Related papers: Monolithic 3D Integration for Null Convention Logi…

An all-digital comparator with full input range is presented. It outperforms the nowaday all-digital comparators with its large rail-to-rail input range. This is achieved by the proposed Yin-yang balance mechanism between the two logic…

At sub-20nm technologies CMOS scaling faces severe challenges primarily due to fundamental device scaling limitations, interconnection overhead and complex manufacturing. Migration to 3D has been long sought as a possible pathway to…

Hybrid photonic integration exploits complementary strengths of different material platforms, thereby offering superior performance and design flexibility in comparison to monolithic approaches. This applies in particular to multi-chip…

Null collapse is an implosive process whereby MHD waves focus their energy in the vicinity of a null point, forming a current sheet and initiating magnetic reconnection. We consider, for the first time, the case of collapsing 3D magnetic…

We present dimensional circuit synthesis, a new method for generating digital logic circuits that improve the efficiency of training and inference of machine learning models from sensor data. The hardware accelerators that the method…

We demonstrated fabrication of black silicon with slanted nanocone array on both planar and 3D micro and meso scale structures produced by a high-throughput lithography-free oblique-angle plasma etching process. Nanocones with gradual…

Gate-all-around Vertical Nanowire Field Effect Transistors (VNWFET) are emerging devices, which are well suited to pursue scaling beyond lateral scaling limitations around 7nm. This work explores the relative merits and drawbacks of the…

Waveguide crossings represent one of the most critical components in very-large-scale photonic integration (VLSPI). Three-dimensional waveguide crossings, which distribute optical pathways across multiple planes, can achieve near-zero…

This paper proposes and evaluates a novel architecture for a low-power Time-to-Digital Converter with high resolution, optimized for both integration in multichannel chips and high rate operation (40 Mconversion/s/channel). This converter…

We investigate the modeling and simulation of ionic transport and charge conservation in lithium-ion batteries (LIBs) at the microscale. It is a multiphysics problem that involves a wide range of time scales. The associated computational…

We present a new asynchronous quasi-delay-insensitive (QDI) block carry lookahead adder with redundancy carry (BCLARC) realized using delay-insensitive dual-rail data encoding and 4-phase return-to-zero (RTZ) and 4-phase return-to-one (RTO)…

Recent years have seen an increasing interest in the development of artificial intelligence circuits and systems for edge computing applications. In-memory computing mixed-signal neuromorphic architectures provide promising ultra-low-power…

Quantum low-density parity-check (qLDPC) codes are a promising construction for drastically reducing the overhead of fault-tolerant quantum computing (FTQC) architectures. However, all of the known hardware implementations of these codes…

Convolutional Neural Networks (CNNs) have been regarded as the go-to models for visual recognition. More recently, convolution-free networks, based on multi-head self-attention (MSA) or multi-layer perceptrons (MLPs), become more and more…

In the past few years, we have witnessed an increased interest in the use of 2D materials for the realization of hybrid photonic nonlinear waveguides. Although graphene has attracted most of the attention, other families of 2D materials…

In semiconductor packaging, accurately recovering 3D information is crucial for non-destructive testing (NDT) to localize circuit defects. This paper presents a novel approach called the 3D Magnetic Inverse Routine (3D MIR), which leverages…

The atomistic-to-continuum (a/c) coupling methods, also known as the quasicontinuum (QC) methods, are a important class of concurrent multisacle methods for modeling and simulating materials with defects. The a/c methods aim to balance the…

Automating molecular design using deep reinforcement learning (RL) has the potential to greatly accelerate the search for novel materials. Despite recent progress on leveraging graph representations to design molecules, such methods are…

Prior studies have largely focused on quantum algorithms, often reducing parallel computing designs to abstract models or overly simplified circuits. This has contributed to the misconception that most applications are feasible only through…

Trapped-ion computing is a leading architecture in the pursuit of scalable and high fidelity quantum systems. Modular quantum architectures based on photonic interconnects offer a promising path for scaling trapped ion devices. In this…