Intelligent optimization of process conditions for maximum metal recovery from spent zinc-manganese batteries
By 2025, 2 million metric tons of batteries must be recycled. Among these batteries, the spent Zinc-Manganese batteries poses a serious threat to environment due to toxic heavy metals. This metals are toxic but at same time vital for various industrial applications. This metals are generally recover...
Saved in:
Published in | IOP conference series. Earth and environmental science Vol. 463; no. 1; pp. 12160 - 12165 |
---|---|
Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Bristol
IOP Publishing
01.03.2020
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | By 2025, 2 million metric tons of batteries must be recycled. Among these batteries, the spent Zinc-Manganese batteries poses a serious threat to environment due to toxic heavy metals. This metals are toxic but at same time vital for various industrial applications. This metals are generally recovered by physical-chemical process which are highly energy intensive and polluting. An eco-friendly recycling process has to be explored to tackle such issue. The bioleaching is one such eco-friendly recycling method. The objective of this work is to optimize the process parameters of bioleaching method, so as to make this process commercially viable. The optimization of this process is done through statistical based automated neural network intelligent optimization approach. The formulated models were inline with the complex behaviour of bioleaching process. The training and validation performance of the models were near to 1. The parametric, global sensitivity and interaction analysis was undertaken for understanding the relationship between different parameters and its affect on the metal yield. The optimum values of process parameters were determined for maximizing the metal yield. |
---|---|
AbstractList | By 2025, 2 million metric tons of batteries must be recycled. Among these batteries, the spent Zinc-Manganese batteries poses a serious threat to environment due to toxic heavy metals. This metals are toxic but at same time vital for various industrial applications. This metals are generally recovered by physical-chemical process which are highly energy intensive and polluting. An eco-friendly recycling process has to be explored to tackle such issue. The bioleaching is one such eco-friendly recycling method. The objective of this work is to optimize the process parameters of bioleaching method, so as to make this process commercially viable. The optimization of this process is done through statistical based automated neural network intelligent optimization approach. The formulated models were inline with the complex behaviour of bioleaching process. The training and validation performance of the models were near to 1. The parametric, global sensitivity and interaction analysis was undertaken for understanding the relationship between different parameters and its affect on the metal yield. The optimum values of process parameters were determined for maximizing the metal yield. Abstract By 2025, 2 million metric tons of batteries must be recycled. Among these batteries, the spent Zinc-Manganese batteries poses a serious threat to environment due to toxic heavy metals. This metals are toxic but at same time vital for various industrial applications. This metals are generally recovered by physical-chemical process which are highly energy intensive and polluting. An eco-friendly recycling process has to be explored to tackle such issue. The bioleaching is one such eco-friendly recycling method. The objective of this work is to optimize the process parameters of bioleaching method, so as to make this process commercially viable. The optimization of this process is done through statistical based automated neural network intelligent optimization approach. The formulated models were inline with the complex behaviour of bioleaching process. The training and validation performance of the models were near to 1. The parametric, global sensitivity and interaction analysis was undertaken for understanding the relationship between different parameters and its affect on the metal yield. The optimum values of process parameters were determined for maximizing the metal yield. |
Author | Ruhatiya, C Gao, Liang Sleesongsom, Suwin Tibrewala, Himanshu Chin, C M M |
Author_xml | – sequence: 1 givenname: C surname: Ruhatiya fullname: Ruhatiya, C organization: School of Engineering Sciences, Mahindra École Centrale , India – sequence: 2 givenname: Himanshu surname: Tibrewala fullname: Tibrewala, Himanshu organization: School of Engineering Sciences, Mahindra École Centrale , India – sequence: 3 givenname: Liang surname: Gao fullname: Gao, Liang email: gaoliang@mail.hust.edu.cn organization: State Key Lab of Digital Manufacturing Equipment & Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology , China – sequence: 4 givenname: Suwin surname: Sleesongsom fullname: Sleesongsom, Suwin organization: Department of Aeronautical Engineering, International Academy of Aviation Industry, King Mongkut's Institute of Technology Ladkrabang , Thailand – sequence: 5 givenname: C M M surname: Chin fullname: Chin, C M M organization: Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham Malaysia Campus |
BookMark | eNqFkF1LwzAUhoNMcJv-BQl4XZvTtE17KcOPgeCNXoe0Ox0ZTVKTTNx-vS2TeenV-Xzfw3kWZGadRUJugd0Dq6oURFEkwKFI85KnkDLIoGQXZH4ezM45E1dkEcKOsVLkvJ4Ts7YR-15v0UbqhqiNPqqonaWuo4N3LYZAW2c3emoG2jlPjfrWZm-owah66rF1X-gPtPPO0DBMRkdt28Qou1UWA9JGxYheY7gml53qA978xiX5eHp8X70kr2_P69XDa9LmmYhJXtVVgzAVWDVl06iu4SqrFdZNzZSAjVIMRJY1vAJRQbepuRBl2YHgyFvkS3J38h0_-NxjiHLn9t6OJ2VWFAUvoYZ63CpPW613IXjs5OC1Uf4ggckJrZyoyYmgHNFKkCe0ozA7CbUb_pz_Ef0APat_IA |
CitedBy_id | crossref_primary_10_3390_pr10051034 |
Cites_doi | 10.1016/j.biortech.2011.12.013 10.1016/j.wasman.2010.05.010 10.1016/j.jhazmat.2011.10.063 10.1016/j.jpowsour.2003.12.026 10.1115/1.4045194 10.1016/j.wasman.2012.10.007 10.1002/est2.130 10.1016/j.hydromet.2008.10.001 10.1016/j.hydromet.2011.02.010 10.1016/j.wasman.2007.01.010 10.1002/jctb.4611 10.1016/j.hydromet.2009.02.008 10.1016/j.jpowsour.2007.11.074 10.1016/j.hydromet.2011.09.010 |
ContentType | Journal Article |
Copyright | Published under licence by IOP Publishing Ltd 2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
Copyright_xml | – notice: Published under licence by IOP Publishing Ltd – notice: 2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
DBID | O3W TSCCA AAYXX CITATION ABUWG AFKRA ATCPS AZQEC BENPR BHPHI CCPQU DWQXO GNUQQ HCIFZ PATMY PIMPY PQEST PQQKQ PQUKI PRINS PYCSY |
DOI | 10.1088/1755-1315/463/1/012160 |
DatabaseName | Open Access: IOP Publishing Free Content IOPscience (Open Access) CrossRef ProQuest Central (Alumni) ProQuest Central ProQuest Agriculture & Environmental Science Database ProQuest Central Essentials AUTh Library subscriptions: ProQuest Central ProQuest Natural Science Collection ProQuest One Community College ProQuest Central Korea ProQuest Central Student SciTech Premium Collection (Proquest) (PQ_SDU_P3) Environmental Science Database Publicly Available Content (ProQuest) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China Environmental Science Collection |
DatabaseTitle | CrossRef Publicly Available Content Database ProQuest Central Student ProQuest Central Essentials ProQuest One Academic Eastern Edition ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Central China ProQuest Central Environmental Science Collection ProQuest One Academic UKI Edition Natural Science Collection ProQuest Central Korea Agricultural & Environmental Science Collection Environmental Science Database ProQuest One Academic |
DatabaseTitleList | Publicly Available Content Database CrossRef |
Database_xml | – sequence: 1 dbid: O3W name: Open Access: IOP Publishing Free Content url: http://iopscience.iop.org/ sourceTypes: Publisher – sequence: 2 dbid: BENPR name: AUTh Library subscriptions: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Geology |
DocumentTitleAlternate | Intelligent optimization of process conditions for maximum metal recovery from spent zinc-manganese batteries |
EISSN | 1755-1315 |
ExternalDocumentID | 10_1088_1755_1315_463_1_012160 EES_463_1_012160 |
GroupedDBID | 1JI 2WC 4.4 5B3 5GY 5VS AAFWJ AAJIO AAJKP ABHWH ACAFW ACHIP AEFHF AEJGL AFKRA AFYNE AHSEE AIYBF AKPSB ALMA_UNASSIGNED_HOLDINGS ASPBG ATCPS ATQHT AVWKF AZFZN BENPR BHPHI CCPQU CEBXE CJUJL CRLBU CS3 DU5 EDWGO EQZZN HCIFZ IJHAN IOP IZVLO KNG KQ8 N5L O3W OK1 PATMY PIMPY PJBAE PYCSY RIN SY9 T37 TR2 TSCCA W28 AAYXX CITATION ABUWG AZQEC DWQXO GNUQQ PQEST PQQKQ PQUKI PRINS |
ID | FETCH-LOGICAL-c427t-4898be1c427e8b6bbafb3a29ae9b90a71daa01722b381781fd937766f173e3ce3 |
IEDL.DBID | O3W |
ISSN | 1755-1307 |
IngestDate | Fri Sep 13 07:43:53 EDT 2024 Fri Aug 23 01:30:48 EDT 2024 Wed Aug 21 03:34:59 EDT 2024 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 1 |
Language | English |
License | Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c427t-4898be1c427e8b6bbafb3a29ae9b90a71daa01722b381781fd937766f173e3ce3 |
OpenAccessLink | https://iopscience.iop.org/article/10.1088/1755-1315/463/1/012160 |
PQID | 2555361919 |
PQPubID | 4998669 |
PageCount | 6 |
ParticipantIDs | proquest_journals_2555361919 crossref_primary_10_1088_1755_1315_463_1_012160 iop_journals_10_1088_1755_1315_463_1_012160 |
PublicationCentury | 2000 |
PublicationDate | 20200301 |
PublicationDateYYYYMMDD | 2020-03-01 |
PublicationDate_xml | – month: 03 year: 2020 text: 20200301 day: 01 |
PublicationDecade | 2020 |
PublicationPlace | Bristol |
PublicationPlace_xml | – name: Bristol |
PublicationTitle | IOP conference series. Earth and environmental science |
PublicationTitleAlternate | IOP Conf. Ser.: Earth Environ. Sci |
PublicationYear | 2020 |
Publisher | IOP Publishing |
Publisher_xml | – name: IOP Publishing |
References | EES_463_1_012160bib4 Huang (EES_463_1_012160bib12) 2010; 30 Li (EES_463_1_012160bib6) 2019; 330 Bernardes (EES_463_1_012160bib2) 2004; 130 Garg (EES_463_1_012160bib11) 2020; 17 Kim (EES_463_1_012160bib13) 2009; 96 Zeng (EES_463_1_012160bib15) 2012; 199 Yun (EES_463_1_012160bib7) 2019; 268 Velgosová (EES_463_1_012160bib17) 2013; 33 Sayilgan (EES_463_1_012160bib9) 2009; 97 Xu (EES_463_1_012160bib1) 2008; 177 Gaines (EES_463_1_012160bib5) 2014; 1 Oldershausen (EES_463_1_012160bib8) 1999 Haghshenas (EES_463_1_012160bib20) 2012; 111 Mishra (EES_463_1_012160bib19) 2008; 28 Chung (EES_463_1_012160bib3) 2016 Chen (EES_463_1_012160bib14) 2011; 108 Xin (EES_463_1_012160bib16) 2012; 106 Ruhatiya (EES_463_1_012160bib10) 2020 Niu (EES_463_1_012160bib18) 2016; 91 |
References_xml | – volume: 330 year: 2019 ident: EES_463_1_012160bib6 publication-title: Electro Acta contributor: fullname: Li – volume: 106 start-page: 147 year: 2012 ident: EES_463_1_012160bib16 publication-title: Bioresource Technology doi: 10.1016/j.biortech.2011.12.013 contributor: fullname: Xin – volume: 1 start-page: 2 year: 2014 ident: EES_463_1_012160bib5 publication-title: Sus Mater and Technol. contributor: fullname: Gaines – year: 2016 ident: EES_463_1_012160bib3 contributor: fullname: Chung – volume: 30 start-page: 2292 year: 2010 ident: EES_463_1_012160bib12 publication-title: Waste management doi: 10.1016/j.wasman.2010.05.010 contributor: fullname: Huang – year: 1999 ident: EES_463_1_012160bib8 contributor: fullname: Oldershausen – ident: EES_463_1_012160bib4 – volume: 199 start-page: 164 year: 2012 ident: EES_463_1_012160bib15 publication-title: Journal of Hazardous Materials doi: 10.1016/j.jhazmat.2011.10.063 contributor: fullname: Zeng – volume: 130 start-page: 291 year: 2004 ident: EES_463_1_012160bib2 publication-title: J Pow Sour. doi: 10.1016/j.jpowsour.2003.12.026 contributor: fullname: Bernardes – volume: 17 year: 2020 ident: EES_463_1_012160bib11 publication-title: Journal of Electrochemical Energy Conversion and Storage doi: 10.1115/1.4045194 contributor: fullname: Garg – volume: 268 year: 2019 ident: EES_463_1_012160bib7 publication-title: IOP Conference Series: EES contributor: fullname: Yun – volume: 33 start-page: 456 year: 2013 ident: EES_463_1_012160bib17 publication-title: Waste management doi: 10.1016/j.wasman.2012.10.007 contributor: fullname: Velgosová – year: 2020 ident: EES_463_1_012160bib10 doi: 10.1002/est2.130 contributor: fullname: Ruhatiya – volume: 96 start-page: 154 year: 2009 ident: EES_463_1_012160bib13 publication-title: Hydrometallurgy doi: 10.1016/j.hydromet.2008.10.001 contributor: fullname: Kim – volume: 108 start-page: 80 year: 2011 ident: EES_463_1_012160bib14 publication-title: Hydrometallurgy doi: 10.1016/j.hydromet.2011.02.010 contributor: fullname: Chen – volume: 28 start-page: 333 year: 2008 ident: EES_463_1_012160bib19 publication-title: Waste management doi: 10.1016/j.wasman.2007.01.010 contributor: fullname: Mishra – volume: 91 start-page: 608 year: 2016 ident: EES_463_1_012160bib18 publication-title: Journal of chemical technology and biotechnology doi: 10.1002/jctb.4611 contributor: fullname: Niu – volume: 97 start-page: 158 year: 2009 ident: EES_463_1_012160bib9 publication-title: Hydrometallurgy doi: 10.1016/j.hydromet.2009.02.008 contributor: fullname: Sayilgan – volume: 177 start-page: 512 year: 2008 ident: EES_463_1_012160bib1 publication-title: J Pow Sour. doi: 10.1016/j.jpowsour.2007.11.074 contributor: fullname: Xu – volume: 111 start-page: 22 year: 2012 ident: EES_463_1_012160bib20 publication-title: Hydrometallurgy doi: 10.1016/j.hydromet.2011.09.010 contributor: fullname: Haghshenas |
SSID | ssj0067439 |
Score | 2.1707137 |
Snippet | By 2025, 2 million metric tons of batteries must be recycled. Among these batteries, the spent Zinc-Manganese batteries poses a serious threat to environment... Abstract By 2025, 2 million metric tons of batteries must be recycled. Among these batteries, the spent Zinc-Manganese batteries poses a serious threat to... |
SourceID | proquest crossref iop |
SourceType | Aggregation Database Publisher |
StartPage | 12160 |
SubjectTerms | Bacterial leaching Batteries bioleaching process Heavy metals Industrial applications Intelligent Optimization methods Leaching Manganese Mathematical models Metals Neural networks Optimization Parameter sensitivity Process parameters Recycling Recycling methods Statistical analysis Zinc |
SummonAdditionalLinks | – databaseName: AUTh Library subscriptions: ProQuest Central dbid: BENPR link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwhV3JSgQxEA2OIngRV1xGycGbhDad3nISlRlHwUFEwVuTdBKZQy9qC45fb1UvzkHQY6-HSvqlXqfeK0JOZOIsDLVjgHwGCIpxTFphmS8dVxwQU0SoRr6bRpOn4PY5fF4ik14Lg2WVPSY2QG3KDP-Re5D6hgKyfS49pfEvQFZ759Urw_5RuM_aNdMYkBWfB7hhu3I5mt4_9KiMtfayEUeGIQPcjnu1MBDA7hwPvSASHvfQ5qyxrFwsVINZWf1C62YJGm-Q9S53pBftYG-SJVtskdXrpjfvfJvkNz_2mjUtAQryTmNJS0erVhBAgf6atkqLQrpKc_U5yz9ymltIwimyY5jac4qiE_pe4Yu-ZkXGclW8KOxVSXXjxwn0eoc8jUePVxPWdVNgWeDHNQsSmWjL8cAmOtJaOS2Uj-bcWp6pmBulkBD6Gk37Eu4MZC5xFDkeCysyK3bJclEWdo9QyQ3aqIpYWxlkSSgDpzMtTSBtKKzJ9onXhy6tWtOMtNnsTpIUg51isFMIdsrTNtj75BQinHbfz_u_dw_7kVg8spggB39fPiRrPpLmppBsSJbrtw97BJlFrY-7SfMN26TKCA priority: 102 providerName: ProQuest |
Title | Intelligent optimization of process conditions for maximum metal recovery from spent zinc-manganese batteries |
URI | https://iopscience.iop.org/article/10.1088/1755-1315/463/1/012160 https://www.proquest.com/docview/2555361919/abstract/ |
Volume | 463 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1dS8MwFA26IfgifuJ0jjz4JrVL04_kUWVzE9yGOPStJG0ie2g73AbOX-9N2ioiIr610IRykt57D73nBKFzzrSCpdYORL4UCEqqHa6ocjyuiSAQMWlo1Mj3o3Aw9e-eg7qb0GphinkV-i_hsjQKLiGsGuKYCwkvcAglgeuH1CWucSULgbU3Ifd6pqtvTJ_qYGxa7LnVRNox3agWCf86z7f8tAnv8CNI28zT30U7VcmIr8oX3EMbKt9HW7f2SN71AcqGn66aS1xABMgqaSUuNJ6XOgAMrDctm7MwVKk4E2-zbJXhTEHtjQ0phh29xkZrghdzM9H7LE-cTOQvwhxRiaW14QRWfYim_d7jzcCpDlFwEt-Llo7POJOKmBvFZCil0JIKz3hyS94VEUmFMDzQk8arjxGdQsEShaEmEVU0UfQINfIiV8cIc5Ia91QaScX9hAXc1zKRPPW5CqhKkxZya-jieemVEdt_3IzFBuzYgB0D2DGJS7Bb6AIQjqvPZvHn0-16Jb6GACUKKLBAwk_-Ndkp2vYMdbbtZG3UWL6u1BnUF0vZQc3r3mjy0EGbw_GkY_fTB_MLx0M |
link.rule.ids | 315,786,790,21416,27957,27958,33779,38900,38925,43840,53877,53903 |
linkProvider | IOP Publishing |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwhV1LT9wwELZgUdVeEFBQt9DiAzdkBcd5-YSggi6vFUIgcbPs2EZ7yKPdRSr99cwkTveARI95HsbO5--LZ74h5EAW3sFQewbIZ0GgWM-kE47F0nPNATFFhtXIN9Ns8pBcPqaP4YfbPKRVDpjYAbVtSvxHHgH1TQWwfS6P218Mu0bh7mpoobFK1hIBUmVE1k7Pprd3AxZjhr3sSiLTlAFa50ONMMi-cI6nUZKJiEdobtYZVS6Xp9VZ077B6G7hOd8g64Ex0pN-iDfJiqu3yIefXUfel8-kuvhnqrmgDQBAFSoraeNp25cBUBC9ts_NokBSaaX_zKrnilYOqDdFTQwT-oViqQmdt_iiv7O6ZJWunzR2qKSmc-EEUb1NHs7P7n9MWOihwMokzhcsKWRhHMcDV5jMGO2N0DFacht5pHNutUYZGBu06iu4t8BX8izzPBdOlE7skFHd1O4LoZJbNE8VuXEyKYtUJt6URtpEulQ4W45JNIROtb1Vhuq2uItCYbAVBltBsBVXfbDH5BAirMJXM__v3XvDSCwfWU6Lr-9f3icfJ_c31-r6Ynq1Sz7FKJu7VLI9Mlr8fnbfgFsszPcwgV4BayHJOw |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1NT9wwELWAqhUXaKEV0KX1oTeUzTrOh32sCgvbUuAAEjfLjm2EqmQjNivB_vrOOFlQW6Gq6i2R4lEyzoznyfOeCfkkhXcw1T6CzGcBoFgfScddlEjPNIOMyXNkI38_y0-u0q_X2fUKOXrkwkybPvUP4bITCu5c2DfEiRgWvCxinGVxmvOYxahKlo_ixvpV8gLit0AMNjm_WCZkbLOXgRcZxo2KJVH4WVu_rFGr8B5_JOqw-ow3uy6RWRAtxKaTH8N5a4bl4jdJx__-sNdko69P6edu0Buy4uot8vI4nP_7sE2qyaOEZ0unkG6qnsdJp542HemAAsS2XScYhZKYVvr-tppXtHJQ6FNE4BA-DxSJLXTWoKHFbV1Gla5vNJ6HSU3Q_AQI_5ZcjY8uv5xE_YkNUZkmRRulQgrjGN44YXJjtDdcJygAbuRIF8xqjaAzMSgMKJi3UB0Vee5ZwR0vHX9H1upp7XYIlcyiVCsvjJNpKTKZelMaaVPpMu5suUvi5RypphPmUGFDXQiFjlToSAWOVEx1jtwlB-B51cfo7K9PD5ZT_jQE8FfGAXIyufdPxj6SVxeHY3U6Ofv2nqwnCNlDG9uArLV3c7cPdU1rPoS_9iciqOnU |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Intelligent+optimization+of+process+conditions+for+maximum+metal+recovery+from+spent+zinc-manganese+batteries&rft.jtitle=IOP+conference+series.+Earth+and+environmental+science&rft.au=Ruhatiya%2C+C&rft.au=Tibrewala%2C+Himanshu&rft.au=Gao%2C+Liang&rft.au=Sleesongsom%2C+Suwin&rft.date=2020-03-01&rft.pub=IOP+Publishing&rft.issn=1755-1307&rft.eissn=1755-1315&rft.volume=463&rft.issue=1&rft_id=info:doi/10.1088%2F1755-1315%2F463%2F1%2F012160&rft.externalDocID=EES_463_1_012160 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1755-1307&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1755-1307&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1755-1307&client=summon |