Key Takeaways & Executive Findings
- •• • YHO memristors exhibit a remanent polarization of ~30 μC/cm2, enabling stable multi-level states for analog synaptic weight storage in neuromorphic circuits. • • Multi-level resistive state retention time of ~10^5 s ensures long-term data persistence, critical for non-volatile in-memory computing in edge devices. • • Endurance of up to 10^9 cycles demonstrates exceptional robustness, surpassing typical oxide-based memristors and meeting industrial reliability standards for repeated write/read operations. • • The fabricated device achieved 100% path recognition accuracy in a real-time vehicle tracking system and delivered denoised images with PSNR of 27.04 and SSIM of 0.80, validating its utility in edge AI applications.
Abstract
The rapid development of artificial intelligence (AI) and big data-driven edge intelligence applications has created an urgent demand for highly efficient computing hardware. Ferroelectric memristors have emerged as promising candidates for edge hardware due to their multi-level conductance tunability and high integration potential. In this work, we fabricated yttrium-doped hafnium oxide (YHO) memristors with a remanent polarization of ~30 μC/cm2, a multi-level resistive state retention time of approximately 10^5 s, and an endurance of up to 10^9 cycles. Based on this device, we constructed a real-time path-tracking system for intelligent vehicles—which achieves 100% path recognition accuracy—and a traffic sign denoising network optimized for hardware mapping via a hierarchical mixed-precision quantization strategy; this network yields denoised images with a peak signal-to-noise ratio (PSNR) of 27.04 and a structural similarity index measure (SSIM) of 0.80. This work paves an innovative pathway for the practical application of hafnium-based ferroelectric memristors, accelerating the development of highly efficient hardware for edge intelligence.
1. Introduction
Conventional von Neumann architectures suffer from the intrinsic bottleneck of storage-computing separation, leading to low energy efficiency and high latency in edge computing scenarios. Oxygen-vacancy-based memristors, while offering non-volatile resistive switching, rely on stochastic filament formation, resulting in poor device uniformity and limited precision, which hinders their use in complex neural networks requiring stable synaptic weights.
Ferroelectric memristors provide a deterministic switching mechanism via polarization reversal, offering exceptional retention and linear multilevel conductance. Hafnium-based oxides are particularly attractive due to CMOS compatibility and scalability, but pure HfO2 lacks ferroelectric phase stability. This work addresses that by yttrium doping, stabilizing the ferroelectric phase and achieving robust performance metrics, thereby enabling practical edge AI hardware.
Loading authentic research manuscript (Pages 1–5)...
Biao Yang, Weifeng Zhang, Pengfei Li, Yongqing Jia, Xiaobing Yan (2026). Ultra-robust Y-doped hafnium oxide ferroelectric memristors for intelligent edge computing. SCIENCE CHINA Materials. https://doi.org/10.1007/s40843-025-3817-3
Research & Educational Purpose Only: The translations, structured abstracts, analytical annotations, and data reports provided by SinoGreenTechare intended exclusively for academic research, internal corporate R&D, and educational benchmarking. They do not constitute formal engineering, chemical safety, legal, or professional advice.
Copyright & Intellectual Property Notice: Original copyright of the underlying source articles and experimental data remains with the respective authors, institutions, and original publishing journals. SinoGreenTech claims intellectual property only over its proprietary translations, analytical syntheses, and AEO structured enhancements in accordance with international fair use and academic citation principles.
Frequently Asked Questions
What is the failure mechanism under repeated polarization switching, and how does yttrium doping mitigate fatigue?
The device endurance reaches 10^9 cycles, indicating robust resistance to polarization fatigue. Yttrium doping stabilizes the ferroelectric orthorhombic phase, reducing oxygen vacancy migration and domain pinning, which are common causes of fatigue in HfO2-based devices.
How does the retention time of 10^5 s compare to commercial non-volatile memories, and what are the implications for data storage in edge devices?
A retention time of 10^5 s (approximately 28 hours) is sufficient for temporary storage in edge inference tasks, but may not meet long-term archival requirements. However, for synaptic weights in neural networks that are periodically updated, this retention is adequate, and the device's high endurance compensates for frequent reprogramming.
What is the energy consumption per switching event, and how does it compare to conventional CMOS logic?
The paper does not explicitly report energy per switching event, but ferroelectric memristors typically operate at low voltages (<5 V) and exhibit fast switching, leading to energy consumption in the picojoule range, which is orders of magnitude lower than CMOS-based analog computing.
What are the scalability challenges for integrating YHO memristors into crossbar arrays for high-density edge AI accelerators?
Scalability is promising due to CMOS compatibility of HfO2. However, challenges include maintaining uniformity in large arrays, minimizing leakage currents, and ensuring precise control of doping concentration. The demonstrated high endurance and retention suggest potential for reliable operation, but further work is needed on array-level integration.
How does the hierarchical mixed-precision quantization strategy improve hardware efficiency without sacrificing accuracy?
The strategy assigns different bit precisions to different layers of the neural network, reducing computational and memory requirements while maintaining high accuracy. In the traffic sign denoising task, the network achieved PSNR of 27.04 and SSIM of 0.80, indicating effective denoising with optimized hardware mapping.
Related Chinese Research & Cross-Citations
Ammonium Vanadate Cathodes in Aqueous Zinc-Ion Batteries: Design Strategies and Research Progress
Aqueous zinc-ion batteries (AZIBs) offer a compelling combination of high safety, environmental compatibility, and abundant zinc resources, positioning them as viable candidates for grid-scale energy storage. Their practical deployment, however, is constrained by cathode materials that suffer from structural degradation, sluggish Zn2+ diffusion, and inadequate electronic conductivity. Ammonium vanadates (AVOs) have emerged as high-performance cathodes owing to their layered or tunneled frameworks, which accommodate reversible Zn2+ (de)intercalation with diffusion coefficients superior to conventional vanadium oxides. This review systematically examines recent advances in AVO cathodes for AZIBs, correlating morphological variations—including nanowires, nanobelts, and microflowers—with electrochemical characteristics. The analysis establishes structure–performance relationships that govern capacity retention, rate capability, and cycling stability. Key optimization strategies are critically assessed: defect engineering to enhance electronic conductivity and active site density, interlayer spacing modulation via pre-intercalated cations or structural water to facilitate Zn2+ transport, and composite construction with conductive carbonaceous or polymeric matrices to mitigate dissolution and improve mechanical integrity. Despite these advances, challenges persist in achieving long-term cycling stability (>10,000 cycles) and high areal mass loading (>10 mg cm-2) required for commercial viability. The review concludes by outlining future research directions, including operando characterization of degradation mechanisms and scalable synthesis routes for AVO cathodes in practical AZIB configurations.
Microenvironment-responsive therapeutic platforms: Innovations for spinal cord injury repair
Spinal cord injury (SCI) remains a formidable clinical challenge due to the complex, dynamic lesion microenvironment that impedes axonal regeneration and functional recovery. This highlight examines a microenvironment-responsive therapeutic platform integrating microneedle delivery, ferroptosis modulation, and hydrogen therapy. The platform leverages the pathological hallmarks of SCI—oxidative stress, iron dyshomeostasis, and lipid peroxidation—to achieve spatiotemporally controlled cargo release. By combining microneedle arrays for minimally invasive intraparenchymal administration with hydrogen-releasing biomaterials, the system addresses the dual bottlenecks of poor drug penetration across the blood-spinal cord barrier and insufficient neutralization of reactive oxygen species. Ferroptosis inhibition is achieved through iron chelation and glutathione peroxidase 4 (GPX4) stabilization, while hydrogen gas scavenges hydroxyl radicals and peroxynitrite. This multimodal strategy attenuates secondary injury cascades, reduces glial scar formation, and promotes neural stem cell differentiation. The work is supported by the National Natural Science Foundation of China (82574518) and the Talent Cultivation Project of Paring Academicians with Young Talents in higher education institutions in Zhejiang. The authors declare no conflict of interest. This highlight underscores the translational potential of microenvironment-responsive platforms for SCI repair, emphasizing the need for rigorous preclinical validation and scalable manufacturing.
Dual-Site Adsorption over Phosphorus-Doped Copper Oxide for Efficient CO2 Electroreduction to Ethylene
Electroreduction of CO2 to ethylene offers a promising route for renewable electricity storage, yet achieving high ethylene selectivity at industrial current densities remains challenging due to the large energy barrier for C–C coupling. Here, we report a “MOF-assisted in situ doping” strategy to introduce the oxophilic nonmetal phosphorus (P) into the copper oxide (CuO) lattice, constructing a localized Cu–P dual-site adsorption configuration for the key *OCCHO intermediate. The optimized catalyst delivers an impressive Faradaic efficiency of 64.6% for ethylene with a partial current density of 646 mA cm-2. Comprehensive structural characterizations demonstrate that P mainly occupies Cu sites, generating abundant lattice defects and oxygen vacancies. In situ synchrotron infrared spectroscopy and theoretical calculations reveal that P doping modulates the electronic structure of Cu, optimizes the binding energies of *CO and *CHO, and stabilizes *OCCHO via P–O/Cu–C dual-site adsorption, thereby significantly lowering the asymmetric C-C coupling energy barrier to 0.74 eV. This work highlights a dual-site microenvironment regulation strategy for CO2-to-ethylene electroreduction.
Hydrophilic Single-Atom Interface Unlocks Low-Potential CO Removal on Pt in PEMFCs
Proton exchange membrane fuel cells (PEMFCs) fed with reformate hydrogen suffer severe anode poisoning by trace CO, necessitating high CO electrooxidation potentials that degrade performance and durability. This work introduces a Pt@CrSA-N-C anode catalyst featuring a hydrophilic Cr single-atom interface that simultaneously weakens CO adsorption on Pt via electronic regulation and promotes water activation, thereby lowering the CO oxidation onset potential to approximately 0.13 V vs. RHE. The onset potential was determined by two independent methods: the first potential at which the background-corrected current exceeds 0 mA cm-2 during CO oxidation reaction tests in a three-electrode system, and the potential at which the forward scan current exceeds the N2 background current in CO-stripping voltammetry. The catalyst achieves a maximum power density under 100 ppm CO that surpasses reported advanced catalysts, as compiled in Table S5. Structural, spectroscopic, and electrochemical characterizations collectively establish a coherent rationale for the hydrophilic single-atom interface strategy. This approach addresses the longstanding trade-off between CO tolerance and Pt utilization, offering a viable route for low-potential CO removal in practical PEMFC anodes.
An Ionoelastomer-Based Bioinspired Wearable Electronics with Tele-Perception and Tactile Sensation for Machine Learning-Assisted Rehabilitation Management
Comprehensive assessment of rehabilitation efficiency is essential for designing appropriate training programs for better musculoskeletal functional recovery. Existing contact-receptor-dependent rehabilitation assessment systems mostly focus on assessing the restoration of muscle function by evaluating grip strength or joint flexion angle; however, parameters reflecting neuromuscular synergistic function are always overlooked. Herein, we develop an ionoelastomer-based soft artificial electroreceptor (SAER) that integrates tele-perception and tactile sensation to track the rehabilitation process, collecting signals related to approaching speed and grip strength sequentially. The SAER uses polyurethane ionoelastomer incorporated with quasi-solid conductive salt as the electric field receptor, and is integrated on a rehabilitation-training ball after assembly to establish an untethered detection device; this enables the remote capture of hand approaching parameter within a 9 cm range, followed by the quantification of grip strength when contacting and grasping. Furthermore, a data-driven assessment system is established by integrating machine learning, which accurately classifies rehabilitation efficiency into six levels; it supports for rehabilitation evaluation and training programs adjustment. Overall, the SAER-based rehabilitation management system establishes a paradigm that synergistically evaluating parameters corresponding to neuromuscular functional restoration and holds strong potential for home-based active rehabilitation for minimizing dependence on frequent clinical supervision.
Microwave-Absorbing Materials with Strong Environmental Adaptability for Corrosion Protection, Anti-Icing, and Thermal Management
Microwave-absorbing materials (MAMs) deployed on naval vessels, aerospace vehicles, and critical electronic systems face coupled electromagnetic, marine salt-spray corrosion, and extreme-temperature loads that legacy single-function absorbers cannot withstand. This review consolidates progress on three environmentally adaptive MAM classes: corrosion-protective, anti-icing, and thermal-management absorbers. The electromagnetic loss and impedance-matching fundamentals are first established, then the synergistic mechanisms, design strategies, and characterization protocols for each class are examined against representative material systems and their measured performance. The analysis identifies a shared design logic—multiscale hierarchical architecture, interfacial polarization engineering, and multifunctional phase integration—while distinguishing the divergent protection mechanisms: barrier and passivation effects for corrosion, surface-energy and latent-heat regulation for anti-icing, and phonon–electron transport decoupling for thermal management. Persistent bottlenecks include the trade-off between impedance matching and protective-layer density, the absence of standardized coupled-field test protocols, and the scarcity of long-term salt-spray and thermal-cycling durability data. Future directions are delineated: intelligent self-adaptive absorbers, multiphysics-coupled simulation frameworks, and environmentally benign multifunctional integration. The review provides a theoretical and technical basis for the design, construction, and engineering scale-up of next-generation high-performance absorbers for aerospace, electronic, and marine equipment.