From the abstract:
"Here, we show for the first time the monolithic integration of a CMOS integrated circuit with graphene, operating as a high mobility phototransistor. We demonstrate a high-resolution image sensor and operate it as a digital camera that is sensitive to UV, visible and infrared light (300 – 2000 nm). The demonstrated graphene-CMOS integration is pivotal for incorporating 2d materials into the next generation microelectronics, sensor arrays, low-power integrated photonics and CMOS imaging systems covering visible, infrared and even terahertz frequencies."
At a closer look, the sensing layer is, actually, "PbS colloidal quantum dots: upon light absorption an electron-hole pair is generated, due to the built in electric field the hole transfers to the graphene while the electron remains trapped in the quantum dots:"
"Due to the high mobility of graphene (here ~1000 cm2/Vs), this photoconductor structure exhibits ultra-high gain of 10^8 and responsivity above 10^7 A/W, which is a strong improvement compared to photodetectors and imaging systems based on quantum dots only."
The sample images are quite nice for a first graphene image sensor ever produced:
"Future graphene-based image sensors can be designed to operate at higher resolution, in a broader wavelength range, and potentially even with a form factor that fits inside a smartphone or smartwatch (Supplementary Notes, Figure S9). In contrast to current hybrid imaging technologies (which are not monolithic), we do not encounter fundamental limits with respect to shrinking the pixel size and increasing the imager resolution. Graphene patterning and contacting, i.e. lithography, will ultimately be the limiting factor. Therefore, competitively performing image sensors with multi-megapixel resolutions and pixel pitches down to 1 µm are within reach."
A somewhat similar paper, albeit from different authors, is going to be presented at ISSCC 2017 Session 15 on Feb. 7:
"15.7 Heterogeneous Integrated CMOS-Graphene Sensor Array for Dopamine Detection," B. Nasri, T. Wu, A. Alharbi, M. Gupta, R. Ranjit Kumar, S. Sebastian, Y. Wang, R. Kiani, D. Shahrjerdi, New York University, Brooklyn, NY.
