Design and Synthesis of Atomically Tunable Memristors

Neuromorphic computing (NC) is a brain-inspired computing that has recently emerged as a promising resolution to the von Neumann bottleneck of data movement in current computing based on separate processing and memory units. NC enables the information to be processed and stored in the same units and is expected to provide critical computing hardware for the emerging artificial intelligence (AI), machine learning, internet of things, etc., and may converge with quantum computing for quantum neuromorphic computing.

Researchers have attempted to mimic biological brain operation by using artificial versions of the elements known as memristors. Memristor, regarded as the fourth fundamental circuit element next to resistor, capacitor, and inductor, consists of a thin dielectric (typically oxide) film of pinched hysteresis of resistance sandwiched with a pair of electrodes to mimic the functionality of biological brain operation.

In memristors, the operations of both memory storage and computing are integrated in one device. However, as the field of NC evolves, the ability to control at the atomic scale the memristive resistance, switching speed, cycling endurance, among other performance criteria, becomes increasingly important as NC circuits potentially require devices with different performance capabilities closely integrated together.

In particular, memristors with tunable properties are critical to mimic biological brain operation. Unfortunately, an atomic-scale control of the memristor parameters has not been achieved due to lack of control in growth of ultrathin (sub-3 nm) oxides films, resulting in defects that in turn lead to reduced energy efficiency, device non-uniformity and low yield in current memristors.

The proposed research aims to address the challenges through a synergetic integration of atomically controlled synthesis of atomically tunable memristors based on ultrathin oxide atomic layer stacks (ALS), atomistic material simulation/modeling that predicts the physical properties of ALS, and advanced characterization both in situ on materials and ex situ on devices. The success of the project can have a broader impact on a large spectrum of commercial applications including NC, AI, quantum information science, etc.

Scientifically, a long-standing question in material research is whether a few atomic layers stacked with an atomic precision can provide the functionality and large-area uniformity as required for advanced electronics. This question is driven by the continuous down-sizing of transistors in last five decades to currently sub-5 nm to meet the need in future electronics with functionality tuned with an atomic precision.

Using an in vacuo ALD approach developed in PI’s prior NSF support, the proposed research aims to address the challenges through a synergetic integration of atomically controlled synthesis of oxide ALS guided by atomistic material simulation/modeling and advanced characterization both in situ and ex situ on materials and devices. Specifically in the two proposed aims, Aim 1 focuses on design and synthesis of ultrathin oxide ALS and Aim 2 investigates ALS properties at material and device levels.

The intellectual merit of the proposed research is through a new fundamental understanding of physical properties of ultrathin oxide ALS that is crucial to achieving atomically tunable memristors for future electronics and computing and a transformative leap in developing novel approaches for design and synthesis of ultrathin ALS to enable new functionalities. The achieved atomically tunable memristors based on the ALS can have a broader impact on a large spectrum of commercial applications including neuromorphic and quantum computing, artificial intelligence, quantum information science, etc.

The project emphasizes forefront education and the cutting-edge research capability which will attract high-quality students, especially those from underrepresented groups, to pursue careers in STEM fields and will further amplify the impacts towards producing a unique and diverse future workforce in science and engineering.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.