Green synthesis of iron oxide nanoparticles for arsenic remediation in water and sludge utilization
Iron oxide nanoparticles (IONPs) were synthesized via an affordable and environmentally friendly route using waste banana peel extract. The polyphenol-rich extract acted as a stabilizing and reducing agent resulting in formation of α-Fe 2 O 3 with a particle size of around 60 nm. The composition, ph...
Gespeichert in:
| Veröffentlicht in: | Clean technologies and environmental policy 2019-05, Vol.21 (4), p.795-813 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 813 |
|---|---|
| container_issue | 4 |
| container_start_page | 795 |
| container_title | Clean technologies and environmental policy |
| container_volume | 21 |
| creator | Majumder, Abhradeep Ramrakhiani, Lata Mukherjee, Debarati Mishra, Umesh Halder, Avik Mandal, Ashish K. Ghosh, Sourja |
| description | Iron oxide nanoparticles (IONPs) were synthesized via an affordable and environmentally friendly route using waste banana peel extract. The polyphenol-rich extract acted as a stabilizing and reducing agent resulting in formation of α-Fe
2
O
3
with a particle size of around 60 nm. The composition, phase, morphology and size of the nanoparticles were analyzed by X-ray diffraction, field emission scanning electron microscopy, Fourier transform infrared spectroscopy, transmission electron microscopy and a Zetasizer. The efficiency of the IONPs was assessed in terms of arsenic(V) remediation from contaminated water within the range of 0.1–2.0 mg/L. Batch study showed that IONPs had a high As(V) adsorption capacity of about 2.715 mg/g at 40 °C. A statistical approach, viz. an artificial neural network, was adapted for modeling and optimization of the process parameters for achieving maximum As(V) removal efficiency. A set of 54 experimental sets were conducted and the predicted model generated showed an
R
2
value of 0.9971 and the corresponding mean squared error value was 0.0000601. Surface binding of the As(V) phenomenon on the green synthesized IONPs was explained on the basis of FTIR spectroscopy, X-ray photoelectron spectroscopy, X-ray fluorescence spectroscopy of the control and the As(V)-loaded IONPs.The spent adsorbent was successfully immobilized in phosphate glass matrix with an objective to provide a complete and sustainable solution for arsenic contamination.
Graphical abstract |
| doi_str_mv | 10.1007/s10098-019-01669-1 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2177847986</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2177847986</sourcerecordid><originalsourceid>FETCH-LOGICAL-c356t-b09585bd295539ed4c75f57181151aa83ddf450c9a099c6c890c8cc5d47cea543</originalsourceid><addsrcrecordid>eNp9UMtKAzEUDaJgrf6Aq4Dr0WRmMkmWUrQVCm4U3IU0uVNTpklNZtD69caO6M7FfcB53MtB6JKSa0oIv0m5S1EQKnM1jSzoEZrQhopCMiaOf_f65RSdpbQhpCx5SSbIzCOAx2nv-1dILuHQYheDx-HDWcBe-7DTsXemg4TbELGOCbwzOMIWrNO9y1zn8bvuIYPe4tQNdg146F3nPg_4OTppdZfg4mdO0fP93dNsUSwf5w-z22VhKtb0xYpIJtjKlvnlSoKtDWct41RQyqjWorK2rRkxUhMpTWOEJEYYw2zNDWhWV1N0NfruYngbIPVqE4bo80lVUs5FzaVoMqscWSaGlCK0ahfdVse9okR9h6nGMFUOUx3CVDSLqlGUMtmvIf5Z_6P6AmvaePk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2177847986</pqid></control><display><type>article</type><title>Green synthesis of iron oxide nanoparticles for arsenic remediation in water and sludge utilization</title><source>PAIS Index</source><source>SpringerLink Journals - AutoHoldings</source><creator>Majumder, Abhradeep ; Ramrakhiani, Lata ; Mukherjee, Debarati ; Mishra, Umesh ; Halder, Avik ; Mandal, Ashish K. ; Ghosh, Sourja</creator><creatorcontrib>Majumder, Abhradeep ; Ramrakhiani, Lata ; Mukherjee, Debarati ; Mishra, Umesh ; Halder, Avik ; Mandal, Ashish K. ; Ghosh, Sourja</creatorcontrib><description>Iron oxide nanoparticles (IONPs) were synthesized via an affordable and environmentally friendly route using waste banana peel extract. The polyphenol-rich extract acted as a stabilizing and reducing agent resulting in formation of α-Fe
2
O
3
with a particle size of around 60 nm. The composition, phase, morphology and size of the nanoparticles were analyzed by X-ray diffraction, field emission scanning electron microscopy, Fourier transform infrared spectroscopy, transmission electron microscopy and a Zetasizer. The efficiency of the IONPs was assessed in terms of arsenic(V) remediation from contaminated water within the range of 0.1–2.0 mg/L. Batch study showed that IONPs had a high As(V) adsorption capacity of about 2.715 mg/g at 40 °C. A statistical approach, viz. an artificial neural network, was adapted for modeling and optimization of the process parameters for achieving maximum As(V) removal efficiency. A set of 54 experimental sets were conducted and the predicted model generated showed an
R
2
value of 0.9971 and the corresponding mean squared error value was 0.0000601. Surface binding of the As(V) phenomenon on the green synthesized IONPs was explained on the basis of FTIR spectroscopy, X-ray photoelectron spectroscopy, X-ray fluorescence spectroscopy of the control and the As(V)-loaded IONPs.The spent adsorbent was successfully immobilized in phosphate glass matrix with an objective to provide a complete and sustainable solution for arsenic contamination.
Graphical abstract</description><identifier>ISSN: 1618-954X</identifier><identifier>EISSN: 1618-9558</identifier><identifier>DOI: 10.1007/s10098-019-01669-1</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Arsenic ; Artificial neural networks ; Contamination ; Earth and Environmental Science ; Emission analysis ; Environment ; Environmental Economics ; Environmental Engineering/Biotechnology ; Environmental policy ; Field emission microscopy ; Fluorescence spectroscopy ; Fourier transforms ; Industrial and Production Engineering ; Industrial Chemistry/Chemical Engineering ; Infrared spectroscopy ; Iron oxides ; Microscopy ; Morphology ; Nanoparticles ; Neural networks ; Original Paper ; Phosphate glass ; Photoelectron spectroscopy ; Photoelectrons ; Plant extracts ; Process parameters ; Reducing agents ; Remediation ; Scanning electron microscopy ; Sludge ; Sludge utilization ; Spectrum analysis ; Sustainable Development ; Synthesis ; Transmission electron microscopy ; Water pollution ; X ray photoelectron spectroscopy ; X-ray diffraction ; X-ray fluorescence</subject><ispartof>Clean technologies and environmental policy, 2019-05, Vol.21 (4), p.795-813</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2019</rights><rights>Clean Technologies and Environmental Policy is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-b09585bd295539ed4c75f57181151aa83ddf450c9a099c6c890c8cc5d47cea543</citedby><cites>FETCH-LOGICAL-c356t-b09585bd295539ed4c75f57181151aa83ddf450c9a099c6c890c8cc5d47cea543</cites><orcidid>0000-0001-9172-1214</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10098-019-01669-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10098-019-01669-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27864,27922,27923,41486,42555,51317</link.rule.ids></links><search><creatorcontrib>Majumder, Abhradeep</creatorcontrib><creatorcontrib>Ramrakhiani, Lata</creatorcontrib><creatorcontrib>Mukherjee, Debarati</creatorcontrib><creatorcontrib>Mishra, Umesh</creatorcontrib><creatorcontrib>Halder, Avik</creatorcontrib><creatorcontrib>Mandal, Ashish K.</creatorcontrib><creatorcontrib>Ghosh, Sourja</creatorcontrib><title>Green synthesis of iron oxide nanoparticles for arsenic remediation in water and sludge utilization</title><title>Clean technologies and environmental policy</title><addtitle>Clean Techn Environ Policy</addtitle><description>Iron oxide nanoparticles (IONPs) were synthesized via an affordable and environmentally friendly route using waste banana peel extract. The polyphenol-rich extract acted as a stabilizing and reducing agent resulting in formation of α-Fe
2
O
3
with a particle size of around 60 nm. The composition, phase, morphology and size of the nanoparticles were analyzed by X-ray diffraction, field emission scanning electron microscopy, Fourier transform infrared spectroscopy, transmission electron microscopy and a Zetasizer. The efficiency of the IONPs was assessed in terms of arsenic(V) remediation from contaminated water within the range of 0.1–2.0 mg/L. Batch study showed that IONPs had a high As(V) adsorption capacity of about 2.715 mg/g at 40 °C. A statistical approach, viz. an artificial neural network, was adapted for modeling and optimization of the process parameters for achieving maximum As(V) removal efficiency. A set of 54 experimental sets were conducted and the predicted model generated showed an
R
2
value of 0.9971 and the corresponding mean squared error value was 0.0000601. Surface binding of the As(V) phenomenon on the green synthesized IONPs was explained on the basis of FTIR spectroscopy, X-ray photoelectron spectroscopy, X-ray fluorescence spectroscopy of the control and the As(V)-loaded IONPs.The spent adsorbent was successfully immobilized in phosphate glass matrix with an objective to provide a complete and sustainable solution for arsenic contamination.
Graphical abstract</description><subject>Arsenic</subject><subject>Artificial neural networks</subject><subject>Contamination</subject><subject>Earth and Environmental Science</subject><subject>Emission analysis</subject><subject>Environment</subject><subject>Environmental Economics</subject><subject>Environmental Engineering/Biotechnology</subject><subject>Environmental policy</subject><subject>Field emission microscopy</subject><subject>Fluorescence spectroscopy</subject><subject>Fourier transforms</subject><subject>Industrial and Production Engineering</subject><subject>Industrial Chemistry/Chemical Engineering</subject><subject>Infrared spectroscopy</subject><subject>Iron oxides</subject><subject>Microscopy</subject><subject>Morphology</subject><subject>Nanoparticles</subject><subject>Neural networks</subject><subject>Original Paper</subject><subject>Phosphate glass</subject><subject>Photoelectron spectroscopy</subject><subject>Photoelectrons</subject><subject>Plant extracts</subject><subject>Process parameters</subject><subject>Reducing agents</subject><subject>Remediation</subject><subject>Scanning electron microscopy</subject><subject>Sludge</subject><subject>Sludge utilization</subject><subject>Spectrum analysis</subject><subject>Sustainable Development</subject><subject>Synthesis</subject><subject>Transmission electron microscopy</subject><subject>Water pollution</subject><subject>X ray photoelectron spectroscopy</subject><subject>X-ray diffraction</subject><subject>X-ray fluorescence</subject><issn>1618-954X</issn><issn>1618-9558</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9UMtKAzEUDaJgrf6Aq4Dr0WRmMkmWUrQVCm4U3IU0uVNTpklNZtD69caO6M7FfcB53MtB6JKSa0oIv0m5S1EQKnM1jSzoEZrQhopCMiaOf_f65RSdpbQhpCx5SSbIzCOAx2nv-1dILuHQYheDx-HDWcBe-7DTsXemg4TbELGOCbwzOMIWrNO9y1zn8bvuIYPe4tQNdg146F3nPg_4OTppdZfg4mdO0fP93dNsUSwf5w-z22VhKtb0xYpIJtjKlvnlSoKtDWct41RQyqjWorK2rRkxUhMpTWOEJEYYw2zNDWhWV1N0NfruYngbIPVqE4bo80lVUs5FzaVoMqscWSaGlCK0ahfdVse9okR9h6nGMFUOUx3CVDSLqlGUMtmvIf5Z_6P6AmvaePk</recordid><startdate>20190501</startdate><enddate>20190501</enddate><creator>Majumder, Abhradeep</creator><creator>Ramrakhiani, Lata</creator><creator>Mukherjee, Debarati</creator><creator>Mishra, Umesh</creator><creator>Halder, Avik</creator><creator>Mandal, Ashish K.</creator><creator>Ghosh, Sourja</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7ST</scope><scope>7TA</scope><scope>7TQ</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X2</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DHY</scope><scope>DON</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>K60</scope><scope>K6~</scope><scope>KR7</scope><scope>L.-</scope><scope>L6V</scope><scope>M0C</scope><scope>M0K</scope><scope>M2O</scope><scope>M2P</scope><scope>M2R</scope><scope>M7S</scope><scope>MBDVC</scope><scope>PATMY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0001-9172-1214</orcidid></search><sort><creationdate>20190501</creationdate><title>Green synthesis of iron oxide nanoparticles for arsenic remediation in water and sludge utilization</title><author>Majumder, Abhradeep ; Ramrakhiani, Lata ; Mukherjee, Debarati ; Mishra, Umesh ; Halder, Avik ; Mandal, Ashish K. ; Ghosh, Sourja</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-b09585bd295539ed4c75f57181151aa83ddf450c9a099c6c890c8cc5d47cea543</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Arsenic</topic><topic>Artificial neural networks</topic><topic>Contamination</topic><topic>Earth and Environmental Science</topic><topic>Emission analysis</topic><topic>Environment</topic><topic>Environmental Economics</topic><topic>Environmental Engineering/Biotechnology</topic><topic>Environmental policy</topic><topic>Field emission microscopy</topic><topic>Fluorescence spectroscopy</topic><topic>Fourier transforms</topic><topic>Industrial and Production Engineering</topic><topic>Industrial Chemistry/Chemical Engineering</topic><topic>Infrared spectroscopy</topic><topic>Iron oxides</topic><topic>Microscopy</topic><topic>Morphology</topic><topic>Nanoparticles</topic><topic>Neural networks</topic><topic>Original Paper</topic><topic>Phosphate glass</topic><topic>Photoelectron spectroscopy</topic><topic>Photoelectrons</topic><topic>Plant extracts</topic><topic>Process parameters</topic><topic>Reducing agents</topic><topic>Remediation</topic><topic>Scanning electron microscopy</topic><topic>Sludge</topic><topic>Sludge utilization</topic><topic>Spectrum analysis</topic><topic>Sustainable Development</topic><topic>Synthesis</topic><topic>Transmission electron microscopy</topic><topic>Water pollution</topic><topic>X ray photoelectron spectroscopy</topic><topic>X-ray diffraction</topic><topic>X-ray fluorescence</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Majumder, Abhradeep</creatorcontrib><creatorcontrib>Ramrakhiani, Lata</creatorcontrib><creatorcontrib>Mukherjee, Debarati</creatorcontrib><creatorcontrib>Mishra, Umesh</creatorcontrib><creatorcontrib>Halder, Avik</creatorcontrib><creatorcontrib>Mandal, Ashish K.</creatorcontrib><creatorcontrib>Ghosh, Sourja</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment Abstracts</collection><collection>Materials Business File</collection><collection>PAIS Index</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Civil Engineering Abstracts</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM Global</collection><collection>Agricultural Science Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Social Science Database</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Environmental Science Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><jtitle>Clean technologies and environmental policy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Majumder, Abhradeep</au><au>Ramrakhiani, Lata</au><au>Mukherjee, Debarati</au><au>Mishra, Umesh</au><au>Halder, Avik</au><au>Mandal, Ashish K.</au><au>Ghosh, Sourja</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Green synthesis of iron oxide nanoparticles for arsenic remediation in water and sludge utilization</atitle><jtitle>Clean technologies and environmental policy</jtitle><stitle>Clean Techn Environ Policy</stitle><date>2019-05-01</date><risdate>2019</risdate><volume>21</volume><issue>4</issue><spage>795</spage><epage>813</epage><pages>795-813</pages><issn>1618-954X</issn><eissn>1618-9558</eissn><abstract>Iron oxide nanoparticles (IONPs) were synthesized via an affordable and environmentally friendly route using waste banana peel extract. The polyphenol-rich extract acted as a stabilizing and reducing agent resulting in formation of α-Fe
2
O
3
with a particle size of around 60 nm. The composition, phase, morphology and size of the nanoparticles were analyzed by X-ray diffraction, field emission scanning electron microscopy, Fourier transform infrared spectroscopy, transmission electron microscopy and a Zetasizer. The efficiency of the IONPs was assessed in terms of arsenic(V) remediation from contaminated water within the range of 0.1–2.0 mg/L. Batch study showed that IONPs had a high As(V) adsorption capacity of about 2.715 mg/g at 40 °C. A statistical approach, viz. an artificial neural network, was adapted for modeling and optimization of the process parameters for achieving maximum As(V) removal efficiency. A set of 54 experimental sets were conducted and the predicted model generated showed an
R
2
value of 0.9971 and the corresponding mean squared error value was 0.0000601. Surface binding of the As(V) phenomenon on the green synthesized IONPs was explained on the basis of FTIR spectroscopy, X-ray photoelectron spectroscopy, X-ray fluorescence spectroscopy of the control and the As(V)-loaded IONPs.The spent adsorbent was successfully immobilized in phosphate glass matrix with an objective to provide a complete and sustainable solution for arsenic contamination.
Graphical abstract</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s10098-019-01669-1</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0001-9172-1214</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1618-954X |
| ispartof | Clean technologies and environmental policy, 2019-05, Vol.21 (4), p.795-813 |
| issn | 1618-954X 1618-9558 |
| language | eng |
| recordid | cdi_proquest_journals_2177847986 |
| source | PAIS Index; SpringerLink Journals - AutoHoldings |
| subjects | Arsenic Artificial neural networks Contamination Earth and Environmental Science Emission analysis Environment Environmental Economics Environmental Engineering/Biotechnology Environmental policy Field emission microscopy Fluorescence spectroscopy Fourier transforms Industrial and Production Engineering Industrial Chemistry/Chemical Engineering Infrared spectroscopy Iron oxides Microscopy Morphology Nanoparticles Neural networks Original Paper Phosphate glass Photoelectron spectroscopy Photoelectrons Plant extracts Process parameters Reducing agents Remediation Scanning electron microscopy Sludge Sludge utilization Spectrum analysis Sustainable Development Synthesis Transmission electron microscopy Water pollution X ray photoelectron spectroscopy X-ray diffraction X-ray fluorescence |
| title | Green synthesis of iron oxide nanoparticles for arsenic remediation in water and sludge utilization |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T07%3A27%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Green%20synthesis%20of%20iron%20oxide%20nanoparticles%20for%20arsenic%20remediation%20in%20water%20and%20sludge%20utilization&rft.jtitle=Clean%20technologies%20and%20environmental%20policy&rft.au=Majumder,%20Abhradeep&rft.date=2019-05-01&rft.volume=21&rft.issue=4&rft.spage=795&rft.epage=813&rft.pages=795-813&rft.issn=1618-954X&rft.eissn=1618-9558&rft_id=info:doi/10.1007/s10098-019-01669-1&rft_dat=%3Cproquest_cross%3E2177847986%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2177847986&rft_id=info:pmid/&rfr_iscdi=true |