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Neuromorphic computing architectures enable the dense co-location of memoryand processing elements within a single circuit. This co-location removes thecommunication bottleneck of transferring data between separate memory andcomputing units as in standard von Neuman architectures for data-criticalapplications including machine learning. The essential building blocks ofneuromorphic systems are non-volatile synaptic elements such as memristors. Keymemristor properties include a suitable non-volatile resistance range,continuous linear resistance modulation and symmetric switching. In this work,we demonstrate voltage-controlled, symmetric and analog potentiation anddepression of a ferroelectric Hf$_{57}$Zr$_{43}$O$_{2}$ (HZO) field effecttransistor (FeFET) with good linearity. Our FeFET operates with a low writingenergy (fJ) and fast programming time (40 ns). Retention measurements have beendone over 4-bits depth with low noise (1%) in the tungsten oxide (WO$_{x}$)read out channel. By adjusting the channel thickness from 15nm to 8nm, theon/off ratio of the FeFET can be engineered from 1% to 200% with anon-resistance ideally >100 kOhm, depending on the channel geometry. The deviceconcept is using earth-abundant materials, and is compatible with a back end ofline (BEOL) integration into complementary metal-oxidesemiconductor (CMOS)processes. It has therefore a great potential for the fabrication of highdensity, large-scale integrated arrays of artificial analog synapses.

A back-end, CMOS compatible ferroelectric Field Effect Transistor for synaptic weights