Open Access

Lithium‐ion battery cells are multiscale and multiphysics systems. Design and material parameters influence the macroscopically observable cell performance in a complex and nonlinear way. Herein, the development and application of three methodologies for model‐based interpretation and visualization of these influences are presented: 1) deconvolution of overpotential contributions, including ohmic, concentration, and activation overpotentials of the various cell components; 2) partial electrochemical impedance spectroscopy, allowing a direct visualization of the origin of different impedance features; and 3) sensitivity analyses, allowing a systematic assessment of the influence of cell parameters on capacity, internal resistance, and impedance. The methods are applied to a previously developed and validated pseudo‐3D model of a high‐power lithium‐ion pouch cell. The cell features a blend cathode. The two blend components show strong coupling, which can be observed and interpreted using the results of overpotential deconvolution, partial impedance spectroscopy, and sensitivity analysis. The presented methods are useful tools for model‐supported lithium‐ion cell research and development.

Astaxanthin is a keto-carotenoid, belongs to the chemical class of terpenes and is a yellow lipid soluble compound. The compound is present in marine animals like salmons and crustacean. Its colour is due to conjugated double bonds and these double bonds are responsible for its antioxidant effect. Its antioxidant activity is ten times stronger than other carotenoids and nearly 500 fold stronger than vitamin-E. We present a new thin layer chromatography (TLC) method to measure astaxanthin on TLC-plates (Merck, 1.05554) in the visible absorption range as well as by using chemiluminescence. For separation a solvent mixture of cyclohexane and acetone (10 + 2.4, v/v) was used. The RF-value of astaxanthin is 0.14.The limit of detection in vis-absorption is 64 ng / band and the limit of quantification is 92 ng/band. In chemiluminescence the values are 90 ng / band and 115 ng/band. The method offers two independently working measurement modes on a single plate which increase the accuracy of the quantification.

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.

The paper focuses on the work of an interdisciplinary project between photonics and digital art. The result is a poster collection dedicated to the International Year of Light 2015. In addition, an internet platform was created that presents the project. It can be accessed at http://www.magic-of-light.org/iyl2015/index.htm. From the idea to the final realization, milestones with tasks and steps will be presented in the paper. As an interdisciplinary project, students from technological degree programs were involved as well as art program students. The 2015 Anniversaries: Alhazen (1015), De Caus (1615), Fresnel (1815), Maxwell (1865), Einstein (1905), Penzias Wilson, Kao (1965) and their milestone contributions in optics and photonics will be highlighted.