Experimental Run Research Articles

Methane fermentation to methanol (biological gas‐to‐liquid process) usingMethylotuvimicrobium buryatense5GB1C

AbstractMethanol is a potential alternate liquid transportation fuel for blending with gasoline. Biochemical conversion of methane to methanol is a green process for methanol production. This paper reports biochemical methanol production using type I γ‐proteobacteriaMethylotuvimicrobium buryatense, which has particular importance from the viewpoint of scalable biological gas to liquid processes for industrial application. A statistical design of experiments (at the serum bottle level) was used to optimize fermentation parameters. Enhancement in methanol accumulation was attempted using methanol dehydrogenase inhibitors. This was followed by a validation experiment run in a bioreactor at optimum conditions. At optimum conditions (pH = 7, phosphate concentration = 140 mM, temperature = 25°C) and optical density (600 nm) of 0.3, a methanol titer of 8.54 mM was achieved in 24 h (methane conversion = 20.8%). The addition of a methanol dehydrogenase inhibitor (0.5 mM Ethylenediaminetetraacetic acid) enhanced the methanol concentration to 10.37 mM. Experiments in a 3.7 L bioreactor using 1.68 bar headspace pressure and optical density (600 nm) of 0.1 yielded 23.7 mM methanol in 24 h (methane conversion = 47.8%). The methanol titers obtained usingM. buryatense5GB1C in 24 h fermentation are significantly higher than several previously reported methanotrophs. These results demonstrate the potential ofM. buryatense5GB1C for the biochemical synthesis of methanol.

Plant based surfactant combined sonication pretreatment on food waste for biomethane generation: Cost and energy procurement

Food waste (FW) can be used as an appropriate feedstock for bioenergy generation. However, the rate limiting hydrolysis step during Anaerobic Digestion (AD) limits the biodegradation of substrate. Hence, pretreatment of food waste is essential prior to AD to circumvent the rate limiting step. Ultrasonic pretreatment of FW has been restricted owing to its greater energy requirement, aggregation of FW particles and lignin binding to methanogenic enzymes during biomethanation process. These limitations could reduce the efficiency of the whole treatment. In this study an effort has been made to enhance the hydrolysis and to improve the methanogenesis by pretreating the FW with plant-based surfactant (saponin) coupled ultrasonic pretreatment. The ultrasonic alone (US alone) pretreatment experimental run was done by varying the ultrasonic power from 80 to 180 Watt and pretreatment time from 0 to 20 min. The ultrasonic combined saponin (US-saponin) pretreatment experimental run was done by varying the time from 0 to 10 min and saponin dosage from 0.0005 to 0.008 g/g TS. The outcome reveals that the specific energy input of 5052 kJ/kg TS, saponin concentration of 0.002 g/g SS, and 2 min pretreatment time was optimum to achieve the maximum solubilization of 37 % in US- saponin sample. The US alone demands a specific energy input of 25263 kJ/kg TS and a pretreatment time 10 min to achieve the maximum solubilization of 30.5 %. The US-saponin pretreatment shows 269 mL/gCOD of methane production, higher than the US alone (148 mL/gCOD) and control (53 mL/gCOD). Regarding energy and cost assessment, the US- saponin pretreatment shows 12.07 USD/ton of net profit, greater than the US alone pretreatment (−260.8 USD/ton).

Effects of power-assist and load torque on vibration characteristics of electric bicycles

There is a growing demand for electric bicycles from environmental and health perspectives. The electric bicycles are power-assisted by electric motors. In order to increase their power output and performance, it is necessary to understand their effects on the vibration characteristics of electric bicycles. However, it is not clear how the vibration characteristics of the bicycle are affected by the electric motors' assist for various load torques. This presentation discusses the effects of power-assist on the vibration response of the electric bicycle for various load torques. By conducting experimental modal analyses and running tests of the bicycle under various conditions, the vibration components caused by the structural vibration mode of the bicycle and by the electromagnetic effects of the power-assist were identified. Frequency components related to the rotational frequency of the tire were observed. Also, regardless of the load condition, frequency components related to mechanical resonance, and sidebands of the switching frequency caused by the power-assist were observed. Moreover, as the load torque increases, the vibration acceleration also increases especially at the handlebar. Furthermore, when the assist is not activated, the vibration acceleration is proportional to the magnitude of the load torque in the ride comfort affected frequency range.

Analysis of the hydraulic interference between the baffles and the composite hydraulic structure

The purpose of the present study is to examine the influence of baffles presence at downstream system on weir gate hydraulic response. Two baffles configuration (triangle and angle shapes) are installed in bed flume. Two different spacing are used between the baffles and two different directions for baffles are also adopted. The study tries to investigate the variation in upstream Froude number, downstream Froude number, Reynolds number, actual discharge, discharge coefficient, downstream average water depth and the hydraulic system efficiency which is expressed as function of downstream water depth. It has been shown that the number of baffles has a direct and significant impact on flow hydraulic characteristics of weir-gate structure regardless of the spacing between baffles and the direction of baffles related to flow. Baffles number and spacing have essential impact on the water flow velocity of system and this impact leads to increase the flow resistance. The results clarify that the upstream Froude number, downstream Froude number, Reynolds number, actual discharge and discharge coefficient are decreased with the increase in baffles number except the average downstream water depth which increases with increase in baffles number. The efficiency of hydraulic system gives a good indicator for using baffles with weir-gate structure. At the end this paper shows a fruitful result of efficiency. This experiment run condense on the baffle’s numbers and directions with respect to the water flow direction at the downstream regime. So, the rises in the water level relies on the numbers and directions of the baffles as compare to the case without using baffles at the flume downstream region. The actual discharge and weir-gate discharge coefficient are more sensitive to the increase in the baffles’ numbers and the baffles direction with respect to the water flow direction

Data-driven estimation of scalar quantities from planar velocity measurements by deep learning applied to temperature in thermal convection

The measurement of the transport of scalar quantities within flows is oftentimes laborious, difficult or even unfeasible. On the other hand, velocity measurement techniques are very advanced and give high-resolution, high-fidelity experimental data. Hence, we explore the capabilities of a deep learning model to predict the scalar quantity, in our case temperature, from measured velocity data. Our method is purely data-driven and based on the u-net architecture and, therefore, well-suited for planar experimental data. We demonstrate the applicability of the u-net on experimental temperature and velocity data, measured in large aspect ratio Rayleigh–Bénard convection at Pr=7.1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{Pr} =7.1$$\\end{document} and Ra=2×105,4×105,7×105\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{Ra} =2\ imes 10^5,4\ imes 10^5,7\ imes 10^5$$\\end{document}. We conduct a hyper-parameter optimization and ablation study to ensure appropriate training convergence and test different architectural variations for the u-net. We test two application scenarios that are of interest to experimentalists. One, in which the u-net is trained with data of the same experimental run and one in which the u-net is trained on data of different Ra\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{Ra}$$\\end{document}. Our analysis shows that the u-net can predict temperature fields similar to the measurement data and preserves typical spatial structure sizes. Moreover, the analysis of the heat transfer associated with the temperature showed good agreement when the u-net is trained with data of the same experimental run. The relative difference between measured and reconstructed local heat transfer of the system characterized by the Nusselt number Nu\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{Nu}$$\\end{document} is between 0.3 and 14.1% depending on Ra\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{Ra}$$\\end{document}. We conclude that deep learning has the potential to supplement measurements and can partially alleviate the expense of additional measurement of the scalar quantity.

Efficient denoising of cold atom images using the optimized eigenface recognition algorithm.

Absorption imaging is a widely employed technique for detecting cold atom clouds and Bose-Einstein condensates (BECs). There are situations where such images may suffer from unwanted interference fringes, resulting in uncertainties in determining crucial parameters such as the atom number, temperatures, or even dynamics in small timescales. Reducing the acoustic vibrations and recording image frames synchronized with the source of such vibrations can largely reduce these fringes; however, some residual fringes still need to be taken care of for precision measurements. In this study, we propose an efficient image post-processing technique for noise reduction that effectively mitigates such interference patterns. Our approach makes use of the well-known eigenface recognition algorithm, combined with an optimized masking strategy applied to the image of the atomic cloud using a small number of basis sets. The use of a limited basis set ensures minimal computational time, allowing this method to be readily incorporated into every experimental run. Through the application of our technique, we successfully reduce interference fringes and improve the accuracy of parameter estimation by 50% in the absorption imaging of cold atoms. The temperature uncertainties of cold 87 R b atoms are reduced by more than 50% after the algorithm is applied. This approach holds significant promise for enhancing the reliability and precision of experimental measurements in diverse research fields where absorption imaging is employed.

Investigation into bevel plate optimal angle required to improve nut cracking in a centrifugal nut cracker

In order to ensure that most of the nuts discharged vertically from the rotor do not escape uncracked through the cracked nut mixture outlet; an investigation into optimal angle for palm nut cracker bevel plate assembly required to increase efficiency of the cracking process was carried out at three different feed gates. In this study, the cracked nut mixture outlet at the cracking drum of an existing centrifugal palm nut cracker was modified to include bevel plate having adjustable angle of inclination. Dried and ready to crack mixed varieties (Pisifera, Tenera and Dura) of palm nuts were sourced and moisture content determined using oven dry method. The nuts (18.6% moisture content wet basis) were subjected to impact at different angles ( = 90, 55, 50, 45, 40, 35, 30, 25 and 200) of bevel plate per feed gate aperture area, A (18, 27 and 36 cm2) of the modified palm nut cracker. The = 90o was full opening of the cracked nut mixture outlet of the existing nut cracker. For each experimental run, ninety (90) nuts were subjected to impact at 3712 rpm rotor speed. The total time taken for each set of the products to be discharged was also noted as t. Data were collected in duplicate and analyzed using Statistical Package for Social Scientists [SPSS] version 20 and Microsoft Excel TM. The performance indices [percentage of nuts cracked with release of whole and split kernels (% NCKR), percentage of uncracked nuts (%UC), percentage of partially cracked nut (%PC) and percentage of uncracked and partially cracked nuts (%UP)], bevel plate efficiency (%CEBP) and nut cracking rate (NCR) were plotted against per feed gate aperture area. The optimum performance indices (%NCKR = 96.67%, %UC = 3.33% and %UP = 3.33% and %PC = 0.00%), %CEBP (93.88%) and NCR = 5 nuts / sec were obtained at = 250 and A =18 cm2. This implies that the modified nut cracker when run at feed rate of 5 nuts/sec and = 250 would improve cracking operation by 93.88% of nuts that should have escaped uncracked at the cracked nut mixture outlet. Hence, it is necessary to incorporate bevel plate.

Model Designed to Acquire an Optimized Performance Implementing L27 Orthogonal Array for the Prandtl Fluid Flow Maneuvering Grey Relational Theory

To design a resourceful model, the optimization technique is executed in the present analysis which helps in attaining a theoretical framework of high productivity which assists in minimising the cost and time. The novelty lies in optimising the responses of surface drag and enhanced heat and mass transfer which is so far not reported in the literature. The stretched geometry is contemplated as replicating a polymer sheet, which endorses substantial application in industries with the effects of linear radiation, thermo-diffusion, and diffusion-thermo impacts. The L27 orthogonal array is explained using the Taguchi optimization method to record the signal-to-noise ratio for the response of heat and mass transfer rate individually. Multi-response optimization is carried out using grey relational analysis, producing grey relational grades and respective ranks. Numerical solutions are retained using the Runge-Kutta Fehlberg method. Parametric results revealed that intense radiation contributes to amplifying the rate of heat transfer and having a strong impact on the diffusion-thermo effect. Elevated mass transmission rate can be procured for higher thermophoresis parameters and Soret numbers. On the other hand, the lowest transfer rate of mass is received at a higher value of the Schmidt number. Outcomes of the work showcase that the 22nd experimental run with the curvature parameter at 3.5, Prandtl number at 7.1, Elastic parameter at 3, radiation parameter at 1.6, and thermophoresis parameter at 0.4 is an optimized level for Nusselt number and Sherwood number. Analysis of variance on grey relational grade reveals that curvature parameter has the largest contribution on grey relational grade of about 41.16%, followed by radiation parameter with 38.96% contribution. The least contribution, as stipulated by Prandtl number, is about 2.07%.

Impact of offshore wind farms on a tropical depression through the amplification effect by the downstream mountainous terrain

The influence of offshore wind farms in the northern South China Sea on a tropical depression far away (over the Beibu Gulf) is investigated through a fully coupled atmosphere-ocean model. Results show that in the experimental run with the offshore wind farms, the tropical depression located downstream of the wind farm are maintained for longer periods of time. This is mainly due to the stronger convection on the western side of the tropical depression. The stronger convergence in the lower level and divergence in the upper level caused by low-level gravity waves become the key dynamic condition. The primary factor influencing such gravity waves is the rapid decrease of the low-level vertical wind shear. The diagnostic analysis shows that wind-farm wakes affect the local low-level vertical velocity through the downstream mountainous terrain, which makes the vertical momentum term as the main contributing term affecting the variation of the horizontal momentum and subsequently the low-level vertical wind shear. This amplified impact of wind farms through the mountainous terrain may also occur in other regions.

NSFuzz: Towards Efficient and State-Aware Network Service Fuzzing - RCR Report

We provide artifacts to reproduce the evaluation results of our article: “NSFuzz: Towards Efficient and State-Aware Network Service Fuzzing”. The provided artifacts can be downloaded from https://zenodo.org/record/7134490 . It includes 14 docker containers, several scripts for execution and analysis, one additional proof for the crash results, and six related documents for the running of experiments. We claim for all three badges, i.e., Available, Functional, and Reusable. This report gives instructions on how to reproduce the answers which mainly involve basic operations on the Ubuntu operating system.

Smart materials for experimental tectonics: Viscous behavior of magnetorheological silicones

Magnetorheological (MR) materials are a relatively new class of materials whose mechanical properties can be controlled by a magnetic field. In this work, we investigate the viscous behavior of MR silicones, i.e., mixtures of Polydimethyl Siloxane (PDMS) and carbonyl iron powder, for analog modeling purposes. The rheological properties were determined using a parallel plate rheometer equipped with a variable strength electromagnet. We measured viscosity, yield stress and response time of MR silicone samples in a wide range of strain rates as a function of concentration of carbonyl iron powder and applied magnetic field. We find that MR silicones in the unmagnetized state show a transition from Newtonian to shear-thinning behavior for increasing strain rates. In the magnetized state, MR silicones behave as Herschel-Bulkley, shear-thinning fluids. Viscosity, yield stress and power-law exponent increase as a function of carbonyl iron powder concentration and magnetic field. A simple experiment is presented to demonstrate how the rheology of the analog material can be easily controlled during an experimental run, a condition that is challenging to achieve with other materials commonly used in experimental tectonics.

Characteristics of Pore Morphology in Aluminum Alloy Foams Fabricated by Semi-Solid Route among Multiple Experimental Runs

A semi-solid route is expected to be a fabrication method that can fabricate aluminum alloy foams with a variety of mechanical properties, but the allowance fluctuation of the fabrication conditions of aluminum alloy foams with high reproducibility is not clear. The objective of this study was to reveal the allowance fluctuation between the setting temperature and the actual temperature of the melt to fabricate stable foams, having pores with small pores and high circularity, and the influence of the increasing volume fraction of the solid on the pore morphology. Al-Si alloy foams were fabricated five times by adding a blowing agent into a semi-solid slurry under the same setting fabrication conditions, such as the temperature and concentration of oxygen in the atmosphere. The results of small relative standard deviations of pore diameter and circularity indicated that the conducted fabrication process had high reproducibility, even if the volume fraction of the solid changed in a range of 5%. When the volume fraction of the solid exceeds the minimal fraction of primary crystals for prevention of drainage, the clogging effect works more efficiently because the ratio of clogged cell walls increases. Additionally, the preferred range of the volume fraction of the solid for the fabrication of stable foam was revealed to be around 15% to 35%.

Gas-liquid hydrodynamics of a fractal flow mixer

Gas-liquid hydrodynamics of a micro-structured device (fractal flow mixer) was experimentally investigated. Experiments were conducted for a range of liquid-to-gas superficial velocity ratios (VSL/VSG). High-speed imaging was used to identify the flow regimes inside the microchannels of the device at different VSL/VSG. At different VSL/VSG, two or more flow regimes were observed simultaneously in different micro-channels. Consequently, a new flow regime map was developed. An optical probe was used to measure the bubble mean size and velocity. The effect of the VSL/VSG towards the bubble mean size, mean velocity, and frequency were analyzed. The bubble mean size decreases with the increase of the VSL/VSG, which can be attributed to the uniform shearing of gas slugs across all channels. To check the consistency of the fractal flow mixer in producing gas bubbles over a single experiment run, the global relative standard deviation (RSD) was used. The fractal flow mixer was able to generate equal flow distribution across the 16 outlets and maintain a Taylor flow over a range of VSL/VSG. . However, depending on the VSL/VSG, the GB and GS vary to a certain extent, governed by the capillary effect and the back-pressure.

Development of a new composite LDH/TiO2-3D for degradation of sulfaguanidine under UV and visible light: Experimental design, kinetic and mechanisms

Constructing 3D heterostructures has been considered an effective approach to enhance the photocatalytic activity of materials. However, the preparation of 3D heterostructures is always a complex process. In this paper, three-dimensional (3D) spherical TiO2 immobilized on Cu3AlCO3 Layered Double Hydroxides (LDH) was successfully synthesized using the impregnation method. The structure, morphology, and property of Cu3AlCO3-LDH/xTiO2-3D were investigated by X-ray diffraction (XRD), FTIR spectroscopy, scanning electron microscopy (SEM), energy dispersive X-ray (EDX), UV-Visible diffuse reflectance spectroscopy. The photocatalytic properties of composite materials were evaluated by degradation of sulfaguanidine (SGD) antibiotic under simulated solar irradiation. To optimize the photocatalysis process, an experimental design methodology was used. The experimental design utilized in most published works involves simple matrices that focus on quantitative factors. In contrast, our work enables the study of both qualitative factors (dissolved oxygen concentration) and quantitative factors (pH, catalyst dose and temperature) for both responses using a mixed matrix (D‐optimal) and a multiplicative model. To achieve this, 22 Run of experiments designed by the AZURAD® software. The optimal values of pH, catalyst dose, temperature, and dissolved oxygen concentration were found to be 8, 0.23 g.L−1, 25 °C, and 2 mg.L−1, respectively. The transformation product and possible degradation pathways of SGD were identified through Orbitrap LC/MS. Additionally, the present composite photocatalysts exhibited satisfactory re-usability for at least four cycles. Due to the facile synthesis process, higher photocatalytic activity under visible light irradiation and satisfactory re-usability, these composites can be considered as potential catalysts for degrading pharmaceutical pollutants in wastewater treatment.

Novel Algebraic Matrix Method Used to Generate Linear Equation for Surface Roughness and Material Removal Rate during Wet/Dry Turning Operation on MMCs Al6061-T6/SiC

Stir casting process is well known for reinforcement of ceramic particle in aluminium. Due to improved properties of Al6061-T6/SiC particulate metal matrix composites have attracted by industry as well as received wider attention of material expertise. The purpose of this study is to evaluate the turning process parameters through algebraic matrix which is unique approach. Also studied effects of spindle speed, feed, SiC silicon carbide-3% and 6%, depth of cut and nose radius on modifier element for instance surface roughness Ra and material removal rate MRR in both dry and wet condition. In addition to optimize the turning process parameters are on Al6061-T6/SiC 3% and 6% with a coated tungsten tool. The experimental runs are designed using the taguchi based multiple factorial design DOE and their outcomes are analyzed using Analysis of Variance ANOVA. Mathematical models are established using algebraic matrix to represent the relationship among turning process parameters as independent variables, surface roughness and material removal rate as dependent variables. For every experimental run, a same cutting insert was used to encourage accurate reporting of the surface roughness and material removal rate. The statistical variations revealed that the main effect of spindle speed, feed, SiC silicon carbide-3% and 6%, depth of cut and nose radius are influenced the surface roughness and material removal rate. Moreover, Built-up-edge BUE formation was observed at every combinations of machining parameters such as spindle speed, feed, SiC silicon carbide-3% and 6%, depth of cut and nose radius which affected the surface quality negatively. The proximity of predicted results and experimental results provide proof that the algebraic matrix – DOE method has successfully established the predictive models. It is strongly suggested SiC silicon carbide 3% and 6% are successfully reinforced in Al6061 as well as optimize turning process parameters in wet condition than dry condition. Mathematical models for surface roughness and material removal rate are found to be statistically significant in wet condition.

Process parameters optimization in machining of monel 400 alloy using abrasive water jet machining

This research examines the optimum machining features for abrasive water jet cutting of Monel 400 alloy. This alloy system faces significant challenges in conventional machining and can be surpassed by using the coolest machining technology, such as AWJM. In this experimental investigation, the water beam jet pressure (AP), the nozzle jet traverse speed (NS), and the abrasive flow rate (AMF) were used to explore the kerf taper angle (Kta) and surface roughness (Ra) response variables. The experimental L-9 layout (Taguchi's/L-9(−|-) standard orthogonal array) was used to run the experiment. The S/N ratios for each experimental run were determined using a mono-output response optimization technique. The input characteristics, such as water beam jet pressure (AP) and abrasive flow rate (AMF), were determined to have the most substantial effects on kerf taper angle (Kta) and surface roughness (Ra). While increased water pressure (AP) caused a narrowed jet, reducing the kerf taper angle (Kta) and surface roughness (Ra). Its simultaneous abrasive mass flow rate (AMF) increase causes constant erosion on the cutting front, resulting in a smooth surface roughness (Ra) and less kerf taper angle (Kta). Confirmation tests were carried out using the optimal input parameter combinations found by the statistical program to establish effective solutions to the machining.

Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes

Abstract. Wildfires influence not only ecosystems but also carbon and water fluxes on Earth. Yet, the fire processes including the occurrence and consequences of fires are still limitedly represented in land surface models (LSMs). In particular, the performance of LSMs in estimating burned areas across high northern latitudes is poor. In this study, we employed the daily burned areas from the satellite-based Global Fire Emissions Database (version 4) (GFED4) into the Community Land Model (version 5.0) with a biogeochemistry module (CLM5-BGC) to identify the effects of accurate fire simulation on carbon and water fluxes over Alaska and Eastern Siberia. The results showed that the simulated carbon emissions with burned areas from GFED4 (i.e., experimental run) were significantly improved in comparison to the default CLM5-BGC simulation, which resulted in opposite signs of the net ecosystem exchange for 2004, 2005, and 2009 over Alaska between the default and experimental runs. Also, we identified that carbon emissions were more sensitive to the wildfires in Alaska than in Eastern Siberia, which could be explained by the vegetation distribution (i.e., tree cover ratio). In terms of water fluxes, canopy transpiration in Eastern Siberia was relatively insensitive to the size of the burned area due to the interaction between leaf area and soil moisture. This study uses CLM5-BGC to improve our understanding of the role of burned areas in ecohydrological processes at high latitudes. Furthermore, we suggest that the improved approach will be required for better predicting future carbon fluxes and climate change.

Nitrogen transformation dynamics in macrophyte-assisted high-rate vermifilter treating real domestic sewage

Due to economic and ecological sustainability, vermifiltration has become a popular alternative to conventional wastewater treatment methods. However, the science behind nitrogen removal in vermifiltration has yet to be adequately explored. Additionally, no study is available on assessing the performance of vermifilters/macrophyte-assisted vermifilters (VFs/MAVFs) at higher hydraulic loading rates (HLRs), which has been a significant loophole regarding the vermifiltration technology. The present study investigated the performance of a MAVF in terms of nitrogen transformation dynamics during the treatment of real domestic sewage subjected to higher HLRs. The designed MAVF ensured a decent removal of ammonium nitrogen (NH4+-N), total Kjeldahl nitrogen (TKN), organic nitrogen, and total nitrogen (TN). In contrast, there was a considerable gain in effluent nitrate nitrogen (NO3−-N) concentration than its influent concentration. The highest removal of NH4+-N (98.2 ± 0.7 %), TKN (99 ± 0.5 %), and organic nitrogen (100 %) corresponded to the experimental run with an influent COD of (200 ± 25) mg/L and HLR of (3 ± 0.1) m3/m2-d, whereas the experimental run with an influent COD of (200 ± 25) mg/L and HLR of (7 ± 0.2) m3/m2-d resulted in the maximum increase in effluent NO3−-N concentration (73 ± 10.6 times its influent concentration). The maximum TN removal of (87 ± 2.2) % was achieved for the experimental run with an influent COD of (700 ± 45) mg/L and HLR of (3 ± 0.1) m3/m2-d. The present research reinforces the suitability of MAVF technology as a cost-effective and ecologically benevolent bio-remediation alternative for domestic sewage.

Optimization of Azadirachta indica leaf extract mediated cerium oxide nanoparticles synthesis, characterization, and its applications

The present study focuses on the novel synthesis of cerium oxide (CeO2) nanoparticles from cerium nitrate hexahydrate by using Azadirachta indica (neem) leaf extract. The parameters associated with the green synthesis process were optimized utilizing the response surface methodology (RSM) paired with the genetic algorithm (GA) to produce a higher yield rate. The experiment run order for the CeO2 green synthesis is then generated using the central composite design in RSM. The regression equation was used as an optimization function, and the optimal values were identified through GA. Using optimized input process parameters, 0.3 g/10 mL of precursor concentration and 5 mL of Azadirachta indica leaf extract centrifuged for 20 min in the green synthesis process resulted in a maximum yield of 15.49 % CeO2 nanoparticles. The synthesized CeO2 nanoparticles are characterized by Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), energy dispersive spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), particle size distribution, and zeta potential analyses, which are used to ensure their presence in the green synthesis process. Subsequently, the green synthesized CeO2 nanoparticles are dosed as an additive to the cotton seed biodiesel (CSB) at different proportions of 25, 50, and 75 ppm, respectively. The prepared biofuel's physico-chemical properties were measured as per ASTM standards and are closer to the diesel fuel. As a result, it was noted that optimizing the green synthesis process parameters gives a maximum rate of CeO2 yield. It is possible to efficiently use the CSB with CeO2 nanoparticles as a suitable replacement for diesel fuel.

Computational analysis on mechanostructural properties of hydroxyapatite–alumina–titanium nanocomposite

AbstractIn this research, Taguchi–grey relational analysis has been applied to mitigate the insufficient assumptions made on the optimization of mechanical and structural (mechanostructural) properties of synthesized hydroxyapatite (HAp)–alumina–titanium nanocomposite. This nanocomposite has already been developed and studied in the previous study. This paper employs the L9 (3**3) orthogonal array, including displaying factors and levels of 3, 5, 7 wt % for alumina, 5, 10, 15 wt % for titanium, and 1100, 1150, 1200 °C sintering temperature. The computational analysis presents the predicted mechanostructural grey relational response as 0.7271, higher than the highest response shown in the ninth experimental run. The optimal control factors are analyzed to be 7 wt % alumina, 15 wt % titanium, and 1200 °C sintering temperature. The obtained result elucidates the hypothesis that a singular response optimization is not enough in the fabrication of biomedical material, disproving the assumption made in the previous literature. Importantly, to fabricate a high clinical grade HAp–alumina–titanium nanocomposite, titanium is the most invaluable contributor with a contribution of 49.11%, followed by alumina (45.52%), and then sintering temperature (3.2%). Although the confidence level and probability distribution analysis show that all the experimental mechanostructural responses were within the 95% confidence level, the employment of the predicted optimal factors is strongly recommended for experimentation.