Engineering Synaptic Dynamics in Ag-Modified TaO$_x$ Memristive Devices

Abstract: Engineering not only the magnitude but also the dynamics of synaptic weight updates is an important challenge for memristive neuromorphic hardware. Here, we show that Ag modification of TaO$_x$ memristors introduces an electrically selectable degree of freedom in synaptic depression through the interplay between Ag-related and oxygen-vacancy dynamics. Reference devices exhibit conventional bipolar switching, whereas Ag-modified devices display symmetric table-with-legs hysteresis loops, metastable intermediate states, and a strongly non-monotonic dependence of depression dynamics on programming amplitude. By varying only the pulse amplitude, the same device can be driven among three regimes: gradual sigmoidal depression, an abrupt update concentrated within a few pulses, and a broadly distributed evolution extending over more than one hundred pulses. A minimal coupled-state model, in which a vacancy-related switching variable interacts with a slower Ag-related internal degree of freedom, reproduces this gradual--abrupt--gradual crossover using two individually monotonic field-activated processes. The functional impact is assessed in a memristor-based multilayer perceptron. For MNIST, the abrupt, sigmoidal, and slowly evolving responses yield accuracies of approximately 50%, 85%, and 88%, respectively, while the gradual regime reaches approximately 72% for Fashion-MNIST. These results show that coupling Ag-related and oxygen-vacancy dynamics can transform synaptic depression from a fixed device characteristic into an electrically programmable property.