http://bura.brunel.ac.uk/handle/2438/28596 Sat, 04 Apr 2026 00:22:55 GMT 2026-04-04T00:22:55Z http://bura.brunel.ac.uk/handle/2438/32339 Title: Engineering biomass combustion fly-ash derived zeolites for post-combustion CO₂ capture Authors: Petrovic, Ben A. Abstract: Mitigation of CO₂ emissions through the use of carbon removal technologies is widely recognised as a pivotal tool on the path to net-zero GHG emissions. Beyond these targets, net-negative emissions will be essential to stabilise global temperatures. Technologies such as bioenergy with carbon capture and storage, considered a net-negative emission technology is therefore poised for a significant share in the power generation mix. However, this is associated with the production of a significant quantity of waste ash residues such as fly ash. Valorisation of this waste stream provides an opportunity to simultaneously mitigate the requirement for waste disposal (i.e. landfilling) and provide a pathway to value-added products, zeolites. In this thesis, industrially produced biomass combustion fly ashes have been comprehensively characterised and subsequently investigated for their potential as zeolite precursors. Suitable design of experiment techniques have been employed to systematically assess the influence of various factors on the alkaline fusion assisted hydrothermal synthesis to maximise the CO₂ equilibrium adsorption capacity. The bulk biomass combustion fly ash has been shown to present a CO₂ adsorption capacity of over 1.8 mmol·g⁻¹ at 50 °C and 1 bar, with a stable capacity of 87% of that after 40 cycles. This adsorbent was then produced at a larger scale to facilitate breakthrough performance assessments in a fixed-bed temperature swing adsorption system designed and built during this research. The process was optimised via Taguchi design of experiment to reveal the influential factors on the bed utilisation efficiency. The results indicate a usable bed capacity of approximately 0.6 mmol·g⁻¹ corresponding to a bed utilisation efficiency of 62% under the optimal factor and level configuration. These findings underscore the feasibility of industrial biomass combustion fly ashes as feedstocks in the preparation of zeolitic adsorbents/catalyst for post-combustion CO₂ capture. Description: This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London Mon, 01 Jan 2024 00:00:00 GMT http://bura.brunel.ac.uk/handle/2438/32339 2024-01-01T00:00:00Z http://bura.brunel.ac.uk/handle/2438/31895 Title: Improving resilience in chemical plant under cyberattack by adversarial reinforcement learning Authors: Smith, Martyn Abstract: With chemical plant contributing $5.4 trillion to the global economy annually, frequently representing a Major Accident Hazard, and their control systems having an average age of 20 years, the prospect of a cyberattack resulting in full or partial breach by threat actors is of great concern to owners, customers and wider stakeholders (the latter frequently including anyone downwind). A great deal of frameworks to deal with this threat exist, including multiple uses of Machine Learning (ML). However, these only go as far as the detection of cyberattacks, leaving a research gap in automated responses or the use of ML agents to both generate novel threat vectors and respond to them. In this thesis, we cover some historical attacks and incidents involving chemical plant and their impacts, and what existing Laws and frameworks already cover how plant safety and cybersecurity should be considered. We then investigate the use of adversarial Reinforcement Learning (RL) for both generating and identifying threat vectors, then detecting and responding to intrusions of chemical plant. To address this gap, we have developed a customised version of the Tennessee Eastman process as example, suitable for use with existing interfaces for training RL agents. We then trialled this with a benchmark suite of test scenarios using different agents, one defending the plant (“Blue Team”) and one attacking the plant (“Red Team”), mimicking a common operational cybersecurity challenge. These agents were implemented with Deep Q learning and Deep Deterministic Policy Gradient algorithms dependent on the scenario, in order to model different Blue Team and Red Team capabilities, with Deep Deterministic Policy Gradient agents having Continuous manipulation of plant variables available. We additionally implemented a variant where the Blue Team was assisted with a digital twin in order to make enhanced predictions of future plant state, and scenarios which varied the Red Team’s goals, with the default being plant shutdown. The Blue Team learnt passive policies during periods of normal plant operation, so that it would not disrupt the plant. The Red Team was primarily effective at achieving its aims, most commonly producing a plant shutdown in slightly under three minutes by inducing an oscillation in reactor pressure, usually by manipulating both setpoints and sensor readings. Deep Q learning variants of the Red Team could also disrupt the plant, sometimes in as little as 25 seconds. This behaviour was, however, independent of the Red Team’s goals. When combined, the Red Team consistently performed well, with the Blue Team only occasionally extending plant uptime. The testbed developed is extensible for further testing against future Blue Team or Red Team agent implementations, however it is likely to require additional theoretical verification in order to be employed on plant. Observed behaviour such as the reactor pressure oscillation observed could be seen as Indicator of Compromise, as could a divergence between the Digtal Twin and physical plant before failure observed in the digital twin assisted version - these indicators would prove of immense value to Security Operations Centre operatives looking to safeguard a real plant. Description: This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London Wed, 01 Jan 2025 00:00:00 GMT http://bura.brunel.ac.uk/handle/2438/31895 2025-01-01T00:00:00Z http://bura.brunel.ac.uk/handle/2438/31493 Title: Synthesis and application of recycled carbon fibre-based adsorbents for the removal of antibiotics from freshwater aquaculture environments Authors: Taylor, Jessica H. Abstract: The growing environmental impact of end-of-life carbon fibre composites and the rising use of antibiotics in aquaculture present two critical sustainability challenges. Carbon fibre reinforced polymers, widely used in aerospace and automotive industries, generate significant waste. While aquaculture is a major source of pharmaceutical pollution. Antibiotics such as ciprofloxacin and oxytetracycline are commonly used in fish farming and have been linked to the emergence of antimicrobial resistance in aquatic environments. This research aimed to develop high-performance, sustainable carbon-based adsorbents using recycled carbon fibres recovered from Carbon fibre reinforced polymer waste, and to optimise their use for the removal of ciprofloxacin and oxytetracycline from water. A systematic approach was applied to optimise each stage of the adsorbent development process including chemical activation, surface modification, adsorption, and regeneration. Design of Experiments techniques were used to identify optimum process parameters. Initial testing with sodium hydroxide-activated recycled carbon fibres yielded low adsorption capacities (16.84 mg/g for methylene blue), indicating incomplete activation. Process optimisation employing potassium hydroxide significantly improved adsorbent performance. The optimum conditions were identified as an activation temperature of 670 °C, impregnation ratio of 1:10 (CF:KOH) and hold time of 0.5 h, achieving methylene blue adsorption capacities above 450 mg/g and yields exceeding 70%. Surface-modified samples utilising 10 M nitirc acid, 16 h contact time at 28 °C, resulted in increased acidity and mesoporosity. However, it was found that additional modification was not essential to maintain high antibiotic removal. Optimised adsorption conditions were identified to be an adsorbent dose of 0.8 g/L, pH of 2 and initial concentration of 2 mg/L, which resulted in removal efficiencies above 95% for both CIP and OTC. Regeneration studies using 0.1 M potassium hydroxide demonstrated strong reusability, with regeneration efficiencies remaining above 75% over seven cycles. The results confirm that recycled carbon fibre-derived adsorbents are effective, reusable, and environmentally sustainable materials for removing antibiotic contaminants from aquaculture wastewater. Description: This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London Mon, 01 Jan 2024 00:00:00 GMT http://bura.brunel.ac.uk/handle/2438/31493 2024-01-01T00:00:00Z http://bura.brunel.ac.uk/handle/2438/31489 Title: The use of rapid pressure swing adsorption to enhance the design of portable medical oxygen concentrators Authors: Kenny, Callum Abstract: Portable oxygen concentrators are restricted by three main factors: power consumption, weight and output. To minimise the weight and output of a portable oxygen concentrator. This paper investigates how rapid pressure swing adsorption will improve oxygen yield per unit volume of adsorbent. It was observed through experimental data the rapid pressure swing adsorption cycle developed in this research could achieve a throughput of 50 sccm, using adsorbent Zeox Z12-49, in one 6.4mm diameter column of 140mm in length, which is a four times improvement when compared to leading market devices. Description: This thesis was submitted for the award of Master of Philosophy and was awarded by Brunel University London Mon, 01 Jan 2024 00:00:00 GMT http://bura.brunel.ac.uk/handle/2438/31489 2024-01-01T00:00:00Z