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In this work we report on the role of ion transport for the dynamic behavior of a double barrier quantum mechanical Al/Al 2 O 3 /Nb x O y /Au memristive device based on numerical simulations in conjunction with experimental measurements. The device consists of an ultra-thin Nb x O y solid state electrolyte between an Al 2 O 3 tunnel barrier and a semiconductor metal interface at an Au electrode. It is shown that the device provides a number of interesting features such as an intrinsic current compliance, a relatively long retention time, and no need for an initialization step. Therefore, it is particularly attractive for applications in highly dense random access memories or neuromorphic mixed signal circuits. However, the underlying physical mechanisms of the resistive switching are still not completely understood yet. To investigate the interplay between the current transport mechanisms and the inner atomistic device structure a lumped element circuit model is consistently coupled with 3D kinetic Monte Carlo model for the ion transport. The simulation results indicate that the drift of charged point defects within the Nb x O y is the key factor for the resistive switching behavior. It is shown in detail that the diffusion of oxygen modifies the local electronic interface states resulting in a change of the interface properties.

Resistive switching devices emerged a huge amount of interest as promising candidates for non-volatile memories as well as artificial synapses due to their memristive behavior. The main physical and chemical phenomena which define their functionality are driven by externally applied voltages, and the resulting electric fields. Although molecular dynamics simulations are widely used in order to describe the dynamics on the corresponding atomic length and time scales, there is a lack of models which allow for the actual driving force of the dynamics, i.e. externally applied electric fields. This is due to the restriction of currently applied models to either solely conductive, non-reactive or insulating materials, with thicknesses in the order of the potential cutoff radius, i.e., 10 Å. In this work, we propose a generic model, which can be applied in particular to describe the resistive switching phenomena of metal-insulator-metal systems. It has been shown that the calculated electric field and force distribution in case of the chosen example system Cu/a-SiO\\(_2\\)/Cu are in agreement with fundamental field theoretical expectations.

We report on resistive switching of memristive electrochemical metallization devices using 3D kinetic Monte Carlo simulations describing the transport of ions through a solid state electrolyte of an Ag/TiO\\(_{\\text{x}}\\)/Pt thin layer system. The ion transport model is consistently coupled with solvers for the electric field and thermal diffusion. We show that the model is able to describe not only the formation of conducting filaments but also its dissolution. Furthermore, we calculate realistic current-voltage characteristics and resistive switching kinetics. Finally, we discuss in detail the influence of both the electric field and the local heat on the switching processes of the device.

The massive parallel approach of neuromorphic circuits leads to effective methods for solving complex problems. It has turned out that resistive switching devices with a continuous resistance range are potential candidates for such applications. These devices are memristive systems - nonlinear resistors with memory. They are fabricated in nanotechnology and hence parameter spread during fabrication may aggravate reproducible analyses. This issue makes simulation models of memristive devices worthwhile. Kinetic Monte-Carlo simulations based on a distributed model of the device can be used to understand the underlying physical and chemical phenomena. However, such simulations are very time-consuming and neither convenient for investigations of whole circuits nor for real-time applications, e.g. emulation purposes. Instead, a concentrated model of the device can be used for both fast simulations and real-time applications, respectively. We introduce an enhanced electrical model of a valence change mechanism (VCM) based double barrier memristive device (DBMD) with a continuous resistance range. This device consists of an ultra-thin memristive layer sandwiched between a tunnel barrier and a Schottky-contact. The introduced model leads to very fast simulations by using usual circuit simulation tools while maintaining physically meaningful parameters. Kinetic Monte-Carlo simulations based on a distributed model and experimental data have been utilized as references to verify the concentrated model.

In this work we report on kinetic Monte-Carlo calculations of resistive switching and the underlying growth dynamics of filaments in an electrochemical metallization device consisting of an Ag/TiO2/Pt sandwich-like thin film system. The developed model is not limited to i) fast time scale dynamics and ii) only one growth and dissolution cycle of metallic filaments. In particular, we present results from the simulation of consecutive cycles. We find that the numerical results are in excellent agreement with experimentally obtained data. Additionally, we observe an unexpected filament growth mode which is in contradiction to the widely acknowledged picture of filament growth, but consistent with recent experimental findings.

In this work we report on the role of ion transport for the dynamic behavior of a double barrier quantum mechanical Al/Al\\(_2\\)O\\(_3\\)/Nb\\(_{\\text{x}}\\)O\\(_{\\text{y}}\\)/Au memristive device based on numerical simulations in conjunction with experimental measurements. The device consists of an ultra-thin Nb\\(_{\\text{x}}\\)O\\(_{\\text{y}}\\) solid state electrolyte between an Al\\(_2\\)O\\(_3\\) tunnel barrier and a semiconductor metal interface at an Au electrode. It is shown that the device provides a number of interesting features for potential applications such as an intrinsic current compliance, a relatively long retention time, and no need for an initialization step. Therefore, it is particularly attractive for applications in highly dense random access memories or neuromorphic mixed signal circuits. However, the underlying physical mechanisms of the resistive switching are still not completely understood yet. To investigate the interplay between the current transport mechanisms and the inner atomistic device structure a lumped element circuit model is consistently coupled with 3D kinetic Monte Carlo model for the ion transport. The simulation results indicate that the drift of charged point defects within the Nb\\(_{\\text{x}}\\)O\\(_{\\text{y}}\\) is the key factor for the resistive switching behavior. It is shown in detail that the diffusion of oxygen modifies the local electronic interface states resulting in a change of the interface properties of the double barrier device.

Memristors based on a double barrier design have been analysed by various nano spectroscopic methods to unveil details about its microstructure and conduction mechanism. The device consists of an AlOx tunnel barrier and a NbOy/Au Schottky barrier sandwiched between Nb bottom electrode and Au top electrode. As it was anticipated that the local chemical composition of the tunnel barrier, i.e. oxidation state of the metals as well as concentration and distribution of oxygen ions, have a major influence on electronic conduction, these factors were carefully analysed. A combined approach was chosen in order to reliably investigate electronic states of Nb and O by electron energy-loss spectroscopy as well as map elements whose transition edges exhibit a different energy range by energy-dispersive X-ray spectroscopy like Au and Al. The results conclusively demonstrate significant oxidation of the bottom electrode as well as a small oxygen vacancy concentration in the Al oxide tunnel barrier. Possible scenarios to explain this unexpected additional oxide layer are discussed and kinetic Monte Carlo simulations were applied in order to identify its influence on conduction mechanisms in the device. In light of the strong deviations between observed and originally sought layout, this study highlights the robustness in terms of structural deviations of the double barrier memristor device.

PurposeFractures of the proximal femur in geriatric patients are life-changing and life-threatening events. Previous research has identified fluid volume as an independent factor contributing to trauma patients’ complications. Therefore, we aimed to investigate the impact of intraoperative fluid volume on outcomes in geriatric patients undergoing hip fracture surgery.MethodsWe conducted a retrospective single-center study with data from the hospital information systems. Our study included patients aged 70 years or older who had sustained a proximal femur fracture. We excluded patients with pathologic, periprosthetic, or peri-implant fractures and those with missing data. Based on the fluids given, we divided patients into high-volume and low-volume groups.ResultsPatients with a higher American Society of Anesthesiologists (ASA) grade and more comorbidities were more likely to receive more than 1500 ml of fluids. We observed significant differences in anesthesiologic management between the two groups, with a higher rate of invasive blood pressure management (IBP) and central venous catheter usage in the high-volume group. High-volume therapy was associated with a higher rate of complications (69.7% vs. 43.6%, p < 0.01), a higher transfusion rate (odds ratio 1.91 [1.26–2.91]), and an increased likelihood of patients being transferred to an intensive care unit (17.1% vs. 6.4%, p = 0.009). These findings were confirmed after adjusting for ASA grade, age, sex, type of fracture, Identification-of-Seniors-At-Risk (ISAR) score, and intraoperative blood loss.ConclusionsOur study suggests that intraoperative fluid volume is a significant factor that impacts the outcome of hip fracture surgery in geriatric patients. High-volume therapy was associated with increased complications.