Broadband image sensor array based on graphene–CMOS integration

Journal name:
Nature Photonics
Year published:
Published online


Integrated circuits based on complementary metal-oxide–semiconductors (CMOS) are at the heart of the technological revolution of the past 40 years, enabling compact and low-cost microelectronic circuits and imaging systems. However, the diversification of this platform into applications other than microcircuits and visible-light cameras has been impeded by the difficulty to combine semiconductors other than silicon with CMOS. Here, we report the monolithic integration of a CMOS integrated circuit with graphene, operating as a high-mobility phototransistor. We demonstrate a high-resolution, broadband image sensor and operate it as a digital camera that is sensitive to ultraviolet, visible and infrared light (300–2,000 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 terahertz frequencies.

At a glance


  1. Back-end-of-line CMOS integration of CVD graphene with 388 × 288 pixel image sensor read-out circuit.
    Figure 1: Back-end-of-line CMOS integration of CVD graphene with 388 × 288 pixel image sensor read-out circuit.

    a, Computer-rendered impression of the CVD graphene transfer process on a single die (real dimensions 15.1 mm height, 14.3 mm width) containing an image sensor read-out circuit that consists of 388 × 288 pixels. b, Side view explaining the graphene photoconductor and the underlying read-out circuit. The graphene channels are sensitized to ultraviolet, visible, near-infrared and short-wave infrared light with PbS CQDs: on 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 CQDs. The schematic represents the CTIA-based balanced read-out scheme per column and global correlated double sampling (CDS) stage and output driver. VDD, drain voltage; VSS, source voltage; VREF, reference voltage. c, 3D impression of the monolithic image sensor displaying the top level with graphene carved into S-shaped channels sensitized with a layer of quantum dots, vertical interconnects and underlying CMOS read-out circuitry. d, Photograph of the image sensor indicating the functionality for each area. To enhance contrast for different regions the photograph was taken before the CQDs were deposited. DAC, digital-to-analog converter. Middle: microscope image of the lower right corner of the active area of the ROIC. Right: scanning electron micrograph of the active area of the image sensor displaying the S-shaped graphene channels. Both images were taken before the CQDs were deposited.

  2. Hybrid graphene–CQD-based image sensor and digital camera system.
    Figure 2: Hybrid graphene–CQD-based image sensor and digital camera system.

    a, Digital camera set-up: the image sensor plus lens module captures the light reflected off objects that are illuminated by an external light source. Supplementary Fig. 3 contains all the details of the image-capturing set-up for each of the images shown. b, Near-infrared (NIR) and short-wave infrared (SWIR) light photograph of an apple and pear. An incandescent light source (1,000 W, 3,200 K) illuminated the objects. As this image sensor is sensitive to visible (VIS), NIR and SWIR light (300–1,850 nm; Fig. 4b), we placed a 1,100 nm long-pass filter in the optical path to reject all light that a conventional Si-CMOS sensor can capture. The tickmarks indicate the column (horizontal axis) and row (vertical axis) numbers. The illumination yielded an irradiance on the image sensor of ∼1 × 10−4 W cm–2. The greyscale represents the photosignal dV in volts (dV = Vout,light – Vout,dark; Supplementary Methods) normalized to dV obtained from a white reference image. An image-processing scheme, as described in the Supplementary Methods, was performed. c, VIS and NIR (this image sensor is sensitive to 300–1,000 nm; Fig. 4a) photograph of a standard image reference ‘Lena’ printed in black and white on paper illuminated with an LED desk lamp. d, VIS, NIR and SWIR photograph of a box of apples, illuminated with the same source as in b, but without the 1,100 nm long-pass filter. e,f, NIR and SWIR image of a rectangular block covered in fog (e) as shown in f, showing that fog is transparent for SWIR light. g,h, NIR and SWIR image of a rectangular block behind a silicon wafer (g) as shown in h, showing that silicon is transparent for SWIR light. i,j, NIR and SWIR image of a glass of water (i) as shown in j, showing that water absorbs SWIR light. For e,g,i, the same optical set-up as in b was used. A smartphone camera captured images f,h,j under office lighting conditions.

  3. Electro-optical characterization.
    Figure 3: Electro-optical characterization.

    a, Map of the conducting (blue) and non-conducting (grey) pixels. The dashed box indicates the area over which the yield was calculated. Inset: 3D bar plot of the total resistance per pixel (Rpixel + Rcomp) values for a 10 × 10 pixel area (green square). Green, Rpixel; blue, Rcomp. b, Histogram of Rpixel before resistance compensation and after compensation (Rpixel + Rcomp). Rcomp varies from 0 to 8 kΩ. c, Histogram of the NEI for all pixels inside the dashed box in a, plotted per column (in total 255 pixels for each column). Light blue, pixels that are sensitive to moonlight; dark blue, pixels that are sensitive to twilight; black, pixels that are not sensitive to light. d, Photoresponse versus power at uniform illumination with λ = 633 nm and measured from twilight (∼10−6 W cm–2) down to starlight (10−10–10−9 W cm–2) conditions. The green crosses are data obtained from a representative pixel in the image sensor. Blue and purple circles represent photoresponse (expressed in light-induced resistance change dR/R) of a reference photodetector with the same type of CQDs and a channel of 48 µm width and 8 µm length. The data points in blue are obtained using a d.c.-coupled amplifier with a bandwidth of 100 Hz. The data in purple are obtained using a lock-in-type measurement technique at 100 Hz modulation. The images below the plot illustrate the illumination conditions: from starlight to moonlight to twilight.

  4. Visible, near-infrared and short-wave infrared sensitivity, and night glow measurement.
    Figure 4: Visible, near-infrared and short-wave infrared sensitivity, and night glow measurement.

    a, Spectral dependence of the photoresponse for one of the pixels of the ROIC sensitized with quantum dots that have an exciton peak at 920 nm measured at a constant irradiance of 5 × 10−5 W cm–2. The solid blue line is a guide to the eye. Inset: absorbance spectrum of the quantum dots in solution. b, Spectral dependence of the photoresponse for one of the pixels of a ROIC sensitized with quantum dots that have an exciton peak at 1,670 nm measured at a constant irradiance of 10−4 W cm–2. Inset: absorbance spectrum of the quantum dots in solution. c, Measurement of the night glow in terms of normalized power spectral density SI/I2 using a SWIR-sensitive (exciton peak at 1,670 nm) reference photodetector of 1 × 1 mm2, aiming at a dark, clear sky for long-pass filtering with a cut-off at 1,100 nm and 1,400 nm (Supplementary Methods). The dashed lines indicate the noise level obtained with a lock-in measurement modulated at 10 Hz. The arrows denote the filter wavelength range used for collecting the data (blue bars). d, Photoresponse versus power for a reference photodetector illuminated with 1,550 nm light (blue crosses) and for the ROIC pixels in the SWIR regime, illuminated with 1,670 nm light (black crosses). The data points in blue are obtained using a d.c.-coupled amplifier with a bandwidth of 35 Hz. The reference photodetector exhibits an exciton peak at 1,580 nm and has a channel of 1 × 1 mm2. Inset: photocurrent versus time of the reference photodetector illuminated with 1,550 nm light at an irradiance of 3 × 10−5 W cm−2, sampled at 10 kS s−1.


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Author information

  1. These authors contributed equally to this work.

    • Stijn Goossens,
    • Gabriele Navickaite,
    • Carles Monasterio &
    • Shuchi Gupta


  1. ICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, 08860 Castelldefels (Barcelona), Spain

    • Stijn Goossens,
    • Gabriele Navickaite,
    • Carles Monasterio,
    • Shuchi Gupta,
    • Juan José Piqueras,
    • Raúl Pérez,
    • Gregory Burwell,
    • Ivan Nikitskiy,
    • Tania Lasanta,
    • Teresa Galán,
    • Eric Puma,
    • Gerasimos Konstantatos &
    • Frank Koppens
  2. Graphenea SA, 20018 Donostia-San Sebastian, Spain

    • Alba Centeno,
    • Amaia Pesquera &
    • Amaia Zurutuza
  3. ICREA – Institució Catalana de Recerça i Estudis Avançats, Lluis Companys 23, 08010 Barcelona, Spain

    • Gerasimos Konstantatos &
    • Frank Koppens


S.Go planned and supervised the experiments and wrote the manuscript. G.N. designed and fabricated all the devices and performed measurements. C.M. performed measurements and data analysis. S.Gu synthesized materials and contributed to material characterization. J.J.P. developed measurement procedures, and contributed to planning of the experiment. R.P. and G.B. developed fabrication procedures. T.G. and I.N. contributed to device fabrication and characterization. E.P. contributed to measurements. T.L. contributed to the synthesis of materials. A.C., A.P. and A.Z. provided materials. F.K. and G.K. supervised the study and wrote the manuscript. All authors provided input to data analysis, discussed the results and assisted in manuscript preparation.

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