Recovery Techniques Research Articles

Dental Implant Artifacts in MRI: Compatibility and Considerations

This review investigated dental implant artifacts in magnetic resonance imaging (MRI) and their safety in clinical practice. Dental prostheses, including implants, crowns, and orthodontic appliances, cause artifacts due to their high magnetic susceptibility, particularly in materials like iron, stainless steel, and cobalt-chromium. Titanium implants are considered safe under MRI environments according to the American Society for Testing and Material (ASTM) standards, with no reported thermal injury or dislodgement during examinations. Despite limited artifacts from titanium's paramagnetic nature, minute ferromagnetic components can still affect visualization. Thus, reducing artifacts in oral and maxillofacial MRI scans is crucial. Two main categories of artifact reduction techniques are identified: improved porous titanium or alternative materials like zirconia and adjusting MR parameters with advanced sequences. Recommendations include increasing the readout bandwidth, reducing slice thickness, using spin-echo sequences instead of gradient-echo, and employing short tau inversion recovery or DIXON techniques for fat suppression. Additional methods like VAT, VAT-SEMAC combination, and MAVRIC show promise, although applicability may be restricted in specific MRI scanners. Continuous advancements in dental implant materials and MRI sequences are needed to improve imaging quality and reduce artifacts. Collaboration among dental practitioners, radiologists, and MRI technologists is essential for refining techniques and ensuring patient safety. Although overall dental implant artifacts pose challenges, safety in MRI is well-established. Ongoing developments hold significant potential to enhance MRI imaging quality in patients with dental devices

“There is a Mental Resistance”: Experiences of Involving Refugee Parents in a Youth Trauma Recovery Program from the Perspective of Participating Youth, Parents and Facilitators

AbstractScalable light-touch programs that align with the Trauma-Focused Cognitive Behavioral Therapy (TF-CBT) approach is becoming an established intervention model for refugee youth with symptoms of post-traumatic stress. Teaching Recovery Techniques (TRT) is one example and, as TF-CBT guidelines state, parent sessions are included as the model relies on parents to provide support and instigate the techniques. In addition to traumatic stress, refugee families are often subjected to acculturative, isolation and resettlement stress. This study sought to understand how refugee parental involvement in TRT functions in practice and how it is perceived by participating youth, parents, and facilitators in Sweden. Thirty semi-structured interviews (11 youth, 8 parents, and 11 TRT facilitators) were conducted by phone or videoconference, transcribed, and analyzed using Thematic Network Analysis. A global theme ‘Parental engagement in trauma recovery requires dedicated attention’ emerged. Three organizing themes sat within this global theme: (i) Shifting roles when adapting differently to a new context; (ii) Tendency to keep parents at a distance; and (iii) Parent sessions don’t just happen. Whilst the potential for refugee parent involvement was recognized, a number of factors preventing their participation were identified. Cultural adaptations within TRT facilitators’ training are recommended, including: raising awareness about contextual factors and changes in family dynamics with regard to trauma and migration; adopting culturally responsive ways to present parental involvement to youth and parents; adding positive parenting skills; addressing parental mental health and readiness; and preparing facilitators to redirect parents to adequate services, when needed.

The effectiveness of cryostimulation exposure on sleep and recovery in male athletes: Timing considerations.

The objectives of the study were (i) to evaluate the effects of whole-body cryostimulation (WBC) after training as an effective tool to improve sleep and recovery and (ii) to determine which exposure schedule for WBC (immediately after training vs. 1h before bedtime) is the most appropriate to improve sleep and recovery. Twenty-two well-trained male athletes or triathletes (23.1±3.5-years) were recruited in this controlled crossover protocol. Each participant completed the three experimental sessions, each composed of a running training session and one night of sleep analysis. Depending on the experimental condition, subjects were exposed-or not (CONT)-to WBC immediately after training (CRYO 7 p.m.) or 1h before going to bed (CRYO 10 p.m.). All participants were randomly assigned to each condition, spaced seven days apart. Sleep was monitored via actimetry, cerebral activity recordings, heart rate variability, body core temperature, and perceptual measurements. WBC after training did not modify subjective or objective sleep parameters compared to the control condition. However, WBC significantly improved cardiac parasympathetic activity. More specifically, it was more activated during the night following the CRYO 10 p.m. condition than in the other experimental conditions. Core body temperature (CBT) 1h after bedtime was the lowest in the CRYO 10 p.m. condition. This study confirmed the effectiveness of WBC as a recovery technique after intense evening training. We suggest that WBC may exhibit the most significant benefit on recovery if the session is performed 1h before bedtime, acting on subsequent parasympathetic activation and CBT drop.

Experimental and theoretical investigation of cationic-based fluorescent-tagged polyacrylate copolymers for improving oil recovery.

The growing need for energy and the depletion of oil wells necessitate advanced Enhanced Oil Recovery (EOR) techniques, particularly water and polymer flooding, which play a crucial role in augmenting hydrocarbon recovery rates. However, water flooding in high-permeability layers often leads to water breakthroughs, reduced sweep efficiency, and the formation of preferential channels, posing significant challenges to oil recovery and reservoir management. Conformance control treatments, including the use of polymer microspheres, offer a promising solution by sealing high-permeability zones and enhancing sweep efficiency. This study focuses on the application of fluorescent polymer microspheres based on polyacrylamide, which is extensively employed in the oil sector as an oil displacement agent. Fluorescent polymers called Poly 400, Poly 200, and Poly 600, incorporating cationic methacrylamide monomers, were synthesized through copolymerization to create amphiphilic polymers with enhanced stability and functionality. These fluorescent polymers were evaluated through flooding tests using a quarter-five-spot model of transparent quartz glass under UV light, allowing for instantaneous measurement and observation of fluorescence intensity. At reservoir conditions, the oil displacement experiments confirm that the incremental oil after water flooding by Poly 400, Poly 200, and Poly 600, is 13.1%, 9.1%, and 6.1% of OOIP respectively. The findings showed that fluorescent polymer microspheres could efficiently target high-permeability layers, adapt to varying pore throat sizes, and improve the plugging rate of high-permeability channels, thereby optimizing oil recovery. A subsequent simulation study using the CMG simulator provided further insights into the efficacy of these fluorescent polymers as EOR agents, revealing their potential to enhance sweep efficiency and enhance oil recovery. Simulation results showed that oil saturation decreased from 68% (initial) to 13.5%, 16.1%, and 18.3% after Poly 400, Poly 200, and Poly 600 flooding respectively. This work highlights the potential of fluorescent polymer microspheres as a valuable tool for EOR applications, offering significant advancements in reservoir management and oil recovery optimization.

A Review on Various Techniques for Boron Recovery: Focusing on Efficiency, Sustainability, Scalability, and Cost-Effectiveness

Boron is a critical element extensively used across various industries—such as glass manufacturing, ceramics, agriculture, detergents, nuclear energy, and aerospace—due to its unique chemical and physical properties. However, its widespread industrial use has raised significant environmental concerns, particularly its accumulation in aquatic systems, posing risks to biodiversity, plant life, and human health. This review examines the impacts of boron pollution on aquatic organisms, plants, and humans, highlighting the necessity for effective recovery strategies. We provide a comprehensive analysis of boron recovery techniques—such as reverse osmosis, electrodialysis, nanofiltration, adsorption, membrane distillation, and leaching—focusing on their efficiency, sustainability, scalability, and cost-effectiveness. The evaluation compares each method’s operational parameters, environmental impact, and economic feasibility. While methods like reverse osmosis and electrodialysis offer high removal efficiencies, they are often limited by operational costs and environmental drawbacks. Alternative methods like adsorption and nanofiltration present more sustainable and cost-effective options but may require optimization for large-scale applications. This review underscores the need for advanced, economically viable, and sustainable boron recovery technologies to mitigate environmental risks and comply with regulatory standards.

The concept of big data and predictive analytics in reservoir engineering: The future of dynamic reservoir models

Reservoir engineering is a critical discipline in the oil and gas industry, aimed at optimizing the extraction and management of subsurface resources. Traditionally, reservoir models have relied on static data and conventional simulation methods, which often fall short in capturing the dynamic complexities of reservoirs. With the advent of big data and predictive analytics, there is a significant opportunity to revolutionize reservoir modeling by integrating real-time data for continuous updates and more accurate predictions. This review introduces a theoretical exploration of how big data and predictive analytics can transform dynamic reservoir models, highlighting their potential to improve reservoir management and hydrocarbon recovery. Big data technologies enable the collection, storage, and processing of vast amounts of structured and unstructured data from multiple sources, including well logs, seismic surveys, drilling operations, and production data. Predictive analytics, through machine learning and statistical techniques, can extract actionable insights from these datasets to predict reservoir behavior, enhance decision-making, and optimize production strategies. This integration facilitates real-time monitoring and adaptive reservoir management, allowing engineers to respond to changing reservoir conditions and uncertainties more effectively. The review further explores the implications of big data-driven predictive models for enhanced hydrocarbon recovery techniques, such as water flooding and gas injection. By automating data processing and integrating real-time field data, predictive analytics can improve the accuracy of reservoir simulations, reduce downtime, and increase operational efficiency. Ultimately, the future of dynamic reservoir modeling lies in the seamless integration of big data and predictive analytics, providing a pathway to smarter, more sustainable resource management and maximized recovery factors in increasingly complex reservoir environments. Keywords: Big Data, Predictive Analytics, Reservoir Engineering, Dynamic Reservoir, Models.

Technology Focus: Drilling and Completion Fluids (November 2024)

This year’s primary selections for the Drilling and Completion Fluids Technology Focus reflect now-well-established industrywide emphases on machine learning (ML), automation, and the achievement of successful drilling of CO2 storage wells. Enhanced methods of modeling and monitoring allow time and cost savings while surpassing safety goals and furthering efforts to optimize CO2 storage. Paper OTC 35433 discusses a study centered on accurate gel-strength estimation. The authors leverage ML techniques, particularly the use of artificial neural networks, to develop predictive models for forecasting the gel strength of synthetic oil-based mud systems at both 10-second and 10-minute intervals, surpassing the precision and speed of techniques based on traditional rotational viscometers. In a similar vein, paper SPE 216322 seeks to bypass traditional manual methods of monitoring drilling fluids, its authors describing a novel online system that measures 10 key parameters continuously. They write that the system has been field-trialed across 200 wells with results that highlight the system’s reliability, with continuous operation for over 125 days. Finally, paper SPE 217711 involves evaluating the effects of an influx of CO2 into drilling fluids, a key task in the drilling of CO2 storage wells. Concentrating on oil-based drilling fluid, the presented study describes the development and integration of models for properties of drilling-fluid/CO2 mixtures into an existing software suite. Recommended-reading papers include an investigation of the use of microwave power in recovering oil from contaminated drill cuttings, reduction of the carbon footprint of drilling fluids, and sedimentation behavior of particles in fibrous sweep fluids. As always, the long-sighted ambition of such research, and the skill applied in its pursuit, reflects the commitment to excellence embodied by the authors of technical papers presented at SPE conferences. Recommended additional reading at OnePetro: www.onepetro.org. SPE 217140 Microwave-Assisted Technique for Oil Recovery From Oily Sludge Shale Drilled Cuttings by A. Agi, Universiti Malaysia Pahang, et al. OTC 34667 Successful Decarbonization of Drilling Fluids by Using Highly Efficient Technology and Reduced Chemical Usage, Logistics, and Casing Sections by Gerardo Jardinez, Pemex, et al. SPE 218631 Application of Machine-Learning Method for Modeling Settling Behavior of a Spherical Particle in Fibrous Drilling Fluids by R.M. Elgaddafi, Australian University, et al.

Comparison of liquid and filter sampling techniques for recovery of Bacillus spores and Escherichia coli from environmental water

Historically, detecting water contamination has involved collecting and directly analyzing liquid samples, but recent advances in filter sampling methods offer numerous potential advantages. Emerging technologies, including environmental DNA (eDNA) samplers, could be used for remote microbial contamination sampling, but work is needed to determine if target microorganisms can be recovered from filters at comparable levels to traditional sampling methods. In this study, Escherichia coli and a surrogate for Bacillus anthracis spores were sampled from synthetic stormwater and quantified using both direct liquid and filter methods, and dwell time tests compared microorganism persistence in water and on filters. At nearly all tested timepoints, the recoveries of spores from membrane filters were within 0.5 log10 colony forming units per sample (CFU/sample) compared to the liquid-only samples, suggesting that the use of filter sampling is a feasible alternative to liquid-based sampling, and samples were held for up to 4 weeks without significant sample degradation. Recoveries for E. coli remained relatively consistent for ∼3 days in phosphate buffered saline (PBS), in synthetic stormwater, and on membrane filters, but decreases in recoveries were observed for samples held for >3 days. These results indicate that emerging water sampling technologies, which reduce logistical burdens and offer potential cost savings, can be leveraged to characterize biological contamination in water matrices with multiple types of microbiological agents.

Experimental investigation of hybrid enhanced oil recovery techniques for Ugnu Heavy Oil on Alaska North Slope

The Alaska North Slope (ANS) is endowed with a substantial reservoir of heavy oil, estimated at 12–18 billion barrels, primarily concentrated within the Ugnu reservoirs. These deposits, situated at depths ranging from 2,000 to 4,000 feet, lie in close proximity to the permafrost and have undergone biodegradation, resulting in in-situ viscosities reaching thousands of centipoise. Following the success in recovering the somewhat less heavy, viscous oils through polymer injection, the deposits in Ugnu Formation are garnering significant interest. Although thermal recovery methods are commonplace for heavy oils, applying these methods on ANS is impractical, given the adjacency to continuous permafrost. Therefore, non-thermal hybrid enhanced oil recovery (cEOR) methods, such as solvent (e.g., CO2) and low salinity water (LSW) based, or LSW and polymer-based techniques, emerge as the primarily feasible options for recovering these vast heavy oil resources. This study experimentally investigates, via systematically carried out fluid property and phase behavior tests and a series of sand-pack coreflood experiments, the potential to enhance the recovery of Ugnu heavy oils. The coreflood experiments reveal the synergistic effect of combining liquid-CO2 with LSW to be the most promising approach in this study as a water alternating gas (WAG) process results in the cumulative recovery factor of 83.5%, doubling the recovery obtained by continuous low salinity waterflood. Additionally, the liquid-CO2-LSW WAG process demonstrated an additional benefit for CO2 storage, with about 25% of the pore volume of the liquid-CO2 injected being sequestered at the end of the injection process. This significant recovery improvement is attributed to a substantial reduction of oil viscosity upon contact with the liquid CO2 during the soaking period, with a reduction of up to 95% of the original oil viscosity. Meanwhile, in-situ emulsion generation was observed in the oil produced from the continuous LSW flooding. This was also evident by the increased differential pressure across the sand-pack compared to that of the liquid-CO2 alternating LSW process. The promising results of this study indicate significant potential for liquid-CO2 alternating LSW injection as an effective cEOR technique for Ugnu heavy oils.

Study Investigates Hydrate Formation Risk in WAG Changeover Operations

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 218101, “Investigating the Effect of Carbon Dioxide Concentration on Hydrate Formation Risk From Water-Alternating-Gas (WAG) Changeover Operations,” by Farzan Sahari Moghaddam, SPE, Majid Abedinzadegan Abdi, SPE, and Lesley A. James, SPE, Memorial University of Newfoundland. The paper has not been peer reviewed. _ Hydrate formation is a flow-assurance challenge for offshore oil and gas operations with subsea pipelines, wells, and tiebacks. In water-alternating-gas (WAG) operations, hydrates can form within the injection wells when switching from water to gas and vice versa. This study investigates hydrate formation in a WAG injection well under water-to-gas and gas-to-water changeover operations. Introduction Few previous studies have focused on hydrate formation in gas injection and production wells. Hydrate formation in a gas well under particular enhanced oil recovery techniques requires more attention. This study aims to investigate the changeover operations of water-to-gas and gas-to-water (well depth: 4096 m) and the effects of gas composition changes in terms of CO2 content (5–44 wt%) and thermodynamic inhibition (5 m3 methanol) after water injection. In terms of flow rates, injection rates of 2300–3800 m3/d for water and 1 million std m3/d for gas, which are applicable for offshore Newfoundland and Labrador (NL), are studied. The complete paper includes a discussion of past studies on hydrate formation in production and injection-gas systems. Methodology Two scenarios were simulated: water-to-gas changeover and gas-to-water changeover over a range of CO2 concentrations of 5–44 wt%. For operational parameters, up to 3 days of shut-in period was considered for the changeover operations. The water injection rate of 2300 m3/d and gas injection rate of 1 million std m3/d were considered. The rate was increased to find the injection rate that could provide full displacement of the water phase within less than 1 hour from a water-to-gas changeover operation. The same injection rate is maintained for other natural-gas cases with increased CO2 content by changing the compressor injection pressure. After modeling the fluid with an appropriate cubic equation of state, the fluid model file was imported to the dynamic multiphase flow simulator. A sample WAG well from offshore NL where hydrate formation was experienced was considered for the simulations. After finalizing the setup of the well, the simulation scenario was finalized according to the changeover operation and the operating conditions. A sensitivity analysis was conducted on various concentrations of CO2 (5–44 wt%) followed by conducting both water-to-gas and gas-to-water changeover operations in the transient multiphase simulator. Finally, hydrate formation in presence of methanol was simulated, and the resulting profiles of hydrate formation temperature minus fluid temperature, known as DTHYD, were compared. The well depth is 4096 m from the seabed, and tubing internal diameter is 0.16 m. The seabed depth is 124 m below mean sea level. The bottomhole is known as the zero depth on the DTHYD, holdup, density, and pressure profiles, and the wellhead is considered to be 4096 m above the bottomhole depth in these profiles. A methanol slug was injected directly into the well under a sea temperature of 3°C at the end of water injection and before the shut-in duration.

New scheme of cooperative compressed spectrum sensing

Abstract This study addresses key challenges in sparse signal recovery and compressed spectrum sensing (CSS), focusing on low signal-to-noise ratios (SNR), and the computational complexity of cooperative systems. Motivated by the need for faster and more accurate recovery techniques, we first investigate and generalize the Reduced-Set Matching Pursuit (RMP) algorithm, which overcomes the speed and accuracy limitations of conventional greedy algorithms. Secondly, we propose a novel spatial averaging technique that enhances detection performance by exploiting data from multiple users to counteract low SNR. Lastly, we integrate cooperation into CSS, further improving the detection capabilities during the recovery process. Compared to existing techniques like Joint Sparse Recovery (JSR) and CoSaMP, which face computational and accuracy constraints in real-time applications, the RMP algorithm, combined with the Virtual method (data transformation) and AND fusion rule, delivers superior performance than JSR methods. Moreover, spatial averaging significantly increases the probability of cooperative detection Q d , with SNR increasing linearly by a factor of L − 1 per channel. The results are validated through the implementation of SDR. These findings demonstrate the potential of RMP and cooperation to overcome current limitations in CSS, advancing the state-of-the-art in spectrum sensing for collaborative networks.

High-Resolution Collaborative Forward-Looking Imaging Using Distributed MIMO Arrays

Airborne radar forward-looking imaging holds significant promise for applications such as autonomous navigation, battlefield reconnaissance, and terrain mapping. However, traditional methods are hindered by complex system design, azimuth ambiguity, and low resolution. This paper introduces a distributed array collaborative, forward-looking imaging approach, where multiple aircraft with linear arrays fly in parallel to achieve coherent imaging. We analyze signal model characteristics and highlight the limitations of conventional algorithms. To address these issues, we propose a high-resolution imaging algorithm that combines an enhanced missing-data iterative adaptive approach with aperture interpolation technique (MIAA-AIT) for effective signal recovery in distributed arrays. Additionally, a novel reference range cell migration correction (reference RCMC) is employed for precise range–azimuth decoupling. The forward-looking algorithm effectively transforms distributed arrays into a virtual long-aperture array, enabling high-resolution, high signal-to-noise ratio imaging with a single snapshot. Simulations and real data tests demonstrate that our method not only improves resolution but also offers flexible array configurations and robust performance in practical applications.

High-Selective Separation Recovery of Ni, Co, and Mn from the Spent LIBs Via Acid Dissolution and Multistage Oxidation Precipitation.

For recovering Ni, Co, and Mn from lithium-ion batteries, traditional chemical precipitation methods demonstrate low selectivity and significantly contribute to environmental pollution. This study proposes a separation recovery technique for transition metals, specifically Ni, Co, and Mn, from spent LIBs, involving "acid dissolution" and "multistage oxidation precipitation". More than 98 % of transition metals can be extracted from spent LIBs using a low acid concentration (0.5 M) without reducing agents. The feasibility of separating different metals via multistage oxidation precipitation, based on their different electrode potentials for oxidizing Me2+ (Me=Mn/Co/Ni), was confirmed. The combination of oxidizing agent S2O8 2- and the precipitant OH- was universally applied to the fractional precipitation of Mn, Co, and Ni respectively. About 99 % of Mn, 97.06 % Co, and 96.62 % Ni could be precipitated sequentially by changing the concentrations of S2O8 2- and the pH value of solution. XRD, XPS, XRF, ICP-MS and other methods were employed to elucidate the mechanism behind the multistage oxidation precipitation of target metal compounds, exploiting the differential electrode potentials for oxidizing Me2+ ions. This technique surpasses traditional solvent extraction in cost-effectiveness and selectivity, showing promise for large-scale industrial applications in recovering Mn, Co, and Ni.

Selective recovery of Au from waste printed circuit board by water-soluble organic leaching: The key role of in situ bromine mediation and identificationof pathway

A large amount of gold in electronic waste (E-waste) is not properly recovered owing to the absence of efficient and safe leaching methods. Herein, we proposed the concept of ‘water-soluble organic Au leaching’ and created a new water-soluble organic leaching agent, WS NBS–DMF, by dissolving millimolar amounts of N-bromosuccinimide (NBS) and dimethylformamide (DMF) in water. Under mild conditions (25 ℃, pH 7.0), WS NBS–DMF achieved a 94.9 % leaching efficiency of Au for waste printed circuit board (WPCB) with limited leaching of base metals. The potent bromine radical (Br•) and ligands significantly contributed to Au complexation and oxidization via in situ bromine generation and radical initiation from WS NBS–DMF. The bidirectional hydrogen-bond effect of DMF facilitated the in situ bromine generation. Two Au(I) complexes ([AuBr2]- and [(NHS)AuBr]-) and an Au(III) complex ([(NHS)AuBr3]-) were confirmed as the Au leaching products by spectroscopy and mass spectrometry. Furthermore, reciprocal σ-donations between the Au center and ligands in the bonding orbitals enhanced the stability of the Au complexes, thereby promoting efficient Au leaching. Comparing with other leaching methods, this study of WS NBS–DMF provides a safe, economic and eco-friendly technique for efficient and selective gold recovery from e-waste.

Toxicity and environmental aspects of surfactants

Abstract As the single largest class of specialty chemicals, surfactants are consumed in huge quantities in our daily life and in many industrial areas. In the past, the attention was focused entirely on technical performance. However, starting from the 1970s and 80s, surfactant related environmental concerns have become the main driving force to upgrade surfactant production technology to make more benign or “greener” products. For this reason, environmental issues, dermatological effects, and oral toxicity are the main priorities when surfactants are considered for a specific purpose. In this paper, we present five cases to demonstrate how the surfactant industry tackles these challenges to mitigate the environmental and health effects associated with surfactant consumption. We also discuss the important role played by surfactants in a current carbon capture and storage (CCS) strategy to reduce the CO2 level in the atmosphere. Surfactant-based stable CO2 foam flooding is a well-established enhanced oil recovery technique. It has been considered to be an economically realistic procedure to sequester large amounts of CO2 in geological formations.

Capacitive lithium capture system using a mixed LiMn2O4 and LiAlO2 material

The increasing demand for lithium (Li), a crucial material in various industries, requires efficient recovery methods and a shift toward a circular economy. This study investigates a fast, eco-friendly technique for selective Li recovery, emphasizing the use of innovative materials from spent Li-ion batteries (SLiBs), particularly LiMn2O4(LMO)/LiAlO2(LAO)-based materials, to enhance Li's circular economy. Conventional Li recovery methods typically involve prolonged processes with chemical additives and environmental concerns, whereas electrochemical systems like membrane-based capacitive deionization (MCDI) offer promising high removal capacities, regeneration ability, and scalability. However, no commercial electrochemical Li recovery system underscores the need for continued research to improve their performance. This study employs MCDI for selective Li recovery, examining various electrode materials, including commercial activated carbon, LMO-based electrodes, and modified LMO/LAO-based electrodes. The mixed LiMn2O4/LiAlO2 cathode exhibited high selectivity for Li+ extraction with a recovery efficiency of 83.1 %, achieving a deionization capacity of 38.15 mg/g at 1.0 V under an initial feed concentration of 5 mM LiCl. The Li+ adsorption reached 900 μmol/g, with a separation factor (αMg2+Li+) of 3.77 (CMg2+/CLi+ = 1), setting a robust foundation for a comprehensive Li recovery framework that meets the increasing Li demand while minimizing environmental impact.

Water hyacinth biorefinery: Improved biofuel production using Trichoderma atroviride pretreatment

AbstractThe pyrolysis of water hyacinth is gaining attention and acceptance as a resource recovery technique due to its availability and economic viability. However, the presence of lignin, one of the three major biomass fractions, presents significant challenges for profitable water hyacinth processing for biofuel production. Fungal pretreatment of water hyacinth for lignin breakdown has been explored but the application of Trichoderma atroviride as a pretreatment for pyrolysis is relatively novel. The efficacy of T. atroviride pretreatment in improving water hyacinth's pyrolytic products using a fixed‐bed reactor was therefore investigated in this study. The optimization process was studied using a central composite design in response surface methodology with Design Expert 13. Delignification of the biomass was established because the elemental analysis showed a 25.42% increase in cellulose content and a 23.40% and 3.37% decrease in lignin and hemicellulose content, respectively. The biomass pretreatment applied influenced the physical and chemical characteristics of the pyrolytic products. The highest pyrolysis oil yield increased by 25.81% at 575 °C and particle size 2290 μm, and the highest char yield decreased by 4.23% at 273 °C and particle size 1500 μm. This research is crucial for policy and research conversations as it offers a scientific basis for the application of T. atroviride pretreatment in biomass pyrolysis technology and emphasizes the optimal utilization of water hyacinths to obtain socio‐environmental benefits.

Sub-THz and THz Cherenkov radiation source with two-dimensional periodic surface lattice and multistage depressed collector

We present the theory, concept and design of an efficient, megawatt coherent Cherenkov radiation source based on a two-dimensional periodic surface lattice (2D-PSL) cavity combined with a novel energy recovery system for the generation of highly efficient (> 50%) single-frequency radiation. We demonstrate the scalability of the transverse dimension of the 2D-PSL cavity of the Cherenkov source and thus the potential for efficient, continuous-wave, high-power (> 1 MW) operation; fundamental to the eventual realization of clean, fusion energy. These new sources, with the capacity to operate in the 0.1-10THz range, hold strong promise to address the long-standing “Terahertz gap”. By combining a Cherenkov oscillator driven by a non-gyrating beam with an innovative four-stage depressed collector energy recovery system, the overall device efficiency can be increased to be competitive with gyrotrons in the requirements for heating and current drive in fusion plasma. In these Cherenkov devices, the frequency independence of the magnetic guide field enables advantageous frequency scaling without deployment constraints, making them especially attractive for high-impact applications in fusion science, turbulence diagnostics, non-destructive testing and biochemical spectroscopy. The novel energy recovery techniques presented in this paper have broad applicability to many electron-beam driven devices, bringing revolutionary potential to future THz source technologies.

Sparse recovery by genetic algorithms for acoustic testing applications

Various acoustic testing applications involve solving inverse problems from acoustic measurements, such as acoustic imaging and duct mode identification. In these problems, the physical quantity to be inferred is sparse, which allows applications of certain sparse recovery techniques, such as the compressive sensing. But such methods usually involve very complex theory, which therefore set a high threshold for beginners. By contrast, this work proposes a similar but much simpler method based on the well-known genetic algorithm, which borrows only a few easily understood concepts from nature evolution and can rely on easily accessed software/toolboxes. The performance of the developed method is demonstrated by two acoustic testing experiments in an anechoic chamber, i.e., acoustic imaging and duct mode identification.

In situ combustion performance in heavy oil carbonate reservoirs: A triple-porosity numerical model

This study aims to address the challenges of oil recovery in highly heterogeneous carbonate reservoirs by employing a novel triple-porosity numerical model approach for in-situ combustion (ISC). The primary focus is on the performance of ISC within isolated vuggy pore spaces, a characteristic feature of such reservoirs. By simulating triple-porosity through artificially induced vuggs, core matrix, and fractures, we evaluated the feasibility of the ISC technique for heavy oil recovery in a dolomite reservoir using a combustion tube setup.The numerical model, calibrated through history matching, incorporates an extended kinetic reaction scheme to better represent high-temperature oxidation processes. Experimental and simulation results show a strong correlation in temperature profiles, ignition timing, and fluid production, effectively reproducing the observed gas compositions. This integrated experimental and numerical approach demonstrates the potential for applying ISC in triple-porosity systems, offering valuable insights for field-scale implementations in similarly complex carbonate reservoirs. The novelty of this research lies in its comprehensive modeling of the first ISC experiment in a triple-porosity framework, providing a deeper understanding of the interactions between matrix, fracture, and vugg networks, and paving the way for enhanced oil recovery (EOR) strategies in challenging reservoir environments.