Exploring the potential of SrTi0.7Fe0.3O3 perovskite/Chitosan nanosheets for the development of a label-free electrochemical sensing assay for determination of naproxen in human plasma samples.

Naproxen is a nonsteroidal anti-inflammatory drug used to treat nonrheumatic inflammation, migraine, and gout. Therefore, the determination of naproxen in pharmaceutical and biological samples is of particular importance. In the present work, SrTi0.7Fe0.3O3 perovskite/Chitosan nanosheets were used to modify the surface of a glassy carbon electrode (GCE) for highly sensitive determination of naproxen. To ensure the successful synthesis of the perovskite nanosheets, morphological studies including scanning electron microscopy (SEM), Energy-dispersive X-ray (EDX), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and X-ray photoelectron spectroscopy (XPS) were carried out. The electrochemical investigations of naproxen on the modified surface of GCE were investigated and the limit of detection (LOD) and limit of quantification (LOQ) were acquired 0.50 and 1.67 µM, respectively. Additionally, the linear range (LR) of 1.99-130.84 µM was obtained for the oxidation of naproxen. The obtained results have been proved that the mentioned method is simple, sensitive, and specific with a short analysis time. The dominant analytical features of the designed sensor are possessing a low detection limit, excellent stability, repeatability, and high selectivity in the presence of naproxen. For investigation of the applicability of the designed assay in real sample analysis, human plasma samples have been examined and a recovery index was acquired 95%.

Modeling and optimization of V2O5/TiO2 nanocatalysts for NH3-Selective catalytic reduction (SCR) of NOx by RSM and ANN techniques.

In the present study, two statistical methods including the response surface method (RSM) and artificial neural network (ANN), were employed for modeling and optimization of selective catalytic reduction of NOx with NH3 (NH3-SCR) over V2O5/TiO2 nanocatalysts. The relationship between catalyst preparation variables, such as metal loading, impregnation temperature, and calcination temperature on NO conversion were investigated. The R2 value of 0.9898 was obtained for quadratic a RSM model, which proves the high agreement of the model with the experimental data. The results of Pareto analysis revealed that three factors including calcination temperature, V loading, and impregnation temperature have a considerable impact on the response. Deduced from the established RSM model, the order of influence on the NO conversion was as follows: calcination followed by V loading and impregnation temperature. The optimum condition of catalyst preparation for maximum NO conversion over V2O5/TiO2 nanocatalysts was predicted to be at 0.0051 mol of V loading, an impregnation temperature of 50 °C and a calcination temperature of 491 °C. Moreover, an ANN model was created by a feed-forward back propagation network (with the topology 4, 12 and 1) to model the relation between the selected catalyst preparation variables and NH3-SCR process temperature. The R2 values for training, validation as well as test sets, were 0.99, 0.9810 and 0.9733. These high values proved the accuracy of the AAN model in modeling and estimating the NO conversion over V2O5/TiO2 nanocatalysts. According to the ANN model, the relative significance of each variable on NO conversion is calcination temperature, process temperature loading, and impregnation temperature from high to low importance, respectively, corroborating the obtained results from RSM.

A modelling study and optimization of catalytic reduction of NO over CeO2-MnOx (0.25)-Ba mixed oxide catalyst using design of experiments.

In this study, the effects of operation variables on catalytic performance of CeO2-MnOx (0.25)-Ba mixed oxide in catalytic reduction of NO with ammonia are investigated by using design of experiments. A response surface methodology (RSM) combined with the central composite design (CCD) is used to model and optimize the process variables, including concentration of 02 (vol.%), NH3/NO ratio in the gas feed, gas hourly space velocity (GHSV) and reaction temperature (degrees C) on the NO conversion and N2 selectivity as responses. The R2 values for both generated models were greater than 0.9, confirming the capability of quadratic RSM model in fitting the obtained experimental data. According to the results, GHSV had the largest and negative effect on the NO conversion, while it was an insignificant parameter on the N2 selectivity in the design space. Also, NH3/NO ratio was the most effective parameter on the N2 selectivity. Under the optimum conditions: 4.75 vol.% O2, NH3/NO ratio of 0.9, GHSV of 12,000 h(-1) and 197.5 degrees C, the predicted values for NO conversion and N2 selectivity were 96.47% and 93.96%, respectively. The obtained experimental values in optimum condition agreed with those predicted, indicating suitability of the RSM model to estimate the values of the responses.

Optimization of Cu/activated carbon catalyst in low temperature selective catalytic reduction of NO process using response surface methodology.

Preparation of Cu/Activated Carbon (Cu/AC) catalyst was optimized for low temperature selective catalytic reduction of NO by using response surface methodology. A central composite design (CCD) was used to investigate the effects of three independent variables, namely pre-oxidization degree (HNO3%), Cu loading (wt.%) and calcination temperature on NO conversion efficiency. The CCD was consisted of 20 different preparation conditions of Cu/AC catalysts. The prepared catalysts were characterized by XRD and SEM techniques. Predicting NO conversion was carried out using a second order model obtained from designed experiments and statistical software Minitab 14. Regression and Pareto graphic analysis showed that all of the chosen parameters and some interactions were effective on the NO conversion. The optimal values were pre-oxidization in 10.2% HNO3, 6.1 wt.% Cu loading and 480°C for calcination temperature. Under the optimum condition, NO conversion (94.3%) was in a good agreement with predicted value (96.12%).

Modelling and optimization of Mn/activate carbon nanocatalysts for NO reduction: comparison of RSM and ANN techniques.

A response surface methodology (RSM) involving a central composite design was applied to the modelling and optimization of a preparation of Mn/active carbon nanocatalysts in NH3-SCR of NO at 250 degrees C and the results were compared with the artificial neural network (ANN) predicted values. The catalyst preparation parameters, including metal loading (wt%), calcination temperature and pre-oxidization degree (v/v% HNO3) were selected as influence factors on catalyst efficiency. In the RSM model, the predicted values of NO conversion were found to be in good agreement with the experimental values. Pareto graphic analysis showed that all the chosen parameters and some of the interactions were effective on response. The optimization results showed that maximum NO conversion was achieved at the optimum conditions: 10.2 v/v% HNO3, 6.1 wt% Mn loading and calcination at 480 degrees C. The ANN model was developed by a feed-forward back propagation network with the topology 3, 8 and 1 and a Levenberg-Marquardt training algorithm. The mean square error for the ANN and RSM models were 0.339 and 1.176, respectively, and the R2 values were 0.991 and 0.972, respectively, indicating the superiority of ANN in capturing the nonlinear behaviour of the system and being accurate in estimating the values of the NO conversion.

The impact of operational factors on degradation of formaldehyde as a human carcinogen using Ag3 PO4 /TiO2 photocatalyst.

Background: The International Agency for Research on Cancer (IARC) identified formaldehyde as a carcinogen in 2004, yet formaldehyde is widely used in health care settings and various industries. In recent years, photocatalytic oxidation has been developed as a potential technique for removing pollutants arising from organic chemical agents and consequently promoting the health indices. This study investigated the effect of operational factors in optimizing formaldehyde removal from the air using Ag3 PO4 /TiO2 photocatalyst. Methods: An experimental study was designed to investigate the effect of operational factors on the efficiency of formaldehyde degradation. The variables investigated in this study include pollutant retention time, initial pollutant concentration and relative humidity. Sol-gel method was used to synthesize the nano-composite photocatalyst. An ideal experimental design was carried out based on Box-Behnken design (BBD) with response surface methodology (RSM). The sample size in this study includes all the glasses coated with Ag3 PO4 /TiO2 photocatalyst. Results: The maximum formaldehyde degradation of 32% was obtained at the initial concentration of 2 ppm, 20% relative humidity, and 90 minutes of retention time. Based on the statistical results, the correlation coefficient of the present study for the impact of operational factors on formaldehyde degradation was 0.9635, which means that there is only 3.65% probability of error in the model. Conclusion: The operational factors examined in this study (retention time, relative humidity, and initial formaldehyde concentration) were significantly influential in the degradation efficiency of formaldehyde by the photocatalyst. Due to the high exposure of employees and clients of health and treatment centers to formaldehyde as a carcinogenic substance, the results of this study can be used in ventilation systems to remove environmental pollutants in health care centers and other occupational settings.

Application of response surface methodology for optimization of the test condition of oxygen evolution reaction over La0.8Ba0.2CoO3 perovskite-active carbon composite.

The Experimental Design was applied to optimize the electrocatalytic activity of La0.8Ba0.2CoO3 perovskite oxide/Active Carbon composite material in the alkaline solution for the Oxygen Evolution Reaction. After the preparation of La0.8Ba0.2CoO3, and structural characterizations, the experimental design was utilized to determine the optimal amount of the composite material and testing conditions. The overpotential was defined as the response variable, and the mass ratio of perovskite/active carbon, Potassium hydroxide (KOH) concentration, and Poly(vinylidene fluoride) (PVDF) amount were considered effective parameters. The significance of model terms is demonstrated by P-values less than 0.0500. The proposed prediction model determined the optimal amounts of 0.665 mg of PVDF, a KOH concentration of 0.609 M, and A perovskite/Active Carbon mass ratio of 2.81 with 308.22 mV overpotential (2.27% greater than the actual overpotential). The stability test of the optimized electrode material over 24 h suggests that it could be a good candidate electrocatalyst for OER with reusability potential.

An Ultrasensitive miRNA-Based Genosensor for Detection of MicroRNA 21 in Gastric Cancer Cells Based on Functional Signal Amplifier and Synthesized Perovskite-Graphene Oxide and AuNPs.

In the present research work, the state-of-art label-free electrochemical genosensing platform was developed based on the hybridization process in the presence of [Fe(CN)6]3-/4- as an efficient redox probe for sensitive recognition of the miRNA-21 in human gastric cell lines samples. To attain this aim, perovskite nanosheets were initially synthesized. Afterward, the obtained compound was combined with the graphene oxide resulting in an effective electrochemical modifier, which was dropped on the surface of the Au electrode. Then, AuNPs (Gold Nano Particles) have been electrochemically-immobilized on perovskite-graphene oxide/Au-modified electrode surface through the chronoamperometry (CA) technique. Finally, a self-assembling monolayer reaction of ss-capture RNA ensued by the thiol group at the end of the probe with AuNPs on the modified electrode surface. miRNA-21 has been cast on the Au electrode surface to apply the hybridization process. To find out the effectiveness of the synthesized modifier agent, the electrochemical behavior of the modified electrode has been analyzed through DPV (differential pulse voltammetry) and CV (cyclic voltammetry) techniques. The prepared biomarker-detection bioassay offers high sensitivity and specificity, good performance, and appropriate precision and accuracy for the highly-sensitive determination of miRNA-21. Different characterization methods have been used, such as XRD, Raman, EDS, and FE-SEM, for morphological characterization and investigation of particle size. Based on optimal conditions, the limit of detection and quantification have been acquired at 2.94 fM and 8.75 fM, respectively. Furthermore, it was possible to achieve a wide linear range which is between 10-14 and 10-7 for miRNA-21. Moreover, the selectivity of the proposed biosensing assay was investigated through its potential in the detection of one, two, and three-base mismatched sequences. Moreover, it was possible to investigate the repeatability and reproducibility of the related bio-assay. To evaluate the hybridization process, it is important that the planned biomarker detection bio-assay could be directly re-used and re-generated.

Preparation and characterization of nano- and non-nanoscale Co3O4 spinels obtained from different methods and study of their performance in combustion of aromatics from polluted air-A comparison with Pt/γ-Al2O3 performance.

This article reports the development of oxidative precipitation (OP) method for synthesis of Co(3)O(4) as an environmental catalyst and comparison of its performance with that of obtained from conventional sol gel combustion (SG) method and industrial Pt/γ-Al(2)O(3) in remediation of toluene from air. Catalytic studies were carried out in a fixed bed reactor at 100-350°C under atmospheric pressure. Co(3)O(4) (OP) showed the highest activity in combustion of toluene. The half conversion temperature of toluene (T(50%)) was 160, 258, and 229°C on Co(3)O(4) (OP), Co(3)O(4) (SG) and Pt/γ-Al(2)O(3), respectively. The higher activity of Co(3)O(4) (OP) was ascribed to nanostructure and reducibility of catalytic sites at lower temperatures, approved by TPR results. The study confirmed that preparation method has a large influence on the chemical-physical properties and activity of the catalyst. The study indicated that oxidative precipitation method could be a promising method to synthesize environmental catalysts considering the simplicity and needless to calcine catalyst at higher temperatures.

Catalytic remediation of 2-propanol on Pt-Mn/γ-Al2O3 bimetallic catalyst during catalytic combustion--experimental study and response surface methodology (RSM) modeling.

Process and composition variables of catalytic oxidation of 2-propanol on Pt-Mn/γ-Al(2)O(3) bimetallic catalysts were optimized and modeled by response surface methodology (RSM). 31 factorial experiments were designed by setting four factors at five levels: X (1) = amount of manganese loading (wt.% Mn = 1, 3, 5, 7, 9); X (2) = reaction temperature (25, 50, 75, 100, 125°C); X (3) = calcination temperature (200, 300, 400, 500, 600°C) and X (4) = calcination time (2, 3, 4, 5, 6 h). A second-order polynomial model and response surface were developed for 2-propanol conversion. The optimum conditions for 2-propanol complete conversion were 4.8wt.% manganese loading, 4h calcination time with 75°C and 395°C for reaction and calcination temperatures, respectively. A good correlation was found between experimental and predicted responses, confirming the reliability of the model.

Application of SrFeO3 perovskite as electrode material for supercapacitor and investigation of Co-doping effect on the B-site.

Energy storage by supercapacitors with short charging time and high power density is one of the types of electrochemical storage systems. Perovskite oxides have been significantly investigated as promising materials for energy storage in electrochemical systems. In this study, three perovskites, SrFeO3, SrCoO3, and SrCo0.5Fe0.5O3, were prepared using the sol-gel method and used as supercapacitor electrode materials. In fact, in this research, two consecutive elements (Fe, Co) from the periodic table that differ by one unit in atomic number are placed in the perovskite structure to study their electrochemical properties for use in supercapacitors. From the obtained results, it was found that Co doping with a ratio of 1/1 (Co/Fe) at B site of SrFeO3 reduced the specific capacitance from 101.687 F g-1 to 60.912 F g-1 at a scan rate of 10 mV s-1. Also, the specific capacitance of SrCoO3 decreased from 68.639 F g-1 to 60.912 F g-1 at the same substitution rate at B site.

Investigating the effect of non-ideal conditions on the performance of a planar CH3NH3PbI3-based perovskite solar cell through SCAPS-1D simulation.

The difference between the simulation and experimental results of solar cells has always been challenging for researchers. Some simplifying assumptions in the simulation programs are the most common reason for this content. However, in some simulation programs, utilizing some nonidealities, the simulated solar cell can approach real conditions. In the present study, we attempted to simulate the conventional FTO/TiO2/CH3NH3PbI3/Spiro-OMeTAD/Au perovskite solar cell by considering resistance paths, reflection in front contact (FTO), and recombination (radiative and Auger) through SCAPS-1D software. For this, the effect of each of these nonidealities was investigated step by step. The efficiency results of the studied solar cell represented significant differences between the efficiency of the device before and after the application of these conditions that was from 19.26% to 8.40%. This significant decrement is mainly due to the reflection and radiative recombination. Besides, to optimize each of the active layers' essential properties, the effect of mentioned parameters, including thickness and doping density, was investigated in terms of efficiency and recombination plots. The novelty of this research was in employing the non-ideal conditions in the simulation phase and approximating them to the reported experimental works' outcomes. Moreover, utilizing the recombination plots helped a lot in choosing the optimum layer property, e.g., doping density selection. Finally, after optimizing all the properties mentioned above, the efficiency was enhanced by about 4% and reached PCE = 12.83%. The general results represent that despite the significant reduction in the cell performance, the simulated cell is closer to the experimental conditions and offers a better model of a solar cell.

Who Does the Job? How Copper Can Replace Noble Metals in Sustainable Catalysis by the Formation of Copper-Mixed Oxide Interfaces.

Following the need for an innovative catalyst and material design in catalysis, we provide a comparative approach using pure and Pd-doped LaCu x Mn1-x O3 (x = 0.3 and 0.5) perovskite catalysts to elucidate the beneficial role of the Cu/perovskite and the promoting effect of Cu y Pd x /perovskite interfaces developing in situ under model NO + CO reaction conditions. The observed bifunctional synergism in terms of activity and N2 selectivity is essentially attributed to an oxygen-deficient perovskite interface, which provides efficient NO activation sites in contact with in situ exsolved surface-bound monometallic Cu and bimetallic CuPd nanoparticles. The latter promotes the decomposition of the intermediate N2O at low temperatures, enhancing the selectivity toward N2. We show that the intelligent Cu/perovskite interfacial design is the prerequisite to effectively replace noble metals by catalytically equally potent metal-mixed-oxide interfaces. We have provided the proof of principle for the NO + CO test reaction but anticipate the extension to a universal concept applicable to similar materials and reactions.

Elucidating the role of earth alkaline doping in perovskite-based methane dry reforming catalysts.

To elucidate the role of earth alkaline doping in perovskite-based dry reforming of methane (DRM) catalysts, we embarked on a comparative and exemplary study of a Ni-based Sm perovskite with and without Sr doping. While the Sr-doped material appears as a structure-pure Sm1.5Sr0.5NiO4 Ruddlesden Popper structure, the undoped material is a NiO/monoclinic Sm2O3 composite. Hydrogen pre-reduction or direct activation in the DRM mixture in all cases yields either active Ni/Sm2O3 or Ni/Sm2O3/SrCO3 materials, with albeit different short-term stability and deactivation behavior. The much smaller Ni particle size after hydrogen reduction of Sm1.5Sr0.5NiO4, and of generally all undoped materials stabilizes the short and long-term DRM activity. Carbon dioxide reactivity manifests itself in the direct formation of SrCO3 in the case of Sm1.5Sr0.5NiO4, which is dominant at high temperatures. For Sm1.5Sr0.5NiO4, the CO : H2 ratio exceeds 1 at these temperatures, which is attributed to faster direct carbon dioxide conversion to SrCO3 without catalytic DRM reactivity. As no Sm2O2CO3 surface or bulk phase as a result of carbon dioxide activation was observed for any material - in contrast to La2O2CO3 - we suggest that oxy-carbonate formation plays only a minor role for DRM reactivity. Rather, we identify surface graphitic carbon as the potentially reactive intermediate. Graphitic carbon has already been shown as a crucial reaction intermediate in metal-oxide DRM catalysts and appears both for Sm1.5Sr0.5NiO4 and NiO/monoclinic Sm2O3 after reaction as crystalline structure. It is significantly more pronounced for the latter due to the higher amount of oxygen-deficient monoclinic Sm2O3 facilitating carbon dioxide activation. Despite the often reported beneficial role of earth alkaline dopants in DRM catalysis, we show that the situation is more complex. In our studies, the detrimental role of earth alkaline doping manifests itself in the exclusive formation of the sole stable carbonated species and a general destabilization of the Ni/monoclinic Sm2O3 interface by favoring Ni particle sintering.

Chemical-physical properties of spinel CoMn2O4 nano-powders and catalytic activity in the 2-propanol and toluene combustion: Effect of the preparation method.

Spinel-type CoMn(2)O(4)nano-powders are prepared using sol-gel auto combustion (SGC) and co-precipitation (CP) methods and their catalytic activities are evaluated in combustion of 2-propanol and toluene. The chemical-physical properties of the oxides are characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), N(2)-adsorption-desorption, temperature programmed reduction (TPR) and scanning electron microscopy (SEM). After calcination at 700°C, CoMn(2)O(4)-SGC shows higher amounts of the normal-type spinel phase and is more crystalline than CoMn(2)O(4)-CP. Higher calcination temperatures (850°C) do not affect very much the weight percentage of the normal-type spinel phase; although the crystal size slightly increased. The TPR analysis evidences a large number of Mn(3+) cations in CoMn(2)O(4)-SGC compared to CoMn(2)O(4)-CP. This difference, together with the higher surface area, could justify the higher activity of CoMn(2)O(4)-SGC in both the investigated reactions.

Steering the Methane Dry Reforming Reactivity of Ni/La2O3 Catalysts by Controlled In Situ Decomposition of Doped La2NiO4 Precursor Structures.

The influence of A- and/or B-site doping of Ruddlesden-Popper perovskite materials on the crystal structure, stability, and dry reforming of methane (DRM) reactivity of specific A2BO4 phases (A = La, Ba; B = Cu, Ni) has been evaluated by a combination of catalytic experiments, in situ X-ray diffraction, X-ray absorption spectroscopy (XAS), X-ray photoelectron spectroscopy (XPS), and aberration-corrected electron microscopy. At room temperature, B-site doping of La2NiO4 with Cu stabilizes the orthorhombic structure (Fmmm) of the perovskite, while A-site doping with Ba yields a tetragonal space group (I4/mmm). We observed the orthorhombic-to-tetragonal transformation above 170 °C for La2Ni0.9Cu0.1O4 and La2Ni0.8Cu0.2O4, slightly higher than for undoped La2NiO4. Loss of oxygen in interstitial sites of the tetragonal structure causes further structure transformations for all samples before decomposition in the temperature range of 400 °C-600 °C. Controlled in situ decomposition of the parent or A/B-site doped perovskite structures in a DRM mixture (CH4:CO2 = 1:1) in all cases yields an active phase consisting of exsolved nanocrystalline metallic Ni particles in contact with hexagonal La2O3 and a mixture of (oxy)carbonate phases (hexagonal and monoclinic La2O2CO3, BaCO3). Differences in the catalytic activity evolve because of (i) the in situ formation of Ni-Cu alloy phases (in a composition of >7:1 = Ni:Cu) for La2Ni0.9Cu0.1O4, La2Ni0.8Cu0.2O4, and La1.8Ba0.2Ni0.9Cu0.1O4, (ii) the resulting Ni particle size and amount of exsolved Ni, and (iii) the inherently different reactivity of the present (oxy)carbonate species. Based on the onset temperature of catalytic DRM activity, the latter decreases in the order of La2Ni0.9Cu0.1O4 ∼ La2Ni0.8Cu0.2O4 ≥ La1.8Ba0.2Ni0.9Cu0.1O4 > La2NiO4 > La1.8Ba0.2NiO4. Simple A-site doped La1.8Ba0.2NiO4 is essentially DRM inactive. The Ni particle size can be efficiently influenced by introducing Ba into the A site of the respective Ruddlesden-Popper structures, allowing us to control the Ni particle size between 10 nm and 30 nm both for simple B-site and A-site doped structures. Hence, it is possible to steer both the extent of the metal-oxide-(oxy)carbonate interface and its chemical composition and reactivity. Counteracting the limitation of the larger Ni particle size, the activity can, however, be improved by additional Cu-doping on the B-site, enhancing the carbon reactivity. Exemplified for the La2NiO4 based systems, we show how the delicate antagonistic balance of doping with Cu (rendering the La2NiO4 structure less stable and suppressing coking by efficiently removing surface carbon) and Ba (rendering the La2NiO4 structure more stable and forming unreactive surface or interfacial carbonates) can be used to tailor prospective DRM-active catalysts.

Engineering Oleaginous Yeast as the Host for Fermentative Succinic Acid Production From Glucose.

Oleaginous yeast Yarrowia lipolytica is a prospective host for production of succinic acid. The interruption of tricarboxylic acid cycle through succinate dehydrogenase gene (SDH) deletion was reported to result in strains incapable of glucose utilization and this ability had to be restored by chemical mutation or long adaptive laboratory evolution. In this study, a succinate producing strain of Y. lipolytica was engineered by truncating the promoter of SDH1 gene, which resulted in 77% reduction in SDH activity but did not impair the ability of the strain to grow on glucose. The flux toward succinic acid was further improved by overexpressing the genes in the glyoxylate pathway and the oxidative TCA branch, and expressing phosphoenolpyruvate carboxykinase from Actinobacillus succinogenes. A short adaptation on glucose reduced the lag phase of the strain and increased its tolerance to high glucose concentrations. The resulting strain produced 7.8 ± 0.0 g/L succinic acid with a yield of 0.105 g/g glucose in shake flasks without pH control, while mannitol (11.8 ± 0.8 g/L) was the main by-product. Further investigations showed that mannitol accumulation was caused by low pH stress and buffering the fermentation medium eliminated mannitol formation. In a fed-batch bioreactor in mineral medium at pH 5, at which point according to Ka values of succinic acid, the major fraction of product was in acidic form rather than dissociated form, the strain produced 35.3 ± 1.5 g/L succinic acid with 0.26 ± 0.00 g/g glucose yield.

Modeling preparation condition and composition-activity relationship of perovskite-type LaxSr1-xFeyCo1-yO3 nano catalyst.

In this paper, an artificial neural network (ANN) is first applied to perovskite catalyst design. A series of perovskite-type oxides with the LaxSr1-xFeyCo1-yO3 general formula were prepared with a sol-gel autocombustion method under different preparation conditions. A three-layer perceptron neural network was used for modeling and optimization of the catalytic combustion of toluene. A high R2 value was obtained for training and test sets of data: 0.99 and 0.976, respectively. Due to the presence of full active catalysts, there was no necessity to use an optimizer algorithm. The optimum catalysts were La0.9Sr0.1Fe0.5Co0.5O3 (Tc=700 and 800 °C and [citric acid/nitrate]=0.750), La0.9Sr0.1Fe0.82Co0.18O3 (Tc=700 °C, [citric acid/nitrate]=0.750), and La0.8Sr0.2Fe0.66Co0.34O3 (Tc=650 °C, [citric acid/nitrate]=0.525) exhibiting 100% conversion for toluene. More evaluation of the obtained model revealed the relative importance and criticality of preparation parameters of optimum catalysts. The structure, morphology, reducibility, and specific surface area of catalysts were investigated with XRD, SEM, TPR, and BET, respectively.