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Large spiking neural networks (SNNs) require ultra-low power and low variability hardware for neuromorphic computing applications. Recently, a band-to-band tunneling-based (BTBT) integrator, enabling sub-kHz operation of neurons with area…

The band-to-band tunneling transistors have some performance advantages over the conventional MOSFETs due to the <60mV/dec sub-threshold slope. In this paper, carbon nanotubes are used as a model channel material to address issues that we…

We present a TCAD compatible multiscale model of phonon-assisted band-to-band tunneling (BTBT) in semiconductors, that incorporates the non-parabolic nature of complex bands within the bandgap of the material. This model is shown capture…

Energy-efficient methods are addressed for leveraging low energy barrier nanomagnetic devices within neuromorphic architectures. Using a Magnetoresistive Random Access Memory (MRAM) probabilistic device (p-bit) as the basis of neuronal…

We investigate the different transport mechanisms that can occur in pn junction devices made using atomic precision advanced manufacturing (APAM) at temperatures ranging from cryogenic to room temperature. We first elucidate the potential…

Magnetic Random-Access Memory (MRAM) based p-bit neuromorphic computing devices are garnering increasing interest as a means to compactly and efficiently realize machine learning operations in Restricted Boltzmann Machines (RBMs). When…

Field-effect transistors based on band-to-band tunneling (BTBT) have gained a lot of recent interest due to their potential for reducing power dissipation in integrated circuits. In this paper we present a detailed performance comparison…

Despite the outstanding performance of transformers in both language and vision tasks, the expanding computation and model size have increased the demand for efficient deployment. To address the heavy computation and parameter drawbacks,…

The human brain comprises about a hundred billion neurons connected through quadrillion synapses. Spiking Neural Networks (SNNs) take inspiration from the brain to model complex cognitive and learning tasks. Neuromorphic engineering…

Determining the steady state of an open quantum system is crucial for characterizing quantum devices and studying various physical phenomena. Often, computing a single steady state is insufficient, and it is necessary to explore its…

We propose a Heterojunction Vertical Tunneling FET and show using self-consistent ballistic quantum transport simulations that it can provide very steep subthreshold swings and high ON current, thereby improving the scalability of Tunnel…

Reliability issues stemming from device level non-idealities of non-volatile emerging technologies like ferroelectric field-effect transistors (FeFET), especially at scaled dimensions, cause substantial degradation in the accuracy of…

We provide a detailed study of the interface Trap Assisted Tunneling (TAT) mechanism in tunnel field effect transistors to show how it contributes a major leakage current path before the Band To Band Tunneling (BTBT) is initiated. With a…

Flexible-grid Elastic Optical Networks (EONs) have been widely deployed in recent years to support the growing demand for bandwidth-intensive applications. To address this cost-efficiently, optimized utilization of EONs is required.…

Deploying Vision Transformers (ViTs) on near-sensor analog accelerators demands training pipelines that are explicitly aligned with device-level noise and energy constraints. We introduce a compact framework for silicon-photonic execution…

The performance and reliability of Ultra-Low-Power (ULP) computing platforms are adversely affected by environmental temperature and process variations. Mitigating the effect of these phenomena becomes crucial when these devices operate…

Band-to-band tunneling (BTBT) devices have recently gained a lot of interest due to their potential for reducing power dissipation in integrated circuits. We have performed extensive simulations for the BTBT operation of carbon nanotube…

In molecular charge transport, transition voltage spectroscopy (TVS) holds the promise that molecular energy levels can be explored at bias voltages lower than required for resonant tunneling. We investigate the theoretical basis of this…

Quantum tunneling dominates coherent transport at low temperatures in many systems of great interest. In this work we report a many--body tunneling (MBT), by nonperturbatively solving the Anderson multi-impurity model, and identify it a…

This paper presents a PVT-resilient, subthreshold SRAM-based computing-in-memory (CIM) macro tailored for energy-efficient spiking neural networks (SNNs). The macro integrates in-situ current sensors and distributed voltage regulators to…