Designing materials to function in harsh environments, such as conductive aqueous media, is a problem of broad interest to a range of technologies, including energy, ocean monitoring and biological applications1,2,3,4. The main challenge is to retain the stability and morphology of the material as it interacts dynamically with the surrounding environment. Materials that respond to mild stimuli through collective phase transitions and amplify signals could open up new avenues for sensing. Here we present the discovery of an electric-field-driven, water-mediated reversible phase change in a perovskite-structured nickelate, SmNiO35,6,7. This prototypical strongly correlated quantum material is stable in salt water, does not corrode, and allows exchange of protons with the surrounding water at ambient temperature, with the concurrent modification in electrical resistance and optical properties being capable of multi-modal readout. Besides operating both as thermistors and pH sensors, devices made of this material can detect sub-volt electric potentials in salt water. We postulate that such devices could be used in oceanic environments for monitoring electrical signals from various maritime vessels and sea creatures.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Nature Communications Open Access 03 August 2022
Nature Communications Open Access 07 May 2020
Nature Communications Open Access 14 February 2020
Subscribe to Nature+
Get immediate online access to Nature and 55 other Nature journal
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
Chen, Y. W. et al. Atomic layer-deposited tunnel oxide stabilizes silicon photoanodes for water oxidation. Nat. Mater. 10, 539–544 (2011)
Uhlig, H. H. in Uhlig’s Corrosion Handbook 3rd edn (ed. Revie, R. W. ) Ch. 51 (John Wiley & Sons, 2011)
Yuh, J. Design and control of autonomous underwater robots: a survey. Auton. Robots 8, 7–24 (2000)
Robison, B. H. Deep pelagic biology. J. Exp. Mar. Biol. Ecol. 300, 253–272 (2004)
Medarde, M. L. Structural, magnetic and electronic properties of RNiO3 perovskites (R= rare earth). J. Phys. Condens. Matter 9, 1679–1707 (1997)
Middey, S. et al. Physics of ultrathin films and heterostructures of rare-earth nickelates. Annu. Rev. Mater. Res. 46, 305–334 (2016)
Catalan, G. Progress in perovskite nickelate research. Phase Transit. 81, 729–749 (2008)
Zhou, Y. et al. Strongly correlated perovskite fuel cells. Nature 534, 231–234 (2016)
Kritzer, P. Corrosion in high-temperature and supercritical water and aqueous solutions: a review. J. Supercrit. Fluids 29, 1–29 (2004)
Pelloquin, D., Barrier, N., Maignan, A. & Caignaert, V. Reactivity in air of the Sr3Co2O7-δ RP= 2 phase: formation of the hydrated Sr3Co2O5(OH)2·xH2O cobaltite. Solid State Sci. 7, 853–860 (2005)
Bedore, C. N. & Kajiura, S. M. Bioelectric fields of marine organisms: voltage and frequency contributions to detectability by electroreceptive predators. Physiol. Biochem. Zool. 86, 298–311 (2013)
Baron, V. D. Electric discharges of two species of stargazers from the South China Sea (Uranoscopidae, Perciformes). J. Ichthyol. 49, 1065–1072 (2009)
Hirota, M. A method to measure ship’s underwater electric field from deck. In Proc. 2000 Int. Symp. on ‘Underwater Technology’ 224–228 (IEEE, 2000); http://ieeexplore.ieee.org/document/852547/
Kim, J.-G., Joo, J.-H. & Koo, S.-J. Development of high-driving potential and high-efficiency Mg-based sacrificial anodes for cathodic protection. J. Mater. Sci. Lett. 19, 477–479 (2000)
Bennett, M. V. L., Wurzel, M. & Grundfest, H. The electrophysiology of electric organs of marine electric fishes. J. Gen. Physiol. 44, 757–804 (1961)
Mathewson, R., Mauro, A., Amatniek, E. & Grundfest, H. Morphology of main and accessory electric organs of Narcine brasiliensis (Olfers) and some correlations with their electrophysiological properties. Biol. Bull. 115, 126–135 (1958)
Kalmijn, A. J. The electric sense of sharks and rays. J. Exp. Biol. 55, 371–383 (1971)
Kalmijn, A. J. Electric and magnetic field detection in elasmobranch fishes. Science 218, 916–918 (1982)
Bellono, N. W., Leitch, D. B. & Julius, D. Molecular basis of ancestral vertebrate electroreception. Nature 543, 391–396 (2017)
Fields, R. D. The shark’s electric sense. Sci. Am. 297, 74–81 (2007)
Josberger, E. E. et al. Proton conductivity in ampullae of Lorenzini jelly. Sci. Adv. 2, e1600112 (2016)
Brown, B. R. Sensing temperature without ion channels. Nature 421, 495 (2003)
Bard, A. J ., Faulkner, L. R ., Leddy, J . & Zoski, C. G. Electrochemical Methods: Fundamentals and Applications 1st edn, Vol. 2 (Wiley, 1980)
Daillant, J. & Gibaud, A. (eds) X-ray and Neutron Reflectivity: Principles and Applications Vol. 770 (Springer, 2008)
Medarde, M. et al. RNiO3 perovskites (R= Pr, Nd): nickel valence and the metal-insulator transition investigated by x-ray-absorption spectroscopy. Phys. Rev. B 46, 14975–14984 (1992)
Mizokawa, T. et al. Electronic structure of PrNiO3 studied by photoemission and x-ray-absorption spectroscopy: band gap and orbital ordering. Phys. Rev. B 52, 13865–13873 (1995)
Li, Z. et al. Correlated perovskites as a new platform for super-broadband-tunable photonics. Adv. Mater. 28, 9117–9125 (2016)
Kreuer, K. D. Proton-conducting oxides. Annu. Rev. Mater. Res. 33, 333–359 (2003)
Dura, J. A. et al. AND/R: advanced neutron diffractometer/reflectometer for investigation of thin films and multilayers for the life sciences. Rev. Sci. Instrum. 77, 74301 (2006)
DeCaluwe, S. C., Kienzle, P. A., Bhargava, P., Baker, A. M. & Dura, J. A. Phase segregation of sulfonate groups in Nafion interface lamellae, quantified via neutron reflectometry fitting techniques for multi-layered structures. Soft Matter 10, 5763–5776 (2014)
Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996)
Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999)
Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996)
Liechtenstein, A. I., Anisimov, V. I. & Zaanen, J. Density-functional theory and strong interactions: orbital ordering in Mott-Hubbard insulators. Phys. Rev. B 52, R5467 (1995)
Allen, M. P. & Tildesley, D. J. Computer Simulation of Liquids (Oxford Univ. Press, 1989)
Henkelman, G., Uberuaga, B. P. & Jónsson, H. A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J. Chem. Phys. 113, 9901–9904 (2000)
Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994)
Persson, K. Materials Data on SmNiO 3 (SG:62) by Materials Project. Dataset No. mp-25588 (Lawrence Berkeley National Laboratory, 2016); https://materialsproject.org/materials/mp-25588/
Blöchl, P. E., Jepsen, O. & Andersen, O. K. Improved tetrahedron method for Brillouin-zone integrations. Phys. Rev. B 49, 16223–16233 (1994)
Pérez-Cacho, J., Blasco, J., Garcia, J., Castro, M. & Stankiewicz, J. Study of the phase transitions in SmNiO3 . J. Phys. Condens. Matter 11, 405–415 (1999)
Shi, J., Ha, S. D., Zhou, Y., Schoofs, F. & Ramanathan, S. A correlated nickelate synaptic transistor. Nat. Commun. 4, 2676 (2013)
Wootton, J. T., Pfister, C. A. & Forester, J. D. Dynamic patterns and ecological impacts of declining ocean pH in a high-resolution multi-year dataset. Proc. Natl Acad. Sci. USA 105, 18848–18853 (2008)
Mamayev, O. I. Temperature–Salinity Analysis of World Ocean Waters Vol. 11, 305–334 (Elsevier, 1975)
S.R. thanks K. Catania (Vanderbilt University) for discussions on bioelectric fields in marine organisms and B. Robinson and K. Benoit-Bird of the Monterey Bay Aquarium Research Institute for technical discussions on electroreception in sharks. We acknowledge financial support from the Army Research Office (W911NF-16-1-0289, W911NF-16-1-0042), National Science Foundation (DMR-1609898, DMR-1610215), Defense Advanced Research Projects Agency (grant D15AP00111), Office of Naval Research (grants N00014-16-1-2442 and N00014-12-1040) and Air Force Office of Scientific Research (grants FA9550-16-1-0159 and FA9550-14-1-0389). Use of the Center for Nanoscale Materials, an Office of Science user facility, was supported by the US Department of Energy (DOE), the Office of Science, Office of Basic Energy Sciences under contract number DE-AC02-06CH11357. This research used resources of the Advanced Photon Source, a US DOE Office of Science User Facility operated by Argonne National Laboratory under contract number DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the US DOE under contract number DE-AC02-05CH11231. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) programme. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the US DOE under contract DE-AC02-06CH11357. S.S.N. acknowledges support from the University of Massachusetts-Amherst through start-up funding. Part of the research described in this paper was performed at the Canadian Light Source, which is supported by the Canada Foundation for Innovation, Natural Sciences and Engineering Research Council of Canada, the University of Saskatchewan, the Government of Saskatchewan, Western Economic Diversification Canada, the National Research Council Canada and the Canadian Institutes of Health Research.
The authors declare no competing financial interests.
Reviewer Information Nature thanks M. Lyons and the other anonymous reviewer(s) for their contribution to the peer review of this work.
Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a, Temperature derivative of the electrical resistivity of SNO after submersion in a 0.6 M NaCl aqueous solution for 24 h (blue curve). The insulator–metal transition temperature (TMIT), where dρ/dT changes sign from negative to positive for submerged SNO is in the same range as reported in the literature5,7,40,41. The purple curve shows the temperature derivative of the electrical resistivity of SNO obtained after applying a reverse bias of 2.0 V for 10 min to a water-treated HSNO sample, where the metal–insulator transition recovers. b, Electrical resistivity of SNO after being submerged in solutions of 0.01 M KOH and 0.01 M citric acid. The electrical resistivity of SNO shows minimal variation over a wide range of pH values for 180 min. c, Non-volatile behaviour of SNO thin film after applying a bias of −2.0 V in a 0.6 M NaCl solution for various durations. The resistivity of SNO after sensing an electric potential remains unchanged for 120 min, which demonstrates its non-volatile nature, in contrast to the surface electrostatic field effect of electric double-layer transistors.
a, Open-circuit potential (VOC) of SNO relative to a standard Ag/AgCl electrode in standard aqueous buffers with pH values covering the pH range of Earth’s oceans42. Error bars show the standard deviation. The potential VOC decreases monotonically with increasing pH. This linear relationship between proton activity (and the corresponding surface adsorption) and VOC enables SNO to operate as a pH sensor. b, Temperature-dependent electrical resistivity of SNO in the temperature range of Earth’s oceans43. The electrical resistivity increases with cooling; this is consistent with the insulating nature of SNO around room temperature, which enables it to function as a thermistor. c, Modulation of normalized electrical resistivity of SNO in an aqueous environment after the application of bias potentials over multiple sensing steps. The bias potentials (versus Ag/AgCl) were ±0.5 V, ±0.05 V and ±0.005 V and their duration was 10 s. The aqueous environment was a 0.6 M NaCl solution with salinity close to that of sea water. The normalized resistivity increases and then decreases following the reversal of the bias potential. The reversibility of the water-mediated phase transition and the facile migration of protons enable SNO to detect the local fluctuation of electric signals in water. This sensing capability persists over multiple cycles, indicating their robustness in aqueous environments. d, Schematic of an ampulla of Lorenzini, an electroreception organ located around the mouth of sharks. e, Electric potential as a function of distance for teleost fishes (Sphyraena barracuda and Ariopsis felis)11. The detection range of elasmobranch predators11 and SNO sensors are shaded with blue and yellow colour, respectively. The calculated detection range of SNO includes the regime where the bioelectric potential of prey fishes is higher than the sensitivity of SNO (about 4.5 μV) experimentally determined from Fig. 1g. The nickelate device is estimated to detect field stimuli over a distance of tens of centimetres, which is similar in range to that of elasmobranch species. f, Experimentally measured resistance modulation of pristine SNO upon the application of pulsed bias potential at −2.0 V and −0.5 V respectively. The response times of the SNO sensor studied here are as low as 0.1 s.
a, Optical image of SNO after applying bias to a selected area, where colour change occurs. b, Current map of pristine area, where the current is in the nanoampere range. c, The corresponding surface topography of the pristine area. d, Current map of water-treated area, which is entirely dark compared with the pristine state (b). The current after sensing is decreased to the picoampere range owing to proton uptake. e, The corresponding surface topography of SNO after sensing, where no evidence of corrosion was observed compared with the pristine state (c). Moreover, almost no variance is observed in the surface roughness of the thin film (Supplementary Information section 3). Scale bars are 0.5 μm.
a, Dependence of water-mediated phase transition in SNO on pH values spanning from an acidic solution (0.01 M citric acid, pH = 2.7) to a basic solution (0.01 M KOH, pH = 12). The transition from SNO to HSNO shifts to more negative potential values with increasing pH, where greater bias is required to compensate for the reduction of the proton activity in the basic solutions. b, Cyclic voltammogram and accompanying reaction for SNO in 0.01 M citric acid from 1.0 V to −1.0 V (versus Ag/AgCl) at various scan rates. Cathodic current peaks at negative potentials indicate the charge transfer as the Ni3+ is reduced to Ni2+. The peak position varies as a function of scan rate, indicating that the reaction is kinetically limited by the charge and mass transfer. c, Linear relationship between peak cathodic current density (Ip/A) and the square root of the scan rate (v0.5). The best fit to the Randles–Sevcik equation23 estimates the number of electrons transferred in the rate-limiting step as 0.95 (Supplementary Information section 4), indicating that the Ni in SNO is almost fully reduced from Ni3+ to Ni2+ upon intercalation.
Extended Data Figure 5 A schematic of the experimental setup for in situ XRR measurement at the Advanced Photon Source.
The SNO thin film was connected to a working electrode and submerged in a 0.01 M KOH aqueous solution. A Kapton film was used to avoid the spillage of electrolyte during measurement. The electric potential was applied through the counter-electrode. After the treatment, the XRR signals were collected in situ.
a, Synchrotron X-ray diffraction curves taken from a SNO/LaAlO3 thin film after treatment in a 0.01 M KOH aqueous solution at −4.0 V for 30 s. The (220) peak of pristine SNO (orthorhombic notation) appears at Q1 ≈ 3.29 Å−1 as a shoulder with slightly lower scattering vector Qz than the LaAlO3 (002) diffraction peak (pseudocubic notation), demonstrating the epitaxial growth of SNO on LaAlO3. After the water treatment, the epitaxial relationship of SNO on LaAlO3 is preserved. Peak 1 shifts to a lower Qz. Peak 2 appears at Qz = 3.11 Å−1, which corresponds to increase of the lattice constant by 5.7%. LAO stands for LaAlO3. b, X-ray diffraction profiles of SNO and water-treated SNO over a wide range of scattering angles 2θ. No new peaks appear, in contrast to what has been observed in other oxides, such as cobaltites, upon exposure to water. c, Comparison of synchrotron XRR curves for SNO after applying a bias of −4.0 V for 5 min in 0.01 M citric acid and 0.01 M KOH aqueous solutions. d, A selected area of the XRR curves, normalized to the oscillation peak at Q ≈ 0.19 Å−1 (marked by black arrows in c). Upon treatment, the XRR oscillation period decreases, demonstrating film expansion regardless of solution type, which indicates a general mechanism of phase change of SNO in various aqueous solutions caused by proton incorporation.
The scattering length density (SLD) profiles were fitted to the data shown in Fig. 2b for the SNO/SiO2/Si films. The surface roughness is nearly unchanged after water treatment (Supplementary Information section 3). The profiles of water-treated and heavy-water-treated samples show similar film expansion. However, differences exist between the scattering length densities of D2O- and H2O-treated films. Because D+ has larger neutron scattering length than H+, the increase of the scattering length density demonstrates the intercalation of D+ from D2O into the lattice after the treatment.
a, b, Reflectivity (a) and absorptivity (b) of pristine and water-treated (−4.0 V, 30 s, in 0.01 M KOH aqueous solution) SNO thin film deposited on a Si substrate. After the treatment, the SNO sensing device shows reduction in both reflectivity and free-electron absorptivity, concurrent with a large increase in electrical resistance. c, Finite-difference time-domain simulation of optical spectra of water-treated SNO/SiO2/Si thin film devices. The experimental results of the transmissivity and reflectivity of water-treated SNO are compared with finite-difference time-domain simulation results of HSNO/SiO2/Si thin film devices, where the optical parameters of samples treated with gas-phase hydrogen27 were adopted for HSNO. The good agreement between experimental and simulation results indicates the occurrence of a phase transition from SNO to HSNO during water treatment with no material decomposition. The thickness of SNO and SiO2 was obtained from neutron reflectivity data. The SiO2 layer between the SNO thin film and Si, which is formed during film synthesis, contributes to the absorption feature observed at 9.2 μm in the transmission spectra. d, An infrared image of a SNO/LaAlO3 sample with water treatment on a selected area (FLIR, infrared camera). SNO becomes more transparent (red colour) in the infrared wavelength range at λ = 8 μm after the treatment. The inset shows a photograph of the sample, where the transparency of the treated area can be observed in the visible wavelength range.
Extended Data Figure 9 Dynamic simulations of SNO–water interactions at an elevated temperature of 500 K.
a, Snapshots of the temporal evolution of a SNO surface submerged in water. Images tracking the evolution of a typical water molecule and the NiO6 octahedra in the SNO layer closest to water are shown in the top panels. At 500 K, the surface protonation mechanisms are identical to those at ambient temperature, where water at the SNO surface dissociates into free protons and OH−; a fraction of the free protons migrates to the oxide/water interface and binds to the surface oxygen of SNO. These atomic-scale processes observed in AIMD simulations support the proton accumulation and surface protonation mechanism depicted schematically in Fig. 1a. b, Top view, showing SNO protonation at the end of 4 ps. Compared with the pristine state at 0 ps, the SNO surface maintains structural stability during the protonation, even at 500 K (well above ocean temperature). c, The Ni–O pair distribution functions (PDF) calculated at various time intervals. The curves demonstrate well defined sharp peaks, suggesting that the SNO surface remains intact after surface protonation at elevated temperature in an aqueous environment. These results are consistent with the good stability inferred from the temperature-dependent electrical resistivity measurement of the submerged SNO samples.
Extended Data Figure 10 First-principles calculations of the structure and electron localization of HSNO.
a–f, The structure of SNO with 1/4 H/SNO (a–c) and 1 H/SNO (d–f), displayed along the three crystallographic axes of the primitive perovskite structure. The crystallographic axes of the supercell were used in the calculations, where the  direction was allowed to relax. In all panels, 12 NiO6 octahedra encompassing the Ni atoms (green) are displayed, with O in red, Sm in purple and H in cyan. The calculations use a supercell (that is, with four Ni atoms). g, Change in the volume of SNO at various protonation levels (denoted as protons per SNO formula unit) obtained from DFT calculations. The calculated volume expansion for 1 H/SNO is about 5.9%, which is close to the value obtained from neutron reflectometry measurements and X-ray diffraction. h, The difference in the electron density between the relaxed HSNO (SmNiO3H) and the initial state (SNO + H), which clearly shows a depletion (cyan) of charge around the hydrogen (cyan) and an accumulation (yellow) of charge around the closest nickel (green) and oxygen (red), which are part of the octahedron that expands upon hydrogen incorporation into the lattice. In this calculation, the c axis was allowed to relax while the other two (in-plane lattice constants) were fixed. For clarity, only the spin-down charge density is plotted because the electron incorporation results in a negative total magnetic moment (see the projected density of states of 1/4 H/SNO in Fig. 3d). i, The plane of the contour plot situated within the supercell.
This file contains supplementary text 1 – 7, supplementary tables 1 – 3 and references. (PDF 796 kb)
MD trajectory highlights the dissociation of water molecules near the oxide-water interface into free protons and OH- ions. A fraction of the protons migrates to the oxide surface and binds to surface oxygen of the SNO. The spheres shown here represent nickel (green), samarium (purple), oxygen (red), and hydrogen (cyan) atoms. (MP4 10068 kb)
The mechanism of protonation of the SNO surface is similar to that observed at 300 K. Note that the surface of SNO maintains its structural integrity even at elevated temperatures. The spheres shown here represent nickel (green), samarium (purple), oxygen (red), and hydrogen (cyan) atoms. (MP4 8694 kb)
AIMD video showing proton hopping between two neighboring O atoms belonging to a NiO6 octahedron in bulk SNO at 300 K.
Only a selected region of bulk SNO is shown, wherein proton hopping occurs within ~1.5 ps. The spheres shown here represent nickel (green), samarium (purple), oxygen (red), and hydrogen (cyan) atoms. (MP4 7265 kb)
About this article
Cite this article
Zhang, Z., Schwanz, D., Narayanan, B. et al. Perovskite nickelates as electric-field sensors in salt water. Nature 553, 68–72 (2018). https://doi.org/10.1038/nature25008
This article is cited by
A review of Mott insulator in memristors: The materials, characteristics, applications for future computing systems and neuromorphic computing
Nano Research (2023)
Nature Communications (2022)
Batch synthesis of rare-earth nickelates electronic phase transition perovskites via rare-earth processing intermediates
Rare Metals (2022)
Journal of Superconductivity and Novel Magnetism (2021)
Nature Communications (2020)