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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.

Copper nanowires are widely used as on-chip interconnects due to their superior conductivity. However, with aggressive Cu interconnect scaling, surface scattering of electrons drastically increases the electrical resistivity. In this work, we have studied the electrical performance of Cu thin films deposited on different materials. By comparing the thickness dependence of Cu films' resistivity on MoS2 and SiO2, we have demonstrated that MoS2 can be used to enhance the electrical performance of ultrathin Cu films due to improved specular surface scattering by up to 40%. By fitting the experimental data with the theoretical Fuchs-Sondheimer (FS) model, we have determined the specularity parameter at the Cu/MoS2 interface to be p ≈ 0.4 at room temperature. Furthermore, first principle calculations based on density functional theory (DFT) indicate that the localized density of states (LDOS) at the Cu/amorphous SiO2 interface is larger than the LDOS at the Cu/MoS2 interface, which is believed to be responsible for the higher resistivity in the Cu thin films that are deposited on SiO2 substrates. Our results suggest that MoS2 may serve as a performance enhancer for future generations of Cu interconnects.

We investigate the performance of 5-nm gate length GaN nMOS nanowire field effect transistor (GaN-NW-nFET) of various geometrical shapes, around the limits of cross-sectional scalability, using atomistic quantum transport simulations. For square cross-sections, the benchmarking results with the simulated Si-NW-nFET reveal over 30% enhancement in GaN drive current in both low standby power (LP − $I_{ \mathrm{\scriptscriptstyle OFF}}=1$ nA/ $\mu \text{m}$ ) and high performance (HP − $I_{ \mathrm{\scriptscriptstyle OFF}}=100$ nA/ $\mu \text{m}$ ) applications. Further performance enhancement is observed with the use of non-square geometries that are akin to GaN’s wurtzite crystal structure. Particularly, for ${T}_{\text {nw}}=2.4 $ mn, triangular cross-section GaN-NW-nFETs exhibit the smallest subthreshold swing, down to 62 mv/decade, excellent drive current, ${I}_{\text {DSAT}} > 2\times 10^{6}\,\, \mu \text {A}/ \mu \text {m}^{2}$ and superior energy-delay product compared to simulated Si-NW-nFET.

Being fundamentally limited to a current–voltage steepness of 60mV/dec, MOSFETs struggle to operate below 0.6 V. Further reduction in ${V}_{\text {DD}}$ 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.

This paper introduces a conceptual 100BillionTransistor (100BT) SuperComputers-on-a-Chip consisting of N big multi-core processors, 1000N small many-core processors, and two hardware accelerators - an ASIC TPU-like fixed-structure systolic array accelerator and a FPGA based flexible-structure re-programmable accelerator for bandwidth-bound and latency-critical Machine Learning applications respectively. The proposed SuperComputers-on-a-chip concept requires interfaces to specific external accelerators based on Quantum, Optical, Molecular, and Biological paradigms (programmable using EnergyFlow programming models - Energy Flow also representing a concept introduced in this paper) but these issues are outside the scope of this article. Keywords - Accelerators, Big Data, ControlFlow, DataFlow, ManyCore, Machine Learning, MultiCore, Systolic Array.

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 metal-semiconductor contact resistivity has started to play a critical role for the overall device performance as Si is reaching 10-nm size ranges. The International Technology Roadmap for Semiconductors (ITRS) target predicts a requirement of $\text{10}^{-9} \; \Omega {\cdot} \text{cm}^{2}$ by 2023 which has been a challenging target to achieve. This paper explores the impact of doping concentration, Schottky barrier height, strain, and SiGe mole fraction on the resistivity of Si/SiGe p-type metal-oxide semiconductor (PMOS) contacts with 20-band atomistic tight binding quantum transport simulations. Commonly used simple effective mass approximation models are shown to overestimate the resistivity values. The predicted model results are compared with experimental data and the device parameters needed to achieve $\text{10}^{-9} \; \Omega {\cdot} \text{cm}^{2}$ are identified.

In this work, vertical tunnel field-effect transistors (v-TFETs) based on vertically stacked heretojunctions from 2D transition metal dichalcogenide (TMD) materials are studied by atomistic quantum transport simulations. The switching mechanism of v-TFET is found to be different from previous predictions. As a consequence of this switching mechanism, the extension region, where the materials are not stacked over is found to be critical for turning off the v-TFET. This extension region makes the scaling of v-TFETs challenging. In addition, due to the presence of both positive and negative charges inside the channel, v-TFETs also exhibit negative capacitance. As a result, v-TFETs have good energy-delay products and are one of the promising candidates for low power applications., Comment: didn't reach to co-author agreement

Low-dimensional material systems provide a unique set of properties useful for solid-state devices. The building block of these devices is the p-n junction. In this paper, we present a dramatic difference in the electrostatics of p-n junctions in lower dimensional systems, as against the well understood three dimensional (3-D) systems. Reducing the dimensionality increases the depletion width significantly. We propose a novel method to derive analytic equations in 2-D and 1-D that considers the impact of neutral regions. The analytical results show an excellent match with both the experimental measurements and numerical simulations. The square root dependence of the depletion width on the ratio of dielectric constant and doping in 3-D changes to a linear and exponential dependence for 2-D and 1-D, respectively. This higher sensitivity of 1-D p-n junctions to its control parameters can be used toward new sensors. Utilizing the unconventional electrostatics of these low-dimensional junctions for sensing and switching applications has been discussed and a novel sensor is proposed.

Controlled, tunable, and reversible negative-differential resistance (NDR) is observed in lithographically defined, atomically thin semiconducting graphene nanoribbon (GNR)-gated Esaki diode transistors at room temperature. Sub-10 nm-wide GNRs patterned by electron-beam lithography exhibit semiconducting energy bandgaps of ~0.2 eV extracted by electrical conductance spectroscopy measurements, indicating an atomically thin realization of the electronic properties of conventional 3D narrow-bandgap semiconductors such as InSb. A p–n junction is then formed in the GNR channel by electrostatic doping using graphene side gates, boosted by ions in a solid polymer electrolyte. Transistor characteristics of this gated GNR p–n junction exhibit reproducible and reversible NDR due to interband tunneling of carriers. All essential experimentally observed features are explained by an analytical model and are corroborated by a numerical atomistic simulation. The observation of tunable NDR in GNRs is conclusive proof of the existence of a lithographically defined bandgap and the thinnest possible realization of an Esaki diode. It paves the way for the thinnest scalable manifestation of low-power tunneling field-effect transistors (TFETs).

In semiconductor physics, interaction of electrons with environmental disorder (phonons, impurity atoms, or other electrons) is important in shaping the band structure. These interactions result in ``tailing'' of the density of states near band edges, and band-gap narrowing. Using atomistic transport calculations with nonlocal scattering, this study assesses the impact of two important effects on band tailing and gap narrowing in $I\phantom{\rule{0}{0ex}}I\phantom{\rule{0}{0ex}}I\ensuremath{-}V$ compounds. Theoreticians modeling nanodevices will appreciate the benchmarked scattering models and formulas, while the predictions of band-gap narrowing and Urbach tails will appeal to experimentalists as they quantify their creations.

The non-equilibrium Green's function (NEGF) method with B\"uttiker 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 B\"uttiker 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 yield at virtual interfaces in homogeneous systems are absent in the present NEGF approach. Spectral information result 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. B\"uttiker probes provide an efficient and reliable way to include anharmonicity in phonon related NEGF. NEGF including the B\"uttiker probes can reliably predict phonon transport across interfaces and at finite temperatures., Comment: 4 pages, 5 figures

Copper nanowires are widely used as on-chip interconnects due to their superior conductivity. However, with aggressive Cu interconnect scaling, surface scattering of electrons drastically increases the electrical resistivity. In this work, we have studied the electrical performance of Cu thin films deposited on different materials. By comparing the thickness dependence of Cu films' resistivity on MoS

In this paper, electrostatically configurable 2D tungsten diselenide (WSe

Modern science has become collaborative and digital. The Internet has supported the emergence of scientific digital platforms that globally connect programmers and users of novel digital scientific products such as scientific interactive software tools. These digital scientific innovations complement traditional text-based products like journal publications. This article is focused on the scientific impact of a platform's programming community that produces these digital scientific innovations. The article's main theoretical argument is that beyond an individual's contribution efforts to these innovations, a new social structure affects his scientific recognition through citations of his tools in text-based publications. Taking a practice theory lens, we introduce the concept of a digital practice structure that emerges from the digital innovation work practice, performed by programmers who jointly work on a tool. This digital practice creates dependence forces among the community members in an analogy to Newton's gravity concept. Our model represents such dependencies in a spatial autocorrelative model. We empirically estimate this model using data of the programming community of nanoHUB in which 477 nanotechnology tool programmers have contributed more than 715 million lines of code. Our results show that a programmer's contributions to digital innovations may have positive effects, while the digital practice structure creates negative dependency effects. Colloquially speaking, being surrounded by star performers can be harmful. Our findings suggest that modeling scientific impact needs to account for a scientist's contribution to programming communities that produce digital scientific innovations and the digital work structures in which these contributions are embedded.