Non-volatile Memory Technologies Research Articles

Effect of Ammonium Salt on Conjugated Polyelectrolyte as an Interlayer for Organic–Inorganic Hybrid Perovskite Memristors

Memristors are promising candidates for next-generation non-volatile memory devices, offering low power consumption and high-speed switching capabilities. However, conventional metal oxide-based memristors are constrained by fabrication complexity and high costs, limiting their commercial viability. Organic–inorganic hybrid perovskites (OIHPs), known for their facile solution processability and unique ionic–electronic conductivity, provide an attractive alternative. This study presents a conjugated polyelectrolyte (CPE), PhNa-1T, as an interlayer for OIHP memristors to enhance the high-resistance state (HRS) performance. A post-treatment process using n-octylammonium bromide (OABr) was further applied to optimize the interlayer properties. Devices treated with PhNa-1T/OABr achieved a significantly improved ON/OFF ratio of 2150, compared to 197 for untreated devices. Systematic characterization revealed that OABr treatment improved film morphology, reduced crystallite strain, and optimized energy level alignment, thereby reinforcing the Schottky barrier and minimizing current leakage. These findings highlight the potential of tailored interlayer engineering to improve OIHP-based memristor performance, offering promising prospects for applications in non-volatile memory technologies.

Ferrimagnetic Heusler tunnel junctions with fast spin-transfer torque switching enabled by low magnetization

AbstractMagnetic random-access memory that uses magnetic tunnel junction memory cells is a high-performance, non-volatile memory technology that goes beyond traditional charge-based memories. Today, its speed is limited by the high magnetization of the memory storage layer. Here we prepare magnetic tunnel junction memory devices with a low magnetization ferrimagnetic Heusler alloy Mn3Ge as the memory storage layer on technologically relevant amorphous substrates using a combination of a nitride seed layer and a chemical templating layer. We switch the magnetic state of the storage layer with nanosecond long write pulses at a reliable write error rate of 10−7 and detect a tunnelling magnetoresistance of 87% at ambient temperature. These results provide a strategy towards lower write switching currents using ferrimagnetic Heusler materials and, therefore, to the scaling of high-performance magnetic random-access memories beyond those nodes possible with ferromagnetic memory layers.

Realizing multi-level phase-change storage by monatomic antimony

With the growing need for extensive data storage, enhancing the storage density of nonvolatile memory technologies presents a significant challenge for commercial applications. This study explores the use of monatomic antimony (Sb) in multi-level phase-change storage, leveraging its thickness-dependent crystallization behavior. We optimized nanoscale Sb films capped with a 4-nm SiO2 layer, which exhibit excellent amorphous thermal stability. The crystallization temperature ranges from 165 to 245 °C as the film thickness decreases from 5 to 3 nm. These optimized films were then assembled into a multilayer structure to achieve multi-level phase-change storage. A typical multilayer film consisting of three Sb layers was fabricated as phase-change random access memory (PCRAM), demonstrating four distinct resistance states with a large on/off ratio (∼102) and significant variation in operation voltage (∼0.5 V). This rapid, reversible, and low-energy multi-level storage was achieved using an electrical pulse as short as 20 ns at low voltages of 1.0, 2.1, 3.0, and 3.6 V for the first, second, and third SET operation, and RESET operation, respectively. The multi-level storage capability, enabled by segregation-free Sb with enhanced thermal stability through nano-confinement effects, offers a promising pathway toward high-density PCRAM suitable for large-scale neuromorphic computing.

Memristor & its application in biological field

Abstract Demand for highly integrated, low-power nonvolatile memories to get beyond the drawbacks of traditional memory systems has led to, Memristive/resistive switching devices which are excellent choices for non-volatile memory technology. Memristor is the 4th fundamental unit proposed by Professor Chua to give a relation between charge and magnetic flux. If a memristor’s constitutive relation is a straight line with a slope of M that passes through the origin in the ɸ –q plane, it is considered linear. The memristor’s physical realizations and potential uses remain a fascinating area for investigation.Semiconductor nanoparticles specially ZnO, ZnS QD exhibit Memristive characteristics. Employing this Memristive behaviour of biofunctionalized nanoscale particles and “voltage gap” as a novel sensing metric, several investigators attempted to assess the precise amount of microbiological contamination. Here in this work, Memristive property of some semiconductor nanoparticles like ZnO, ZnS as well as metal nanoparticle like PbS, Ag particles are studied and tried to focus on application of Memristive devices in near future in biological fields. The switching properties of bio-voltage memristors can now be used to achieve bio-voltage matching.

Natural Organic Pectin Polysaccharide Based Resistive Random Access Memory

Nowadays, non-volatile memory technologies have been widely applied in different areas. Of these memory technologies, non-volatile resistive random access memory (ReRAM) is attractive because of its simple device architecture and fabrication process, high scalability and data density, good performances in terms of switching speed, high power efficiency and reasonably wide memory window. In order to address the issues of disposable and degradation of electronic waste by typical ReRAM with the active layer made of inorganic oxide materials and fossil-fuel based polymeric materials, a green and sustainable strategy has been adopted in producing ReRAM by using natural organic-based materials based on protein and carbohydrate, such as honey, fructose, aloe vera, etc. Among these materials, pectin-polysaccharide thin film has demonstrated promising resistive switching characteristics. The two ranges of pectin concentrations that have been investigated are ³5 mg/ml and £1.5 mg/ml, and it showed that pectin with concentration <1.5 mg/ml reveals a higher ON/OFF ratio. However, the resistive switching characteristics with pectin concentration between 1.5 mg/ml and 5 mg/ml have yet been explored and reported. In this work, pectin with concentrations of 1.5~5 mg/ml were prepared from pectin-polysaccharide solution into the active switching layer, and ReRAM devices with such pectin resistive switching layer were fabricated. The pectin-polysaccharide solution, pectin resistive film, and ReRAM devices were systematically investigated. Surface tension and contact angle of pectin-polysaccharide precursor solutions as a function of pectin concentration on the substrate were measured by a goniometer. Surface topography of solidified thin films was characterized by an atomic force microscope (AFM) and a field-emission scanning electron microscope (FE-SEM). Chemical functional groups of the pectin-polysaccharide precursor solutions and solidified thin films were examined by a Fourier transform infrared (FTIR) spectroscopy. The resistive switching behaviors were characterized and compared by electrical measurement. The results show that 4 mg/ml recorded the highest ON/OFF ratio compared to ever reported values, as well as desirable memory window, non-volatility in retention, and stability over 100 cycles. This study proves that pectin-polysaccharide is a promising green and sustainable bio-organic material for non-volatile ReRAM for electronic applications such as in emerging neuromorphic computing systems.

NVM-Enhanced Machine Learning Inference in 6G Edge Computing

With the increasing popularization of smart terminals and real-time interactive applications, fast growing technical requirements push both academia and industry to look beyond 5G and conceptualize the sixth generation (6G) mobile network. Artificial intelligence (AI) with machine learning capacities at the edge is one crucial component of a 6G mobile network which makes various time-sensitive and high-stake services possible, e.g., smart security, virtual reality, self-driving vehicles. However, resource constraints, especially the memory limitation of edge servers, become major obstacles to deploying machine learning services at the edge. Fortunately, the new generation of non-volatile memory (NVM) provides new affordable memory resources that can be easily attached to existing edge servers. In this paper, we propose a novel machine learning application placement scheme using the NVM technology at the edge to reduce the end-to-end latency. Specifically, the proposed NVM-enhanced placement scheme takes into consideration the latency of various machine learning applications over NVM devices and the network. The corresponding optimization problem is exceedingly challenging, i.e., NP-hard. Therefore, we developed a novel approximation algorithm with both low computational complexity and theoretical guarantees. Experiments and extensive simulations using real-world applications highlight that our scheme provides significantly lower end-to-end latency compared with existing baselines.

The structure and formation of non-volatile memory cells of Superflash

Split-gate embedded Flash memory technology has been around for decades and has become the standard for a wide range of devices, such as microcontrollers and smart cards. Among the, due to a number of advantages, Silicon Storage Technology Super Flash non-volatile memory technology has become the most widespread. This article presents the results of a study of the memory cells structure, examines in detail the principle of their operation and the main technological stages of the production process of forming transistor structures.

Emerging non-volatile memory (NVM) technologies based nano-oscillators: Materials to applications

This comprehensive study provides a detailed review toward ongoing research on emerging non-volatile memory technologies based nano-oscillators, i.e., from the perspective of materials to applications. Depending on the materials used to fabricate them, the whole class of emerging nano-oscillators has been broadly classified into two categories: (i) electronic and (ii) spintronic oscillators. Moreover, various material-compositions explored for fabricating the oscillatory devices, their physical properties responsible for generating the oscillations, and device architectures are thoroughly reviewed. Furthermore, various advanced computing applications (i.e., realized through these oscillatory devices), such as Internet of Things, neuro-inspired computing, and sensing, are also studied and their key attributes are highlighted.

Exploring charge transfer and schottky barrier modulation at monolayer Ge2Sb2Te5-metal interfaces

Monolayer Ge2Sb2Te5exhibits great potential in non-volatile memory technology due to its excellent electronic properties and phase-change characteristics, while the fundamental nature of Ge2Sb2Te5-metal contacts has not been well understood yet. Here, we provide a comprehensiveab initiostudy of the electronic properties between monolayer Ge2Sb2Te5and Pt, Pd, Au, Cu, Cr, Ag, and W contacts based on first-principles calculations. We find that the strong interaction interfaces formed between monolayer Ge2Sb2Te5and Pt, Pd, Cr, and W contacts show chemical bonding and strong charge transfer. In contrast, no apparent chemical bonding and weak charge transfer are observed in the weak interaction interfaces formed with Au, Cu, and Ag. Additionally, our study reveals the presence of a pronounced Fermi level pinning effect between monolayer Ge2Sb2Te5and metals, with pinning factors ofSn=0.325andSp=0.350. By increasing the interlayer distance, an effective transition fromn-type Ohmic contact ton-type Schottky contact is facilitated because the band edge of Ge2Sb2Te5is shifted upwards. Our study not only provides a theoretical basis for selecting suitable metal electrodes in Ge2Sb2Te5-based devices but also holds significant implications for understanding Schottky barrier height modulation between semiconductors and metals.

Non-Volatile Memory Technology Poised for Game-Changing Breakthrough

Why novel nanocomposite-superlattices for low-energy, high-stability nanoscale phase-change memory is poised as an innovation touchstone for the memory segment and the entire industrial ecosystem.

Influence of HfO2 oxide layer on crystallization properties of In3SbTe2 phase change material

Phase Change Memory (PCM) represents a potential paradigm in the realm of non-volatile memory technologies, and several phase change materials are studied for utilization in PCM devices. This work employs a less explored In3SbTe2 (IST) phase change material (active layer) integrated with an oxide (HfO2) layer and investigates the influence of the oxide layer on the active layer. The oxide layer remains amorphous when annealed at 400 °C, and it doesn’t alter the crystallization temperature (290 °C) of the active layer in IST with HfO2 thin-film. However, after crystallization, the grain size of the active layer is reduced to ∼8.23 nm in IST with HfO2 thin-film, compared to only IST thin-film. XPS core-level spectra (In 3d, Sb 3d, Te 3d) of IST active layer reveal the peak shifting towards higher binding energy at 300 °C and 400 °C annealed films, implying bond energy increase with crystallization and film stability improves. The Hf or O atoms of the oxide layer don’t diffuse into the active layer with annealing, suggesting no interference with the phase switching property of IST. A higher optical bandgap of 1.154 eV in as-deposited IST with HfO2 thin-film compared to the only IST thin-film illustrates better stability of the amorphous state in the film with the oxide layer. In addition, the fabricated PCM device using the IST with the oxide layer demonstrates phase switching at a lower threshold voltage of (2.1 ± 0.1) V, compared to the IST-based device. The findings indicate that the enhanced structural and electrical switching characteristics of IST phase change layer coupled with an oxide layer make it beneficial for data storage PCM applications.

A verified durable transactional mutex lock for persistent x86-TSO

The advent of non-volatile memory technologies has spurred intensive research interest in correctness and programmability. This paper addresses both by developing and verifying a durable (aka persistent) transactional memory (TM) algorithm, dTMLPx86. Correctness of dTMLPx86 is judged in terms of durable opacity, which ensures both failure atomicity (ensuring memory consistency after a crash) and opacity (ensuring thread safety). We assume a realistic execution model, Px86, which represents Intel’s persistent memory model and extends the Total Store Order memory model with instructions that control persistency. Our TM algorithm, dTMLPx86, is an adaptation of an existing software transactional mutex lock, but with additional synchronisation mechanisms to cope with Px86. Our correctness proof is operational and comprises two distinct types of proofs: (1) proofs of invariants of dTMLPx86 and (2) a proof of refinement against an operational specification that guarantees durable opacity. To achieve (1), we build on recent Owicki–Gries logics for Px86, and for (2) we use a simulation-based proof technique, which, as far as we are aware, is the first application of simulation-based proofs for Px86 programs. Our entire development has been mechanised in the Isabelle/HOL proof assistant.

Tunable magnetic synapse for reliable neuromorphic computing

Artificial neural networks (ANNs), inspired by the structure and function of the human brain, have achieved remarkable success in various fields. However, ANNs implemented using conventional complementary metal oxide semiconductor technology face significant limitations. This has prompted exploration of nonvolatile memory technologies as potential solutions to overcome these limitations by integrating storage and computation within a single device. These emerging technologies can retain resistance values without power, allowing them to serve as analog weights in ANNs, mimicking the behavior of biological synapses. While promising, these nonvolatile devices often exhibit inherent nonlinear relationships between resistance and applied voltage, complicating training processes and potentially impacting learning accuracy. This article proposes a magnetic synapse device based on the spin–orbit torque effect with geometrically controlled linear and nonlinear response characteristics. The device consists of a magnetic multilayer stack patterned into a designed shape, where the width variation along the current flow direction allows for controllable magnetic domain wall propagation. Through finite element method simulations and experimental studies, we demonstrate that by engineering the device geometry, a linear relationship between the applied current and the resulting Hall resistance can be achieved, mimicking the desired linear weight-input behavior in artificial neural networks. Additionally, this study explores the influence of current pulse width on the response curves, revealing a deviation from linearity at longer pulse durations. The geometric tunability of the magnetic synapse device offers a promising approach for realizing reliable and energy-efficient neuromorphic computing architectures.

A read-efficient and write-optimized hash table for Intel Optane DC Persistent Memory

Emerging non-volatile memory technologies are driving the next generation of storage systems and durable data structures. Among them, many hash table proposals employ NVM as the storage layer for both fast access and efficient persistence. Most of them are based on the assumption that NVM has cacheline access granularity, poor write endurance, DRAM-comparable read latency and relatively higher write latency. However, a commercial non-volatile memory product, namely Intel Optane DC Persistent Memory (Optane), has some interesting features that are different from previous assumptions, such as 256-byte OptaneLine access granularity, higher read latency than DRAM and DRAM-comparable write latency, limited read/write bandwidth, and hardware-layer wear-leveling. Confronted with the new challenges brought by Optane, we propose Rewo-Hash, a novel read-efficient and write-optimized persistent hash table. Our incremental contributions over our previous work are summarized as follows. First, provide a more detailed technical description for cached table-inclined read mechanism and log-free atomic write mechanism. Second, we devise a consistent shadowing synchronization scheme to mask the data synchronization overhead. Third, we propose a non-blocking lightweight resizing scheme and elaborate the crash recovery mechanism. Fourth, we conduct a comprehensive analysis of the implications of Intel ceasing the production of Optane, and provide a forward-looking perspective on the future of non-volatile memory. The experimental results show that compared with state-of-the-art NVM-Optimized hash tables, Rewo-Hash gains remarkable performance improvement.

Synthesis of tantalum oxide thin films using RF magnetron sputtering for RRAM application

Resistive Random Access Memory (RRAM) is a prominent contender in the realm of emerging non-volatile memory technologies owing to its numerous advantages like simple structure, low power usage, high speed, and exceptional scalability. In the current study, RRAM device was fabricated using tantalum oxide (TaOx) as a resistive switching insulating oxide layer, which was sandwiched between two conducting electrodes, namely Ag and ITO. RF magnetron sputtering was used to deposit the insulating layer of TaOx at room temperature on the ITO substrate. Further, X-ray reflectivity and hard X-ray photoelectron spectroscopy analyses were conducted to find the thickness, roughness, and elemental composition of the deposited TaOx films. Using a semiconductor analyzer, the RRAM cell's first DC switching characteristics were determined. The data acquired exhibited a resistance ratio (R HRS/R LRS) of 120 showing a good distinction between the two-resistance states. Additionally, a thorough investigation was conducted to examine the electrical conduction mechanism occurring inside the fabricated RRAM device.

Memristor In Non-Volatile Memory Technology and Computer Architecture

Memristor In Non-Volatile Memory Technology and Computer Architecture

Ultrafast high-endurance memory based on sliding ferroelectrics.

The persistence of voltage-switchable collective electronic phenomena down to the atomic scale has extensive implications for area- and energy-efficient electronics, especially in emerging nonvolatile memory technology. We investigate the performance of a ferroelectric field-effect transistor (FeFET) based on sliding ferroelectricity in bilayer boron nitride at room temperature. Sliding ferroelectricity represents a different form of atomically thin two-dimensional (2D) ferroelectrics, characterized by the switching of out-of-plane polarization through interlayer sliding motion. We examined the FeFET device employing monolayer graphene as the channel layer, which demonstrated ultrafast switching speeds on the nanosecond scale and high endurance exceeding 1011 switching cycles, comparable to state-of-the-art FeFET devices. These characteristics highlight the potential of 2D sliding ferroelectrics for inspiring next-generation nonvolatile memory technology.

Research on Improved Crystallization Properties and Underlying Mechanism of the Sb2Te3 Phase-Change Thin Film by Inserting Sn15Sb85 Layers.

As a non-volatile semiconductor memory technology, phase-change memory has a wide range of application prospects as a result of the excellent comprehensive performance. In this paper, multilayer thin films based on Sb2Te3 material were designed and prepared by inserting the Sn15Sb85 layer. The thermal and electrical properties of superlattice-like Sb2Te3/Sn15Sb85 phase-change films can be adjusted by controlling the thickness ratio of Sb2Te3/Sn15Sb85. In comparison to the monolayer Sb2Te3 film, the multilayer layer Sb2Te3/Sn15Sb85 materials have a higher crystallization temperature, larger crystallization activation energy, and longer data lifetime, indicating the great improvement of thermal stability. The changes in the phase structure and vibrational modes of multilayer Sb2Te3/Sn15Sb85 films were characterized by X-ray diffraction and Raman spectroscopy, respectively. The presence of Sn15Sb85 layers restrains grain growth and refines the grain size. The multilayer Sb2Te3/Sn15Sb85 films exhibit better surface flatness, smaller surface potential undulation, and lower thickness variations than single-layer Sb2Te3. Phase-change memory cells based on the [Sb2Te3 (1 nm)/Sn15Sb85 (9 nm)]5 thin film has a lower threshold voltage (1.9 V) and threshold current (3.1 μA) compared to the Ge2Sb2Te5 film. Meanwhile, the electrical heating model of a phase-change memory cell based on a [Sb2Te3 (1 nm)/Sn15Sb85 (9 nm)]5 multilayer structure was established by multiphysics coupling analysis, proving the great improvement in heat transfer performance and efficiency. The experimental and theoretical studies confirm that the insertion of the Sn15Sb85 layer can significantly improve the crystallization properties of Sb2Te3 films, paving the way for optimizing the phase-change materials by regulating the microstructural parameters.

A quantum sensing metrology for magnetic memories

Magnetic random access memory (MRAM) is a leading emergent memory technology that is poised to replace current non-volatile memory technologies such as eFlash. However, controlling and improving distributions of device properties becomes a key enabler of new applications at this stage of technology development. Here, we introduce a non-contact metrology technique deploying scanning NV magnetometry (SNVM) to investigate MRAM performance at the individual bit level. We demonstrate magnetic reversal characterization in individual, <60 nm-sized bits, to extract key magnetic properties, thermal stability, and switching statistics, and thereby gauge bit-to-bit uniformity. We showcase the performance of our method by benchmarking two distinct bit etching processes immediately after pattern formation. In contrast to ensemble averaging methods such as perpendicular magneto-optical Kerr effect, we show that it is possible to identify out of distribution (tail-bits) bits that seem associated to the edges of the array, enabling failure analysis of tail bits. Our findings highlight the potential of nanoscale quantum sensing of MRAM devices for early-stage screening in the processing line, paving the way for future incorporation of this nanoscale characterization tool in the semiconductor industry.

Ferro-Electric RAM

Ferroelectric RAM (FRAM) is a promising non-volatile memory technology that combines the advantages of both DRAM and Flash memory. FRAM offers fast read and write speeds, low power consumption, and high endurance, making it suitable for a wide range of applications. It stores data by utilizing the ferroelectric properties of certain materials, which can retain their polarization even when the power is off. This allows FRAM to offer high-speed operation with low power consumption, making it ideal for use in IoT devices, smart cards, and automotive systems