Academic literature on the topic 'Two-dimensional materials; quantum-mechanical modeling; electron transport simulations'

Several electronic and optoelectronic devices have been proposed in recent years based on vertical heterostructures of two-dimensional (2D) materials. The large number of combinations of available 2D materials and the even larger number of possible heterostructures require effective and predictive device-simulation methods, to inform and accelerate experimental research and to support the interpretation of experiments. Here, we propose a computationally effective and physically sound method to model electron transport in 2D van der Waals heterostructures, based on a multiscale approach and quasiatomistic Hamiltonians. The method uses&nbsp;<em>ab initio</em>&nbsp;simulations to extract the parameters of a simplified tight-binding Hamiltonian based on a uniform three-dimensional lattice geometry that enables device simulations using the nonequilibrium Green&rsquo;s function approach in a computationally effective way. We describe the application and limitations of the method and discuss the examples of two use cases of practical electronic devices based on 2D materials, such as a field-effect transistor and a floating-gate memory, composed of molybdenum disulphide, hexagonal boron nitride and graphene.

During the last decades, the Nonequilibrium Green’s function (NEGF) formalism has been proposed to develop nano-scaled device-simulation tools since it is especially convenient to deal with open device systems on a quantum-mechanical base and allows the treatment of inelastic scattering. In particular, it is able to account for inelastic effects on the electronic and thermal current, originating from the interactions of electron–phonon and phonon–phonon, respectively. However, the treatment of inelastic mechanisms within the NEGF framework usually relies on a numerically expensive scheme, implementing the self-consistent Born approximation (SCBA). In this article, we review an alternative approach, the so-called Lowest Order Approximation (LOA), which is realized by a rescaling technique and coupled with Padé approximants, to efficiently model inelastic scattering in nanostructures. Its main advantage is to provide a numerically efficient and physically meaningful quantum treatment of scattering processes. This approach is successfully applied to the three-dimensional (3D) atomistic quantum transport OMEN code to study the impact of electron–phonon and anharmonic phonon–phonon scattering in nanowire field-effect transistors. A reduction of the computational time by about ×6 for the electronic current and ×2 for the thermal current calculation is obtained. We also review the possibility to apply the first-order Richardson extrapolation to the Padé N/N − 1 sequence in order to accelerate the convergence of divergent LOA series. More in general, the reviewed approach shows the potentiality to significantly and systematically lighten the computational burden associated to the atomistic quantum simulations of dissipative transport in realistic 3D systems.

A first-principles theoretical study of a monolayer-thick lateral heterostructure (LH) joining two different transition metal dichalcogenides, NbS₂&nbsp;and WSe₂, is reported. The NbS₂//WSe₂&nbsp;LH can be considered a prototypical example of a metal (NbS₂)/semiconductor (WSe₂) 2D hybrid heterojunction. First, realistic atomistic models of the NbS₂//WSe₂&nbsp;LH are generated and validated, its band structure is derived, and it is subjected to a fragment decomposition and electrostatic potential analysis to extract a simple but quantitative model of this interfacial system. Stoichiometric fluctuations models are also investigated and found not to alter the qualitative picture. Then, electron transport simulations are conducted and they are analyzed via band alignment analysis. It is concluded that the NbS₂//WSe₂&nbsp;LH appears as a robust seamless in-plane 2D modular junction for potential use in optoelectronic devices going beyond the present miniaturization technology.

Moore’s scaling law has survived during more than 50 years because the transistor fabrication recipes have been continuously adapted and technology boosters have been gradually introduced, e.g. strain, high- dielectrics, or 3-D FinFETs. The driving force behind these innovations has always been the intuition of clever researchers who benefited from classical technology computer aided design (TCAD) tools. The latter have been used in the semiconductor industry since the end of the 1970’s, when the first 2-D simulations of CMOS devices became feasible on a supercomputer [1]. Over the last 40 years, transistors have undergone tremendous evolutions, their dimensions being reduced by several orders of magnitude, while the physical models at the core of commercially available device simulators have remained the same: electron transport is still described by classical drift-diffusion (DD) equations, which have been modified to capture parts of the quantum mechanical effects affecting nano-transistors, e.g. geometrical confinement tunnelling leakages, or energy quantization [2]. A new generation of advanced TCAD tools that go beyond the DD equations and rely on atomistic quantum mechanical concepts is needed to reproduce the characteristics of today’s nanostructures and to predict the performance of not-yet-fabricated components. Such tools should combine different modelling approaches to be able to treat various device types, from state-of-the-art nano-transistors to photo-detectors based on two-dimensional materials or resistive switching random access memories. For example, to shed light on the behaviour of valence change memory (VCM) cells, which consist of metal-insulator-metal stacks, molecular dynamics (MD), kinetic Monte Carlo (KMC), density functional theory (DFT), and quantum transport (QT) should be allied, as illustrated in the accompanying figure. By doing so, the growth of nano-filaments through realistic oxides embedded between two metallic electrodes can be accurately simulated and the electrical current flowing through computed with, e.g., the Non-equilibrium Green’s Function (NEGF) formalism [3]. In this presentation the multi-method simulation environment shown the accompanying Figure will be briefly reviewed. The main focus will be set on the discussion of few applications, among them transistors and memory cells. References: [1] S. Selberherr, W. Fichtner, and H.W. Potzl, “Minimos - A program package to facilitate MOS device design and analysis”, Proceedings of NASECODE I, 275 (1979). [2] A. Wettstein, A. Schenk, and W. Fichtner, “Quantum device-simulation with the density-gradient model on unstructured grids”, IEEE Trans. On Elec. Dev. 48, 279 (2001). [3] M. Kaniselvan, M. Luisier, and M. Mladenovic, “An Atomistic Modelling Framework for Valence Change Memory Cells”, Solid-State Electronics 199, 108506 (2023). Figure Caption: Multi-method simulation framework dedicated to the investigation of resistive switching devices, here valence change memory (VCM) cells. First, oxide samples with a low defect concentration are constructed withclassical molecular dynamics (MD) using a melt-and-quench procedure. They arethentransferredto akinetic Monte Carlo (KMC) solver that determines the distribution of oxygen vacancies (VO,green spheres) within the oxide layer. All input parameters to KMC (diffusioncoefficients and generation/recombination rates) are computed with density functional theory(DFT), which is also used to calculate the Hamiltonian (H) and Overlap (S) matrices of the created VCM structure. Finally, these quantities are passed to aquantum transport (QT) tool to perform ab initiodevice simulations. Figure 1

Lithium-ion battery (LIB) cathodes are porous electrodes made of active material (AM) that stores lithium, a composite of carbon additives and polymeric binder (CBD) that facilitates electron transport and ensures the mechanical integrity of the electrode, and electrolyte-filled pore space that facilitates lithium-ion transport [1]. The volume fraction and morphology of the different constituents at the microscale necessarily determine transport properties and influence the measurable performance [2]. In this work, the impact of NMC electrode microstructure on the effective transport properties is studied using FIB-SEM-based three-dimensional (3D) particle-resolved microscale simulations. The effect of AM and CBD bulk electronic conductivity on the effective electronic conductivity is first studied and used to highlight that the impact of the AM bulk conductivity is negligible compared to that of the CBD. Next, the impact of CBD volume fraction, in isolation from its morphology, is studied using morphological operations by eroding and dilating the CBD phase in the FIB-SEM images and analyzing its impact on the effective conductivity using multiple 3D reconstructions. Increasing the CBD volume fraction results in a nonlinear increase in the effective electronic conductivity. To study the effect of CBD morphology, two stochastic CBD reconstruction techniques are proposed. The first method places new CBD voxels preferentially next to existing CBD voxels, and the second method deposits the CBD randomly in the pore space. The effective electronic conductivity for microstructures containing stochastic CBD morphologies is calculated and compared to that evaluated for microstructures with eroded and dilated CBD. The CBD generated stochastically results in a predicted higher effective electronic conductivity primarily due to a lower CBD tortuosity when compared to the CBD generated with morphological operations. Finally, the impact of CBD porosity on electrode tortuosity is studied by estimating the pore-phase tortuosity considering a solid and a porous CBD. The diffusivity of the porous CBD is estimated using multi-resolution FIB-SEM images. Results show that not accounting for the CBD porosity increases the electrode tortuosity by a factor of up to three at low electrode porosities. References [1] B. L. Trembacki, A. N. Mistry, D. R. Noble, M. E. Ferraro, P. P. Mukherjee, S. A. Roberts, Mesoscale analysis of conductive binder domain morphology in lithium-ion battery electrodes, Journal of The Electrochemical Society 165 (13) (2018) E725–E736 [2] Xu, Hongyi, et al. ‘Guiding the Design of Heterogeneous Electrode Microstructures for Li‐Ion Batteries: Microscopic Imaging, Predictive Modeling, and Machine Learning’. Advanced Energy Materials, vol. 11, no. 19, May 2021, p. 2003908. DOI.org (Crossref), https://doi.org/10.1002/aenm.202003908. Figure 1

AbstractEntangled quantum particles, in which operating on one particle instantaneously influences the state of the entangled particle, are attractive options for carrying quantum information at the nanoscale. However, fully-describing entanglement in traditional time-dependent quantum transport simulation approaches requires significant computational effort, bordering on being prohibitive. Considering electrons, one approach to analyzing their entanglement is through modeling the Coulomb interaction via the Wigner formalism. In this work, we reduce the computational complexity of the time evolution of two interacting electrons by resorting to reasonable approximations. In particular, we replace the Wigner potential of the electron–electron interaction by a local electrostatic field, which is introduced through the spectral decomposition of the potential. It is demonstrated that for some particular configurations of an electron–electron system, the introduced approximations are feasible. Purity, identified as the maximal coherence for a quantum state, is also analyzed and its corresponding analysis demonstrates that the entanglement due to the Coulomb interaction is well accounted for by the introduced local approximation.

Graphene and silicon are two prominent lithium-ion battery anode materials that have recently received a lot of attention. In this paper we have modelled and simulated the charge transport phenomena in Graphene on Si / SiO2 and SrTiO3 substrates. The Graphene monolayer's interface with the SrTiO3 (111) surface is analyzed using ab initio density-functional measurements. Both charge and heat flows are produced in solids, at the same time when an electrochemical potential is available, bringing about novel properties. The band structure and the electron dissolution process decide the Seebeck coefficient and electrical conductivity. It has been discovered that the interaction of Graphene with SiTiO3 accommodates electronic properties, Seebeck coefficient, and electronic conductivity. For the Graphene / SrTiO3 interface, the best values for the Seebeck coefficient were calculated. All the findings of this work suggest that the Graphene-SrTiO3 (111) and Graphene-Si structure could exhibit interesting quantum transport behavior.

Environmentally assisted cracking phenomena are widespread across the transport, defence, energy and construction sectors. However, predicting environmentally assisted fractures is a highly cross-disciplinary endeavour that requires resolving the multiple material-environment interactions taking place. In this manuscript, an overview is given of recent breakthroughs in the modelling of environmentally assisted cracking. The focus is on the opportunities created by two recent developments: phase field and multi-physics modelling. The possibilities enabled by the confluence of phase field methods and electro-chemo-mechanics modelling are discussed in the context of three environmental assisted cracking phenomena of particular engineering interest: hydrogen embrittlement, localised corrosion and corrosion fatigue. Mechanical processes such as deformation and fracture can be coupled with chemical phenomena like local reactions, ionic transport and hydrogen uptake and diffusion. Moreover, these can be combined with the prediction of an evolving interface, such as a growing pit or a crack, as dictated by a phase field variable that evolves based on thermodynamics and local kinetics. Suitable for both microstructural and continuum length scales, this new generation of simulation-based, multi-physics phase field models can open new modelling horizons and enable Virtual Testing in harmful environments.

Abstract The efficiency and effectiveness of the production system are influenced by the logistical arrangement of material flows. The smooth production, especially for assembly lines in the required quantity and at the required time (JIT or JIS systems), is currently ensured by automatically controlled towing sets (logistics trains), which consist of a tractor and several trucks. Another factor that affects the smooth production of assembly lines is the system of controlling the circulation of transport units. The number of transport units used in combination with the transport system significantly affects the efficiency of assembly workplaces. This article presents an analysis of the supply of assembly workplaces using a system of two shuttle boxes. The aim of this article is to investigate the influence of transport speed and capacity on the smoothness of the assembly process. Within the described analysis, the transport of 50,000 components is analyzed using a simulation model, while the length of the transport route is 32 km and 65 transport units per shift are used.

The article describes the modeling of two-dimensional supermolecular materials using ab initio methods. It discusses the results of studies on the atomic and electronic structure of Re6Se8Cl2 in bulk and two-dimensional form. It analyzes the difference in the effective masses of electrons and holes between these two types of materials, which is important for transport in nanoelectronics.

The transport of charge due to electric stimulus is the primary mechanism of actuation for a class of polymeric active materials known as ionomeric polymer transducers (IPTs). A two-dimensional ion hopping model has been built to describe ion transport in the IPT. In a Monte Carlo simulation, a square lattice of 50nm × 50nm is investigated containing 200 cations and 200 anions. Step voltages are applied between the electrodes of the IPT, causing the thermally-activated hopping between multiwell energy structures. The energy barrier height includes three parts: intrinsic energy, energy height due to the electric field and energy height due to ion-ion interactions. Periodic boundary conditions have been applied in the direction perpendicular to the electric field. The influence of the electrodes on both faces of IPT is formulated by the method of image charges. The charge density profile over the material has been calculated by the ion distribution in steady state. The Monte Carlo simulation is repeated multiple times to obtain an average result of the charge density. The averaged profile shows regions of cation depletion close to the anode, charge neutrality in the central part and ion accumulation close to the cathode, which qualitatively agrees with the results from conventional continuum models. To quantatively examine the Monte Carlo simulation of the ion hopping model, comparisons with a computational model of transport and electromechanical transduction are performed. This computational model is based upon a coupled chemo-electrical multi-field formulation and computes the spatio-temporal charge density profile to an applied potential at the boundaries. It can be seen that both methods, the statistical theory and the continuum theory, match quite well and are both able to represent the actual behavior inside the IPT. Moreover, experiments are performed to validate the current density calculated by the Monte Carlo simulation. The active material is Nafion 117 (Dupont) in the form of a cantilevered transducer with conductive electrodes on both surfaces and with mobile Na+ counter-ions. Voltage inputs are provided by a dSPACE DS 1102 DSP and amplified using an HP power amplifier. The current is measured by placing a small resistor in series with the sample, between the sample and ground. The voltage across the resistor is amplified and measured by dSPACE. The electrical current is calculated by dividing the voltage drop across the resistor by its resistance. Current density in both simulation results and experimental results exhibits an exponential decay over time.

Ionic winds are formed when air ions are drawn through the atmosphere by applied electric and/or magnetic fields. The ions collide with neutral air molecules, exchanging momentum, causing the neutral molecules to move. Continued collisions and momentum exchanges generate a net flow called an ionic wind [1]. Ionic winds formed near flat plates can produce local boundary layer distortion in the presence of a bulk flow. This concept has been studied experimentally at the macroscale as a method for drag reduction [2] and has been suggested at the microscale for convective cooling enhancement [3]. Specifically, microfabricated ion wind engines can be integrated onto electronic chips to provide additional local cooling at "hot-spot" locations. In our previous work, continuum modeling of the ionic wind phenomena showed an approximately 50% increase in the local heat transfer coefficient at the location of the ion wind engine [3]. However, in that work, ionization physics were not modeled, rather assumptions for ion current and concentrations were used as a basis for modeling ion transport. At the microscale, ionization occurs when field-emitted electrons from closely spaced electrodes collide with neutral air molecules, stripping away electrons and forming molecular ions. Geometric enhancement of the electrodes using nanostructured materials enables low ionization voltages conducive to microelectronic devices. Understanding the microscale ionization process is necessary to accurately predict the ensuing ionic wind and cooling. Direct Simulation Monte Carlo (DSMC) is used in the present work to predict field emission between two planar electrodes and the consequent ionization of the interstitial air.

Since its isolation in 2004, graphene has attracted the attention of many scientists due to its excellent transport and mechanical features. However, the use of this material in optoelectronics is limited since it has no bandgap. One can detour it by cutting a graphene sheet laterally. The new carbon nanostructure that emerges from this procedure is known as graphene nanoribbon (GNR). Nowadays, a quest to develop a viable production of these materials drives many researchers. Narita et al.[2] successfully synthesized a candidate using a bottom-up solution procedure, known as cove-type GNR. Despite all the promising attributes, the electronic transport mechanism of this material is so far unexplored. In this work, we investigated through computational simulations the electronic transport of the cove-type GNR. We did so by employing an extended two-dimensional SSH model [3] with a tight-binding effect (electron-phonon coupling). A self-consistent field method generates stationary states, while time evolution is conducted based on the Ehrenfest theorem. Results reveal the formation of two polarized regions after photoionization: a polaron and a bipolaron. These quasiparticles are mobile by the application of a uniform electric field, unveiling its role as a charge transporter. Finally, a semi-classical algorithm evaluates their mobility and effective mass. Calculations indicate that both structures have a low effective mass along with intrinsic mobility. Hence, the cove-type GNRs may be suitable to perform as highly efficient semiconductors in future applications. This study contributes as well to the theoretical understanding of confined quantum systems.