| Title |
Response surface methodology (RSM) modeling to improve removal of ciprofloxacin from aqueous solutions in photocatalytic process using copper oxide nanoparticles (CuO/UV)
|
|---|---|
| Published in |
AMB Express, March 2018
|
| DOI | 10.1186/s13568-018-0579-2 |
| Pubmed ID | |
| Authors |
Nahid Khoshnamvand, Ferdos Kord Mostafapour, Amir Mohammadi, Maryam Faraji |
| Abstract |
Ciprofloxacin (CIP) antibiotic is considered as an emerging and biological resistant pollutant. This study aimed to improve of the removal of CIP from synthetic aqueous solutions in photocatalytic process through copper oxide nanoparticles as catalyst (CuO/UV). The effect of CIP concentration (10-200 mg/l), catalyst dosage included CuO (0.01-0.1 g/l) and pH (3-11) as independent variables on the COD removal efficiency as response in photocatalytic process using UV-C lamps with three different powers of 8, 15 and 30-W were optimized through the central composite design in response surface method using design-expert software. A second order model was selected as the best model with R2 values and lack of fit as 0.85 and 0.06 for lamp 8-W, 0.89 and 0.11 for lamp 15-W, and 0.86 and 0.19 for lamp 30-W, respectively. Optimum conditions were obtained in CIP concentration of 11.2 (mg/l), CuO dosage of 0.08 (g/l), and pH value of 8.17. In this condition, predicted maximum COD removal was respectively found 83.79, 93.18, and 98.90% for lamps 8, 15 and 30-W. According to the results, photocatalytic process using copper oxide nanoparticles can effectively compose CIP in aqueous solutions. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 89 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 16% |
| Student > Master | 13 | 15% |
| Student > Bachelor | 7 | 8% |
| Student > Doctoral Student | 6 | 7% |
| Researcher | 5 | 6% |
| Other | 9 | 10% |
| Unknown | 35 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 14 | 16% |
| Chemistry | 10 | 11% |
| Engineering | 9 | 10% |
| Chemical Engineering | 6 | 7% |
| Agricultural and Biological Sciences | 4 | 4% |
| Other | 7 | 8% |
| Unknown | 39 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 March 2018.
All research outputs
#15,498,204
of 23,031,582 outputs
Outputs from AMB Express
#447
of 1,241 outputs
Outputs of similar age
#210,475
of 329,889 outputs
Outputs of similar age from AMB Express
#15
of 61 outputs
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So far Altmetric has tracked 1,241 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
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We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.