Publication date: 10th April 2024
Mixed ionic and electronic conducting oxides, such as WO3, MoO3 or V2O5 are suitable candidates for programmable resistors in crossbar arrays, one of the most promising novel computing architectures for implementing artificial neural networks with high energy efficiency [1],[2]. By intercalation and distribution of mobile ions, such as H+, Li+, or Mg2+, the electronic conductivity of these materials can be finely tuned over a wide range, hence facilitating a high degree of control over the resistance state of each device [3],[4]. To reach target values for the operation speed of these so-called electrochemical ionic synapses, fast ion redistribution, and thus fast ion migration in these mixed conducting oxides is a key requirement [2].
In this contribution, we present our recent results from computational investigations of ion migration in these mixed conducting oxides with density functional theory (DFT) methods. We investigated the most favorable migration pathways with a particular focus on the effect of polarons on the proton mobility, which are the predominant type of mobile electronic charge carriers in these materials at low degrees of ion intercalation. Ultimately, aiming at accelerating ion migration and consequently the resistance modulation in electrochemical ionic synapses, we discuss methods to improve ion mobility in these mixed conducting oxides. Inspired by strategies to accelerate ion diffusion in high-temperature oxide ion conductors [5],[6],[7], we investigated lattice strain as a tool to tailor the migration characteristics for different ions and found significant potential to reduce migration barriers for intercalated ions in channel materials.
M.S. acknowledges the support of a Max Kade fellowship from the Max Kade foundation.
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