The over-reset phenomenon in Ta2O5 RRAM device investigated by the RTN-based defect probing technique

IEEE Despite the tremendous efforts in the past decade devoted to the development of filamentary resistive-switching devices (RRAM), there is still a lack of in-depth understanding of its over-reset phenomenon. At higher reset stop voltages that exceed a certain threshold, the resistance at high resistance state reduces, leading to an irrecoverable window reduction. The over-reset phenomenon limits the maximum resistance window that can be achieved by using a higher Vreset, which also degrades its potential in applications such as multi-level memory and neuromorphic synapses. In this work, the over-reset is investigated by cyclic reset operations with incremental stop voltages, and is explained by defect generation in the filament constriction region of Ta2O5 RRAM devices. This is supported by the statistical spatial defects profile obtained from the random telegraph noise based defect probing technique. The impact of forming compliance current on the over-reset is also evaluated

Stochastic computing based on volatile GeSe ovonic threshold switching selectors

Stochastic computing (SC) is a special type of digital compute strategy where values are represented by the probability of 1 and 0 in stochastic bit streams, which leads to superior hardware simplicity and error-tolerance. In this paper, we propose and demonstrate SC with GeSe based Ovonic Threshold Switching (OTS) selector devices by exploiting their probabilistic switching behavior. The stochastic bit streams generated by OTS are demonstrated with good computation accuracy in both multiplication operation and image processing circuit. Moreover, the bit distribution has been statistically studied and linked to the collective defect de/localization behavior in the chalcogenide material. Weibull distribution of the delay time supports the origin of such probabilistic switching, facilitates further optimization of the operation condition, and lays the foundation for device modelling and circuit design. Considering its other advantages such as simple structure, fast speed, and volatile nature, OTS is a promising material for implementing SC in a wide range of novel applications, such as image processors, neural networks, control systems and reliability analysis

GeSe-based Ovonic Threshold Switching Volatile True Random Number Generator

In this paper, we propose and demonstrate a novel technique for true random number generator (TRNG) application using GeSe-based Ovonic threshold switching (OTS) selector devices. The inherent variability in OTS threshold voltage results in a bimodal distribution of on/off states which can be easily converted into digital bits. The experimental evaluation shows that the proposed TRNG enables the generation of high-quality random bits that passed 12 tests in the National Institute of Standards and Technology statistical test suite without complex external circuits for post-processing. The randomness is further evidenced by the prediction rate of ∼50% using machine learning algorithm. Compared with the TRNGs based on non-volatile memories, the volatile nature of OTS avoids the reset operation, thus further simplifying the operation and improving the generation frequency

Conformational effects on the Circular Dichroism of Human Carbonic Anhydrase II: a multilevel computational study

Circular Dichroism (CD) spectroscopy is a powerful method for investigating conformational changes in proteins and therefore has numerous applications in structural and molecular biology. Here a computational investigation of the CD spectrum of the Human Carbonic Anhydrase II (HCAII), with main focus on the near-UV CD spectra of the wild-type enzyme and it seven tryptophan mutant forms, is presented and compared to experimental studies. Multilevel computational methods (Molecular Dynamics, Semiempirical Quantum Mechanics, Time-Dependent Density Functional Theory) were applied in order to gain insight into the mechanisms of interaction between the aromatic chromophores within the protein environment and understand how the conformational flexibility of the protein influences these mechanisms. The analysis suggests that combining CD semi empirical calculations, crystal structures and molecular dynamics (MD) could help in achieving a better agreement between the computed and experimental protein spectra and provide some unique insight into the dynamic nature of the mechanisms of chromophore interactions

Impact of RTN on Pattern Recognition Accuracy of RRAM-based Synaptic Neural Network

Resistive switching memory devices can be categorized into either filamentary or non-filamentary ones depending on the switching mechanisms. Both types have been investigated as novel synaptic devices in hardware neural networks, but there is a lack of comparative study between them, especially in random telegraph noise (RTN) which could induce large resistance fluctuations. In this work, we analyze the amplitude and occurrence rate of RTN in both Ta2O5 filamentary and TiO2/a-Si (a-VMCO) non-filamentary RRAM devices and evaluate its impact on the pattern recognition accuracy of neural networks. It is revealed that the non-filamentary RRAM has a tighter RTN amplitude distribution and much lower RTN occurrence rate than its filamentary counterpart which leads to negligible RTN impact on recognition accuracy, making it a promising candidate in synaptic application

On‐Demand Reconfiguration of Nanomaterials: When Electronics Meets Ionics

Rapid advances in the semiconductor industry, driven largely by device scaling, are now approaching fundamental physical limits and face severe power, performance, and cost constraints. Multifunctional materials and devices may lead to a paradigm shift toward new, intelligent, and efficient computing systems, and are being extensively studied. Herein examines how, by controlling the internal ion distribution in a solid‐state film, a material’s chemical composition and physical properties can be reversibly reconfigured using an applied electric field, at room temperature and after device fabrication. Reconfigurability is observed in a wide range of materials, including commonly used dielectric films, and has led to the development of new device concepts such as resistive random‐access memory. Physical reconfigurability further allows memory and logic operations to be merged in the same device for efficient in‐memory computing and neuromorphic computing systems. By directly changing the chemical composition of the material, coupled electrical, optical, and magnetic effects can also be obtained. A survey of recent fundamental material and device studies that reveal the dynamic ionic processes is included, along with discussions on systematic modeling efforts, device and material challenges, and future research directions.By controlling the internal ion distribution in a solid‐state film, the material’s chemical composition and physical (i.e., electrical, optical, and magnetic) properties can be reversibly reconfigured, in situ, using an applied electric field. The reconfigurability is achieved in a wide range of materials, and can lead to the development of new memory, logic, and multifunctional devices and systems.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141225/1/adma201702770.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141225/2/adma201702770_am.pd

Macrocyclic β-Sheet Peptides That Inhibit the Aggregation of a Tau-Protein-Derived Hexapeptide

This paper describes studies of a series of macrocyclic β-sheet peptides 1 that inhibit the aggregation of a tau-protein-derived peptide. The macrocyclic β-sheet peptides comprise a pentapeptide "upper" strand, two δ-linked ornithine turn units, and a "lower" strand comprising two additional residues and the β-sheet peptidomimetic template "Hao". The tau-derived peptide Ac-VQIVYK-NH(2) (AcPHF6) aggregates in solution through β-sheet interactions to form straight and twisted filaments similar to those formed by tau protein in Alzheimer's neurofibrillary tangles. Macrocycles 1 containing the pentapeptide VQIVY in the "upper" strand delay and suppress the onset of aggregation of the AcPHF6 peptide. Inhibition is particularly pronounced in macrocycles 1a, 1d, and 1f, in which the two residues in the "lower" strand provide a pattern of hydrophobicity and hydrophilicity that matches that of the pentapeptide "upper" strand. Inhibition varies strongly with the concentration of these macrocycles, suggesting that it is cooperative. Macrocycle 1b containing the pentapeptide QIVYK shows little inhibition, suggesting the possibility of a preferred direction of growth of AcPHF6 β-sheets. On the basis of these studies, a model is proposed in which the AcPHF6 amyloid grows as a layered pair of β-sheets and in which growth is blocked by a pair of macrocycles that cap the growing paired hydrogen-bonding edges. This model provides a provocative and appealing target for future inhibitor design