Hybrid ferroelectric-ionic memristive in-memory computing platform

In-memory computing (IMC) paradigms comprised of two-terminal memristor-based crossbar arrays have emerged as a promising solution to address the growing demand for data intensive computing and its exponentially rising energy consumption. However, these devices suffer from poor array scalability due to a lack of self-rectifying behavior, resulting in sneak path issues and additional selector devices. Furthermore, the best-performing memristors are often based on emerging materials (e.g., complex oxides, van der Waals chalcogenides) that are not yet compatible with complementary metal-oxide-semiconductor (CMOS) and very large-scale integration (VLSI) processes, impeding high-density array integration. Here, we experimentally realize a self-rectifying memristor combining the ideal switching and rectification behavior of tunnel junctions and diodes, respectively, i.e., a hybrid ferroelectric-ionic tunnel diode (HTD) fabricated using the CMOS materials and VLSI processes employed in modern microelectronics. From a material perspective, we harness the collective (ferroelectric-antiferroelectric polymorphism) and defective (ionic) switching character of HfO2-ZrO2 to synergistically enhance both its electroresistance and rectifying behavior. From a device perspective, we leverage the conformal growth capability of atomic layer deposition to integrate three-dimensional (3D) HTD structures to improve both the electrostatic control and array density, yielding record-high on/off (9.3 × 10^7) and rectifying (1.7 × 10^6) ratios across all two-terminal paradigms. From an array perspective, the enhanced self-rectifying behavior leads to the highest array scalability and storage capacity (10 Gb) reported for any memristive system. Overall, its unprecedented memristive performance positions the HTD as an ideal hardware building block for future 3D IMC platforms. Furthermore, the potential for engineering breakthrough properties in conventional materials and processes utilized inmodernmicroelectronics promises to accelerate the technological translation of novel functional devices and computing paradigms.