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Printed electronics, due to its manufacturability using printing technology, allows for fabrication on large areas and the usage of flexible substrates and thus enables novel applications. Non-impact printing technology, such as inkjet-printing, permits for flexible, decentralized manufacturing of electronic devices and systems. This further facilitates split-manufacturing in security-critical electrical components, as well as a maximum in design flexibility in terms of free form factors and non-standardized structures with different geometrical sizes, reaching from a few micrometers up to several millimeters.
Based on the technological benefits printed electronics offers, it provides an interesting counterpart to classical silicon-based electronics, which is usually densely integrated on miniaturized, rigid areas. By utilizing both technologies in a complementary manner, novel systems in the form of hybrid systems can be enabled. Whilst hybrid systems, incorporating passive printed components and electrically conductive wiring concepts, are already commercialized, complex printed systems, which also utilize active components remain rare. To enable more complex (hybrid) systems, various building blocks are required. This includes possibilities for lightweight, printed data storage, the capability to provide sustainable, self-powered printed components and especially circuits for secure, unique identification for holistic printed systems, deployed in the internet of things.
The presented thesis focuses on inkjet-printed electronic devices, circuits and hybrid systems. It investigates solutions for current scientific questions in the area of efficient data storage, sustainable electronics and hardware-based security in printed electronics.
For data storage, an inkjet-printed memristor is developed. The device is fully electrically evaluated with a focus on its data storage capabilities. Furthermore, the printed device is of special interest due to its easy manufacturability and integration capabilities. The experimental analysis reveals that the developed memristor is highly suitable as lightweight non-volatile memory device.
In order to enable sustainable electronic systems, an inkjet-printed full-wave rectifier based on near-zero threshold voltage electrolyte-gated transistors is developed and fully electrically characterized. The circuit is capable for small alternating voltage rectification of low-frequency vibration energy harvesters in the sub-volt region. This provides an important building block in enabling sustainable, self-powered electronic systems. The inkjet-printed full-wave rectifier is evaluated by electrical simulation and experimentally.
To tackle hardware-based security for printed electronics, two implementations for inkjet-printed physically unclonable functions are developed and presented. For unique identification, intrinsic variation in active printed devices are exploited. One implementation is based on a crossbar architecture, incorporating integrable electrolyte-gated transistor cells. The second implementation, the so-called differential circuit physically unclonable function, is based on inverter structures, which provide the basis for unique response generation. Both physically unclonable functions are evaluated using an electrical simulation-based approach and experimentally. The differential circuit approach is furthermore fully integrated within a silicon-based electronic platform environment and serves as intrinsic variation source in a hybrid system. The hybrid system physically unclonable function is fully verified regarding performance metrics and is capable to generate highly unique responses for secure identification.
Electrolyte-Gated Field-Effect Transistors Based on Oxide Semiconductors: Fabrication and Modeling
(2017)
Oxide semiconductors have the potential to increase the performance of inkjet printed microelectronic devices such as field-effect transistors (FETs), due to their high electron mobilities. Typical metal oxides are n-type semiconductors, while p-type oxides, although realizable, exhibit lower carriermobilities. Therefore, the circuit design based on oxide semiconductors is mostly in n-type logic only. Here we present an inkjet printed pn-diode based on p- and n-type oxide semiconductors.Copper oxide or nickel oxide is used as p-typesemiconductor whereas n-typesemiconductor is realized with indium oxide. Themeasurements show that the pn-diodes operate in the voltage window typical for printed electronics and the emission coefficient is 1.505 and 2.199 for the copper oxide based and nickel oxidebased pn-diode, respectively.Furthermore, a pn-diode model is developed and integrable into a circuit simulator.
Physically Unclonable Functions (PUFs) are hardware-based security primitives, which allow for inherent device fingerprinting. Therefore, intrinsic variation of imperfect manufactured systems is exploited to generate device-specific, unique identifiers. With printed electronics (PE) joining the internet of things (IoT), hardware-based security for novel PE-based systems is of increasing importance. Furthermore, PE offers the possibility for split-manufacturing, which mitigates the risk of PUF response readout by third parties, before commissioning. In this paper, we investigate a printed PUF core as intrinsic variation source for the generation of unique identifiers from a crossbar architecture. The printed crossbar PUF is verified by simulation of a 8×8-cells crossbar, which can be utilized to generate 32-bit wide identifiers. Further focus is on limiting factors regarding printed devices, such as increased parasitics, due to novel materials and required control logic specifications. The simulation results highlight, that the printed crossbar PUF is capable to generate close-to-ideal unique identifiers at the investigated feature size. As proof of concept a 2×2-cells printed crossbar PUF core is fabricated and electrically characterized.
Printed electronics (PE) offers flexible, extremely low-cost, and on-demand hardware due to its additive manufacturing process, enabling emerging ultra-low-cost applications, including machine learning applications. However, large feature sizes in PE limit the complexity of a machine learning classifier (e.g., a neural network (NN)) in PE. Stochastic computing Neural Networks (SC-NNs) can reduce area in silicon technologies, but still require complex designs due to unique implementation tradeoffs in PE. In this paper, we propose a printed mixed-signal system, which substitutes complex and power-hungry conventional stochastic computing (SC) components by printed analog designs. The printed mixed-signal SC consumes only 35% of power consumption and requires only 25% of area compared to a conventional 4-bit NN implementation. We also show that the proposed mixed-signal SC-NN provides good accuracy for popular neural network classification problems. We consider this work as an important step towards the realization of printed SC-NN hardware for near-sensor-processing.
Printed electronics can add value to existing products by providing new smart functionalities, such as sensing elements over large-areas on flexible or non-conformal surfaces. Here we present a hardware concept and prototype for a thinned ASIC integrated with an inkjet-printed temperature sensor alongside in-built additional security and unique identification features. The hybrid system exploits the advantages of inkjet-printable platinum-based sensors, physically unclonable function circuits and a fluorescent particle-based coating as a tamper protection layer.