12 results
Search Results
Now showing 1 - 10 of 12
- ItemEnhanced thermal stability of yttrium oxide-based RRAM devices with inhomogeneous Schottky-barrier(Melville, NY : American Inst. of Physics, 2020) Piros, Eszter; Petzold, Stefan; Zintler, Alexander; Kaiser, Nico; Vogel, Tobias; Eilhardt, Robert; Wenger, Christian; Molina-Luna, Leopoldo; Alff, LambertThis work addresses the thermal stability of bipolar resistive switching in yttrium oxide-based resistive random access memory revealed through the temperature dependence of the DC switching behavior. The operation voltages, current levels, and charge transport mechanisms are investigated at 25 °C, 85 °C, and 125 °C, and show overall good temperature immunity. The set and reset voltages, as well as the device resistance in both the high and low resistive states, are found to scale inversely with increasing temperatures. The Schottky-barrier height was observed to increase from approximately 1.02 eV at 25 °C to approximately 1.35 eV at 125 °C, an uncommon behavior explained by interface phenomena. © 2020 Author(s).
- ItemAC electrokinetic immobilization of organic dye molecules(Berlin [u.a.] : Springer, 2020) Laux, Eva-Maria; Wenger, Christian; Bier, Frank F.; Hölzel, RalphThe application of inhomogeneous AC electric fields for molecular immobilization is a very fast and simple method that does not require any adaptions to the molecule’s functional groups or charges. Here, the method is applied to a completely new category of molecules: small organic fluorescence dyes, whose dimensions amount to only 1 nm or even less. The presented setup and the electric field parameters used allow immobilization of dye molecules on the whole electrode surface as opposed to pure dielectrophoretic applications, where molecules are attracted only to regions of high electric field gradients, i.e., to the electrode tips and edges. In addition to dielectrophoresis and AC electrokinetic flow, molecular scale interactions and electrophoresis at short time scales are discussed as further mechanisms leading to migration and immobilization of the molecules. [Figure not available: see fulltext.] © 2020, The Author(s).
- ItemDielectrophoretic Immobilization of Yeast Cells Using CMOS Integrated Microfluidics(Basel : MDPI AG, 2020) Ettehad, Honeyeh Matbaechi; Soltani Zarrin, Pouya; Hölzel, Ralph; Wenger, ChristianThis paper presents a dielectrophoretic system for the immobilization and separation of live and dead cells. Dielectrophoresis (DEP) is a promising and efficient investigation technique for the development of novel lab-on-a-chip devices, which characterizes cells or particles based on their intrinsic and physical properties. Using this method, specific cells can be isolated from their medium carrier or the mixture of cell suspensions (e.g., separation of viable cells from non-viable cells). Main advantages of this method, which makes it favorable for disease (blood) analysis and diagnostic applications are, the preservation of the cell properties during measurements, label-free cell identification, and low set up cost. In this study, we validated the capability of complementary metal-oxide-semiconductor (CMOS) integrated microfluidic devices for the manipulation and characterization of live and dead yeast cells using dielectrophoretic forces. This approach successfully trapped live yeast cells and purified them from dead cells. Numerical simulations based on a two-layer model for yeast cells flowing in the channel were used to predict the trajectories of the cells with respect to their dielectric properties, varying excitation voltage, and frequency.
- ItemTowards the Growth of Hexagonal Boron Nitride on Ge(001)/Si Substrates by Chemical Vapor Deposition(Basel : MDPI, 2022) Franck, Max; Dabrowski, Jaroslaw; Schubert, Markus Andreas; Wenger, Christian; Lukosius, MindaugasThe growth of hexagonal boron nitride (hBN) on epitaxial Ge(001)/Si substrates via high-vacuum chemical vapor deposition from borazine is investigated for the first time in a systematic manner. The influences of the process pressure and growth temperature in the range of 10−7–10−3 mbar and 900–980 °C, respectively, are evaluated with respect to morphology, growth rate, and crystalline quality of the hBN films. At 900 °C, nanocrystalline hBN films with a lateral crystallite size of ~2–3 nm are obtained and confirmed by high-resolution transmission electron microscopy images. X-ray photoelectron spectroscopy confirms an atomic N:B ratio of 1 ± 0.1. A three-dimensional growth mode is observed by atomic force microscopy. Increasing the process pressure in the reactor mainly affects the growth rate, with only slight effects on crystalline quality and none on the principle growth mode. Growth of hBN at 980 °C increases the average crystallite size and leads to the formation of 3–10 well-oriented, vertically stacked layers of hBN on the Ge surface. Exploratory ab initio density functional theory simulations indicate that hBN edges are saturated by hydrogen, and it is proposed that partial de-saturation by H radicals produced on hot parts of the set-up is responsible for the growth.
- ItemOptimization of Multi-Level Operation in RRAM Arrays for In-Memory Computing(Basel : MDPI, 2021) Pérez, Eduardo; Pérez-Ávila, Antonio Javier; Romero-Zaliz, Rocío; Mahadevaiah, Mamathamba Kalishettyhalli; Pérez-Bosch Quesada, Emilio; Roldán, Juan Bautista; Jiménez-Molinos, Francisco; Wenger, ChristianAccomplishing multi-level programming in resistive random access memory (RRAM) arrays with truly discrete and linearly spaced conductive levels is crucial in order to implement synaptic weights in hardware-based neuromorphic systems. In this paper, we implemented this feature on 4-kbit 1T1R RRAM arrays by tuning the programming parameters of the multi-level incremental step pulse with verify algorithm (M-ISPVA). The optimized set of parameters was assessed by comparing its results with a non-optimized one. The optimized set of parameters proved to be an effective way to define non-overlapped conductive levels due to the strong reduction of the device-to-device variability as well as of the cycle-to-cycle variability, assessed by inter-levels switching tests and during 1 k reset-set cycles. In order to evaluate this improvement in real scenarios, the experimental characteristics of the RRAM devices were captured by means of a behavioral model, which was used to simulate two different neuromorphic systems: an 8 × 8 vector-matrix-multiplication (VMM) accelerator and a 4-layer feedforward neural network for MNIST database recognition. The results clearly showed that the optimization of the programming parameters improved both the precision of VMM results as well as the recognition accuracy of the neural network in about 6% compared with the use of non-optimized parameters.
- ItemProgramming Pulse Width Assessment for Reliable and Low-Energy Endurance Performance in Al:HfO2-Based RRAM Arrays(Basel : MDPI AG, 2020) Pérez, Eduardo; Ossorio, Óscar González; Dueñas, Salvador; Castán, Helena; García, Héctor; Wenger, ChristianA crucial step in order to achieve fast and low-energy switching operations in resistive random access memory (RRAM) memories is the reduction of the programming pulse width. In this study, the incremental step pulse with verify algorithm (ISPVA) was implemented by using different pulse widths between 10 μ s and 50 ns and assessed on Al-doped HfO 2 4 kbit RRAM memory arrays. The switching stability was assessed by means of an endurance test of 1k cycles. Both conductive levels and voltages needed for switching showed a remarkable good behavior along 1k reset/set cycles regardless the programming pulse width implemented. Nevertheless, the distributions of voltages as well as the amount of energy required to carry out the switching operations were definitely affected by the value of the pulse width. In addition, the data retention was evaluated after the endurance analysis by annealing the RRAM devices at 150 °C along 100 h. Just an almost negligible increase on the rate of degradation of about 1 μ A at the end of the 100 h of annealing was reported between those samples programmed by employing a pulse width of 10 μ s and those employing 50 ns. Finally, an endurance performance of 200k cycles without any degradation was achieved on 128 RRAM devices by using programming pulses of 100 ns width.
- ItemModulating the Filamentary-Based Resistive Switching Properties of HfO2 Memristive Devices by Adding Al2O3 Layers(Basel : MDPI, 2022) Kalishettyhalli Mahadevaiah, Mamathamba; Perez, Eduardo; Lisker, Marco; Schubert, Markus Andreas; Perez-Bosch Quesada, Emilio; Wenger, Christian; Mai, AndreasThe resistive switching properties of HfO2 based 1T-1R memristive devices are electrically modified by adding ultra-thin layers of Al2 O3 into the memristive device. Three different types of memristive stacks are fabricated in the 130 nm CMOS technology of IHP. The switching properties of the memristive devices are discussed with respect to forming voltages, low resistance state and high resistance state characteristics and their variabilities. The experimental I–V characteristics of set and reset operations are evaluated by using the quantum point contact model. The properties of the conduction filament in the on and off states of the memristive devices are discussed with respect to the model parameters obtained from the QPC fit.
- ItemIn-Vitro Classification of Saliva Samples of COPD Patients and Healthy Controls Using Machine Learning Tools(New York, NY : IEEE, 2020) Zarrin, Pouya Soltani; Roeckendorf, Niels; Wenger, ChristianChronic Obstructive Pulmonary Disease (COPD) is a life-threatening lung disease and a major cause of morbidity and mortality worldwide. Although a curative therapy has yet to be found, permanent monitoring of biomarkers that refiect the disease progression plays a pivotal role for the effective management of COPD. The accurate examination of respiratory tract fiuids like saliva is a promising approach for staging disease and predicting its upcoming exacerbations in a Point-of-Care (PoC) environment. However, the concurrent consideration of patients' demographic and medical parameters is necessary for achieving accurate outcomes. Therefore, Machine Learning (ML) tools can play an important role for analyzing patient data and providing comprehensive results for the recognition of COPD in a PoC setting. As a result, the objective of this research work was to implement ML tools on data acquired from characterizing saliva samples of COPD patients and healthy controls as well as their demographic information for PoC recognition of the disease. For this purpose, a permittivity biosensor was used to characterize dielectric properties of saliva samples and, subsequently, ML tools were applied on the acquired data for classification. The XGBoost gradient boosting algorithm provided a high classification accuracy and sensitivity of 91.25% and 100%, respectively, making it a promising model for COPD evaluation. Integration of this model on a neuromorphic chip, in the future, will enable the real-time assessment of COPD in PoC, with low cost, low energy consumption, and high patient privacy. In addition, constant monitoring of COPD in a near-patient setup will enable the better management of the disease exacerbations.
- ItemToward Reliable Compact Modeling of Multilevel 1T-1R RRAM Devices for Neuromorphic Systems(Basel : MDPI AG, 2021) Perez-Bosch Quesada, Emilio; Romero-Zaliz, Rocio; Perez, Eduardo; Kalishettyhalli Mahadevaiah, Mamathamba; Reuben, John; Schubert, Markus Andreas; Jimenez-Molinos, Francisco; Roldan, Juan Bautista; Wenger, ChristianIn this work, three different RRAM compact models implemented in Verilog-A are analyzed and evaluated in order to reproduce the multilevel approach based on the switching capability of experimental devices. These models are integrated in 1T-1R cells to control their analog behavior by means of the compliance current imposed by the NMOS select transistor. Four different resistance levels are simulated and assessed with experimental verification to account for their multilevel capability. Further, an Artificial Neural Network study is carried out to evaluate in a real scenario the viability of the multilevel approach under study.
- ItemRole of Oxygen Defects in Conductive-Filament Formation in Y2O3-Based Analog RRAM Devices as Revealed by Fluctuation Spectroscopy(College Park, Md. [u.a.] : American Physical Society, 2020) Piros, Eszter; Lonsky, Martin; Petzold, Stefan; Zintler, Alexander; Sharath, S.U.; Vogel, Tobias; Kaiser, Nico; Eilhardt, Robert; Molina-Luna, Leopoldo; Wenger, Christian; Müller, Jens; Alff, LambertLow-frequency noise in Y2O3-based resistive random-access memory devices with analog switching is studied at intermediate resistive states and as a function of dc cycling. A universal 1/fα-type behavior is found, with a frequency exponent of α≈1.2 that is independent of the applied reset voltage or the device resistance and is attributed to the intrinsic abundance of oxygen vacancies unique to the structure of yttria. Remarkably, the noise magnitude in the high resistive state systematically decreases through dc training. This effect is attributed to the stabilization of the conductive filament via the consumption of oxygen vacancies, thus reducing the number of active fluctuators in the vicinity of the filament.