Stimulated Transitions of Directed Nonequilibrium Self‐Assemblies

Near‐equilibrium stimulus‐responsive polymers have been used extensively to introduce morphological variations in dependence of adaptable conditions. Far‐less‐well studied are triggered transformations at constant conditions. These require the involvement of metastable states, which are either able to approach the equilibrium state after deviation from metastability or can be frozen on returning from nonequilibrium to equilibrium. Such functional nonequilibrium macromolecular systems hold great promise for on‐demand transformations, which result in substantial changes in their material properties, as seen for triggered gelations. Herein, a diblock copolymer system consisting of a hydrophilic block and a block that is responsive to both pressure and temperature, is introduced. This species demonstrates various micellar transformations upon leaving equilibrium/nonequilibrium states, which are triggered by a temperature deflection or a temporary application of hydrostatic pressure.     

A High-Voltage,Dendrite-Free,and Durable Zn–Graphite Battery

The intrinsic advantages of metallic Zn, like high theoretical capacity (820 mAh g⁻¹), high abundance, low toxicity, and high safety have driven the recent booming development of rechargeable Zn batteries. However, the lack of high-voltage electrolyte and cathode materials restricts the cell voltage mostly to below 2 V. Moreover, dendrite formation and the poor rechargeability of the Zn anode hinder the long-term operation of Zn batteries. Here a high-voltage and durable Zn–graphite battery, which is enabled by a LiPF₆-containing hybrid electrolyte, is reported. The presence of LiPF₆ efficiently suppresses the anodic oxidation of Zn electrolyte and leads to a super-wide electrochemical stability window of 4 V (vs Zn/Zn²⁺). Both dendrite-free Zn plating/stripping and reversible dual-anion intercalation into the graphite cathode are realized in the hybrid electrolyte. The resultant Zn–graphite battery performs stably at a high voltage of 2.8 V with a record midpoint discharge voltage of 2.2 V. After 2000 cycles at a high charge–discharge rate, high capacity retention of 97.5% is achieved with ≈100% Coulombic efficiency.     

High-Order Numerical Methods for 2D Parabolic Problems in Single and Composite Domains

In this work, we discuss and compare three methods for the numerical approximation of constant- and variable-coefficient diffusion equations in both single and composite domains with possible discontinuity in the solution/flux at interfaces, considering (i) the Cut Finite Element Method; (ii) the Difference Potentials Method; and (iii) the summation-by-parts Finite Difference Method. First we give a brief introduction for each of the three methods. Next, we propose benchmark problems, and consider numerical tests—with respect to accuracy and convergence—for linear parabolic problems on a single domain, and continue with similar tests for linear parabolic problems on a composite domain (with the interface defined either explicitly or implicitly). Lastly, a comparative discussion of the methods and numerical results will be given.     

A Nyström-based finite element method on polygonal elements

We consider families of finite elements on polygonal meshes, that are defined implicitly on each mesh cell as solutions of local Poisson problems with polynomial data. Functions in the local space on each mesh cell are evaluated via Nyström discretizations of associated integral equations, allowing for curvilinear polygons and non-polynomial boundary data. Several experiments demonstrate the approximation quality of interpolated functions in these spaces.     

Toward an execution system for self-healing workflows in cyber-physical systems

Cyber-physical systems (CPS) represent a new class of information system that also takes real-world data and effects into account. Software-controlled sensors, actuators and smart objects enable a close coupling of the cyber and physical worlds. Introducing processes into CPS to automate repetitive tasks promises advantages regarding resource utilization and flexibility of control systems for smart spaces. However, process execution systems face new challenges when being adapted for process execution in CPS: the automated processing of sensor events and data, the dynamic invocation of services, the integration of human interaction, and the synchronization of the cyber and physical worlds. Current workflow engines fulfill these requirements only to a certain degree. In this work, we present PROtEUS—an integrated system for process execution in CPS. PROtEUS integrates components for event processing, data routing, dynamic service selection and human interaction on the modeling and execution level. It is the basis for executing self-healing model-based workflows in CPS. We demonstrate the applicability of PROtEUS within two case studies from the Smart Home domain and discuss its feasibility for introducing workflows into cyber-physical systems.     

Model-driven development of mobile applications for Android and iOS supporting role-based app variability

Rapidly increasing numbers of applications and users make the development of mobile applications to one of the most promising fields in software engineering. Due to short time to market, differing platforms, and fast emerging technologies, mobile application development faces typical challenges where model-driven development (MDD) can help. We present a modeling language and an infrastructure for the MDD of native apps in Android and iOS. Our approach allows a flexible app development on different abstraction levels: compact modeling of standard app elements such as standard data management and increasingly detailed modeling of individual elements to cover, for example, specific behavior. Moreover, a kind of variability modeling is supported such that mobile apps with variants can be developed. We demonstrate our MDD approach with several apps including a conference app, a museum guide with augmented reality functionality, and a SmartPlug.     

Interfacial instability of liquid films coating the walls of a parallel-plate channel and sheared by a gas flow

The stability and coupling of liquid films coating the walls of a parallel-plate channel and sheared by a pressure-driven gas flow along the channel center plane is studied. The films are susceptible to a long-wavelength instability. For sufficiently low Reynolds numbers and thick gas layers, the dynamic behavior is found to be described by two coupled nonlinear partial differential equations. A linear stability analysis is conducted under the condition that the material properties and the initial undisturbed liquid-film thicknesses are equal. The linear analysis is utilized to determine whether the interfaces are predominantly destabilized by the variations of the shear stress or by the pressure gradient acting upon them. The analysis of the weakly nonlinear equations performed for this case shows that instabilities corresponding to a vanishing Reynolds number are absent from the system. Moreover, for this configuration, the patterns emerging along the two interfaces are found to be identical in the long-time limit, implying that the films are fully synchronized. A different setup, where the liquid films have identical material properties but their undisturbed thicknesses differ, is studied numerically. The results show that, even for this configuration, the interfacial waves remain phase-synchronized and closely correlated for an extended period of time. These findings are particularly relevant for gaseous flow through narrow ducts with liquid-coated walls.     

Detecting and preventing replay attacks in industrial automation networks operated with profinet IO

Modern industrial facilities consist of controllers, actuators and sensors that are connected via traditional IT equipment. The ongoing integration of these systems into the communication network yields to new threats and attack possibilities. In industrial networks, often distinct communication protocols like Profinet IO (PNIO) are used. These protocols are often not supported by typical network security tools. In this work, we present two attack techniques that allow to take over the control of a PNIO device, enabling an attacker to replay previously recorded traffic. We model attack detection rules and propose an intrusion detection system (IDS) for industrial networks which is capable of detecting those replay attacks by correlating alerts from traditional IT IDS with specific PNIO alarms. As an additional effort, we introduce defense in depth mechanisms in order to prevent those attacks from taking effect in the physical world. Thereafter, we evaluate our IDS in a physical demonstrator and compare it with another IDS dedicated to securing PNIO networks. In a conceptual design, we show how network segmentation with flow control allows for preventing some, but not all of the attacks.     

Data Parallel Algorithmic Skeletons with Accelerator Support

Hardware accelerators such as GPUs or Intel Xeon Phi comprise hundreds or thousands of cores on a single chip and promise to deliver high performance. They are widely used to boost the performance of highly parallel applications. However, because of their diverging architectures programmers are facing diverging programming paradigms. Programmers also have to deal with low-level concepts of parallel programming that make it a cumbersome task. In order to assist programmers in developing parallel applications Algorithmic Skeletons have been proposed. They encapsulate well-defined, frequently recurring parallel programming patterns, thereby shielding programmers from low-level aspects of parallel programming. The main contribution of this paper is a comparison of two skeleton library implementations, one in C++ and one in Java, in terms of library design and programmability. Besides, on the basis of four benchmark applications we evaluate the performance of the presented implementations on two test systems, a GPU cluster and a Xeon Phi system. The two implementations achieve comparable performance with a slight advantage for the C++ implementation. Xeon Phi performance ranges between CPU and GPU performance.