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Record W2981608917 · doi:10.1021/acs.langmuir.9b02855

Applications of Molecular Structural Aspects of Gemini Surfactants in Reducing Nanoparticle–Nanoparticle Interactions

2019· article· en· W2981608917 on OpenAlexaff
Rajpreet Kaur, Kultar Singh, Poonam Khullar, Anita Gupta, Gurinder Kaur Ahluwalia, Mandeep Singh Bakshi

Bibliographic record

VenueLangmuir · 2019
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsCollege of the North Atlantic
Fundersnot available
KeywordsChemistrySodium dodecyl sulfateNanoparticleBromideColloidHydrocarbonCationic polymerizationDynamic light scatteringAqueous solutionSalting outChemical engineeringInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Oppositely charged nanoparticle (NP)-nanoparticle (NP) interactions were studied by titrating sodium dodecyl sulfate (SDS) stabilized NPs with cetyltrimethylammonium bromide (CTAB) stabilized NPs at constant temperature with the help of UV-visible and dynamic light scattering measurements. CTAB stabilized NPs were systematically replaced with a series of cationic gemini surfactants to demonstrate the effect of head group and hydrocarbon tail modifications on the electrostatic interactions with SDS stabilized NPs. Introduction of the dimeric gemini head group (alkylammonium or imidazolium), spacer length, and double tail hydrocarbon length all significantly reduced the NP-NP interactions and delayed their salting-out process. They lead to the formation of stable colloidal aqueous solubilized NP-NP complexes. The results concluded that NP-NP interactions can be overcome if appropriately stabilized NPs are used to maintain their colloidal stability so as to achieve maximum applicability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.248
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2019
Admission routes1
Has abstractyes

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