Error Function Analysis Research Articles

Removal of reactive black 5 in water using adsorption and electrochemical oxidation technology: kinetics, isotherms and mechanisms

AbstractIn this work, a novel graphite intercalation compound (GIC) particle electrode was used to investigate the adsorption of Reactive Black 5 (RB5) and the electrochemical regeneration in a three-dimensional (3D) electrochemical reactor to recover its adsorptive capacity. Various adsorption kinetics and isotherm models were used to characterise the adsorption behaviour of GIC. Several adsorption kinetics were modelled using linearised and non-linearised rate laws to evaluate the viability of the sorption process. Studies on the selective removal of RB5 dyes from binary mixture in solution were evaluated. RSM optimisation studies were integrated with ANOVA analysis to provide insight into the significance of selectivity reversal from the salting effect of textile dye solution on GIC adsorbent. A unique range of adsorption kinetics and isotherms were used to evaluate the adsorption process. Non-linear models best simulated the kinetic data in the order: Elovich > Bangham > Pseudo-second-order > Pseudo-first-order. The Redlich–Peterson isotherm was calculated to have a dye loading capacity of 0.7316 mg/g by non-linear regression analysis. An error function analysis with ERRSQ/SSE of 0.1390 confirmed the accuracy of dye loading capacity predicted by Redlich–Peterson isotherm using non-linear regression analysis. The results showed that Redlich–Peterson and SIPS isotherm models yielded better fitness to experimental data than the Langmuir type. The best dye removal efficiency achieved was ~ 93% using a current density of 45.14 mA/cm2, whereas the highest TOC removal efficiency achieved was 67%.

Pulse wave-based evaluation of the blood-supply capability of patients with heart failure via machine learning

Pulse wave, as a message carrier in the cardiovascular system (CVS), enables inferring CVS conditions while diagnosing cardiovascular diseases (CVDs). Heart failure (HF) is a major CVD, typically requiring expensive and time-consuming treatments for health monitoring and disease deterioration; it would be an effective and patient-friendly tool to facilitate rapid and precise non-invasive evaluation of the heart’s blood-supply capability by means of powerful feature-abstraction capability of machine learning (ML) based on pulse wave, which remains untouched yet. Here we present an ML-based methodology, which is verified to accurately evaluate the blood-supply capability of patients with HF based on clinical data of 237 patients, enabling fast prediction of five representative cardiovascular function parameters comprising left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVDd), left ventricular end-systolic diameter (LVDs), left atrial dimension (LAD), and peripheral oxygen saturation (SpO2). Two ML networks were employed and optimized based on high-quality pulse wave datasets, and they were validated consistently through statistical analysis based on the summary independent-samples t-test (p > 0.05), the Bland–Altman analysis with clinical measurements, and the error-function analysis. It is proven that evaluation of the SpO2, LAD, and LVDd performance can be achieved with the maximum error < 15%. While our findings thus demonstrate the potential of pulse wave-based, non-invasive evaluation of the blood-supply capability of patients with HF, they also set the stage for further refinements in health monitoring and deterioration prevention applications.

Removal of anthracene from vehicle-wash wastewater through adsorption using eucalyptus wood waste-derived biochar

The removal of anthracene from vehicle-wash wastewater (VWW) was investigated using adsorption employing biochar (EWB) generated from eucalyptus wood waste. The EWB was characterized using analytical techniques such as surface area analysis (SAA), scanning electron microscopy (SEM), and fourier transform infrared (FT-IR). The study determined that the most effective conditions to achieve maximum anthracene adsorption (98.40%) were as follows: an initial concentration of 40 ppm, a contact time of 60 min, a pH level of 5, a temperature of 50 °C, and an adsorbent dose of 0.4 g. Isotherms and kinetic models were utilized to evaluate the adsorptive capacity of anthracene. The kinetic analysis results indicate that the anthracene adsorption process onto the EWB is controlled by a pseudo 2nd order kinetic model. The experiment's findings showed that the Langmuir isotherm model provided the most accurate fit to the data. Also, error function analysis was performed. The exothermic and spontaneous nature of the adsorption process is evident based on the values of thermodynamic parameters, including enthalpy (ΔH°), Gibbs free energy (ΔG°), and entropy (ΔS°). The outcomes were also contrasted with the capabilities of a few commercial adsorbents in real-world applications. According to this investigation, the novel EWB exhibits a significant potential, which exceeds 95%, for the extraction and recovery of anthracene from industrial wastewater.

Adsorptive capture of fluoride ion from water by Co/Fe-LDH@Avocado kernel seeds biochar@Caboxymethylcellulose nanobiosorbent: Optimization, error function and multivariate analysis

The current investigation is devoted to synthesize a sustainable and effective nanobiosorbent by simple combination of cobalt-iron layered double hydroxide with avocado kernel seeds biochar and carboxymethyl cellulose to form a novel multifunctionalized Co/Fe-LDHs@AKS biochar@CMC material for adsorptive capture of fluoride under optimized conditions. The EDX analysis referred to 42.7 %(C) 33.4 %(O), 14.3 %(Co) 5.3 %(Fe) 2.6 %(Na) 1.2 %(Cl) and 0.52 %(Mn). The highest adsorptive capture of fluoride ion by Co/Fe-LDH@AKS biochar@CMC) nanobiosorbent were at pH ≤ 2.0 and pH 7.0 due to ion-pair interaction and anion exchange mechanisms. The fluoride removal achieved 90.9–100.0 % upon using 100 mg of Co/Fe-LDH@AKS biochar@CMC. The modeled data by four linear and non-linear expressions confirmed the highest average relative error (ARE) by the non-linear Jovanovich (ARE = 4.66) and linear Jovanovich (ARE = 12.69). The kinetic study ascertained that the adsorptive capturing reaction of fluoride ion was best fitted to both linear and nonlinear pseudo 2nd order.

Tailor-made biochar-based nanocomposite for enhancing aqueous phase antibiotic removal

In the present study, an innovative biochar-based metal(loid) oxide nano-matrix doped hybrid nanocomposite (nMOC) from kitchen waste-derived biochar (KWB) and ZnO/SiO2 was used for aqueous phase tetracycline removal. It involved a three-stage process, entailing thermal conversion of biomass to KWB, synthesis of ZnO/SiO2 nano-matrix, and nMOC fabrication via ball-milling. Advanced characterizations were employed to determine surface chemistry, surface morphology, surface area, and elemental composition, exhibited thermostable, mesoporous, heterogeneous, ZnO/SiO2-doped matrix with rich active surface-functional groups. The nMOC showed excellent performance (95.27 ± 0.304 %) for TC removal through batch mode adsorption study for 7.0 mg L−1 aqueous TC solution at ambient temperature. The sorption data were statistically evaluated through linear and non-linear isotherms, kinetics, and thermodynamics modelling incorporating error function analysis, suggested spontaneous, exothermic, and multilayer chemisorption with complex diffusional adsorption phenomenon. The adsorption mechanisms were governed by, electrostatic interaction, H-bonding, π-π stacking interactions, and pore-filling. Regeneration study demonstrated the maximum efficiency using EDTA (81.39 ± 1.234 %). Experiments on interference by co-existing ions suggested lesser impact by monovalent anions (NO3−) than divalent anions (SO42−), and monovalent cations (NH4+). The nMOC showed enhanced TC adsorption and excellent reusability along with dual benefits of minimization of solid kitchen waste and very effective antibiotic removal from (waste)water.

Isothermal Remodelling of the Biosorption of Congo Red onto Kaolin

A remodeling analysis was conducted on the sorption isotherm data for Congo Red adsorption onto kaolin using nonlinear regression. (CR) also known as 1-naphthalenesulfonic acid, 3,3′-(4,4′-biphenylenebis(azo)) bis(4-amino-) disodium salt, is a synthetic anionic azo dye widely utilized in various industrial sectors, including rubber, plastic, textiles, paper, and printing. This dye is of significant interest due to its versatile applications and unique chemical properties. To prevent overfitting due to the limited data points, isotherm models with up to three parameters were utilized. Statistical analysis based on error function assessments, including root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), accuracy factor (AF), bias factor (BF), Bayesian Information Criterion (BIC), corrected AICc (Akaike Information Criterion), and Hannan-Quinn Criterion (HQC), revealed that the best performance was achieved by the Freundlich model, followed by the Langmuir and Jovanovic models, which ranked as the top three models.The best isotherm model was found to be the Unilan followed by (descending order) Brouers–Sotolongo, Hill, Sips and Langmuir. The Unilan maximum adsorption capacity, shows large deviation from the experimentally observed value with a large 95% confidence interval, indicating poor fitting parameters despite being the best model based on the error function analysis. The next best model was Brouers–Sotolongo with a maximum adsorption capacity, qmBS of 5.48 mg g-1 (95% confidence interval from 4.791 to 6.172) which agrees with experimental observations. The value of the maximum monolayer adsorption capacity for Congo Red binding to kaolin according to the Langmuir’s parameter qmL was 5.49 mg g-1 (95% Confidence interval from 5.018 to 5.967), while bL (L mg-1), the Langmuir model constants was 0.5 L mg-1 (95% C.I. from 0.285 to 0.710).

Comparison between the Four-parameter and Five-parameter Logistics Equations in the Determination of the Limits of Detection of Ochratoxin A

Ochratoxin A, a type of mycotoxin, was detected in plant sample matrices using the "optical waveguide lightmode spectroscopy" (OWLS) method. The calibration curve for the detection of ochratoxin A utilizing "optical waveguide lightmode spectroscopy" (OWLS) displayed a sigmoidal shape; hence, the 5-parameter logistics (5-PL) or 4-parameters logistics (4-PL) model should be used to fit the data rather than a linear model. Through the use of error function analysis and various functions such as Bias Factor, corrected Akaike Information Criterion (AICc), adjusted correlation coefficient (adjR2), Hannan–Quinn information criterion (HQC), Root Mean Square Error (RMSE), Bayesian Information Criterion (BIC), and Accuracy Factor, the distinction between the 5-PL and 4-PL models is found to be inconsistent. The half maximal effective concentration (EC50) confidence intervals overlapped, indicating no difference between the two methods; the 4-PL model was chosen because of its fewer parameters. The Limits of Detection (LOD) calculated using the 4-PL equation was 0.818 ng/mL, with a 95% confidence interval of 0.526-1.143 ng/mL. This value falls within the estimated range of 0.5 to 10 ng/mL found in the first investigation. Not only was the linear component of the data curve successfully represented by this study's use of the 4-PL model, but the model was also successful in representing the entire date curve.

Synthesis and Performance Evaluation of Novel Bentonite-Supported Nanoscale Zero Valent Iron for Remediation of Arsenic Contaminated Water and Soil

Groundwater arsenic (As) pollution is a naturally occurring phenomenon posing serious threats to human health. To mitigate this issue, we synthesized a novel bentonite-based engineered nano zero-valent iron (nZVI-Bento) material to remove As from contaminated soil and water. Sorption isotherm and kinetics models were employed to understand the mechanisms governing As removal. Experimental and model predicted values of adsorption capacity (qe or qt) were compared to evaluate the adequacy of the models, substantiated by error function analysis, and the best-fit model was selected based on corrected Akaike Information Criterion (AICc). The non-linear regression fitting of both adsorption isotherm and kinetic models revealed lower values of error and lower AICc values than the linear regression models. The pseudo-second-order (non-linear) fit was the best fit among kinetic models with the lowest AICc values, at 57.5 (nZVI-Bare) and 71.9 (nZVI-Bento), while the Freundlich equation was the best fit among the isotherm models, showing the lowest AICc values, at 105.5 (nZVI-Bare) and 105.1 (nZVI-Bento). The adsorption maxima (qmax) predicted by the non-linear Langmuir adsorption isotherm were 354.3 and 198.5 mg g-1 for nZVI-Bare and nZVI-Bento, respectively. The nZVI-Bento successfully reduced As in water (initial As concentration = 5 mg L-1; adsorbent dose = 0.5 g L-1) to below permissible limits for drinking water (10 µg L-1). The nZVI-Bento @ 1% (w/w) could stabilize As in soils by increasing the amorphous Fe bound fraction and significantly diminish the non-specific and specifically bound fraction of As in soil. Considering the enhanced stability of the novel nZVI-Bento (upto 60 days) as compared to the unmodified product, it is envisaged that the synthesized product could be effectively used for removing As from water to make it safe for human consumption.

Modelling the Kinetics of Tartrazine Sorption by Bottom Ash

Bottom ash is the solid residue left over from municipal waste combustion or incineration in a Municipal Waste Incineration Furnace. Its use as a sorption agent, particularly for dye sorption, is a new and important application. Linearized adsorption kinetics has drawbacks such as inaccurate representation of the parameters' 95 percent confidence interval output, unbalanced attention to potential outliers, and magnification of errors may result in inaccurate parameter values. In this study, we used nonlinear regression to investigate 16 adsorption kinetics models of tartrazine by bottom ash. The pseudo-second order was the best model based on the Bias and Accuracy factor near unity, but based on other error function analysis, this model performs equally well with the exponential and fractal-like pseudo-second order based other error functions such as Root-Mean-Square Error (RMSE), adjusted coefficient of determination (adjR2), Marquardt’s percent standard deviation (MPSD), Bayesian Information Criterion (BIC), Hannan-Quinn Information Criterion (HQC), and especially the corrected Akaike Information Criterion (AICc) function as the absolute difference is 5 absolute unit making discriminatory activity difficult. Furthermore, because the pseudo-second order and exponential models have only two parameters, they are less complicated according to Occam's razor. Because the pseudo-second order model is more popular and has more applications than the less well-known exponential model, we chose it as the best model for tartrazine sorption to bottom ash. Kinetic analysis using the PSO model gave a value of equilibrium adsorption capacity, qe of 21.88 mg g-1 (95% confidence interval (C.I.), 20.93 to 22.84) and k2 (g/(mg.sec)) of 0.00002 (95%, C.I., 0.00001 to 0.00002).

Limits of Detection Determination of Aflatoxin B1 using the Optical Waveguide Lightmode Spectroscopy via the Four-Parameter Logistic Model

Mycotoxins are harmful secondary metabolites generated by a variety of fungi, and they may be found in a vast array of food and feed commodities and processed meats from animals fed infected meal. Numerous mycotoxins are extremely resistant and survive food processing, entering the food chain and posing a concern to human health. The "optical waveguide lightmode spectroscopy" (OWLS) method was used to detect aflatoxin B1 in plant sample matrices. The calibration curve for the detection of aflatoxin B1 utilizing "optical waveguide lightmode spectroscopy" (OWLS) displayed a sigmoidal shape; hence, the 5-PL or 4-PL model should be used to fit the data rather than a linear model. Using error function analysis with functions such as AICc, HQC, BIC, RMSE, adjR2, Bias Factor, and Accuracy Factor, the 5-PL and 4-Pl models are distinguished inconsistently. The overlapping confidence intervals of the LogEC50 values suggested that the two techniques did not differ much, and the 4-PL model was selected due to its smaller number of parameters. The Limits of Detection for aflatoxin B1 value based on the 4-PL equation was 8.787 ng/mL with the 95% confidence interval from 5.728 to 13.100. In this study, the use of the 4-PL model was successful and was able to represent the entire date curve, not only the linear section. The linear component is crucial as a handy and swift approach for assessing the sensitivity of a developed biosensor technology and is often a more beneficial method for field applications when a quick and straightforward evaluation is required.

Determination of the Limits of Detection for Acetamiprid Based on Gold Nanoparticle Aptasensor: Comparison Between Four-Parameter and Five-Parameter Logistics Equations

Acetamiprid is a kind of broad-spectrum systemic pesticide that works on the nicotinic acetylcholine receptor. This chemical disrupts the transmission of a signal and causes a buildup of neurotransmitters, which leads to pests being paralyzed and eventually dying as a result. The calibration curve for the detection of acetamiprid utilizing a gold nanoparticle-based visual aptasensor showed a sigmoidal shape profile; hence, the 5-PL or 4-PL model should be used to fit the data rather than a linear model. The result of the error function analysis shows that the simpler 4-PL model is more reliable having smaller AICc, R2 and adjR2, values whilst the other error functions such as RMSE, BIC and HQF, BF and AF values indicated that the 5-PL model shows that the 5-PL model was marginally superior to the 4-PL. As the 95% confidence interval overlap, the IC50 values were deemed not significantly different, and when this occur, based on Occam’s razor, the model having a lower number of parameters, which was 4-PL, should be chosen instead. The 4-PL equation produced a value for the LOD of 0.159 mM, and the confidence interval for 95 percent of the results ranged from 0.132 to 0.177. According to the first study, the LOD was 3.81 mM, and the calculated LOD using 4-PL model with pooled standard deviations was much more sensitive. This indicates that utilizing only the linear portion of a sigmoidal curve to report the LOD values gave a less sensitive value than it should be.

Hybrid Coordination Networks for Removal of Pollutants from Wastewater.

The adsorption properties of two coordination polymers, resulting from the reaction of divalent metal (Ca2+ or Co2+) salts with (2-carboxyethyl)(phenyl)phosphinic acid, are presented in this paper. The structural and textural characterization before and after adsorption experiments is presented. The adsorbent materials were prepared using the hydrothermal procedure. The compound Ca[O2P(CH2CH2COOH)(C6H5)]2 (CaCEPPA) has a layered topology, with the phenyl groups oriented into the interlayer space and crystallizes in the monoclinic system. Compound Co2[(O2P(CH2CH2COO)(C6H5)(H2O)]2·2H2O (CoCEPPA) has a 1D structure composed of zig-zag chains. The adsorption performances of CaCEPPA and CoCEPPA materials were tested in the removal of cadmium and lead from aqueous solutions. The optimum pH of ions adsorption was found to be five for both adsorbent materials. Pseudo-first and second-order kinetic models were used for fitting kinetic experimental data, and Langmuir and Freundlich isotherms were used for modeling the equilibrium experimental data. The pseudo-second-order kinetic model and Langmuir isotherm best described the adsorption of Cd and Pb ions onto the studied materials, judging from the results of the error function (correlation coefficient, sum of square error, chi-square test, and average relative error) analysis. The studied materials present a higher affinity for Cd ions compared with the adsorption capacity developed for the removal of Pb ions from aqueous solutions. CoCEPPA showed the highest adsorption performance in the removal process of metal ions from aqueous solutions compared with CaCEPPA (qm = 54.9 mg Cd2+/g of CoCEPPA, qm = 36.5 mg Cd2+/g of CaCEPPA).

Study on the degradation law of harmonic gear drive backlash with wear and assembly errors

Harmonic gear drive mechanism has been widely used in space mechanism, robot and other precision actuators. Based on the theory of probability and statistics, this paper establishes a mathematical model of harmonic gear transmission error considering the assembly and wear among components, and conducts sensitivity analysis and normalization of factors affecting harmonic gear transmission error model. Through Kriging model and Monte Carlo method, reliability degradation law of transmission accuracy is obtained by transmission error function and reliability analysis. Some suggestions are given in the design of harmonic gear drive in the future.

Effect of Pyrolysis Temperature on Mechanistic Transformation for Adsorption of Methylene Blue on Leached Rice‐Straw Biochar

AbstractToxicity characteristic leaching procedure (TCLP) leached biochar is studied for adsorption of methylene blue (MB). Rice straw biochar obtained from slow pyrolysis at 400, 500, and 600 °C, respectively, is TCLP leached to furnish leached biochar, BL4, BL5, and BL6. The leached biochar BL4–6 have been characterized for pH, CHN analysis, ash, zeta potential, surface area morphology and functional groups. Batch adsorption studies are optimized for pH (3–9), adsorbent dose (0.5–4 g L−1), and initial MB concentration (20–135 mg L−1). Nonlinear fitting to Langmuir, Freundlich, and Redlich‐Peterson adsorption isotherm with due statistical treatment and error function analysis is carried out. Leached biochar, BL4, BL5, and BL6, is characterized by the dominance of carboxylic acid, lactone, and phenols moieties, respectively. The MB adsorption on leached biochar exhibits maximum adsorption of 26.87, 51.34, and 18.83 mg g−1 for BL4, BL5, and BL6, respectively. The underlying mechanism for adsorption of MB using BL5, is characterized by non‐ionic lactone ring opening in presence of MB under alkaline conditions that is supported by X‐ray photoelectron spectroscopy(XPS) and Fourier transformed infrared spectroscopy (FTIR) studies. Desorption of MB and regeneration from BL5 is studied with methanol and 0.1 m HCl as stripping solvent for four cycles. Recovery of MB is better with methanol in comparison to 0.1 m HCl.

Evaluation of the Microsoft Excel Solver Spreadsheet-Based Program for Nonlinear Expressions of Adsorption Isotherm Models onto Magnetic Nanosorbent

The sorption of basic dyes onto magnetic nanosorbent is commonly used as a novel material to combat powdered activated carbon, which is difficult to handle and separate during water and wastewater treatment. This adsorption method is commonly implemented in water and wastewater treatment due to its low cost and high performance. To explore the feasibility of adsorption, six different nonlinear isotherm models were applied and introduced to evaluate the performance and adsorption mechanisms via Microsoft Excel, and they were then compared to those of MATLAB and OriginPro. The Langmuir best provided the sorption of methylene blue adsorbed for a two-parameter isotherm model. The three-parameter model Toth gave a goodness of fit indicating a heterogeneous sorbent surface. Error function analysis found that the Residual Sum of Squares Error, Chi-square, Coefficient of determination, Average Relative Error, Hybrid Fractional Error Function, Marquardt’s Percent Standard Deviation and Root Mean Square Error provided the best overall results. In comparison, it could be concluded that six isotherm models showed the confidence interval that is simply the best fit at all experimental data points provided by the three software tools. All error function results indicated that the Microsoft Excel Solver function spreadsheet method satisfied all the statistic measures to predict the real variance of the probability of experimental data for all six isotherm models of adsorption of basic dye removal. One added benefit of this Microsoft Excel software tool is the built-in function associated with the desired type of application, which designates the desired type of error/statistical functions not mentioned in this research to the adsorbent materials used.

Preparation and characterization of modified anion exchange resin for uranium adsorption: estimation of nonlinear optimum isotherm, kinetic model parameters, error function analysis and thermodynamic studies

In this study, a modified metal hydroxides on surface of Lewatit resin (HMO @LM500, where M indicates to Al, Fe, Mn or Zn) were designed and used as efficient adsorbents for uranium (U(VI)) ions capture from aqueous solution. The prepared materials were characterized by using transform infrared spectroscopy, scanning electron microscope, energetic dispersive x-ray techniques. Batch adsorption methods were done to investigate all factors affecting adsorption process such as the effect of pH, concentration, contact time and temperature. Optimum values of each parameter were calculated as pH of 1.8, temperature of 298 K (25 °C), contact time of 60 min for the removal of uranium ions. Analysis within the nonlinear isotherm models indicates that the Liu model offers the best description for the equilibrium data since it has the highest R 2 value and the lowest error analysis value when compared with the other models. The calculated adsorption capacity of Liu model is 217.06 mg g−1, whereas analysis within the nonlinear kinetic models indicate that pseudo-second-order behavior is involved. The thermodynamic examination of the equilibrium data proved that the adsorption process of U(VI) was found to be a spontaneous and exothermic process. The ΔH 0 and ΔS 0 parameters were calculated as −66.5827 kJ mol−1 and −0.2051 kJ mol−1 K−1, respectively. Therefore, the prepared adsorbent can be applied to capture of U(VI) ions from aqueous medium.

Tobacco Stalk Waste Biomass Holds Multilayer and Spontaneous Adsorption Capabilities for Reactive Black 5 Dye: Equilibrium Modelling and Error Function Analysis

Tobacco Stalk Waste Biomass Holds Multilayer and Spontaneous Adsorption Capabilities for Reactive Black 5 Dye: Equilibrium Modelling and Error Function Analysis

Tile selection method based on error minimization for photomosaic image creation

Photomosaic images are composite images composed of many small images called tiles. In its overall visual effect, a photomosaic image is similar to the target image, and photomosaics are also called “montage art”. Noisy blocks and the loss of local information are the major obstacles in most methods or programs that create photomosaic images. To solve these problems and generate a photomosaic image in this study, we propose a tile selection method based on error minimization. A photomosaic image can be generated by partitioning the target image in a rectangular pattern, selecting appropriate tile images, and then adding them with a weight coefficient. Based on the principles of montage art, the quality of the generated photomosaic image can be evaluated by both global and local error. Under the proposed framework, via an error function analysis, the results show that selecting a tile image using a global minimum distance minimizes both the global error and the local error simultaneously. Moreover, the weight coefficient of the image superposition can be used to adjust the ratio of the global and local errors. Finally, to verify the proposed method, we built a new photomosaic creation dataset during this study. The experimental results show that the proposed method achieves a low mean absolute error and that the generated photomosaic images have a more artistic effect than do the existing approaches.

Modelling the Inhibition Kinetics of Molybdenum Reduction by the Molybdate-reducing Enterobacter cloacae

The mathematical simulation of physical, chemical or biological data can assist a researcher in explaining the physicochemical or biological phenomenon by predicting or estimating the possible actions, to replicate a prediction or retroactivity and to schedule better experiments. Bacteria are an emerging instrument for the bioremediation of the molybdenum pollutant in the world, molybdenum reduction into insoluble molybdenum blue. In this study, the molybdenum reduction rate by the bacterium Enterobacter cloacae was studied for its inhibitory kinetics characteristics using sodium molybdate as a substrate. Modeling kinetics showed that molybdenum reduction could be explained by several models such as Monod, Haldane, Hans-Levenspiel, Luong, Teissier, Aiba and Yano with Aiba as the best model as judged using error function analysis such as bias and accuracy factors (BF and AF), root mean square error (RMSE), adjusted coefficient of determination (adjR2), and corrected Akaike Information Criterion (AICc). The calculated value for the Teissier-Edward’s constants, which are qmax, Ks, and Ki that are maximal reduction rate, half saturation constant for maximal reduction, half saturation constant for inhibition of reduction were 7.77 (95% C.I., 4.41 to 19.95) mole Mo-blue hr-1, 26.63 (95% C.I., 12.82 to 40.44) mM and 51.39 (95% C.I., 23.67 to 79.10) mM, respectively. The true maximal reduction rate, which occurred when the slope of the curve is zero occurs at 36 mM molybdate concentration and a corresponding value of 1.85 mole Mo-blue hr-1. The fitting parameters of the Monod model prove a strong bacterial resistance to higher toxic molybdenum levels, making the bacterium useful tool for metals bioremediation work.

Inhibition Kinetics Study of Molybdenum Reduction by Pantoea sp. strain HMY-P4

Physical, chemical or biological data mathematical simulation may assist the investigator to describe a phenomenon found based on physical, chemical or biological mechanisms. The model may also be used to forecast or predict future behavior, simulate a hypothetical event or feedback, and better tests can be planned. Molybdenum reduction to the insoluble molybdenum blue by bacteria is an emerging tool for bioremediation of molybdenum pollutant worldwide. In this study, the molybdenum reduction rate by the bacterium Pantoea sp. strain HMY-P4 was studied for its inhibitory kinetics characteristics using sodium molybdate as a substrate. Modeling kinetics showed that molybdenum reduction could be explained by several models such as Monod, Haldane, Hans-Levenspiel, Luong, Teissier, Aiba and Yano with Aiba as the best model as judged using error function analysis such as bias and accuracy factors (BF and AF), root mean square error (RMSE), adjusted coefficient of determination (adjR2), and corrected Akaike Information Criterion (AICc). The calculated values for the Aiba constants qmax (the maximum specific substrate degradation rate (h−1), Ks (concentration of substrate at the half maximal degradation rate (mg/L) or saturation constant and Ki (inhibition constant (mg/L)) were 0.060 (95% CI, 0.024 to 0.096), 0.302 (95% CI, 0.381 to 0.222) and 0.953 (95% CI, 0.568 to 1.338), respectively. These model parameters indicate a good tolerance of the bacterium against high concentration of toxic molybdenum making the bacterium useful for bioremediation works.&#x0D;