Gerhard Klimeck

A topological phase transition in high-temperature superconductor FeTe1−xSex, occurring at a critical range of Se concentration x, underlies their intrinsic topological superconductivity and emergence of Majorana states within vortices. However, how Se concentration and distribution determine the electronic states, particularly the presence or absence of Majorana states, in FeTe1−xSex remains unclear. In this study, we combine density functional theory calculations with pz–dxz/yz-based analysis and Wannier-based Hamiltonian analysis to systematically explore the electronic structures of diverse FeTe1−xSex compositions. Our investigation reveals a nonlinear variation of the spin–orbit coupling (SOC) gap between pz and dxz/yz bands in response to the Se concentration x, with the maximum gap occurring at x = 0.5. The pz–pz and dx2−y2–pz interactions are found to be critical for pd band inversion. Furthermore, the distribution of Se significantly modulates the SOC gap, thereby influencing the emergence of Majorana states within local vortices.

nanoHUB is an open cyber platform for online simulation, data, and education that seeks to make scientific software and associated data widely available and useful. This paper describes recent developments in our simulation infrastructure to address modern data needs. nanoHUB's Sim2Ls (pronounced sim tools) make simulation, modeling, and data workflows discoverable and accessible to all users for cloud computing using standard APIs. In addition, published tools are findable (with digital object identifiers), reusable (via documented requirements and services), and reproducible via containerization. In addition, all Sim2L runs are automatically cached, and their results indexed into a global and queryable database (ResultsDB). We believe this infrastructure significantly lowers the barriers towards making simulation/data workflows and their data findable, accessible, interoperable, and reusable (FAIR). This frictionless access to simulations and data enables researchers, instructors, and students to focus on the application of these products to advance their fields.

The research landscape has become increasingly interdisciplinary and complex with novel hardware, software, data, and lab instruments. Reproducibility of research results, the usability of tools, and sharing of methods are all crucial for timely collaboration for research and teaching. Hubzero is a widely used science gateway framework designed to support online communities with efficient sharing and publication processes. The paper discusses the growth of communities for the four science gateways nanoHUB, MyGeoHub, QUBEShub, and HubICL using the Hubzero Platform to foster open science and tackling education with a diverse set of approaches and target communities.

This article describes a teaching strategy that synergizes computing and management, aimed at the running of complex projects in industry and academia, in the areas of civil engineering, physics, geosciences, and a number of other related fields. The course derived from this strategy includes four parts: (a) Computing with a selected set of modern paradigms—the stress is on Control Flow and Data Flow computing paradigms, but paradigms conditionally referred to as Energy Flow and Diffusion Flow are also covered; (b) Project management that is holistic—the stress is on the wide plethora of issues spanning from the preparation of project proposals, all the way to incorporation activities to follow after the completion of a successful project; (c) Examples from past research and development experiences—the stress is on experiences of leading experts from academia and industry; (d) Student projects that stimulate creativity—the stress is on methods that educators could use to induce and accelerate the creativity of students in general. Finally, the article ends with selected pearls of wisdom that could be treated as suggestions for further elaboration.

This article presents a taxonomy and represents a repository of open problems in computing for numerically and logically intensive problems in a number of disciplines that have to synergize for the best performance of simulation-based feasibility studies on nature-oriented engineering in general and civil engineering in particular. Topics include but are not limited to: Nature-based construction, genomics supporting nature-based construction, earthquake engineering, and other types of geophysical disaster prevention activities, as well as the studies of processes and materials of interest for the above. In all these fields, problems are discussed that generate huge amounts of Big Data and are characterized with mathematically highly complex Iterative Algorithms. In the domain of applications, it has been stressed that problems could be made less computationally demanding if the number of computing iterations is made smaller (with the help of Artificial Intelligence or Conditional Algorithms), or if each computing iteration is made shorter in time (with the help of Data Filtration and Data Quantization). In the domain of computing, it has been stressed that computing could be made more powerful if the implementation technology is changed (Si, GaAs, etc.…), or if the computing paradigm is changed (Control Flow, Data Flow, etc.…).

Triple heterojunction (THJ) tunneling field-effect transistors (TFETs) have been proposed to resolve the low ON-current challenge of TFETs. However, the design space for THJ-TFETs is limited by fabrication challenges with respect to device dimensions and material interfaces. This work shows that the original THJ-TFET design with 12-nm body thickness has poor performance because its subthreshold swing (SS) is 50 mV/decade and the ON-current is only $6~\mu A/\mu m$ . To improve the performance, the doping profile of THJ-TFET is engineered to boost the resonant tunneling efficiency. The proposed THJ-TFET design shows an SS of 40 mV/decade over four orders of drain current and an ON-current of $325~\mu A/\mu m$ with ${V}_{\textit {GS}} =0.3$ V. Since THJ-TFETs have multiple quantum wells and material interfaces in the tunneling junction, quantum transport simulations in such devices are complicated. State-of-the-art mode-space quantum transport simulation, including the effect of thermalization and scattering, is employed in this work to optimize THJ-TFET design.

The triple heterojunction tunnel field-effect transistor (TFET) has been originally proposed to resolve the TFET’s low ON-current challenge. The carrier transport in such devices is complicated due to the presence of quantum wells and strong scattering. Hence, the full-band atomistic nonequilibrium Green’s function (NEGF) approach, including scattering, is required to model the carrier transport accurately. However, such simulations for devices with realistic dimensions are computationally unfeasible. To mitigate this issue, we have employed the empirical tight-binding mode-space approximation to simulate the triple heterojunction TFETs with the body thickness up to 12 nm. The triple heterojunction TFET design is optimized using the model to achieve a sub-60-mV/decade transfer characteristic under realistic scattering conditions.

The nonequilibrium Green's function (NEGF) method with Büttiker probe scattering self-energies is assessed by comparing its predictions for the thermal boundary resistance with molecular dynamics (MD) simulations. For simplicity, the interface of Si/heavy-Si is considered, where heavy-Si differs from Si only in the mass value. With Büttiker probe scattering parameters tuned against MD in homogeneous Si, the NEGF-predicted thermal boundary resistance quantitatively agrees with MD for wide mass ratios. Artificial resistances that the unaltered Landauer approach yields at virtual interfaces in homogeneous systems are absent in the present NEGF approach. Spectral information results from NEGF in its natural representation without further transformations. The spectral results show that the scattering between different phonon modes plays a crucial role in thermal transport across interfaces. Büttiker probes provide an efficient and reliable way to include anharmonicity in phonon related NEGF. NEGF including the Büttiker probes can reliably predict phonon transport across interfaces and at finite temperatures.

Being fundamentally limited to a current-voltage steepness of 60mV/dec, MOSFETs struggle to operate below 0.6 V. Further reduction in V _DD and, consequently, power consumption can be achieved with novel devices, such as tunneling transistors (TFETs) that can overcome this limitation. TFETs, however, face challenges with low ON-current leading to slow performance. TFETs made from III-nitride heterostructures are quite promising in this regard. The lattice mismatch induces a piezoelectric polarization field in a nitride heterojunction that can boost the ON-current. However, it is shown here that the carrier thermalization at the heterointerface degrades the subthreshold characteristics. Therefore, a good design should minimize the number of confined quantum well (QW) states at the heterointerface so as not to degrade the subthreshold characteristics while maintaining the lattice mismatch induced polarization to boost the ON-current. We show here that an InAlN QW on an InGaN substrate alloy engineered TFET design is promising to fulfill these requirements. Proper engineering of the alloy mole fractions and the width of the well can eliminate (or at least minimize) the undesired thermalization effects and, at the same time, provide a lattice mismatch to induce a piezoelectric field for boosting the ON-current. We have used a suitable atomistic quantum transport model to simulate these devices. The model accounts for the different mechanisms that are involved, and captures realistic scattering thermalization effects. This model has been benchmarked in our earlier work with experimental measurements of nitride tunneling heterojunction diodes and is used here to optimize the alloy engineered nitride TFET.

The 2-D material-based TFETs are among the most promising candidates for low-power electronics applications since they offer ultimate gate control and high-current drives that are achievable through small tunneling distances (Λ) during the device operation. The ideal device is characterized by a minimized Λ. However, devices with the thinnest possible body do not necessarily provide the best performance. For example, reducing the channel thickness (T _ch ) increases the depletion width in the source, which can be a significant part of the total Λ. Hence, it is important to determine the optimum T _ch for each channel material individually. In this paper, we study the optimum T _ch for three channel materials: WSe ₂ , black phosphorus, and InAs using full-band self-consistent quantum transport simulations. To identify the ideal T _ch for each material at a specific doping density, a new analytic model is proposed and benchmarked against the numerical simulations.