# All-Solution-Processable Robust Carbon Nanotube Photo-Thermoelectric Devices for Multi-Modal Inspection Applications

## TL;DR

This paper reviews carbon nanotube-based sensors that can detect materials using millimeter-wave, terahertz, and infrared light for non-destructive inspection.

## Contribution

The paper introduces recent advances in carbon nanotube film-based photo-thermoelectric imagers for multi-modal inspection.

## Key findings

- Carbon nanotube sensors enable non-invasive material identification across MMW–IR wavelengths.
- These sensors offer sub-millimeter-resolution 3D reconstruction with high sensitivity.
- The integration of visible-light computer vision enhances material identification capabilities.

## Abstract

While recent industrial automation trends emphasize the importance of non-destructive inspection by material-identifying millimeter-wave, terahertz-wave, and infrared (MMW, THz, IR) monitoring, fundamental tools in these wavelength bands (such as sensors) are still immature. Although inorganic semiconductors serve as diverse sensors with well-established large-scale fine-processing fabrication, the use of those devices is insufficient for non-destructive monitoring due to the lack of photo-absorbent properties for such major materials in partial regions across MMW–IR wavelengths. To satisfy the inherent advantageous non-destructive MMW–IR material identification, ultrabroadband operation is indispensable for photo-sensors under compact structure, flexible designability, and sensitive performances. This review then introduces the recent advances of carbon nanotube film-based photo-thermoelectric imagers regarding usable and high-yield device fabrication techniques and scientific synergy among computer vision to collectively satisfy material identification with three-dimensional (3D) structure reconstruction. This review synergizes material science, printable electronics, high-yield fabrication, sensor devices, optical measurements, and imaging into guidelines as functional non-destructive inspection platforms. The motivation of this review is to introduce the recent scientific fusion of MMW–IR sensors with visible-light computer vision, and emphasize its significance (non-invasive material-identifying sub-millimeter-resolution 3D-reconstruction with 660 nm–1.15 mm-wavelength imagers at noise equivalent power within 100 pWHz−1/2) among the existing testing methods.