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Self-rectifying magnetoelectric metamaterials for remote neural stimulation and motor function restoration


Magnetoelectric materials convert magnetic fields into electric fields. These materials are often used in wireless electronic and biomedical applications. For example, magnetoelectrics could enable the remote stimulation of neural tissue, but the optimal resonance frequencies are typically too high to stimulate neural activity. Here we describe a self-rectifying magnetoelectric metamaterial for a precisely timed neural stimulation. This metamaterial relies on nonlinear charge transport across semiconductor layers that allow the material to generate a steady bias voltage in the presence of an alternating magnetic field. We generate arbitrary pulse sequences with time-averaged voltage biases in excess of 2 V. As a result, we can use magnetoelectric nonlinear metamaterials to wirelessly stimulate peripheral nerves to restore a sensory reflex in an anaesthetized rat model and restore signal propagation in a severed nerve with latencies of less than 5 ms. Overall, these results showing the rational design of magnetoelectric metamaterials support applications in advanced biotechnology and electronics.

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Fig. 1: MNMs enable wireless neuromodulation using magnetic fields.
Fig. 2: Engineered material properties in metamaterials.
Fig. 3: Arbitrary pulse trains and characterization of MNM.
Fig. 4: In vivo experiments and controls using the MNM.
Fig. 5: Measured stimulation latency of MNM in a severed-nerve rodent model.

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All the relevant data supporting the results of this study are presented in the Article or its Supplementary Information. Raw data are available at

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  1. Hallett, M. et al. Transcranial magnetic stimulation and the human brain. Nature 406, 147–150 (2000).

    Article  CAS  Google Scholar 

  2. Chen, R. et al. Wireless magnetothermal deep brain stimulation. Science 347, 1477–1480 (2015).

  3. Huang, H. et al. Remote control of ion channels and neurons through magnetic-field heating of nanoparticles. Nat. Nanotechnol. 5, 602–606 (2010).

    Article  CAS  Google Scholar 

  4. Munshi, R. & Pralle, A. Remote modulation of neuronal cells in the brain. Nat. Mater. 20, 912–913 (2021).

    Article  Google Scholar 

  5. Moon, J. et al. Magnetothermal multiplexing for selective remote control of cell signaling. Adv. Funct. Mater. 30, 2000577 (2020).

    Article  CAS  Google Scholar 

  6. Sebesta, C. et. al. Subsecond multichannel magnetic control of select neural circuits in freely moving flies. Nat. Mater. 21, 951–958 (2022).

  7. Rao, S. et al. Remotely controlled chemomagnetic modulation of targeted neural circuits. Nat. Nanotechnol. 14, 967–973 (2019).

    Article  CAS  Google Scholar 

  8. Boyden, E. S. et al. Millisecond-timescale, genetically targeted optical control of neural activity. Nat. Neurosci. 8, 1263–1268 (2005).

    Article  CAS  Google Scholar 

  9. Bhave, G. et al. Distributed sensor and actuator networks for closed-loop bioelectronic medicine. Mater. Today 46, 125–135 (2021).

    Article  CAS  Google Scholar 

  10. Gregurec, D. et al. Magnetic vortex nanodiscs enable remote magnetomechanical neural stimulation. ACS Nano 14, 8036–8045 (2020).

    Article  CAS  Google Scholar 

  11. Dobson, J. et al. Remote control of cellular behaviour with magnetic nanoparticles. Nat. Nanotechnol. 3, 139–143 (2008).

    Article  CAS  Google Scholar 

  12. Lee, J. et al. Non-contact long-range magnetic stimulation of mechanosensitive ion channels in freely moving animals. Nat. Mater. 20, 1029–1036 (2021).

    Article  CAS  Google Scholar 

  13. Nguyen, T. et al. In vivo wireless brain stimulation via non-invasive and targeted delivery of magnetoelectric nanoparticles. Neurotherapeutics 18, 2091–2106 (2021).

  14. Kozielski, K. et al. Nonresonant powering of injectable nanoelectrodes enables wireless deep brain stimulation in freely moving mice. Sci. Adv. 7, eabc4189 (2021).

    Article  CAS  Google Scholar 

  15. Tu, C. et al. Mechanical-resonance-enhanced thin-film magnetoelectric heterostructures for magnetometers, mechanical antennas, tunable RF inductors, and filters. Materials 12, 2259 (2019).

    Article  CAS  Google Scholar 

  16. Grossman, N. et al. Noninvasive deep brain stimulation via temporally interfering electric fields. Cell 169, 1029–1041.E16 (2017).

    Article  Google Scholar 

  17. Singer, A. et al. Magnetoelectric materials for miniature, wireless neural stimulation at therapeutic frequencies. Neuron 107, 631–643 (2020).

    Article  CAS  Google Scholar 

  18. Yu, Z. et al. MagNI: a magnetoelectrically powered and controlled wireless neurostimulating implant. IEEE Trans. Biomed. Circuits Syst. 14, 1241–1252 (2020).

    Article  Google Scholar 

  19. Alrashdan, F. et al. Wearable wireless power systems for ‘ME-BIT’ magnetoelectric-powered bio implants. J. Neural Eng. 18, 045011 (2021).

    Article  Google Scholar 

  20. Chen, J. C. et al. Wireless endovascular nerve stimulation with a millimeter-sized magnetoelectric implant. Nat. Biomed. Eng. 6, 706–716 (2022).

  21. Li, Z. et al. In situ ZnO nanowire growth to promote the PVDF piezo phase and the ZnO-PVDF hybrid self-rectified nanogenerator as a touch sensor. Phys. Chem. Chem. Phys. 16, 5475–5479 (2014).

    Article  CAS  Google Scholar 

  22. Kang, B. J. et al. Ultrafast and low-threshold THz mode switching of two-dimensional nonlinear metamaterials. Nano Lett. 22, 2016–2022 (2022).

    Article  Google Scholar 

  23. Misewich, J. A. et al. Electrically induced optical emission from a carbon nanotube FET. Science 300, 783–786 (2003).

    Article  CAS  Google Scholar 

  24. Lincoln, R. et al. Multifunctional composites: a metamaterial perspective. Multifunct. Mater. 2, 043001 (2019).

    Article  CAS  Google Scholar 

  25. Cuong, T. D. et al. Giant magnetoelectric effects in serial-parallel connected Metglas/PZT arrays with magnetostrictively homogeneous laminates. J. Sci. Adv. Mater. Devices 5, 354–360 (2020).

    Article  Google Scholar 

  26. Park, Y. et al. Unidirectional oxide hetero-interface thin-film diode. Appl. Phys. Lett. 107, 143506 (2015).

    Article  Google Scholar 

  27. Krajewski, T. A. et al. Hafnium dioxide as a passivating layer and diffusive barrier in ZnO/Ag Schottky junctions obtained by atomic layer deposition. Appl. Phys. Lett. 98, 263502 (2011).

    Article  Google Scholar 

  28. Brillson, L. J. & Lu, Y. ZnO Schottky barriers and ohmic contacts. J. Appl. Phys. 109, 121301 (2011).

    Article  Google Scholar 

  29. Mondal, S. et al. Preparation of ZnO Film on p-Si and I-V characteristics of p-Si/n-ZnO. Mater. Res. 16, 94–99 (2013).

    Article  CAS  Google Scholar 

  30. Guziewicz, E. et al. ALD grown zinc oxide with controllable electrical properties. Semicond. Sci. Technol. 27, 074011 (2012).

    Article  Google Scholar 

  31. Jeon, S. et al. Structural and electrical properties of ZnO thin films deposited by atomic layer deposition at low temperatures. J. Electrochem. Soc. 155, H738–H743 (2008).

    Article  CAS  Google Scholar 

  32. Xie, X. et al. Long-term reliability of Al2O3 and parylene C bilayer encapsulated Utah electrode array based neural interfaces for chronic implantation. J. Neural Eng. 11, 026016 (2014).

    Article  Google Scholar 

  33. Pak, A. et al. Thin film encapsulation for LCP-based flexible bioelectronic implants: comparison of different coating materials using test methodologies for life time estimation. Micromachines 13, 544 (2022).

    Article  Google Scholar 

  34. Prominski, A. et al. Porosity-based heterojunctions enable leadless optoelectronic modulation of tissues. Nat. Mater. 21, 647–655 (2022).

    Article  CAS  Google Scholar 

  35. Cummer, S. A. et al. Controlling sound with acoustic metamaterials. Nat. Rev. Mater. 1, 16001 (2016).

    Article  Google Scholar 

  36. Suchowski, H. et al. Phase mismatch-free nonlinear propagation in optical zero-index materials. Science 342, 1223–1226 (2013).

    Article  Google Scholar 

  37. Canalias, C. & Pasiskevicius, V. Mirrorless optical parametric oscillator. Nat. Photon. 1, 459–462 (2007).

    Article  CAS  Google Scholar 

  38. Shalaev et al. Optical negative-index metamaterials. Nat. Photon. 1, 41–48 (2007).

    Article  CAS  Google Scholar 

  39. Surjadi, J. et al. Mechanical metamaterials and their engineering applications. Adv. Eng. Mater. 21, 1800864 (2019).

    Article  CAS  Google Scholar 

  40. Montgomery, S. et al. Magneto-mechanical metamaterials with widely tunable mechanical properties and acoustic bandgaps. Adv. Funct. Mater. 31, 2005319 (2020).

    Article  Google Scholar 

  41. Hu, J. Z. et al. Crystal data for high-pressure phases of silicon. Phys. Rev. B 34, 4679 (1986).

    Article  CAS  Google Scholar 

  42. Ahmed, N. Numerical analysis of transport properties of ZnO based Schottky diode. Phys. Scr. 96, 065211 (2021).

    Article  Google Scholar 

  43. Wang, B. et al. Multichannel power electronics and magnetic nanoparticles for selective thermal magnetogenetics. J. Neural Eng. 19, 026015 (2022).

    Article  Google Scholar 

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We would like to acknowledge A. Singer, A. Tuppen, M. Parker and V. Nair for their useful discussions on magnetoelectrics. We would also like to acknowledge E. C. Lai for his assistance with the rat nerve surgeries, S. Coffler for her assistance with the biocompatibility assay and A. Bayles for his assistance with the X-ray diffraction measurements. We also thank the staff at the Shared Equipment Authority (SEA) at Rice University, as well as T. Gilheart, J. Guo, J. Kerwin and H. Guo, for their assistance and excellent discussions. We acknowledge funding from the National Science Foundation ECCS-2023849 (G.B., J.C.C., F.A. and J.T.R.), National Institutes of Health U18EB029353 (G.B., J.C.C., F.A. and J.T.R.) and National Institutes of Health F31 DE030333 (K.J.H. and A.G.M.).

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Authors and Affiliations



J.C.C., G.B. and J.T.R. conceived the MNM concept. J.T.R. supervised the research. J.C.C. and G.B. completed a majority of the experiments and data collection. F.A., A.D., K.J.H. and A.G.M. assisted with the material characterization. J.C.C., G.B. and J.T.R. prepared the manuscript with input from all the authors. F.A. reviewed and edited the manuscript.

Corresponding author

Correspondence to Jacob T. Robinson.

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Competing interests

J.T.R. is a co-founder of Motif Neurotech, Inc., where he has an equity stake and receives compensation. The views presented here should not be considered as endorsements of any specific product or company. The remaining authors declare no competing interests.

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Nature Materials thanks Shad Roundy and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–23.

Reporting Summary

Supplementary Video 1

Toe-pinch experiment.

Supplementary Video 2

Severed nerve.

Supplementary Video 3

Open wound.

Supplementary Video 4

Closed wound.

Supplementary Video 5

Thermal imaging.

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Chen, J.C., Bhave, G., Alrashdan, F. et al. Self-rectifying magnetoelectric metamaterials for remote neural stimulation and motor function restoration. Nat. Mater. 23, 139–146 (2024).

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