Modelling and Optimization of Biogenic Synthesis of Gold Nanoparticles from Leaf Extract of Swertia chirata Using Artificial Neural Network

 J Clust Sci 29, 1151–1159 (2018)

Swertia chirata is a medicinal plant studied for its ability to synthesize polyshaped gold nanoparticles (AuNP). The process of AuNP biosynthesis was studied using artificial neural networks (ANN) with different activation function on output node (logistic or linear) and different training algorithm (back propagation or Levenberg–Marquardt). The maximum biosynthesis was checked under the optimized condition of 17.24% leaf extract, pH 4.61, gold chloride concentration 4 mM and temperature 53.61 °C. A significant improvement in the model efficiency for predicting AuNP biosynthesis around 37.60%, in terms of root mean square error was obtained with the developed ANN-linear2 model, compared to the traditional response surface methodology.

Modelling and Optimization of Biogenic Synthesis of Gold Nanoparticles from Leaf Extract of Swertia chirata Using Artificial Neural Network

Journal of Cluster Science (2018) 29:1151–1159

DOI: 10.1007/s10876-018-1429-8

Swertia chirata is a medicinal plant studied for its ability to synthesize polyshaped gold nanoparticles (AuNP). The process of AuNP biosynthesis was studied using artificial neural networks (ANN) with different activation function on output node (logistic or linear) and different training algorithm (back propagation or Levenberg–Marquardt). The maximum biosyn- thesis was checked under the optimized condition of 17.24% leaf extract, pH 4.61, gold chloride concentration 4 mM and temperature 53.61 °C. A significant improvement in the model efficiency for predicting AuNP biosynthesis around 37.60%, in terms of root mean square error was obtained with the developed ANN-linear2 model, compared to the traditional response surface methodology.

Polycyclic Aromatic Hydrocarbons in Soil Organic Horizons Depending on the Soil Burn Severity and Type of Ecosystem

Land Degradation & Development

DOI: 10.1002/ldr.2806

Because forest fires are a source of polycyclic aromatic hydrocarbons (PAHs), the influence of burnt conditions is of paramount importance and has not been thoroughly studied yet. In this study, two types of forest stands (Pinus nigra and Pinus pinaster) and two shrubland systems (Erica arborea and Ulex europaeus), differing in litter properties (composition and flammability), were considered. Changes in PAH levels were analysed in unburnt and charred litter, and they were related to different levels of soil burn severity and the organic matter composition of the charred litter, including charcoal and/or ashes. For monitoring PAH levels, an analytical method to determine them in unburnt and burnt woodland samples by pressure liquid extraction using a solid phase extraction cleanup was optimized. The highest levels of PAHs were found in the charred litter of P. pinaster (especially at soil burn severity = 200–400 °C), followed by U. europaeus, which presented similar concentration than Erica arborea and, finally, P. nigra. An association between the low molecular weight PAHs and 50% burn‐off temperature differential scanning calorimetry supports the idea of fire smoke as the main source of low molecular weight PAHs in charred biomass generated at temperatures of 200–400 °C. Instead, the fraction of high molecular weight PAHs is related to hydrogen‐to‐carbon and oxygen‐to‐carbon ash‐free dry weight, with charring depending on their organic matter content in the burnt material. PAH mobility will depend on the solubility of the organic matter, which is higher at higher pHs. The higher risk is the transport downstream to rivers or wet systems.