In Situ TEM Observation of the Behavior of an Individual Fullerene-Like MoS<Subscript>2</Subscript> Nanoparticle in a Dynamic Contact

Inorganic fullerene-(IF)-like nanoparticles made of metal dichalcogenides (IF-MoS₂, IF-WS₂) have been known to be effective as anti-wear and friction modifier additives under boundary lubrication. The lubrication mechanism of these nanoparticles has been widely investigated in the past and even if the exfoliation and third body transfer of molecular sheets onto the asperities constitute the prevalent mechanism for the improved tribological behavior of IF nanoparticles, it has also been suggested that a rolling friction process could also play a role for well crystallized and spherical particles. In this study, in situ Transmission Electron Microscopy (TEM) observations of the behavior of single IF-MoS₂ nanoparticles were conducted using a sample holder that combines TEM and Atomic Force Microscopy (AFM) which simultaneously can apply normal and shear loads. It was shown that depending on the test conditions, either a rolling process or a sliding of the fullerenes could be possible. These in situ TEM observations are the first carried out with IF nanoparticles.     

Time-correlations as a contrast mechanism in scanning-tunneling-microscopy-induced photon emission

We have developed an experimental technique based on scanning-tunneling microscope (STM) which permits to record simultaneously topography, STM-induced photon emission and a map of two-photon auto-correlations for time resolutions down to the sub-nanosecond range. In the case of a gold surface at air, we show that the tip-induced luminescence exhibits a photon-bunching phenomenon at a 10-ns time scale which depends both on bias and on local topography. The photon bunching was exclusively observed at specific bumps of the surface.     

Nonlinear creep behavior of viscoelastic polycarbonate

A study of the tension behavior of polycarbonate (PC) under room temperature and various sustained loads is presented. Time-dependent axial elongations and transverse contractions of the specimen were simultaneously measured at nine different stress levels, from 15.89 to 59.4 MPa, and modeled according to a time-stress superposition principle. The test duration was only one hour. It was shown that creep compliance vs. log time curves at different stresses can be horizontally shifted to form a smooth master curve for one year at a reference stress of 30.97 MPa. Moreover, the stress shift factors for axial extension creep curves and transverse contraction creep curves are found to be identical for the stress levels considered, and this is verified using the Poisson's ratio measurements.     

Simultaneous Edge‐on to Face‐on Reorientation and 1D Alignment of Small π‐Conjugated Molecules Using Room‐Temperature Mechanical Rubbing

In this study, room‐temperature mechanical rubbing is used to control the 3D orientation of small π‐conjugated molecular systems in solution‐processed polycrystalline thin films without using any alignment substrate. High absorption dichroic ratio and significant anisotropy in charge carrier mobilities (up to 130) measured in transistor configuration are obtained in rubbed organic films based on the ambipolar quinoidal quaterthiophene (QQT(CN)4). Moreover, a solvent vapor annealing treatment of the rubbed film is found to improve the optical and charge transport anisotropy due to an increased crystallinity. X‐ray diffraction and atomic force microscopy measurements demonstrate that rubbing does not only lead to an excellent 1D orientation of the QQT(CN)4 molecules over large areas but also modifies the orientation of the crystals, moving molecules from an edge‐on to a face‐on configuration. The reasons why a mechanical alignment technique can be used at room temperature for such a polycrystalline film are rationalized, by the plastic characteristics of the QQT(CN)4 layer and the role of the flexible alkyl side chains in the molecular packing. This nearly complete conversion from edge‐on to face‐on orientation by mechanical treatment in polycrystalline small‐molecule‐based thin films opens perspectives in terms of fundamental research and practical applications in organic optoelectronics.     

Associating and Tuning Sodium and Oxygen Mixed‐Ion Conduction in Niobium‐Based Perovskites

Pure ionic conductors as solid‐state electrolytes are of high interest in electrochemical energy storage and conversion devices. They systematically involve only one ion as the charge carrier. The association of two mobile ionic species, one positively and the other negatively charged, in a specific network should strongly influence the total ion conduction. Nb⁵⁺‐ (4d⁰) and Ti⁴⁺‐based (3d⁰) derived‐perovskite frameworks containing Na⁺ and O^2? as mobile species are investigated as mixed ion conductors by electrochemical impedance spectroscopy. The design of Na⁺ blocking layers via sandwiched pellet sintered by spark plasma sintering at high temperatures leads to quantified transport number of both ionic charge carriers t_Na+ and t_O2?. In the 350–700 °C temperature range, ionic conductivity can be tuned from major Na⁺ contribution (t_Na+ = 88%) for NaNbO₃ to pure O^2? transport in NaNb_0.9Ti_0.1O_2.95 phase. Such a Ti‐substitution is accompanied with a ≈100‐fold increase in the oxygen conductivity, approaching the best values for pure oxygen conductors in this temperature range. Besides the demonstration of tunable mixed ion conduction with quantifiable cationic and anionic contributions in a single solid‐state structure, a strategy is established from structural analysis to develop other architectures with improved mixed ionic conductivity.     

A user parameter-free approach for mining robust sequential classification rules

Recent years have witnessed extensive studies of graph classification due to the rapid increase in applications involving structural data and complex relationships. To support graph classification, all existing methods require that training graphs should be relevant (or belong) to the target class, but cannot integrate graphs irrelevant to the class of interest into the learning process. In this paper, we study a new universum graph classification framework which leverages additional “non-example” graphs to help improve the graph classification accuracy. We argue that although universum graphs do not belong to the target class, they may contain meaningful structure patterns to help enrich the feature space for graph representation and classification. To support universum graph classification, we propose a mathematical programming algorithm, ugBoost, which integrates discriminative subgraph selection and margin maximization into a unified framework to fully exploit the universum. Because informative subgraph exploration in a universum setting requires the search of a large space, we derive an upper bound discriminative score for each subgraph and employ a branch-and-bound scheme to prune the search space. By using the explored subgraphs, our graph classification model intends to maximize the margin between positive and negative graphs and minimize the loss on the universum graph examples simultaneously. The subgraph exploration and the learning are integrated and performed iteratively so that each can be beneficial to the other. Experimental results and comparisons on real-world dataset demonstrate the performance of our algorithm.     

Exact algorithms for single-machine scheduling with time windows and precedence constraints

We study a single-machine scheduling problem that is a generalization of a number of problems for which computational procedures have already been published. Each job has a processing time, a release date, a due date, a deadline, and a weight representing the penalty per unit-time delay beyond the due date. The goal is to schedule all jobs such that the total weighted tardiness penalty is minimized and both the precedence constraints as well as the time windows (implied by the release dates and the deadlines) are respected. We develop a branch-and-bound algorithm that solves the problem to optimality. Computational results show that our approach is effective in solving medium-sized instances, and that it compares favorably with existing methods for special cases of the problem.     

Efficient Cryptosystems From $$\mathbf{2}^{{\varvec{k}}}$$-th Power Residue Symbols

Goldwasser and Micali (J Comput Syst Sci 28(2):270–299, 1984) highlighted the importance of randomizing the plaintext for public-key encryption and introduced the notion of semantic security. They also realized a cryptosystem meeting this security notion under the standard complexity assumption of deciding quadratic residuosity modulo a composite number. The Goldwasser–Micali cryptosystem is simple and elegant but is quite wasteful in bandwidth when encrypting large messages. A number of works followed to address this issue and proposed various modifications. This paper revisits the original Goldwasser–Micali cryptosystem using \(2^k\)-th power residue symbols. The so-obtained cryptosystems appear as a very natural generalization for \(k \ge 2\) (the case \(k=1\) corresponds exactly to the Goldwasser–Micali cryptosystem). Advantageously, they are efficient in both bandwidth and speed; in particular, they allow for fast decryption. Further, the cryptosystems described in this paper inherit the useful features of the original cryptosystem (like its homomorphic property) and are shown to be secure under a similar complexity assumption. As a prominent application, this paper describes an efficient lossy trapdoor function-based thereon.     

Modulating the Ferromagnet/Molecule Spin Hybridization Using an Artificial Magnetoelectric

Spin‐polarized charge transfer at the interface between a ferromagnetic (FM) metal and a molecule can lead to ferromagnetic coupling and to a high spin polarization at room temperature. The magnetic properties of these interfaces can not only alter those of the ferromagnet but can also stabilize molecular spin chains with interesting opportunities toward quantum computing. With the aim to enhance an organic spintronic device's functionality, external control over this spin polarization may thus be achieved by altering the ferromagnet/molecule interface's magnetic properties. To do so, the magnetoelectric properties of an underlying ferroelectric/ferromagnetic interface are utilized. Switching the ferroelectric polarization state of a PbZr_0.2Ti_0.8O₃ (PZT) bottom layer within a PZT/Co/FePc‐based (Pc ‐ phthalocyanine) device alters the X‐ray magnetic circular dichroism of the Fe site within the phthalocyanine molecular top layer. Thus, how to electrically alter the magnetic properties of an interface with high spin polarization at room temperature is demonstrated. This expands electrical control over spin‐polarized FM/molecule interfaces, which is first demonstrated using ferroelectric molecules, to all molecular classes.     

Collaborative simulation and scientific big data analysis: Illustration for sustainability in natural hazards management and chemical process engineering

Classical approaches for remote visualization and collaboration used in Computer-Aided Design and Engineering (CAD/E) applications are no longer appropriate due to the increasing amount of data generated, especially using standard networks. We introduce a lightweight and computing platform for scientific simulation, collaboration in engineering, 3D visualization and big data management. This ICT based platform provides scientists an “easy-to-integrate” generic tool, thus enabling worldwide collaboration and remote processing for any kind of data. The service-oriented architecture is based on the cloud computing paradigm and relies on standard internet technologies to be efficient on a large panel of networks and clients. In this paper, we discuss the need of innovations in (i) pre and post processing visualization services, (ii) 3D large scientific data set scalable compression and transmission methods, (iii) collaborative virtual environments, and (iv) collaboration in multi-domains of CAD/E. We propose our open platform for collaborative simulation and scientific big data analysis. This platform is now available as an open project with all core components licensed under LGPL V2.1. We provide two examples of usage of the platform in CAD/E for sustainability engineering from one academic application and one industrial case study. Firstly, we consider chemical process engineering showing the development of a domain specific service. With the rise of global warming issues and with growing importance granted to sustainable development, chemical process engineering has turned to think more and more environmentally. Indeed, the chemical engineer has now taken into account not only the engineering and economic criteria of the process, but also its environmental and social performances. Secondly, an example of natural hazards management illustrates the efficiency of our approach for remote collaboration that involves big data exchange and analysis between distant locations. Finally we underline the platform benefits and we open our platform through next activities in innovation techniques and inventive design.