Skip to content
Open access

Multistate Ferroelectric Memory for in-Memory Differential Computing in C‑Axis‑Oriented HZO‑ZrO2 Films Enabled by Interfacial Engineering.

Sep 2026 · Small · pp. e75990 · 0 citations · 32 references
Medicine

Abstract

The von Neumann bottleneck limits energy-efficient computing. While ferroelectric hafnium zirconium oxide (HZO) memories are promising for in-memory computing, achieving high speed, endurance, and reliable multilevel control remains challenging. This work addresses these challenges through interfacial engineering with an ultrathin ZrO2 seed layer. Atomic-resolution microscopy reveals that this interlayer promotes preferential c-axis orientation of the ferroelectric orthorhombic phase, aligning the polarization axis with the applied electric field. This enables nanosecond (6 ns) switching, long-term retention (>104 s), and stable programming of 10 distinct polarization states. Based on these capabilities, we demonstrate an in-memory differentiator within a single device. Analog values encoded as discrete polarization levels enable direct first- and second-order derivative calculations, where the transient switching current represents the differential output. This atomic-scale structural control provides a materials-to-system link that may facilitate real-time, energy-efficient data processing.

Read PDF

Similar papers

Open access Sep 2026

High-precision hyperdimensional computing enabled by in-memory computing using high-polarization ferroelectric Hf0.5Zr0.5O2 capacitors

We demonstrate high-precision hyperdimensional computing using an in-memory computing (IMC) architecture based on ferroelectric Hf0.5Zr0.5O2 (HZO) capacitors. By exploiting the high polarization charge density of CMOS back-end-compatible HZO, we achieved 32 well-separated and linearly programmable intermediate states i...

Ella Paasio, Simon Thomann, Anika Anu et al. · 0 citations
Sep 2026

Self-Limiting Oxide Dielectric Enables Interface-State Engineering in p-Type m-GaTe Transistors Toward Bio-Inspired Visual Recognition.

The development of efficient artificial intelligence hardware has spurred interest in neuromorphic systems that unify sensing, memory, and computing. Optoelectronic synaptic transistors are appealing due to their rapid response times, broad spectral range, and low energy consumption. However, most 2D material-based sys...

Bo-Xiang Gao, Ruihan Xu, He Shao et al. · 0 citations
Aug 2026

Thermal-Budget-Decoupled Integration of Freestanding Hafnium-Based Ferroelectric Dielectrics for van der Waals Memory Transistors.

Ferroelectric memories have emerged as promising candidates for nonvolatile memory and neuromorphic computing owing to their capability for direct channel modulation through polarization switching. However, the high thermal budget required for synthesis and post-annealing processes hampers scalable integration and degr...

Song Zhao, Ming-Chun Zheng, Feng-Shou Yang et al. · 0 citations
Aug 2026

Ferroelectric-Enhanced Ultrafast Nonvolatile Floating-Gate Memory.

Floating-gate memory, as one of the most widely used nonvolatile memories for practical deployments, plays a significant role in modern electronics. However, its inherent speed limitations make it challenging to keep pace with the explosive growth of data generation and the evolving demands of innovative hardware appli...

Zheng Zhang, Kang Wang, Jianguo Dong et al. · 0 citations
Open access Sep 2026

Array-Level Integration of MoS2-Hf0.5Zr0.5O2 Ferroelectric Memristors for in-Memory Image Preprocessing in Neural Networks.

In-memory computing using floating-gate memristor (FGMEM) arrays with 2D channels enables large-scale parallelism, low energy consumption, efficient hardware-level matrix-vector multiplications. However, tunneling-based FGMEM faces high operating voltage, slow programming, low on/off ratio, and a small memory window. H...

J. Lee, Won Woo Lee, Jung Um Park et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.