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Investigations of Hydrocarbon Species on Solid Catalysts by Inelastic Neutron ScatteringAbstract: The status of surface species on solid catalysts during heterogeneous catalysis is often mysterious. Investigations of these surface species are crucial to deconvolute the reaction network and design more efficient catalysts. Vibrational spectroscopy is a powerful technique to study the interactions between surface species and the catalysts and infrared (IR) and Raman spectroscopies have been widely applied to study reaction mechanisms in heterogeneous catalysis. However, IR/Raman spectra are difficult to model computationally and important vibrational modes may be IR-, Raman- (or both) inactive due to restrictions by optical selection rules. Inelastic neutron scattering (INS) is another form of vibrational spectroscopy and relies on the scattering of neutrons by the atomic nucleus. A consequence of this is that INS is not subject to any optical selection rules and all vibrations are measurable in principle. INS spectroscopy has been used to investigate surface species on catalysts in a wide range of heterogeneous catalytic reactions. In this mini-review, we focus on applications of INS in two important fields: petrochemical reactions and C1 chemistry. We introduce the basic principles of the INS technique, followed by a discussion of its application in investigating two key catalytic systems: (i) the behaviour of hydrocarbons on metal-oxide and zeolite catalysts and (ii) the formation of hydrocarbonaceous species on methane reforming and Fischer–Tropsch catalysts. The power of INS in studying these important catalytic systems is demonstrated.
Modelling trend life cycles in scientific research using the Logistic and Gompertz equationsAbstract: Scientific topics vary in popularity over time. In this paper, we model the life cycles of 200 trending topics by fitting the Logistic and Gompertz models to their frequency over time in published abstracts. Unlike other work, the topics we use are algorithmically extracted from large datasets of abstracts covering computer science, particle physics, cancer research, and mental health. We find that the Gompertz model produces lower median error, leading us to conclude that it is the more appropriate model. Since the Gompertz model is asymmetric, with a steep rise followed a long tail, this implies that scientific topics follow a similar trajectory. We also explore the case of double-peaking curves and find that in some cases, topics will peak multiple times as interest resurges. Finally, when looking at the different scientific disciplines, we find that the lifespan of topics is longer in some disciplines (e.g. cancer research and mental health) than it is others, which may indicate differences in research process and culture between these disciplines.
Contractible, hyperbolic but non-CAT(0) complexesAbstract: We prove that almost all arc complexes do not admit a CAT(0) metric with finitely many shapes, in particular any finite-index subgroup of the mapping class group does not preserve such a metric on the arc complex. We also show the analogous statement for all but finitely many disc complexes of handlebodies and free splitting complexes of free groups. The obstruction is combinatorial. These complexes are all hyperbolic and contractible but despite this we show that they satisfy no combinatorial isoperimetric inequality: for any n there is a loop of length 4 that only bounds discs consisting of at least n triangles. On the other hand we show that the curve complexes satisfy a linear combinatorial isoperimetric inequality, which answers a question of Andrew Putman.
Large cell neuroendocrine lung carcinoma: consensus statement from The British Thoracic Oncology Group and the Association of Pulmonary PathologistsAbstract: Over the past 10 years, lung cancer clinical and translational research has been characterised by exponential progress, exemplified by the introduction of molecularly targeted therapies, immunotherapy and chemo-immunotherapy combinations to stage III and IV non-small cell lung cancer. Along with squamous and small cell lung cancers, large cell neuroendocrine carcinoma (LCNEC) now represents an area of unmet need, particularly hampered by the lack of an encompassing pathological definition that can facilitate real-world and clinical trial progress. The steps we have proposed in this article represent an iterative and rational path forward towards clinical breakthroughs that can be modelled on success in other lung cancer pathologies.