Publication date: 15th December 2025
The future edge computing applications, such as the Internet of Things (IoT), demand substantial data processing performed locally. This makes the conventional von Neumann computing architecture unfit for such applications due to the limited energy supply in edge computing. In this circumstance, highly energy-efficient computing paradigms are needed, such as neuromorphic computing and in-memory computing (IMC) [1]. IMC refers to local information processing where data is generated and stored, making it particularly appealing for data-intensive applications. Emerging non-volatile memory technologies are the key enablers for IMC, and among them, memristors are regarded as the most promising memory devices due to their low-energy and fast switching characteristics. Memristor-based stateful logic [2] forms the fundamental IMC primitive, where the output is stored in the same cells that perform the computation, thereby eliminating write operations to a separate non-volatile memory block. In this talk, we present experimental demonstrations of five stateful logic operations—AND, OR, XOR, NOR, and NOT—implemented with inkjet-printed Ag/ZnO/Au memristors [3]. We discuss that the switching characteristics of the printed memristors, namely the asymmetric switching voltages of SET (1.43 V) and RESET (−0.41 V), and a compliance current during logic operation, prevent input switching of memristors in an anti-series circuit configuration. This allows for higher output accuracy rates and crossbar-compatible circuit topologies. The presented results show high output accuracy rates of 94% for OR and 98.5% for AND. With the reliable OR and AND gates, we demonstrate the realization of a compare-and-swap (CAS) sorting circuit for an in-memory unary sorting application. The presented results highlight the potential of using printed memristive stateful logic as a general-purpose in-memory computing solution for emerging applications requiring local data processing, such as wearable electronics for healthcare and low-power sensor nodes for agricultural monitoring.
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