Molecular-Scale Hardware that Mimic Synapses
Departme
nt of Molecules and Materials, MESA+ Institute for Nanotechnology, Molecules Center and Center for Brain-Inspired Nano Systems (BRAINS), Faculty of Science and Technology, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands.
Inspired by the energy efficiency of brains and the ever-increasing demand for miniaturised electronics, there is a drive to develop devices that mimic the dynamic character of neurons and synapses to realize, for instance, non-von Neumann neuromorphic computing. Mostly, such operations are realized with energy inefficient and complex silicon-based circuits or with mesoscale memristors, but molecular hardware for doing so is not available yet [1]. In this context, molecular switches are an interesting approach, but so far molecular switches lack the dynamical, time-dependent character inherent to synapses [2,3]. It has been notoriously difficult, however, to reversibly address molecular switches in solid-state tunnel junctions. After a brief introduction, I will discuss our recent efforts to develop multi-functional molecular devices[3,4,5]. Recently, we developed a new type of an electrically driven molecular switch that can toggle between two different functionalities.[5] By coupling fast electron transport to slow proton addition steps, we created dynamic molecular switches that show large hysteretic negative differential conductance [6]. These switches mimic basic spike-rate dependent plasticity, Pavlovian learning, and emulate all Boolean logic gates. These molecular switches are promising to develop spiking neural networks and open new ways to design molecular-electronic devices.
References
1) Christensen et al. Neuromorph. Comput. Eng. 2022, 2, 022501.
2) Gehring, P., Thijssen, J. M., van der Zant, H. S. J. Nat. Rev. Phys. 2019, 1, 381-396.
3) Thompson, D.; Barco, E. d.; Nijhuis, C. A. Appl. Phys. Lett. 2020, 117, 030502.
4) Chen, X.; Roemer, M.; Yuan, L.; Du, W.; Thompson, D.; del Barco, E.; Nijhuis, C. A. Nat. Nanotechnol. 2017, 12, 797–803.
5) Han, Y.; Nickle, C.; Zhang, Z.; Asstier, P. A. G.; Duffin, T. J.; Qi, D.; Wang, Z.; del Barco, E.; Thompson D.; Nijhuis, C. A. Nat. Mater. 2020, 19, 843-848.
6) Wang, Y.; Zhang, Q.; Nickle, C.; Venkatakrishnarao, D.; Zhang, Z.; Leoncini A.; Qi, D.-C.; Han, Y.; del Barco, E.; Thompson, D.; Nijhuis, C. A. Nat. Mater. 2022, Accepted.