Materials engineering using atomistic modeling is an essential tool for the development of qubits and quantum sensors. Traditional density-functional theory (DFT) does however not adequately capture the complete physics involved, including key aspects and dynamics of superconductivity, surface states, etc. There are also significant challenges regarding the system sizes that can be simulated, not least for thermal properties which are key in quantum-computing applications. The QuantumATK tool combines DFT, based on LCAO basis sets, with non-equilibrium Green's functions, to compute the characteristics of interfaces between superconductors and insulators, as well as the surface states of topological insulators. Additionally, the software leverages machine-learned force-fields to simulate thermal properties and to generate realistic amorphous geometries in large-scale systems. Finally, the description of superconducting qubits and sensors as two-level systems modeled with a double-well potential requires many-body physics, and this paper demonstrates how electron-electron interaction can be added to the single-particle energy levels from an atomistic tight-binding model to describe a realistic double-quantum dot system.

We present a computational study of the band alignment in GAA nanosheet structures. We present a dielectric dependent hybrid functional approach with metallic corrections that correctly predicts the band gaps of semiconductors and insulators as well as the density of states of metals. We use this method to study the band alignment of a silicon nanosheet in a GAA structure with respect to the TiN Fermi level. The band alignment is shown to be tunable by the Ge concentration in a thin Si 1-x Ge x cladding layer.

This paper presents simulation of a three- dimensional ferroelectric NAND memory using a multi-domain Ginzburg-Landau-Khalatnikov polarization model. The model parameters with a variation range following a Gaussian function are calibrated based on experimental polarization-electric field hysteresis for undoped and 5 mol% Al-doped Hf02 thin films. The allowed memory window between program and erase states can be enlarged from 2.9 to 12.6V through the incorporation of Al dopant in Hf02. The 3-sigma standard variation of threshold voltage change due to the grain-to-grain variability is also examined and estimated to be 0.57V. This polarization enhancement by substituting Hf with Al atom is also justified through atomistic simulation.

In this work, by means of a multiscale simulation approach, we study noise-related phenomena in 3D NANDs, which are ruled by the stochastic behavior of polysilicon grain boundary defects. Ab-initio simulation is, firstly, carried out to gain a physics-based understanding of the polysilicon bands and its traps properties. In particular, we have assessed the stability of our results against several configurations of most structurally diverse defects in amorphous silicon. The defect energies are then used to inform 3D TCAD to enable a Kinetic Monte Carlo simulation of the program noise and the evaluation of cross-temperature effects in the read operation.

As new materials and designs are being investigated for the development of next generation semiconductor technology nodes [1], this work focuses on atomically thin two-dimensional (2D) transition metal dichalcogenide (TMD) materials for future transistor designs [2,3]. In such devices, the metallic phase of TMDs (T') can be used as the source and drain electrodes and the semiconducting phase (H) a...

We demonstrate an efficient method for high-accuracy ab initio simulations for semiconductor device technology development, such as high-k metal gate stack engineering and investigation of 2D material-based FET performance. The method combines the HSE06 hybrid density functional with linear combination of atomic orbitals (LCAO) basis sets, as implemented in the QuantumATK atomic-scale modeling platform. We show that HSE06-LCAO predicts accurate band energies and enables large-scale HSE06 simulations for systems comprising thousands of atoms using modest computational resources.

We study grain boundary scattering as a source of resistance increase in narrow interconnects. We consider both copper and a potential next-generation metal, ruthenium. The increase in resistance due to grain boundary scattering is often calculated using the Mayadas and Schatzkes model, which in addition to the average grain size depends on the bulk resistivity, the electron mean free path, and the average reflection coefficient at grain boundaries. We demonstrate a workflow to calculate all the latter three material properties using first-principles calculations. Calculated values for copper are used to verify our method, while experimental results for the cubic phase of ruthenium are unavailable and thus must rely on first-principles calculations. Using an automated workflow, we consider significantly more grain boundary structures than in other works, and find an almost twice as large average reflection coefficient for copper than previously reported. In spite of the larger copper reflection coefficient, the corresponding reflection coefficients for ruthenium grain boundaries are consistently larger, but with a smaller variation than observed for copper. Our results demonstrate the importance of studying a large set of grain boundary structures.

Recent observations of ferroelectricity in mixed hafnia and zirconia thin films have been surprising, since the bulk crystal phases of the individual materials are non-polar in the absence of applied electric fields. The ferroelectricity can be traced back to a metastable, polar orthorhombic phase, which however is nearly indistinguishable from the tetragonal phase in grazing incidence X-ray diffraction. This indicates that better tools for optical characterization and identification of thin film crystalline phases are needed. Here we describe a first-principles methodology for obtaining a collection of optical properties such as the dielectric and electro-optical tensors, as well as infrared and Raman spectra. We illustrate how these can be used to guide material characterization of thin film dielectrics, by identifying distinct fingerprint signatures for each phase, which potentially can be used for real-space identification and characterization of ferroelectric regions.

We propose a first-principles atomistic method based on density functional theory and the non-equilibrium Green’s-function method to investigate the electronic and structural response of metal-insulator-metal capacitors under applied bias voltages. We validate our method by showing its usefulness in two paradigmatic cases where including finite-bias structural relaxation effects is critical to describe the device behavior: formation of dielectric dead layers in a paraelectric SRO|STO|SRO capacitor due to an applied bias voltage, and the switching behavior of a ferroelectric SRO|BTO|SRO capacitor due to an external electric field.

QuantumATK is an integrated set of atomic-scale modelling tools developed since 2003 by professional software engineers in collaboration with academic researchers. While different aspects and individual modules of the platform have been previously presented, the purpose of this paper is to give a general overview of the platform. The QuantumATK simulation engines enable electronic-structure calculations using density functional theory or tight-binding model Hamiltonians, and also offers bonded or reactive empirical force fields in many different parametrizations. Density functional theory is implemented using either a plane-wave basis or expansion of electronic states in a linear combination of atomic orbitals. The platform includes a long list of advanced modules, including Green's-function methods for electron transport simulations and surface calculations, first-principles electron-phonon and electron-photon couplings, simulation of atomic-scale heat transport, ion dynamics, spintronics, optical properties of materials, static polarization, and more. Seamless integration of the different simulation engines into a common platform allows for easy combination of different simulation methods into complex workflows. Besides giving a general overview and presenting a number of implementation details not previously published, we also present four different application examples. These are calculations of the phonon-limited mobility of Cu, Ag and Au, electron transport in a gated 2D device, multi-model simulation of lithium ion drift through a battery cathode in an external electric field, and electronic-structure calculations of the composition-dependent band gap of SiGe alloys.

Bentonite clays will be used as barriers in geological repositories for radioactive wastes. Anoxic conditions will prevail in such repositories, and the presence of sulphide-producing bacteria in commercial bentonites and deep groundwater environments is well established. In this study, sulphide was found to reduce ferric iron in bentonites denoted Asha, MX-80 and Calcigel under the formation of elemental sulphur, ferrous iron and iron sulphide. These reactions rendered an immobilisation capacity of the clays that was 40 μmole sulphide (g clay) or more, depending on the load of sulphide, and type of clay. In addition, the effective diffusion coefficients for sulphide in Asha bentonite, compacted to saturated wet densities of 1750 kg m and 2000 kg m, were determined to 2.74 × 10 m s and 6.60 × 10 m s, respectively. The found immobilisation effect can reduce the mass of sulphide that corrode metal canisters over repository life times, but the concomitant reduction of ferric iron may be problematic due to the destabilizing effect of ferrous iron on dioctahedral smectites such as montmorillonites.

Electronic structure calculations for a homo-material semimetal (thick Sn)/semiconductor (thin Sn) heterodimensional junction and two conventional metal (Ag or Pt)/silicon hetero-material junctions are performed. Charge distributions and local density of states are examined to compare the physics of junctions formed by quantum confinement in a homo-material, heterodimensional semimetal junction with that of conventional Schottky hetero-material junctions. Relative contributions to the Schottky barrier heights are described in terms of the interface dipoles arising due to charge transfer at the interface and the effects of metal induced gap states extending into the semiconducting regions. Although the importance of these physical mechanisms vary for the three junctions, a single framework describing the junction energetics captures the behaviors of both the heterodimensional semimetal junction and the more conventional metal/semiconductor junctions.

Protein electronics is a relatively new branch of molecular electronics which goal is to analyze the mechanism and utilize the gained knowledge for the construction of robust super small flexible protein- and biological cell-based electronic materials for bioinorganic hybrids, including sensors, actuators, electrochemical cell, and catalytic devices. Though widely discussed, the mechanism and the structural components controlling ET through multi-atomic proteins, which calculation requires unique software and high-performance computers, are not completely understood. In the present work, we calculate from first principles ET through two proteins, (a) helical region of PilA, an extracellular proteinaceous filament of Geobacter sulfurreducens with was reported to conduct electrons over long distances (>1 micron) and (b) through bacterial FeS protein, rubredoxin, a small non-heme protein widely used by biological cells as a soluble redox mediator. For comparison, we also calculate ET through an artificially designed carbon nanotube (CNT)-histidine-heme-histidine-CNT conjugate that mimics bacterial cytochromes. Our calculations show that iron atom incorporated into protein structure as a heme or an iron-sulfur cluster opens up a transmission path at the energy corresponding to the Fermi energy level of the electrodes that substantially (by several folds) increases efficiency of ET through the protein. Neither aromatic Tyr, nor Phe at any ring orientation can get the compatible effect, though bipolar Asn might participate in ET at high bias voltages. The conductivity of the proteins substantially depends on the polarity of applied electric field allowing for the protein operation of as a molecular rectifier. These data explain the origin of experimentally observed high conductivity of iron-containing native proteins and can be used for wise de novo construction of new proteins for molecular electronics and bio-inspired energy converting devices.

Protein molecular conductance has attracted attention from researchers for the possibility of constructing innovative flexible biocompatible nanoscale electronic devices and smart hybrid materials. Due to protein complexity, most evaluations of protein conductivity are based on the simple estimation of protein's molecular orbital energy levels and spatial distributions without analysing its protein interaction with electrodes and the calculation of the rates of electron transfer (ET). In the present work, we included in our density functional theory (DFT) analysis an approach based on the non-equilibrium Green's function (NEGF) allowing for calculation from the first principles the molecular interaction with electrodes and thus the role of electrode materials, Fermi level, the thermal distribution of electronic energy levels, and the coupling efficiency between the molecule and the electrodes. Compared to proteins studied so far, mainly artificial peptides, heme-containing cytochromes, and bacterial pili, we choose rubredoxin for our calculation. Rubredoxin contains a non-heme iron that, as we have discovered recently, can be involved in extracellular ET in electroactive bacterial biofilms (Yates et al., Energy Environ. Sci., 2016, 9, 3544-3558). Our calculations show that an iron atom incorporated into the protein structure as an iron-sulfur cluster opens a transmission path at the energy corresponding to the Fermi level of the electrodes. This allows the protein to become an extremely efficient conductor at very low bias voltages (<±350 mV). Calculation of the role of protein amino acids based on the local density of states and electron transfer paths reveals that neither aromatic amino acid Tyr nor Phe at any ring orientation participates in coherent ET through the FeS cluster of the protein. Moreover, direct ET through surrounding amino acids, bypassing FeS, is possible only at biases ±1.5 to ±2 V. The polar amino acid Asn might participate in ET at these bias voltages. The conductivity of the protein core substantially depends on the polarity of the applied electric field, allowing for unidirectional ET and operation of the protein as a molecular rectifier. These results can be used for a wise de novo design of proteins for molecular electronics and cellular energy converting devices, particularly for utilization of iron doping in the construction of conductive protein wires.

We present several extensions to the Boltzmann Transport Equation (BTE) solver implemented in QuantumATK. This enables computational efficient simulations of first-principles transport coefficients in linear response to an applied electric field, magnetic field or temperature gradient. We calculate the phonon-limited resistivity in three FCC metals (Gold, Silver and Cobber) with the calculation of scattering rates from the electron-phonon interaction from first-principles. We correctly find that Gold has the highest resistivity while the resitivity of Copper is only slightly larger than that of Silver. In addition, we find that the resistivity of a 1 nm diameter Au nanowire is more than doubled as compared to that of bulk Au due to the increased electron-phonon coupling in nanowires. The simulations illustrate the predictive capabilities of the implemented Boltzmann Transport Equation (BTE) solver.

In this presentation we will demonstrate how it is possible to compute properties of Si i-x Ge x alloys, using modern first-principles approaches which provide values for the band gaps in the entire range 0 ≤ x ≤ 1, as well as effective masses for Si and Ge (also when strain is applied) which all are in excellent agreement with experiments. These benchmarks show that appropriately chosen DFT methods can be used for predictive atomistic device simulations of e.g. SiGe FinFETs or nanowire FETs.

ATK-ForceField is a software package for atomistic simulations using classical interatomic potentials. It is implemented as a part of the Atomistix ToolKit (ATK), which is a Python programming environment that makes it easy to create and analyze both standard and highly customized simulations. This paper will focus on the atomic interaction potentials, molecular dynamics, and geometry optimization features of the software, however, many more advanced modeling features are available. The implementation details of these algorithms and their computational performance will be shown. We present three illustrative examples of the types of calculations that are possible with ATK-ForceField: modeling thermal transport properties in a silicon germanium crystal, vapor deposition of selenium molecules on a selenium surface, and a simulation of creep in a copper polycrystal.