The deluge of sensors and data generating devices has driven a paradigm shift in modern computing from arithmeticlogic centric to data-centric processing. Data-centric processing require innovations at the device level to enable novel compute-inmemory (CIM) operations. A key challenge in the construction of CIM architectures is the conflicting trade-off between the performance and their flexibility for various essential data operations. Here, we present a transistor-free CIM architecture that permits storage, search, and neural network operations on sub-50 nm thick Aluminum Scandium Nitride ferroelectric diodes (FeDs). Our circuit designs and devices can be directly integrated on top of Silicon microprocessors in a scalable process. By leveraging the field-programmability, nonvolatility, and nonlinearity of FeDs, search operations are demonstrated with a cell footprint <0.12 μm 2 when projected onto 45 nm node technology. We further demonstrate neural network operations with 4-bit operation using FeDs. Our results highlight FeDs as candidates for efficient and multifunctional CIM platforms.

Developing materials that enable fabricating multifunctional devices has been the cornerstone of present-day materials science and engineering. Such multi-functionality makes these devices capable of novel applications ranging from energy, storage,...

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