Ion Intercalation in 2D Channel Materials for Fast Conductivity Modulation in Neuromorphic Computing Devices

Electrochemical ionic synapses (EIS), also known as electrochemical random-access memory (ECRAM), have emerged as programmable resistors for crossbar arrays, promising high energy efficiency for artificial neural networks.^1,2 An EIS consists of three key functional layers: ion reservoir, solid electrolyte, and channel. Voltage-driven intercalation of mobile ions (such as H⁺, Li⁺, or Mg²⁺) finely tunes the channel's conductivity, facilitating a high degree of control over the resistance state of each device.^3,4 The use of bulk mixed ionic and electronic conducting oxides as channel materials, such as WO₃, MoO₃or V₂O₅,⁵ inevitably necessitates 3D ion redistribution and potentially causes undesirably long settling times of the channel conductivity. 2D channel materials, such as monolayers of transition metal oxides or transition metal dichalcogenides,⁶ present an alternative to bulk channel materials. Our experiments have demonstrated successful modulation of the conductivity of a 2H-MoS₂ monolayer with hydrogen ions in ECRAM, highlighting its potential as a 2D channel material.<br/><br/>In this study, we aim to understand proton energetics and proton diffusion at the interfaces between SiO₂ (solid electrolyte) and MoS₂ (2D channel material) by using Density Functional Theory (DFT) simulations, as we believe these are the key ingredients to tune ECRAM devices with 2D channel materials towards optimal performance. We examine various proton configurations in the channel, electrolyte and at their interface and determine the most stable intercalation sites. According to our results, H⁺ ions prefer to sit within the channel/electrolyte interface close to the O-terminated (001) SiO₂ surface. In addition, we focus on the effects of ion intercalation on the electronic structure of the channel and electrolyte material. Depending on the location of H, different charge redistribution patterns and the most stable charge states were identified, providing insight on the mechanism of the conductivity modulation in MoS₂. To investigate the kinetics of H intercalation into MoS₂ channels, we also study the migration of protons at the channel/electrolyte interface and across the van der Waals gap (approximately 3 Å), which is expected to present a bottleneck for the proton transfer.<br/><br/>Based on the understanding gained from this model system, this research provides valuable insight into the development of high-performance, energy-efficient neuromorphic computing hardware by modulating the conductivity in 2D channels for ECRAM devices.<br/><br/>(1) Huang, M., Schwacke, M., Onen, M., Del Alamo, J.A., Li, J. and Yildiz, B., 2023. Electrochemical ionic synapses: progress and perspectives. <i>Advanced Materials</i>, <i>35</i>(37), p.2205169.<br/>(2) Schwacke, M., Zguns, P., Del Alamo, J.A., Li, J. and Yildiz, B., 2024. Electrochemical Ionic Synapses with Mg2+ as the Working Ion. <i>Advanced Electronic Materials</i>, p.2300577.<br/>(3) Yao, X., Klyukin, K., Lu, W., Onen, M., Ryu, S., Kim, D., Emond, N., Waluyo, I., Hunt, A., Del Alamo, J.A. and Li, J., 2020. Protonic solid-state electrochemical synapse for physical neural networks. <i>Nature communications</i>, <i>11</i>(1), p.3134.<br/>(4) Onen, M., Emond, N., Wang, B., Zhang, D., Ross, F.M., Li, J., Yildiz, B. and Del Alamo, J.A., 2022. Nanosecond protonic programmable resistors for analog deep learning. <i>Science</i>, <i>377</i>(6605), pp.539-543.<br/>(5) Siebenhofer, M., Zguns, P. and Yildiz, B., 2024, April. Ion migration in mixed conducting oxides for fast conductivity modulation in neuromorphic devices. In <i>Proceedings of 24th International Conference on Solid State Ionics (SSI24)</i>.<br/>(6) Sahoo, S., Kumari, P., Som, N.N., Kar, S., Ahuja, R. and Ray, S.J., 2024. Remarkable enhancement of the adsorption and diffusion performance of alkali ions in two-dimensional (2D) transition metal oxide monolayers via Ru-doping. <i>Scientific Reports</i>, <i>14</i>(1), p.4371.