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Multifunctional fluidized bed reactors for process intensification
No full textPublisher Copyright: © 2024 The Author(s)Fluidized bed reactors (FBRs) are crucial in the chemical industry, serving essential roles in gasoline production, manufacturing materials, and waste treatment. However, traditional up-flow FBRs have limitations in applications where rapid kinetics, catalyst deactivation, sluggish mass/heat transfer processes, particle erosion or agglomeration (clustering) occur. This review investigates multifunctional FBRs that can function in multiple ways and intensify processes. These reactors can reduce reaction steps and costs, enhance heat and mass transfer, make processes more compact, couple different phenomena, improve energy efficiency, operate in extreme fluidized regimes, have augmented throughput, or solve problems inherited by traditional reactor configurations. They address constraints associated with conventional counterparts and contribute to favorable energy, fuels, and environmental footprints. These reactors can be classified as two-zone, vortex, and internal circulating FBRs, with each concept summarized, including their advantages, disadvantages, process applicability, intensification, visualization, and simulation work. This discussion also includes shared considerations for these reactor types, along with perspectives on future advancements and opportunities for enhancing their performance.Peer reviewe
Impact of rainfall on air temperature, humidity and thermal comfort in tropical urban parks
No full textPublisher Copyright: © 2024 Elsevier B.V.Urban areas in hot and humid tropical regions are frequently exposed to uncomfortable thermal levels. A well-developed urban heat mitigation strategy is increasing vegetation infrastructure, even though the impact differs based on regional climate. In this study we have evaluated the impact of rainfall on air temperature, humidity and thermal comfort inside a large urban park in Singapore, based on measurement campaigns. A comparison between the park and an urban site is presented. Results show that rainfall significantly reduces air temperature and improves thermal comfort levels, not only right after the rain event but also in the after-event dry period. The cooling potential of rainfall depends not only on the intensity and duration of the event, but also on the weather conditions after the event, especially incoming solar radiation. The maximum cooling potential of rainfall is lower in the park but also the park tends to stay cooler longer (lower recovery of air temperature recuperation) after the rain event. An increase of humidity after the event does not prevent an improvement in thermal comfort levels inside the park. Overall, results provide a grounded argument for the promotion of use of parks after rain events, especially during daytime.Peer reviewe
Verification of scaling behavior near dynamic phase transitions for nonantisymmetric field sequences
No full textPublisher Copyright: © 2024 American Physical Society.We investigate the scaling behavior of the magnetic dynamic order parameter Q in the vicinity of the dynamic phase transition (DPT) in the presence of temporal field sequences H(t) that are periodic with period P but lack half-wave antisymmetry. We verify by means of mean-field calculations that the scaling of Q is preserved in the vicinity of the second-order phase transition if one defines a suitable generalized conjugate field H∗ that reestablishes the proper time-reversal symmetry. For the purpose of our quantitative data analysis, we employ the dynamic equivalent of the Arrott-Noakes equation of state, which allows for a simultaneous scaling analysis of the period P and the conjugate-field H∗ dependence of Q. By doing so, we demonstrate that both the scaling behavior and universality are preserved, even if the dynamics is driven by a more general applied field sequence that lacks antisymmetry.Peer reviewe
Biomass extract of green macroalga Halimeda opuntia assisted ZnO nanoparticles: preparation, physico-chemical characterization, and antibacterial activity against Vibrio harveyi
No full textPublisher Copyright: © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Zinc oxide (ZnO) nanoparticles are particularly interesting for antibacterial applications, unlike many other forms of metal and metal oxide nanoparticles. ZnO is an FDA-approved nanomaterial that is widely considered safe, efficient, and non-toxic at lower doses. In this study, biomass extract of Halimeda opuntia assisted preparation of ZnO nanoparticles and their antibacterial effect against aquaculture pathogenic Vibrio harveyi. X-ray diffraction (XRD) studies revealed that the ZnO nanoparticles are crystalline in nature with hexagonal wurtzite structure. The crystallite size (D) of ZnO nanoparticles was calculated from the full width at half-maximum of the most intense peak (101) using Scherrer’s formula and was around 33 nm. Furthermore, the various lattice parameters such as lattice constants (a and c), c/a ratio, unit cell volume (V), interplanar angle (φ), dislocation density (δ), and measure of atom displacement (μ) were calculated. Crystalline quality and binding energy were also investigated using X-ray photoelectron spectroscopy (XPS). From XPS studies, the chemical valence of Zn at the surface of ZnO nanoparticles was found to be + 2 oxidation state. The morphologies and elemental composition have been studied using SEM equipped with EDAX. The identification and composition of the major bioactive compounds present in the biomass extract of H. opuntia were characterized using GC–MS analysis. Furthermore, antibacterial test was performed by well diffusion assay and bacterial growth kinetics studies against shrimp pathogenic V. harveyi. The results revealed that ZnO nanoparticles at 1, 2.5, 5, 7.5, and 10 µg mL−1 caused 5, 10, 13, 16, and 19 mm (diameter) growth inhibition zone against V. harveyi, respectively. Graphical abstract: [Figure not available: see fulltext.]The author KG thanks the Ministry of Earth Sciences (MoES)-Earth Science and Technology Cell (ESTC) under Marine Biotechnological Studies, Government of India, for the financial assistance (MoES/11-MRDFIESTC-MEB (SU)/2/2014 PCIII). The authors KV, DM, SM, and MR thank the management of Sathyabama Institute of Science and Technology (SIST) for its strong support to carry out research activities.Peer reviewe
Multilayer GZ/YSZ thermal barrier coating from suspension and solution precursor plasma spray
No full textPublisher Copyright: © 2023 The AuthorsGas turbines rely on thermal barrier coating (TBC) to thermally insulate the nickel-based superalloys underneath during operation; however, current TBCs, yttria stabilised zirconia (YSZ), limit the operating temperature and hence efficiency. At an operating temperature above 1200 °C, YSZ is susceptible to failure due to phase instability and CMAS (Calcia-Magnesia-Alumina-Silica) attack. Gadolinium zirconates (GZ) could overcome the drawback of YSZ, complementing each other with the multi-layer approach. This study introduces a novel approach utilising axial suspension plasma spray (ASPS) and axial solution precursor plasma spray (ASPPS) to produce a double-layer and a triple-layer TBCs with improved CMAS resistance. The former comprised suspension plasma sprayed GZ and YSZ layers while the latter had an additional dense layer deposited through a solution precursor to minimise the columnar gaps that pre-existed in the SPS GZ layer, thus resisting CMAS infiltration. Both coatings performed similarly in furnace cycling test (FCT) and burner rig testing (BRT). In the CMAS test, the triple-layer coating exhibited better CMAS reactivity, as evidenced by the limited CMAS infiltration observed on the surface.Peer reviewe
Uncertainty Aware Segmentation Quality Assessment in Medical Images
No full textPublisher Copyright: © 2024 IEEE.Image segmentation is a fundamental step in most computational biomedical image analysis pipelines. During model training and validation, we can measure segmentation performance using well-established similarity metrics like the Dice coefficient. However, once the model is deployed in a clinical scenario, this is no longer possible as manual annotations are not available. In addition, segmentation models that produce a solution with no indication of its reliability result in harder adoption by end-users. To approach these two challenges, this paper introduces a segmentation quality prediction framework that does not rely on manual annotations in test time. This framework integrates uncertainty estimates on the underlying segmentation model, which we show to be advantageous for quality scoring purposes. We validate our approach on a popular skin lesion segmentation dataset, carefully analyzing the impact of different uncertainty modeling and estimation techniques on the performance of segmentation quality prediction performance.Peer reviewe
Magneto-optical detection of non-collinear magnetization states in ferromagnetic multilayers
No full textPublisher Copyright: © 2024 IOP Publishing Ltd.We have experimentally studied the relationship in between non-collinear magnetization states in ferromagnetic (FM) multilayers and their resulting magneto-optical (MO) properties. Hereby, we observe that the phase of the complex-valued MO parameters are especially sensitive towards non-collinear magnetization states and enable their unambiguous detection. For the purpose of our experimental study, we designed, fabricated and characterized a set of epitaxial FM/NM/FM multilayers with in-plane uniaxial anisotropy, in which the non-magnetic (NM) interlayer thickness t was varied, so that tunable FM interlayer exchange coupling strength in between the two FM layers could be achieved. Furthermore, the two FM layers were made from different alloys, so that they exhibit different levels of magnetocrystalline anisotropy, which enables a collinear to non-collinear magnetization state transition upon applying a magnetic field H away from the in-plane easy axis for samples with sufficiently large t . Utilizing generalized MO ellipsometry, we determined the full reflection matrix R as a function of H and we observed that the phases of the complex-valued MO coefficients in R change with H in multilayers that have sufficiently weak interlayer coupling strength, i.e. large t, which can only happen if non-collinear magnetization states of varying non-collinearity occur in those samples. For samples with small t, corresponding to strongly exchange coupled FM layers, this effect is absent, consistent with the existence of collinear magnetization states in those multilayers for all H values.Peer reviewe
K-Means Clustering Identifies Diverse Clinical Phenotypes in COVID-19 Patients: Implications for Mortality Risks and Remdesivir Impact
No full textPublisher Copyright: © The Author(s) 2024.Introduction: The impact of remdesivir on mortality in patients with COVID-19 is still controversial. We aimed to identify clinical phenotype clusters of COVID-19 hospitalized patients with highest benefit from remdesivir use and validate these findings in an external cohort. Methods: We included consecutive patients hospitalized between February 2020 and February 2021 for COVID-19. The derivation cohort comprised subjects admitted to Hospital Clinic of Barcelona. The validation cohort included patients from Hospital Universitari Mutua de Terrassa (Terrassa) and Hospital Universitari La Fe (Valencia), all tertiary centers in Spain. We employed K-means clustering to group patients according to reverse transcription polymerase chain reaction (rRT-PCR) cycle threshold (Ct) values and lymphocyte counts at diagnosis, and pre-test symptom duration. The impact of remdesivir on 60-day mortality in each cluster was assessed. Results: A total of 1160 patients (median age 66, interquartile range (IQR) 55–78) were included. We identified five clusters, with mortality rates ranging from 0 to 36.7%. Highest mortality rate was observed in the cluster including patients with shorter pre-test symptom duration, lower lymphocyte counts, and lower Ct values at diagnosis. The absence of remdesivir administration was associated with worse outcome in the high-mortality cluster (10.5% vs. 36.7%; p < 0.001), comprising subjects with higher viral loads. These results were validated in an external multicenter cohort of 981 patients. Conclusions: Patients with COVID-19 exhibit varying mortality rates across different clinical phenotypes. K-means clustering aids in identifying patients who derive the greatest mortality benefit from remdesivir use.Peer reviewe
Real-Time Lithium Battery Aging Prediction Based on Capacity Estimation and Deep Learning Methods
No full textPublisher Copyright: © 2023 by the authors.Lithium-ion batteries are key elements in the development of electrical energy storage solutions. However, due to cycling, environmental, and operating conditions, battery capacity tends to degrade over time. Capacity fade is a common indicator of battery state of health (SOH) because it is an indication of how the capacity has been degraded. However, battery capacity cannot be measured directly, and thus, there is an urgent need to develop methods for estimating battery capacity in real time. By analyzing the historical data of a battery in detail, it is possible to predict the future state of a battery and forecast its remaining useful life. This study developed a real-time, simple, and fast method to estimate the cycle capacity of a battery during the charge cycle using only data from a short period of each charge cycle. This proposal is attractive because it does not require data from the entire charge period since batteries are rarely charged from zero to full. The proposed method allows for simultaneous and accurate real-time prediction of the health and remaining useful life of the battery over its lifetime. The accuracy of the proposed method was tested using experimental data from several lithium-ion batteries with different cathode chemistries under various test conditions.Peer reviewe