Abstract
Versatile, self-powered chemical sensing is essential for environmental monitoring, industrial safety and point-of-care diagnostics, yet remains challenging to realize in compact, fully autonomous systems. Here we present a platform that integrates graphene-based devices for chemical sensing, monolayer MoS2 logic circuits for on-chip digitization and a silicon photovoltaic module for energy harvesting. The graphene sensors detect a diverse set of analytes, including inorganic salts, alcohols and sugars, as well as liquids spanning wide ranges of physical properties such as viscosity and surface tension. We further demonstrate sensing of environmental pollutants and food-relevant and bio-relevant fluids, highlighting the platform’s versatility. The MoS2 circuitry converts analogue responses from the graphene sensors into stable digital outputs in real time, while the photovoltaic module powers both sensing and processing under ambient light. These results establish a pathway towards compact, deployable, self-powered chemical sensing systems for diverse real-world applications.
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Data availability
Datasets generated during and/or analysed during the current study are available from the corresponding author on request.
Code availability
The codes used for plotting the data are available from the corresponding author on request.
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Acknowledgements
S.D. acknowledges funding support from the National Science Foundation (NSF) for NSF Career under grant number ECCS-2042154, NSF Fuse, under grant number ECCS-2328741, Office of Naval Research under grant number N00014-24-1-2565 and Army Research Office under grant number W911NF-23-1-0279. The metal-organic chemical vapour deposition transition metal dichalcogenide films were grown in the 2D Crystal Consortium–Materials Innovation Platform (2DCC-MIP) facility, which is supported by the NSF under cooperative agreement no. DMR-2039351.
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S.D. conceived of the idea. S.G., P.V., A.C., M.S.A., A.R. and J.M.K. fabricated the devices. A.R., R.T.N., S.G., P.V., A.C. and S.D. measured the devices and performed the experiments. K.M. helped with the data analysis. A.R. and S.G. contributed equally. All authors contributed to the preparation of the paper.
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Nature Sensors thanks Sang-Hoon Bae, Hyeon-Jin Shin and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data
Extended Data Fig. 1 Graphene-based ion sensitive field effect transistor (ISFET).
a) Schematic and b) optical image of exemplary graphene ISFET. The device architecture employs an insulating capping layer over the source and drain contacts, leaving only the graphene channel exposed to the liquid. This configuration suppresses parasitic electrochemical reactions at the electrodes and ensures that signal modulation originates from the graphene/liquid interface. An integrated reference electrode, fabricated on-chip and in direct contact with the analyte, applies the gate potential, forming the EDL at the graphene/liquid interface that acts as an ultra-thin, high-capacitance dielectric. In liquid-gated operation, leakage currents can occur through the electrolyte; however, the high intrinsic conductivity of graphene ensures that the channel current dominates over leakage current, yielding a superior signal-to-noise ratio (\({\rm{SNR}}\)) compared to many other nanomaterials of similar dimensions.
Extended Data Fig. 2 Transient response of graphene ISFET.
Representative transfer curves and corresponding transient responses measured at a given VLTG for several analytes. A finite EDL formation time is observed on the order of one to few minutes, beyond which conductance stabilizes.
Extended Data Fig. 3 Signal to noise ratio (SNR) for graphene ISFET.
SNR evaluated as 20\(\log ({{\rm{I}}}_{{\rm{DS}}}/{{\rm{I}}}_{{\rm{G}}})\), where \({{\rm{I}}}_{{\rm{DS}}}\) is the source-to-drain and \({{\rm{I}}}_{{\rm{G}}}\) is the gate leakage current for graphene ISFETs corresponding to several analytes. The \({\rm{SNR}}\) values were found to be more than 40 dB for most analytes across the entire \({{\rm{V}}}_{{\rm{LTG}}}\) range.
Extended Data Fig. 4 Cycle-to-cycle repeatability for graphene ISFET.
Transfer curves of graphene ISFETs after randomized A–B–C–A–B–C (A: DI water, B: 100% Honey C: 10 mM KCl) exposure sequences. \({{\rm{V}}}_{{\rm{Dirac}}}\) and \({{\rm{I}}}_{{\rm{Dirac}}}\) were found to be consistent across repeated tests and recover to their original values when the same analyte is revisited.
Extended Data Fig. 5 Chemical response of graphene ISFET under ambient illumination.
Transfer curves of graphene ISFETs for honey measured in dark and under various indoor illuminations with no measurable change in chemical response.
Extended Data Fig. 6 Design of on-chip chemi-sensor based on graphene ISFETs.
a) Two graphene ISFETs (\({\rm{GI}}1\) and \({\rm{GI}}2\)) connected in series to convert the conductance modulation of graphene ISFETs into a voltage signal that can be directly digitized. The output is read as a voltage (\({{\rm{V}}}_{{\rm{GR}}}\)) at the common terminal. b) optical images of graphene channel in a serpentine layout and c) corresponding current versus voltage measurements for devices with \({{\rm{W}}}_{{\rm{CH}}}\)/\({{\rm{L}}}_{{\rm{CH}}}\) spanning 0.01 to 1. d) Time-resolved voltage readouts from the graphene chemi-sensor for representative analyte cases.
Extended Data Fig. 7 Switching speed of MoS2 based comparator.
The output transients for both logic transitions were found to be faster than the time resolution of the measurement set-up, which was 100 µs. Given that the EDL formation requires several seconds, the overall speed of our platform is limited by graphene chemo-sensor module than the MoS2 FET based compute module.
Extended Data Fig. 8 Graphene chemi-sensor response to ionic salt solutions.
\({{\rm{V}}}_{{\rm{GR}}}\) extracted at different \({{\rm{V}}}_{{\rm{LTG}}}\) for 1 mM solutions of NaCl, KCl, MgCl2, CaCl2, FeCl2, Na2CO3, Na2SO4, and NaNO3.
Extended Data Fig. 9 Programmable 2D Comparator.
Transfer characteristics of a MoS2-based programmable comparator demonstrating sharp transitions at multiple different switching thresholds with an interval of 50 mV.
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Supplementary Figs. 1–4, Note 1 and Table 1.
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Rasyotra, A., Ghosh, S., Nair, R.T. et al. Self-powered chemical sensing via graphene, MoS2 and silicon integration. Nat. Sens. (2026). https://doi.org/10.1038/s44460-026-00042-2
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DOI: https://doi.org/10.1038/s44460-026-00042-2
