The intrinsic stochasticity of the memristor can be used to generate true random numbers, essential for non-decryptable hardware-based security devices. Here, we propose a novel and advanced method to generate true random numbers utilizing the stochastic oscillation behavior of a NbOx mott memristor, exhibiting self-clocking, fast and variation tolerant characteristics. The random number generation rate of the device can be at least 40 kb s−1, which is the fastest record compared with previous volatile memristor-based TRNG devices. Also, its dimensionless operating principle provides high tolerance against both ambient temperature variation and device-to-device variation, enabling robust security hardware applicable in harsh environments.
Memristive stateful logic enables energy‐ and cost‐efficient in‐memory computing, which is desirable for edge computing in the coming Internet of Things (IoT) era. Researchers have recently developed various stateful logic gates and have shown viable computing applications based on ideal memristive characteristics. However, few studies have demonstrated a system‐level in‐memory computing operation that can address the practical issues affecting device realization. Herein, a practically viable stateful logic device based on a 1‐transistor−1‐memristor (1T1M) array structure is proposed, considering the inherently stochastic memristor characteristics. Details on how to select the viable stateful logic gates in a given memristor are shown, and as an example of logic cascading, they are implemented in a device to operate a multibit carry look‐ahead adder. Then, an in‐memory computing layout that can perform all of the computing functions—data storing, transferring, and executing—inside the memory, addressing data traffic issues, is suggested. Finally, a software/hardware mixed stateful logic emulator that can virtually mimic array‐level in‐memory computing hardware based on cell‐level memristive characteristics is demonstrated.
Self-limited switching is a technique that can control the memristor resistance up to a specific value by limiting excessive switching. [14,15] For example, in self-limited "set" switching, a series resistor (R S ) is connected to a memristor (M). The R S -M configuration is biased with a programming voltage (V P ) to switch the M from the HRS to the LRS. Before the switching happens, if the node voltage on M is V M , the V M is almost equal to the V P because the R HRS is much larger than the resistance of R S (V M ≈ V P ). As soon as the resistance state of M changes to the lower value (i.e., the set switching happens), the LRS is not uniform because of the stochastic characteristic of the memristor switching. Afterward, the V P is redistributed by the voltage divider effect, and the redistributed V M (V M ′) is lower than the V P . Then, the V M ′ leads to additional minor set switching of the M.Here, the amount of additional set switching depends on the V M ′; if the R LRS is relatively small, the V M ′ is also small, so there is less additional set switching. However, if the R LRS is relatively high, the V M ′ is also high and this leads to additional set switching. Therefore, if enough time is allowed, the set switching can spontaneously saturate to a certain value.Self-limited "reset" switching is complicated, but it is also possible to realize by adopting both series and parallel resistor components. [14,16] If such self-limited switching is applied to control the intermediate states, more uniform intermediate states can be achieved. Furthermore, if the resistance of the intermediate states is the same as the series resistor value, one can directly copy any resistance values from the R to the M under the self-limited switching regime. This suggests that the analog data programming will be more efficient and faster.In this study, we propose a novel analog data programming method that transfers reference analog resistance values to a target memristor directly via a stateful in-memory logic operation. We demonstrate the methodology by adopting an ideal memristor model design. The desired memristive behavior, characterized by a gradual set switching without a sudden current jump, was achieved using a Ti-doped NbO x charge trap memristor, but with some discrepancy in switching behavior compared to the theoretic ideal. [17] Afterward, we introduced parallel resistors in the programming circuit to reduce the discrepancy and bring the memristor behavior closer to that of the ideal model. Finally, a computational simulation was employed Analog memristors enable compact neuromorphic computing with low power consumption. One of the issues with the technology is slow precise analog data programming. In this study, a novel analog data programming method utilizing a self-limited set switching is proposed. The method can transfer any resistance values from reference resistors to the target memristor accurately inside a crossbar array by performing an appropriate voltage clocking. An ideal memristor model based on the me...
Valence change-type resistance switching behaviors in oxides can be understood by well-established physical models describing the field-driven oxygen vacancy distribution change. In those models, electroformed residual oxygen vacancy filaments are crucial as they work as an electric field concentrator and limit the oxygen vacancy movement along the vertical direction. Therefore, their movement outward by diffusion is negligible. However, this situation may not be applicable in the electroforming-free system, where the field-driven movement is less prominent, and the isotropic oxygen vacancy diffusion by concentration gradient is more significant, which has not been given much consideration in the conventional model. Here, we propose a modified physical model that considers the change in the oxygen vacancies’ charged state depending on their concentrations and the resulting change in diffusivity during switching to interpret the electroforming-free device behaviors. The model suggests formation of an hourglass-shaped filament constituting a lower concentration of oxygen vacancies due to the fluid oxygen diffusion in the thin oxide. Consequently, the proposed model can explain the electroforming-free device behaviors, including the retention failure mechanism, and suggest an optimized filament configuration for improved retention characteristics. The proposed model can plausibly explain both the electroformed and the electroforming-free devices. Therefore, it can be a standard model for valence change memristors.
In this study, inductively coupled plasma-mass spectrometry (ICP-MS) was used to determine the concentration of 15 elements (Mg, Al, K, Ca, Cr, Mn, Co, Ni, Cu, Zn, Rb, Sr, Cd, Ba, and Pb) of sesame seeds. Multivariate analysis was then performed to discriminate the origin of sesame seeds. Korean (48), Chinese (44), and Indian (21) samples were used to develop the calibration model. Another 10 samples were used to validate this model. All elements were significantly different (<0.05) among the samples from three countries, and all elements were subjected to both principal component analysis (PCA) and discriminant analysis. The concentrations of multi-element showed a trend of clustering according to the origin of samples based on PCA. They showed a discrimination rate of 92.0% in the discriminant analysis. The results demonstrated that a combination of ICP-MS multi-element determination and multivariate analysis could be used to discriminate the sesame seed origin.
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