High temperature cobalt-base alloy Patent

High temperature cobalt-base alloy resistant to corrosion by liquid metals and to sublimation in vacuum environmen

Effect of variations in silicon and iron content on embrittlement of L-605 /HS-25/

Silicon and iron content effects on ductility and tensile strength of cobalt alloy after agin

Nasa developments in cobalt-base superalloys

Chemical, mechanical and physical properties of cobalt-refractory-metal superalloys for high temperature aerospace application

Knowledge is at the Edge! How to Search in Distributed Machine Learning Models

With the advent of the Internet of Things and Industry 4.0 an enormous amount of data is produced at the edge of the network. Due to a lack of computing power, this data is currently send to the cloud where centralized machine learning models are trained to derive higher level knowledge. With the recent development of specialized machine learning hardware for mobile devices, a new era of distributed learning is about to begin that raises a new research question: How can we search in distributed machine learning models? Machine learning at the edge of the network has many benefits, such as low-latency inference and increased privacy. Such distributed machine learning models can also learn personalized for a human user, a specific context, or application scenario. As training data stays on the devices, control over possibly sensitive data is preserved as it is not shared with a third party. This new form of distributed learning leads to the partitioning of knowledge between many devices which makes access difficult. In this paper we tackle the problem of finding specific knowledge by forwarding a search request (query) to a device that can answer it best. To that end, we use a entropy based quality metric that takes the context of a query and the learning quality of a device into account. We show that our forwarding strategy can achieve over 95% accuracy in a urban mobility scenario where we use data from 30 000 people commuting in the city of Trento, Italy.Comment: Published in CoopIS 201

Performative interaction in public space

Building on the assumption that every human action in public space has a performative aspect, this workshop seeks to explore issues of interactions with technology in public settings. More and more interfaces are used in public on an everyday basis. Simultaneously, metaphors from performance and theatre studies find their way into research on these interfaces, addressing how interaction with technology can be understood in a performative sense. However, the term 'performativity' is rarely addressed in ways that accentuate its nuances and its analytic power, and this is the focus of the workshop. We will examine the design of performative technologies, the evaluation of user experience, the importance of spectator and performer roles, and the social acceptability of performative actions in public spaces

Determining the surface structure of silicated alumina catalysts via isotopic enrichment and dynamic nuclear polarization surface-enhanced NMR spectroscopy

We would like to thank SASOL and EPSRC (EP/L505079/1) for studentship funding for AGMR. SEA would also like to thank the Royal Society and Wolfson Foundation for a merit award. PBW would like to thank the Royal Society for the award of an Industry Fellowship. The University of Nottingham DNP MAS NMR Facility used in this research was funded by EPSRC and the University of Nottingham, and assistance from the Facility Manager (Subhradip Paul, University of Nottingham) is also acknowledged. This work was also supported by ERC Advanced Grant No. 320860. The research data (and/or materials) supporting this publication can be accessed at DOI: http://dx.doi.org/10.17630/00533fb3-e938-498d-bfe4-f07d82c309d6.Isotopic enrichment of 29Si and DNP-enhanced NMR spectroscopy are combined to determine the detailed surface structure of a silicated alumina catalyst. The significant sensitivity enhancement provided by DNP is vital to the acquisition of multinuclear and multidimensional experiments that provide information on the atomic-level structure of the species present at the surface. Isotopic enrichment not only facilitates spectral acquisition, particularly given the low (1.5 wt%) Si loading, but also enables spectra with higher resolution than those acquired using DNP to be obtained. The unexpected similarity of conventional, CP and DNP NMR spectra is attributed to the presence of adventitious surface water that forms a sufficiently dense 1H network at the silica surface so as to mediate efficient polarization transfer to all Si species regardless of their chemical nature. Spectra reveal the presence of Si-O-Si linkages at the surface (identified as Q4(3Al)-Q4(3Al)), and confirm that the anchoring of the surface overlayer with the alumina occurs through AlIV and AlV species only. This suggests the presence of Q3/Q4 Si at the surface affects the neighboring Al species, modifying the surface structure and making it less likely AlVI environments are in close spatial proximity. In contrast, Q1/Q2 species, bonded to the surface by fewer covalent bonds, have less of an effect on the surface and more AlVI species are consequently found nearby. The combination of isotropic enrichment and DNP provides a definitive and fully quantitative description of the Si-modified alumina surface, and we demonstrate that almost one-third of the silicon at the surface is connected to another Si species, even at the low level of coverage used, lowering the propensity for the formation of Brønsted acid sites. This suggests that a variation in the synthetic procedure might be required to obtain a more even coverage for optimum performance. The work here will allow for more rigorous future investigations of structure-function relationships in these complex materials.PostprintPeer reviewe

Exploring the self-assembly and energy transfer of dynamic supramolecular iridium-porphyrin systems

EZ-C acknowledges the University of St Andrews for financial support. IDWS acknowledges support from EPSRC (EP/J009016) and the European Research Council (grant 321305). IDWS also acknowledges support from a Royal Society Wolfson research merit award. DJ acknowledges the European Research Council (grant: 278845) and the RFI Lumomat for financial support.We present the first examples of dynamic supramolecular systems composed of cyclometalated Ir(III) complexes of the form of [Ir(C^N)2(N^N)]PF6 (where C^N is mesppy = 2-phenyl-4-mesitylpyridinato and dFmesppy = 2-(4,6-difluorophenyl)-4-mesitylpyridinato and N^N is 4,4':2',2'':4'',4'''-quaterpyridine, qpy) and zinc tetraphenylporphyrin (ZnTPP), assembled through non-covalent interactions between the distal pyridine moieties of the qpy ligand located on the iridium complex and the zinc of the ZnTPP. The assemblies have been comprehensively characterized by a series of analytical techniques (1H NMR titration experiments, 2D COSY and HETCOR NMR spectra and low temperature 1H NMR spectroscopy) and the crystal structures have been elucidated by X-ray diffraction. The optoelectronic properties of the assemblies and the electronic interaction between the iridium and porphyrin chromophoric units have been explored with detailed photophysical measurements, supported by time-dependent density functional theory (TD-DFT) calculations.PostprintPeer reviewe

Post-synthetic modification of zinc metal-organic frameworks through palladium-catalysed carbon-carbon bond formation

The EPSRC is thanked for financial support.Post-synthetic Suzuki coupling reactions have been undertaken on the halide-functionalised metal-organic frameworks (MOFs) [Zn4O(bdc-Br)3] (bdc-Br = 2-bromo-1,4-benzenedicarboxylate, IRMOF-2) and [Zn4O(bdc-I)3] (bdc-I = 2-iodo-1,4-benzenedicarboxylate). Although the bulky catalyst employed leads to relatively low conversions, the use of core–shell MOFs demonstrates that the reactions are not confined to the crystal surfaces.PostprintPeer reviewe

An NMR crystallographic investigation of the relationships between the crystal structure and 29Si isotropic chemical shift in silica zeolites

This work was supported by the ERC (EU FP7 Consolidator Grant 614290 ‘‘EXONMR’’) and EPSRC for computational support through the Collaborative Computational Project on NMR Crystallography (CCP-NC), via EP/M022501/1). SEA would also like to thank the Royal Society and Wolfson Foundation for a merit award. The research data supporting this publication can be accessed at DOI: 10.17630/2daa020f-315d-451e-bdec-9a788ab810fe.NMR crystallography has recently been applied to great effect for silica zeolites. Here we investigate whether it is possible to extend the structural information available from routine NMR spectra via a simple structure-spectrum relationship. Unlike previous empirically-derived relationships that have compared experimental crystal structures for (often disordered) silicates with experimental NMR spectra, where the structure may not be an accurate representation of the material studied experimentally, we use NMR parameters calculated by density functional theory (DFT) for both model Si(OSi(OH)3)4 clusters and also extended zeolitic SiO2 frameworks, for which the input structure corresponding to the NMR parameters is known exactly. We arrive at a structure-spectrum relationship dependent on the mean Si–O bond length, mean Si–O–Si bond angle, and the standard deviations of both parameters, which can predict to within 1.3 ppm the 29Si isotropic magnetic shielding that should be obtained from a DFT calculation. While this semi-empirical relationship will never supersede DFT where this is possible, it does open up the possibility of a rapid estimation of the outcome of a DFT calculation where the actual calculation would be prohibitively costly or otherwise challenging. We also investigate the structural optimisation of SiO2 zeolites using DFT, demonstrating that the mean Si–O bond lengths all tend to 1.62 Å and the distortion index tends to <2.0°, suggesting that these metrics may be suitable for rapid validation of whether a given crystal structure represents a realistic local geometry around Si, or merely a bulk average with contributions from several different local geometries.PostprintPostprintPeer reviewe

Random matrix ensembles of time correlation matrices to analyze visual lifelogs

Visual lifelogging is the process of automatically recording images and other sensor data for the purpose of aiding memory recall. Such lifelogs are usually created using wearable cameras. Given the vast amount of images that are maintained in a visual lifelog, it is a significant challenge for users to deconstruct a sizeable collection of images into meaningful events. In this paper, random matrix theory (RMT) is applied to a cross-correlation matrix C, constructed using SenseCam lifelog data streams to identify such events. The analysis reveals a number of eigenvalues that deviate from the spectrum suggested by RMT. The components of the deviating eigenvectors are found to correspond to “distinct significant events” in the visual lifelogs. Finally, the cross-correlation matrix C is cleaned by separating the noisy part from the non-noisy part. Overall, the RMT technique is shown to be useful to detect major events in SenseCam images