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.     

Automated design of error-resilient and hardware-efficient deep neural networks

Applying deep neural networks (DNNs) in mobile and safety-critical systems, such as autonomous vehicles, demands a reliable and efficient execution on hardware. The design of the neural architecture has a large influence on the achievable efficiency and bit error resilience of the network on hardware. Since there are numerous design choices for the architecture of DNNs, with partially opposing effects on the preferred characteristics (such as small error rates at low latency), multi-objective optimization strategies are necessary. In this paper, we develop an evolutionary optimization technique for the automated design of hardware-optimized DNN architectures. For this purpose, we derive a set of inexpensively computable objective functions, which enable the fast evaluation of DNN architectures with respect to their hardware efficiency and error resilience. We observe a strong correlation between predicted error resilience and actual measurements obtained from fault injection simulations. Furthermore, we analyze two different quantization schemes for efficient DNN computation and find one providing a significantly higher error resilience compared to the other. Finally, a comparison of the architectures provided by our algorithm with the popular MobileNetV2 and NASNet-A models reveals an up to seven times improved bit error resilience of our models. We are the first to combine error resilience, efficiency, and performance optimization in a neural architecture search framework.

     

What are the characteristics of popular APIs? A large-scale study on Java,Android, and 165 libraries

Software systems are commonly implemented with the support of libraries, which provide features via APIs. Ideally, APIs should have some characteristics, for example, they should be well documented and stable so that client systems can confidently rely on them. However, not all APIs are equal in number of clients: while some APIs are very popular and used worldwide, other may face much lower usage rates. In this context, one question appears: are there particular characteristics that differentiate popular APIs from ordinary APIs? Answering this question can uncover how worldwide APIs are actually implemented and maintained, revealing practices to better support both research and development on APIs. In this paper, we assess the characteristics of popular APIs, including their size, legibility, documentation, stability, and client adoption. We analyze 1491 APIs provided by Java, Android, and 165 libraries. We detect that popular APIs are distinct from ordinary ones, for example, often, popular APIs are larger, have more comments, and are more unstable than ordinary APIs. Finally, we provide a set of lessons learned from the popular APIs on factors that developers can control, such as the exposure of public methods and the API stability.

     

SkaSim – Skalierbare HPC‐Software für molekulare Simulationen in der chemischen Industrie

This article outlines advances in molecular modeling and simulation using massively parallel high‐performance computers (HPC). In the SkaSim project, partners from the HPC community collaborated with users from science and industry. The aim was to optimize the prediction of thermodynamic property data in terms of efficiency, quality and reliability using HPC methods. In this context, various topics were dealt with: atomistic simulation of homogeneous gas bubble formation, surface tension of classical fluids and ionic liquids, multicriteria optimization of molecular models, the development of the molecular simulation codes ls1 mardyn and ms2, atomistic simulation of gas separation processes, molecular membrane structure generators, transport resistors and the evaluation of predictive property data models based on specific mixture types.     

Strong and super tough: Layered ceramic‐polymer composites with bio‐inspired morphology

Bio‐inspired layered ceramic‐polymer composites with high strength and toughness were prepared from sintered aluminum oxide ceramic sheets and cationically curing epoxy resins toughened with poly(ε‐caprolactone) (PCL). The architecture of the composite is inspired by nacre but is arranged on a larger scale. Ceramic sheets with a nominal thickness of 250 μm were assembled into composite plates by adhesive layers with a nominal thickness of 20 μm. Before the manufacturing of the composites, the stress‐strain properties of the polymer component were tailored by the variation in the PCL content between 0 and 39 wt%. For composites with 4 and 15 ceramic layers, the bending strengths achieved 327 MPa and 376 MPa, which are higher than that of pure ceramic sheets. Moreover, composites with 15 ceramic layers show a 16 times higher toughness compared to that of the pure ceramic sheets. The results indicate that the toughness of the layered composites increases significantly with the number of layers. Inspired by the geometrical ratio of the natural sheet composite nacre, we have achieved a similar strength but a 2 times higher toughness than nacre by only adding up to 6 vol% of the polymer.     

Improvement of the short‐ and long‐term mechanical properties of injection‐molded poly(etheretherketone) and hydroxyapatite nanocomposites

Nanocomposites of polyetheretherketone (PEEK) and hydroxyapatite (HA) nanoparticles treated with a silane coupling agent were successfully prepared by twin screw extrusion and injection molding. Some of the samples were annealed after the injection molding. The silane treatment promoted an improvement of the short‐ and long‐term mechanical properties of the nanocomposites. A higher stress and a six times higher deformation at break and a higher impact strength were observed in the silane‐treated nanocomposites when compared to the nontreated ones. The number of cycles to fail of the treated nanocomposites was almost 200% higher than the number of cycles to fail of the nontreated samples. The treatment also decreased the glass transition temperature and amount of crystallinity of the samples. This improvement in mechanical properties obtained from the silane treatment was attributed to the strengthening of the PEEK/HA interfacial bond, to the plasticization of the PEEK matrix by silane oligomers produced during the processing and to a better dispersion of the HA nanoparticles within the PEEK matrix. Samples annealing, however, diminished all these properties due to the increase in crystallinity. Studies of the short‐ and long‐term mechanical properties of these nanocomposites under physiological conditions and of the proliferation of stem cells are under way. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44476.     

Manifestation of <Emphasis Type="Italic">PT</Emphasis> symmetry in the exciton spectra of quantum wells

The reflection and photoluminescence excitation spectra under circular polarization of the incident light are measured in wide quantum wells whose width is much larger than the exciton Bohr radius. It is found that, in the absence of a magnetic field, the relation between the intensities of even and odd absorption peaks is reversed upon reversal of the sign of circular polarization.     

Hydrothermally treated chitosan spontaneously forms water-soluble spherical particles stable at a wide pH range

The authors report the spontaneous formation of water-soluble chitosan-tartaric acid (CS-TA) spherical particles. Particles are formed by heating chitosan in the presence of tartaric acid under hydrothermal conditions. Tartaric acid serves as an ionic cross-linker, a depolymerizing agent, and a particle stabilizer in aqueous phase. The CS-TA particles exhibit superior colloidal stability at a wide pH range due to their surface charge tunability, which is due to the colocalization of surface hydroxyl, amine, and carboxyl groups. At physiological pH condition, particles have zwitterionic structure as determined by the zeta potential measurements. Still, CS-TA maintains colloidal stability at neutral pH due to the abundance of surface hydroxyl groups. As a proof-of-concept study, the CS-TA particles were labeled with a model insoluble cargo (fluorescein isothiocyanate [FITC]) to demonstrate their capacity for solubilizing hydrophobic drugs. The CS-TA/FITC conjugates were found to remain well dispersed at neutral pH, while maintaining FITC fluorescence properties.     

Intelligence by mechanics

Research on the biomechanics of animal and human locomotion provides insight into basic principles of locomotion and respective implications for construction and control. Nearly elastic operation of the leg is necessary to reproduce the basic dynamics in walking and running. Elastic leg operation can be modelled with a spring-mass model. This model can be used as a template with respect to both gaits in the construction and control of legged machines. With respect to the segmented leg, the humanoid arrangement saves energy and ensures structural stability. With the quasi-elastic operation the leg inherits the property of self-stability, i.e. the ability to stabilize a system in the presence of disturbances without sensing the disturbance or its direct effects. Self-stability can be conserved in the presence of musculature with its crucial damping property. To ensure secure foothold visco-elastic suspended muscles serve as shock absorbers. Experiments with technically implemented leg models, which explore some of these principles, are promising.