Charge disproportionate molecular redox for discrete memristive and memcapacitive switching


Electronic symmetry breaking by charge disproportionation results in multifaceted changes in the electronic, magnetic and optical properties of a material, triggering ferroelectricity, metal/insulator transition and colossal magnetoresistance. Yet, charge disproportionation lacks technological relevance because it occurs only under specific physical conditions of high or low temperature or high pressure. Here we demonstrate a voltage-triggered charge disproportionation in thin molecular films of a metal–organic complex occurring in ambient conditions. This provides a technologically relevant molecular route for simultaneous realization of a ternary memristor and a binary memcapacitor, scalable down to a device area of 60 nm2. Supported by mathematical modelling, our results establish that multiple memristive states can be functionally non-volatile, yet discrete—a combination perceived as theoretically prohibited. Our device could be used as a binary or ternary memristor, a binary memcapacitor or both concomitantly, and unlike the existing ‘continuous state’ memristors, its discrete states are optimal for high-density, ultra-low-energy digital computing.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Molecular and thin film electronic properties.
Fig. 2: Test structures and electrical characterizations.
Fig. 3: Compact memristor model and state trajectory.
Fig. 4: Identification of molecular states.
Fig. 5: Reaction coordinate diagram and the role of temperature in stabilizing the charge disproportionate state.
Fig. 6: Role of counterions in charge disproportionation.

Data availability

The data that support the findings of this study are available from the corresponding authors on reasonable request.


  1. 1.

    Long, Y. et al. Temperature-induced A–B intersite charge transfer in an A-site-ordered LaCu3Fe4O12 perovskite. Nature 458, 60–63 (2009).

  2. 2.

    Cheng, J. et al. Charge disproportionation and the pressure-induced insulator–metal transition in cubic perovskite PbCrO3. Proc. Natl Acad. Sci. USA 112, 1670–1674 (2015).

  3. 3.

    Harter, J., Zhao, Z., Yan, J.-Q., Mandrus, D. & Hsieh, D. A parity-breaking electronic nematic phase transition in the spin-orbit coupled metal Cd2Re2O7. Science 356, 295–299 (2017).

  4. 4.

    Kawamoto, T. et al. Interlayer charge disproportionation in the layered organic superconductor κH-(DMEDO-TSeF)2[Au(CN)4](THF) with polar dielectric insulating layers. Phys. Rev. Lett. 109, 147005 (2012).

  5. 5.

    Senn, M. S., Wright, J. P. & Attfield, J. P. Charge order and three-site distortions in the Verwey structure of magnetite. Nature 481, 173 (2012).

  6. 6.

    Moskvin, A. Perspectives of disproportionation driven superconductivity in strongly correlated 3d compounds. J. Phys. Condens. Matter 25, 085601 (2013).

  7. 7.

    Shimakawa, Y., Kubo, Y. & Manako, T. Giant magnetoresistance in Ti2Mn2O7 with the pyrochlore structure. Nature 379, 53–55 (1996).

  8. 8.

    Kusmartseva, A. F., Sipos, B., Berger, H., Forro, L. & Tutiš, E. Pressure induced superconductivity in Pristine 1T–TiSe2. Phys. Rev. Lett. 103, 236401 (2009).

  9. 9.

    Zhang, J. et al. Cooperative photoinduced metastable phase control in strained manganite films. Nat. Mater. 15, 956–960 (2016).

  10. 10.

    Yang, J. J. et al. High switching endurance in TaOx memristive devices. Appl. Phys. Lett. 97, 232102 (2010).

  11. 11.

    Lee, M.-J. et al. A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O5–x/TaO2–x bilayer structures. Nat. Mater. 10, 625–630 (2011).

  12. 12.

    Kumar, S. et al. Conduction channel formation and dissolution due to oxygen thermophoresis/diffusion in hafnium oxide memristors. ACS Nano 10, 11205–11210 (2016).

  13. 13.

    Chua, L. Five non-volatile memristor enigmas solved. Appl. Phys. A 124, 563 (2018).

  14. 14.

    Prezioso, M. et al. Training and operation of an integrated neuromorphic network based on metal-oxide memristors. Nature 521, 61–64 (2015).

  15. 15.

    Sheridan, P. M. et al. Sparse coding with memristor networks. Nat. Nanotechnol. 12, 784–789 (2017).

  16. 16.

    Nili, H. et al. Hardware-intrinsic security primitives enabled by analogue state and nonlinear conductance variations in integrated memristors. Nat. Electron. 1, 197–202 (2018).

  17. 17.

    Yang, J. J., Strukov, D. B. & Stewart, D. R. Memristive devices for computing. Nat. Nanotechnol. 8, 13–24 (2013).

  18. 18.

    Rütten, M., Kaes, M., Albert, A., Wuttig, M. & Salinga, M. Relation between bandgap and resistance drift in amorphous phase change materials. Sci. Rep. 5, 17362 (2015).

  19. 19.

    Liu, R., Lee, H.-Y. & Yu, S. Analyzing inference robustness of RRAM synaptic array in low-precision neural network. In Proc. 47th European Solid-State Device Research Conference (ESSDERC) 18–21 (IEEE, 2017).

  20. 20.

    Nagashima, K. et al. Resistive switching multistate nonvolatile memory effects in a single cobalt oxide nanowire. Nano Lett. 10, 1359–1363 (2010).

  21. 21.

    Kim, W. et al. Multistate memristive tantalum oxide devices for ternary arithmetic. Sci. Rep. 6, 36652 (2016).

  22. 22.

    Choi, S. et al. SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations. Nat. Mater. 17, 335–340 (2018).

  23. 23.

    Wang, Z. et al. Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing. Nat. Mater. 16, 101–108 (2017).

  24. 24.

    Zidan, M. A. et al. A general memristor-based partial differential equation solver. Nat. Electron. 1, 411–420 (2018).

  25. 25.

    Le Gallo, M. et al. Mixed-precision in-memory computing. Nat. Electron. 1, 246–253 (2018).

  26. 26.

    Reed, D., Larus, J. R. & Gannon, D. Imagining the future: thoughts on computing. Computer 45, 25–30 (2012).

  27. 27.

    Pan, J. & McElhannon, J. Future edge cloud and edge computing for internet of things applications. IEEE Internet Things J. 5, 439–449 (2018).

  28. 28.

    Khan, H. N., Hounshell, D. A. & Fuchs, E. R. Science and research policy at the end of Moore’s law. Nat. Electron. 1, 14–21 (2018).

  29. 29.

    Bhunia, P. et al. A non-volatile memory device consisting of graphene oxide covalently functionalized with ionic liquid. Chem. Commun. 48, 913–915 (2012).

  30. 30.

    Cui, B.-B. et al. Tuning of resistive memory switching in electropolymerized metallopolymeric films. Chem. Sci. 6, 1308–1315 (2015).

  31. 31.

    Bessonov, A. A. et al. Layered memristive and memcapacitive switches for printable electronics. Nat. Mater. 14, 199–204 (2015).

  32. 32.

    Chan, H., Wong, H.-L., Ng, M., Poon, C.-T. & Yam, V. W.-W. Switching of resistive memory behavior from binary to ternary logic via alteration of substituent positioning on the subphthalocyanine core. J. Am. Chem. Soc. 139, 7256–7263 (2017).

  33. 33.

    Hong, E. Y.-H., Poon, C.-T. & Yam, V. W.-W. A phosphole oxide-containing organogold(III) complex for solution-processable resistive memory devices with ternary memory performances. J. Am. Chem. Soc. 138, 6368–6371 (2016).

  34. 34.

    Fan, F. et al. Conjugated polymer covalently modified graphene oxide quantum dots for ternary electronic memory devices. Nanoscale 9, 10610–10618 (2017).

  35. 35.

    Wang, Z. et al. Capacitive neural network with neuro-transistors. Nat. Commun. 9, 3208 (2018).

  36. 36.

    Chua, L. If it’s pinched it’s a memristor. Semicond. Sci. Technol. 29, 104001 (2014).

  37. 37.

    Najem, J. S. et al. Dynamical nonlinear memory capacitance in biomimetic membranes. Nat. Commun. 10, 1–11 (2019).

  38. 38.

    Saeki, A. & Seki, S. in Chemical Science of π-Electron Systems (eds Akasaka, T. et al.) 605–620 (Springer, 2015).

  39. 39.

    Goswami, S. et al. Robust resistive memory devices using solution-processable metal-coordinated azo aromatics. Nat. Mater. 16, 1216–1224 (2017).

  40. 40.

    Paul, N. D., Rana, U., Goswami, S., Mondal, T. K. & Goswami, S. Azo anion radical complex of rhodium as a molecular memory switching device: isolation, characterization, and evaluation of current–voltage characteristics. J. Am. Chem. Soc. 134, 6520–6523 (2012).

  41. 41.

    Goswami, S., Sengupta, D., Paul, N. D., Mondal, T. K. & Goswami, S. Redox non‐innocence of coordinated 2‐(arylazo)pyridines in iridium complexes: characterization of redox series and an insight into voltage‐induced current characteristics. Chem. Eur. J. 20, 6103–6111 (2014).

  42. 42.

    Valov, I. & Kozicki, M. Non-volatile memories: organic memristors come of age. Nat. Mater. 16, 1170–1172 (2017).

  43. 43.

    Tayi, A. S., Kaeser, A., Matsumoto, M., Aida, T. & Stupp, S. I. Supramolecular ferroelectrics. Nat. Chem. 7, 281–294 (2015).

  44. 44.

    Jayaram, B. et al. Sanjeevini: a freely accessible web-server for target directed lead molecule discovery. BMC Bioinformatics 13, S7 (2012).

  45. 45.

    Goswami, S., Mukherjee, R. & Chakravorty, A. Chemistry of ruthenium. 12. Reactions of bidentate ligands with diaquabis[2-(arylazo)pyridine]ruthenium(II) cation. Stereoretentive synthesis of tris chelates and their characterization: metal oxidation, ligand reduction, and spectroelectrochemical correlation. Inorg. Chem. 22, 2825–2832 (1983).

  46. 46.

    Ghosh, P. et al. Introducing a new azoaromatic pincer ligand. Isolation and characterization of redox events in its ferrous complexes. Inorg. Chem. 53, 4678–4686 (2014).

  47. 47.

    Evans, D. F. 400. The determination of the paramagnetic susceptibility of substances in solution by nuclear magnetic resonance. J. Chem. Soc. 2003–2005 (1959).

  48. 48.

    Prakash, S. et al. Intrinsic hydrophilic nature of epitaxial thin-film of rare-earth oxide grown by pulsed laser deposition. Nanoscale 10, 3356–3361 (2018).

  49. 49.

    Sarkar, T. et al. The effect of oxygen vacancies on water wettability of transition metal based SrTiO3 and rare-earth based Lu2O3. RSC Adv. 6, 109234–109240 (2016).

  50. 50.

    Santos, G., Cavallari, M. R., Fonseca, F. J. & Pereira, L. Oxygen plasma surface treatment onto ITO surface for OLEDs based on europium complex. J. Integr. Circuits Systems 10, 7–12 (2015).

  51. 51.

    Wu, C., Wu, C., Sturm, J. C. & Kahn, A. Surface modification of indium tin oxide by plasma treatment: an effective method to improve the efficiency, brightness, and reliability of organic light emitting devices. Appl. Phys. Lett. 70, 1348–1350 (1997).

  52. 52.

    Yuan, Y. et al. Ultra-high mobility transparent organic thin film transistors grown by an off-centre spin-coating method. Nat. Commun. 5, 3005 (2014).

  53. 53.

    Shi, X. & Zhao, Y.-P. Comparison of various adhesion contact theories and the influence of dimensionless load parameter. J. Adhes. Sci. Technol. 18, 55–68 (2004).

  54. 54.

    Han, J. et al. Surface energy approach and AFM verification of the (CF)n treated surface effect and its correlation with adhesion reduction in microvalves. J. Micromech. Microeng. 19, 085017 (2009).

  55. 55.

    Johnson, K., Kendall, K. & Roberts, A. Surface energy and the contact of elastic solids. Proc. R. Soc. Lond. A 324, 301–313 (1971).

  56. 56.

    Derjaguin, B., Muller, V. & Toporov, Y. P. Effect of contact deformations on the adhesion of particles. Prog. Surf. Sci. 45, 131–143 (1994).

  57. 57.

    Muller, V., Derjaguin, B. & Toporov, Y. P. On two methods of calculation of the force of sticking of an elastic sphere to a rigid plane. Colloids Surf. 7, 251–259 (1983).

  58. 58.

    Celano, U. et al. Evaluation of the electrical contact area in contact-mode scanning probe microscopy. J. Appl. Phys. 117, 214305 (2015).

  59. 59.

    Mayer, M. SIMNRA, a simulation program for the analysis of NRA, RBS and ERDA. In 15th International Conference on the Application of Accelerators in Research and Industry 541–544 (AIP, 1999).

  60. 60.

    Feldman, L. C. & Mayer, J. W. Fundamentals of Surface and Thin Film Analysis. (North Holland, 1986).

  61. 61.

    Kresse, G. & Hafner, J. Ab initio molecular-dynamics for liquid-metals. Phys. Rev. B 47, 558–561 (1993).

  62. 62.

    Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 78, 3865–3868 (1996).

  63. 63.

    Blochl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994).

Download references


We thank A. Castiñeiras for solving crystal structures, S. Kumar for helpful discussions on the mathematical modelling, A. Tempez for discussions regarding c-AFM measurements and M. Lal for helping with the nanostructure. T.V. and Sreetosh Goswami acknowledge support from NRF-CRP15-2015-01. Sreetosh Goswami thanks the NGS for funding support. Sreebrata Goswami acknowledges the financial support from SERB, India through grants SR/S2/JCB-09/2011 and EMR/2014/000520. D.T. thanks Science Foundation Ireland (SFI) for support (awards number 15/CDA/3491 and 12/RC/2275_P2) and for computing resources at the SFI/Higher Education Authority Irish Center for High-End Computing (ICHEC). C.A.N. acknowledges the Ministry of Education (MOE) for supporting this research under award no. MOE2015-T2-2-134.

Author information

Sreetosh Goswami devised the project and designed the experiments. Sreetosh Goswami performed the electrical and in situ spectroscopic measurements. S.P.R. and R.P. carried out the chemical synthesis and characterization under the supervision of Sreebrata Goswami. S. Hooda performed the RBS measurements. B.R.I. fabricated the nanopatterns. D.T. performed the theoretical calculations. M.A. performed the c-AFM measurements. R.S.W. developed the mathematical model. Sreetosh Goswami, R.S.W., T.V., Sreebrata Goswami, J.M., D.T., S. Hedström and S.S. performed data analysis. C.A.N. participated in discussions. Sreetosh Goswami, R.S.W., D.T., Sreebrata Goswami, J.M. and T.V. wrote the paper.

Correspondence to Sreetosh Goswami or Damien Thompson or Jens Martin or Sreebrata Goswami or T. Venkatesan.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Nanotechnology thanks Alec Talin 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

Extended Data Fig. 1 Multiple repeated traces.

500 repeated J(V) traces obtained from (a) structure A, (b) structure B and (c) structure C. The translucent cloud is the overlap of all the traces and the solid lines show one representative characteristic. The spread of the cloud indicates the maximum current variation in different traces which are orders of magnitude smaller than the conductance differences between the plateaus.

Extended Data Fig. 2 Non-volatility of the three states.

Grey curve: J(V) for full voltage sweep. Blue curve: J(V) with the forward scan stopped at the positive intermediate plateau (that is, V<V2, see Fig. 2) demonstrating that 11-state is robust and readable. Red curve: J(V) with the backward scan stopped in the negative intermediate plateau (that is, V>V4, see Fig. 2). This proves that the intermediate state is stable, and our device can be used both as binary or ternary memristors, that is both the upper and lower memristive loops can be used for (a) structure A, (b) structure B and (c) structure C. Arrows indicate the direction of the voltage sweep.

Extended Data Fig. 3 Effect of nano structures.

The J(V)s obtained for structure A, B and C are plotted in the same scale to visually illustrate the effect of nano structures in reducing switching voltage by ~30 times and increasing switching current by ~ 6 orders of magnitude.

Extended Data Fig. 4 Endurance.

a Response of structure B to pulses with 30 ns rise time. The current overshoot indicates that the switching time is <30 ns. b Endurance of structure B over ~1010 cycles measured with pulses as shown in (a) showing no indication of any degradation.

Extended Data Fig. 5 Retention and stability.

a, Pulse test to prove retention of structure B at 0 V. After writing, reading operations were performed after 1 hour, 2 hours and 2 days with the written state intact. b, Stability of individual conductance states: Three devices (structure B) with the same dimensions were fabricated and set into three different conductance states: 00 (on), 11 (intermediate), and 31 (off). All devices were measured simultaneously with constant application of read voltage V=500 mV at 350 K.

Extended Data Fig. 6 Top and bottom electrode variation.

The qualitatively similar J(V) response of the film in different electrode combinations, viz. (a) Pt/film/Pt, (b) Au/film/Pt, (c) Au/film/Au proving that the switching phenomenon is not an interface-specific phenomenon. The switching with noble metal electrodes also excludes the role of atomic/ ionic migration of the electrode materials in our observed switching.

Extended Data Fig. 7 Device characteristics with ITO top electrode.

The J(V) of devices with ITO as the top electrode for (a) structure A and (b) structure B. These structures are used for performing in-situ spectroscopic measurements. The current levels are similar to Au/film/ITO structure with small differences in switching voltage values due to the different work function of ITO. Consistent with redox mechanism, because of lower work function of ITO compared to Au, the switch-on voltage values with ITO top electrode increase whereas the switch-off voltages decrease.

Supplementary information

Supplementary Information

Supplementary Figs. S1–S38, Tables S1–S5 and refs. 1–39.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Goswami, S., Rath, S.P., Thompson, D. et al. Charge disproportionate molecular redox for discrete memristive and memcapacitive switching. Nat. Nanotechnol. (2020).

Download citation