Analogue Switching Mejorado en Análogos de MoTe₂ Bidimensionales mediante Procesamiento Láser y Pasivación ALD para...

Neuro-based computing, enabled by memristors and memtransistors, has drawn significant attention, with two-dimensional (2D) molybdenum ditelluride (MoTe₂) emerging as a promising candidate for its low phase-change energy barrier and tunable electrical behavior. However, realizing the full potential of MoTe₂ for neuromorphic applications has been hindered by the lack of a sufficiently large memory window in pristine devices. In this work, we present an effective method to significantly enhance the analogue switching of lateral MoTe₂ devices. This method involves two sequential processes: laser treatment followed by the atomic layer deposition of Al₂O₃. The synergistic effects of both processes yielded significant performance improvements, with a 70-fold improvement in dynamic range when operating as a memristor and a 20-fold enhancement when functioning as a memtransistor. Consequently, artificial neural network simulations demonstrated a 10-fold enhancement in pattern recognition accuracy, while the dual memristor/memtransistor capability enabled the emulation of both homosynaptic and heterosynaptic plasticity.