5,575 research outputs found

    The application of in situ generated hydrogen peroxide for corrosion inhibition, disinfection and pollutant degradation

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    This thesis describes the utilisation and activation of in situ generation of hydrogen peroxide (H2O2) from dioxygen (O2) for corrosion inhibition, disinfection and pollutant degradation. MnCl2· 4H2O and Tiron (disodium 4,5-dihydroxy-1,3-benzenedisulfonate) rapidly remove O2 from aqueous solution at a rate of ~20 mg∙ L^(-1) min^(-1) using hydroxylamine (NH2OH) as reducing substrate. A mechanism is proposed that involves two 1-electron transfers from bound NH2OH to bound O2 to produce H2O2 concomitant with two proton transfers from catecholate oxygen atoms. This system can act as an anti-corrosion formulation as the catalytic reduction of O2 results in the removal of O2 from open aqueous solutions and the in situ generated H2O2 can be used as a biocide e.g. to kill L. pneumophila. The same system, which involves manganese(II) ions (Mn(II)) and Tiron as the co-catalyst for the in situ generation of H2O2, was also utilised for the oxidative degradation of Calmagite (CAL, 2-hydroxy-1-(2-hydroxy-5methylphenylazo)-4-naphthalenesulfonic acid) at room temperature. Percarbonate (HCO4-) was found to be the main reactive species for CAL degradation in the added H2O2 system buffered by carbonate at pH 9.0 in the absence of Mn(II). Manganese(IV)=O (Mn(IV)=O) and manganese(V)=O (Mn(V)=O) are the main reactive species in the added H2O2/Mn(II) system buffered by carbonate and non-carbonate buffers respectively. This system was enhanced by activation using ultrasound and copper(II) ions (Cu2+) as catalyst, forming the Cu2+/O2/ultrasound/NH2OH (COUN) system for the degradation of bisphenol AF (BPAF). Using a two-stage kinetic model, quantitative analysis of the catalytic efficiency showed that Cu2+ was relatively stable in the COUN system in contrast to the Cu2+/H2O2/ultrasound (CHU) system. This work contributes to a better understanding of the use of Cu2+, NH2OH and O2 for the in situ generation of H2O2, as well as the role of Cu2+ and NH2OH in Fenton-like systems

    Hydrodeoxygenation of Lignin-Derived Model Compound for Sustainable Aviation Fuel Production Using Bifunctional Catalysts

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    The development for sustainable and renewable fuels is driven by the current reliance on fossil fuels and a need to reduce contaminant gas emissions and adhere to climate-related regulations. The main challenge for the aviation industry in particular is the transition towards cleaner energy sources. A promising solution is manufacturing hydrocarbons from renewable sources, minimizing the environmental impact and high costs required for alternative green technologies. Lignin is considered as a promising source of materials and biofuels, as it can be transformed through various thermochemical processes to valuable products. To obtain liquid hydrocarbons, lignin needs to undergo pyrolysis, resulting in bio-oil, which requires additional upgrading due to its low heating value, high viscosity, and acidity. Hydrodeoxygenation can be used to remove the oxygen groups, obtaining hydrocarbons compatible with the existing infrastructure. In this study, hydrodeoxygenation of isoeugenol, a lignin-derived model compound, was investigated using various bifunctional catalysts in both batch and continuous reactors. A series of bimetallic platinum-rhenium catalysts supported on mesoporous and activated carbon were studied, with the purpose of revealing the role of both metals for hydrogenation and deoxygenation. The results indicated that a higher rhenium loading resulted in improved activity, providing the oxygen vacancies required for deoxygenation. Further research performed in a continuous reactor allowed high conversion (100%) and deoxygenation level (90%) at 200 ÂșC. For the first time studies simulating industrial catalysts and eventual scaling-up were performed for a lignin-derived model compound in batch and continuous reactors using powders and extrudates, respectively, comprising platinum as the active metal, zeolite beta and a binder. The effects of the binder addition, platinum location, and zeolite acidity were evaluated for the powder catalyst, while the effect of platinum location and reaction temperature was evaluated for the extrudates. The addition of binder resulted in a decrease of surface area, total pore volume, and acidity, additionally, the catalysts containing the more acidic zeolite (H-Beta-25) exhibited better catalytic performance (ca. 80% conversion and over 50% yield of the deoxygenated product) compared to the H-Beta-300. The proximity of platinum to acid sites enhanced considerably catalytic activity, resulting in ca. 20% higher conversion when platinum was deposited on the zeolite rather than only on the binder. The extrudates displayed good stability, with a 10% decrease in catalytic activity after 30 hours of time on stream. Additionally, an effectiveness factor of 0.17 and an apparent activation energy of 14.7 kJ/mol revealed the presence of mass transfer limitations. A high conversion (100%) and a significant yield of deoxygenated products (80%), were obtained at 200 ÂșC.Utvecklingen av hĂ„llbara och förnybara brĂ€nslen drivs av det nuvarande beroendet av fossila brĂ€nslen och av ett behov att minska utslĂ€ppen av förorenande gaser och följa klimatrelaterade bestĂ€mmelser. Den största utmaningen i synnerhet för flygindustrin Ă€r övergĂ„ngen till renare energikĂ€llor. En hoppingivande lösning Ă€r att tillverka kolvĂ€ten frĂ„n förnybara kĂ€llor, vilket minimerar miljöpĂ„verkan och de höga kostnaderna för alternativ grön teknik. Lignin anses vara en lovande kĂ€lla till material och biobrĂ€nslen, eftersom det kan omvandlas till vĂ€rdefulla produkter genom olika termokemiska processer. För att fĂ„ flytande kolvĂ€ten mĂ„ste lignin genomgĂ„ pyrolys, vilket resulterar i bioolja, som i sin tur krĂ€ver ytterligare uppgradering pĂ„ grund av dess lĂ„ga vĂ€rmevĂ€rde, höga viskositet och surhet. Hydrodeoxygenering kan anvĂ€ndas för att avlĂ€gsna syregrupperna och erhĂ„lla kolvĂ€ten som Ă€r kompatibla med den befintliga infrastrukturen. I detta arbete undersöktes hydrodeoxygenering av isoeugenol, en ligninbaserad modellförening, med olika bifunktionella katalysatorer i bĂ„de satsreaktorer och kontinuerliga reaktorer. En serie bimetalliska platina-rhenium-katalysatorer pĂ„ mesoporöst och aktivt kol studerades, i syfte att undersöka de bĂ„da metallernas roll i hydrogenering och i deoxygenering. Det visade sig att en högre rheniumhalt, med större antal syresĂ€ten, resulterade i förbĂ€ttrad deoxygeneringsaktivitet. Det var möjligt att uppnĂ„ full omsĂ€ttningsgrad av isoeugenol med 90% deoxygenering i en kontinuerlig reaktor vid 200 °C. För första gĂ„ngen utfördes studier med industriellt efterliknande katalysatorer, bĂ„de i pulverform och i extrudatform med platina som den aktiva metallen, zeolitbeta som bĂ€rarmaterial samt ett bindemedel. Studierna innehöll dessutom eventuell uppskalning för en ligninbaserad modellförening i satsreaktorer och kontinuerliga reaktorer. Effekterna av bindemedelstillsatsen, platinaplaceringen och zeolitens surhet utvĂ€rderades för pulverkatalysatorn, medan effekterna av platinaplaceringen och reaktionstemperaturen studerades för extrudaten. Tillsatsen av bindemedel resulterade i en förminskad ytarea, total porvolym och surhet. Det visade sig att katalysatorerna som innehöll den mer sura zeoliten (H-Beta-25) hade bĂ€ttre katalytisk prestanda (ca 80% omsĂ€ttningsgrad och över 50% utbyte av den deoxygenerade produkten) jĂ€mfört med andra zeoliter. Placeringen av platina pĂ„verkade de katalytiska resultaten. Det pĂ„visades att platina belĂ€get nĂ€ra surasĂ€ten förbĂ€ttrade aktiviteten med ca 20% jĂ€mfört med platina deponerat pĂ„ bindemedlet. Extrudaten visade god stabilitet, med bara 10% minskning av katalytisk aktivitet efter 30 timmars drift. MassöverföringsbegrĂ€nsningar pĂ„visades av en effektivitetsfaktor pĂ„ 0,17 och en aktiveringsenergi pĂ„ 14,7 kJ/mol. En hög omsĂ€ttningsgrad (100%) och ett betydande utbyte av deoxygenerade produkter (80%) erhölls vid 200 ÂșC med de industriellt efterliknande katalysatorerna

    Computational Analyses of Metagenomic Data

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    Metagenomics studies the collective microbial genomes extracted from a particular environment without requiring the culturing or isolation of individual genomes, addressing questions revolving around the composition, functionality, and dynamics of microbial communities. The intrinsic complexity of metagenomic data and the diversity of applications call for efficient and accurate computational methods in data handling. In this thesis, I present three primary projects that collectively focus on the computational analysis of metagenomic data, each addressing a distinct topic. In the first project, I designed and implemented an algorithm named Mapbin for reference-free genomic binning of metagenomic assemblies. Binning aims to group a mixture of genomic fragments based on their genome origin. Mapbin enhances binning results by building a multilayer network that combines the initial binning, assembly graph, and read-pairing information from paired-end sequencing data. The network is further partitioned by the community-detection algorithm, Infomap, to yield a new binning result. Mapbin was tested on multiple simulated and real datasets. The results indicated an overall improvement in the common binning quality metrics. The second and third projects are both derived from ImMiGeNe, a collaborative and multidisciplinary study investigating the interplay between gut microbiota, host genetics, and immunity in stem-cell transplantation (SCT) patients. In the second project, I conducted microbiome analyses for the metagenomic data. The workflow included the removal of contaminant reads and multiple taxonomic and functional profiling. The results revealed that the SCT recipients' samples yielded significantly fewer reads with heavy contamination of the host DNA, and their microbiomes displayed evident signs of dysbiosis. Finally, I discussed several inherent challenges posed by extremely low levels of target DNA and high levels of contamination in the recipient samples, which cannot be rectified solely through bioinformatics approaches. The primary goal of the third project is to design a set of primers that can be used to cover bacterial flagellin genes present in the human gut microbiota. Considering the notable diversity of flagellins, I incorporated a method to select representative bacterial flagellin gene sequences, a heuristic approach based on established primer design methods to generate a degenerate primer set, and a selection method to filter genes unlikely to occur in the human gut microbiome. As a result, I successfully curated a reduced yet representative set of primers that would be practical for experimental implementation

    On the Generation of Realistic and Robust Counterfactual Explanations for Algorithmic Recourse

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    This recent widespread deployment of machine learning algorithms presents many new challenges. Machine learning algorithms are usually opaque and can be particularly difficult to interpret. When humans are involved, algorithmic and automated decisions can negatively impact people’s lives. Therefore, end users would like to be insured against potential harm. One popular way to achieve this is to provide end users access to algorithmic recourse, which gives end users negatively affected by algorithmic decisions the opportunity to reverse unfavorable decisions, e.g., from a loan denial to a loan acceptance. In this thesis, we design recourse algorithms to meet various end user needs. First, we propose methods for the generation of realistic recourses. We use generative models to suggest recourses likely to occur under the data distribution. To this end, we shift the recourse action from the input space to the generative model’s latent space, allowing to generate counterfactuals that lie in regions with data support. Second, we observe that small changes applied to the recourses prescribed to end users likely invalidate the suggested recourse after being nosily implemented in practice. Motivated by this observation, we design methods for the generation of robust recourses and for assessing the robustness of recourse algorithms to data deletion requests. Third, the lack of a commonly used code-base for counterfactual explanation and algorithmic recourse algorithms and the vast array of evaluation measures in literature make it difficult to compare the per formance of different algorithms. To solve this problem, we provide an open source benchmarking library that streamlines the evaluation process and can be used for benchmarking, rapidly developing new methods, and setting up new experiments. In summary, our work contributes to a more reliable interaction of end users and machine learned models by covering fundamental aspects of the recourse process and suggests new solutions towards generating realistic and robust counterfactual explanations for algorithmic recourse

    A Trojan horse route to emergent active and stable platinum nanoparticles from a perovskite system

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    Platinum (Pt), generally dispersed on a solid oxide support, has been widely used for catalytic chemical reactions in automobile, petroleum and energy industries. During the reactions, Pt is exposed to severe conditions, for example, heat and impurities, that cause Pt agglomeration and poisoning, respectively, resulting in activity/stability decrease. Here, perovskite materials are designed with Pt for significant catalytic properties through novel doping and exsolution methods. Perovskite structured materials (ABO₃) are selected because these are basically stable at heat and redox environments with coke/sulfur resistances at the catalytic or electrochemical conditions. When perovskite oxides are employed as supporting frameworks, certain catalysts like Pt can be incorporated as cations on the B site of the perovskite lattice under oxidizing conditions (doping). By tailoring the stoichiometry of the doped perovskite materials, the dopants can be partly exsolved as nanoparticles (NP) on subsequent reductions, which provides the possibility of the in situ growth of NP (emergence). This method can improve the catalytic property of Pt by less loading, proper size, high dispersion, unique active sites and strong bonding structure with the perovskite. Because only a few studies have been carried out due to the difficulty in the handling of Pt, the goal is to develop an innovative Pt perovskite catalyst to use in various catalytic applications."Thank you to the EPSRC for an industrial CASE scholarship with Johnson Matthey."--Acknowledgement

    Integrating forecasting in metaheuristic methods to solve dynamic routing problems: evidence from the logistic processes of tuna vessels

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    The multiple Traveling Salesman Problem (mTSP) is a widespread phenomenon in real-life scenarios, and in fact it has been addressed from multiple perspectives in recent decades. However, mTSP in dynamic circumstances entails a greater complexity that recent approaches are still trying to grasp. Beyond time windows, capacity and other parameters that characterize the dynamics of each scenario, moving targets is one of the underdeveloped issues in the field of mTSP. The approach of this paper harnesses a simple prediction method to prove that integrating forecasting within a metaheuristic evolutionary-based method, such as genetic algorithms, can yield better results in a dynamic scenario than their simple non-predictive version. Real data is used from the retrieval of Fish Aggregating Devices (FADs) by tuna vessels in the Indian Ocean. Based on historical data registered by the GPS system of the buoys attached to the devices, their trajectory is firstly forecast to feed subsequently the functioning of a genetic algorithm that searches for the optimal route of tuna vessels in terms of total distance traveled. Thus, although valid for static cases and for the Vehicle Routing Problem (VRP), the main contribution of this method over existing literature lies in its application as a global search method to solve the multiple TSP with moving targets in many dynamic real-life optimization problems.Ministerio de EconomĂ­a y Competitividad | Ref. ECO2016-76625-RXunta de Galicia | Ref. GRC2014/02

    Algorithms and complexity for approximately counting hypergraph colourings and related problems

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    The past decade has witnessed advancements in designing efficient algorithms for approximating the number of solutions to constraint satisfaction problems (CSPs), especially in the local lemma regime. However, the phase transition for the computational tractability is not known. This thesis is dedicated to the prototypical problem of this kind of CSPs, the hypergraph colouring. Parameterised by the number of colours q, the arity of each hyperedge k, and the vertex maximum degree Δ, this problem falls into the regime of LovĂĄsz local lemma when Δ â‰Č qᔏ. In prior, however, fast approximate counting algorithms exist when Δ â‰Č qᔏ/Âł, and there is no known inapproximability result. In pursuit of this, our contribution is two-folded, stated as follows. ‱ When q, k ≄ 4 are evens and Δ ≄ 5·qᔏ/ÂČ, approximating the number of hypergraph colourings is NP-hard. ‱ When the input hypergraph is linear and Δ â‰Č qᔏ/ÂČ, a fast approximate counting algorithm does exist

    Order and Change in Art: Towards an Active Inference Account of Aesthetic Experience

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    How to account for the power that art holds over us? Why do artworks touch us deeply, consoling, transforming or invigorating us in the process? In this paper, we argue that an answer to this question might emerge from a fecund framework in cognitive science known as predictive processing (a.k.a. active inference). We unpack how this approach connects sense-making and aesthetic experiences through the idea of an ‘epistemic arc’, consisting of three parts (curiosity, epistemic action and aha experiences), which we cast as aspects of active inference. We then show how epistemic arcs are built and sustained by artworks to provide us with those satisfying experiences that we tend to call ‘aesthetic’. Next, we defuse two key objections to this approach; namely, that it places undue emphasis on the cognitive component of our aesthetic encounters—at the expense of affective aspects—and on closure and uncertainty minimization (order)—at the expense of openness and lingering uncertainty (change). We show that the approach offers crucial resources to account for the open-ended, free and playful behaviour inherent in aesthetic experiences. The upshot is a promising but deflationary approach, both philosophically informed and psychologically sound, that opens new empirical avenues for understanding our aesthetic encounters. This article is part of the theme issue ‘Art, aesthetics and predictive processing: theoretical and empirical perspectives’
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