<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>BURA Collection:</title>
    <link>http://bura.brunel.ac.uk/handle/2438/25431</link>
    <description />
    <pubDate>Sat, 27 Jun 2026 02:20:21 GMT</pubDate>
    <dc:date>2026-06-27T02:20:21Z</dc:date>
    <item>
      <title>Synthesis of a novel adsorbent-photocatalytic material using a low energy route and its application to the remediation of water from contamination of 17-α ethinyl estradiol</title>
      <link>http://bura.brunel.ac.uk/handle/2438/33512</link>
      <description>Title: Synthesis of a novel adsorbent-photocatalytic material using a low energy route and its application to the remediation of water from contamination of 17-α ethinyl estradiol
Authors: Todd, Angeli Grace
Abstract: Endocrine-disrupting compounds such as 17α-ethinylestradiol (EE2) pose significant risks to aquatic ecosystems and human health, necessitating the development of advanced water purification materials. This thesis presents the synthesis and characterization of a novel composite coating of hydroxyapatite (HAP) and titanium dioxide (TiO₂) applied to hollow glass microspheres (HGMs) for the efficient removal of EE2 from aqueous systems. The composite was fabricated via a sol-gel assisted deposition method, leveraging the high surface area of HGMs and the complementary adsorption–photocatalytic properties of HAP and TiO₂. Comprehensive material characterization was performed using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), and atomic force microscopy (AFM) to confirm morphological, structural, and functional properties of the composite. Surface area and porosity were evaluated through BET N₂ adsorption isotherms. EE2 degradation and residual concentrations were quantified through high-performance liquid chromatography (HPLC) and liquid chromatography–mass spectrometry (LC-MS). The composite coatings demonstrated superior adsorption–photocatalytic performance compared to individual HAP and TiO₂ coatings, attributed to synergistic interactions that enhanced EE2 binding and photodegradation efficiency. &#xD;
Kinetic analysis revealed rapid removal rates, while repeated use confirmed the composite’s structural stability and reusability. Notably, the composite materials outperformed the current industry standard – activated carbon – in both removal efficiency and overall cost-effectiveness under comparable experimental conditions. These findings underscore the potential of hydroxyapatite–TiO₂ composites as next-generation materials for sustainable water purification, offering a promising strategy to mitigate emerging contaminants in aquatic environments.
Description: This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London</description>
      <pubDate>Thu, 01 Jan 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://bura.brunel.ac.uk/handle/2438/33512</guid>
      <dc:date>2026-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>The self-healing mechanisms of bacterial cementitious materials via novel isolated ureolytic bacterium species</title>
      <link>http://bura.brunel.ac.uk/handle/2438/32411</link>
      <description>Title: The self-healing mechanisms of bacterial cementitious materials via novel isolated ureolytic bacterium species
Authors: Yousef, Wasef
Abstract: The self-healing approach used in this study is based on the urease hydrolysing bacterium, namely, Bacillus Sphaericus. The scope of the work is diverse as it combines and brings together both aspects of the bioengineering and civil engineering in order to provide better understanding of the self-healing mechanisms that lie behind the yielding of the calcium carbonate precipitation. The initial stage of this study, comprised of collecting different soil samples from different alkaline sources to extract and isolate urease bacterium species. In addition, a collection of more than 100 different bacterial strains belong to bacillus Sphaericus were screened for the presence of urease enzyme and ability to produce copious amount of calcium carbonate under extreme alkaline conditions. &#xD;
In-vitro calcium carbonate precipitation experiments were performed to stress the selected bacterial strains prior to the application for the self-healing mortar. Parameters such as temperature, pH, shaking conditions, ability to form endospores and the production of copious amount of calcium carbonate were placed under scrutiny. The biochemical properties of the selected bacterial strain were studied and investigated further by monitoring the evolution in pH, the production of ammonium, insoluble and soluble calcium and the colony forming unit. Following the characterisation, three strains were promoted forward for the use of self-healing mortar. &#xD;
In-vitro calcium carbonate perception in broth state showed that the yielding of CaCO3 was maximum in the case of strain 89 and strain 67 at 0.5932g/100ml and 0.8398 g/100ml, respectively. &#xD;
The need for an encapsulating material that provides suitable environment for the bacteria to endure the mechanical and physical forces in addition to the high alkaline environment of the cement matrix, is indeed a key component towards the self-healing applications. As a result, the autoclaved aerated recycled concrete (AAC) aggregates were selected for this study, due to the high porous structure which implies high absorption properties. Three healing systems were proposed for the application of the self-healing mortar. The first approach comprises of bacterial spores impregnated under vacuum into the AARC aggregates along with a suitable nutrient designed specifically for maximum yielding of calcium carbonate precipitation. The second approach comprised of a three-component healing system with the introduction of a mixed culture to enhance the healing capacity in addition to providing reinforcement for the cement matrix. The third approach comprised of direct incorporation of different bacterial cells into cement mortar to test for the capacity of the strain to heal cracks under high alkaline environment. &#xD;
Mortar specimens were cracked at 28 days of curing, ranging from 0.127 to 0.875mm, the introduction of the three-healing system provided promising results in regard to healing cracks of 0.875mm over the period of 289 days of curing. Direct incorporation of bacterial strains at different concentrations 107cells/ml and 108cells/ml showed the tendency to heal cracks of 0.127 and 0.253mm, respectively. &#xD;
Furthermore, direct incorporation of bacterial cells into the cement matrix, supported the analysis that urea hydrolysing bacteria is indeed an enzymatic activity. Two key enzymes were defined and strongly linked to the calcium carbonate precipitation process that is the urease enzyme and the carbonic anhydrase enzyme, where the latter is a zinc enzyme that catalyses the conversion of calcium dioxide into carbonate acid and ultimately promotes further insoluble calcium carbonate precipitation.  &#xD;
The introduction of a three-component healing system showed enhanced healing capacity, Direct Incorporation of 107cells/ml with 30% impregnated aggregates showed the capacity to partially heal cracks of 0.791mm by 28.3% over 14 days and 100% over 28 days healing period. Increasing the number of cells showed expected higher healing efficiency, specimens in set 22.1B were able to completely seal cracks of 0.875mm by 99.085 % over the period of 28 days.
Description: This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London</description>
      <pubDate>Wed, 01 Jan 2020 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://bura.brunel.ac.uk/handle/2438/32411</guid>
      <dc:date>2020-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Engineering biomass combustion fly-ash derived zeolites for post-combustion CO₂ capture</title>
      <link>http://bura.brunel.ac.uk/handle/2438/32339</link>
      <description>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&#xD;
pivotal tool on the path to net-zero GHG emissions. Beyond these targets, net-negative emissions will&#xD;
be essential to stabilise global temperatures. Technologies such as bioenergy with carbon capture and&#xD;
storage, considered a net-negative emission technology is therefore poised for a significant share in the&#xD;
power generation mix. However, this is associated with the production of a significant quantity of waste&#xD;
ash residues such as fly ash. Valorisation of this waste stream provides an opportunity to simultaneously&#xD;
mitigate the requirement for waste disposal (i.e. landfilling) and provide a pathway to value-added&#xD;
products, zeolites. In this thesis, industrially produced biomass combustion fly ashes have been&#xD;
comprehensively characterised and subsequently investigated for their potential as zeolite precursors.&#xD;
Suitable design of experiment techniques have been employed to systematically assess the influence of&#xD;
various factors on the alkaline fusion assisted hydrothermal synthesis to maximise the CO₂ equilibrium&#xD;
adsorption capacity. The bulk biomass combustion fly ash has been shown to present a CO₂ adsorption&#xD;
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.&#xD;
This adsorbent was then produced at a larger scale to facilitate breakthrough performance assessments&#xD;
in a fixed-bed temperature swing adsorption system designed and built during this research. The process&#xD;
was optimised via Taguchi design of experiment to reveal the influential factors on the bed utilisation&#xD;
efficiency. The results indicate a usable bed capacity of approximately 0.6 mmol·g⁻¹ corresponding to&#xD;
a bed utilisation efficiency of 62% under the optimal factor and level configuration. These findings&#xD;
underscore the feasibility of industrial biomass combustion fly ashes as feedstocks in the preparation of&#xD;
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</description>
      <pubDate>Mon, 01 Jan 2024 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://bura.brunel.ac.uk/handle/2438/32339</guid>
      <dc:date>2024-01-01T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Improving resilience in chemical plant under cyberattack by adversarial reinforcement learning</title>
      <link>http://bura.brunel.ac.uk/handle/2438/31895</link>
      <description>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&#xD;
a Major Accident Hazard, and their control systems having an average age of 20 years, the&#xD;
prospect of a cyberattack resulting in full or partial breach by threat actors is of great concern to&#xD;
owners, customers and wider stakeholders (the latter frequently including anyone downwind).&#xD;
A great deal of frameworks to deal with this threat exist, including multiple uses of Machine&#xD;
Learning (ML). However, these only go as far as the detection of cyberattacks, leaving a research&#xD;
gap in automated responses or the use of ML agents to both generate novel threat vectors and&#xD;
respond to them.&#xD;
In this thesis, we cover some historical attacks and incidents involving chemical plant and their&#xD;
impacts, and what existing Laws and frameworks already cover how plant safety and cybersecurity&#xD;
should be considered. We then investigate the use of adversarial Reinforcement Learning (RL)&#xD;
for both generating and identifying threat vectors, then detecting and responding to intrusions of&#xD;
chemical plant.&#xD;
To address this gap, we have developed a customised version of the Tennessee Eastman process&#xD;
as example, suitable for use with existing interfaces for training RL agents. We then trialled&#xD;
this with a benchmark suite of test scenarios using different agents, one defending the plant (“Blue&#xD;
Team”) and one attacking the plant (“Red Team”), mimicking a common operational cybersecurity&#xD;
challenge. These agents were implemented with Deep Q learning and Deep Deterministic Policy&#xD;
Gradient algorithms dependent on the scenario, in order to model different Blue Team and Red&#xD;
Team capabilities, with Deep Deterministic Policy Gradient agents having Continuous manipulation&#xD;
of plant variables available. We additionally implemented a variant where the Blue Team was&#xD;
assisted with a digital twin in order to make enhanced predictions of future plant state, and scenarios&#xD;
which varied the Red Team’s goals, with the default being plant shutdown.&#xD;
The Blue Team learnt passive policies during periods of normal plant operation, so that it would&#xD;
not disrupt the plant. The Red Team was primarily effective at achieving its aims, most commonly&#xD;
producing a plant shutdown in slightly under three minutes by inducing an oscillation in reactor&#xD;
pressure, usually by manipulating both setpoints and sensor readings. Deep Q learning variants of&#xD;
the Red Team could also disrupt the plant, sometimes in as little as 25 seconds. This behaviour&#xD;
was, however, independent of the Red Team’s goals. When combined, the Red Team consistently&#xD;
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&#xD;
agent implementations, however it is likely to require additional theoretical verification in order to&#xD;
be employed on plant. Observed behaviour such as the reactor pressure oscillation observed could&#xD;
be seen as Indicator of Compromise, as could a divergence between the Digtal Twin and physical&#xD;
plant before failure observed in the digital twin assisted version - these indicators would prove of&#xD;
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</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://bura.brunel.ac.uk/handle/2438/31895</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
    </item>
  </channel>
</rss>

