Chiral antiferromagnets1,2 host octupole order3,4 and combine the advantages of antiferromagnets and ferromagnets. Despite the development of numerous switching strategies5-9, the field-free full switching remains unknown, posing an important obstacle to their practical application in memory technology. Here we prepared a homo-junction constituted of Mn3Sn(0001) bottom layer and polycrystalline Mn3Sn top layer. The tilted Kagomé geometry in polycrystalline Mn3Sn divides the out-of-plane spin polarization from Mn3Sn(0001) layer10,11 into the out-of-Kagomé-plane and in-Kagomé-plane components, generating the symmetric (antiferromagnet-type) and asymmetric (ferromagnet-type) driving forces, respectively. The former accelerates octupole rotation, whereas the latter determines switching chirality. Field-free full switching is realized in the unconventional protocol that integrates the advantages of both antiferromagnetic and ferromagnetic switching. It goes beyond the conventional full-switching framework requiring perpendicular uniaxial anisotropy7,12. An unprecedented switching efficiency is achieved, with both current density and power consumption an order of magnitude lower than in previous configurations, by virtue of the highly efficient driving forces due to spin-torque characteristics of octupole order and the ultralow energy barrier arising from easy-plane anisotropy, overcoming their trade-off in conventional protocols. The zero-field switching also shows the advantages of octupole-programmable chirality and robustness to external magnetic field.

NAND flash memory reliability is increasingly challenged by rising data density and frequent program/erase cycles. While Error Correction Codes (ECC) are standard, the simultaneous use of ECC-embedded NAND and ECC-capable host systems is generally avoided due to the risk of unpredictable behavior and file system corruption. Existing studies on the use of dual ECC primarily focus on switching between different ECC structures or adaptive decoding based on error rates and data characteristics. In contrast, this paper introduces a novel driver-level coordination framework that enables the concurrent and integrated operation of two independent ECC mechanisms. By managing the interaction within the Memory Technology Device (MTD) layer, our approach enables the simultaneous utilization of internal NAND ECC and host-side ECC—a combination traditionally considered incompatible. Our approach improves overall system reliability and relaxes product-matching restrictions. Although the solution introduces a minor latency penalty, it is highly effective for applications where data integrity is the primary concern. Experimental results demonstrate that our solution prevents data corruption and extends the lifetime of NAND flash memory.

Organic ferroelectric field-effect transistors (OFeFETs) are promising candidates for next-generation wearable electronics and non-volatile memory technologies owing to their bistable switching, low power consumption, and mechanical flexibility. Here, room-temperature organic chiral multiferroic FETs are demonstrated, in which both gate field and chiral field dependence of charge-spin conversion are studied. Remarkably, the chiral FET presents tens of micrometer chiral signal transport. This long-range chiral transport provides an ideal platform for probing the interaction between charge and chirality-induced polarized spin. The interfacial dipoles in the ferroelectric layer could impact the degree of charge carrier localization to further modulate spin polarization, presenting a charge-spin conversion-dependent magnetoelectric coupling. Conversely, polarized spin in the organic chiral layer could modify saturated ferroelectric polarization and ferroelectric hysteresis loop, apparently. In addition, when an external magnetic field is applied parallel (antiparallel) to the chiral axis, the OFET shows an enhanced (weakened) chiral magneto-chiral current, which can also be modulated by remanent polarization.

Phase-change random-access memory (PCRAM) is an emerging technology for next-generation memory owing to its high on/off ratio, simple fabrication, and excellent stability. However, its unipolar operation limits its ability to replicate the complex synaptic behaviors required for neuromorphic applications. Although unipolar PCRAM has been explored as a neuromorphic device, its performance is limited by the intricacies of peripheral circuit requirements. To achieve better bipolar operation, this study introduces a novel bipolar PCRAM structure by incorporating titanium interlayers into an SbTe-based PCRAM device. The integration of titanium as an atomic migration moderator reduces diffusion pathways, thereby stabilizing the operating voltage to approximately ±0.6 V while increasing endurance to more than 8 × 104 cycles. Furthermore, various synaptic behaviors such as potentiation, depression, and spike-timing-dependent plasticity were reliably mimicked. Neural network simulations performed with experimental data from the device achieved 88% classification accuracy on the Modified National Institute of Standards and Technology dataset, highlighting the feasibility of this architecture for real-world neuromorphic applications. The proposed bipolar PCRAM structure simplifies circuit design and offers a scalable approach for efficient neuromorphic computing.

As dynamic random-access memory (DRAM) technology continues to scale down to sub-10 nm nodes, achieving high memory density and enhanced operational performance poses increasing challenges. In particular, maintaining sufficient cell capacitance and minimizing the leakage current density have emerged as key issues. To address these issues, the development of novel electrode materials and carefully engineered interfaces between high-k dielectrics and electrodes is crucial. In this study, thermal atomic layer deposition (ALD) of Sn-incorporated MoOx (TMO) films was performed using (NtBu)2(NMe)2Mo and Sn(dmamp)2 as the Mo and Sn precursors, respectively. The growth characteristics of the TMO films, particularly the interaction between the MoOx and SnOx subcycles, were systematically investigated. Controlled Sn incorporation into MoOx successively stabilized the formation of the monoclinic MoO2 phase, resulting in a smooth surface morphology and enhanced thermal and chemical stability. ALD TMO films were employed as an interface control layer (ICL) in a metal-insulator-metal capacitor to improve the interfacial properties between the (Al-doped) TiO2 and TiN bottom electrodes. ALD TMO films promoted the in situ crystallization of rutile TiO2 (with a dielectric constant of up to 156) and effectively suppressed the unwanted formation of a low-k TiOxNy layer, resulting in significant equivalent oxide thickness (EOT) scaling. Furthermore, the insertion of the TMO ICL significantly reduced the leakage current density of the (Al-doped) TiO2 films, which was attributed to the higher work function of TMO (4.7-4.8 eV) compared to that of TiN (4.5 eV) and the minimal formation of defective TiOxNy. To evaluate the scalability of the ALD TMO ICL, its thickness was varied from 20 to 1 nm. Remarkably, even at the ultrathin thickness of 1-2 nm, TMO ICL maintained high capacitance and low leakage current density, achieving an EOT of 0.58 nm and leakage current density of 2.4 × 10-7 A/cm2. These results highlight the potential of ALD-grown TMO films as ICLs in next-generation DRAM capacitors.

ABSTRACT Phase‐change memory (PCM) displays great promise for the storage‐class memory (SCM) technology due to its combination of fast speed of dynamic random‐access memory and nonvolatility of Flash. Yet, to meet the high industrial requirement of write/erase speed for the SCM application, robust strategies for further accelerating phase transition, particularly from amorphous to crystalline PCM materials, are urgently needed. In this work, we propose a unique strategy of coherent‐interface induced ultrafast crystallization in PCM materials. Employing rock‐salt YAs/Ge 2 Sb 2 Te 5 as a prototype, systematic first‐principles molecular dynamics demonstrate that rapid nonstochastic crystallization behaviors can be achieved by the rock‐salt‐lattice‐matching and high‐temperature‐resistant heterogeneous interface attached to the popular PCM material Ge 2 Sb 2 Te 5 (GST). Further experiment shows that the YAs‐incorporated GST device has a faster SET process compared with the pure GST device. Finally, to extend the strategy in the family of inorganic materials, high‐throughput screening from over 150 000 structures discovers as many as 71 candidates for coherent interfaces with PCM GST. The present study establishes a promising strategy to overcome the speed bottleneck of PCM through atomic‐scale interface design for future storage‐class memory implementation.

It is of great interest to develop methods to rapidly and effectively control the magnetic configurations in artificial spin ices, which are arrangements of dipolar coupled nanomagnets that have a variety of fascinating collective magnetic phenomena associated with them. This is not only valuable in terms of acquiring fundamental understanding but is also important for future high-performance applications. Here, we demonstrate ultrafast control of magnetic relaxation in artificial square ice through femtosecond laser pulsed excitation, enabling rapid access to low-energy states via dipolar interactions. Time-resolved magneto-optical Kerr effect measurements reveal that, after laser-induced demagnetization, the magnetization recovers 60% of its original value within 40 picoseconds. During this brief time window, dipolar coupling drives a collective magnetic ordering. magnetic force microscopy confirms the emergence of extended domains with the lowest-energy vertex configuration, characteristic of ground-state ordering, thus establishing ultrafast laser-driven relaxation as a route to attain the low-energy states. Through complementary energy barrier calculations and micromagnetic simulations incorporating Landau-Lifshitz-Bloch dynamics, we elucidate the underlying mechanism: transient ultrafast demagnetization followed by rapid remagnetization that enables a dipolar-driven collective rearrangement. Moreover, a tailored decreasing-fluence laser excitation protocol is shown to enhance ground-state ordering, consistently achieving over 92% ground-state vertex populations. This work opens the way to ultrafast and spatially selective control of magnetic states in artificial spin ice for spin-based computation and memory technologies, and highlights the critical interplay of thermal fluctuations, magnetostatic coupling, and transient magnetization dynamics.

The reliable integration of high-κ dielectrics within van der Waals (vdW) heterostructures is essential for achieving low-power, high-performance nonvolatile floating gate transistors (FGTs). Here, we demonstrate fully functional vdW FGTs employing thermally oxidized hafnia HfOx from layered HfSe2 as both tunneling and control dielectric layers. A ∼5 nm-thick HfOx layer enables efficient Fowler–Nordheim tunneling at low bias, while a thicker layer of >10 nm serves as a robust gate dielectric, providing efficient gate controllability. The resulting FGTs can be operated with low voltages below 4 V, showing pronounced memory hysteresis, multilevel memory capability, and excellent data retention reaching 104 s. This work establishes a feasible strategy for integrating high-quality ultrathin oxides into 2D heterostructures, providing a promising route toward energy-efficient and high-density nonvolatile memory technologies.

The superconducting diode effect (SDE), which manifests as directional, dissipationless supercurrents, is pivotal for realizing energy-efficient superconducting logic and memory technologies. However, achieving high-efficiency SDE without external magnetic fields remains a fundamental challenge. In this study, a strongly enhanced, field-free SDE in Pt/Co/Nb heterostructures are proposed, enabled by the interplay of engineered geometric asymmetry and stray fields from a perpendicularly magnetized Co layer. This configuration promotes directional vortex entry and spatially selective pinning, yielding diode efficiencies that exceed all previously reported field-free values in ferromagnet/superconductor multilayers. Temperature- and field-dependent transport measurements, supported by micromagnetic simulations, reveal that the enhanced nonreciprocity results from three cooperative mechanisms: asymmetric vortex entry, localized magnetic pinning, and Lorentz-force imbalance. These findings establish a CMOS-compatible platform for high-performance superconducting rectifiers, offering new opportunities for cryogenic spintronics and quantum electronics.

HfO2-based ferroelectric materials have emerged as leading candidates for next-generation non-volatile memory technologies, owing to their nanoscale robust ferroelectricity and complementary metal-oxide-semiconductor (CMOS) compatibility. However, challenges and debates persist in advancing and comprehensively understanding their ferroelectric behavior. In particular, conventional approaches typically regard non-ferroelectric phases as detrimental and primarily focus on suppressing their formation, yet overlooking their potentially synergistic contributions-particularly those of the tetragonal (T) phase. Here, we unambiguously clarify the beneficial role of the T-phase and introduce a phase-boundary engineering strategy that deliberately harnesses it to enhance ferroelectricity in HfO2 films. By stabilizing optimal coherent boundaries between ferroelectric orthorhombic (O) and T phases in epitaxial La-doped HfO2 films, we achieve significant improvements in ferroelectric properties-doubling the remanent polarization (Pr ∼ 30 µC/cm2) and substantially reducing the coercive field (Ec ∼ 3 MV/cm) by 30% compared to low-La doped samples without such boundaries. Atomic-scale electron microscopy reveals the structural nature of the atomically sharp, coherent O-T boundaries. Combined with deep-learning enhanced molecular dynamics simulations, our results unravel that these boundaries facilitate intermediate polarization states that lower the switching energy barrier. Consequently, phase coexistence shifts from an inherent drawback to a tunable design element, offering a broadly applicable route to ultra-low-power HfO2-based nanoelectronics.

Ferroelectric field-effect transistors (FeFETs), a type of ferroelectric memory with a transistor-based structure, have attracted significant attention from integrated circuit researchers due to their compact device architecture, non-destructive readout capability, and elimination of additional selector devices. These advantages make FeFETs highly promising for achieving higher storage density and enabling computing-in-memory applications. For their practical industrial deployment, extensive studies have been conducted on device fabrication, circuit design, and reliability. Among the key challenges, enlarging the memory window (MW) while maintaining stability is critical, as it directly affects data accuracy and retention. In this work, we experimentally investigate the modulation of the MW and interface defect density (ΔNit) in Zr-doped HfO2(HfZrOx)-based FeFETs under different polarization states of the ferroelectric gate dielectric. The results demonstrate that with progressively enhanced ferroelectric polarization, the MW expands, while the interface trap density is simultaneously suppressed, suggesting that robust polarization effectively inhibits the formation of interface defects and improves subthreshold swing characteristics of the device. Furthermore, TCAD simulations were conducted to systematically investigate the impact of various ferroelectric properties, including remanent polarization (Pr), saturation polarization (Ps) and variations in coercive field (Ec), on the memory characteristics of HfZrOxFeFETs. It was confirmed that higher polarization can alleviate the degradation caused by defects. In addition, an increase inPrandPs, together with a lowerEc, enhances the surface potential difference, charge separation, and switching efficiency, thereby improving both the MW and the stability of the device. This study provides valuable insights for the development of reliable FeFET-based memory technologies.

ABSTRACT The accelerating evolution of artificial intelligence (AI) has underscored the need for energy‐efficient hardware that can overcome the memory bottleneck inherent to von Neumann architectures. To address this challenge, compute‐in‐memory (CIM) architectures based on emerging memory technologies with analog tunability and scalability have emerged as an effective solution for parallel and low‐power computation. This review discusses recent progress in emerging memories—including resistive, phase‐change, ferroelectric, electrochemical, and charge‐based devices—and their implementation in CIM architectures for both training and inference. We highlight material‐ and device‐level strategies to achieve high endurance, analog multilevel switching, and linear weight updates required for training‐centric systems, as well as stable retention and low power crucial for inference‐centric applications. Furthermore, we discuss efforts on system‐level integration that combine device‐level advances with circuit/architecture co‐optimization to construct efficient hardware platforms. By bridging materials science, device physics, and system‐level integration, this review provides a comprehensive perspective on the pathways toward energy‐efficient CIM hardware for next‐generation edge and on‐device AI systems.

Persistent Memory (PM) technologies provide fast, byte-addressable access to durable storage but face crash consistency challenges, motivating extensive work of testing and verification of PM programs. Central to PM testing tools is the specification of program properties for object persistence order and atomicity. Prior work on PM property inference has focused on ordering properties and offers limited support for reasoning about atomicity. This paper explores a class of important atomicity properties between the container-like arrays and their logical size variables, referred to as the counting correlation. These properties are prevalent in PM programs but are not adequately addressed by existing techniques. We introduce C3, a tool designed to infer these counting-related atomicity properties and detect related bugs in PM programs. Our approach begins by proposing invariants to capture the necessary behaviors of counting-correlated variables. We then utilize symbolic range analysis to extract PM program behaviors, and encode them into SMT constraints. These constraints are checked against the invariants to infer likely PM program properties. Our bug detection method is based on the existing output checking approach, but adapted to be aware of input properties to detect and confirm the atomicity bugs efficiently. Our evaluation shows that C3 has found 14 atomicity bugs (including 11 previously unknown ones) from real-world PM programs.

This study investigates research trends in cultural memory through bibliometric analysis, applying Bradford’s Law to identify core journals and VOSviewer (v1.6.19) for network visualization. Data was extracted from 409 Scopus-indexed journal articles (with ≥5 citations) on cultural memory. Bradford’s Law revealed that forty-eight core journals published approximately one-third of the literature, with Memory Studies as the leading journal (nineteen articles). The United States contributed the most publications (112 articles, 27.4%). A Pearson Correlation test examined the relationship between publication year and citations. Analysis of 177 high-frequency terms from titles/abstracts identified war as the most prominent research theme, alongside other recurring terms like heritage, power, narrative, knowledge, and identity. Findings indicate that cultural memory research predominantly addresses collective memory, trauma, and sociopolitical dimensions, but gaps remain in emerging areas. Future research directions include (1) the intersection of cultural memory and digital technology, (2) transnational and cross-cultural memory dynamics, (3) memory politics and contestation, (4) cultural memory in conflict/post-conflict societies, and (5) the economics of memory. The study highlights the field’s interdisciplinary nature while proposing underexplored topics to advance theoretical and empirical frameworks.

Achieving non-volatile, low-loss phase modulation with ultra-low energy consumption remains a challenge in photonic in-memory computing. Inspired by electrical memory technologies, mechanisms such as ion-migration, phase change transitions, and ferroelectric polarization have been explored in photonic platforms for memory functions. However, existing materials typically require large device footprints to achieve effective optical index tuning, leading to increased insertion loss and energy consumption. Here, we demonstrate a compact non-volatile phase modulator by incorporating 2D ferroelectric CuInP2S6 (CIPS) into a WS2/CIPS/graphene heterostructure, integrated on a SiN microring resonator. This vertical configuration leverages Cu+-induced polarization in CIPS to electrostatically tune the refractive index of WS2 without introducing additional optical loss or static power consumption. The intralayer Cu+-mediated ferroelectric switching (free from domain wall motion) and high dielectric constant enable the device to operate with an ultra-low switching energy of 2.5pJ per cycle, a fast write speed of 5V/µs, and an insertion loss of 0.2dB. The device further shows stable multi-level (8-bit) memory, with projected retention beyond 10 years. We showcase its potential in photonic in-memory computing by implementing the modulator within an optical neural network, achieving 92% accuracy on the MNIST handwritten digit recognition, establishing new avenues for hardware-accelerated neural networks.

The continued scaling of flash memory technologies faces challenges such as limited operation speed, poor data retention, and interface defects inherent to conventional three-dimensional architectures. Two-dimensional (2D) materials, with van der Waals interfaces and atomic-scale thickness, offer a promising pathway to overcome these limitations by enabling efficient charge modulation while minimizing surface defects. In this work, a nonvolatile 2D flash memory device is developed employing monolayer Janus MoSSe as the charge-trapping layer and hexagonal boron nitride (h-BN) as an ultrathin tunneling barrier. The intrinsic structural asymmetry of Janus MoSSe induces a strong vertical dipole moment, resulting in enhanced charge trapping, deeper energy barriers, and directional polarization compared with symmetric 2D materials. Consequently, the devices exhibit outstanding retention times exceeding 104s, endurance beyond 104 program/erase cycles, and large memory window ratios (ΔV/VG,max of 50%-70% for 10 and 6nmh-BN, respectively), with charge-trapping rates up to 8.96 × 1014cm-2s-1. In addition, Janus MoSSe-based devices show synaptic characteristics under electrical pulses and perform recognition simulations in artificial neural networks. These findings establish a design paradigm for 2D memory devices, enabling ultrathin, flexible, and energy-efficient nonvolatile memories.

With the rapid advancement in portable electronics, artificial intelligence, and the Internet of Things, there is an escalating demand for high-density, low-voltage non-volatile memory (NVM) technologies. Germanium (Ge) nanocrystals (NCs) have emerged as a promising candidate for NVM applications; however, traditional synthesis methodologies suffer from limitations in achieving precise control over the size and density of these nanocrystals, which exert a significant influence on device performance. This study presents an innovative Ag-catalyzed chemical vapor deposition (CVD) methodology for the synthesis of Ge NCs with precisely controllable size and density on SiO2/Si substrates, tailored for NVM applications. Scanning electron microscopy characterization confirms the successful growth of faceted Ge NCs. Electrical characterization of the fabricated devices reveals that Ge NCs grown at temperatures ranging from 700 to 1000 °C exhibit memory windows spanning from 3.0 to 6.8 V under a ±6 V bias. Notably, the device synthesized at 900 °C demonstrates an exceptional memory window of 7.0 V under a ±8 V bias. Furthermore, the Ge NC-based NVM devices exhibit excellent charge retention characteristics. Specifically, for the device with Ge NCs grown at 700 °C, the time required to retain charge from 100% to 95% of its initial value exceeds 10 years, demonstrating long-term stable charge storage capability. These findings underscore the significant potential of this approach for the development of high-performance NVM technologies.

Within cultural tourism, the literature on memorable experiences is fragmented and lacks clear systematization, which constitutes the knowledge gap that guides this study. The goal was to analyze the recent literature on memorable experiences in cultural tourism, through a systematic literature review pointing out an organization of the dispersion found in the three main moments of the trip of every tourist: before, during and after. For this purpose, 58 articles published between 2019 and 2024 in Scopus were examined. The results identified fourteen factors, including authenticity, engagement and cultural exchange as determinants, and other emerging factors such as mindfulness, agreed memory and new technologies. A structured synthesis and framework for managing cultural experiences is provided.

Phase-change memory (PCM) has emerged as a promising non-volatile memory technology, offering significant potential for next-generation artificial intelligence and neuromorphic computing systems. However, conventional Ge1Sb4Te7 (GST), a prototypical stoichiometric phase-change chalcogenide, suffers from intrinsic limitations such as inadequate thermal stability and pronounced resistance drift, hindering its practical applications in high-performance devices and chips. In this study, we demonstrate that carbon (C) doping in GST markedly enhances its thermal robustness and data retention, while elucidating the underlying microstructure property relationships. Carbon doping significantly increases the crystallization temperature of GST, shifting it to and beyond 200 °C with increasing carbon content. Higher carbon incorporation also yields up to a fourfold improvement in data retention, achieving 10-year stability at 100 °C. Moreover, GST-C-based PCM devices exhibit excellent electrical stability, featuring ultralow resistance drift (ν = 0.03) and highly reproducible multilevel resistance states. Through ab initio simulations, we uncover the atomic-scale mechanisms governing these enhancements: carbon incorporation induces the formation of robust, shortened bonds with Ge/Sb/Te, promoting tetrahedral C clusters that impede crystallization by elevating the activation energy barrier. This work identifies GST-C as a promising candidate for reliable, high-density PCM and highlights its potential for neuromorphic computing applications.

This study presents an atomistic nonequilibrium Green's function (NEGF) approach for modeling radiation-induced charge loss in floating-gate flash memories, which become increasingly vulnerable to radiation effects as device features shrink. Nonradiative charge-carrier recombination at localized deep-level defect centers is treated by coupling the defect Green's function to delocalized interface states derived from a two-probe tight-binding description, via multiphonon-scattering self-energies. Using oxygen vacancies as representative deep-level traps, the trap-assisted tunneling current under retention conditions is calculated by integrating the NEGF formalism within a drift-diffusion solver. This NEGF framework significantly improves agreement with experimental data from heavy-ion irradiation, and provides insights beyond semiclassical models. These findings underscore the necessity of atomistic, fully quantum treatments for reliable assessment and design of radiation-hardened nonvolatile memory technologies.