In situ measurement and simulation of nano-magnetite mobility in porous media subject to transient salinity
Nanotechnologies have been proposed for a variety of environmental applications, including subsurface characterization, enhanced oil recovery, and in situ contaminant remediation. For such applications, quantitative predictive models will be of great utility for system design and implementation. Ele...
Saved in:
Published in | Nanoscale Vol. 7; no. 3; pp. 1047 - 1057 |
---|---|
Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
England
21.01.2015
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Nanotechnologies have been proposed for a variety of environmental applications, including subsurface characterization, enhanced oil recovery, and
in situ
contaminant remediation. For such applications, quantitative predictive models will be of great utility for system design and implementation. Electrolyte chemistry, which can vary substantially within subsurface pore waters, has been shown to strongly influence nanoparticle aggregation and deposition in porous media. Thus, it is essential that mathematical models be capable of tracking changes in electrolyte chemistry and predicting its influence on nanoparticle mobility. In this work, a modified version of a multi-dimensional multispecies transport simulator (SEAWAT) was employed to model nanoparticle transport under transient electrolyte conditions. The modeling effort was supported by experimental measurements of paramagnetic magnetite (Fe
3
O
4
) nanoparticle, coated with polyacrylamide-methylpropane sulfonic acid – lauryl acrylate (nMag-PAMPS), mobility in columns packed with 40–50 mesh Ottawa sand. Column effluent analyses and magnetic resonance imaging (MRI) were used to quantify nanoparticle breakthrough and
in situ
aqueous phase concentrations, respectively. Experimental observations revealed that introduction of de-ionized water into the brine saturated column (80 g L
−1
NaCl + 20 g L
−1
CaCl
2
) promoted release and remobilization of deposited nanoparticles along a diagonal front, coincident with the variable density flow field. This behavior was accurately captured by the simulation results, which indicated that a two-site deposition-release model provided the best fit to experimental observations, suggesting that heterogeneous nanoparticle–surface interactions governed nanoparticle attachment. These findings illustrate the importance of accounting for both physical and chemical processes associated with changes in electrolyte chemistry when predicting nanoparticle transport behavior in subsurface formations. |
---|---|
AbstractList | Nanotechnologies have been proposed for a variety of environmental applications, including subsurface characterization, enhanced oil recovery, and
in situ
contaminant remediation. For such applications, quantitative predictive models will be of great utility for system design and implementation. Electrolyte chemistry, which can vary substantially within subsurface pore waters, has been shown to strongly influence nanoparticle aggregation and deposition in porous media. Thus, it is essential that mathematical models be capable of tracking changes in electrolyte chemistry and predicting its influence on nanoparticle mobility. In this work, a modified version of a multi-dimensional multispecies transport simulator (SEAWAT) was employed to model nanoparticle transport under transient electrolyte conditions. The modeling effort was supported by experimental measurements of paramagnetic magnetite (Fe
3
O
4
) nanoparticle, coated with polyacrylamide-methylpropane sulfonic acid – lauryl acrylate (nMag-PAMPS), mobility in columns packed with 40–50 mesh Ottawa sand. Column effluent analyses and magnetic resonance imaging (MRI) were used to quantify nanoparticle breakthrough and
in situ
aqueous phase concentrations, respectively. Experimental observations revealed that introduction of de-ionized water into the brine saturated column (80 g L
−1
NaCl + 20 g L
−1
CaCl
2
) promoted release and remobilization of deposited nanoparticles along a diagonal front, coincident with the variable density flow field. This behavior was accurately captured by the simulation results, which indicated that a two-site deposition-release model provided the best fit to experimental observations, suggesting that heterogeneous nanoparticle–surface interactions governed nanoparticle attachment. These findings illustrate the importance of accounting for both physical and chemical processes associated with changes in electrolyte chemistry when predicting nanoparticle transport behavior in subsurface formations. Nanotechnologies have been proposed for a variety of environmental applications, including subsurface characterization, enhanced oil recovery, and in situ contaminant remediation. For such applications, quantitative predictive models will be of great utility for system design and implementation. Electrolyte chemistry, which can vary substantially within subsurface pore waters, has been shown to strongly influence nanoparticle aggregation and deposition in porous media. Thus, it is essential that mathematical models be capable of tracking changes in electrolyte chemistry and predicting its influence on nanoparticle mobility. In this work, a modified version of a multi-dimensional multispecies transport simulator (SEAWAT) was employed to model nanoparticle transport under transient electrolyte conditions. The modeling effort was supported by experimental measurements of paramagnetic magnetite (Fe3O4) nanoparticle, coated with polyacrylamide-methylpropane sulfonic acid - lauryl acrylate (nMag-PAMPS), mobility in columns packed with 40-50 mesh Ottawa sand. Column effluent analyses and magnetic resonance imaging (MRI) were used to quantify nanoparticle breakthrough and in situ aqueous phase concentrations, respectively. Experimental observations revealed that introduction of de-ionized water into the brine saturated column (80 g L(-1) NaCl + 20 g L(-1) CaCl2) promoted release and remobilization of deposited nanoparticles along a diagonal front, coincident with the variable density flow field. This behavior was accurately captured by the simulation results, which indicated that a two-site deposition-release model provided the best fit to experimental observations, suggesting that heterogeneous nanoparticle-surface interactions governed nanoparticle attachment. These findings illustrate the importance of accounting for both physical and chemical processes associated with changes in electrolyte chemistry when predicting nanoparticle transport behavior in subsurface formations. Nanotechnologies have been proposed for a variety of environmental applications, including subsurface characterization, enhanced oil recovery, and in situ contaminant remediation. For such applications, quantitative predictive models will be of great utility for system design and implementation. Electrolyte chemistry, which can vary substantially within subsurface pore waters, has been shown to strongly influence nanoparticle aggregation and deposition in porous media. Thus, it is essential that mathematical models be capable of tracking changes in electrolyte chemistry and predicting its influence on nanoparticle mobility. In this work, a modified version of a multi-dimensional multispecies transport simulator (SEAWAT) was employed to model nanoparticle transport under transient electrolyte conditions. The modeling effort was supported by experimental measurements of paramagnetic magnetite (Fe sub(3)O sub(4)) nanoparticle, coated with polyacrylamide-methylpropane sulfonic acid - lauryl acrylate (nMag-PAMPS), mobility in columns packed with 40-50 mesh Ottawa sand. Column effluent analyses and magnetic resonance imaging (MRI) were used to quantify nanoparticle breakthrough and in situ aqueous phase concentrations, respectively. Experimental observations revealed that introduction of de-ionized water into the brine saturated column (80 g L super(-1) NaCl + 20 g L super(-1) CaCl sub(2)) promoted release and remobilization of deposited nanoparticles along a diagonal front, coincident with the variable density flow field. This behavior was accurately captured by the simulation results, which indicated that a two-site deposition-release model provided the best fit to experimental observations, suggesting that heterogeneous nanoparticle-surface interactions governed nanoparticle attachment. These findings illustrate the importance of accounting for both physical and chemical processes associated with changes in electrolyte chemistry when predicting nanoparticle transport behavior in subsurface formations. Nanotechnologies have been proposed for a variety of environmental applications, including subsurface characterization, enhanced oil recovery, and in situ contaminant remediation. For such applications, quantitative predictive models will be of great utility for system design and implementation. Electrolyte chemistry, which can vary substantially within subsurface pore waters, has been shown to strongly influence nanoparticle aggregation and deposition in porous media. Thus, it is essential that mathematical models be capable of tracking changes in electrolyte chemistry and predicting its influence on nanoparticle mobility. In this work, a modified version of a multi-dimensional multispecies transport simulator (SEAWAT) was employed to model nanoparticle transport under transient electrolyte conditions. The modeling effort was supported by experimental measurements of paramagnetic magnetite (Fe3O4) nanoparticle, coated with polyacrylamide-methylpropane sulfonic acid - lauryl acrylate (nMag-PAMPS), mobility in columns packed with 40-50 mesh Ottawa sand. Column effluent analyses and magnetic resonance imaging (MRI) were used to quantify nanoparticle breakthrough and in situ aqueous phase concentrations, respectively. Experimental observations revealed that introduction of de-ionized water into the brine saturated column (80 g L(-1) NaCl + 20 g L(-1) CaCl2) promoted release and remobilization of deposited nanoparticles along a diagonal front, coincident with the variable density flow field. This behavior was accurately captured by the simulation results, which indicated that a two-site deposition-release model provided the best fit to experimental observations, suggesting that heterogeneous nanoparticle-surface interactions governed nanoparticle attachment. These findings illustrate the importance of accounting for both physical and chemical processes associated with changes in electrolyte chemistry when predicting nanoparticle transport behavior in subsurface formations.Nanotechnologies have been proposed for a variety of environmental applications, including subsurface characterization, enhanced oil recovery, and in situ contaminant remediation. For such applications, quantitative predictive models will be of great utility for system design and implementation. Electrolyte chemistry, which can vary substantially within subsurface pore waters, has been shown to strongly influence nanoparticle aggregation and deposition in porous media. Thus, it is essential that mathematical models be capable of tracking changes in electrolyte chemistry and predicting its influence on nanoparticle mobility. In this work, a modified version of a multi-dimensional multispecies transport simulator (SEAWAT) was employed to model nanoparticle transport under transient electrolyte conditions. The modeling effort was supported by experimental measurements of paramagnetic magnetite (Fe3O4) nanoparticle, coated with polyacrylamide-methylpropane sulfonic acid - lauryl acrylate (nMag-PAMPS), mobility in columns packed with 40-50 mesh Ottawa sand. Column effluent analyses and magnetic resonance imaging (MRI) were used to quantify nanoparticle breakthrough and in situ aqueous phase concentrations, respectively. Experimental observations revealed that introduction of de-ionized water into the brine saturated column (80 g L(-1) NaCl + 20 g L(-1) CaCl2) promoted release and remobilization of deposited nanoparticles along a diagonal front, coincident with the variable density flow field. This behavior was accurately captured by the simulation results, which indicated that a two-site deposition-release model provided the best fit to experimental observations, suggesting that heterogeneous nanoparticle-surface interactions governed nanoparticle attachment. These findings illustrate the importance of accounting for both physical and chemical processes associated with changes in electrolyte chemistry when predicting nanoparticle transport behavior in subsurface formations. |
Author | Wang, Yonggang Pennell, Kurt D. Song, Yi-Qiao Becker, Matthew D. Abriola, Linda M. L. Paulsen, Jeffrey |
Author_xml | – sequence: 1 givenname: Matthew D. surname: Becker fullname: Becker, Matthew D. organization: Department of Civil and Environmental Engineering, Tufts University, Medford, USA – sequence: 2 givenname: Yonggang surname: Wang fullname: Wang, Yonggang organization: Department of Civil and Environmental Engineering, Tufts University, Medford, USA – sequence: 3 givenname: Jeffrey surname: L. Paulsen fullname: L. Paulsen, Jeffrey organization: Schlumberger-Doll Research Center, Cambridge, USA – sequence: 4 givenname: Yi-Qiao surname: Song fullname: Song, Yi-Qiao organization: Schlumberger-Doll Research Center, Cambridge, USA – sequence: 5 givenname: Linda M. surname: Abriola fullname: Abriola, Linda M. organization: Department of Civil and Environmental Engineering, Tufts University, Medford, USA – sequence: 6 givenname: Kurt D. surname: Pennell fullname: Pennell, Kurt D. organization: Department of Civil and Environmental Engineering, Tufts University, Medford, USA |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25474703$$D View this record in MEDLINE/PubMed |
BookMark | eNqNkU1LxDAQhoOsuB968QdIjiJUkyZNm6MsfiwsCqLnkrRTydoma5Me_Pdm3V0F8eBphuF5X2bemaKRdRYQOqXkkhImr-b84YlkpChuD9AkJZwkjOXp6LsXfIym3q8IEZIJdoTGacZznhM2QW8Li70JA-5A-aGHDmzAytZx2A2tCsZZ7BpslXVJp14tBBMAd06b1oQPbCxeu94NPupro7Af9AqqgIPDoVfWm42dV62xkT5Gh41qPZzs6gy93N48z--T5ePdYn69TCqW5SFRGriWeS4krSmvq0wLyjMlCqBNChqYLGjRFHUqtK6AaSUJRJYTqWqRcs5m6Hzru-7d-wA-lJ3xFbStshBXLanIKE9zzrJ_oExyWRScRvRshw46Hluue9Op_qPcZxkBsgWq3nnfQ1NWJnwlGKMwbUlJuXlX-fOuKLn4Jdm7_gF_AhjTlbM |
CitedBy_id | crossref_primary_10_3390_nano12091536 crossref_primary_10_1016_j_jhazmat_2020_123443 crossref_primary_10_1021_acs_est_7b04037 crossref_primary_10_1021_acs_est_0c00123 crossref_primary_10_1016_j_scitotenv_2019_03_007 crossref_primary_10_1016_j_jconhyd_2016_08_006 crossref_primary_10_1021_acs_energyfuels_4c04583 crossref_primary_10_1007_s11356_015_5193_0 crossref_primary_10_1016_j_cis_2017_06_002 crossref_primary_10_1016_j_jcis_2015_01_024 crossref_primary_10_1039_C7EN00152E crossref_primary_10_1016_j_petsci_2024_12_027 crossref_primary_10_1021_acs_energyfuels_5b01785 |
Cites_doi | 10.1007/s11051-013-1805-0 10.1002/aic.690450305 10.1016/j.cageo.2006.04.005 10.1021/es60058a005 10.1021/es0490018 10.1016/j.watres.2011.12.033 10.1021/ma202511b 10.1021/es802628n 10.1021/am4003974 10.1016/j.jconhyd.2011.09.005 10.1897/08-039.1 10.1021/la2006327 10.1016/j.jmr.2011.06.025 10.1201/9781315274287 10.1021/es100598h 10.1021/ef402453b 10.1016/j.watres.2013.02.025 10.1039/b907658a 10.1021/es801305y 10.1021/es071936b 10.1021/es2034747 10.1016/S0169-7722(01)00215-7 10.1021/es800128m 10.1016/j.advwatres.2012.02.005 10.1021/es902240k 10.1021/es402075f 10.1016/j.jmmm.2010.05.044 10.3390/s91008130 10.1021/es202643c 10.1016/S0169-7722(01)00160-7 10.1021/es900245d 10.1080/10643380091184174 10.1021/la404387t 10.1029/2006WR005151 10.1029/2012WR012468 10.1007/s13204-014-0305-6 10.1021/ef401338c 10.1021/es803388u 10.1016/S0009-2509(99)00422-4 10.1021/es500523p 10.1016/j.jconhyd.2012.04.008 10.1021/ef3020537 10.1021/es3036779 10.1016/j.jconhyd.2012.05.004 10.1039/c2ee21574h 10.1093/oso/9780198539445.001.0001 10.1016/j.watres.2011.05.025 10.1021/es402046u 10.1016/j.jcis.2011.04.111 10.1021/es903277p 10.1021/la204628c 10.1016/j.jconhyd.2010.10.002 |
ContentType | Journal Article |
DBID | AAYXX CITATION NPM 7X8 7SR 7U5 8BQ 8FD F28 FR3 JG9 L7M |
DOI | 10.1039/C4NR05088F |
DatabaseName | CrossRef PubMed MEDLINE - Academic Engineered Materials Abstracts Solid State and Superconductivity Abstracts METADEX Technology Research Database ANTE: Abstracts in New Technology & Engineering Engineering Research Database Materials Research Database Advanced Technologies Database with Aerospace |
DatabaseTitle | CrossRef PubMed MEDLINE - Academic Materials Research Database Engineered Materials Abstracts Technology Research Database Solid State and Superconductivity Abstracts Engineering Research Database Advanced Technologies Database with Aerospace ANTE: Abstracts in New Technology & Engineering METADEX |
DatabaseTitleList | CrossRef PubMed Materials Research Database MEDLINE - Academic |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Engineering |
EISSN | 2040-3372 |
EndPage | 1057 |
ExternalDocumentID | 25474703 10_1039_C4NR05088F |
Genre | Research Support, U.S. Gov't, Non-P.H.S Research Support, Non-U.S. Gov't Journal Article |
GroupedDBID | --- 0-7 0R~ 29M 4.4 53G 705 7~J AAEMU AAIWI AAJAE AANOJ AARTK AAWGC AAXHV AAYXX ABASK ABDVN ABEMK ABIQK ABJNI ABPDG ABRYZ ABXOH ACGFS ACIWK ACLDK ACRPL ADMRA ADNMO ADSRN AEFDR AENEX AENGV AESAV AETIL AFLYV AFOGI AFRDS AFRZK AFVBQ AGEGJ AGQPQ AGRSR AHGCF AHGXI AKBGW AKMSF ALMA_UNASSIGNED_HOLDINGS ALSGL ALUYA ANBJS ANLMG ANUXI APEMP ASKNT ASPBG AUDPV AVWKF AZFZN BLAPV BSQNT C6K CAG CITATION COF DU5 EBS ECGLT EE0 EF- EJD F5P FEDTE GGIMP H13 HVGLF HZ~ H~N J3G J3H J3I L-8 O-G O9- OK1 P2P R56 RAOCF RCNCU RNS RPMJG RSCEA RVUXY NPM 7X8 7SR 7U5 8BQ 8FD F28 FR3 JG9 L7M |
ID | FETCH-LOGICAL-c357t-abe4b977691d14dc5b6145a68e1f2ebe39818f8d26bbce3ba90e691409ad62443 |
ISSN | 2040-3364 2040-3372 |
IngestDate | Fri Jul 11 00:01:58 EDT 2025 Fri Jul 11 10:13:17 EDT 2025 Mon Jul 21 05:55:54 EDT 2025 Tue Jul 01 00:33:15 EDT 2025 Thu Apr 24 23:08:07 EDT 2025 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 3 |
Language | English |
LinkModel | OpenURL |
MergedId | FETCHMERGED-LOGICAL-c357t-abe4b977691d14dc5b6145a68e1f2ebe39818f8d26bbce3ba90e691409ad62443 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
PMID | 25474703 |
PQID | 1639498841 |
PQPubID | 23479 |
PageCount | 11 |
ParticipantIDs | proquest_miscellaneous_1651427435 proquest_miscellaneous_1639498841 pubmed_primary_25474703 crossref_citationtrail_10_1039_C4NR05088F crossref_primary_10_1039_C4NR05088F |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2015-01-21 |
PublicationDateYYYYMMDD | 2015-01-21 |
PublicationDate_xml | – month: 01 year: 2015 text: 2015-01-21 day: 21 |
PublicationDecade | 2010 |
PublicationPlace | England |
PublicationPlace_xml | – name: England |
PublicationTitle | Nanoscale |
PublicationTitleAlternate | Nanoscale |
PublicationYear | 2015 |
References | Wang (C4NR05088F-(cit39)/*[position()=1]) 2008; 42 Petosa (C4NR05088F-(cit14)/*[position()=1]) 2010; 44 Elimelech (C4NR05088F-(cit16)/*[position()=1]) 1998 Liang (C4NR05088F-(cit24)/*[position()=1]) 2013; 47 Quinn (C4NR05088F-(cit9)/*[position()=1]) 2005; 39 Bergendahl (C4NR05088F-(cit44)/*[position()=1]) 1999; 45 Thorne (C4NR05088F-(cit56)/*[position()=1]) 2006; 32 Hwang (C4NR05088F-(cit3)/*[position()=1]) 2012; 5 Hashemi (C4NR05088F-(cit5)/*[position()=1]) 2013; 27 Hiemenz (C4NR05088F-(cit15)/*[position()=1]) 1997 Quevedo (C4NR05088F-(cit25)/*[position()=1]) 2009; 43 Bai (C4NR05088F-(cit60)/*[position()=1]) 2012; 136–137 El Badawy (C4NR05088F-(cit30)/*[position()=1]) 2010; 44 Chowdhury (C4NR05088F-(cit21)/*[position()=1]) 2011; 360 Ersenkal (C4NR05088F-(cit11)/*[position()=1]) 2011; 126 Tosco (C4NR05088F-(cit12)/*[position()=1]) 2012; 46 Yao (C4NR05088F-(cit37)/*[position()=1]) 1971; 5 Park (C4NR05088F-(cit33)/*[position()=1]) 2012; 28 Schijven (C4NR05088F-(cit58)/*[position()=1]) 2000; 30 Park (C4NR05088F-(cit32)/*[position()=1]) 2014; 30 Paulsen (C4NR05088F-(cit48)/*[position()=1]) 2011; 212 French (C4NR05088F-(cit20)/*[position()=1]) 2009; 43 Petosa (C4NR05088F-(cit28)/*[position()=1]) 2012; 46 Chowdhury (C4NR05088F-(cit22)/*[position()=1]) 2012; 46 Schijven (C4NR05088F-(cit59)/*[position()=1]) 2002; 57 Bradford (C4NR05088F-(cit47)/*[position()=1]) 2012; 48 Wang (C4NR05088F-(cit23)/*[position()=1]) 2012; 14 Yoon (C4NR05088F-(cit35)/*[position()=1]) 2012; 45 Jeong (C4NR05088F-(cit26)/*[position()=1]) 2009; 11 Torkzaban (C4NR05088F-(cit41)/*[position()=1]) 2010; 118 Bagaria (C4NR05088F-(cit34)/*[position()=1]) 2013; 5 Li (C4NR05088F-(cit27)/*[position()=1]) 2011; 45 Bergendahl (C4NR05088F-(cit45)/*[position()=1]) 2000; 55 Callaghan (C4NR05088F-(cit50)/*[position()=1]) 1991 Brown (C4NR05088F-(cit51)/*[position()=1]) 2010; 322 Torkzaban (C4NR05088F-(cit29)/*[position()=1]) 2013; 47 Wang (C4NR05088F-(cit17)/*[position()=1]) 2008; 27 Yoon (C4NR05088F-(cit36)/*[position()=1]) 2011; 27 Ehtesabi (C4NR05088F-(cit6)/*[position()=1]) 2014; 28 Pensini (C4NR05088F-(cit19)/*[position()=1]) 2012; 46 Hendraningrat (C4NR05088F-(cit7)/*[position()=1]) 2014 Torkzaban (C4NR05088F-(cit42)/*[position()=1]) 2012; 136–137 Torkzaban (C4NR05088F-(cit46)/*[position()=1]) 2010; 44 Bear (C4NR05088F-(cit53)/*[position()=1]) 1972 Simmons (C4NR05088F-(cit31)/*[position()=1]) 2001; 52 O'Carroll (C4NR05088F-(cit10)/*[position()=1]) 2013; 51 Li (C4NR05088F-(cit40)/*[position()=1]) 2008; 42 Sun (C4NR05088F-(cit8)/*[position()=1]) 2014; 28 Tosco (C4NR05088F-(cit38)/*[position()=1]) 2009; 43 Goswami (C4NR05088F-(cit57)/*[position()=1]) 2007; 43 Liang (C4NR05088F-(cit43)/*[position()=1]) 2013; 47 Wang (C4NR05088F-(cit49)/*[position()=1]) 2014; 48 Koh (C4NR05088F-(cit61)/*[position()=1]) 2009; 9 Wang (C4NR05088F-(cit13)/*[position()=1]) 2013; 15 Saleh (C4NR05088F-(cit18)/*[position()=1]) 2008; 42 |
References_xml | – volume: 15 start-page: 1805 year: 2013 ident: C4NR05088F-(cit13)/*[position()=1] publication-title: J. Nanopart. Res. doi: 10.1007/s11051-013-1805-0 – volume: 45 start-page: 475 year: 1999 ident: C4NR05088F-(cit44)/*[position()=1] publication-title: AIChE J. doi: 10.1002/aic.690450305 – volume: 32 start-page: 1758 year: 2006 ident: C4NR05088F-(cit56)/*[position()=1] publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2006.04.005 – volume: 5 start-page: 1105 year: 1971 ident: C4NR05088F-(cit37)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es60058a005 – volume: 39 start-page: 1309 year: 2005 ident: C4NR05088F-(cit9)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es0490018 – volume: 46 start-page: 1273 year: 2012 ident: C4NR05088F-(cit28)/*[position()=1] publication-title: Water Res. doi: 10.1016/j.watres.2011.12.033 – volume: 45 start-page: 5157 year: 2012 ident: C4NR05088F-(cit35)/*[position()=1] publication-title: Macromolecules doi: 10.1021/ma202511b – volume: 43 start-page: 1354 year: 2009 ident: C4NR05088F-(cit20)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es802628n – volume: 5 start-page: 3329 year: 2013 ident: C4NR05088F-(cit34)/*[position()=1] publication-title: ACS Appl. Mater. Interfaces doi: 10.1021/am4003974 – volume: 126 start-page: 248 year: 2011 ident: C4NR05088F-(cit11)/*[position()=1] publication-title: J. Contam. Hydrol. doi: 10.1016/j.jconhyd.2011.09.005 – volume: 27 start-page: 1860 year: 2008 ident: C4NR05088F-(cit17)/*[position()=1] publication-title: Environ. Toxicol. Chem. doi: 10.1897/08-039.1 – volume: 27 start-page: 10962 year: 2011 ident: C4NR05088F-(cit36)/*[position()=1] publication-title: Langmuir doi: 10.1021/la2006327 – volume: 212 start-page: 133 year: 2011 ident: C4NR05088F-(cit48)/*[position()=1] publication-title: J. Magn. Reson. doi: 10.1016/j.jmr.2011.06.025 – volume-title: Principles of Colloid and Surface Chemistry year: 1997 ident: C4NR05088F-(cit15)/*[position()=1] doi: 10.1201/9781315274287 – volume: 44 start-page: 6532 year: 2010 ident: C4NR05088F-(cit14)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es100598h – volume: 28 start-page: 2384 year: 2014 ident: C4NR05088F-(cit8)/*[position()=1] publication-title: Energy Fuels doi: 10.1021/ef402453b – volume: 47 start-page: 2572 year: 2013 ident: C4NR05088F-(cit24)/*[position()=1] publication-title: Water Res. doi: 10.1016/j.watres.2013.02.025 – volume: 11 start-page: 1595 year: 2009 ident: C4NR05088F-(cit26)/*[position()=1] publication-title: J. Environ. Monit. doi: 10.1039/b907658a – volume: 42 start-page: 7174 year: 2008 ident: C4NR05088F-(cit40)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es801305y – volume: 42 start-page: 3349 year: 2008 ident: C4NR05088F-(cit18)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es071936b – volume: 46 start-page: 6968 year: 2012 ident: C4NR05088F-(cit22)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es2034747 – volume: 57 start-page: 259 year: 2002 ident: C4NR05088F-(cit59)/*[position()=1] publication-title: J. Contam. Hydrol. doi: 10.1016/S0169-7722(01)00215-7 – volume: 42 start-page: 3588 year: 2008 ident: C4NR05088F-(cit39)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es800128m – volume: 51 start-page: 104 year: 2013 ident: C4NR05088F-(cit10)/*[position()=1] publication-title: Adv. Water Resour. doi: 10.1016/j.advwatres.2012.02.005 – volume-title: Particle Deposition and Aggregation: Measurement, Modelling and Simulation year: 1998 ident: C4NR05088F-(cit16)/*[position()=1] – volume: 44 start-page: 1260 year: 2010 ident: C4NR05088F-(cit30)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es902240k – volume: 47 start-page: 11528 year: 2013 ident: C4NR05088F-(cit29)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es402075f – volume: 322 start-page: 3122 year: 2010 ident: C4NR05088F-(cit51)/*[position()=1] publication-title: J. Magn. Magn. Mater. doi: 10.1016/j.jmmm.2010.05.044 – volume: 9 start-page: 8130 year: 2009 ident: C4NR05088F-(cit61)/*[position()=1] publication-title: Sensors doi: 10.3390/s91008130 – volume: 46 start-page: 4008 year: 2012 ident: C4NR05088F-(cit12)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es202643c – volume: 52 start-page: 245 year: 2001 ident: C4NR05088F-(cit31)/*[position()=1] publication-title: J. Contam. Hydrol. doi: 10.1016/S0169-7722(01)00160-7 – volume: 43 start-page: 4425 year: 2009 ident: C4NR05088F-(cit38)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es900245d – volume: 30 start-page: 49 year: 2000 ident: C4NR05088F-(cit58)/*[position()=1] publication-title: Crit. Rev. Environ. Sci. Technol. doi: 10.1080/10643380091184174 – volume: 30 start-page: 784 year: 2014 ident: C4NR05088F-(cit32)/*[position()=1] publication-title: Langmuir doi: 10.1021/la404387t – volume: 43 start-page: W04418 year: 2007 ident: C4NR05088F-(cit57)/*[position()=1] publication-title: Water Resour. Res. doi: 10.1029/2006WR005151 – volume: 48 start-page: W09509 year: 2012 ident: C4NR05088F-(cit47)/*[position()=1] publication-title: Water Resour. Res. doi: 10.1029/2012WR012468 – year: 2014 ident: C4NR05088F-(cit7)/*[position()=1] publication-title: Appl. Nanosci. doi: 10.1007/s13204-014-0305-6 – volume: 28 start-page: 423 year: 2014 ident: C4NR05088F-(cit6)/*[position()=1] publication-title: Energy Fuels doi: 10.1021/ef401338c – volume: 43 start-page: 3176 year: 2009 ident: C4NR05088F-(cit25)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es803388u – volume: 55 start-page: 1523 year: 2000 ident: C4NR05088F-(cit45)/*[position()=1] publication-title: Chem. Eng. Sci. doi: 10.1016/S0009-2509(99)00422-4 – volume: 48 start-page: 10664 year: 2014 ident: C4NR05088F-(cit49)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es500523p – volume: 136–137 start-page: 43 year: 2012 ident: C4NR05088F-(cit60)/*[position()=1] publication-title: J. Contam. Hydrol. doi: 10.1016/j.jconhyd.2012.04.008 – volume: 27 start-page: 2194 year: 2013 ident: C4NR05088F-(cit5)/*[position()=1] publication-title: Energy Fuels doi: 10.1021/ef3020537 – volume: 46 start-page: 13401 year: 2012 ident: C4NR05088F-(cit19)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es3036779 – volume: 136–137 start-page: 86 year: 2012 ident: C4NR05088F-(cit42)/*[position()=1] publication-title: J. Contam. Hydrol. doi: 10.1016/j.jconhyd.2012.05.004 – volume: 5 start-page: 8304 year: 2012 ident: C4NR05088F-(cit3)/*[position()=1] publication-title: Energy Environ. Sci. doi: 10.1039/c2ee21574h – volume-title: Principles of Nuclear Magnetic Resonance Microscopy year: 1991 ident: C4NR05088F-(cit50)/*[position()=1] doi: 10.1093/oso/9780198539445.001.0001 – volume: 45 start-page: 4409 year: 2011 ident: C4NR05088F-(cit27)/*[position()=1] publication-title: Water Res. doi: 10.1016/j.watres.2011.05.025 – volume: 47 start-page: 12229 year: 2013 ident: C4NR05088F-(cit43)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es402046u – volume: 360 start-page: 548 year: 2011 ident: C4NR05088F-(cit21)/*[position()=1] publication-title: J. Colloid Interface Sci. doi: 10.1016/j.jcis.2011.04.111 – volume: 44 start-page: 1662 year: 2010 ident: C4NR05088F-(cit46)/*[position()=1] publication-title: Environ. Sci. Technol. doi: 10.1021/es903277p – volume: 28 start-page: 6246 year: 2012 ident: C4NR05088F-(cit33)/*[position()=1] publication-title: Langmuir doi: 10.1021/la204628c – volume: 118 start-page: 208 year: 2010 ident: C4NR05088F-(cit41)/*[position()=1] publication-title: J. Contam. Hydrol. doi: 10.1016/j.jconhyd.2010.10.002 – volume-title: Dynamics of Fluids in Porous Media year: 1972 ident: C4NR05088F-(cit53)/*[position()=1] – volume: 14 start-page: 1 year: 2012 ident: C4NR05088F-(cit23)/*[position()=1] publication-title: J. Nanopart. Res. |
SSID | ssj0069363 |
Score | 2.2057774 |
Snippet | Nanotechnologies have been proposed for a variety of environmental applications, including subsurface characterization, enhanced oil recovery, and
in situ... Nanotechnologies have been proposed for a variety of environmental applications, including subsurface characterization, enhanced oil recovery, and in situ... |
SourceID | proquest pubmed crossref |
SourceType | Aggregation Database Index Database Enrichment Source |
StartPage | 1047 |
SubjectTerms | Computer simulation Deposition Electrolytes Magnetic resonance imaging Mathematical models Nanostructure Sand Transport |
Title | In situ measurement and simulation of nano-magnetite mobility in porous media subject to transient salinity |
URI | https://www.ncbi.nlm.nih.gov/pubmed/25474703 https://www.proquest.com/docview/1639498841 https://www.proquest.com/docview/1651427435 |
Volume | 7 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwELagvcAB8WZ5yQguKHJJYjsbH0tFaUFUArUqPUV24qwiiFM12Qu_nrHjPFbaIuASRYl3I_n7PJ6xvxkj9EaKVNtD34ngYUEY1wlJS0aJKhTnMJ7ixIkxv5wkR2fs03c-22h32SWd2st_bc0r-R9U4RngarNk_wHZ8U_hAdwDvnAFhOH6Vxgfm6CtunVQTwt9bjOgrWp_KpfTaUjTkFqujE0o00HdOD2sy_cD59tKYF36SNCulV2Ucd6oncFspmTQSps62W1s_oJFblrAdtqQ14M4wx8fPumIz_169EVjVivpp0krAHKaRL_849PJxtUeLxO-qMjXSjbzhYnIagBJn-28p50Bi61akdLlhrVdzkhFZ5bTlozYatJDaiui5sxchdaZLOeNAI7L2oELcS4ERiGdprVRbDi8uol2Y4glwBju7n9-__F8mLATQRM6VK6l4t30KVsp2v940225JhZxPsnpXXTHBxN4v2fGPXRDm_vo9qzE5AP049hgyxE84wgGjuCJI7gp8SZH8MARXBnccwQ7jmDPEdw1eOQIHjjyEJ0dfjg9OCL-gA2SU77siFSaKQgAEhEVEStyrsBZ4zKB4VvGMLqpAHeuTGHAKpVrqqQINbRloZBFAn4hfYR2TGP0E4S5jMDTg5Gt09j2l4BQt4wkV4UoYp0nC_R26L8s99Xn7SEoPzOngqAiO2An31y3Hy7Q67HtZV9zZWurVwMMGZhEu88ljYYOySDEEEykKYv-1AYihRjcZ75Aj3sMx28NmD-99s0zdGti_HO0012t9QtwTjv10pPrN8XFk8o |
linkProvider | Royal Society of Chemistry |
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=In+situ+measurement+and+simulation+of+nano-magnetite+mobility+in+porous+media+subject+to+transient+salinity&rft.jtitle=Nanoscale&rft.au=Becker%2C+Matthew+D&rft.au=Wang%2C+Yonggang&rft.au=L+Paulsen%2C+Jeffrey&rft.au=Song%2C+Yi-Qiao&rft.date=2015-01-21&rft.eissn=2040-3372&rft.volume=7&rft.issue=3&rft.spage=1047&rft_id=info:doi/10.1039%2Fc4nr05088f&rft_id=info%3Apmid%2F25474703&rft.externalDocID=25474703 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2040-3364&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2040-3364&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2040-3364&client=summon |