Optimal Value Research Articles

The optimization of mechanical properties of polypropylene/styrene butadiene rubber/silicon carbide nanocomposites using response surface methodology

AbstractPolypropylene is a useful and widely consumed thermoplastic with very good properties that can be mixed with a combination of rubber and nanoparticles in order to eliminate its shortcomings. In this paper, the simultaneous combination of both the toughening effect of styrene–butadiene rubber (SBR) and the reinforcing effect of silicon carbide (SiC) nanoparticles were investigated in polypropylene matrix. Mechanical properties (tensile and impact strength [TS and IS]) of compounds were analyzed using the central composite design approach in Design‐Expert software. With two factors for input variables of SBR and SiC weight percentages, and their five levels (5, 10, 15, 20, and 25) and (0, 1.5, 3, 4.5, and 6), respectively, the central composite design approach employs 11 experiments for creation of models and the analysis of variance investigations with two output responses of TS and IS. Statistical results revealed that SBR and SiC contents had a significant effect on TS, IS, and the microstructure of compounds, as confirmed by scanning electron microscopy and energy‐dispersive spectroscopy images. To maximize all mechanical properties simultaneously with desirability functions, TS and IS of the optimum sample were computed to be 21.98 MPa and 8.66 kJ/m2 in amounts of 13.45 and 2.80 weight percentage (wt%) of SBR and SiC, respectively.Highlights By increasing silicon carbide (SiC) in polypropylene/styrene–butadiene rubber (SBR), tensile strength decreases after a peak due to agglomeration effect. By increasing SiC in polypropylene/SBR, impact strength decreases after a peak due to agglomeration effect. By increasing SiC, the rubber particles' dimensions decrease according to scanning electron microscopy analysis. Simultaneous maximum of tensile strength and impact strength are 21.98 MPa and 8.66 KJ/m2, respectively. Optimum value of SBR and SiC in above maximums are 13.45 and 2.8 wt%, respectively.

Incorporation of Liquid WTP Sludge into Compacted Soil–Cement Mixtures

The sludge from water treatment plants (WTP) is a waste from the water process. This study evaluated the effect of incorporating water treatment plant (WTP) sludge, replacing the water used in compacted soil–cement mixtures. The materials were characterized by Scanning Electron Microscopy (SEM) associated with Energy Dispersive Spectroscopy (EDS) and Atomic Absorption Spectrometry (AAS). The soil, with the addition of liquid WTP sludge, presented an apparent dry specific weight (ƴd) of 1.77 gf·cm−3, the optimum moisture value in the compaction test of 15%, and the cement contents tested were 7, 11, and 14%. The specimens were molded using a WTP sludge–cement–soil mixture under the conditions mentioned above, and the simple compression results showed values within the range of 2.5 to 9.3 MPa, as specified by the Brazilian Technical Standard (NBR) 8491/2012. The hydraulic conductivity performed on the test specimen after 28 days of curing resulted in a coefficient (k) of 7.49 × 10−9 cm·s−1, classified as little permeable. The result obtained from aluminum leaching was 0.12 mg·L−1, within the maximum limit allowed by NBR 10004/2004. Therefore, liquid WTP sludge has a significant capacity for incorporation into the compacted soil–cement mixture and the potential to manufacture ecological bricks, an alternative environmentally sustainable brick.

Enhanced methanol formation in CO2 hydrogenation through synergistic copper and gallium interaction

Methanol production from CO2 hydrogenation has attracted great attention, due to the demand for carbon neutralization. Ga-promoted Cu catalysts show promising properties for methanol formation in CO2 hydrogenation, urging a fundamental investigation of the active state. In this study, we synthesized CuGa species on mesoporous SiO2, varying the amount of Ga. The structural characterizations revealed that Ga existed mostly in highly dispersed GaOx species with Cu in the form of metallic Cu clusters. The addition of Ga significantly increased the methanol formation with an optimum Ga value compared to Cu and Ga on SiO2. The surface-sensitive measurements showed the mixed form of Cu+ and Cu0 on the Cu surface exhibited, where the Cu+ state was proportional to the methanol formation rate. Therefore, we conclude that the Cu+-GaOx interface constitutes an active site for methanol production. Furthermore, we found that the Ga addition influences the oxidation state and dispersion of Cu.

Analysis of Diagnostic Efficacy of the International Ovarian Tumor Analysis ADNEX Model and the ACR O-RADS US (Ovarian-Adnexal Reporting and Data System) for Benign and Malignant Ovarian Tumors: A Retrospective Study in a Tumor Center in Northeast China.

This study is to analyze and compare the diagnostic efficacy of the ADNEX model and O-RADS in Northeast China for benign and malignant ovarian-adnexal tumors. From July 2020 to February 2022, ultrasound images of 312 ovarian-adnexal masses included in the study were analyzed retrospectively, and the properties of these masses were identified using the ADNEX model and O-RADS. The diagnostic efficiency of the ADNEX model and O-RADS was analyzed using a ROC curve, and the capacities of the two models in differentiating benign and malignant ovarian masses at the optimum cutoff value were compared, as well as the consistency of their diagnosis results was evaluated. The study included 312 ovarian-adnexal masses, including 145 malignant masses and 167 benign masses from 287 patients with an average age of (46.8 ± 11.3) years. The AUC of the ADNEX model was 0.974, and the optimum cutoff value was the risk value > 24.2%, with the corresponding sensitivity and specificity being 97.93 and 86.83, respectively. The AUC of the O-RADS was 0.956, and the optimum cutoff value was > O-RADS 3, with the corresponding sensitivity and specificity being 97.24 and 85.03, respectively. The AUCs of the two models were 0.924 and 0.911 at the optimum cutoff values, with no statistical differences between them (P = 0.284). Consistency analysis: the kappa values of the two models for the determination and pathological results of masses were 0.840 and 0.815, respectively, and that for the diagnostic outcomes was 0.910. Both the ADNEX model and O-RADS had good diagnostic performance in people from Northeast China. Their diagnostic capabilities were similar, and diagnostic results were highly consistent at the optimum cutoff values.

Accelerated PMA and its application in reliability-based design optimization

This paper proposes a novel approach based on the performance measure approach (PMA), which is termed accelerated PMA (aPMA) to overcome the non-convergence of the advanced mean value(AMV) and extend it to the reliability-based design optimization (RBDO). In aPMA, a threshold value by using inequality is integrated with the formula of AMV to make the efficiency and robustness of searching for the minimum performance target point (MPTP) better. The threshold value is able to eliminate the unnecessary probabilistic constraint in the inverse reliability analysis, thereby reducing the risk of numerical instability in AMV. Meanwhile, a judgment condition is defined according to the threshold value and reliability index in the design optimization, in which the active deterministic constraints can be quickly identified and updated. In addition, the recommended aPMA is merged into the double loop method (DLM) to consolidate the accuracy, efficiency and robustness of that for the high-dimensional RBDO problem. Since reliability analysis and structural optimization are carried out simultaneously, the convergence rate is enhanced. Besides, both the efficiency and robustness of the proposed aPMA are firstly trialed on six numerical/structural examples along with its performance on RBDO is tested through three RBDO problems quoted, showing significant merits.

Performance investigation of a novel free piston Stirling pump for reverse osmosis desalination systems

Renewable energy (RE)-powered desalination technology is considered a cleaner and promising alternative for alleviating energy exhaustion and environmental pollution resulting from traditional desalination. Currently available solar thermal reverse osmosis (RO) desalination systems are based on the organic Rankine cycle. With the aim to expand the driving mode of reverse osmosis desalination as well as simplify the transmission chain and reduce mechanical energy losses, a novel hydraulic free piston Stirling pump (FPSP) is developed and a simple model is designed and tested for conceptual validation. A free piston Stirling pump - powered reverse osmosis desalination system is presented, and a thermodynamic–dynamic coupling model is established. A parametric analysis is performed with an emphasis on the effects of temperatures, charge pressure, spring stiffnesses, damping coefficients, and masses on the system performance, including the frequency, power output, water yield, and efficiency. Results showed that the frequency in the pumping process was higher than that in the suction process because of the different loads. Within the range investigated, the performance improved as the hot-end temperature, charge pressure, spring stiffnesses, and damping coefficient of the power piston increased, while it deteriorated with a decrease in the damping coefficient of the displacer and the piston masses. Specifically, the power output and water yield reached the optimum value as the cold-end temperature was maintained around 310 K. Under representative parameter conditions, the power output could reach 12.15 kW and the water yield was approximately 6.07 × 10−4 m3/s. In addition, the temperatures and charge pressure influence the system efficiency most.

Copper - nickel electro-explosive powder feedstocks for extrusion-based additive manufacturing

The average sizes of copper and nickel nano- and microparticles formed at exploding wires in the range of inhomogeneous and homogeneous heating have been established. The average size of nanoparticles grows, and that of microparticles decreases when the value of energy input into wires reaching E ≈ 0,5Es (Es - sublimation energy). While E > 0.5Es the dependence of the average sizes of nano- and microparticles is weakly expressed. The viscosity of feedstocks increases as the proportion of nanoparticles in the powder increases and their size decreases. At equal dispersity and mass content of particles in the polymer, the feedstock viscosity has been found to depend on the adsorption behavior of metals. The analysis of temperature dependence of the feedstock viscosity based on copper and nickel powders has shown that the optimum values of E/Es for one-stage production of micro-nanoparticle powders by the exploding wires lie in the range of 0.4 … 0.7.

In-depth insight into the driving factors of the compressive strength development of MKPC based on interpretable machine learning methods

Magnesium potassium phosphate cement (MKPC) is a kind of Mg-chemically bonded phosphate ceramic commonly used for rapidly repairing dilapidated structures. In this study, a compressive strength dataset of MKPC was constructed, and four advanced machine learning (ML) algorithms (XGBoost, RF, GBDT and ANN) were selected to establish a high-precision compressive strength prediction model of MKPC. The SHAP and PDP methods are also used for interpretability analysis of ML-MKPC models. The XGBoost model has good generalizability and reliability while achieving high prediction accuracy. The RF and GBDT models performed similarly to the XGBoost model on the training set but performed poorly on the testing set. The ANN model is poorly trained on both the training and testing sets, with a risk of underfitting. The R2 of the XGBoost model at the different compressive strength stages still reaches above 0.80, indicating that it not only captures the complex relationships of the overall dataset well but also effectively predicts the staged strength dataset. Feature importance analysis revealed that the curing age (T), water-to-binder ratio (W/B), mineral admixtures-to-binder ratio (MA/B) and phosphate-to-magnesium ratio (P/M) are the principal variables affecting the compressive strength of MKPC. The partial interpretation shows that the optimum value range is determined when W/B is 0.10–0.18, MA/B is 0–0.20, P/M is 0.40–1.0, and R/M is 0–0.12. The composition of mineral admixtures with high-Ca, high-Si and low-Al systems seems to be more conducive to participating in the hydration reaction of MKPC. The ML-MKPC compressive strength prediction model developed in this study can provide theoretical support for the subsequent composition design and performance optimization of MKPC.

Facile synthesis, enhanced annealing-structural investigation and supercapacitive potentials of NiFe2O4 spinel nanopowder

Herein, we examined and optimized the influence of annealing temperature on microstructural and electrochemical charge storage properties of spinel NiFe2O4 nanopowder synthesized from a simple one-pot sol-gel route. Microstructural techniques encompassing Raman spectroscopy, scanning electron microscopy, transmission electron microscopy, x-ray diffractometry, and Fourier transform infra-red spectroscopy indicate the resulting powder are composed of spinel NiFe2O4 nanoparticle with metal oxygen vibration, crystal properties and lattice strain, all dependent on annealing temperature. Electrochemical charge storage performance of the electrode fabricated from the synthesized material were investigated with the aid of cyclic voltammetry, galvanostatic charge-discharge and electrochemical impedance spectroscopy measurements. The obtained results showed that the charge storage performance and rate capability of NiFe2O4 electrode is dependent on the annealing temperature. The study also showed that the electrode from the material annealed at 400 °C demonstrated optimum electrochemical charge storage performance having exhibited optimum specific capacitance and capacity values of 1128 Fg−1 and 58 mAh g−1 at 5 mVs−1 scan rate and 0.5 Ag−1 current density, respectively. The electrode EIS fitted equivalent circuit values were also found dependent on annealing temperature indicating the charge transfer process and rate capability of spinel NiFe2O4 nano-powder can be tailored by simply varying the annealing temperature. The study demonstrates cheap route by which spinel NiFe2O4 powder can be prepared. It also unveils the effect annealing temperature on the microstructural build-up and electrochemical charge storage performance of the material.

Energy and exergy analysis of an ideal molten carbonate fuel cell (MCFC) and reheat & regenerative braysson cycle hybrid system

Direct energy conversion devices are gaining prominence because of their high efficiency, as the process involves the direct conversion of chemical energy to its electrical counterpart, bypassing the thermal energy phase. Fuel cells work on the principle of a chemical reaction between fuels like Hydrogen, Methane, propane, ammonia, and an oxidizer. The working temperature of the fuel cell is as high as (600 °C–700 °C). Generally, waste heat liberated from the fuel cells was used to generate power by running the Brayton (or) Rankine cycle. This work involves exergy and energy analysis on a hybrid system made of a Molten Carbonate Fuel Cell and reheat & regenerative Braysson cycle. Combining a molten carbonate fuel cell (MCFC) with a Braysson cycle results in a novel hybrid system that offers exciting possibilities for power generation. In the analysis, Molten Carbonate Fuel Cell is assumed to operate at 650 °C, and the turbine inlet temperature (TIT) range of the Braysson cycle is taken as 400 to 600 °C. It has been noticed that different optimum pressure ratio values exist to obtain maximum output of power and maximum efficiencies. Both the exergy and energy efficiencies of the combined cycle increase with the increase in turbine inlet temperature. This combined system depicts maximum energy and exergy efficiency of 96.84% and 95.13%, respectively. Destruction rates of exergy for individual equipment and the total system are also obtained as a function of TIT and pressure ratio. The exergy destruction rates are found to be maximum in the fuel cells. An optimum pressure ratio is found to be 1.4, where fuel consumption is the least and efficiencies are the maximum.

Microstructure Analysis, Piezoelectrical Resistivity, and Compressive Strength Concrete Incorporated with Waste Steel Slag as a Fine Aggregate Replacement

Abstract This study aims to investigate the effect of waste steel slag (SS) as partially replaced with cement and fine aggregate on conventional concrete for different mixes named M25, M35, and M47 in terms of compressive strength (CS), electrical resistivity (ER), and piezoresistivity behavior. SS is a molten mixture of silicates and oxides that solidifies upon cooling, a byproduct of the steel-making process. Before doing the design experiments, the optimum value of SS as powder and fine aggregate was determined using seven different mixes to investigate the effect of different SS sizes on the CS and piezoresistivity of normal concrete. Based on the results achieved, the optimum value and size of SS were selected to modify and investigate the effect of SS on three different mixes of conventional concrete named M25, M35, and M47 in terms of CS, ER, and piezoresistivity behavior. The resistivity of all concrete mixes was measured using four-probe from early curing to 28 days of curing time. The results demonstrated that M47 mix modified with SS has lower resistivity than the rest of the concrete mixes. The results of piezoresistivity behavior indicated that M47 mix modified with SS has a higher resistivity change while applying stress at 3 days of curing compared to the M25 and M35 concrete mix modified with SS by 44.1 % and 37.6 %, respectively. The Vipulandanan p-q model was applied to predict both ER versus time and change of resistivity versus stress for all mixes. The results demonstrated that the model predicted the change of resistivity versus applied stress with a high coefficient of determination that varied between 0.82 and 0.989, and a low root mean square error changed between 0.81 Ω.m and 7.94 Ω.m.

Learning-Assisted Fast Determination of Regularization Parameter in Constrained Image Reconstruction.

To leverage machine learning (ML) for fast selection of optimal regularization parameter in constrained image reconstruction. Constrained image reconstruction is often formulated as a regularization problem and selecting a good regularization parameter value is an essential step. We solved this problem using an ML-based approach by leveraging the finding that for a specific constrained reconstruction problem defined for a fixed class of image functions, the optimal regularization parameter value is weakly subject-dependent and the dependence can be captured using few experimental data. The proposed method has four key steps: a) solution of a given constrained reconstruction problem for a few (say, 3) pre-selected regularization parameter values, b) extraction of multiple approximated quality metrics from the initial reconstructions, c) predicting the true quality metrics values from the approximated values using pre-trained neural networks, and d) determination of the optimal regularization parameter by fusing the predicted quality metrics. The effectiveness of the proposed method was demonstrated in two constrained reconstruction problems. Compared with L-curve-based method, the proposed method determined the regularization parameters much faster and produced substantially improved reconstructions. Our method also outperformed state-of-the-art learning-based methods when trained with limited experimental data. This paper demonstrates the feasibility and improved reconstruction quality by using machine learning to determine the regularization parameter in constrained reconstruction. The proposed method substantially reduces the computational burden of the traditional methods (e.g., L-curve) or relaxes the requirement of large training data by modern learning-based methods, thus enhancing the practical utility of constrained reconstruction.

The Relationship Between the Endoscopic Healing Index, Fecal Calprotectin, and Magnetic Resonance Enterography in Crohn's Disease.

The serum-based endoscopic healing index (EHI) test identifies endoscopic Crohn's disease (CD) activity. Data are lacking on the relationship between EHI with other endpoints. We assessed the relationship between EHI and the simplified Magnetic Resonance Index of Activity. Data were prospectively collected on patients with CD with either an EHI or fecal calprotectin (FCAL) within 90 days of magnetic resonance enterography (MRE). Diagnostic accuracy was assessed using area under the receiver operator characteristics. Proportions with any, severe, and terminal ileum MR inflammation were compared above/below identified thresholds for both EHI and FCAL. A total of 241 MREs paired to either EHI or FCAL from 155 patients were included. Both EHI and FCAL had similar accuracy to diagnose inflammation (area under the receiver operator characteristics: EHI: 0.635 to 0.651, FCAL: 0.680 to 0.708). Optimal EHI values were 42 and 26 for inflammation on MRE and endoscopy, respectively. Patients with EHI ≥42 (100% vs. 63%, P =0.002), FCAL >50µg/g (87% vs. 64%, P <0.001) and FCAL >250µg/g (90% vs. 75%, P =0.02) had higher rates of simplified Magnetic Resonance Index of Activity ≥1 compared with lower values. EHI differentiated ileitis numerically more than FCAL (delta: 24% to 25% vs. 11% to 21%). Patients with FCAL ≥50µg/g had higher rates of severe inflammation compared with FCAL <50µg/g (75% vs. 47%, P <0.001), whereas smaller differentiation existed for EHI threshold of 42 (63% vs. 49%, P =0.35). Both EHI and FCAL were specific in their confirmation of inflammation and disease activity on MRE in patients with CD. However, MRE-detected inflammation was frequently present in the presence of low EHI and FCAL in similar proportions.

Optimization of excitation field depending on magnetic nanoparticle parameters for magnetic hyperthermia under safety constraint

Hysteresis loss (P) of magnetic nanoparticles (MNPs) under alternating current excitation has been used to induce hyperthermia in cancer cells. We theoretically optimized the excitation field amplitude Hac and frequency f required to maximize P, while the product C = Hacf did not exceed a threshold value to avoid side effects in biomedical applications. We obtained analytical expressions for the optimum values of Hac and f as functions of C and MNP parameters. Almost the same P could be obtained for MNPs with magnetic core diameters dc ranging over 20–40 nm if Hac and f were optimized according to the dc value. A numerical example was a P of ∼0.4 kW/g Fe for immobilized MNPs under C = 2 × 109 A/(ms). We also examined the dependences of P on MNP parameters under the optimum excitation field. A large saturation magnetization was essential for a large P. The degradation of P caused by the dc distribution in a practical (realistic) sample was examined, and the conditions that reduce degradation were determined. There was a strong agreement among these properties between the analyses and numerical simulations. Finally, we showed how much P increased for suspended MNPs relative to that for immobilized MNPs. Overall, these results will be useful for the development of high-performance hyperthermia systems.

Developing a numerical framework to study the cavitation and non-cavitation behaviour of a centrifugal pump inducer

The present work explores the impact of tip clearance on the mean blade height ratio, inlet tip blade angle, and surface roughness of the inducer. The objective is to find an optimized inducer to limit the secondary flows over the blades, which in turn improves the pump efficiency and reduces the life cycle costs. A model framework is achieved to investigate efficient operational and geometrical parameters on an inducer's non-cavitation and cavitation presentations. The catalyser functioning is simulated by applying a 3D CFD model, and the results are assessed against empirical data. The results show a reliable agreement with empirical data and suggest that the increment of tip clearance in the mean blade height ratio causes the hydraulic performance and the analytical cavitation number to decline in cavitation and non-cavitation conditions. Moreover, the optimum value of 85o is found for the inlet tip blade angle, which improves the non-cavitation performance.

Increased plasma levels of N-terminal pro-B-type natriuretic peptide as biomarker for the diagnosis of cardioembolic ischaemic stroke

BackgroundDespite comprehensive study, the aetiology of stroke is not identified in 35% of cases. AimsWe conducted a study to assess the diagnostic capacity of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in the identification of ischaemic stroke of cardioembolic origin. The secondary purpose of the study was to evaluate the prognostic value of NT-proBNP for predicting 90-day all-cause mortality. MethodsWe designed a prospective observational study including patients hospitalised due to stroke between March 2019 and March 2020. Blood samples were collected on admission to the emergency department and serum NT-proBNP levels were determined. Statistical analysis was performed using a bivariate logistic regression model and receiver operating characteristic (ROC) and Kaplan–Meier curves. Statistical significance was established at p<.05. ResultsThe study included 207 patients with first ischaemic stroke. Plasma NT-proBNP levels were significantly higher (p<.001) in the cardioembolic stroke group (2069pg/mL±488.5). ROC curves showed that NT-proBNP>499pg/mL was the optimum value for diagnosing cardioembolic ischaemic stroke (sensitivity, 82%; specificity, 80%). Moreover, plasma NT-proBNP levels>499pg/mL were independently associated with cardioembolic stroke (OR: 9.881; p=.001). Finally, NT-proBNP>1500pg/mL was useful for predicting 90-day mortality (sensitivity, 70%; specificity, 93%). ConclusionsNT-proBNP was independently associated with cardioembolic stroke and should be quantified in blood tests within 24h of stroke onset. High plasma levels (>499pg/mL) may indicate an underlying cardioembolic cause, which should be further studied, while NT-proBNP >1500pg/mL was associated with increased 90-day mortality.

Prediction of defects in deep drawn rectangular parts using Finite Element Analysis (FEA) and Response Surface Methodology (RSM)

Abstract Deep drawing defects such as thinning and earing present challenges to sheet metal forming industry while designers tend to favour the usage of new materials and production processes. The present work introduces an integrated approach using Design of Experiment, FEA experimentation and RSM to study the effect of deep drawing process parameters and resulting defects associated with sheet metal forming processes such as thinning and earing particularly in deep drawing of non-circular parts. The Design of Experiment (DoE) is used to generate a series of experiments for different process parameters in deep drawn rectangular products which are then simulated using Simulia 2022, a finite element package. The results are then fed to statistical analysis software, Design Expert 12.0, to develop regression equations that predict minimum sheet thickness and earing defects using RSM. FE models for deep drawing of different products have been built and results have been verified through comparisons with published data. Critical process parameters were selected for investigation in the present work. Based on the results of these experiments, a two-level design of experiment is conduct to generate 64 FE experiments. The relationships between these parameters and minimum sheet thickness after drawing and earing defects are then obtained using RSM. Optimum values of different parameters are obtained for maximum sheet thickness after drawing and minimum earing.

Experimental, theoretical and computational studies of oxalyl dihydrazide as a novel corrosion inhibitor for mild steel in neutral saline solution

In this work, the corrosion inhibition performance and mechanism of oxalyl dihydrazide (ODH) for mild steel in neutral saline solution are in-depth studied using weight-loss and electrochemical tests, surface characterizations, theoretical calculation and computational simulations. Results indicate that ODH can act as a novel and superior mixed-type corrosion inhibitor for mild steel in neutral saline solution, its corrosion inhibition efficiency increases with the rising ODH concentration, and the optimum value reaches 88.7 % with adding 200 mg/L. Its corrosion inhibition ability becomes better with immersion time. A compact corrosion product film mainly consisting of Fe, O, N and Cl elements formed on metal surface after adding ODH. ODH molecules adsorb on metal surface in an orderly fashion to form a hydrophobic film, which is belonging to the physicochemical adsorption and obeys the Langmuir adsorption isotherm model. The corrosion inhibition process of ODH molecule on mild steel is the endothermic process, which enlarges the activation energy barrier of corrosion reactions. ODH molecule can expel the adsorbed water molecules on metal surface and form copolymers with increasing of ODH concentration, retarding the diffusion of water molecule thus protecting metal from corrosion. ODH is proved to be an effective organic corrosion inhibitor for protecting mild steel in neutral saline solution, and contributes toward research and application of easily accessible sources for organic corrosion inhibitors.

Utilization of Palm Shell Ash as a Filler in Making AC-WC Type Porous Asphalt

The background to the research that will be carried out is that the large amount of standing water on the road pavement in each rainy season results in disturbances to motorists' comfort. This is due to impermeable road pavement and poor drainage along the road. Porous asphalt can increase rainwater absorption, thereby reducing puddles on the road surface. Porous asphalt is a new breakthrough in the world of road pavement to reduce the appearance of puddles of water when it rains. Porous asphalt is also designed to have high porosity so that water can flow through side channels and a waterproof base layer to prevent water from seeping into the subbase layer and road body so as to minimize puddles of water on the road surface which often occur after rain and disrupt the smooth flow of traffic. cross. Advances in road pavement technology have encouraged researchers to conduct research using palm shell ash (fly ash) as a filler in porous asphalt mixtures. The use of palm shell ash is expected to increase the stability value and have large cavities so that water can pass through the road surface, as well as to reduce palm oil waste in Indonesia. The objectives of this research are 1. To find out the optimum asphalt content value in porous asphalt mixtures, 2. To know the results of using palm shell ash at 0%, 1% and 2% as a filler for porous asphalt mixtures in flexible road pavement. The research method is Marshall and Permeability Testing. The tests that will be carried out on a laboratory scale use an AC-WC hot mix asphalt system with guidance, namely the basics of asphalt concrete road construction. The research results showed that by adding palm shell ash as a filler in making AC-WC type porous asphalt, it showed that the stability value was higher, while the permeability value was lower, meaning that the addition of palm shell ash to the porous asphalt mixture did not have a significant effect because it was smaller. air voids in the mixture. The addition of palm shell ash to the porous asphalt mixture increases the stability value which can increase the ability of road construction to accept loads, but the pavement layer is not permeable and water flows over the surface more slowly.

Microencapsulation of Yeast Cells and Its Potential Usage as a Post-Harvest Biocontrol Agent for Citrus Storage

In this study, yeasts isolated from citrus groves, trees and leaves were identified, phylogenetic analyzes were performed and their antifungal effects were determined. Wickerhamomyces anamolus (M72), Meyerozyma guilliermondii (M77), and Pichia kudriavzevii (M74) species were identified and were found to have antifungal effects against P. digitatum and P. italicum. Pichia kudriavzevii (M74), which has the highest antifungal effect, showed 67% and 62% inhibition rates against P. digitatum and P. italicum, respectively. An encapsulation study was carried out using a microencapsulation process to ensure that the M74 strain, which has the most antifungal effect, is long-lived enough to be a biopesticide. The optimum spray drying process parameters as well as the optimum concentration values of wall materials were investigated in the spray drying process for the microencapsulation of Pichia kudriavzevii (M74) through the Taguchi methodology. The formulation containing 0.1% sodium alginate (SA) and 10% corn starch (CS) showed a good performance in the inhibition of P. digitatum, a mold that causes losses in orange, thanks to its high percentage of viability (73%). The inhibition percentages may indicate that this formulation may be a candidate to be considered as a potential alternative application to synthetic fungicides on orange fruits for the effective control of P. digitatum mold.