Process development using oscillatory baffled mesoreactors

PhD ThesisThe mesoscale oscillatory baffled reactor (meso-OBR) is a flow chemistry platform whose niche is the ability to convert long residence time batch processes to continuous processes. This reactor can rapidly screen reaction kinetics or optimise a reaction in flow with minimal waste. In this work, several areas were identified that could be addressed to broaden the applicability of this platform. Four main research themes were subsequently formulated and explored: (I) development of deeper understanding of the fluid mechanics in meso-OBRs, (II) development of a new hybrid heat pipe meso-OBR for improved thermal management, (III) further improvement of continuous screening using meso-OBRs by removing the solvent and employing better experiment design methodologies, and (IV) exploration of 3D printing for rapid reactor development. I. The flow structures in a meso-OBR containing different helical baffle geometries were studied using computational fluid dynamics simulations, validated by particle image velocimetry (PIV) experiments for the first time. It was demonstrated, using new quantification methods for the meso-OBR, that when using helical baffles swirling is responsible for providing a wider operating window for plug flow than other baffle designs. Further, a new flow regime resembling a Taylor-Couette flow was discovered that further improved the plug flow response. This new double vortex regime could conceivably improve multiphase mixing and enable flow measurements (e.g. using thermocouples inside the reactor) to be conducted without degrading the mixing condition. This work also provides a new framework for validating simulated OBR flows using PIV, by quantitatively comparing turbulent flow features instead of qualitatively comparing average velocity fields. II. A new hybrid heat pipe meso-OBR (HPOBR) was prototyped to provide better thermal control of the meso-OBR by exploiting the rapid and isothermal properties of the heat pipe. This new HPOBR was compared with a jacketed meso-OBR (JOBR) for the thermal control of an exothermic imination reaction conducted without a solvent. Without a solvent or thermal control scheme, this reaction exceeded the boiling point of one of the reactants. A central composite experiment design explored the effects of reactant net flow rate, oscillation intensity and cooling capacity on the thermal and chemical response of the reaction. The HPOBR was able to passively control the temperature below the boiling point of the reactant at all conditions through heat spreading. Overall, a combined 260-fold improvement in throughput was demonstrated compared to a reactor requiring the use of a solvent. Thus, this ii wholly new reactor design provides a new approach to achieving green chemistry that could be theoretically easily adapted to other reactions. III. Analysis of in situ Fourier transform infrared (FTIR) spectroscopic data also suggested that the reaction kinetics of this solventless imination case study could be screened for the first time using the HPOBR and JOBR. This was tested by applying flow-screening protocols that adjusted the reactant molar ratio, residence time, and temperature in a single flow experiment. Both reactor configurations were able to screen the Arrhenius kinetics parameters (pre-exponential factors, activation energies, and equilibrium constants) of both steps of the imination reaction. By defining experiment conditions using design of experiments (DoE) methodologies, a theoretical 70+% reduction in material usage/time requirement for screening was achieved compared to the previous state-of-the-art screening using meso-OBRs in the literature. Additionally, it was discovered that thermal effects on the reaction could be inferred by changing other operating conditions such as molar ratio and residence time. This further simplifies the screening protocols by eliminating the need for active temperature control strategies (such as a jacket). IV. Finally, potential application areas for further development of the meso-OBR platform using 3D printing were devised. These areas conformed to different “hierarchies” of complexity, from new baffle structures (simplest) to entirely new methods for achieving mixing (most complex). This latter option was adopted as a case study, where the passively generated pulsatile flows of fluidic oscillators were tested for the first time as a means for improving plug flow. Improved plug flow behaviour was indeed demonstrated in three different standard reactor geometries (plain, baffled and coiled tubes), where it could be inferred that axial dispersion was decoupled from the secondary flows in an analogous manner to the OBR. The results indicate that these devices could be the basis for a new flow chemistry platform that requires no moving parts, which would be appealing for various industrial applications. It is concluded that, for the meso-OBR platform to remain relevant in the next era of tailor-made reactors (with rapid uptake of 3D printing), the identified areas where 3D printing could benefit the meso-OBR should be further explored

The Relation Between White Matter Microstructure and Network Complexity: Implications for Processing Efficiency

Brain structure has been proposed to facilitate as well as constrain functional interactions within brain networks. Simulation models suggest that integrity of white matter (WM) microstructure should be positively related to the complexity of BOLD signal – a measure of network interactions. Using 121 young adults from the Human Connectome Project, we empirically tested whether greater WM integrity would be associated with greater complexity of the BOLD signal during rest via multiscale entropy. Multiscale entropy measures the lack of predictability within a given time series across varying time scales, thus being able to estimate fluctuating signal dynamics within brain networks. Using multivariate analysis techniques (Partial Least Squares), we found that greater WM integrity was associated with greater network complexity at fast time scales, but less network complexity at slower time scales. These findings implicate two separate pathways through which WM integrity affects brain function in the prefrontal cortex – an executive-prefrontal pathway and a perceptuo-occipital pathway. In two additional samples, the main patterns of WM and network complexity were replicated. These findings support simulation models of WM integrity and network complexity and provide new insights into brain structure-function relationships

Measuring Urbanity One Block at a Time: The Neighborhood Transit Readiness Scorecard

This paper outlines a methodology that assesses urbanity in three dimensions (density, diversity, and design) and creates a combined scorecard that weights each dimension according to its influence on transit usage and walkability. Using no proprietary methods, this approach can be repeated by any individual or local government with GIS software and basic internet access. The resulting measurements can be used by communities to assess what types of investments and regulatory changes are necessary to create more transitand pedestrian-friendly communities

Multi-Fidelity Data-Driven Design and Analysis of Reactor and Tube Simulations

The development of new manufacturing techniques such as 3D printing have enabled the creation of previously infeasible chemical reactor designs. Systematically optimizing the highly parameterized geometries involved in these new classes of reactor is vital to ensure enhanced mixing characteristics and feasible manufacturability. Here we present a framework to rapidly solve this nonlinear, computationally expensive, and derivative-free problem, enabling the fast prototype of novel reactor parameterizations. We take advantage of Gaussian processes to adaptively learn a multi-fidelity model of reactor simulations across a number of different continuous mesh fidelities. The search space of reactor geometries is explored through an amalgam of different, potentially lower, fidelity simulations which are chosen for evaluation based on weighted acquisition function, trading off information gain with cost of simulation. Within our framework we derive a novel criteria for monitoring the progress and dictating the termination of multi-fidelity Bayesian optimization, ensuring a high fidelity solution is returned before experimental budget is exhausted. The class of reactor we investigate are helical-tube reactors under pulsed-flow conditions, which have demonstrated outstanding mixing characteristics, have the potential to be highly parameterized, and are easily manufactured using 3D printing. To validate our results, we 3D print and experimentally validate the optimal reactor geometry, confirming its mixing performance. In doing so we demonstrate our design framework to be extensible to a broad variety of expensive simulation-based optimization problems, supporting the design of the next generation of highly parameterized chemical reactors.Comment: 22 Pages with Appendi

Machine Learning-Assisted Discovery of Novel Reactor Designs via CFD-Coupled Multi-fidelity Bayesian Optimisation

Additive manufacturing has enabled the production of more advanced reactor geometries, resulting in the potential for significantly larger and more complex design spaces. Identifying and optimising promising configurations within broader design spaces presents a significant challenge for existing human-centric design approaches. As such, existing parameterisations of coiled-tube reactor geometries are low-dimensional with expensive optimisation limiting more complex solutions. Given algorithmic improvements and the onset of additive manufacturing, we propose two novel coiled-tube parameterisations enabling the variation of cross-section and coil path, resulting in a series of high dimensional, complex optimisation problems. To ensure tractable, non-local optimisation where gradients are not available, we apply multi-fidelity Bayesian optimisation. Our approach characterises multiple continuous fidelities and is coupled with parameterised meshing and simulation, enabling lower quality, but faster simulations to be exploited throughout optimisation. Through maximising the plug-flow performance, we identify key characteristics of optimal reactor designs, and extrapolate these to produce two novel geometries that we 3D print and experimentally validate. By demonstrating the design, optimisation, and manufacture of highly parameterised reactors, we seek to establish a framework for the next-generation of reactors, demonstrating that intelligent design coupled with new manufacturing processes can significantly improve the performance and sustainability of future chemical processes.Comment: 11 pages, 8 figure

Identification of Novel sRNAs in Mycobacterial Species

Bacterial small RNAs (sRNAs) are short transcripts that typically do not encode proteins and often act as regulators of gene expression through a variety of mechanisms. Regulatory sRNAs have been identified in many species, including Mycobacterium tuberculosis, the causative agent of tuberculosis. Here, we use a computational algorithm to predict sRNA candidates in the mycobacterial species M. smegmatis and M. bovis BCG and confirmed the expression of many sRNAs using Northern blotting. Thus, we have identified 17 and 23 novel sRNAs in M. smegmatis and M. bovis BCG, respectively. We have also applied a high-throughput technique (Deep-RACE) to map the 5′ and 3′ ends of many of these sRNAs and identified potential regulators of sRNAs by analysis of existing ChIP-seq datasets. The sRNAs identified in this work likely contribute to the unique biology of mycobacteria

Blockade ofthe negative co-stimulatory molecules PD-1 and CTLA-4 improves survival in primary and secondary fungal sepsis

INTRODUCTION: Fungal sepsis is an increasingly common problem in intensive care unit patients.Mortality from fungal sepsis remains high despite antimicrobial therapy that is highly active against most fungal pathogens, a finding consistent with defective host immunity that is present in many patients with disseminated fungemia.One recently recognized immunologic defect that occurs in patients with sepsis is T cell "exhaustion" due to increased expression of programmed cell death -1 (PD-1).This study tested the ability of anti-PD-1 and anti-programmed cell death ligand -1 (anti-PD-L1) antagonistic antibodies to improve survival and reverse sepsis-induced immunosuppression in two mouse models of fungal sepsis. METHODS: Fungal sepsis was induced in mice using two different models of infection, that is, primary fungal sepsis and secondary fungal sepsis occurring after sub-lethal cecal ligation and puncture (CLP).Anti-PD-1 and anti-PD-L1 were administered 24 to 48 h after fungal infection and effects on survival, interferon gamma production, and MHC II expression were examined. RESULTS: Anti-PD-1 and anti-PD-L1 antibodies were highly effective at improving survival in primary and secondary fungal sepsis.Both antibodies reversed sepsis-induced suppression of interferon gamma and increased expression of MHC II on antigen presenting cells.Blockade of cytotoxic T-lymphocyte antigen-4 (CTLA-4), a second negative co-stimulatory molecule that is up-regulated in sepsis and acts like PD-1 to suppress T cell function, also improved survival in fungal sepsis. CONCLUSIONS: Immuno-adjuvant therapy with anti-PD-1, anti-PD-L1 and anti-CTLA-4 antibodies reverse sepsis-induced immunosuppression and improve survival in fungal sepsis.The present results are consistent with previous studies showing that blockade of PD-1 and CTLA-4 improves survival in bacterial sepsis.Thus, immuno-adjuvant therapy represents a novel approach to sepsis and may have broad applicability in the disorder.Given the relative safety of anti-PD-1 antibody in cancer clinical trials to date, therapy with anti-PD-1 in patients with life-threatening sepsis who have demonstrable immunosuppression should be strongly considered

Mitochondrial Genetic Diversity and its Determinants in Island Melanesia

For a long time, many physical anthropologists and human geneticists considered Island Melanesian populations to be genetically impoverished, dominated by the effects of random genetic drift because of their small sizes, internally very homogeneous, and therefore of little relevance in reconstructing past human migrations. This view is changing. Here we present the developing detailed picture of mitochondrial DNA (mtDNA) variation in eastern New Guinea and Island Melanesia that reflects linguistic distinctions within the region as well as considerable island-by-island isolation. It also appears that the patterns of variation reflect marital migration distinctions between bush and beach populations. We have identified a number of regionally specific mtDNA variants. We also question the widely accepted hypothesis that the mtDNA variant referred to as the ‘Polynesian Motif’ (or alternatively the ‘Austronesian Motif’) developed outside this region somewhere to the west. It may well have first appeared among certain non-Austronesian speaking groups in eastern New Guinea or the Bismarcks. Overall, the developing mtDNA pattern appears to be more easily reconciled with that of other genetic and biometric variables

Multiscale, multimodal analysis of tumor heterogeneity in IDH1 mutant vs wild-type diffuse gliomas.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations

Perfluorinated alkyl acids and fecundity assessment in striped mullet (\u3ci\u3eMugil cephalus\u3c/i\u3e) at Merritt Island national wildlife refuge

This study investigated wild caught striped mullet (Mugil cephalus) at Merritt Island National Wildlife Refuge (MINWR) for levels of 15 perfluoroalkyl acids (PFAA) in tandem with individual fecundity measurements (Oocyte sub-stage 2 late, n=42) and oocyte reproductive stages (Stages 1–5, n=128). PFAAmeasurementswere quantified in stripedmullet liver (n=128),muscle (n=49), and gonad (n=10). No significant negative impacts of liver PFAA burden on wild-caught,mullet fecundity endpoints were observed in this study; however, changes in PFAAwere observed in the liver asmullet progressed through different sub-stages of oocyte development. Of the PFAA with significant changes by sub-stage of oocyte development, the carboxylic acids (perfluorooctanoic acid, perfluorononanoic acid, and perfluorotridecanoic acid) increased in the liver with increasing sub-stage while the sulfonic acid and its precursor (perfluorooctanesulfonic acid (PFOS) and perfluorooctanesulfonamide, respectively) decreased in the liver with increasing sub-stage of oocyte development. This is a unique find and suggests PFAA change location of compartmentalization as mullet progress towards spawning. Investigations also revealed higher than expected median muscle and gonad levels of PFOS in striped mullet collected at MINWR (9.01 ng/g and 80.2 ng/g, respectively)