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Recognizing Spatiotemporal Features by a Neuromorphic Network with Highly Reliable Ferroelectric Capacitors on Epitaxial GeSn Film.

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Epitaxial GeSn (epi-GeSn) shows the capability to form ferroelectric capacitors (FeCAPs) with a higher remanent polarization (Pr) than epi-Ge. With the interface engineering by a high-k AlON, the reliability of… Click to show full abstract

Epitaxial GeSn (epi-GeSn) shows the capability to form ferroelectric capacitors (FeCAPs) with a higher remanent polarization (Pr) than epi-Ge. With the interface engineering by a high-k AlON, the reliability of the epi-GeSn-based FeCAPs is enhanced. Using the highly reliable FeCAP in series with a resistor as the synapse and axon, a simplified neuromorphic network based on a differentiator circuit is proposed. The network not only holds the leaky integrate-and-fire (LIF) function but is also capable of recognizing the spatiotemporal features, which sets it apart from other LIF neurons arising from the FeCAP-modulated leaky behavior of the potential on the axon by spiking-time-dependent plasticity. Furthermore, it is more energy efficient to operate, nondestructive to read, and simpler to fabricate by employing FeCAPs, making it eligible for emergent spiking neural network hardware accelerators.

Keywords: highly reliable; network; neuromorphic network; epitaxial gesn; gesn; ferroelectric capacitors

Journal Title: ACS applied materials & interfaces
Year Published: 2021

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