Performance analysis of floating bifacial stand-alone photovoltaic module in tropical freshwater systems of Southern Asia: an experimental study.

The optimization of floating bifacial solar panels (FBS PV) in tropical freshwater systems is explored by employing response surface methodology (RSM) and central composite design (CCD). Previous studies have yet to explore the long-term durability, environmental impact, economic viability, and performance of FBS PV systems under various climatic conditions. This study addresses this gap by focusing on panel height, water depth, and tilt angle to improve performance. The quadratic model reveals significant non-linear relationships impacting FBS PV power generation with freshwater cooling. Our models demonstrate high explanatory power, with R-squared values of 0.9831 for output power and 0.9900 for Bi-Facial gain. Experimental validation using conventional white surface (CWS) and proposed freshwater surface (PFS) indicates notable improvements in power generation, achieving a 4.34 to 4.86% gain in bifacial efficiency across various irradiation levels. Under 950 W/m2 irradiation, freshwater cooling achieves a 3.19% higher bifacial gain compared to CWS cooling. Panel temperature analysis shows consistent reductions with freshwater cooling, ranging from 1.43 to 2.72 °C, enhancing overall efficiency and longevity. This research highlights the potential of freshwater cooling in optimizing bifacial solar systems, offering actionable insights for sustainable energy solutions in tropical regions.

Dandelion inspired microparticles with highly efficient drug delivery to deep lung.

Active pharmaceutical ingredient (API) embedded dry powder for inhalation (AeDPI) shows higher drug loading and delivery dose for directly treating various lung infections. Inspired by the dandelion, we propose a novel kind of AeDPI microparticle structure fabricated by spray freeze drying technology, which would potentially enhance the alveoli deposition efficiency. When inhaling, such microparticles are expected to be easily broken-up into fragments containing API that acts as 'seed' and could be delivered to alveoli aided by the low density 'pappus' composed of excipient. Herein, itraconazole (ITZ), a first-line drug for treating pulmonary aspergillosis, was selected as model API. TPGS, an amphiphilic surfactant, was used to achieve stable primary ITZ nanocrystal (INc) suspensions for spray freeze drying. A series of microparticles were prepared, and the dandelion-like structure was successfully achieved. The effects of feed liquid compositions and freezing parameters on the microparticle size, morphology, surface energy, crystal properties and in vitro aerosol performance were systematically investigated. The optimal sample (SF(-50)D-INc7Leu3-2) in one-way experiment showed the highest fine particle fraction of ∼ 68.96 % and extra fine particle fraction of ∼ 36.87 %, equivalently ∼ 4.60 mg and ∼ 2.46 mg could reach the lung and alveoli, respectively, when inhaling 10 mg dry powders. The response surface methodology (RSM) analysis provided the optimized design space for fabricating microparticles with higher deep lung deposition performance. This study demonstrates the advantages of AeDPI microparticle with dandelion-like structure on promoting the delivery efficiency of high-dose drug to the deep lung.

Process parameters optimization of EDM for hybrid aluminum MMC using hybrid optimization technique.

This study explores how machining parameters affect Surface Roughness (SR), Tool Wear Rate (TWR), and Material Removal Rate (MRR) during Electrical Discharge Machining (EDM) of a hybrid aluminum metal matrix composite (AMMC). The composite includes 6 % Silicon carbide (SiC) and 6 % Boron carbide (B4C) in an Aluminum 7075 (Al7075) matrix. A combined optimization approach was used to balance these factors, evaluating Pulse ON time, Current, Voltage, and Pulse OFF time. Response Surface Methodology (RSM) optimized single responses, while multi-response optimization employed a hybrid method combining the Entropy Weight Method (EWM), Taguchi approach, TOPSIS, and GRA. Analysis of Variance (ANOVA) assessed parameter significance, revealing substantial impacts on SR, MRR, and EWR. Based on TOPSIS and GRA, optimized parameters achieved a desirable balance: high MRR (0.4172, 0.5240 mm³/min), minimal EWR (0.0068, 0.0103 mm³/min), and acceptable SR (10.3877, 9.1924 µm) based on EWM-weighted priorities. Confirmation experiments validated a 15 % improvement in the closeness coefficient, and a 16 % improvement in the Grey relational grade, which considers combined SR, MRR, and EWR performance. Scanning Electron Microscope (SEM) analysis of surfaces machined with optimal parameters showed minimal debris, cracks, and no recast layer, indicating high surface integrity. This research enhances EDM optimization for AMMC, achieving efficiency in machining, minimizing tool wear, and meeting surface quality requirements.

Enhancing the antioxidant properties of functional herbal beverages using Ultrasonic-Assisted extraction: Optimized formulation and synergistic combinations of taurine and vit. C.

Functional herbal beverages are gaining popularity in the beverage industry due to their natural antioxidants. However, the high concentration of antioxidants in these beverages can lead to increased toxicity, limiting their use. Moreover, the composition of tap water, including mineral salts and hydrogen carbonate ions, hampers the extraction process of polyphenolic compounds, thereby reducing the antioxidant properties. This study aims to address these challenges by enhancing antioxidant properties, reducing toxic effects, and improving the extraction process. Low-dose herbal extracts of green tea, rosemary, milk thistle, and sage were extracted using 100 ml of boiling water as a solvent, with ultrasonication employed for 20 min. Taurine, vit. C, and their combination were added to the extracts. The antioxidant properties, polyphenol, and flavonoid content were evaluated. The results demonstrated that the low-dose herbal tea combined with taurine and vit. C exhibited higher antioxidant activity compared to high-dose tea. Notably, the combination of taurine and vit. C showed the strongest synergistic effect. The addition of vit. C to these combinations eliminated any antagonism and resulted in a robust synergistic effect. The optimal conditions for enhancing antioxidant properties were determined as follows: an herbal type of 0.030 ≈ 0 (sage), vit. C concentration of 0.045 g/100 ml, and taurine concentration of 0.179 g/100 ml. The measured responses for reducing power, DPPH, and ABTS were 0.152 µg vit. C equivalent/ml, 67.778 %, and 87.630 %, respectively. This study provides valuable insights into optimizing the antioxidant properties of herbal beverages through the synergistic combinations of taurine and vit. C. By employing proper preparation techniques and including taurine and vit. C, the antioxidant capacity of these beverages can be significantly improved, potentially offering health benefits against degenerative diseases.

[Determination of eight neonicotinoid pesticides in wastewater by solid phase extraction combined with liquid chromatography-tandem mass spectrometry].

Neonicotinoid pesticides are a relatively new class of pesticides that have garnered significant attention owing to their potential ecological risks to nontarget organisms. A method combining solid phase extraction with liquid chromatography-tandem mass spectrometry (SPE-LC-MS/MS) was developed for the rapid and accurate detection of eight neonicotinoid pesticides (dinotefuran, E-nitenpyram, thiamethoxam, clothianidin, imidacloprid, imidaclothiz, acetamiprid, and thiacloprid) in wastewater. The chromatographic mobile phase and MS parameters were selected, and a single-factor method was used to determine the optimal column type, extraction volume, sample loading speed, and pH for SPE. The optimal parameters were as follows: column type, HLB column (500 mg/6 mL); sample extraction volume, 500 mL; sample loading speed, 10 mL/min; and sample pH, 6-8. The matrix effects of the wastewater samples were reduced by optimizing the chromatographic gradient-elution program, examining the dilution factor of the samples, and using the isotope internal standard calibration method. Prior to analysis, the wastewater samples were diluted 5-fold with ultrapure water for pretreatment. Subsequently, 2 mmol/L ammonium acetate aqueous solution containing 0.1% (v/v) formic acid and methanol was used as mobile phases for gradient elution on a ZORBAX Eclipse Plus C18 column (100 mm×2.1 mm, 1.8 µm). The samples were quantified using positive-ion multiple reaction monitoring (MRM) mode for 10 min. Imidacloprid-d4 was used as the isotope internal standard. The SPE process was further optimized by applying response surface methodology to select the type and mass of rinsing and elution solvents. The optimal pretreatment of the SPE column included rinsing with 10% methanol aqueous solution and elution with methanol-acetonitrile (1∶1, v/v) mixture (7 mL). The eight neonicotinoid pesticides showed satisfactory linearity within the relevant range, with linear correlation coefficients (r) all greater than 0.9990. The method detection limits (MDLs) ranged from 0.2 to 1.2 ng/L, and the method quantification limits (MQLs) ranged from 0.8 to 4.8 ng/L. The average recoveries of the eight neonicotinoid pesticides were in the range of 82.6%-94.2% at three spiked levels, with relative standard deviations (RSDs) ranging from 3.9% to 9.4%. Finally, the optimized method was successfully applied to analyze wastewater samples collected from four sewage treatment plants. The results indicated that the eight neonicotinoid pesticides could be generally detected at concentrations ranging from not detected (ND) to 256 ng/L. The developed method has a low MDL and high accuracy, rendering it a suitable choice for the trace detection of the eight neonicotinoid pesticides in wastewater when compared with other similar methods. The proposed method can be utilized to monitor the environmental impact and assess the potential risks of neonicotinoid pesticides in wastewater, thus promoting the protection of nontarget organisms and the sustainable use of these pesticides in agriculture.

Optimization of Processing Parameters for Continuous Microwave Drying of Crab Apple Slices via Response Surface Methodology.

To improve product quality and obtain suitable processing parameters for crab apple slices (CASs) produced by continuous microwave drying (CMD), the effects of processing parameters, including slice thickness, microwave power, air velocity, and conveyor belt speed, on the evaluation indexes in terms of temperature, moisture content, color (L*, a*, b*), hardness, brittleness, and total phenolic content of CASs were investigated via the response surface method. The results indicated that microwave power has the greatest effect on the evaluation indexes applied to the CASs under CMD, followed by air velocity, slice thickness, and conveyor belt speed. To produce the desired product quality, the appropriate parameters for CMD of CASs were optimized as 1.25 mm slice thickness, 14,630 W microwave power, 0.50 m·s-1 air velocity, and 0.33 m·min-1 conveyor belt speed. Following that, the moisture content under CMD was found to be 13.53%, the desired color, hardness 0.79 g, brittleness 12.97 (number of peaks), and the total phenolic content 5.48 mg·g-1. This research provides a theoretical framework for optimizing the processing parameters of CASs using the response surface method.

Validation of DOE Factorial/Taguchi/Surface Response Models of Mechanical Properties of Synthetic and Natural Fiber Reinforced Epoxy Matrix Hybrid Material.

A validation of the factorial, Taguchi and response surface methodology (RSM) statistical models is developed for the analysis of mechanical tests of hybrid materials, with an epoxy matrix reinforced with natural Chambira fiber and synthetic fibers of glass, carbon and Kevlar. These materials present variability in their properties, so for the validation of the models a research methodology with a quantitative approach based on the statistical process of the design of experiments (DOE) was adopted; for which the sampling is in relation to the design matrix using 90 treatments with three replicates for each of the study variables. The analysis of the models reveals that the greatest pressure is obtained by considering only the source elements that are significant; this is reflected in the increase in the coefficient of determination and in the predictive capacity. The modified factorial model is best suited for the research, since it has an R2 higher than 90% in almost all the evaluated mechanical properties of the material; with respect to the combined optimization of the variables, the model showed an overall contribution of 99.73% and global desirability of 0.7537. These results highlight the effectiveness of the modified factorial model in the analysis of hybrid materials.

Evaluation of hydrogen production via steam reforming and partial oxidation of dimethyl ether using response surface methodology and artificial neural network.

This study aims to develop two models for thermodynamic data on hydrogen generation from the combined processes of dimethyl ether steam reforming and partial oxidation, applying artificial neural networks (ANN) and response surface methodology (RSM). Three factors are recognized as important determinants for the hydrogen and carbon monoxide mole fractions. The RSM used the quadratic model to formulate two correlations for the outcomes. The ANN modeling used two algorithms, namely multilayer perceptron (MLP) and radial basis function (RBF). The optimum configuration for the MLP, employing the Levenberg-Marquardt (trainlm) algorithm, consisted of three hidden layers with 15, 10, and 5 neurons, respectively. The ideal RBF configuration contained a total of 80 neurons. The optimum configuration of ANN achieved the best mean squared error (MSE) performance of 3.95e-05 for the hydrogen mole fraction and 4.88e-05 for the carbon monoxide mole fraction after nine epochs. Each of the ANN and RSM models produced accurate predictions of the actual data. The prediction performance of the ANN model was 0.9994, which is higher than the RSM model's 0.9771. The optimal condition was obtained at O/C of 0.4, S/C of 2.5, and temperature of 250 °C to achieve the highest H2 production with the lowest CO emission.

Optimisation of fermentation conditions for the production of gamma-aminobutyric acid (GABA)-rich soy sauce.

This study addresses the challenge of enhancing gamma-aminobutyric acid (GABA) content in soy sauce through optimized fermentation condition. Using a multiple starter culture, consisting of Aspergillus oryzae strain NSK, Bacillus cereus strain KBC and Tetragenococcus halophilus strain KBC, the incubation conditions including the percentage of bacterial inoculum (10, 15 and 20 %), pH (3, 5 and 7) and agitation speed (100, 150 and 200 rpm) were optimized through Response Surface Methodology (RSM). Under the optimal conditions (20 % inoculum, pH 7 and stirring at 100 rpm), the multiple starter culture generated 128.69 mg/L of GABA after 7 days and produced 239.08 mg/L of GABA after 4 weeks of fermentation, which is 36 % higher than under non-optimized conditions (153.48 mg/L). Furthermore, sensory analysis revealed high consumer acceptance of the fermented soy sauce than the control (soy sauce without any treatment and additional bacteria) and commercial soy sauce. Consumers indicated that the starter culture offered an improved umami taste and reduced bitter, sour and salty flavours compared to the commercial product. Under optimal fermentation conditions determined by RSM statistical analysis, the multiple starter culture is able to produce high levels of GABA and is more likely to be accepted by consumers. The findings of this research have the potential to impact the food sector by offering a functional soy sauce with added health benefits and also being well-received by consumers.

A machine learning approach to investigate the impact of land use land cover (LULC) changes on groundwater quality, health risks and ecological risks through GIS and response surface methodology (RSM).

Groundwater resources are enormously affected by land use land cover (LULC) dynamics caused by increasing urbanisation, agricultural and household discharge as a result of global population growth. This study investigates the impact of decadal LULC changes in groundwater quality, human and ecological health from 2009 to 2021 in a diverse landscape, West Bengal, India. Using groundwater quality data from 479 wells in 2009 and 734 well in 2021, a recently proposed Water Pollution Index (WPI) was computed, and its geospatial distribution by a machine learning-based 'Empirical Bayesian Kriging' (EBK) tool manifested a decline in water quality since the number of excellent water category decreased from 30.5% to 28% and polluted water increased from 44% to 45%. ANOVA and Friedman tests revealed statistically significant differences (p < 0.0001) in year-wise water quality parameters as well as group comparisons for both years. Landsat 7 and 8 satellite images were used to classify the LULC types applying machine learning tools for both years, and were coupled with response surface methodology (RSM) for the first time, which revealed that the alteration of groundwater quality were attributed to LULC changes, e.g. WPI showed a positive correlation with built-up areas, village-vegetation cover, agricultural lands, and a negative correlation with surface water, barren lands, and forest cover. Expansion in built-up areas by 0.7%, and village-vegetation orchards by 2.3%, accompanied by a reduction in surface water coverage by 0.6%, and 2.4% in croplands caused a 1.5% drop in excellent water and 1% increase in polluted water category. However, ecological risks through the ecological risk index (ERI) exhibited a lower risk in 2021 attributed to reduced high-risk potential zones. This study highlights the potentiality in linking LULC and water quality changes using some advanced statistical tools like GIS and RSM for better management of water quality and landscape ecology.

Optimization of iron electrocoagulation parameters for enhanced turbidity and chemical oxygen demand removal from laundry greywater.

This study explores the optimization of iron electrocoagulation for treating laundry greywater, which accounts for up to 38% of domestic greywater. Characterized by high concentrations of surfactants, detergents, and suspended solids, laundry greywater presents complex challenges for treatment processes, posing significant environmental and health risks. Utilizing response surface methodology (RSM), this research developed a second-order polynomial regression model focused on key operational parameters such as the area-to-volume ratio (A/V), current density, electrolysis time, and settling time. Optimal treatment conditions were identified: an A/V ratio of 30 m2/m3, a current density of 10 mA/cm2, an electrolysis duration of 50 min, and a settlement period of 12 h. Under these conditions, exceptional treatment outcomes were achieved, with turbidity removal reaching 94.26% and COD removal at 99.64%. The model exhibited high effectiveness for turbidity removal, with an R2 value of 94.16%, and moderate effectiveness for COD removal, with an R2 value of 75.90%. The interaction between the A/V ratio and electrolysis time particularly underscored their critical role in electrocoagulation system design. Moreover, these results highlight the potential for optimizing electrocoagulation parameters to adapt to daily fluctuations in greywater production and meet specific household reuse needs, such as toilet flushing. This tailored approach aims to maximize contaminant separation and coagulant efficiency, balance energy use and operational costs, and contribute to sustainable water management.

Response surface methodology and machine learning optimisations comparisons of recycled AA6061-B4C-ZrO2 hybrid metal matrix composites via hot forging forming process.

The optimal conditions of applied factors to reuse Aluminium AA6061 scraps are (450, 500, and 550) °C preheating temperature, (1-15) % Boron Carbide (B4C), and Zirconium (ZrO2) hybrid reinforced particles at 120 min forging time via Hot Forging (HF) process. The response surface methodology (RSM) and machine learning (ML) were established for the optimisations and comparisons towards materials strength structure. The Ultimate Tensile Strength (UTS) strength and Microhardness (MH) were significantly increased by increasing the processed temperature and reinforced particles because of the material dispersion strengthening. The high melting point of particles caused impedance movements of aluminium ceramics dislocations which need higher plastic deformation force and hence increased the material's mechanical and physical properties. But, beyond Al/10 % B4C + 10 % ZrO2 the strength and hardness were decreased due to more particle agglomeration distribution. The optimisation tools of both RSM and ML show high agreement between the reported results of applied parameters towards the materials' strength characterisation. The microstructure analysis of Field Emission Scanning Electron Microscopy (FE-SEM) and Atomic Force Microscope (AFM) provides insights mapping behavioural characterisation supports related to strength and hardness properties. The distribution of different volumes of ceramic particle proportion was highlighted. The environmental impacts were also analysed by employing a life cycle assessment (LCA) to identify energy savings because of its fewer processing steps and produce excellent hybrid materials properties.

Optimizing Cellulase-Limosilactobacillus fermentum ZC529 Synergy Fermentation for Preserving Macadamia integrifolia Pericarp's Potential Use as Antioxidants.

Macadamia integrifolia pericarps (MIP) are byproducts of nut production which are rich in natural antioxidant compounds, making them an excellent source for extracting bioactive compounds. However, the antioxidant compounds in MIP are easily oxidized under natural storage conditions, resulting in significant biomass loss and resource wastage. To preserve the potential of MIP to be used as an antioxidant product, we employed cellulase and Limosilactobacillus fermentum ZC529 (L.f ZC529) fermentation and utilized response surface methodology to optimize the fermentation parameters for mitigating the antioxidant loss. Total antioxidant capacity (T-AOC) was used as the response variable. The fermented MIP water extract (FMIPE) was obtained via ultrasound-assisted extraction, and its biological activity was evaluated to optimize the best fermentation conditions. Results indicated that a cellulase dosage of 0.9%, an L.f ZC529 inoculation size of 4 mL/100 g, and a fermentation time of 7 days were the optimal conditions for MIP fermentation. Compared to spontaneous fermentation, these optimal conditions significantly increased the total phenolic and total flavonoid contents (p < 0.05). T-AOC was 160.72% increased by this optimal fermentation (p < 0.05). Additionally, supplementation with varying concentrations of FMIPE (6.25%, 12.5%, and 25%) increased the T-AOC, SOD activity, and GSH content, and reduced MDA levels of the oxidative-stressed Drosophila melanogaster (p < 0.05). Moreover, 12.5% and 25% of FMIPE treatments elevated CAT activity in the Drosophila melanogaster (p < 0.05). The effects of FMIPE on GSH and MDA in Drosophila melanogaster were equivalent to the 0.5% vitamin C (Vc) treatment. In summary, synergistic fermentation using cellulase and L.f ZC529 effectively preserves the antioxidant activity of the MIP, offering a simple, eco-friendly method to promote the utilization of MIP resources.

Optimization of Oil and Tocopherol Extraction from Maqui (Aristotelia chilensis (Mol.) Stuntz) by Supercritical CO2 Procedure.

This study focused on the oil extraction from freeze-dried maqui (Aristotelia chilensis) by supercritical fluid extraction with carbon dioxide (SFE-CO2). The basic objective was to optimize the oil yield and the tocopherol concentration. A Box/Behnken experimental design was developed with three processing variables: supercritical pressure (74, 187, and 300 bar), temperature (35, 48, and 60 °C), and extracting time (30, 135, and 240 min). Multiple optimizations, based on the combination of factor levels at 274 bar, 240 min, and 60 °C, led to the highest oil yield and tocopherol values. The validation of the optimized conditions of maqui oil extraction led to an oil yield of 8% and values of 735, 53, and 97 (mg·kg-1 oil) for α-tocopherol, α-tocotrienol, and γ-tocopherol, respectively. A higher concentration of tocopherol compounds was observed when compared to the employment of the conventional extracting method. The optimized SFE-CO2 method led to an oil extract exhibiting higher Hydrophilic-Oxygen Radical Absorbance Capacity (H-ORAC) assay and total phenol content (22 µmol Trolox equivalents·g-1 oil and 28 mg gallic acid equivalents·g-1 oil) than the oil obtained by the conventional procedure. A practical and accurate oil extraction is proposed for obtaining tocopherol-enriched oil including high concentrations of valuable lipophilic antioxidants.

Optimizing the compression resistance of low-nickel stainless steel coronary stents using finite element and response surface methodology.

Considering the high strength and excellent biocompatibility of low-nickel stainless steel, this paper focused on optimizing the design of a vascular stent made from this material using finite element analysis (FEA) combined with the response surface methodology (RSM). The aim is to achieve the desired compressive resistance for the stent while maintaining a thin stent wall thickness. The parameters of the stent's support unit width (H), strut width (W), and thickness (T) were selected as input parameters, while the output parameters obtained from FEA included the compressive load, the equivalent plastic strain (PEEQ), axial shortening rate, radial recoil rate, and metal coverage rate. The mathematical models of input parameters and output parameters were established by using the Box Behnken design (BBD) of RSM. The model equations were solved under constrained conditions, and the optimal structural parameters, namely H, W, and T, were finally determined as 0.770 mm, 0.100 mm, and 0.075 mm respectively. In this situation, the compression load of the stent reached the target value of 0.38 N/mm; the PEEQ resulting from the stent expansion was small; the axial shortening, radial recoil, and metal coverage index were all minimized within the required range.

Development and Evaluation of Calcium-Fortified Multi-Millet Biscuits: A Nutritious Alternative to Refined Wheat Flour.

Millet products have garnered global recognition for their exceptional nutritional profile, appealing to various age demographics, and, therefore, fortifying such products with minerals can ensure nutritional security. This research explores the feasibility of utilizing millet as a substitute for refined wheat flour in biscuit production. Three distinct millet varieties were investigated: finger, pearl, and buckwheat. Employing response surface methodology (RSM), the optimal ratio of these flours was determined, resulting in a blend of 1.5:1:1, respectively. The optimized multi-millet biscuits were further enhanced with calcium fortification and subjected to comprehensive physico-chemical analysis. Proximate composition analysis revealed favorable levels of protein (5.472 ± 0.31%), ash (2.80 ± 0.57 g/100 g), and energy density (5.8015 ± 0.004 kcal/g), indicating a significantly higher protein content, enriched mineral profile, and high energy density as compared to refined wheat flour products. Sensory evaluation encompassing attributes such as color and texture and organoleptic assessment using a nine-point hedonic scale demonstrated favorable acceptance. Additionally, the overall acceptability of the biscuits remained consistently high throughout storage, ranging from 8.263 ± 0.65 (day 0) to 8.053 ± 0.85 (day 14). This study underscores the potential of multi-millet biscuits as a nutritious and palatable alternative to traditional wheat-based snacks, offering an avenue for diversifying dietary options and promoting healthier food choices.

Surfactant-modified coconut coir powder (SMCCP) as a low-cost adsorbent for the treatment of dye-contaminated wastewater: parameters and adsorption mechanism.

The dye-contaminated wastewater discharged from various industries such as dye manufacturing, paint, textile, paper, and cosmetic is a prime source of surface water pollution having serious detrimental effects on both the environment and human beings. These hazardous dyes when exposed to water obstruct the penetration of sunlight into the water and thus restrain aquatic plants from generating photosynthetic compounds. Moreover, some dyes are potential cancer-causing and also negatively impact the human nervous and respiratory systems. In this current study, modification of coconut coir powder (CCP) was carried out through cationic surfactant treatment and was successively utilized as the adsorbent for decoloring anionic dye (acid blue 185 (AB 185)) containing waste stream. Further, a comparative investigation of the dye removal efficiency of raw CCP and surfactant-modified coconut coir powder (SMCCP) as the adsorbent was studied. On surfactant treatment, using a very minimal SMCCP dosage of 8.3 g/L, a very high percentage dye removal of 98.4% is possible, whereas with raw CCP, even after using a higher dosage of 14 g/L, only 70.1% dye removal can be achieved. Characterization of SMCCP adsorbent was done by Fourier transform infrared, thermogravimetric, X-ray, and scanning electron microscope analyses. Furthermore, the optimization of critical operating parameters was investigated for the effective adsorption of AB 185 dye in batch mode. The adsorption of AB 185 onto SMCCP was a thermodynamically spontaneous endothermic process, following the Langmuir isotherm and pseudo-second-order kinetic model. Moreover, regeneration of exhausted SMCCP by 0.1 (M) NaOH was achieved with a satisfactorily high recovery of 97% in the first cycle. Subsequently, SMCCP can be successfully reutilized for five consecutive cycles with a loss of 17.6% in the total adsorption capacity. With all such advantages, the present study delivers a new paradigm to utilize the novel adsorbent SMCCP as a promising eco-friendly adsorbent aided by its advantage of regeneration and reusability for the treatment of dye-contaminated wastewater.

Enhanced production of lactic acid from pretreated rice straw using co-cultivation of Bacillus licheniformis and Bacillus sonorenesis.

Lactic acid (LA) production from sugar mixture derived from lignocellulosic rice straw employing co- culture system of thermotolerant and inhibitor tolerant Bacillus licheniformis DGB and Bacillus sonorenesis DGS15 was carried out. In minimal media, both the strains of Bacillus DGB and DGS15 worked together by efficiently utilising glucose and xylose respectively. Response Surface Methodology (RSM) was used for optimisation of pretreatment of rice straw to achieve maximum yield of 50.852 g/L total reducing sugar (TRS) from 100 gm of rice straw biomass. Pretreatment of rice straw resulted in its delignification, as confirmed by FTIR spectroscopy, since the peak at 1668 cm-1 disappeared due to removal of lignin and scanning electron microscopy (SEM) revealed disruption in structural and morphological features. Crystallinity index (CrI) of treated rice straw increased by 15.54% in comparison to native biomass. DGB and DGS15 individually yielded 0.64 g/g and 0.82 g/g lactic acid respectively, where as their co-cultivation led to effective utilisation of both glucose and xylose within 15 h (70%) and complete utilisation in 48 h, producing 49.75 g/L LA with a yield of 0.98 g/g and productivity of 1.036 g/L/h, and resulting in reduction in fermentation time. Separate hydrolysis of rice straw and co-fermentation (SHCF) of hydrolysates by Bacillus spp. enhanced the production of lactic acid, can circumvent challenges in biorefining of lignocellulosic biomass.

Optimization of process conditions for ionic liquid-based ultrasound-enzyme-assisted extraction of resveratrol from Polygonum Cuspidatum.

This work offered a productive technique for resveratrol extraction from Polygonum Cuspidatum (P. Cuspidatum) using ionic liquids in synergy with ultrasound-enzyme-assisted extraction (UEAE). Firstly, ionic liquids with different carbon chains and anions were evaluated. Subsequently, a comprehensive investigation was carried out to evaluate the effect of seven crucial parameters on the resveratrol yield: pH value, enzyme concentration, extraction temperature, extraction time, ultrasonic power, concentration of ionic liquid (IL concentration) and the liquid-solid ratio. Employing the Plackett-Burman Design (PBD), the critical factors were effectively identified. Building upon this foundation, the process was further optimized through the application of Response Surface Methodology (RSM) and an Artificial Neural Network-Genetic Algorithm (ANN-GA). The following criteria were determined to be the ideal extraction conditions: an enzyme concentration of 2.18%, extraction temperature of 58 °C, a liquid-solid ratio of 29 mL/g, pH value of 5.5, extraction time of 30 min, ultrasonic power of 250 W, and extraction solvent of 0.5 mol/L 1-butyl-3-methylimidazolium bromide. Under these conditions, the resveratrol yield was determined to be 2.90 ± 0.15 mg/g. Comparative analysis revealed that the ANN-GA model provided a better fit to the experimental data of resveratrol yield than the RSM model, suggesting superior predictive capabilities of the ANN-GA approach. The introduction of a novel green solvent system in this experiment not only simplifies the extraction process but also enhances safety and feasibility. This research paves the way for innovative approaches to extracting resveratrol from botanical sources, showcasing its significant potential for a wide range of applications.

Green synthesis of nZVI-modified biochar significantly enhanced the removal of Cr(VI) from aqueous solution.

Water contamination by hexavalent chromium (Cr(VI)) seriously jeopardizes human health, which is a pressing environmental concern. Biochar-loaded green-synthesized nZVI, as a green and environmentally friendly material, can efficiently reduce Cr(VI) to Cr(III) while removing Cr(VI) from water. Therefore, in this study, an efficient green-modified biochar material (TP-nZVI/BC) was successfully prepared using tea polyphenol (TP) and sludge biochar (BC) using a low-cost and environmentally friendly green synthesis method. The preparation conditions of TP-nZVI/BC were optimized using response surface methodology (RSM), revealing that the dosage of tea polyphenols plays a crucial role in the removal performance (R2 = 1271.09), followed by reaction time and temperature. The quadratic regression model proved accurate. The optimal preparation conditions are as follows: tea polyphenols (TP) dosage at 48 g/L, reaction temperature at 75 ℃, and a reaction time of 3 h. TP-nZVI/BC removed Cr(VI) from water at a rate 7.6 times greater than BC. The pseudo-second-order kinetic model (R2 = 0.987) accurately describes the adsorption process, suggesting that chemical adsorption predominantly controls the removal process. The adsorption of Cr(VI) by TP-nZVI/BC can be well described by the Langmuir model, and the maximum adsorption capacity reached 105.65 mg/g. FTIR and XPS analyses before and after adsorption demonstrate that nZVI plays a crucial role in the reduction process of Cr(VI), and the synergistic effects of surface adsorption, reduction, and co-precipitation enhance Cr(VI) removal. In summary, using green-modified biochar for Cr(VI) removal is a feasible and promising method with significant potential.