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Uncovering the PET-Degrading Potential of Mangrove-Derived Microbial Communities from the Red Sea
No full textMicroplastic pollution has emerged as a global concern due to its widespread distribution. Mangrove ecosystems, in particular, have been reported to accumulate microplastics within their sediments. Although these coastal environments are vulnerable to plastic contamination, they also serve as important reservoirs for isolating microorganisms capable of degrading plastics. Such microbes may offer environmentally sustainable solutions for plastic degradation.
Polyethylene terephthalate (PET) is among the most widely produced synthetic polymers and can be biodegraded by microorganisms through hydrolytic enzymes, including PETase, MHETase, cutinase, and lipase. This enzymatic activity presents a promising biological approach for plastic degradation. However, PET-degrading microorganisms have not been identified in mangrove sediments, especially within the ecologically significant and understudied Red Sea mangrove ecosystems.
This thesis presents the first comprehensive study that integrates microplastic characterization with microbial community profiling in Red Sea mangrove sediments. The findings offer new insights into the potential for natural PET biodegradation in this environment. The research investigates microbial diversity and predicts the enzymatic potential of PET-catabolizing communities in these sediments, with the goal of identifying putative PET-degrading taxa and enzymes.
This study pursued two main objectives. The first objective was to predict plastic-degrading microbial assemblages inhabiting mangrove sediments across three ecological zones: shore, nearshore, and offshore. The second objective was to enrich PET-degrading microbial consortia using PET and cork as sole carbon sources, employing dilution-to-stimulation and artificial selection strategies. By examining microbial diversity, community composition, and enzymatic potential, this research contributes to the development of sustainable, nature-based approaches for mitigating plastic pollution in coastal ecosystems
Optimizing Coarse Grained Arrays on FPGAs Using DSP Primitives
No full textCoarse-Grained Reconfigurable Array (CGRA)s are increasingly recognized as
a compelling architectural solution for accelerating compute-intensive workloads,
offering a balance between the energy efficiency and performance of dedicated
hardware like Application-Specific Integrated Circuit (ASIC)s and the flexibility
of Field-Programmable Gate Array (FPGA)s. However, despite their potential,
existing CGRA architectures often underutilize advanced hardware primitives
available in modern FPGAs, particularly Digital Signal Processing (DSP) blocks
such as the Specific Digital Signal Processing block primitive in AMD/Xilinx
FPGAs (DSP58) primitive. These DSP blocks are highly optimized for arithmetic
and signal processing operations, yet their integration into CGRA Processing
Element (PE)s remains largely unexplored.
In this thesis, we propose an enhanced CGRA architecture by integrating
DSP58 blocks primitives into the PEs of the HyCUBE architecture, a CGRA de-
sign known for its reconfigurable interconnects and computational efficiency. By
replacing traditional arithmetic units in HyCUBE PEs with DSP58 primitives,
the proposed design leverages the inherent parallelism and computational power
of FPGA hardware. Furthermore, pipelining techniques are employed to enhance
data throughput and maximize the operating frequency of the architecture, ad-
dressing key performance bottlenecks in current CGRA designs
Chatty-KG: A Multi-Agent AI System for On-Demand Conversational Question Answering over Knowledge Graphs
No full textConversational Question Answering over Knowledge Graphs (KGs) combines the factual grounding of KG-based QA with the interactive nature of dialogue systems. KGs are widely used in enterprise and domain applications to provide structured, evolving, and reliable knowledge. Large language models (LLMs) enable natural and context-aware conversations, but lack direct access to private and dynamic KGs. Retrieval-augmented generation (RAG) systems can retrieve graph content but often serialize structure, struggle with multi-turn context, and require heavy indexing. Traditional KGQA systems preserve structure but typically support only single-turn QA, incur high latency, and struggle with coreference and context tracking. To address these limitations, we propose Chatty-KG, a modular multi-agent system for conversational QA over KGs. Chatty-KG combines RAG-style retrieval with structured execution by generating SPARQL queries through task-specialized LLM agents. These agents collaborate for contextual interpretation, dialogue tracking, entity and relation linking, and efficient query planning, enabling accurate and low-latency translation of natural questions into executable queries. Experiments on large and diverse KGs show that Chatty-KG significantly outperforms state-of-the-art baselines in both single-turn and multi-turn settings, achieving higher F1 and P@1 scores. Its modular design preserves dialogue coherence and supports evolving KGs without fine-tuning or pre-processing. Evaluations with commercial (e.g., GPT-4o, Gemini-2.0) and open-weight (e.g., Phi-4, Gemma 3) LLMs confirm broad compatibility and stable performance. Overall, Chatty-KG unifies conversational flexibility with structured KG grounding, offering a scalable and extensible approach for reliable multi-turn KGQA
Comprehensive Investigation of Transient Joule-Thomson Cooling and CO2 Hydrate Formation in Depleted Gas Reservoirs
No full textStoring carbon in depleted gas reservoirs is crucial for mitigating global carbon dioxide (CO2) emissions. Injecting high-pressure CO2 into low-pressure reservoirs results in Joule-Thomson (JT) cooling caused by gas expansion. This temperature drop can lead to pore water freezing or the formation of CO2 hydrates, potentially affecting injectivity and compromising well integrity. These processes remain poorly understood due to their complexity and non-linear behavior.
In this study, we present a coupled model that simulates non-isothermal fluid flow, hydrate formation kinetics, and the associated equations of rock properties. We verified this model using both steady-state and transient analytical solutions to analyze the dynamics of pore pressure propagation, thermal fronts, and fluid properties. Our results show that the developed model accurately captures the dynamics of these variables. Furthermore, we validated the model against experimental results, and it effectively predicts the spatial and temporal variations in pore pressure dynamics, both before and after the formation of CO2 hydrates.
We applied the model to a field case (Viking gas reservoir), which has been considered for CO2 storage. We presented field test cases with injection temperatures (Tinj) of 75°C, 50°C, and 25°C . The analysis of the gas reservoir provided critical insights into pressure and temperature evolution, especially under the different injection temperatures for each test case. Notably, when Tinj =25°C, all test cases experienced the formation of CO2 hydrates in the highly permeable layers, significantly affecting pressure gradients both before and after encountering the permeability barrier. Therefore, the developed non-isothermal flow model, which incorporates hydrate formation kinetics, can be utilized in complex heterogeneous and simple homogeneous models to forecast the dynamics of physical processes during the injection of CO2 into depleted reservoirs.Manojkumar Gudala, and Hussein Hoteit thanks for Research Support from King Abdullah University of Science and Technology (KAUST), Saudi Arabia
Influence of organic matter and mineral composition on carbonate source rock wettability: Implications for CO2 geostorage
No full textWettability is critical in determining carbon dioxide (CO2) behavior during geological sequestration in unconventional reservoirs. Unconventional reservoirs are compositionally heterogeneous, affecting CO2 plume migration, containment security, and storage capacity during geological sequestration. Previous studies on CO2 storage in unconventional reservoirs have primarily attributed to changes in organic matter content; however, this study examines how variations in the mineralogical and organic matter content combined affect wettability in CO2/brine systems under subsurface conditions. Three samples with varied mineralogy and TOC content were selected from a well drilled in Jordan source rocks—an immature analog of marine-derived, carbonate-dominated, Type IIS source rocks. Samples were analyzed using RockEval pyrolysis, X-ray diffraction, X-ray fluorescence, and Thermogravimetric analysis to characterize their organic and inorganic compositions. Samples were pyrolyzed at 600 °C to remove Volatile Organic Content (VOC), followed by a Brunauer–Emmett–Teller analysis and contact angle measurements (advancing: θa and receding: θr) via a tilted-plate goniometer using the sessile drop method. The results revealed that θa and θr increase with pressure (e.g., from 55° to 70° at 0.1 MPa to 119° to 121° at 20 MPa for organic-rich samples), whereas temperature effects depend on mineralogy, likely due to CO2/shale interfacial energy shifts from the changing CO2 density. Removing VOC reduced the brine contact angles (e.g., from 119° to 121° to less than 80° at 35 °C and 20 MPa), revealing a significant shift from CO2-wet to intermediate to strongly water-wet conditions. Additionally, the CO2 column height considerably increased after the VOC removal, with quartz-rich samples exhibiting the greatest effects (e.g., from –1050 to 3536 m at 35 °C and 20 Mpa). These findings demonstrate how geochemical variability driven by changes in rock mineralogy and organic matter content at subsurface conditions can affect CO2 storage capacity, plume migration, pore parameters, and competitive adsorption of CO2 on rock surfaces.The authors acknowledge King Abdullah University for Science and Technology (KAUST) and Edith Cowan University (ECU) for providing the required infrastructure for this work. The study and acquisition of cores were supported by KAUST faculty funding to Prof. V. Vahrenkamp. In addition, the authors acknowledge the Karak International Oil (KIO) and Ministry of Energy and Mineral Resources (MEMR) in Jordan for permitting sampling and Dr. Israa Abu Mahfouz for organizing the coring campaign
Lithium Potential in Saudi Arabia – An Initial Assessment
No full textLithium (Li) is a key element in the global energy transition, playing a vital role in low-carbon energy storage systems, particularly in batteries for electric vehicles (EVs). This study provides the first comprehensive geological assessment of lithium potential in Saudi Arabia by examining the natural occurrence of lithium in igneous and sedimentary rocks and the processes that lead to its enrichment in subsurface brines. The results suggest that the west coast rift basins and the Arabian Shield hold significant potential, while the eastern sedimentary basin appears to be less favorable.
Lithium naturally occurs in felsic igneous rocks, especially in their glass and micaceous components, and in sedimentary rocks derived from them, such as micaceous sandstones. Enrichment of lithium in pore waters may result from two primary mechanisms: (1) Water–rock interaction at elevated temperatures (>120°C), which leaches lithium from host minerals into formation fluids; and (2) Evaporative concentration of seawater, where lithium remains in the residual brine during progressive evaporite precipitation.
The felsic igneous rocks of the Arabian Shield and syn-rift sedimentary formations along the Saudi west coast show strong potential as lithium sources. In addition, evaporative processes in the region that lead to the precipitation of thick salt deposits further contribute to lithium enrichment in subsurface brines. Although current data is limited, the study identifies the west coast rift basins as the most promising areas for lithium-rich deep brines suitable for Direct Lithium Extraction (DLE). Lithium originates from the leaching of shield sediments in the deep rift basins and from leftover brines associated with the km-thick Miocene evaporates deposited in the Red Sea rift. In contrast, the Eastern Arabian Basin shows limited potential for lithium-rich brines. Evaporites are limited to a thin gypsum layer in the Jurassic Hith and older (Precambrian) deeply buried Hormuz salts, while clastic material eroded from the shield is shallow and too proximal to the outcrops for significant contributions to basinal brines.
This study provides the first comprehensive assessment of lithium potential in Saudi Arabia, offering valuable insights into sustainable resource development and future exploration opportunities in the Kingdom.<br
Metagenomic Insights in Antimicrobial Resistance Threats in Sludge from Aerobic and Anaerobic Membrane Bioreactors
No full textSludge is a biohazardous solid waste that is produced during wastewater treatment. It contains antibiotic resistance genes (ARGs) that pose significant antimicrobial resistance (AMR) threats. Herein, aerobic and anaerobic membrane bioreactors (AeMBRs and AnMBRs, respectively) were compared in terms of the volume of waste sludge generated by them, the presence of ARGs in the sludge, and the potential for horizontal gene transfer (HGT) events using metagenomics to determine which treatment process can better address AMR concerns associated with the generation of waste sludge. The estimated abundance of ARGs in the suspended sludge generated by the AnMBR per treated volume is, on average, 5–55 times lower than that of sludge generated by the AeMBR. Additionally, the ratio of potential HGT in the two independent runs was lower in the anaerobic sludge (0.6 and 0.9) compared with that in the aerobic sludge (2.4 and 1.6). The AnMBR sludge exhibited reduced HGT of ARGs involving potential opportunistic pathogens (0.09) compared with the AeMBR sludge (0.27). Conversely, the AeMBR sludge displayed higher diversity and more transfer events, encompassing genes that confer resistance to quinolones, rifamycin, multidrug, aminoglycosides, and tetracycline. A significant portion of these ARGs were transferred to Burkholderia sp. By contrast, the AnMBR showed a lower abundance of mobile genetic elements associated with conjugation and exhibited less favorable conditions for natural transformation. Our findings suggest that the risk of potential HGT to opportunistic pathogens is greater in the AeMBR sludge than in AnMBR sludge.The authors thank Dr. Xiang Zhao and Dr. Ruben Diaz (KAUST Bioscience core laboratories) for their assistance in sequencing, Jianqiang Zhou for his support in operating the AnMBR reactor, and Mohammed Abu Nasar, Mahmoud M. Abdel Hamid, and FM utilities of KAUST for their support
with the samples from the Aerobic MBRThis study was supported by funding from the King Abdullah University of Science and Technology (KAUST) Center of Excellence on Sustainable Food Security under award number 593
Hydrogen Spillover-Mediated Spatial Decoupling Process Boosts Syngas Conversion to Higher Oxygenates.
No full textThe direct conversion of syngas to higher oxygenates presents a fundamental challenge in simultaneously achieving high CO conversion, superior oxygenate selectivity, and minimal undesired C1 byproducts. Here, we develop a series of multifunctional CuxPd1/SiO2|CoMn catalysts with granule stacking architecture, which overcome the challenge by precisely controlling the spatial arrangement of active sites and the intermediate transport pathway. Systematic optimization reveals a distinct volcano-shaped relationship on Pd loadings, with the Cu28Pd1/SiO2|CoMn composite emerging as the optimal candidate. Such a catalyst achieves an exceptional oxygenates molar selectivity of 44.4% (C2+OH/ROH = 95.4%) while maintaining low C1 products (6.4% CO2 and 5.7% CH4) at considerable 27.3% CO conversion. Mechanistic studies reveal that the breakthrough stems from precise control of spatial intimacy of functional components, optimized mass balance between CHxO* and CHx*, and isolated Pd atom-mediated hydrogen spillover effects. Based on spectroscopic evidence with theoretical calculations, we propose a synergistic catalytic system wherein PdCu single-atom alloys facilitate H2 activation and CHxO* formation through hydrogen spillover, while Co0-Co2C interfaces produce abundant CHx* species. The synergistic interaction enables the migration of CHxO* intermediates from single-atom alloy sites to Co0-Co2C interfaces, where they undergo further insertion into CHx* species, ultimately leading to hydrogenation and formation of higher oxygenates.We are grateful for the financial support from National Key Research and Development Program of China (2023YFB4103200), the National Natural Science Foundation of China (22179137), and the Major Science and Technology Projects of Shanxi Province (202005D121002). We thank the Shanghai Synchrotron Radiation Facility of BL11B (https://cstr.cn/31124.02.SSRF.BL11B) for the assistance on XAFS measurements. We thank the Photoemission (BL10B) and Combustion (BL03U) End stations at the National Synchrotron Radiation Laboratory (NSRL) in Hefei for providing sufficient beamline time. We thank the State Key Laboratory of Coal Liquefaction, Gasification and Utilization with High Efficiency and Low Carbon Technology, Shanghai Yankuang Energy R&D Co., Ltd. for in situ DRIFTS under high pressure. We gratefully acknowledge Dr. Tiejun Lin of the Shanghai Advanced Research Institute, Chinese Academy of Sciences for his insightful contributions to the discussion in response to the reviewers’ comments
Machine Learning for 2D Material–Based Devices
No full textTwo-dimensional (2D) materials have emerged as a cornerstone for next-generation electronics, offering unprecedented opportunities for device miniaturization, energy-efficient computing, and novel functional applications. Their atomic-scale thickness, coupled with exceptional electrical, mechanical, and optical properties, makes them highly promising for applications ranging from ultra-scaled transistors to neuromorphic and quantum devices. However, optimizing these materials for device fabrication remains a complex and resource-intensive challenge due to the vast parameter space involved in their synthesis, processing, and integration. Machine learning (ML), a pivotal aspect of artificial intelligence (AI), has emerged as a powerful tool to accelerate the development of 2D material–based electronics by extracting insights from large experimental datasets and automating decision-making in high-throughput experimentation. This review highlights the critical role of ML in advancing 2D material research, focusing on growth optimization through material selection and morphology control, characterization for quality assessment, and device design through fabrication parameter optimization and performance prediction. This work aims to provide a comprehensive overview of the synergistic relationship between ML and 2D materials, outlining current advancements, challenges, and future prospects in AI-assisted material and device engineering.The authors acknowledge the support from Clark University, Quinnipiac University and National University of Singapore. The work was partially supported by the internal grants program of University of Notre Dame
Dynamic Adsorption–Desorption of Water on Carbonaceous Adsorbents: The Role of Hysteresis in the Breakthrough Curve
No full textHysteresis is present in the adsorption equilibrium isotherm of different materials. Their existence has been associated with different phenomena, but their effect in dynamic desorption is not yet clear. This study aimed to correlate the hysteresis cycles in the adsorption isotherms with dynamic adsorption and desorption breakthrough behavior. Water adsorption equilibrium isotherms, together with a detailed hysteresis loop scan, were determined experimentally as well as adsorption and desorption breakthrough. A methodology updated from the literature was used to predict the secondary adsorption and desorption branches within the hysteresis loop. Furthermore, the adsorption equilibrium theory (AET) was used to predict the adsorption and desorption dynamic breakthroughs using the adsorption/desorption isotherm. As a benchmark for the AET results, a bi-LDF and nonisothermal model was used. The results showed that hysteresis significantly changes the desorption breakthrough shape and the time required for complete column elution. However, this behavior is visible only on hysteresis loading above 65%. This behavior is due to a change in the desorption slope as a function of the hysteresis loading. In this way, these findings showed the importance of incorporating hysteresis phenomena into the design of adsorption-based processes in a way to ensure accurate predictions and optimized performanceThis research was supported by the King Abdullah University of Science and Technology (KAUST)