Comparing Protonolysis and Transmetalation Reactions: Microcalorimetric Studies of C–AuI Bonds in [AuRL] Complexes

Producción CientíficaThe protonolysis of C–Au bonds in [AuRL] organometallic complexes has been studied by calorimetry for twelve R groups. The experimental data have been combined with DFT calculations to obtain Bond Dissociation Energy values (BDE). The C–Au BDE values show a good correlation with the corresponding isolobal C–H BDE values. The heat released in the protonolysis of [AuRL] has also been measured for R = Ph and L = P(OPh)3, PPh3, PMe3, PCy3, and IPr, and these values strongly depend on the trans influence of L because of the mutual destabilization of the L–Au and Au–C bonds. The enthalpy of the transmetalation reactions [AuR(PPh3)] + SnIBu3 → [AuI(PPh3)] + SnRBu3 for seven R groups have been measured and compared with the corresponding [AuR(PPh3)] protonolysis.Ministerio de Economía, Industria y Competitividad (Project CTQ2016-80913-P)Junta de Castilla y León (Project VA 051P17

NMF: A Modeling Framework for the .NET Platform

For its promises in terms of increased productivity, Modeldriven engineering (MDE) is getting applied increasingly often in both industry and academia. However, most tools currently available are based on the Eclipse Modeling Framework (EMF) and hence based on the Java platform whereas tool support for other platforms is limited. This leads to a language and tool adoption problem for developers of other platforms such as .NET. As a result, few projects on the .NET platform adopt MDE. Furthermore, the limited tool availability introduces a technical barrier in the interoperability between EMF and .NET applications. In this paper, we present the .NET Modeling Framework (NMF), a tool set for model repositories, model-based incrementalization, model transformation, model synchronization and code generation. The framework makes intensive use of the C# language as host language for model transformation and synchronization languages, whereas the model repository serialization is compatible with EMF. This solves the language adoption problem for C# programmers and creates a bridge to the EMF platform

A closer look at creativity as search

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Deep Modeling through Structural Decomposition

In some applications, traditional metamodeling in two levels gets to its limits when model elements of a domain should be described as instances of other model elements. In architecture description languages, components may be instances of their component types. Although workarounds exist, these require many validation constraints and imply a cumbersome interface. To obtain more elegant metamodels that require less constraints, deep modeling seeks ways to represent non-transitive instantiation chains. However, these concepts often make existing techniques for model transformation and analysis obsolete as these languages have to be adapted. In this paper, we present an approach to realize deep modeling only through structural decomposition, which can be implemented as a non-invasive extension to meta-metamodels similar to Ecore. As a consequence, existing tools need not be adapted. We validate our concept by creating a deep modeling architecture description language and demonstrate its advantages by modeling a synthetic web application

SimpleSSD: Modeling Solid State Drives for Holistic System Simulation

Existing solid state drive (SSD) simulators unfortunately lack hardware and/or software architecture models. Consequently, they are far from capturing the critical features of contemporary SSD devices. More importantly, while the performance of modern systems that adopt SSDs can vary based on their numerous internal design parameters and storage-level configurations, a full system simulation with traditional SSD models often requires unreasonably long runtimes and excessive computational resources. In this work, we propose SimpleSSD, a highfidelity simulator that models all detailed characteristics of hardware and software, while simplifying the nondescript features of storage internals. In contrast to existing SSD simulators, SimpleSSD can easily be integrated into publicly-available full system simulators. In addition, it can accommodate a complete storage stack and evaluate the performance of SSDs along with diverse memory technologies and microarchitectures. Thus, it facilitates simulations that explore the full design space at different levels of system abstraction.Comment: This paper has been accepted at IEEE Computer Architecture Letters (CAL

Predicting size-dependent emergence of crystallinity in nanomaterials: titania nanoclusters versus nanocrystals

Bottom-up and top-down derived nanoparticle structures refined by accurate ab initio calculations are used to investigate the size dependent emergence of crystallinity in titania from the monomer upwards. Global optimisation and data mining are used to provide a series of ( TiO2) N global minima candidates in the range N = 1-38, where our approach provides many new low energy structures for N > 10. A range of nanocrystal cuts from the anatase crystal structure are also considered up to a size of over 250 atoms. All nanocrystals considered are predicted to be metastable with respect to non-crystalline nanoclusters, which has implications with respect to the limitations of the cluster approach to modelling large titania nanosystems. Extrapolating both data sets using a generalised expansion of a top-down derived energy expression for nanoparticles, we obtain an estimate of the non-crystalline to crystalline crossover size for titania. Our results compare well with the available experimental results and imply that anatase-like crystallinity emerges in titania nanoparticles of approximately 2-3 nm diameter