Book Chapters
Recent Submissions
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Inshimtu – A Lightweight In Situ Visualization “Shim”(Springer Nature Switzerland, 2023-08-25) [Book Chapter, Conference Paper]In situ visualization and analysis is a valuable yet under utilized commodity for the simulation community. There is hesitance or even resistance to adopting new methodologies due to the uncertainties that in situ holds for new users. There is a perceived implementation cost, maintenance cost, risk to simulation fault tolerance, potential lack of scalability, a new resource cost for running in situ processes, and more. The list of reasons why in situ is overlooked is long. We are attempting to break down this barrier by introducing Inshimtu. Inshimtu is an in situ “shim” library that enables users to try in situ before they buy into a full implementation. It does this by working with existing simulation output files, requiring no changes to simulation code. The core visualization component of Inshimtu is ParaView Catalyst, allowing it to take advantage of both interactive and non-interactive visualization pipelines that scale. We envision Inshimtu as stepping stone to show users the value of in situ and motivate them to move to one of the many existing fully-featured in situ libraries available in the community. We demonstrate the functionality of Inshimtu with a scientific workflow on the Shaheen II supercomputer.
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Turbulent Hydrogen Flames: Physics and Modeling Implications(Springer International Publishing, 2023-07-15) [Book Chapter]Hydrogen exhibits special burning characteristics such as fast laminar and, thereby, turbulent flame speed, and a wide flammability limit. Because of these features, the existing numerical models that have been developed for e.g., natural gas or fuels with unity Lewis number assumption could be limited or even unusable. This chapter discusses the models for turbulent flame speed and local displacement speed of pure lean hydrogen premixed flames, particularly for a wide range of turbulence levels. Moreover, the predictive capability of the probability density function (PDF) modeling adopting the widely used laminar flamelet concept for Reynolds averaged Navier–Stokes (RANS) or large-eddy simulation (LES) approaches is assessed a priori using a set of state-of-the-art direct numerical simulation (DNS) data. The general conclusion suggests that the main turbulent parameter dictating the turbulent flame speed is found to be the size of the most energy-containing eddies rather than non-dimensional numbers such as Reynolds (Re) or Karlovitz (Ka) numbers. The local displacement speed models also suggest that a model developed for moderate turbulence level (Ka ≈O(10)) predicts well flames with Ka >O(1,000). PDF modeling using the flamelet concept is evaluated up to Ka >O(100), for which the mass fractions of major species are reasonably well predicted.
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Hydrogen-Fueled Spark Ignition Engines(Springer International Publishing, 2023-07-15) [Book Chapter]Hydrogen is most easily used as combustion engine fuel in a spark ignition engine. This chapter starts from the properties of hydrogen and hydrogen mixtures to present the various options for running spark ignition engines on hydrogen, reviewing the power density potential, emissions and efficiency. This is then linked to past and present research and development of hydrogen fueled vehicles, before concluding with the most promising emerging markets.
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Lipids, docosahexaenoic acid (DHA), and traumatic brain injury(Elsevier, 2023-06-16) [Book Chapter]Traumatic brain injury (TBI) is one of the leading causes of death or disability in incidents of trauma. It continues to be clinically challenging to find absolute treatments that can manage and control all aspects of secondary injury post-TBI. While some fat diets, like high-fat diet (HFD), are bad, emerging evidence suggests that early treatment with omega-3 polyunsaturated fatty acids (PUFAs), given at optimal doses, offers therapeutic potential in improving TBI outcomes. Omega-3 PUFA family is the main structural components of cell membranes, and namely, the docosahexaenoic acid (DHA) is mostly concentrated in the brain. This chapter will shed light on fat diets, and on how omega-3 supplementation offers a safe and promising therapeutic approach for TBI among other neurological disorders. More specifically, it will highlight the effects of DHA of the omega-3 PUFA family, on neuroinflammation and neuroprotection in the context of TBI.
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Development of Multiwalled Carbon Nanotube Doped Polypropylene Melt-Blown Fiber Mat Interleaved Hierarchical Single-Polypropylene Composites(Springer Nature Switzerland, 2023-06-08) [Book Chapter]In this chapter, the method of producing a multiwalled carbon nanotube (MWCNT)-doped Polypropylene (PP) fine fibers via melt-blowing was demonstrated. The MWCNT-doped fiber mats were then applied as an interleaving veil to create hierarchical single-PP composites. The morphological, thermal and mechanical properties of the nanocomposite fibers are discussed. The effect of the nanocomposite fine fiber mat interleaving on the thermal and mechanical properties of the SPCs was systematically and comparatively investigated. Results implied that incorporating MWCNT increased the melt-blowing grade PP resin viscosity. Incorporating MWCNT enhanced the melt-blown (MB) PP fiber mat's specific strength by 78% and improved thermal stability. Hierarchical single-polypropylene composites (SPCs) were produced by film-stacking, for which a PP film was used as a matrix, a PP woven fabric was used as primary reinforcement, and the MB fiber mat was used as interleaves. Interleaving enhanced the SPC's tensile modulus by up to 37%. Interleaving of the MWCNT doped PP fiber mat provided a robust interfacial adhesion and higher damage tolerance under tensile load. Master curves were constructed from dynamic mechanical analysis (DMA) frequency sweep tests based on the time–temperature-superposition (TTS) principle. Results revealed that the SPCs storage modulus increased by 33%, while the tanδ decreased by around 10% with the interleaving PP/MWCNT fiber mat.
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Multiscale Single-Polypropylene Composites: Melt-Blown Polypropylene Fiber Mat Interleaving(Springer Nature Switzerland, 2023-06-08) [Book Chapter]In this chapter, integrating melt-blown (MB) Polypropylene (PP) fiber mat interleaves into single-polymer composites (SPCs) was demonstrated. SPCs were created by film-stacking using PP film as a matrix, a PP woven fabric as primary reinforcement, and the MB PP fiber mats as an interleaving veil. MB PP fiber mat interleaving improved the SPC’s tensile modulus and interlaminar shear strength by up to 46% and 17%, respectively. The perforation energy of the laminae at impact was also increased by 14% with the PP fiber mat interleaving. Differential scanning calorimetry (DSC) tests showed that MB fibers acted as a nucleating agent in the matrix, resulting in improved crystallinity. Dynamic mechanical analysis (DMA) was conducted, and master curves were constructed based on the time–temperature superposition principle. The storage modulus significantly increased while the tanδ decreased. MB PP fibers created a net-like structure between reinforcing woven and matrix, enhancing interfacial performance. The interleaving concept can promote SPCs utilization in respective engineering applications where high toughness and impact resistance are required.
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Conclusion of Experimental Results and Future Suggestions(Springer Nature Switzerland, 2023-06-08) [Book Chapter]This book investigated melt-blown fibers' production methods and applications for sustainable and green composite production. Firstly, the melt-blown fiber formation mechanism was investigated, considering the effect of processing parameters on the fiber mat properties. And then, a new concept of making advanced single-polymer composites with melt-blown fiber mat interleaving was demonstrated. The effect of melt-blown fiber mat interleaving on the composite laminae’s thermal and mechanical behavior was evaluated. The multiwalled carbon nanotube-doped polypropylene melt-blown fiber mats were produced, and the effect of multiwalled carbon nanotube doping on thermal and mechanical properties was analyzed. Carbon nanotube-doped melt-blown fiber mats were also used as an interleaving veil to produce single-polymer composites. The effect of the nanocomposite fiber mat on the single-polymer composite’s thermal and mechanical characteristics was also detailed. In this chapter, results from these experimental studies were summarized, and significant findings were highlighted. Furthermore, the past and future of melt blowing research and development were briefly discussed. New concepts and future directions of melt-blown fibers and their composites were discussed in light of the sustainable industrial revolution goals.
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Literature Overview(Springer Nature Switzerland, 2023-06-08) [Book Chapter]This chapter aims to facilitate an outlook on melt-blown fiber mats and related composites by reviewing the recent developments in melt blowing, melt-blown fiber mats and their related applications, nano-/submicron fiber reinforced composites. The chapter also focuses on advancing sustainable fibers and composites via knowledge. The literature overview summarizes the materials used in the melt blowing, the effects of processing parameters on the structure and performance of the fiber mats and their products, thermal and physical properties, mechanical behaviors of fiber mat interleaved and reinforced composites, and related composite manufacturing methods and their potential implementation in polymer and composite science & engineering.
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Understanding the Structure–Property-Parameter Relationship of Polypropylene Melt-Blown Fibers(Springer Nature Switzerland, 2023-06-08) [Book Chapter]In this chapter, the structure of (polypropylene) PP fibers was evaluated systematically and comparatively using different processing conditions via melt blowing. The influence of four parameters (air pressure, air temperature, die-to-collector distance (DCD), and collector speed) on the fiber morphology (fiber diameter, pore size, porosity) and mechanical and thermal properties were detailed and the fiber formation mechanism was investigated. Melting temperature, melting enthalpy and crystallinity were obtained using the differential scanning calorimetry (DSC) technique as a function of melt-blowing parameters. The crystallite size and crystal phase evaluations were carried out using the peak parameters obtained by the curve fitting of the equatorial wide-angle X-ray diffraction (WAXD) profiles. A new factor, the mat consolidation coefficient, was introduced and used to efficiently summarize melt-blown (MB) PP fiber mats’ process-property-structure relationships. This study details how to control the melt blowing parameters to tailor the PP fiber mat features for the respective application fields. It also gives insight into fiber formation mechanisms during melt blowing to generate self-bonded, defect-free, fine fiber mats.
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Epigenetics and Brain Plasticity: Back to Function(Springer International Publishing, 2023-06-07) [Book Chapter]Throughout our entire life, our brain is constantly shaped by the experience of both the outer and the inner environments. Sensory perceptions, as well as thoughts and feelings, are constantly processed and integrated in order to create a plastic representation of these environments and to efficiently adapt to perturbations; such a high demand of plasticity is met by the extraordinary capacity of our nervous system to quickly modify upon specific stimuli. Since a great number of neuronal plasticity processes rely on changes in gene induction/repression, a responsive, fine-tuned regulation of gene expression is of primary importance for a correct adaptation. Epigenetic regulation orchestrates the spatiotemporal regulation of gene expression in response to intracellular and extracellular stimuli, specifically through modifying chromatin accessibility to the transcriptional machinery, and is therefore likely to play a fundamental role in nervous system homeostasis and functioning. Despite being studied for more than forty years, our current understanding of the importance of epigenetics, particularly in highly complex fields such as neurophysiology and cognitive processes, is still very limited. This chapter aims to summarize our current knowledge on the role epigenetics plays in brain repair and how epigenome alterations may be involved in the pathophysiology of some common psychiatric disorders.
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Cation distribution in ferrite nanoparticles and thin films using X-ray absorption spectroscopy methods(Elsevier, 2023-04-28) [Book Chapter]Cation distribution in spinel ferrites strongly influences their magnetic and catalytic properties. Cation distribution depends on the electronic configuration and valence of ions, but rearrangement can occur at the nanometric scale. The optimization of the technological applications of ferrites is therefore reliant on detailed information on the distribution of cations between the octahedral and tetrahedral sites of the spinel structure. To this end, X-ray absorption spectroscopy has proven to be a very powerful method due to the ability to study selectively and independently the coordination environment of two cations present in ferrites. The information provided is reviewed in this chapter.
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Advances in Organometallic Perovskites Enabled Radiation Detection Technologies(Springer International Publishing, 2023-04-20) [Book Chapter]In this chapter, the background knowledge on ionizing radiation is classified based on the nature of the photons and particles, and recent advances in the emerging field of metal-halide perovskite (MHP)-based radiation detection are presented. The chapter introduces the underlying principles of ionized particle and high-energy radiation detection and emphasizes the critical performance metrics. Then, the appropriate fundamental characteristics and advantages of MHPs for radiation detection are discussed in detail. After that, recent accomplishments in detecting α-, β-, γ-, and X-rays using halide perovskites are summarized. The chapter’s last part focuses on current challenges and future perspectives.
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Comparative analysis of the inverted Joule cycle, closed Joule cycle, and various approximate Ericsson cycles for waste heat recovery from exhaust gases with the working fluid as a variable(CRC Press, 2023-04-19) [Book Chapter]Decarbonization for a net-zero future has gained momentum in recent years due to the impact of greenhouse gases on our environment. Various governments and industries have announced their strategies to achieve low-carbon or net-zero carbon strategies, which will require the use of renewable energy resources and alternative fuels. Achieving a net-zero carbon future may take anywhere between 20–50 years. In the interim, it is apparent that there is a need to make the current energy-producing devices such as internal combustion engines and gas turbines more efficient, helping to bridge the gap. One such concept is waste heat recovery (WHR) from hot exhaust gases. In this paper, Aspen Plus software is used to model and analyze WHR systems, based on different variations of the Joule Cycle: Inverted Joule Cycle, Closed Joule Cycle (CJC), CJC with heat recuperation, two-stage Ericsson Cycle (approximated as a CJC with two stages of compression with intercooling between the compression stages, two stages of expansion with reheating between the expansion stages, and heat recuperation), three-stage Ericsson Cycle (approximated as a CJC with three stages of compression with intercooling between the compression stages, three stages of expansion with reheating between the expansion stages, and heat recuperation), CJC with two stages of expansion, reheating and heat recuperation, and CJC with two stages of compression, intercooling and heat recuperation. In multistage compression, the temperature of the inlet stream into all the compressors was kept constant using intercoolers, and equally, in multistage expansion, the temperature of the inlet stream into all the turbines was also kept constant through reheaters. Air, argon, and carbon dioxide are separately investigated as working fluids. Sensitivity studies of the exhaust gas temperature and the system pressure ratio and their impact on the cycle thermodynamic efficiency and specific net work output were carried out for the considered working fluids and a comparative analysis of the different system models was also performed. The results show that for an exhaust gas temperature of 600°C, theoretical cycle thermodynamic efficiencies up to about 40%, and specific net work output values up to about 160 kW/kg of exhaust gas can be obtained, with the two-stage Ericsson cycle and the CJC with heat recuperation and intercooling striking a pragmatic balance between 232system efficiency and system complexity. Also, the results show that argon is the most effective working fluid at low-pressure ratios while carbon dioxide is most suitable for high-pressure ratio applications.
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Atomically Precise Copper Nanoclusters: Syntheses, Structures, and Properties(Wiley, 2023-03-31) [Book Chapter]Compared with gold and silver nanoclusters (NCs), copper NCs often exhibit different but more complex geometrical motifs, thereby generating a potentially wider variety of nanocluster species. This chapter focuses on superatom-like copper NCs and copper(I) hydride NCs, including their synthesis, structural diversity, and properties. It also focuses on the synthesis of copper NCs with atomically precise structure. Such copper NCs are readily prepared by two main approaches: direct synthesis via the chemical reaction of cationic metal precursors and surface ligands and indirect synthesis, or nanocluster-to-nanocluster transformation, which is used to obtain novel copper-based NCs with different surface ligands, metal compositions, and dimensions. Hydrides are considered to play an indispensable role in constructing and stabilizing the structure of copper NCs. The chapter discusses copper NCs based on the electron count and hydrides in copper NCs.
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Chemistry diagnostics for monitoring(Elsevier, 2023-03-03) [Book Chapter]Chemically sensitive diagnostics are indispensable to unravel reactive processes in combustion and beyond, to understand their development in time and space and to monitor the reaction progress under the conditions of interest. A multitude of techniques is available that may provide species composition together with other process-controlling variables as a function of the reaction environment. Analytical tools have been developed that range from one-of-a-kind large-facility instrumentation to robust sensors for use in technical systems and in the field. In this chapter, needs and developments for the near and midterm future are addressed combining individual contributions from selected perspectives and intertwining thoughts and ideas from different fields and expertise. Major advances can be expected from combinations of instrumentation and digital processes, with beneficial uses for a multitude of processes in carbon-reduced and carbon-neutral environments.
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Exploration and collection of Quinoa's wild ancestor in Argentina(Springer International Publishing, 2023-02-28) [Book Chapter]In this paper we tested the performance of the Species Distribution Models (SDMs) to provide reliable guidelines for planning a collection mission for quinoa's wild ancestor, Chenopodium hircinum, across Argentina. A model was constructed by combining a prediction of the species' geographic distribution based on biocli-matic variables and herbarium specimen records. Annual temperature and precipi-tation seasonality, and mean temperature of the wettest quarter were the bioclimatic variables with the highest mean contribution to the model. Northwest and Central Argentina were the regions predicted with the highest habitat suitability. Then, SDMs predictions were tested by conducting a field-collection trip during February 2017 to previously unsampled localities. In each locality we determined whether or not C. hircinum was present. The model performed relatively poorly, as a significant number of collected populations came from localities with a low estimated proba-bility of occurrence. On the other hand, the Humid Pampas, a region with abundant previous reports, yielded just one sample. This result is relevant for the development of new SDMs to plan subsequent field-collection trips for C. hircinum and points to further improvement of these models based on information gathered here. The field-collection trip produced 59 samples of C. hircinum populations covering a wide range of contrasting environments in terms of latitude, elevation, temperature and precip-itation regimes. Moreover, a large number of collected populations came from Dry Chaco and High Monte ecoregions, which are very hot environments with maximum temperatures often higher than 25 °C during C. hircinum's growing season (spring- summer). A comparative analysis of adaptability ranges between quinoa cultivars from the whole range of the species distribution and collected wild C. hircinum populations from Argentina reveals that quinoa's wild ancestor explores a hotter range and suggests it can increase quinoa's adaptation range and yield stability by providing new allelic variation to breeding programs.
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Membrane bioreactor for wastewater treatment: Fouling and abatement strategies(Elsevier, 2023-02-27) [Book Chapter]A membrane bioreactor (MBR) is considered to be one of the advanced technologies used to produce high-quality effluents. However, membrane fouling is the main hindrance to the widespread use of MBR technology. Fouling reduction can make the technology more sustainable and comparable to conventional biological treatment technology in energy footprints. The characteristics of the wastewater, the reactor's operational parameters, and the characteristics of the membrane affect the fouling. This chapter discusses the types of configuration of an MBR and compares the anaerobic MBR (AnMBR) and aerobic MBR. Factors affecting membrane fouling are discussed in detail. In addition, potential physiochemical and biological fouling abatement strategies are reviewed.
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Monitoring agricultural ecosystems(Elsevier, 2023-02-17) [Book Chapter]Unmanned aerial system (UAS)-based sensing technologies are considered an invaluable component of digital agriculture through delivery of timely and accurate information that can contribute to food and water security and sustainable food production. Precision agriculture, which focuses on optimization procedures to increase food production with fewer inputs, is already benefiting from regular UAS-derived information on crop function, performance, and condition. UAS can also benefit yield prediction-related studies, further facilitating effective management and planning aspects of the production chain. While red–green–blue and multispectral sensors provide a means for many operational crop mapping and monitoring solutions, detection of plant disease and assessment of evapotranspiration of crops generally require more exploratory analysis of hyperspectral and thermal infrared data, respectively. This chapter provides an overview of UAS-based crop monitoring applications suitable for precision agriculture and demonstrates, through two separate case studies focusing on macadamia and orange trees, the UAS data processing chain and workflows required for individual tree crown delineation, crown area and tree height measurements, tree condition assessment and identification of evaporative fractions, canopy temperature, and associated water stress. This chapter concludes with a discussion of best practices for UAS-based data collection and processing, as well as an exploration of challenges and prospects for delivering valuable agricultural insights to meet the future demands for increasing food production.
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Membrane sensors for pollution problems(Elsevier, 2023-02-08) [Book Chapter]The in-field detection of pollutants and the assessment of the quality of industrial exhausts and wastewaters are essential activities in the environmental management. Thus, the modern society continuously demands the development of cost-effective, quick, real-time, and reliable sensors. Membrane technology consists of a solid background for the development of advanced sensors to detect pollutants. In fact, highly selective membranes responsible for the molecular recognition and/or selective capture of target analyte(s) are the core of highly sensitive sensors. In this chapter, we discuss the implementation of membranes in sensors aimed to detect gaseous pollutants and elucidate the mechanism of detection. Also, the key features of membranes for the detection of nano/microplastics and pathogens, two of the trending emerging questions, are highlighted.
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Preface(WORLD SCIENTIFIC, 2023-02-07) [Book Chapter, Editorial]Quantum and kinetic models have been widely used in the modeling and description for many problems arising in science and engineering with quantum effect (wave-particle duality and/or quantization) and/or particle interaction. Over the last two decades, quantum and kinetic models have been adapted for the kinetic description of emerging applications in biology and social science, such as cell migration, collective motion of active matter, network formation and dynamics in social sciences, coherent structures in crowd and traffic dynamics, flocking, swarming, and for the modeling of tremendous new experiments in physics, such as Bose-Einstein condensation, fermion condensation, quantum fluids of light, degenerate quantum gas, graphene and 2D materials, etc. These new surprising experiments and emerging applications generate a big wave in the study of challenging quantum and kinetic problems in terms of modeling, analysis and simulation. In fact, the new experiments and applications also call for greater participation of mathematicians and computational scientists to address some fundamental questions related to quantum and kinetic problems, to work together with applied scientists from the modeling to computational stages, to provide mathematical analysis for justifying different models, and to design efficient and accurate computational methods. A thematic program on Quantum and Kinetic Problems: Modeling, Analysis, Numerics and Applications was held at the Institute for Mathematical Sciences (IMS) at the National University of Singapore (NUS) from September 2019to March 2020.