An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique
<p dir="ltr">Tetracyclines (TCs) have been extensively used for humans and animal diseases treatment and livestock growth promotion. The consumption of such antibiotics has been ever-growing nowadays due to various bacterial infections and other pathologic conditions, resulting in mo...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , , , , |
| Published: |
2022
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1864513531615903744 |
|---|---|
| author | Majedeh Gheytanzadeh (17541927) |
| author2 | Alireza Baghban (5159648) Sajjad Habibzadeh (5548580) Karam Jabbour (17541942) Amin Esmaeili (17541204) Ahmad Mohaddespour (17541948) Otman Abida (2071714) |
| author2_role | author author author author author author |
| author_facet | Majedeh Gheytanzadeh (17541927) Alireza Baghban (5159648) Sajjad Habibzadeh (5548580) Karam Jabbour (17541942) Amin Esmaeili (17541204) Ahmad Mohaddespour (17541948) Otman Abida (2071714) |
| author_role | author |
| dc.creator.none.fl_str_mv | Majedeh Gheytanzadeh (17541927) Alireza Baghban (5159648) Sajjad Habibzadeh (5548580) Karam Jabbour (17541942) Amin Esmaeili (17541204) Ahmad Mohaddespour (17541948) Otman Abida (2071714) |
| dc.date.none.fl_str_mv | 2022-04-22T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1038/s41598-022-10563-8 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/An_insight_into_tetracycline_photocatalytic_degradation_by_MOFs_using_the_artificial_intelligence_technique/24717477 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Chemical sciences Physical chemistry Theoretical and computational chemistry Engineering Chemical engineering Information and computing sciences Artificial intelligence Machine learning Tetracyclines (TCs) MOFs Artificial intelligence Gaussian process regression (GPR) |
| dc.title.none.fl_str_mv | An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Tetracyclines (TCs) have been extensively used for humans and animal diseases treatment and livestock growth promotion. The consumption of such antibiotics has been ever-growing nowadays due to various bacterial infections and other pathologic conditions, resulting in more discharge into the aquatic environments. This brings threats to ecosystems and human bodies. Up to now, several attempts have been made to reduce TC amounts in the wastewater, among which photocatalysis, an advanced oxidation process, is known as an eco-friendly and efficient technology. In this regard, metal organic frameworks (MOFs) have been known as the promising materials as photocatalysts. Thus, studying TC photocatalytic degradation by MOFs would help scientists and engineers optimize the process in terms of effective parameters. Nevertheless, the costly and time-consuming experimental methods, having instrumental errors, encouraged the authors to use the computational method for a more comprehensive assessment. In doing so, a wide-ranging databank including 374 experimental data points was gathered from the literature. A powerful machine learning method of Gaussian process regression (GPR) model with four kernel functions was proposed to estimate the TC degradation in terms of MOFs features (surface area and pore volume) and operational parameters (illumination time, catalyst dosage, TC concentration, pH). The GPR models performed quite well, among which GPR-Matern model shows the most accurate performance with R2, MRE, MSE, RMSE, and STD of 0.981, 12.29, 18.03, 4.25, and 3.33, respectively. In addition, an analysis of sensitivity was carried out to assess the effect of the inputs on the TC photodegradation by MOFs. It revealed that the illumination time and the surface area play a significant role in the decomposition activity.</p><h2>Other Information</h2><p dir="ltr">Published in: Scientific Reports<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/s41598-022-10563-8" target="_blank">https://dx.doi.org/10.1038/s41598-022-10563-8</a></p><p dir="ltr">Disclaimer: The University of Doha for Science and Technology replaced the now-former College of the North Atlantic-Qatar after an Amiri decision in 2022. UDST has become and first national applied University in Qatar; it is also second national University in the country.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_e771fa1ac5da1ef5f86d86a8256ec029 |
| identifier_str_mv | 10.1038/s41598-022-10563-8 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24717477 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence techniqueMajedeh Gheytanzadeh (17541927)Alireza Baghban (5159648)Sajjad Habibzadeh (5548580)Karam Jabbour (17541942)Amin Esmaeili (17541204)Ahmad Mohaddespour (17541948)Otman Abida (2071714)Chemical sciencesPhysical chemistryTheoretical and computational chemistryEngineeringChemical engineeringInformation and computing sciencesArtificial intelligenceMachine learningTetracyclines (TCs)MOFsArtificial intelligenceGaussian process regression (GPR)<p dir="ltr">Tetracyclines (TCs) have been extensively used for humans and animal diseases treatment and livestock growth promotion. The consumption of such antibiotics has been ever-growing nowadays due to various bacterial infections and other pathologic conditions, resulting in more discharge into the aquatic environments. This brings threats to ecosystems and human bodies. Up to now, several attempts have been made to reduce TC amounts in the wastewater, among which photocatalysis, an advanced oxidation process, is known as an eco-friendly and efficient technology. In this regard, metal organic frameworks (MOFs) have been known as the promising materials as photocatalysts. Thus, studying TC photocatalytic degradation by MOFs would help scientists and engineers optimize the process in terms of effective parameters. Nevertheless, the costly and time-consuming experimental methods, having instrumental errors, encouraged the authors to use the computational method for a more comprehensive assessment. In doing so, a wide-ranging databank including 374 experimental data points was gathered from the literature. A powerful machine learning method of Gaussian process regression (GPR) model with four kernel functions was proposed to estimate the TC degradation in terms of MOFs features (surface area and pore volume) and operational parameters (illumination time, catalyst dosage, TC concentration, pH). The GPR models performed quite well, among which GPR-Matern model shows the most accurate performance with R2, MRE, MSE, RMSE, and STD of 0.981, 12.29, 18.03, 4.25, and 3.33, respectively. In addition, an analysis of sensitivity was carried out to assess the effect of the inputs on the TC photodegradation by MOFs. It revealed that the illumination time and the surface area play a significant role in the decomposition activity.</p><h2>Other Information</h2><p dir="ltr">Published in: Scientific Reports<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/s41598-022-10563-8" target="_blank">https://dx.doi.org/10.1038/s41598-022-10563-8</a></p><p dir="ltr">Disclaimer: The University of Doha for Science and Technology replaced the now-former College of the North Atlantic-Qatar after an Amiri decision in 2022. UDST has become and first national applied University in Qatar; it is also second national University in the country.</p>2022-04-22T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1038/s41598-022-10563-8https://figshare.com/articles/journal_contribution/An_insight_into_tetracycline_photocatalytic_degradation_by_MOFs_using_the_artificial_intelligence_technique/24717477CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/247174772022-04-22T03:00:00Z |
| spellingShingle | An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique Majedeh Gheytanzadeh (17541927) Chemical sciences Physical chemistry Theoretical and computational chemistry Engineering Chemical engineering Information and computing sciences Artificial intelligence Machine learning Tetracyclines (TCs) MOFs Artificial intelligence Gaussian process regression (GPR) |
| status_str | publishedVersion |
| title | An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique |
| title_full | An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique |
| title_fullStr | An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique |
| title_full_unstemmed | An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique |
| title_short | An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique |
| title_sort | An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique |
| topic | Chemical sciences Physical chemistry Theoretical and computational chemistry Engineering Chemical engineering Information and computing sciences Artificial intelligence Machine learning Tetracyclines (TCs) MOFs Artificial intelligence Gaussian process regression (GPR) |