Zeta Potential and Colloidal Stability Predictions for Inorganic Nanoparticle Dispersions: Effects of Experimental Conditions and Electrokinetic Models on the Interpretation of Results

In this work, a set of experimental electrophoretic mobility (μe) data was used to show how inappropriate selection of the electrokinetic model used to calculate the zeta potential (ζ-potential) can compromise the interpretation of the results for nanoparticles (NPs). The main consequences of using...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Langmuir Ročník 37; číslo 45; s. 13379
Hlavní autoři: Pochapski, Daniel José, Carvalho Dos Santos, Caio, Leite, Gabriel Wosiak, Pulcinelli, Sandra Helena, Santilli, Celso Valentim
Médium: Journal Article
Jazyk:angličtina
Vydáno: 16.11.2021
ISSN:1520-5827, 1520-5827
On-line přístup:Zjistit podrobnosti o přístupu
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract In this work, a set of experimental electrophoretic mobility (μe) data was used to show how inappropriate selection of the electrokinetic model used to calculate the zeta potential (ζ-potential) can compromise the interpretation of the results for nanoparticles (NPs). The main consequences of using ζ-potential values as criteria to indicate the colloidal stability of NP dispersions are discussed based on DLVO interaction energy predictions. For this, magnetite (Fe3O4) NPs were synthesized and characterized as a model system for performing electrokinetic experiments. The results showed that the Fe3O4 NPs formed mass fractal aggregates in solution, so the ζ-potential could not be determined under ideal conditions when μe depends on the NP radius. In addition, the Dukhin number (Du) estimated from potentiometric titration results indicated that stagnant layer conduction (SLC) could not be neglected for this system. The electrokinetic models that do not consider SLC grossly underestimated the ζ-potential values for the Fe3O4 NPs. The DLVO interaction energy predictions for the colloidal stability of the Fe3O4 NP dispersions also depended on the electrokinetic model used to calculate the ζ-potential. The results obtained for the Fe3O4 NP dispersions also suggested that, contrary to many reports in the literature, high ζ-potential values do not necessarily reflect high colloidal stability for charge-stabilized NP dispersions.In this work, a set of experimental electrophoretic mobility (μe) data was used to show how inappropriate selection of the electrokinetic model used to calculate the zeta potential (ζ-potential) can compromise the interpretation of the results for nanoparticles (NPs). The main consequences of using ζ-potential values as criteria to indicate the colloidal stability of NP dispersions are discussed based on DLVO interaction energy predictions. For this, magnetite (Fe3O4) NPs were synthesized and characterized as a model system for performing electrokinetic experiments. The results showed that the Fe3O4 NPs formed mass fractal aggregates in solution, so the ζ-potential could not be determined under ideal conditions when μe depends on the NP radius. In addition, the Dukhin number (Du) estimated from potentiometric titration results indicated that stagnant layer conduction (SLC) could not be neglected for this system. The electrokinetic models that do not consider SLC grossly underestimated the ζ-potential values for the Fe3O4 NPs. The DLVO interaction energy predictions for the colloidal stability of the Fe3O4 NP dispersions also depended on the electrokinetic model used to calculate the ζ-potential. The results obtained for the Fe3O4 NP dispersions also suggested that, contrary to many reports in the literature, high ζ-potential values do not necessarily reflect high colloidal stability for charge-stabilized NP dispersions.
AbstractList In this work, a set of experimental electrophoretic mobility (μe) data was used to show how inappropriate selection of the electrokinetic model used to calculate the zeta potential (ζ-potential) can compromise the interpretation of the results for nanoparticles (NPs). The main consequences of using ζ-potential values as criteria to indicate the colloidal stability of NP dispersions are discussed based on DLVO interaction energy predictions. For this, magnetite (Fe3O4) NPs were synthesized and characterized as a model system for performing electrokinetic experiments. The results showed that the Fe3O4 NPs formed mass fractal aggregates in solution, so the ζ-potential could not be determined under ideal conditions when μe depends on the NP radius. In addition, the Dukhin number (Du) estimated from potentiometric titration results indicated that stagnant layer conduction (SLC) could not be neglected for this system. The electrokinetic models that do not consider SLC grossly underestimated the ζ-potential values for the Fe3O4 NPs. The DLVO interaction energy predictions for the colloidal stability of the Fe3O4 NP dispersions also depended on the electrokinetic model used to calculate the ζ-potential. The results obtained for the Fe3O4 NP dispersions also suggested that, contrary to many reports in the literature, high ζ-potential values do not necessarily reflect high colloidal stability for charge-stabilized NP dispersions.In this work, a set of experimental electrophoretic mobility (μe) data was used to show how inappropriate selection of the electrokinetic model used to calculate the zeta potential (ζ-potential) can compromise the interpretation of the results for nanoparticles (NPs). The main consequences of using ζ-potential values as criteria to indicate the colloidal stability of NP dispersions are discussed based on DLVO interaction energy predictions. For this, magnetite (Fe3O4) NPs were synthesized and characterized as a model system for performing electrokinetic experiments. The results showed that the Fe3O4 NPs formed mass fractal aggregates in solution, so the ζ-potential could not be determined under ideal conditions when μe depends on the NP radius. In addition, the Dukhin number (Du) estimated from potentiometric titration results indicated that stagnant layer conduction (SLC) could not be neglected for this system. The electrokinetic models that do not consider SLC grossly underestimated the ζ-potential values for the Fe3O4 NPs. The DLVO interaction energy predictions for the colloidal stability of the Fe3O4 NP dispersions also depended on the electrokinetic model used to calculate the ζ-potential. The results obtained for the Fe3O4 NP dispersions also suggested that, contrary to many reports in the literature, high ζ-potential values do not necessarily reflect high colloidal stability for charge-stabilized NP dispersions.
Author Santilli, Celso Valentim
Carvalho Dos Santos, Caio
Leite, Gabriel Wosiak
Pulcinelli, Sandra Helena
Pochapski, Daniel José
Author_xml – sequence: 1
  givenname: Daniel José
  surname: Pochapski
  fullname: Pochapski, Daniel José
– sequence: 2
  givenname: Caio
  surname: Carvalho Dos Santos
  fullname: Carvalho Dos Santos, Caio
– sequence: 3
  givenname: Gabriel Wosiak
  surname: Leite
  fullname: Leite, Gabriel Wosiak
– sequence: 4
  givenname: Sandra Helena
  surname: Pulcinelli
  fullname: Pulcinelli, Sandra Helena
– sequence: 5
  givenname: Celso Valentim
  surname: Santilli
  fullname: Santilli, Celso Valentim
BookMark eNpNkMtOAyEUhompiW31DVywdNMKzDAXd2YctUnVxsvGTUPhTEUpVKCJvpmPJ5O6cHUu-f_vPzkjNLDOAkKnlEwpYfRcyDA1wq43O-2nVBJGeHGAhpQzMuEVKwf_-iM0CuGdEFJneT1EP68QBV64CDZqYbCwCjfOGKdVmp6iWGmj4zdeeFBaRu1swJ3zeGadXwurJb4X1m2Fj1oawFc6bMGHXnaB264DGQN2HW6_0lpvUkiiNs4qvUf1ca1JKu8-tIUEwXdOgUkmi-MbpJwIfuvTkb2hRz1C2JkYjtFhJ0yAk786Ri_X7XNzO5k_3Myay_lE5CSPE1bx9KGSd0oWGeTAKGVQ1x2DkuZEKaoqruqsWhUFZCTjnaSKVDSnlSpKKDkbo7M9d-vd5w5CXG50kGDSv8HtwpLxilYsLwhjv4U9fqo
CitedBy_id crossref_primary_10_1016_j_molliq_2022_118560
crossref_primary_10_3390_pharmaceutics14030479
crossref_primary_10_1007_s12668_025_02151_7
crossref_primary_10_1016_j_envres_2024_118632
crossref_primary_10_1016_j_polymer_2024_127616
crossref_primary_10_1002_ppsc_202200118
crossref_primary_10_1016_j_jenvman_2024_122587
crossref_primary_10_1016_j_seppur_2025_132255
crossref_primary_10_1002_anie_202505855
crossref_primary_10_1016_j_nxnano_2025_100263
crossref_primary_10_1039_D4RA06614F
crossref_primary_10_1016_j_nxnano_2025_100141
crossref_primary_10_3390_antibiotics13121199
crossref_primary_10_1111_1750_3841_70563
crossref_primary_10_1016_j_colsurfa_2025_137697
crossref_primary_10_3390_pharmaceutics17020140
crossref_primary_10_1002_aoc_70227
crossref_primary_10_1016_j_jece_2024_114190
crossref_primary_10_1016_j_cscm_2025_e05239
crossref_primary_10_1016_j_sajb_2024_04_005
crossref_primary_10_1016_j_cej_2025_164237
crossref_primary_10_1039_D5TC01636C
crossref_primary_10_1002_jbm_b_35633
crossref_primary_10_1186_s43094_025_00851_1
crossref_primary_10_1016_j_foodhyd_2024_110602
crossref_primary_10_3390_futurepharmacol5030044
crossref_primary_10_2174_0122103155292898240902065307
crossref_primary_10_1016_j_porgcoat_2022_107333
crossref_primary_10_1007_s11696_025_04072_x
crossref_primary_10_3390_ijms24010869
crossref_primary_10_1016_j_inoche_2022_109828
crossref_primary_10_1007_s13399_025_06859_0
crossref_primary_10_1016_j_seppur_2024_128494
crossref_primary_10_1016_j_watres_2025_124133
crossref_primary_10_1016_j_mtsust_2025_101195
crossref_primary_10_3390_antibiotics13080686
crossref_primary_10_1016_j_jcis_2023_11_047
crossref_primary_10_1021_acs_molpharmaceut_5c00276
crossref_primary_10_1016_j_biteb_2025_102284
crossref_primary_10_1016_j_fbio_2023_103318
crossref_primary_10_1515_opag_2025_0452
crossref_primary_10_1016_j_nxsust_2024_100094
crossref_primary_10_1016_j_mtchem_2024_102004
crossref_primary_10_1007_s12668_023_01160_8
crossref_primary_10_1016_j_porgcoat_2023_108173
crossref_primary_10_2147_IJN_S448578
crossref_primary_10_3390_catal14070427
crossref_primary_10_1016_j_nantod_2024_102466
crossref_primary_10_3390_nano14060516
crossref_primary_10_1016_j_carbpol_2025_124369
crossref_primary_10_3390_pharmaceutics17020167
crossref_primary_10_3390_ma15228050
crossref_primary_10_3390_polym16131829
crossref_primary_10_3390_antiox13070826
crossref_primary_10_1016_j_mtcomm_2023_107260
crossref_primary_10_1002_jev2_12353
crossref_primary_10_1002_aelm_202500073
crossref_primary_10_1002_jsde_12621
crossref_primary_10_1016_j_rineng_2024_102516
crossref_primary_10_1021_acs_langmuir_5c01263
crossref_primary_10_1021_acs_langmuir_5c01147
crossref_primary_10_1016_j_jddst_2024_106041
crossref_primary_10_1002_smll_202500748
crossref_primary_10_1016_j_carbpol_2024_122456
crossref_primary_10_1007_s42452_025_06654_6
crossref_primary_10_1016_j_envpol_2022_120315
crossref_primary_10_1016_j_rineng_2025_107156
crossref_primary_10_1016_j_cej_2025_161501
crossref_primary_10_1016_j_pmatsci_2022_100945
crossref_primary_10_2147_IJN_S512524
crossref_primary_10_1016_j_bbii_2025_100133
crossref_primary_10_1016_j_micromeso_2022_112008
crossref_primary_10_1016_j_ceramint_2025_05_161
crossref_primary_10_1016_j_ijbiomac_2025_147204
crossref_primary_10_1021_acs_iecr_5c00944
crossref_primary_10_1038_s41598_025_96758_1
crossref_primary_10_1007_s00396_025_05477_6
crossref_primary_10_1007_s11696_025_04315_x
crossref_primary_10_1063_5_0225268
crossref_primary_10_1093_jpp_rgaf072
crossref_primary_10_1016_j_ceramint_2024_06_221
crossref_primary_10_3390_nano13091543
crossref_primary_10_3390_magnetochemistry9040106
crossref_primary_10_1007_s12247_025_09922_5
crossref_primary_10_1134_S1087659624601059
crossref_primary_10_1038_s41598_025_03421_w
crossref_primary_10_1039_D5NJ01870F
crossref_primary_10_2147_IJN_S387681
crossref_primary_10_1016_j_ijbiomac_2024_136929
crossref_primary_10_1016_j_inoche_2023_111969
crossref_primary_10_1021_acs_est_5c04935
crossref_primary_10_1002_ange_202505855
crossref_primary_10_1016_j_ajps_2025_101093
crossref_primary_10_3390_molecules29112495
crossref_primary_10_1016_j_cej_2025_167705
crossref_primary_10_1016_j_colsurfa_2025_137094
crossref_primary_10_1186_s12951_025_03560_2
crossref_primary_10_3390_ijms26189203
crossref_primary_10_1002_adfm_202508939
crossref_primary_10_1016_j_colsurfb_2025_114949
crossref_primary_10_3390_molecules28041711
crossref_primary_10_1007_s42452_025_07458_4
crossref_primary_10_1002_chem_202203764
crossref_primary_10_1002_aic_17897
crossref_primary_10_1016_j_carbon_2025_120538
crossref_primary_10_1016_j_jhazmat_2025_137194
crossref_primary_10_1016_j_jddst_2024_105662
crossref_primary_10_1016_j_inoche_2024_112790
crossref_primary_10_1016_j_cemconres_2024_107574
crossref_primary_10_3390_molecules28083320
crossref_primary_10_1016_j_molliq_2025_126924
crossref_primary_10_1080_20565623_2024_2367849
crossref_primary_10_1016_j_clay_2025_107917
crossref_primary_10_2147_IJN_S480592
crossref_primary_10_26599_JAC_2023_9220780
crossref_primary_10_1016_j_mseb_2025_118172
crossref_primary_10_1016_j_colsurfa_2025_137553
crossref_primary_10_3390_separations12050107
crossref_primary_10_1016_j_colsurfa_2025_137677
crossref_primary_10_1016_j_jhazmat_2025_138722
crossref_primary_10_1016_j_colsurfb_2025_115002
crossref_primary_10_1007_s12668_024_01573_z
crossref_primary_10_1016_j_jconhyd_2024_104387
crossref_primary_10_1007_s00210_025_04296_4
crossref_primary_10_1016_j_ijbiomac_2025_147634
crossref_primary_10_3389_fphar_2025_1611507
crossref_primary_10_1016_j_chemosphere_2025_144666
crossref_primary_10_1039_D2PY00331G
crossref_primary_10_1016_j_jconrel_2025_114146
crossref_primary_10_3390_gels10120796
crossref_primary_10_1039_D5NJ01836F
crossref_primary_10_1016_j_saa_2022_121372
crossref_primary_10_3390_nano12010028
crossref_primary_10_1515_gps_2025_0007
crossref_primary_10_2217_nnm_2022_0198
crossref_primary_10_1016_j_jwpe_2023_103903
crossref_primary_10_3390_plants12091832
crossref_primary_10_1016_j_ultras_2025_107751
crossref_primary_10_1007_s11033_025_10241_8
crossref_primary_10_1016_j_mtcomm_2025_113805
crossref_primary_10_3390_jfb14090440
crossref_primary_10_1038_s41598_025_01101_3
crossref_primary_10_1007_s10876_025_02782_6
crossref_primary_10_1080_1061186X_2025_2549579
crossref_primary_10_3390_polym16192805
crossref_primary_10_1002_cnma_202500186
crossref_primary_10_1016_j_micromeso_2024_113032
crossref_primary_10_1016_j_ijpharm_2025_125683
crossref_primary_10_1080_02652048_2025_2480597
crossref_primary_10_1002_aoc_7638
crossref_primary_10_3390_magnetochemistry10070044
crossref_primary_10_1016_j_molliq_2025_127953
crossref_primary_10_1016_j_inoche_2025_115161
crossref_primary_10_3390_biom15081157
crossref_primary_10_1016_j_colsurfa_2025_137179
crossref_primary_10_1007_s12033_025_01454_0
crossref_primary_10_1016_j_jddst_2022_103749
crossref_primary_10_1016_j_microc_2023_108864
crossref_primary_10_1016_j_molliq_2025_128251
crossref_primary_10_1002_smll_202504031
crossref_primary_10_1088_2632_959X_adc757
crossref_primary_10_3390_pharmaceutics16101305
crossref_primary_10_1016_j_cej_2025_160385
crossref_primary_10_61554_ijnrph_v3i1_2025_140
crossref_primary_10_1016_j_ijbiomac_2024_133608
crossref_primary_10_1002_app_56243
crossref_primary_10_1016_j_ijbiomac_2025_144363
crossref_primary_10_1007_s00284_024_03790_x
crossref_primary_10_1016_j_colsurfa_2022_130831
crossref_primary_10_3390_chemengineering8060119
crossref_primary_10_3390_pharmaceutics14030640
crossref_primary_10_3390_w16010180
crossref_primary_10_1016_j_microc_2025_115149
crossref_primary_10_1002_adfm_202508062
crossref_primary_10_1016_j_chemphys_2024_112399
crossref_primary_10_1515_biol_2025_1121
crossref_primary_10_1088_1361_6528_ace6a5
crossref_primary_10_1080_00986445_2025_2556139
crossref_primary_10_3390_nano13152250
crossref_primary_10_1016_j_idairyj_2025_106355
crossref_primary_10_1016_j_jconrel_2024_09_017
crossref_primary_10_1016_j_chemosphere_2023_138887
crossref_primary_10_1016_j_ijbiomac_2025_146775
crossref_primary_10_1016_j_jddst_2023_104789
crossref_primary_10_3390_pharmaceutics17050633
crossref_primary_10_1016_j_csite_2025_106594
crossref_primary_10_1039_D4NR05271D
crossref_primary_10_1080_1536383X_2024_2367577
crossref_primary_10_1186_s44331_025_00003_5
crossref_primary_10_1039_D4TC05145A
crossref_primary_10_1016_j_mser_2025_100933
crossref_primary_10_1016_j_jece_2025_115745
crossref_primary_10_1016_j_jconrel_2024_09_029
crossref_primary_10_1007_s12666_023_02957_7
crossref_primary_10_1007_s12668_024_01483_0
crossref_primary_10_1016_j_jphotochem_2022_114471
crossref_primary_10_1016_j_ijbiomac_2025_142264
crossref_primary_10_1007_s12668_024_01593_9
crossref_primary_10_1016_j_biopha_2023_115041
crossref_primary_10_3390_pharmaceutics17010072
crossref_primary_10_1016_j_cej_2024_151933
crossref_primary_10_1016_j_diamond_2025_112593
crossref_primary_10_1016_j_eti_2024_103564
crossref_primary_10_1016_j_arabjc_2024_106029
crossref_primary_10_1002_adma_202419496
crossref_primary_10_1016_j_bioorg_2024_107459
crossref_primary_10_1016_j_ceja_2025_100806
crossref_primary_10_1016_j_xphs_2025_103897
crossref_primary_10_1016_j_porgcoat_2024_108929
crossref_primary_10_1680_jgrma_24_00127
crossref_primary_10_1016_j_colsurfa_2024_135822
crossref_primary_10_1021_acsomega_5c03575
crossref_primary_10_22159_ijap_2025v17i5_54215
crossref_primary_10_1039_D4EN00572D
crossref_primary_10_3389_fbioe_2023_1220336
crossref_primary_10_3390_ma17112666
crossref_primary_10_1007_s13346_025_01959_w
crossref_primary_10_1002_smll_202301884
crossref_primary_10_1016_j_envres_2024_119527
crossref_primary_10_1016_j_jphotochem_2023_115424
crossref_primary_10_1002_adma_202510140
crossref_primary_10_3390_polym14142965
crossref_primary_10_1016_j_molliq_2023_121251
crossref_primary_10_1007_s13399_025_06804_1
crossref_primary_10_1016_j_scitotenv_2023_166458
crossref_primary_10_1016_j_ijhydene_2024_04_036
crossref_primary_10_1016_j_btre_2025_e00916
crossref_primary_10_1021_acsomega_5c03224
crossref_primary_10_3390_cryst15020132
crossref_primary_10_1002_aic_18237
crossref_primary_10_1016_j_jlumin_2025_121186
crossref_primary_10_1039_D5EN00188A
crossref_primary_10_1016_j_inoche_2025_114782
crossref_primary_10_3389_fonc_2024_1296091
crossref_primary_10_1007_s11696_024_03528_w
crossref_primary_10_1016_S1003_6326_23_66203_X
crossref_primary_10_1016_j_ijbiomac_2025_147274
crossref_primary_10_1016_j_xphs_2023_06_006
crossref_primary_10_3390_molecules27010168
crossref_primary_10_1007_s10787_023_01274_1
crossref_primary_10_3390_magnetochemistry9090211
crossref_primary_10_1016_j_nantod_2023_101998
crossref_primary_10_1016_j_cej_2024_155700
crossref_primary_10_1016_j_rechem_2025_102717
crossref_primary_10_3390_cosmetics12040141
crossref_primary_10_1016_j_triboint_2024_109506
crossref_primary_10_1088_2043_6262_adb55f
crossref_primary_10_1016_j_foodchem_2025_145004
crossref_primary_10_1016_j_ijbiomac_2023_125779
crossref_primary_10_1038_s41598_025_93496_2
crossref_primary_10_1002_jbm_b_35409
crossref_primary_10_3390_app13042182
crossref_primary_10_1016_j_pestbp_2025_106543
crossref_primary_10_1016_j_ijbiomac_2024_138802
crossref_primary_10_1016_j_bbagen_2025_130777
crossref_primary_10_3390_gels11080641
crossref_primary_10_3390_mi16020130
crossref_primary_10_1016_j_jphotochem_2024_116253
crossref_primary_10_3390_pharmaceutics16121536
crossref_primary_10_1002_jrs_70039
crossref_primary_10_1016_j_ces_2024_121094
crossref_primary_10_1080_03639045_2025_2525952
crossref_primary_10_1021_acs_langmuir_4c03490
crossref_primary_10_1111_ijac_14844
crossref_primary_10_3390_ijms251910519
crossref_primary_10_3390_nano13071209
crossref_primary_10_1007_s10971_025_06741_5
crossref_primary_10_1007_s12011_025_04682_2
crossref_primary_10_1016_j_dci_2025_105409
crossref_primary_10_1016_j_ijbiomac_2024_138236
crossref_primary_10_1038_s41598_025_12096_2
crossref_primary_10_1016_j_jhazmat_2024_136775
crossref_primary_10_1080_01932691_2023_2295024
crossref_primary_10_1016_j_jddst_2024_106368
crossref_primary_10_1063_5_0219098
ContentType Journal Article
DBID 7X8
DOI 10.1021/acs.langmuir.1c02056
DatabaseName MEDLINE - Academic
DatabaseTitle MEDLINE - Academic
DatabaseTitleList MEDLINE - Academic
Database_xml – sequence: 1
  dbid: 7X8
  name: MEDLINE - Academic
  url: https://search.proquest.com/medline
  sourceTypes: Aggregation Database
DeliveryMethod no_fulltext_linktorsrc
Discipline Chemistry
EISSN 1520-5827
GroupedDBID ---
-~X
.K2
4.4
53G
55A
5GY
5VS
7X8
7~N
AABXI
AAHBH
ABBLG
ABJNI
ABLBI
ABMVS
ABQRX
ABUCX
ACGFS
ACJ
ACNCT
ACS
ADHLV
AEESW
AENEX
AFEFF
AGXLV
AHGAQ
ALMA_UNASSIGNED_HOLDINGS
AQSVZ
BAANH
CS3
CUPRZ
DU5
EBS
ED~
F5P
GGK
GNL
IH9
IHE
JG~
RNS
ROL
TN5
UI2
UPT
VF5
VG9
W1F
YQT
~02
ID FETCH-LOGICAL-a404t-28502175fdc63e4e2112e99f2e7140dd1d85d938b66e3035fc1d081418d67e752
IEDL.DBID 7X8
ISICitedReferencesCount 335
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000721132300020&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1520-5827
IngestDate Thu Jul 10 18:02:49 EDT 2025
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 45
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-a404t-28502175fdc63e4e2112e99f2e7140dd1d85d938b66e3035fc1d081418d67e752
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
OpenAccessLink http://hdl.handle.net/11449/233753
PQID 2581824602
PQPubID 23479
ParticipantIDs proquest_miscellaneous_2581824602
PublicationCentury 2000
PublicationDate 2021-11-16
PublicationDateYYYYMMDD 2021-11-16
PublicationDate_xml – month: 11
  year: 2021
  text: 2021-11-16
  day: 16
PublicationDecade 2020
PublicationTitle Langmuir
PublicationYear 2021
SSID ssj0009349
Score 2.7161195
Snippet In this work, a set of experimental electrophoretic mobility (μe) data was used to show how inappropriate selection of the electrokinetic model used to...
SourceID proquest
SourceType Aggregation Database
StartPage 13379
Title Zeta Potential and Colloidal Stability Predictions for Inorganic Nanoparticle Dispersions: Effects of Experimental Conditions and Electrokinetic Models on the Interpretation of Results
URI https://www.proquest.com/docview/2581824602
Volume 37
WOSCitedRecordID wos000721132300020&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8QwEA7qCnrxLb6J4DXaps3Li8i6oiCyiMriRbJNCotrq9uu4D_z5znTdlHxIngspNPSDN98mZnOR8iB6WuRchWyVAWOxSY1zFqjmQPo4zbiJq6m899fqetr3euZbpNwK5q2ygkmVkDt8gRz5EdcQGjhsQz4ycsrQ9UorK42EhrTpBUhlQF_Vr2vaeEmqugvhKiACc3V5Nc5Hh7ZpDjEjODzeDA6DBMgTUL-guMqxpwv_vftlshCwy7pae0Oy2TKZytkrj0RdVslHw--tLSbl9gkBCtt5ijmDvKBgytgnlWv7DvtjrCAU_kkBVpLL7Na_imhAMdwzq4fQM8GOGgcE27FMa0HIRc0T2nnm24A2MeyeGUKH9ephXeegN6CEYpibEO4KaNARenPHkg0deOL8bAs1sjdeee2fcEa8QZm4yAuGdcCjzsidYmMfOzhoMm9MSn3OCLQudBp4Uyk-1J6CKMiTUIH9CQOtZPKK8HXyUyWZ36DUBxbp_p9qaWSsbaBDYX3gDXWqAisB5tkf7Ipj_A5seJhM5-Pi8evbdn6w5ptMs-xYwWb_OQOaaUAAH6XzCZv5aAY7VW-9Ql04t0k
linkProvider ProQuest
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=Zeta+Potential+and+Colloidal+Stability+Predictions+for+Inorganic+Nanoparticle+Dispersions%3A+Effects+of+Experimental+Conditions+and+Electrokinetic+Models+on+the+Interpretation+of+Results&rft.jtitle=Langmuir&rft.au=Pochapski%2C+Daniel+Jos%C3%A9&rft.au=Carvalho+Dos+Santos%2C+Caio&rft.au=Leite%2C+Gabriel+Wosiak&rft.au=Pulcinelli%2C+Sandra+Helena&rft.date=2021-11-16&rft.issn=1520-5827&rft.eissn=1520-5827&rft.volume=37&rft.issue=45&rft.spage=13379&rft_id=info:doi/10.1021%2Facs.langmuir.1c02056&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1520-5827&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1520-5827&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1520-5827&client=summon