Faculty of Science (Research Outputs)

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Start date: 2020Subject: search.filters.subject.SDG-17: Partnerships for the goals

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    Batch and semi-continuous fermentation with Parageobacillus thermoglucosidasius DSM 6285 for H2 production
    (BMC, 2025) de Maayer, Pieter; Ardila, Magda S.; Aliyu, Habibu; Neumann, Anke
    Background Parageobacillus thermoglucosidasius is a facultatively anaerobic thermophile that is able to produce hydrogen (H2) gas from the oxidation of carbon monoxide through the water–gas shift reaction when grown under anaerobic conditions. The water–gas shift (WGS) reaction is driven by a carbon monoxide dehydrogenase– hydrogenase enzyme complex. Previous experiments exploring hydrogenogenesis with P. thermoglucosidasius have relied on batch fermentations comprising defned media compositions and gas atmospheres. This study evaluated the efects of a semi-continuous feeding strategy on hydrogenogenesis. Results A batch and two semi-continuous fermentations, with feeding of the latter fresh media (with glucose) in either 24 h or 48 h intervals were undertaken and H2 production, carbon monoxide dehydrogenase (CODH) activity, and metabolite consumption/production were monitored throughout. Maximum H2 production rates (HPR) of 0.14 and 0.3 mmol min−1, were observed for the batch and the semi-continuous fermentations, respectively. Daily feeding attained stable H2 production for 7 days, while feeding every 48 h resulted in high variations in H2 production. CODH enzyme activity correlated with H2 production, with a maximum of 1651 U mL−1 on day 14 with the 48 h feeding strategy, while CODH activity remained relatively constant throughout the fermentation process with the 24 h feeding strategy. Conclusions The results emphasize the signifcance of a semi-continuous glucose-containing feed for attaining stable hydrogen production with P. thermoglucosidasius. The semi-continuous fermentations achieved a 46% higher HPR than the batch fermentation. The higher HPRs achieved with both semi-continuous fermentations imply that this approach could enhance the biohydrogen platform. However, optimizing the feeding interval is pivotal to ensuring stable hydrogen production.
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    New modern and Pleistocene fossil micromammal assemblages from Swartkrans, South Africa: Paleobiodiversity, taphonomic, and environmental context
    (Elsevier, 2024-03) Steininger, Christine; Clarke, Ronald J.; Caruana, Matthew V.; Kuman, Kathleen; Pickering, Travis Rayne; Linchamps, Pierre; Stoetzel, Emmanuelle; Amberny, Laurie
    The oldest deposit at the hominin-bearing cave of Swartkrans, South Africa, is the Lower Bank of Member 1, dated to ca. 2.2 million years ago. Excavations of this unit have produced a diverse and extensive mammalian fossil record, including Paranthropus robustus and early Homo fossils, along with numerous Oldowan stone tools. The present study focuses on the taxonomic analysis of the micromammalian fossil assemblage obtained from recent excavations of the Lower Bank, conducted between 2005 and 2010, as part of the Swartkrans Paleoanthropological Research Project. The taxonomic composition of this assemblage is dominated by Mystromys, a rodent indicative of grassland environments. Taphonomic analysis indicates an accumulation of prey by Tyto alba (Barn owl) or a related species. Environments inferred from this evidence reflect an open landscape primarily covered by grassland vegetation, but they also feature components of wooded areas, rocky outcrops, and the proximity of a river. The Swartkrans fossil assemblage is compared with Cooper's D (dated to ca. 1.4 Ma) and a modern coprocoenosis of Bubo africanus (spotted eagle-owl) collected within the Swartkrans cave for taxonomic, taphonomic, and paleoecological perspectives. Contrasting fossil and modern micromammalian data provide a better understanding of accumulation processes and facilitate a diachronic reconstruction of changes in climate and landscape evolution. Issues regarding paleoenvironmental reconstruction methodologies based on micromammals are also discussed.
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    Accurate hyperspectral imaging of mineralised outcrops: An example from lithium-bearing pegmatites at Uis, Namibia
    (Elsevier Inc, 2021) Booysen, René; Nex, Paul A.M.; Lorenz, Sandra; Thiele, Samuel T.; Fuchsloch, Warrick C.; Marais, Timothy; Gloaguen, Richard
    Efficient, socially acceptable and rapid methods of exploration are required to discover new deposits and enable the green energy transition. Sustainable exploration requires a combination of innovative thinking and new technologies. Hyperspectral imaging (HSI) is a rapidly developing technology and allows for fast and systematic mineral mapping, facilitating exploration of the Earth’s surface at various scales on a variety of platforms. Newly available sensors allow data capture over a wide spectral range, and provide information about the abundance and spatial location of ore and pathfinder minerals in drill-core, hand samples and outcrops with mm to cm precision. Conversely, the complex geometries of the imaged surfaces affect the spectral quality and signal-to-noise ratio (SnR) of HSI data at these very narrow spatial samplings. Additionally, the complex mineral assemblages found in hydrothermally altered ore deposits can make interpretation of spectral results a challenge. In this contribution, we propose an innovative approach that integrates multiple sensors and scales of data acquisition to help disentangle complex mineralogy associated with lithium and tin mineralisation in the Uis pegmatite complex, Namibia. We train this method using hand samples and finally produce a three-dimensional (3D) point cloud for mapping lithium mineralisation in the open pit. We were able to identify and map lithium-bearing cookeite and montebrasite at outcrop scale. The accuracy of the approach was validated by drill-core data, XRD analysis and LIBS measurements. This approach facilitates efficient mapping of complex terrains, as well as important monitoring and optimisation of ore extraction. Our method can easily be adapted to other minerals relevant to the mining industry.
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    Detection of REEs with lightweight UAV‑based hyperspectral imaging
    (Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations., 2020) Booysen, René; Nex, Paul A.M.; Zimmermann, Robert; Loren, Sandra; Kirsch, Moritz; Jackish, Robert; Gloaguen, Richard
    Rare earth elements (REEs) supply is important to ensure the energy transition, e-mobility and ultimately to achieve the sustainable development goals of the United Nations. Conventional exploration techniques usually rely on substantial geological field work including dense in-situ sampling with long delays until provision of analytical results. However, this approach is limited by land accessibility, financial status, climate and public opposition. Efficient and innovative methods are required to mitigate these limitations. The use of lightweight unmanned aerial vehicles (UAVs) provides a unique opportunity to conduct rapid and non-invasive exploration even in socially sensitive areas and in relatively inaccessible locations. We employ drones with hyperspectral sensors to detect REEs at the earth’s surface and thus contribute to a rapidly evolving field at the cutting edge of exploration technologies. We showcase for the first time the direct mapping of REEs with lightweight hyperspectral UAV platforms. Our solution has the advantage of quick turn-around times (< 1 d), low detection limits (< 200 ppm for Nd) and is ideally suited to support exploration campaigns. This procedure was successfully tested and validated in two areas: Marinkas Quellen, Namibia, and Siilinjärvi, Finland. This strategy should invigorate the use of drones in exploration and for the monitoring of mining activities.
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    Geological Remote Sensing
    (Acdemic Press, United Kingdom, 2021) Booysen, René; Nex, Paul A.M.; Gloaguen, Richard; Lorenz, Sandra; Zimmermann, Robert; Alderton, David; Elias, Scott A.
    The field of remote sensing has recently witnessed major innovations that have been translated to Earth science applications. Before they can be used, remote sensing data must be corrected for effects originating from the sensors, the platforms on which they are deployed, atmospheric characteristics, and geometrical constraints. When the data are calibrated and geolocated, they can be used either as physical quantities, such as reflectance and temperatures, or as images. The recent development of new sensors has permitted the remote measurement of a large area of the Earth's surface, with direct geological applications. Additionally, advances in machine vision, machine learning and artificial intelligence, combined with an unprecedented increase in computer processing power, have led to innovative remote sensing data processing techniques that simplify the handling of large amounts of complex data. As a consequence, it is now possible to characterize the geological settings of large areas with precision and even their changes through time. Remote sensing data are now directly integrated into modelling algorithms that describe surface and subsurface processes at different scales. Geological remote sensing currently encompasses multi temporal, multi-source and multi scale approaches. The retrieval of big data in disseminated archives, as well as (near) real time processing are the challenges that remain to be solved. These new applications in geology ensure cost efficient, safe, and rapid surveys and monitoring that not only benefit the research community but society at large.