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Exploring Multilevel Properties of GeTe-Based Phase Change Memory Devices for Programmable Synaptic Activity

Amiya Mishra, Anushmita Pathak, Shivendra Kumar Pandey

2025ACS Applied Electronic Materials6 citationsDOI

Abstract

Phase change memory (PCM) is a promising technology to emulate the synaptic behavior of neuromorphic systems. The efficient development of artificial synaptic arrays for brain-inspired neuromorphic applications is crucial for overcoming the Von Neumann bottleneck at the device level. Hence, GeTe-based PCM performance is investigated in this work for neuromorphic applications. XRD analysis of the GeTe material shows the amorphous to rhombohedral structural evolution at a 250 °C annealing temperature. The intensity of Raman spectra peaks at 250 °C increases, while FWHM decreases, indicating an improvement in the sample crystallinity. Ge 3d and Te 3d X-ray photoelectron spectroscopy core-level spectra confirmed the presence of Ge–Te bonds. A TiN/GeTe/TiN PCM device is fabricated and electrically tested to imitate its functioning as an electronic synapse. A noticeable rise in conductance is observed at a threshold voltage of ∼(2.5 ± 0.1) V on applying a DC voltage sweep from 0 to 4 V. The device also achieves a rise in conductance values from 10 to 451 μS, while a decrement of conductance from 385.8 to 13 μS reveals the potentiation and depression behavior of a biological synapse when subjected to a programmed electrical pulse. The nonlinearity (NL) is around 30.35 and 5.35 for the potentiation and depression pulse, respectively, essential for high recognition accuracy in neural networks. These findings indicate that the GeTe-based PCM device is well-suited for emulating artificial synapses and promoting efficient neuromorphic application systems.

Topics & Concepts

Neuromorphic engineeringPhase-change memoryMaterials scienceMemristorOptoelectronicsRaman spectroscopyConductanceSynapseAmorphous solidCrystallinityX-ray photoelectron spectroscopyTinNanotechnologyComputer scienceArtificial neural networkElectronic engineeringCondensed matter physicsOpticsComposite materialPhysicsNuclear magnetic resonanceArtificial intelligenceChemistryNeuroscienceMetallurgyLayer (electronics)BiologyEngineeringOrganic chemistryAdvanced Memory and Neural ComputingPhase-change materials and chalcogenidesTransition Metal Oxide Nanomaterials