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

Theory and simulation of quantum photovoltaic devices based on the non-equilibrium Green's function formalism

This article reviews the application of the non-equilibrium Green's function formalism to the simulation of novel photovoltaic devices utilizing quantum confinement effects in low dimensional absorber structures. It covers well-known aspects of the fundamental NEGF theory for a system of interacting electrons, photons and phonons with relevance for the simulation of optoelectronic devices and introduces at the same time new approaches to the theoretical description of the elementary processes of photovoltaic device operation, such as photogeneration via coherent excitonic absorption, phonon-mediated indirect optical transitions or non-radiative recombination via defect states. While the description of the theoretical framework is kept as general as possible, two specific prototypical quantum photovoltaic devices, a single quantum well photodiode and a silicon-oxide based superlattice absorber, are used to illustrated the kind of unique insight that numerical simulations based on the theory are able to provide.Comment: 20 pages, 10 figures; invited review pape

Surface reconstruction and ferroelectricity in PbTiO3_3 thin films

Surface and ferroelectric properties of PbTiO$_3$ thin films are investigated using an interatomic potential approach with parameters computed from first-principles calculations. We show that a model developed for the bulk describes properly the surface properties of PbTiO$_3$. In particular, the antiferrodistortive surface reconstruction, recently observed from X-ray scattering, is correctly reproduced as a result of the change in the balance of long-range Coulombic and short-range interactions at the surface. The effects of the surface reconstruction on the ferroelectric properties of ultrathin films are investigated. Under the imposed open-circuit electrical boundary conditions, the model gives a critical thickness for ferroelectricity of 4 unit cells. The surface layer, which forms the antiferrodistortive reconstruction, participates in the ferroelectricity. A decrease in the tetragonality of the films leads to the stabilization of a phase with non-vanishing in-plane polarization. A peculiar effect of the surface reconstruction on the in-plane polarization profile is found.Comment: 6 pages, 5 figure

Ab initio scattering from random discrete charges and its impact on the intrinsic parameter fluctuations in nano-CMOS devices

This thesis is concerned with the Monte Carlo simulation of device parameter variation associated with the discrete nature and random variation of ionized impurity atoms within ultra-small conventional n-MOS devices. In particular, the Monte Carlo method is applied to accurately resolve electron interactions with individual ionized impurity atoms and in so doing capture the variation in impurity scattering associated with randomly configured dopant distributions. To date, variation in transport due to position dependent variation in Coulomb scattering has not received any attention although is expected to increase the inherent device parameter variation.A detailed methodology for the accurate treatment of Coulomb scattering within the Ensemble Monte Carlo framework is presented and verified. Improvement over existing methodologies is presented with a short-range force model that significantly reduces errors in conservation of energy during short-range attractive interactions compared with models proposed in similar work. Details of the simulated reproduction of bulk mobility are thoroughly presented to validate the method, while to date such detail is not to be found anywhere in the literature.A charge assignment method is developed to be applied to traditional 'continuously' doped regions in order to allow a consistent description of doping charge when combined with 'atomistic' doping assigned via the Cloud-In-Cell scheme. The charge assignment method also represents the only consistent description of electron charge assigned via CIC and the continuous doping charge.Trapping of a single electron in a series of scaled n-channel MOSFETs was studied with the ab initio Coulomb scattering method and is consistently seen to increase the Random Telegraph Signal, associated with the trapping and de-trapping of such charges, when compared with Drift-Diffusion simulations. It is seen that the electrostatic influence of the trapped charge is most prominent at low applied gate voltages where it accounts for nearly 70 - 80% of the total current reduction when including transport variation in devices with channel lengths of 30- \nm. At high gate voltages, transport variation is the dominant factor with the electrostatic impact accounting for only 40 - 60% of the total variation in the same devices.Extending this treatment to an ensemble of atomistic devices, it is seen that the inclusion of transport variations significantly increases the distribution in device parameters and that the transport variation is significantly dependent upon the specific dopant distribution. Within an ensemble of 50 'atomistic' devices, it was seen from Drift-Diffusion simulation that the average current showed a 3.0% increase over the continuously doped device, while Monte Carlo simulations resulted in a decrease in average current of 1.5%. The standard deviation of the current distribution from Drift-Diffusion simulations was 2.4% while, significantly, Monte Carlo simulations returned a value of 6.7%. This has implications for the published data obtained from Drift-Diffusion simulations which will underestimate the variation

Ab initio RNA folding

RNA molecules are essential cellular machines performing a wide variety of functions for which a specific three-dimensional structure is required. Over the last several years, experimental determination of RNA structures through X-ray crystallography and NMR seems to have reached a plateau in the number of structures resolved each year, but as more and more RNA sequences are being discovered, need for structure prediction tools to complement experimental data is strong. Theoretical approaches to RNA folding have been developed since the late nineties when the first algorithms for secondary structure prediction appeared. Over the last 10 years a number of prediction methods for 3D structures have been developed, first based on bioinformatics and data-mining, and more recently based on a coarse-grained physical representation of the systems. In this review we are going to present the challenges of RNA structure prediction and the main ideas behind bioinformatic approaches and physics-based approaches. We will focus on the description of the more recent physics-based phenomenological models and on how they are built to include the specificity of the interactions of RNA bases, whose role is critical in folding. Through examples from different models, we will point out the strengths of physics-based approaches, which are able not only to predict equilibrium structures, but also to investigate dynamical and thermodynamical behavior, and the open challenges to include more key interactions ruling RNA folding.Comment: 28 pages, 18 figure

Computer calculations across time and length scales in photovoltaic solar cells

Photovoltaic (PV) solar cells convert solar energy to electricity through a cascade of microscopic processes spanning over 10 order of magnitudes of time and length. PV conversion involves a complex interplay of photons, charge carriers, and excited states. Processes following light absorption include generation of charge carriers or excitons, exciton dissociation over nanometer lengths and subpicosecond times, and carrier transport over ns–ms times and nm–mm lengths. Computer calculations have become an indispensable tool to understand and engineer solar cells across length and time scales. In this article, we examine the microscopic processes underlying PV conversion and review state-of-the-art computational methods to study PV solar cells. Recent developments and future research challenges are outlined

Efficient and realistic device modeling from atomic detail to the nanoscale

As semiconductor devices scale to new dimensions, the materials and designs become more dependent on atomic details. NEMO5 is a nanoelectronics modeling package designed for comprehending the critical multi-scale, multi-physics phenomena through efficient computational approaches and quantitatively modeling new generations of nanoelectronic devices as well as predicting novel device architectures and phenomena. This article seeks to provide updates on the current status of the tool and new functionality, including advances in quantum transport simulations and with materials such as metals, topological insulators, and piezoelectrics.Comment: 10 pages, 12 figure