scholarly journals Application of response surface methodology and green carbon dots as reducing agents in speciation of iron

RSC Advances ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 2173-2180 ◽  
Author(s):  
Masoud Shariati-Rad ◽  
Tahereh Mohseninasab ◽  
Fatemeh Parno
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Carbon Dots ◽  
Reducing Agents ◽  
Synthetic Approach ◽  
First Time

Herein, green synthetic approach was used to produce reducing carbon dots (CDs) and for the first time, corresponding reducing strengths were estimated.

scholarly journals Sustainable Synthesis Processes for Carbon Dots through Response Surface Methodology and Artificial Neural Network.

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 704 ◽  
Author(s):  
Yahaya Pudza ◽  
Zainal Abidin ◽  
Abdul Rashid ◽  
Md Yasin ◽  
Noor ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Design Of Experiment ◽  
Smart Materials ◽  
Carbon Dots ◽  
Synthesis Process ◽  
Artificial Neural ◽  
Hidden Layer

Nowadays, to ensure sustainability of smart materials, it is imperative to eliminate or reduce carbon footprint related to nano material production. The concept of design of experiment to provide an optimal synthesis process, with a desired yield, is indispensable. It is the researcher’s goal to get optimum value for experiments that requires multiple runs and multiple inputs. Herein, is a reliable approach of utilizing design of experiment (DOE) for response surface methodology (RSM). Thus, to optimize a facile and effective synthesis process for fluorescent carbon dots (CDs) derived from tapioca that is in line with green chemistry principles for sustainable synthesis. The predictions for fluorescent CDs synthesis from RSM were in excellent agreement with the artificial neural network (ANN) model prediction by the Levenberg–Marquardt back propagation (LMBP) algorithm. Considering R2, root mean square error (RMSE) and mean absolute error (MAE) have all revealed a positive hidden layer size. The best hidden layer of neurons were discovered at point 4-8, to confirm the validity of carbon dots, characterization of surface morphology and particles sizes of CDs were conducted with favorable confirmations of the unique characteristics and attributes of synthesized CDs by hydrothermal route.

scholarly journals Response Surface Methodology for the Optimisation of Electrochemical Biosensors for Heavy Metals Detection

Biosensors ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 26 ◽  
Author(s):  
Giuseppe De Benedetto ◽  
Sabrina Di Masi ◽  
Antonio Pennetta ◽  
Cosimino Malitesta
Keyword(s):  
Response Surface Methodology ◽  
Experimental Design ◽  
Response Surface ◽  
Enzyme Concentration ◽  
Experimental Parameters ◽  
Number Of Cycles ◽  
Metal Ions Detection ◽  
First Time ◽  
Central Composite ◽  
Biosensor Response

Herein, we report the application of a chemometric tool for the optimisation of electrochemical biosensor performances. The experimental design was performed based on the responses of an amperometric biosensor developed for metal ions detection using the flow injection analysis. The electrode preparation and the working conditions were selected as experimental parameters, and thus, were modelled by a response surface methodology (RSM). In particular, enzyme concentration, flow rates, and number of cycles were reported as continuous factors, while the sensitivities of the biosensor (S, µA·mM−1) towards metals, such as Bi3+ and Al3+ were collected as responses and optimised by a central composite design (CCD). Bi3+ and Al3+ inhibition on the Pt/PPD/GOx biosensor response is for the first time reported. The optimal enzyme concentration, scan cycles and flow rate were found to be 50 U·mL−1, 30 and, 0.3 mL·min−1, respectively. Descriptive/predictive performances are discussed: the sensitivities of the optimised biosensor agreed with the experimental design prediction. The responses under the optimised conditions were also tested towards Ni2+ and Ag+ ions. The multivariate approach used in this work allowed us to obtain a wide working range for the biosensor, coupled with a high reproducibility of the response (RSD = 0.72%).

scholarly journals Polysaccharides and polyphenol in dried Morinda citrifolia fruit tea after different processing conditions: Optimization analysis using response surface methodology

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11507
Author(s):  
Qingfen Wang ◽  
Fei Yang ◽  
Dandan Jia ◽  
Tian Wu
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Maximum Level ◽  
Scientific Basis ◽  
Morinda Citrifolia ◽  
Tea Polysaccharides ◽  
Fruit Powder ◽  
First Time ◽  
Optimum Extraction ◽  
Boiled Water

The increasing popularity of Morinda citrifolia has many medical and health benefits because of its rich polysaccharides (PSC) and polyphenols (PPN). It has become popular to brew the dry M. citrifolia fruit slice as tea in some regions of China. In this study, optimize the extraction parameters of M. citrifolia fruit tea polysaccharides and polyphenols using response surface methodology. The results indicated the highest PSC yield of 17% at 46 °C for 11 min and the ratio of water/M. citrifolia fruit powder was 78 mL/g. The optimum extraction of PPN was at 95 °C for 10 min and the ratio of water/M. citrifolia fruit powder 90 mL/g, with 8.93% yield. Using dry M. citrifolia fruit slices as a tea is reported for the first time. Based on the results, the maximum level of PSC can be obtained under condition by infusing about four dried M. citrifolia fruit slice with average thickness and size in warm boiled water for 11 min, taking a 300 mL cup (300 mL of water) for example. The maximum level of PPN can be obtained by adding three slices of dried M. citrifolia fruit slice to boiled water for 10 min. Considering the powder used in our study, the further pulverization of cutting into powder is more conducive to material precipitation. This study provides a scientific basis for obtaining PSC and PPN from dry M. citrifolia fruit slice tea by brewing.

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