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Detection of triboelectric discharges during dust events on Mars

Nature volume 647, pages 865–869 (2025)Cite this article

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Abstract

Lightning is among the most energetic manifestation of electrical activity in planetary atmospheres, with documented observations not only on Earth but also on Saturn and Jupiter1. On Mars, the existence of electrical activity has long been suspected2,3 but never directly demonstrated. The dusty atmosphere of Mars undergoes aeolian processes, ranging from wind-blown dust and sand, metre-to-hundred-metre-sized dust devils to thousand-kilometre-scale dust storms4, which, in Earth’s deserts, can become electrified through triboelectric charging5,6,7. For this reason, electric fields have been predicted to build up on Mars8,9,10, but with no measurement of Martian atmospheric electrical activity so far. Here we report in situ detections of triboelectric discharges, identified by their electrical and acoustic signatures captured by the SuperCam microphone aboard the Perseverance rover11,12. Fifty-five events have been detected over two Martian years, usually associated with dust devils and dust storm convective fronts. These serendipitous observations demonstrate that Martian electric fields can reach the breakdown threshold of the near-surface atmosphere of Mars, predicted to be on the order of several tens of kV m−1. Such electrical activity could affect dust dynamics13,14 and potentially fuel a reactive electrochemical environment enhancing the oxidizing capacity of the atmosphere, with consequences for the preservation of organic molecules15,16. This in situ evidence may have implications for surface chemistry, habitability and human exploration.

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Fig. 1: Microphone signals of triboelectric discharges.
Fig. 2: Seasonal context of the detected discharges.

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Data availability

All data from Perseverance used in this study are publicly available through the Planetary Data System: acoustic calibrated data from SuperCam can be found on the Geosciences node (https://doi.org/10.17189/1522646), MEDA calibrated on the Atmospheres node (https://doi.org/10.17189/1522849) and the Mars 2020 Perseverance Rover Navigation Cameras calibrated data products on the Imaging node (https://doi.org/10.17189/yvkm-rx37).

Code availability

The LTspice electronic model is not publicly available owing to intellectual property restrictions related to the circuit design but a detailed description of the model and its implementation on the LTspice software can be provided on request.

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Acknowledgements

We thank the Mars 2020 science, operation and engineering teams for their work to support the mission that has enabled the scientific research presented in this manuscript. This project was supported in the United States by the National Aeronautics and Space Administration’s Mars Exploration Program and in France is conducted under the authority of Centre National d’Etudes Spatiales. R.H. was supported by grant PID2023-149055NB-C31 financed by MICIU/AEI/10.13039/501100011033 and FEDER, UE and by Grupos de Investigacion del Gobierno Vasco IT-1366-19. We gratefully thank J.-J. Berthelier for his careful reading and insightful comments. We thank A. Cadu from ISAE-SUPAERO for his contribution to the design of the electronics of the microphone.

Author information

Authors and Affiliations

  1. Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse, CNRS, CNES, Toulouse, France

    Baptiste Chide, Sylvestre Maurice, Yann Parot, Pierre-Yves Meslin & Agnès Cousin

  2. Space Exploration Sector, Johns Hopkins Applied Physics Laboratory, Laurel, MD, USA

    Ralph D. Lorenz

  3. Laboratoire Atmosphères, Milieux, Observations Spatiale, CNRS, Université Saint-Quentin-en-Yvelines, Sorbonne Université, Guyancourt, France

    Franck Montmessin

  4. Física Aplicada, Escuela de Ingeniería de Bilbao, University of the Basque Country (UPV/EHU), Bilbao, Spain

    Ricardo Hueso & Agustin Sánchez-Lavega

  5. Centro de Astrobiología (INTA-CSIC), Madrid, Spain

    German Martinez & Alvaro Vicente-Retortillo

  6. Institut de Mécanique des Fluides, Université de Toulouse, INP, CNRS, Toulouse, France

    Xavier Jacob

  7. Space Science Institute, Boulder, CO, USA

    Mark Lemmon

  8. Observatoire Midi-Pyrénées, Université de Toulouse, Toulouse, France

    Bruno Dubois

  9. Aeolis Research, Chandler, AZ, USA

    Claire Newman

  10. Ulster University, Coleraine, UK

    Claire Newman

  11. LIRA, Observatoire de Paris, Université PSL, Sorbonne Université, Université Paris Cité, CY Cergy Paris Université, CNRS, Meudon, France

    Tanguy Bertrand

  12. European Space Research and Technology Centre (ESTEC), European Space Agency, Noordwijk, The Netherlands

    Grégoire Deprez

  13. Instituto Nacional de Técnica Aeroespacial (INTA), Madrid, Spain

    Daniel Toledo

  14. Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA

    Roger C. Wiens

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  1. Baptiste Chide
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Contributions

B.C. led the writing of the manuscript. B.C., R.D.L., F.M. and S.M. conceptualized the study and led the investigations. B.C., R.D.L., F.M., S.M., Y.P., R.H., G.M., A.V.-R., X.J., M.L. and B.D. contributed to the methodology, investigation and data processing. P.-Y.M., C.N., T.B., G.D., D.T. and A.S.-L. provided substantial contributions to the writing and reviewing of the manuscript. A.C. and R.C.W. are the leads of the SuperCam instrument investigation. All co-authors provided helpful comments and inputs to the manuscript.

Corresponding author

Correspondence to Baptiste Chide.

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The authors declare no competing interests.

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Nature thanks Giles Harrison, Daniel Mitchard who co-reviewed with Phillip Lugg-Widger, James Kasting and Armin Kleinboehl for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Coverage of the microphone recording during the first two Martian years of the Perseverance mission.

Each bar indicates the fraction of a given sol recorded by the microphone. On average, the microphone acquires one 167-s recording every two sols, which is a very small percent of time.

Extended Data Fig. 2 Coupling of magnetic field induced by a discharge with the SuperCam microphone.

a, Accommodation of the SuperCam microphone within the SuperCam Mast Unit. The microphone component is standing outside the housing of the instrument and is connected to its amplification electronics through two harnesses routed in a loop. This loop is probably where the electromagnetic field from the discharge interferes with the microphone subsystem (Methods section ‘Microphone response to an electromagnetic discharge’). b, Current waveform of a discharge (top) and the waveform of the induced voltage (bottom) defined as proportional to the derivative of the discharge current waveform.

Extended Data Fig. 3 Comparison between discharge and laser-induced acoustic signal.

Solid blue and red spectra represent the acoustic signal of discharges recorded on Sol 317 and Sol 1,296, respectively. Red spectrum is offset by a factor of 2 for display. The dotted blue spectrum corresponds to the noise floor of the instrument. They are compared with the average spectrum of SuperCam laser-induced acoustic signals (grey curve, offset by a factor 100) recorded for targets ablated at 3 m from the instrument (blast of approximately 0.5 Pa amplitude, comparable with the sound amplitude of the Sol 1,296 discharge). The two discharges are recorded at a sampling frequency of 25 kHz, whereas the laser-induced acoustic signal is recorded at a sampling frequency of 100 kHz (Methods section ‘Microphone data collection’). The similar lobed shape spectra indicate that the acoustic source is of the same nature, that is, a shock wave. Laser-induced acoustic spectrum and discharge spectra show the spectral notch around 6 kHz, indicative of the echo on the SuperCam housing.

Extended Data Fig. 4 Discharge generated with a Wimshurst machine recorded with the ground model of the SuperCam microphone.

a, A Wimshurst machine uses rotating discs and metal sectors to generate high voltage through triboelectric charging, storing the accumulated charge in capacitors (Leyden jars) for a subsequent discharge between the two spherical electrodes when they reach the air breakdown voltage. A discharge was generated in air, at ambient room conditions, for a distance between the two electrodes of 10 mm and a machine to microphone distance of about 1.2 m. This corresponds to a discharge energy on the order of tens of mJ (considering a capacitance of 100 pF and a breakdown potential of roughly 3 MV m−1). b, Time series of the microphone output signal in which the three electromagnetic (EM) signatures observed in the Mars data are reproduced: (1) spikes (around −15 and −5 ms); (2) the overshoot (at 0 ms); and (3) the relaxation, up to 10 ms. The acoustic signal is recorded at 3.5 ms with a long coda owing to the numerous echoes in the room in which the experiment was performed. Spikes occur during the charging of the capacitors while no arc between the two electrodes is seen. The overshoot and the relaxation are synchronized with the ignition of an arc discharge between the two electrodes. Amplitudes of the overshoot and the acoustic signal differ from Mars data owing to the different natures of the discharges (discharge current waveforms change as a result of the different properties of the background atmospheres) and sound propagation conditions. The characteristic time of the relaxation is longer than on Mars data, probably attributed to differences between the two sets of electronics.

Extended Data Fig. 5 Overpressure of the discharge-induced acoustic signal as a function of the distance of the discharge from the microphone.

The points indicated by an arrow represent saturated overpressure values. They are compared with overpressure profiles derived from the weak shock-wave propagation theory (Methods section ‘Discharge energy estimation’) computed for three different blast energies E0. The solid horizontal line represents the noise floor of the microphone at 2.5 mPa. As a consequence, discharges of 0.1 nJ cannot be recorded if they occur more than 70 cm away from the microphone.

Extended Data Fig. 6 Energy of a single grain discharge as a function of its size.

The energy of the discharge is computed as Egrain = 0.5qgrainEbdd, with Ebd = 25 kV m−1 the breakdown threshold potential for the Mars atmosphere and qgrain the charge of a single spherical grain of a given diameter, considering a charging density of about 10 µC kg−1 and a density of 2,500 kg m−3. d is the length of the discharge; 0.1, 1-mm and 10-mm examples are represented here.

Extended Data Fig. 7 Constraint on the sol 1,296 discharge length.

a, Measurement of Δt, the duration of the compression wave for the acoustic signal radiated from the discharge on sol 1,296. b, Assumed geometry of the discharge of length d, located at a distance r from the microphone, in an atmosphere having a sound speed c. The time delay Δt between the arrival time of the acoustic waves from the two ends of the discharge is computed as a function of r and d (Methods section ‘Constraint on the discharge length’).

Extended Data Fig. 8 Wind conditions from sound recording.

Distribution of wind intensity in microphone recording (blue, left axis) compared with the detection of discharges per wind bin (red, right axis). The wind intensity is computed as the root mean square pressure of the microphone signal in the 20–60-Hz frequency bandwidth31. This distribution is separated in three regimes: the low wind regime for wind intensity lower than 10−3 Pa, which corresponds to speed lower than 3 m s−1; the moderate wind regime from 10−3 to 10−2 Pa, which corresponds to wind speeds between 3 and 10 m s−1; and the high wind regime above 10−2 Pa, corresponding to speeds faster than 10 m s−1 (see ref. 31).

Extended Data Fig. 9 Acoustic and MEDA meteorological data during the detection of discharges.

a, Sol 215. b, Sol 1,296. The first row corresponds to the sound amplitude recorded by the microphone. Discharge signals are highlighted in red. The second row is a spectrogram (time–frequency) plot of the recording showing the wind signal at low frequency (<2 kHz) and the grain impacts signal around 3.5 kHz. The continuous tone at 870 Hz is radiated from the pumps of the rover. Spikes detected in these recordings are distinguished from grain impacts by their frequency content, which radiates at all frequencies. The third row is the static pressure as recorded by MEDA, showing the pressure drop associated with the passage of a dust devil. The fourth row is the air temperature as recorded by MEDA at a height of 1.45 m. The last row is the downwelling shortwave flux on the MEDA RDS Top-7 photodiode in W m−2. The dust carried by the dust devil locally above the rover induces a reduction of the flux during the passage of the dust devil. For Sol 1,296, the pressure and RDS acquisitions started only 5 and 11 s, respectively, after beginning microphone recording, losing the data from the approach phase of the dust devil.

Extended Data Fig. 10 Visibility of the northern fan during the dust event on sols 1,245 and 1,246.

Navcam images73 aimed at 72° are shown from Sols 1,242 (a), 1,245 (b), 1,246 (c) and 1,248 (d). The images show a 96° × 18° field of view looking towards the northern to eastern rim of Jezero crater and were taken with the NCAM00500 sequence. Low visibility around Sols 1,245 and 1,246 shows that there was an increase in boundary-layer dust despite the lack of increase in column optical depth. Note that the rover moved westward between the images.

Extended Data Table 1 Discharge parameters inferred from the sound signal characteristics
Full size table
Extended Data Table 2 Order of magnitude of common discharges
Full size table

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Chide, B., Lorenz, R.D., Montmessin, F. et al. Detection of triboelectric discharges during dust events on Mars. Nature 647, 865–869 (2025). https://doi.org/10.1038/s41586-025-09736-y

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