Research

Introduction

The goal of this work is to investigate how to maximally extract information from the photon field by combining the unique properties of different nanoscale materials, for optimal detection as well as pre-processing information as part of the sensing process, in order to sidestep the power-hungry electronic data transmission and computing bottleneck that would result from massive amounts of raw sensor data. Conventional sensor architectures transmit raw outputs to downstream electronics for analysis, leading to high power consumption and communication bottlenecks. In contrast, our design incorporates pre-processing at the sensor level, directly inspired by the bio-architecture of human vision.

In the retina, sensory cells and processing neurons are integrated, and the visual system transmits compact, pre-processed signals to the cortex rather than raw images, thus enabling our amazing vision within a tiny bandwidth and power budget, and with extreme sensitivity approaching or achieving in some cases single photon detection at room temperature. By mimicking this strategy with engineered nanoscale materials, we can both sense and process optical information at the point of capture, drastically reducing downstream computational load.

What is a nanoscale hybrid?

A nanoscale hybrid consists of multiple individual, low-dimensionality nanostructures, such as nanotubes, nanowires, and quantum dots, where each one is responsible for a different process in optoelectronic detection (absorption, transduction, amplification), in contrast to existing sensors where a single bulk material is asked to perform all tasks. By controlling the coupling between the components of a nanoscale hybrid, new paradigms for sensing can be achieved that go much beyond existing approaches.

Traditional imaging and sensing systems face a growing data bottleneck, where massive sensor outputs demand significant energy for transmission and computation. Our bio-inspired approach directly addresses these challenges by:

Reducing bandwidth requirements via local feature extraction and signal compression.

Achieving extreme sensitivity, including the potential for single-photon-level operation at room temperature.

Lowering power consumption, enabling scalable deployment in distributed or embedded sensing platforms.

Research objectives

Our primary objective is to understand and demonstrate the photon sensing and energy-efficient processing performance possible with nanoscale hybrids.

In order to achieve this, we will work on the research and development of:

Concepts and theory for energy-efficient photonic processing and sensing
Modeling capabilities for co-design of nanomaterial elements with CMOS readout and control circuitry
Novel low dimensional nanomaterial hybrids with controlled properties
CMOS-compatible heterogeneous integration

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