

Advanced numerical modeling of semiconductor material properties and their device performances

With the renewed concept of "Materials by Design" attracting particular attentions from the engineering communities in recent years, numerical methods that can reliably predict the optical and electrical properties of materials is highly preferable. Since the growth or the synthesis of a "designed" material and the ensuing devices is usually prohibitively expensive and time-consuming, numerical simulation tools that predict the properties of a proposed material together with its device performance before production is especially important and cost-effective. Furthermore, as the technology advances, semiconductor devices have been pushed to operate at their material limits, which requires a thorough understanding of the materials' microscopic processes under different conditions. Therefore, developing numerical models that are capable of investigating the semiconductor properties from material level to device level is highly desirable. This dissertation develops a suite of numerical models in which optical absorption and Auger recombination in semiconductor materials are studied and simulated together with their device performances. In particular, Green's function theory with full band structures is employed to investigate the material properties by evaluating the broadening of the electronic bands under the perturbation of phonons. As a result, both direct and phonon-assisted indirect processes are computed and compared among different materials. Drift-diffusion model and a 3D Monte-Carlo model are subsequently used to simulate the device characteristics with the obtained material parameters. This work first determines the full band structures for Si, Ge, α-Sn, HgCdTe, InAsSb and InGaAs alloys from EPM model, and then investigated the materials' minority carrier lifetime for IR detector applications. Finally device level simulations using drift-diffusion and 3D Monte-Carlo models are demonstrated. In particular, two issues of developing 3D Monte-Carlo device simulation models, namely the use of unstructured spatial meshes and elimination of particle-mesh forces, are discussed, which are crucial in simulating modern semiconductor devices having complex geometry and doping profiles

Analysis of Potential and Electron Density Behaviour in Extremely Scaled Si and InGaAs MOSFETs Applying Monte Carlo Simulations

Scaling of Silicon and InGaAs MOSFETs of a 25 nm gate length till shortest gate length of 5 nm, simulated this nano-device by Monte Carlo (MC) with quantum corrections. The transistors are scaled-down only in lateral dimensions in order to study electron transport approaching a ballistic limit along the scaled channel following experimental works. These MC simulations are able to give detailed insight into physical behaviour of electron velocity, electron density, and potential in relation to the drive current. We found that electron peak velocity increases during the scaling in Si MOSFETs till the 10 nm gate length and then dramatically declines due to a strong long-range Coulomb interaction among the source and the drain [16]. This effect is not observed in the equivalent InGaAs MOSFETs in which electron peak velocity exhibits double peak which steadily increases during the scaling [16]. However, the increasing of current in the equivalent InGaAs MOSFETs is moderate, by about 24 %, by comparing of current in the Si MOSFETs of 74 % delivered by 5 nm channel transistor

3D drift diffusion and 3D Monte Carlo simulation of on-current variability due to random dopants

In this work Random Discrete Dopant induced on-current variations have been studied using the Glasgow 3D atomistic drift/diffusion simulator and Monte Carlo simulations. A methodology for incorporating quantum corrections into self-consistent atomistic Monte Carlo simulations via the density gradient effective potential is presented. Quantum corrections based on the density gradient formalism are used to simultaneously capture quantum confinement effects. The quantum corrections not only capture charge confinement effects, but accurately represent the electron impurity interaction used in previous \textit{ab initio} atomistic MC simulations, showing agreement with bulk mobility simulation. The effect of quantum corrected transport variation in statistical atomistic MC simulation is then investigated using a series of realistic scaled devices nMOSFETs transistors with channel lengths 35 nm, 25 nm, 18nm, 13 nm and 9 nm. Such simulations result in an increased drain current variability when compared with drift diffusion simulation. The comprehensive statistical analysis of drain current variations is presented separately for each scaled transistor. The investigation has shown increased current variation compared with quantum corrected drift diffusion simulation and with previous classical MC results. Furthermore, it has been studied consistently the impact of transport variability due to scattering from random discrete dopants on the on-current variability in realistic nano CMOS transistors. For the first time, a hierarchic simulation strategy to accurately transfer the increased on-current variability obtained from the ‘ab initio’ MC simulations to DD simulations is subsequently presented. The MC corrected DD simulations are used to produce target $I_D-V_G$ characteristics from which statistical compact models are extracted for use in preliminary design kits at the early stage of new technology development. The impact of transport variability on the accuracy of delay simulation are investigated in detail. Accurate compact models extraction methodology transferring results from accurate physical variability simulation into statistical compact models suitable for statistical circuit simulation is presented. In order to examine te size of this effect on circuits Monte Carlo SPICE simulations of inverter were carried out for 100 samples

Anisotropic Quantum Corrections for 3-D Finite-Element Monte Carlo Simulations of Nanoscale Multigate Transistors

Anisotropic 2-D Schrödinger equation-based quantum corrections dependent on valley orientation are incorporated into a 3-D finite-element Monte Carlo simulation toolbox. The new toolbox is then applied to simulate nanoscale Si Siliconon-Insulator FinFETs with a gate length of 8.1 nm to study the contributions of conduction valleys to the drive current in various FinFET architectures and channel orientations. The 8.1 nm gate length FinFETs are studied for two cross sections: rectangular-like and triangular-like, and for two channel orientations: 〈100〉 and 〈110〉. We have found that quantum anisotropy effects play the strongest role in the triangular-like 〈100〉 channel device increasing the drain current by ~13% and slightly decreasing the current by 2% in the rectangular-like 〈100〉 channel device. The quantum anisotropy has a negligible effect in any device with the 〈110〉 channel orientation

Developement of simulation tools for the analysis of variability in advanced semiconductor electron devices

The progressive down-scaling has been the driving force behind the integrated circuit (IC) industry for several decades, continuously delivering higher component densities and greater chip functionality, while reducing the cost per function from one CMOS technology generation to the next. Moore’s law boosts IC industry profits by constantly releasing high-quality and inexpensive electronic applications into the market using new technologies. From the 1 m gate lengths of the eighties to the 35 nm gate lengths of contemporary 22 nm technology, the industry successfully achieved its scaling goals, not only miniaturizing devices but also improving device performance

A Statistical phonon transport model for thermal transport in cyrstalline materials from the diffuse to ballistic regime

Phonon transport in micro- nanoscale crystalline materials can be well modeled by the Boltzmann transport equation (BTE). The complexities associated with solving the BTE have led to the development of various numerical models to simulate phonon transport. These models have been applied to predict thermal transport from the di¤use to ballistic regime. While some success using techniques such as the Monte Carlo method has been achieved, there are still a significant number of approximations related to the intricacies of phonon transport that must be more accurately modeled for better predictions of thermal transport at reduced length scales. The objective of the present work is to introduce a Statistical Phonon Transport (SPT) model for simulating thermal transport in crystalline materials from the diffuse to ballistic regime. The SPT model provides a theoretically more realistic treatment of phonon transport physics by eliminating some of the common approximations utilized by other numerical modeling techniques. The SPT model employs full anisotropic dispersion. Phonon populations are modeled without the use of scaling factors or pseudo-random number generation. Three-phonon scattering is rigorously enforced following the selection rules of energy and pseudo-momentum. The SPT model provides a flexible framework for incorporating various phonon scattering mechanisms and models. Results related to the determination of allowable three-phonon interactions are presented along with several three-phonon scattering models. Steady-state and transient thermal transport results for silicon from the diffuse to ballistic regimes are presented and compared to analytical and experimental results. Recommendations for future work related to increasing the robustness of the SPT model as well as utilizing the SPT model to predict thermal transport in practical applications are given