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A physical unclonable function (PUF) is a hardware circuit that produces a random sequence based on its manufacturing-induced intrinsic characteristics. In the past decade, silicon-based PUFs have been extensively studied as a security primitive for identification and authentication. The emerging field of printed electronics (PE) enables novel application fields in the scope of the Internet of Things (IoT) and smart sensors. In this paper, we design and evaluate a printed differential circuit PUF (DiffC-PUF). The simulation data are verified by Monte Carlo analysis. Our design is highly scalable while consisting of a low number of printed transistors. Furthermore, we investigate the best operating point by varying the PUF challenge configuration and analyzing the PUF security metrics in order to achieve high robustness. At the best operating point, the results show areliability of 98.37% and a uniqueness of 50.02%, respectively. This analysis also provides useful and comprehensive insights into the design of hybrid or fully printed PUF circuits. In addition, the proposed printed DiffC-PUF core has been fabricated with electrolyte-gated field-effect transistor technology to verify our design in hardware.
Printed electronics can benefit from the deployment of electrolytesas gate insulators,which enables a high gate capacitance per unit area (1–10 μFcm−2) due to the formation of electrical double layers (EDLs). Consequently, electrolyte-gated field-effect transistors (EGFETs) attain high-charge carrier densities already in the subvoltage regime, allowing for low-voltage operation of circuits and systems. This article presents a systematic study of lumped terminal capacitances of printed electrolyte-gated transistors under various dc bias conditions. We perform voltage-dependent impedancemeasurements and separate extrinsic components from the lumped terminal capacitance.
The proposed Meyer-like capacitance model, which also accounts for the nonquasi-static (NQS) effect, agrees well with experimental data. Finally, to verify the model, we implement it in Verilog-A and simulate the transient response of an inverter and a ring oscillator circuit. Simulation results are in good agreement with the measurement data of fabricated devices.
Printed systems spark immense interest in industry, and for several parts such as solar cells or radio frequency identification antennas, printed products are already available on the market. This has led to intense research; however, printed field-effect transistors (FETs) and logics derived thereof still have not been sufficiently developed to be adapted by industry. Among others, one of the reasons for this is the lack of control of the threshold voltage during production. In this work, we show an approach to adjust the threshold voltage (Vth) in printed electrolyte-gated FETs (EGFETs) with high accuracy by doping indium-oxide semiconducting channels with chromium. Despite high doping concentrations achieved by a wet chemical process during precursor ink preparation, good on/off-ratios of more than five orders of magnitude could be demonstrated. The synthesis process is simple, inexpensive, and easily scalable and leads to depletion-mode EGFETs, which are fully functional at operation potentials below 2 V and allows us to increase Vth by approximately 0.5 V.
Development of Fully Printed Oxide Field-Effect Transistors using Graphene Passive Structures
(2019)
During the past decade to the present time, the topic of printed electronics has gained a lot of attention for their potential use in a number of practical applications, including biosensors, photovoltaic devices, RFIDs, flexible displays, large-area circuits, and so on. To fully realize printed electronic components and devices, effective techniques for the printing of passive structures and electrically and chemically compatible materials in the printed devices need to be developed first. The opportunity of using electrically conducting graphene inks will enable the integration of passive structures into active devices, as for example, printed electrolyte-gated transistors (EGTs). Accordingly, in this study, we present the parametric results obtained on fully printed electrolyte-gated transistors having graphene as the passive electrodes, an inorganic oxide semiconductor as the active channel, and a composite solid polymer electrolyte (CSPE) as the gate insulating material. This configuration offers high chemical and electrical stability while at the same time allowing EGT operation at low potentials, implying the distinct advantage of operation at low input voltages. The printed in-plane EGTs we developed exhibit excellent performance with device mobility up to 16 cm2 V–1 s–1, an ION/IOFF ratio of 105, and a subthreshold slope of 120 mV dec–1.
Printed electronics (PE) circuits have several advantages over silicon counterparts for the applications where mechanical flexibility, extremely low-cost, large area, and custom fabrication are required. The custom (personalized) fabrication is a key feature of this technology, enabling customization per application, even in small quantities due to low-cost printing compared with lithography. However, the personalized and on-demand fabrication, the non-standard circuit design, and the limited number of printing layers with larger geometries compared with traditional silicon chip manufacturing open doors for new and unique reverse engineering (RE) schemes for this technology. In this paper, we present a robust RE methodology based on supervised machine learning, starting from image acquisition all the way to netlist extraction. The results show that the proposed RE methodology can reverse engineer the PE circuits with very limited manual effort and is robust against non-standard circuit design, customized layouts, and high variations resulting from the inherent properties of PE manufacturing processes.
Printed electrolyte-gated oxide electronics is an emerging electronic technology in the low voltage regime (≤1 V). Whereas in the past mainly dielectrics have been used for gating the transistors, many recent approaches employ the advantages of solution processable, solid polymer electrolytes, or ion gels that provide high gate capacitances produced by a Helmholtz double layer, allowing for low-voltage operation. Herein, with special focus on work performed at KIT recent advances in building electronic circuits based on indium oxide, n-type electrolyte-gated field-effect transistors (EGFETs) are reviewed. When integrated into ring oscillator circuits a digital performance ranging from 250 Hz at 1 V up to 1 kHz is achieved. Sequential circuits such as memory cells are also demonstrated. More complex circuits are feasible but remain challenging also because of the high variability of the printed devices. However, the device inherent variability can be even exploited in security circuits such as physically unclonable functions (PUFs), which output a reliable and unique, device specific, digital response signal. As an overall advantage of the technology all the presented circuits can operate at very low supply voltages (0.6 V), which is crucial for low-power printed electronics applications.
Electrolyte-gated, printed field-effect transistors exhibit high charge carrier densities in the channel and thus high on-currents at low operating voltages, allowing for the low-power operation of such devices. This behavior is due to the high area-specific capacitance of the device, in which the electrolyte takes the role of the dielectric layer of classical architectures. In this paper, we investigate intrinsic double-layer capacitances of ink-jet printed electrolyte-gated inorganic field-effect transistors in both in-plane and top-gate architectures by means of voltage-dependent impedance spectroscopy. By comparison with deembedding structures, we separate the intrinsic properties of the double-layer capacitance at the transistor channel from parasitic effects and deduce accurate estimates for the double-layer capacitance based on an equivalent circuit fitting. Based on these results, we have performed simulations of the electrolyte cutoff frequency as a function of electrolyte and gate resistances, showing that the top-gate architecture has the potential to reach the kilohertz regime with proper optimization of materials and printing process. Our findings additionally enable accurate modeling of the frequency-dependent capacitance of electrolyte/ion gel-gated devices as required in the small-signal analysis in the circuit simulation.
In the domain of printed electronics (PE), field-effect transistors (FETs) with an oxide semiconductor channel are very promising. In particular, the use of high gate-capacitance of the composite solid polymer electrolytes (CSPEs) as a gate-insulator ensures extremely low voltage requirements. Besides high gate capacitance, such CSPEs are proven to be easily printable, stable in air over wide temperature ranges, and possess high ion conductivity. These CSPEs can be sensitive to moisture, especially for high surface-to-volume ratio printed thin films. In this paper, we provide a comprehensive experimental study on the effect of humidity on CSPE-gated single transistors. At the circuit level, the performance of ring oscillators (ROs) has been compared for various humidity conditions. The experimental results of the electrolyte-gated FETs (EGFETs) demonstrate rather comparable currents between 30%-90% humidity levels. However, the shifted transistor parameters lead to a significant performance change of the RO frequency behavior. The study in this paper shows the need of an impermeable encapsulation for the CSPE-gated FETs to ensure identical performance at all humidity conditions.
Finding clusters in high dimensional data is a challenging research problem. Subspace clustering algorithms aim to find clusters in all possible subspaces of the dataset, where a subspace is a subset of dimensions of the data. But the exponential increase in the number of subspaces with the dimensionality of data renders most of the algorithms inefficient as well as ineffective. Moreover, these algorithms have ingrained data dependency in the clustering process, which means that parallelization becomes difficult and inefficient. SUBSCALE is a recent subspace clustering algorithm which is scalable with the dimensions and contains independent processing steps which can be exploited through parallelism. In this paper, we aim to leverage the computational power of widely available multi-core processors to improve the runtime performance of the SUBSCALE algorithm. The experimental evaluation shows linear speedup. Moreover, we develop an approach using graphics processing units (GPUs) for fine-grained data parallelism to accelerate the computation further. First tests of the GPU implementation show very promising results.
In this paper pathophysiological interrelated deactivation/activation phenomena are set out in the example of whiplash injury. These phenomena could have been underestimated in previous positron emission tomography studies as their focus was on hypoperfusion rather than hyperperfusion. In addition, statistical parametric mapping analysis of cerebral studies is normally not fine-tuned to special interesting areas rather than to obvious clusters of difference.
In users of a cochlear implant (CI) together with a contralateral hearing aid (HA), so-called bimodal listeners, differences in processing latencies between digital HA and CI up to 9 ms constantly superimpose interaural time differences. In the present study, the effect of this device delay mismatch on sound localization accuracy was investigated. For this purpose, localization accuracy in the frontal horizontal plane was measured with the original and minimized device delay mismatch. The reduction was achieved by delaying the CI stimulation according to the delay of the individually worn HA. For this, a portable, programmable, battery-powered delay line based on a ring buffer running on a microcontroller was designed and assembled. After an acclimatization period to the delayed CI stimulation of 1 hr, the nine bimodal study participants showed a highly significant improvement in localization accuracy of 11.6% compared with the everyday situation without the delay line (p < .01). Concluding, delaying CI stimulation to minimize the device delay mismatch seems to be a promising method to increase sound localization accuracy in bimodal listeners.
Im Beitrag wird für lineare, zeitinvariante, zeitdiskrete und stabile Regelstrecken beschrieben, wie zwei bekannte Zustandsraumverfahren zur Windup-Vermeidung so miteinander kombiniert werden können, dass dadurch für sämtliche PI-Zustandsregler Strecken- und Regler-Windup verhindert wird, sofern diese Regler im unbegrenzten Fall stabil sind. Zurückgegriffen wird hierbei auf das „Additional Dynamic Element“ (ADE) von Hippe zur Vermeidung von Strecken-Windup [Hippe, P.: Windup in control – Its effects and their prevention, 2006; at – Automatisierungstechnik, 2007], dessen Übertragung auf zeitdiskrete Systeme im Beitrag kurz skizziert wird, sowie auf das Verfahren der Führungsgrößenkorrektur [Nuß, U.: at – Automatisierungstechnik, 2017] zur Vermeidung von Regler-Windup. Das vorgestellte Kombinationsverfahren setzt für die jeweilige Regelstrecke lediglich die Einbeziehung eines bereits existierenden P-Zustandsreglers voraus, der Strecken-Windup vermeidet. Die Bereitstellung eines möglichst einfachen und dennoch nicht allzu einschränkenden Kriteriums zur Überprüfung, ob ein P-Zustandsregler diese Eigenschaft besitzt, ist ebenfalls ein Anliegen des Beitrags. Diesbezüglich wird auf der Basis einer geeigneten Ljapunow-Funktion ein hinreichendes Kriterium angegeben, das umfassender ist als das in [Nuß, U.: at – Automatisierungstechnik, 2017] verwendete. Ein Beispiel aus der elektrischen Antriebstechnik demonstriert die Leistungsfähigkeit der vorgestellten Methode.
Spinal cord stimulation (SCS) is the most commonly used technique of neurostimulation. It involves the stimulation of the spinal cord and is therefore used to treat chronic pain. The existing esophageal catheters are used for temperature monitoring during an electrophysiology study with ablation and transesophageal echocardiography. The aim of the study was to model the spine and new esophageal electrodes for the transesophageal electrical pacing of the spinal cord, and to integrate them in the Offenburg heart rhythm model for the static and dynamic simulation of transesophageal neurostimulation. The modeling and simulation were both performed with the electromagnetic and thermal simulation software CST (Computer Simulation Technology, Darmstadt). Two new esophageal catheters were modelled as well as a thoracic spine based on the dimensions of a human skeleton. The simulation of directed transesophageal neurostimulation is performed using the esophageal balloon catheter with an electric pacing potential of 5 V and a trapezoidal signal. A potential of 4.33 V can be measured directly at the electrode, 3.71 V in the myocardium at a depth of 2 mm, 2.68 V in the thoracic vertebra at a depth of 10 mm, 2.1 V in the thoracic vertebra at a depth of 50 mm and 2.09 V in the spinal cord at a depth of 70 mm. The relation between the voltage delivered to the electrodes and the voltage applied to the spinal cord is linear. Virtual heart rhythm and catheter models as well as the simulation of electrical pacing fields and electrical sensing fields allow the static and dynamic simulation of directed transesophageal electrical pacing of the spinal cord. The 3D simulation of the electrical sensing and pacing fields may be used to optimize transesophageal neurostimulation.
The visualization of heart rhythm disturbance and atrial fibrillation therapy allows the optimization of new cardiac catheter ablations. With the simulation software CST (Computer Simulation Technology, Darmstadt) electromagnetic and thermal simulations can be carried out to analyze and optimize different heart rhythm disturbance and cardiac catheters for pulmonary vein isolation. Another form of visualization is provided by haptic, three-dimensional print models. These models can be produced using an additive manufacturing method, such as a 3d printer. The aim of the study was to produce a 3d print of the Offenburg heart rhythm model with a representation of an atrial fibrillation ablation procedure to improve the visualization of simulation of cardiac catheter ablation. The basis of 3d printing was the Offenburg heart rhythm model and the associated simulation of cryoablation of the pulmonary vein. The thermal simulation shows the pulmonary vein isolation of the left inferior pulmonary vein with the cryoballoon catheter Arctic Front Advance™ from Medtronic. After running through the simulation, the thermal propagation during the procedure was shown in the form of different colors. The three-dimensional print models were constructed on the base of the described simulation in a CAD program. Four different 3d printers are available for this purpose in a rapid prototyping laboratory at the University of Applied Science Offenburg. Two different printing processes were used and a final print model with additional representation of the esophagus and internal esophagus catheter was also prepared for printing. With the help of the thermal simulation results and the subsequent evaluation, it was possible to draw a conclusion about the propagation of the cold emanating from the catheter in the myocardium and the surrounding tissue. It was measured that just 3 mm from the balloon surface into the myocardium the temperature dropped to 25 °C. The simulation model was printed using two 3d printing methods. Both methods, as well as the different printing materials offer different advantages and disadvantages. All relevant parts, especially the balloon catheter and the conduction, are realistically represented. Only the thermal propagation in the form of different colors is not shown on this model. Three-dimensional heart rhythm models as well as virtual simulations allow very clear visualization of complex cardiac rhythm therapy and atrial fibrillation treatment methods. The printed models can be used for optimization and demonstration of cryoballoon catheter ablation in patients with atrial fibrillation.
In many application domains, in particular automotives, guaranteeing a very low failure rate is crucial to meet functional and safety standards. Especially, reliable operation of memory components such as SRAM cells is of essential importance. Due to aggressive technology downscaling, process and runtime variations significantly impact manufacturing yield as well as functionality. For this reason, a thorough memory failure rate assessment is imperative for correct circuit operation and yield improvement. In this regard, Monte Carlo simulations have been used as the conventional method to estimate the variability induced failure rate of memory components. However, Monte Carlo methods become infeasible when estimating rare events such as high-sigma failure rates. To this end, Importance Sampling methods have been proposed which reduce the number of required simulations substantially. However, existing methods still suffer from inaccuracies and high computational efforts, in particular for high-sigma problems. In this paper, we fill this gap by presenting an efficient mixture Importance Sampling approach based on Bayesian optimization, which deploys a surface model of the objective function to find the most probable failure points. Its advantages include constant complexity independent of the dimensions of design space, the potential to find the global extrema, and higher trustworthiness of the estimated failure rate by accurately exploring the design space. The approach is evaluated on a 6T-SRAM cell as well as a master-slave latch based on a 28nm FDSOI process. The results show an improvement in accuracy, resulting in up to 63× better accuracy in estimating failure rates compared to the best state-of-the-art solutions on a 28nm technology node.
Time-Sensitive Networking (TSN) is the most promising time-deterministic wired communication approach for industrial applications. To extend TSN to "IEEE 802.11" wireless networks two challenging problems must be solved: synchronization and scheduling. This paper is focused on the first one. Even though a few solutions already meet the required synchronization accuracies, they are built on expensive hardware that is not suited for mass market products. While next Wi-Fi generation might support the required functionalities, this paper proposes a novel method that makes possible high-precision wireless synchronization using commercial low-cost components. With the proposed solution, a standard deviation of synchronization error of less than 500 ns can be achieved for many use cases and system loads on both CPU and network. This performance is comparable to modern wired real-time field busses, which makes the developed method a significant contribution for the extension of the TSN protocol to the wireless domain.
Amorphous In-Ga-Zn-O (IGZO) is a high-mobility semiconductor employed in modern thin-film transistors for displays and it is considered as a promising material for Schottky diode-based rectifiers. Properties of the electronic components based on IGZO strongly depend on the manufacturing parameters such as the oxygen partial pressure during IGZO sputtering and post-deposition thermal annealing. In this study, we investigate the combined effect of sputtering conditions of amorphous IGZO (In:Ga:Zn=1:1:1) and post-deposition thermal annealing on the properties of vertical thin-film Pt-IGZO-Cu Schottky diodes, and evaluated the applicability of the fabricated Schottky diodes for low-frequency half-wave rectifier circuits. The change of the oxygen content in the gas mixture from 1.64% to 6.25%, and post-deposition annealing is shown to increase the current rectification ratio from 10 5 to 10 7 at ±1 V, Schottky barrier height from 0.64 eV to 0.75 eV, and the ideality factor from 1.11 to 1.39. Half-wave rectifier circuits based on the fabricated Schottky diodes were simulated using parameters extracted from measured current-voltage and capacitance-voltage characteristics. The half-wave rectifier circuits were realized at 100 kHz and 300 kHz on as-fabricated Schottky diodes with active area of 200 μm × 200 μm, which is relevant for the near-field communication (125 kHz - 134 kHz), and provided the output voltage amplitude of 0.87 V for 2 V supply voltage. The simulation results matched with the measurement data, verifying the model accuracy for circuit level simulation.
Analysis of Miniaturized Printed Flexible RFID/NFC Antennas Using Different Carrier Substrates
(2020)
Antennas for Radio Frequency Identification (RFID) provide benefits for high frequencies (HF) and wireless data transmission via Near Field Communication (NFC) and many other applications. In this case, various requirements for the design of the reader and transmitter antennas must be met in order to achieve a suitable transmission quality. In this work, a miniaturized cost-effective RFID/NFC antenna for a microelectronic measurement system is designed and printed on different flexible carrier substrates using a new and low-cost Direct Ink Writing (DIW) technology. Various practical aspects such as reflection and impedance magnitude as well as the behavior of the printed RFID/NFC antennas are analyzed and compared to an identical copper-based antenna of the same size. The results are presented in this paper. Furthermore, the problems during the printing process itself on the different substrates are evaluated. The effects of the characteristics on the antenna under kink-free bending tests are examined and subsequently long-term measurements are carried out.
A disturbed synchronization of the ventricular contraction can cause a highly developed systolic heart failure in affected patients with reduction of the left ventricular ejection fraction, which can often be explained by a diseased left bundle branch block (LBBB). If medication remains unresponsive, the concerned patients will be treated with a cardiac resynchronization therapy (CRT) system. The aim of this study was to integrate His-bundle pacing into the Offenburg heart rhythm model in order to visualize the electrical pacing field generated by His-Bundle-Pacing. Modelling and electrical field simulation activities were performed with the software CST (Computer Simulation Technology) from Dessault Systèms. CRT with biventricular pacing is to be achieved by an apical right ventricular electrode and an additional left ventricular electrode, which is floated into the coronary vein sinus. The non-responder rate of the CRT therapy is about one third of the CRT patients. His- Bundle-Pacing represents a physiological alternative to conventional cardiac pacing and cardiac resynchronization. An electrode implanted in the His-bundle emits a stronger electrical pacing field than the electrical pacing field of conventional cardiac pacemakers. The pacing of the Hisbundle was performed by the Medtronic Select Secure 3830 electrode with pacing voltage amplitudes of 3 V, 2 V and 1,5 V in combination with a pacing pulse duration of 1 ms. Compared to conventional pacemaker pacing, His-bundle pacing is capable of bridging LBBB conduction disorders in the left ventricle. The His-bundle pacing electrical field is able to spread via the physiological pathway in the right and left ventricles for CRT with a narrow QRS-complex in the surface ECG.
Diffracted waves carry high‐resolution information that can help interpreting fine structural details at a scale smaller than the seismic wavelength. However, the diffraction energy tends to be weak compared to the reflected energy and is also sensitive to inaccuracies in the migration velocity, making the identification of its signal challenging. In this work, we present an innovative workflow to automatically detect scattering points in the migration dip angle domain using deep learning. By taking advantage of the different kinematic properties of reflected and diffracted waves, we separate the two types of signals by migrating the seismic amplitudes to dip angle gathers using prestack depth imaging in the local angle domain. Convolutional neural networks are a class of deep learning algorithms able to learn to extract spatial information about the data in order to identify its characteristics. They have now become the method of choice to solve supervised pattern recognition problems. In this work, we use wave equation modelling to create a large and diversified dataset of synthetic examples to train a network into identifying the probable position of scattering objects in the subsurface. After giving an intuitive introduction to diffraction imaging and deep learning and discussing some of the pitfalls of the methods, we evaluate the trained network on field data and demonstrate the validity and good generalization performance of our algorithm. We successfully identify with a high‐accuracy and high‐resolution diffraction points, including those which have a low signal to noise and reflection ratio. We also show how our method allows us to quickly scan through high dimensional data consisting of several versions of a dataset migrated with a range of velocities to overcome the strong effect of incorrect migration velocity on the diffraction signal.