Green synthesis of zinc oxide nanoparticles from Sida acuta leaf extract for antibacterial and antioxidant applications, and catalytic degradation of dye through the use of convolutional neural network

This study synthesized zinc oxide nanoparticles (ZnO NPs) using a novel green approach, with Sida acuta leaf extract as a capping and reducing agent to initiate nucleation and structure formation. The innovation of this study lies in demonstrating the originality of utilizing zinc oxide nanoparticle...

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Veröffentlicht in:Environmental research 2024-10, Vol.258, p.119204, Article 119204
Hauptverfasser: Du, Jiang, AL-Huqail, Arwa, Cao, Yan, Yao, Hui, Sun, Yiding, Garaleh, Mazen, El Sayed Massoud, Ehab, Ali, Elimam, Assilzadeh, Hamid, Escorcia-Gutierrez, José
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container_title Environmental research
container_volume 258
creator Du, Jiang
AL-Huqail, Arwa
Cao, Yan
Yao, Hui
Sun, Yiding
Garaleh, Mazen
El Sayed Massoud, Ehab
Ali, Elimam
Assilzadeh, Hamid
Escorcia-Gutierrez, José
description This study synthesized zinc oxide nanoparticles (ZnO NPs) using a novel green approach, with Sida acuta leaf extract as a capping and reducing agent to initiate nucleation and structure formation. The innovation of this study lies in demonstrating the originality of utilizing zinc oxide nanoparticles for antibacterial action, antioxidant potential, and catalytic degradation of Congo red dye. This unique approach harnesses eco-friendly methods to initiate nucleation and structure formation. The synthesized nanoparticles' structure and conformation were characterized using UV–vis (λmax = 280 nm), X-ray, atomic force microscopy, SEM, HR-TEM and FTIR. The antibacterial activity of the Nps was tested against Pseudomonas sp, Klebsiella sp, Staphylococcus aureus, and E. coli, demonstrating efficacy. The nanoparticles exhibited unique properties, with a crystallite size of 20 nm (XRD), a surface roughness of 2.5 nm (AFM), and a specific surface area of 60 m2/g (SEM). A Convolutional Neural Network (CNN) was effectively employed to accurately classify and analyze microscopic images of green-synthesized zinc oxide nanoparticles. This research revealed their exceptional antioxidant potential, with an average DPPH scavenging rate of 80% at a concentration of 0.05 mg/mL. Additionally, zeta potential measurements indicated a stable net negative surface charge of approximately −12.2 mV. These quantitative findings highlight the promising applications of green-synthesized ZnO NPs in healthcare, materials science, and environmental remediation. The ZnO nanoparticles exhibited catalytic capabilities for dye degradation, and the degradation rate was determined using UV spectroscopy. Key findings of the study encompass the green synthesis of versatile zinc oxide nanoparticles, demonstrating potent antibacterial action, antioxidant capabilities, and catalytic dye degradation potential. These nanoparticles offer multifaceted solutions with minimal environmental impact, addressing challenges in various fields, from healthcare to environmental remediation. [Display omitted] •Eco-friendly production of ZnO NPs using Sida acuta leaf extract demonstrates a green synthesis approach.•ZnO NPs exhibit efficacy against major pathogens like Pseudomonas, Klebsiella, S. aureus, and E. coli.•Enhanced antioxidant capability: The presence of flavonoids in ZnO NPs aids in combating oxidative stress effectively.•Potent catalytic degradation: ZnO NPs showcase efficient degradation of Congo red dy
doi_str_mv 10.1016/j.envres.2024.119204
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The innovation of this study lies in demonstrating the originality of utilizing zinc oxide nanoparticles for antibacterial action, antioxidant potential, and catalytic degradation of Congo red dye. This unique approach harnesses eco-friendly methods to initiate nucleation and structure formation. The synthesized nanoparticles' structure and conformation were characterized using UV–vis (λmax = 280 nm), X-ray, atomic force microscopy, SEM, HR-TEM and FTIR. The antibacterial activity of the Nps was tested against Pseudomonas sp, Klebsiella sp, Staphylococcus aureus, and E. coli, demonstrating efficacy. The nanoparticles exhibited unique properties, with a crystallite size of 20 nm (XRD), a surface roughness of 2.5 nm (AFM), and a specific surface area of 60 m2/g (SEM). A Convolutional Neural Network (CNN) was effectively employed to accurately classify and analyze microscopic images of green-synthesized zinc oxide nanoparticles. This research revealed their exceptional antioxidant potential, with an average DPPH scavenging rate of 80% at a concentration of 0.05 mg/mL. Additionally, zeta potential measurements indicated a stable net negative surface charge of approximately −12.2 mV. These quantitative findings highlight the promising applications of green-synthesized ZnO NPs in healthcare, materials science, and environmental remediation. The ZnO nanoparticles exhibited catalytic capabilities for dye degradation, and the degradation rate was determined using UV spectroscopy. Key findings of the study encompass the green synthesis of versatile zinc oxide nanoparticles, demonstrating potent antibacterial action, antioxidant capabilities, and catalytic dye degradation potential. These nanoparticles offer multifaceted solutions with minimal environmental impact, addressing challenges in various fields, from healthcare to environmental remediation. [Display omitted] •Eco-friendly production of ZnO NPs using Sida acuta leaf extract demonstrates a green synthesis approach.•ZnO NPs exhibit efficacy against major pathogens like Pseudomonas, Klebsiella, S. aureus, and E. coli.•Enhanced antioxidant capability: The presence of flavonoids in ZnO NPs aids in combating oxidative stress effectively.•Potent catalytic degradation: ZnO NPs showcase efficient degradation of Congo red dye, as proven by UV spectroscopy.•CNN application: Successful classification and analysis of synthesized ZnO NPs using a Convolutional Neural Network.</description><identifier>ISSN: 0013-9351</identifier><identifier>ISSN: 1096-0953</identifier><identifier>EISSN: 1096-0953</identifier><identifier>DOI: 10.1016/j.envres.2024.119204</identifier><identifier>PMID: 38802033</identifier><language>eng</language><publisher>Netherlands: Elsevier Inc</publisher><subject>Antibacterial activity ; Antibacterial efficacy ; antibacterial properties ; antioxidant activity ; Antioxidant potential ; antioxidants ; atomic force microscopy ; Catalytic dye degradation ; Congo red ; Convolutional neural network (CNN) ; crystallites ; environmental impact ; Escherichia coli ; health services ; Klebsiella ; leaf extracts ; nanoparticles ; neural networks ; Pseudomonas ; remediation ; Sida acuta ; Staphylococcus aureus ; surface area ; surface roughness ; ultraviolet-visible spectroscopy ; X-radiation ; zeta potential ; zinc oxide ; Zinc oxide NPs synthesis</subject><ispartof>Environmental research, 2024-10, Vol.258, p.119204, Article 119204</ispartof><rights>2024</rights><rights>Copyright © 2024. Published by Elsevier Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c325t-9180787b2beb8ddbf79dc97aec634619015692f9ab831932daf414cc48b766663</citedby><cites>FETCH-LOGICAL-c325t-9180787b2beb8ddbf79dc97aec634619015692f9ab831932daf414cc48b766663</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0013935124011095$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38802033$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Du, Jiang</creatorcontrib><creatorcontrib>AL-Huqail, Arwa</creatorcontrib><creatorcontrib>Cao, Yan</creatorcontrib><creatorcontrib>Yao, Hui</creatorcontrib><creatorcontrib>Sun, Yiding</creatorcontrib><creatorcontrib>Garaleh, Mazen</creatorcontrib><creatorcontrib>El Sayed Massoud, Ehab</creatorcontrib><creatorcontrib>Ali, Elimam</creatorcontrib><creatorcontrib>Assilzadeh, Hamid</creatorcontrib><creatorcontrib>Escorcia-Gutierrez, José</creatorcontrib><title>Green synthesis of zinc oxide nanoparticles from Sida acuta leaf extract for antibacterial and antioxidant applications, and catalytic degradation of dye through the use of convolutional neural network</title><title>Environmental research</title><addtitle>Environ Res</addtitle><description>This study synthesized zinc oxide nanoparticles (ZnO NPs) using a novel green approach, with Sida acuta leaf extract as a capping and reducing agent to initiate nucleation and structure formation. The innovation of this study lies in demonstrating the originality of utilizing zinc oxide nanoparticles for antibacterial action, antioxidant potential, and catalytic degradation of Congo red dye. This unique approach harnesses eco-friendly methods to initiate nucleation and structure formation. The synthesized nanoparticles' structure and conformation were characterized using UV–vis (λmax = 280 nm), X-ray, atomic force microscopy, SEM, HR-TEM and FTIR. The antibacterial activity of the Nps was tested against Pseudomonas sp, Klebsiella sp, Staphylococcus aureus, and E. coli, demonstrating efficacy. The nanoparticles exhibited unique properties, with a crystallite size of 20 nm (XRD), a surface roughness of 2.5 nm (AFM), and a specific surface area of 60 m2/g (SEM). A Convolutional Neural Network (CNN) was effectively employed to accurately classify and analyze microscopic images of green-synthesized zinc oxide nanoparticles. This research revealed their exceptional antioxidant potential, with an average DPPH scavenging rate of 80% at a concentration of 0.05 mg/mL. Additionally, zeta potential measurements indicated a stable net negative surface charge of approximately −12.2 mV. These quantitative findings highlight the promising applications of green-synthesized ZnO NPs in healthcare, materials science, and environmental remediation. The ZnO nanoparticles exhibited catalytic capabilities for dye degradation, and the degradation rate was determined using UV spectroscopy. Key findings of the study encompass the green synthesis of versatile zinc oxide nanoparticles, demonstrating potent antibacterial action, antioxidant capabilities, and catalytic dye degradation potential. These nanoparticles offer multifaceted solutions with minimal environmental impact, addressing challenges in various fields, from healthcare to environmental remediation. [Display omitted] •Eco-friendly production of ZnO NPs using Sida acuta leaf extract demonstrates a green synthesis approach.•ZnO NPs exhibit efficacy against major pathogens like Pseudomonas, Klebsiella, S. aureus, and E. coli.•Enhanced antioxidant capability: The presence of flavonoids in ZnO NPs aids in combating oxidative stress effectively.•Potent catalytic degradation: ZnO NPs showcase efficient degradation of Congo red dye, as proven by UV spectroscopy.•CNN application: Successful classification and analysis of synthesized ZnO NPs using a Convolutional Neural Network.</description><subject>Antibacterial activity</subject><subject>Antibacterial efficacy</subject><subject>antibacterial properties</subject><subject>antioxidant activity</subject><subject>Antioxidant potential</subject><subject>antioxidants</subject><subject>atomic force microscopy</subject><subject>Catalytic dye degradation</subject><subject>Congo red</subject><subject>Convolutional neural network (CNN)</subject><subject>crystallites</subject><subject>environmental impact</subject><subject>Escherichia coli</subject><subject>health services</subject><subject>Klebsiella</subject><subject>leaf extracts</subject><subject>nanoparticles</subject><subject>neural networks</subject><subject>Pseudomonas</subject><subject>remediation</subject><subject>Sida acuta</subject><subject>Staphylococcus aureus</subject><subject>surface area</subject><subject>surface roughness</subject><subject>ultraviolet-visible spectroscopy</subject><subject>X-radiation</subject><subject>zeta potential</subject><subject>zinc oxide</subject><subject>Zinc oxide NPs synthesis</subject><issn>0013-9351</issn><issn>1096-0953</issn><issn>1096-0953</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNqFUU2PFCEQJUbjjqv_wBiOHuwRGvqDi4nZ6GqyiQf1TGio3mFkoAV63PEf-q-kp1ePyuXlVb16Reoh9JySLSW0fb3fgj9GSNua1HxLqagJf4A2lIi2IqJhD9GGEMoqwRp6gZ6ktC-UNow8Rhes70lNGNugX9cRwON08nkHySYcRvzTeo3DnTWAvfJhUjFb7SDhMYYD_myNwkrPWWEHasRwl6PSGY8hYuWzHQqBaJUrzJwri1VBrKbJWa1KwadX524hyp2KOzZwG5U595YvmBPgvIthvt0VBDwnWMo6-GNw86Iq_h7meIb8I8RvT9GjUbkEz-7xEn19_-7L1Yfq5tP1x6u3N5VmdZMrQXvS9d1QDzD0xgxjJ4wWnQLdMt5SQWjTinoUaugZFaw2auSUa837oWvLY5fo5eo7xfB9hpTlwSYNzikPYU6SlRt3hHPe_V9KWkpZX7e0SPkq1TGkFGGUU7QHFU-SErnkLfdyzVsuecs17zL24n7DPBzA_B36E3ARvFkFUE5ytBBl0ha8BmMj6CxNsP_e8BvPusLC</recordid><startdate>20241001</startdate><enddate>20241001</enddate><creator>Du, Jiang</creator><creator>AL-Huqail, Arwa</creator><creator>Cao, Yan</creator><creator>Yao, Hui</creator><creator>Sun, Yiding</creator><creator>Garaleh, Mazen</creator><creator>El Sayed Massoud, Ehab</creator><creator>Ali, Elimam</creator><creator>Assilzadeh, Hamid</creator><creator>Escorcia-Gutierrez, José</creator><general>Elsevier Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20241001</creationdate><title>Green synthesis of zinc oxide nanoparticles from Sida acuta leaf extract for antibacterial and antioxidant applications, and catalytic degradation of dye through the use of convolutional neural network</title><author>Du, Jiang ; AL-Huqail, Arwa ; Cao, Yan ; Yao, Hui ; Sun, Yiding ; Garaleh, Mazen ; El Sayed Massoud, Ehab ; Ali, Elimam ; Assilzadeh, Hamid ; Escorcia-Gutierrez, José</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c325t-9180787b2beb8ddbf79dc97aec634619015692f9ab831932daf414cc48b766663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Antibacterial activity</topic><topic>Antibacterial efficacy</topic><topic>antibacterial properties</topic><topic>antioxidant activity</topic><topic>Antioxidant potential</topic><topic>antioxidants</topic><topic>atomic force microscopy</topic><topic>Catalytic dye degradation</topic><topic>Congo red</topic><topic>Convolutional neural network (CNN)</topic><topic>crystallites</topic><topic>environmental impact</topic><topic>Escherichia coli</topic><topic>health services</topic><topic>Klebsiella</topic><topic>leaf extracts</topic><topic>nanoparticles</topic><topic>neural networks</topic><topic>Pseudomonas</topic><topic>remediation</topic><topic>Sida acuta</topic><topic>Staphylococcus aureus</topic><topic>surface area</topic><topic>surface roughness</topic><topic>ultraviolet-visible spectroscopy</topic><topic>X-radiation</topic><topic>zeta potential</topic><topic>zinc oxide</topic><topic>Zinc oxide NPs synthesis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Du, Jiang</creatorcontrib><creatorcontrib>AL-Huqail, Arwa</creatorcontrib><creatorcontrib>Cao, Yan</creatorcontrib><creatorcontrib>Yao, Hui</creatorcontrib><creatorcontrib>Sun, Yiding</creatorcontrib><creatorcontrib>Garaleh, Mazen</creatorcontrib><creatorcontrib>El Sayed Massoud, Ehab</creatorcontrib><creatorcontrib>Ali, Elimam</creatorcontrib><creatorcontrib>Assilzadeh, Hamid</creatorcontrib><creatorcontrib>Escorcia-Gutierrez, José</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Environmental research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Du, Jiang</au><au>AL-Huqail, Arwa</au><au>Cao, Yan</au><au>Yao, Hui</au><au>Sun, Yiding</au><au>Garaleh, Mazen</au><au>El Sayed Massoud, Ehab</au><au>Ali, Elimam</au><au>Assilzadeh, Hamid</au><au>Escorcia-Gutierrez, José</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Green synthesis of zinc oxide nanoparticles from Sida acuta leaf extract for antibacterial and antioxidant applications, and catalytic degradation of dye through the use of convolutional neural network</atitle><jtitle>Environmental research</jtitle><addtitle>Environ Res</addtitle><date>2024-10-01</date><risdate>2024</risdate><volume>258</volume><spage>119204</spage><pages>119204-</pages><artnum>119204</artnum><issn>0013-9351</issn><issn>1096-0953</issn><eissn>1096-0953</eissn><abstract>This study synthesized zinc oxide nanoparticles (ZnO NPs) using a novel green approach, with Sida acuta leaf extract as a capping and reducing agent to initiate nucleation and structure formation. The innovation of this study lies in demonstrating the originality of utilizing zinc oxide nanoparticles for antibacterial action, antioxidant potential, and catalytic degradation of Congo red dye. This unique approach harnesses eco-friendly methods to initiate nucleation and structure formation. The synthesized nanoparticles' structure and conformation were characterized using UV–vis (λmax = 280 nm), X-ray, atomic force microscopy, SEM, HR-TEM and FTIR. The antibacterial activity of the Nps was tested against Pseudomonas sp, Klebsiella sp, Staphylococcus aureus, and E. coli, demonstrating efficacy. The nanoparticles exhibited unique properties, with a crystallite size of 20 nm (XRD), a surface roughness of 2.5 nm (AFM), and a specific surface area of 60 m2/g (SEM). A Convolutional Neural Network (CNN) was effectively employed to accurately classify and analyze microscopic images of green-synthesized zinc oxide nanoparticles. This research revealed their exceptional antioxidant potential, with an average DPPH scavenging rate of 80% at a concentration of 0.05 mg/mL. Additionally, zeta potential measurements indicated a stable net negative surface charge of approximately −12.2 mV. These quantitative findings highlight the promising applications of green-synthesized ZnO NPs in healthcare, materials science, and environmental remediation. The ZnO nanoparticles exhibited catalytic capabilities for dye degradation, and the degradation rate was determined using UV spectroscopy. Key findings of the study encompass the green synthesis of versatile zinc oxide nanoparticles, demonstrating potent antibacterial action, antioxidant capabilities, and catalytic dye degradation potential. These nanoparticles offer multifaceted solutions with minimal environmental impact, addressing challenges in various fields, from healthcare to environmental remediation. [Display omitted] •Eco-friendly production of ZnO NPs using Sida acuta leaf extract demonstrates a green synthesis approach.•ZnO NPs exhibit efficacy against major pathogens like Pseudomonas, Klebsiella, S. aureus, and E. coli.•Enhanced antioxidant capability: The presence of flavonoids in ZnO NPs aids in combating oxidative stress effectively.•Potent catalytic degradation: ZnO NPs showcase efficient degradation of Congo red dye, as proven by UV spectroscopy.•CNN application: Successful classification and analysis of synthesized ZnO NPs using a Convolutional Neural Network.</abstract><cop>Netherlands</cop><pub>Elsevier Inc</pub><pmid>38802033</pmid><doi>10.1016/j.envres.2024.119204</doi></addata></record>
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source Elsevier ScienceDirect Journals
subjects Antibacterial activity
Antibacterial efficacy
antibacterial properties
antioxidant activity
Antioxidant potential
antioxidants
atomic force microscopy
Catalytic dye degradation
Congo red
Convolutional neural network (CNN)
crystallites
environmental impact
Escherichia coli
health services
Klebsiella
leaf extracts
nanoparticles
neural networks
Pseudomonas
remediation
Sida acuta
Staphylococcus aureus
surface area
surface roughness
ultraviolet-visible spectroscopy
X-radiation
zeta potential
zinc oxide
Zinc oxide NPs synthesis
title Green synthesis of zinc oxide nanoparticles from Sida acuta leaf extract for antibacterial and antioxidant applications, and catalytic degradation of dye through the use of convolutional neural network
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