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- ItemToward Reliable Multi-Level Operation in RRAM Arrays: Improving Post-Algorithm Stability and Assessing Endurance/Data Retention(Piscataway : Institute of Electrical and Electronics Engineers Inc., 2019) Perez, E.; Zambelli, C.; Mahadevaiah, M.K.; Olivo, P.; Wenger, C.Achieving a reliable multi-level operation in resistive random access memory (RRAM) arrays is currently a challenging task due to several threats like the post-algorithm instability occurring after the levels placement, the limited endurance, and the poor data retention capabilities at high temperature. In this paper, we introduced a multi-level variation of the state-of-the-art incremental step pulse with verify algorithm (M-ISPVA) to improve the stability of the low resistive state levels. This algorithm introduces for the first time the proper combination of current compliance control and program/verify paradigms. The validation of the algorithm for forming and set operations has been performed on 4-kbit RRAM arrays. In addition, we assessed the endurance and the high temperature multi-level retention capabilities after the algorithm application proving a 1 k switching cycles stability and a ten years retention target with temperatures below 100 °C.
- ItemImpact of the precursor chemistry and process conditions on the cell-to-cell variability in 1T-1R based HfO2 RRAM devices(London : Nature Publishing Group, 2018) Grossi, A.; Perez, E.; Zambelli, C.; Olivo, P.; Miranda, E.; Roelofs, R.; Woodruff, J.; Raisanen, P.; Li, W.; Givens, M.; Costina, I.; Schubert, M.A.; Wenger, C.The Resistive RAM (RRAM) technology is currently in a level of maturity that calls for its integration into CMOS compatible memory arrays. This CMOS integration requires a perfect understanding of the cells performance and reliability in relation to the deposition processes used for their manufacturing. In this paper, the impact of the precursor chemistries and process conditions on the performance of HfO2 based memristive cells is studied. An extensive characterization of HfO2 based 1T1R cells, a comparison of the cell-to-cell variability, and reliability study is performed. The cells’ behaviors during forming, set, and reset operations are monitored in order to relate their features to conductive filament properties and process-induced variability of the switching parameters. The modeling of the high resistance state (HRS) is performed by applying the Quantum-Point Contact model to assess the link between the deposition condition and the precursor chemistry with the resulting physical cells characteristics.
- 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.
- 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.
- 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.
- 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.
- ItemA Flashback on Control Logic Injection Attacks against Programmable Logic Controllers(Basel : MDPI, 2022) Alsabbagh, Wael; Langendörfer, PeterProgrammable logic controllers (PLCs) make up a substantial part of critical infrastructures (CIs) and industrial control systems (ICSs). They are programmed with a control logic that defines how to drive and operate critical processes such as nuclear power plants, petrochemical factories, water treatment systems, and other facilities. Unfortunately, these devices are not fully secure and are prone to malicious threats, especially those exploiting vulnerabilities in the control logic of PLCs. Such threats are known as control logic injection attacks. They mainly aim at sabotaging physical processes controlled by exposed PLCs, causing catastrophic damage to target systems as shown by Stuxnet. Looking back over the last decade, many research endeavors exploring and discussing these threats have been published. In this article, we present a flashback on the recent works related to control logic injection attacks against PLCs. To this end, we provide the security research community with a new systematization based on the attacker techniques under three main attack scenarios. For each study presented in this work, we overview the attack strategies, tools, security goals, infected devices, and underlying vulnerabilities. Based on our analysis, we highlight the current security challenges in protecting PLCs from such severe attacks and suggest security recommendations for future research directions.
- 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.
- ItemResilience in the Cyberworld: Definitions, Features and Models(Basel : MDPI, 2021) Vogel, Elisabeth; Dyka, Zoya; Klann, Dan; Langendörfer, PeterResilience is a feature that is gaining more and more attention in computer science and computer engineering. However, the definition of resilience for the cyber landscape, especially embedded systems, is not yet clear. This paper discusses definitions provided by different authors, on different years and with different application areas the field of computer science/computer engineering. We identify the core statements that are more or less common to the majority of the definitions, and based on this we give a holistic definition using attributes for (cyber-) resilience. In order to pave a way towards resilience engineering, we discuss a theoretical model of the life cycle of a (cyber-) resilient system that consists of key actions presented in the literature. We adapt this model for embedded (cyber-) resilient systems.
- 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.