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Laser ultrasound was used to determine dispersion curves of surface acoustic waves on a Si (001) surface covered by AlScN films with a scandium content between 0 and 41%. By including off-symmetry directions for wavevectors, all five independent elastic constants of the film were extracted from the measurements. Results for their dependence on the Sc content are presented and compared to corresponding data in the literature, obtained by alternative experimental methods or by ab-initio calculations.
Infolge des stetigen Wandels auf den Märkten und der heutigen Gesellschaft durch die Digitalisierung verändern sich auch die Maßnahmen im Bereich Marketing (Kaiser 2019). In den Unternehmen befinden sich Marketingaktivitäten stetig in der Umwandlung, um sich den sich verändernden Gegebenheit anzupassen. Die vielfältigen Möglichkeiten, die das Internet heutzutage bietet, sind ein wesentlicher Grund dafür, dass Käufer und Verbraucher der klassischen Werbung immer weniger Vertrauen schenken und stattdessen Empfehlungen von Freunden, Bekannten oder Experte folgen (Kaiser 2019). Diese Entwicklung wird im digitalen Bereich durch die Influencer Kooperationen bedient. Mit der Ausweitung von Onlineangeboten haben sich die Grenzen der Unternehmenskommunikation immer weiter verschoben und umfassen nun neue Kommunikationspartner, die Influencer (Herzmann 2015, S. 9). Influencer sind sogenannte Meinungsführer und Multiplikatoren in den Sozialen Medien. Das Thema der Zusammenarbeit mit Influencern ist schon lange nichts Neues mehr. Wenn man als Unternehmen Aufmerksamkeit erlangen möchte, kann dies mit Hilfe von Meinungsmachern erreicht werden. Denn Influencer haben mehr als nur Reichweite zu bieten, sie haben echte Anhänger und Fans, die auf die Glaubwürdigkeit der Influencer vertrauen, wodurch eine enge Bindung entstehen kann. Infolgedessen, dass es neue Kooperationspartner gibt, müssen die Kommunikationsinhalte und -strukturen im Unternehmen anders aufbereitet werden. Wer sich für Influencer Kooperationen in der Kommunikation entscheidet, muss sich des Stellenwerts erst einmal bewusst werden. Denn insbesondere durch das Beziehungsmanagement zu Influencern kann die digitale Reputation aufgebaut werden und maßgeblich zum Erfolg der Organisation führen (Herzmann 2015, S. 11). Wer sein Produkt oder seine Marke voranbringen will und auf eine genaue Zielgruppe ausrichten möchte, kommt nicht um das Thema Influencer herum. Denn Meinungsmacher haben extrem viele Facetten und kommunizieren über Social Media Kanäle.
Aus Ideen werden Produkte
(2020)
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.
Modern society is more than ever striving for digital connectivity -- everywhere and at any time, giving rise to megatrends such as the Internet of Things (IoT). Already today, 'things' communicate and interact autonomously with each other and are managed in networks. In the future, people, data, and things will be interlinked, which is also referred to as the Internet of Everything (IoE). Billions of devices will be ubiquitously present in our everyday environment and are being connected over the Internet.
As an emerging technology, printed electronics (PE) is a key enabler for the IoE offering novel device types with free form factors, new materials, and a wide range of substrates that can be flexible, transparent, as well as biodegradable. Furthermore, PE enables new degrees of freedom in circuit customizability, cost-efficiency as well as large-area fabrication at the point of use.
These unique features of PE complement conventional silicon-based technologies. Additive manufacturing processes enable the realization of many envisioned applications such as smart objects, flexible displays, wearables in health care, green electronics, to name but a few.
From the perspective of the IoE, interconnecting billions of heterogeneous devices and systems is one of the major challenges to be solved. Complex high-performance devices interact with highly specialized lightweight electronic devices, such as e.g. smartphones and smart sensors. Data is often measured, stored, and shared continuously with neighboring devices or in the cloud. Thereby, the abundance of data being collected and processed raises privacy and security concerns.
Conventional cryptographic operations are typically based on deterministic algorithms requiring high circuit and system complexity, which makes them unsuitable for lightweight devices.
Many applications do exist, where strong cryptographic operations are not required, such as e.g. in device identification and authentication. Thereby, the security level mainly depends on the quality of the entropy source and the trustworthiness of the derived keys. Statistical properties such as the uniqueness of the keys are of great importance to precisely distinguish between single entities.
In the past decades, hardware-intrinsic security, particularly physically unclonable functions (PUFs), gained a lot of attraction to provide security features for IoT devices. PUFs use their inherent variations to derive device-specific unique identifiers, comparable to fingerprints in biometry.
The potentials of this technology include the use of a true source of randomness, on demand key derivation, as well as inherent key storage.
Combining these potentials with the unique features of PE technology opens up new opportunities to bring security to lightweight electronic devices and systems. Although PE is still far from being matured and from being as reliable as silicon technology, in this thesis we show that PE-based PUFs are promising candidates to provide key derivation suitable for device identification in the IoE.
Thereby, this thesis is primarily concerned with the development, investigation, and assessment of PE-based PUFs to provide security functionalities to resource constrained printed devices and systems.
As a first contribution of this thesis, we introduce the scalable PE-based Differential Circuit PUF (DiffC-PUF) design to provide secure keys to be used in security applications for resource constrained printed devices. The DiffC-PUF is designed as a hybrid system architecture incorporating silicon-based and inkjet-printed components. We develop an embedded PUF platform to enable large-scale characterization of silicon and printed PUF cores.
In the second contribution of this thesis, we fabricate silicon PUF cores based on discrete components and perform statistical tests under realistic operating conditions. A comprehensive experimental analysis on the PUF security metrics is carried out. The results show that the silicon-based DiffC-PUF exhibits nearly ideal values for the uniqueness and reliability metrics. Furthermore, the identification capabilities of the DiffC-PUF are investigated and it is shown that additional post-processing can further improve the quality of the identification system.
In the third contribution of this thesis, we firstly introduce an evaluation workflow to simulate PE-based DiffC-PUFs, also called hybrid PUFs. Hereof, we introduce a Python-based simulation environment to investigate the characteristics and variations of printed PUF cores based on Monte Carlo (MC) simulations. The simulation results show, that the security metrics to be expected from the fabricated devices are close to ideal at the best operating point.
Secondly, we employ fabricated printed PUF cores for statistical tests under varying operating conditions including variations in ambient temperature, relative humidity, and supply voltage. The evaluations of the uniqueness, bit aliasing, and uniformity metrics are in good agreement with the simulation results. The experimentally determined mean reliability value is relatively low, which can be explained by the missing passivation and encapsulation of the printed transistors. The investigation of the identification capabilities based on the raw PUF responses shows that the pure hybrid PUF is not suitable for cryptographic applications, but qualifies for device identification tasks.
The final contribution is to switch to the perspective of an attacker. To judge on the security capabilities of the hybrid PUF, a comprehensive security analysis in the manner of a cryptanalysis is performed. The analysis of the entropy of the hybrid PUF shows that its vulnerability against model-based attacks mainly depends on the selected challenge building method. Furthermore, an attack methodology is introduced to assess the performances of different mathematical cloning attacks on the basis of eavesdropped challenge-response pairs (CRPs). To clone the hybrid PUF, a sorting algorithm is introduced and compared with commonly used supervised machine learning (ML) classifiers including logistic regression (LR), random forest (RF), as well as multi-layer perceptron (MLP).
The results show that the hybrid PUF is vulnerable against model-based attacks. The sorting algorithm benefits from shorter training times compared to the ML algorithms. If the eavesdropped CRPs are erroneous, the ML algorithms outperform the sorting algorithm.
Das im Rahmen psychosomatischer und neurologischer Grundlagenforschung an der Uniklinik Heidelberg entwickelte Experimentalsystem der „zweigriffigen Baumsäge“ kann als bio-kybernetisches Experimentalsystem erster Stunde bezeichnet werden. Der Psychosomatiker und Philosoph Martin Dornberg und der Medienkünstler Daniel Fetzner diskutieren in einem Gespräch Kontexte und Folgen der um den Heidelberger Psychosomatiker Victor v. Weizsäcker in den 1940/1950er Jahren durchgeführten medizinischen Experimente in den Bereichen von Medizin und Psychotherapie einerseits, aber auch in den Technik- und Medienwissenschaften, der Kybernetik und der Medienkunst. Herausgearbeitet werden Querbezüge zu den von den Autoren durchgeführten künstlerisch-philosophischen Forschungen in Form von Installationen, Performances und interaktiven Webdokumentationen.