Estimation of Nanoparticle’s Surface Electrostatic Potential in Solution Using Acid–Base Molecular Probes I: <i>In Silico</i> Implementation for Surfactant Micelles

Farafonov, Vladimir; Lebed, Alexander V.; Nerukh, Dmitry; Mchedlov‐Petrossyan, Nikolay O.

doi:10.1021/acs.jpcb.2c07012

Cited by 2 publications

(9 citation statements)

References 62 publications

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“…In total, seventeen molecular probes were examined mainly in SDS and CTAB micellar solutions. The results of our research group have been reported in seventeen articles from 2016 to the present [53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69]. We thought it is expedient to summarize the data obtained and the regularities found.…”

Section: Introductionmentioning

confidence: 80%

Solvatochromic and Acid–Base Molecular Probes in Surfactant Micelles: Comparison of Molecular Dynamics Simulation with the Experiment

Mchedlov‐Petrossyan

Farafonov

Lebed

2023

Liquids

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This article summarizes a series of seventeen publications by the authors devoted to molecular dynamics modeling of various indicator dyes (molecular probes) enclosed in surfactant micelles. These dyes serve as generally recognized tools for studying various types of organized solutions, among which surfactant micelles in water are the simplest and most explored. The modeling procedure involves altogether 50 to 95 surfactant molecules, 16 to 28 thousand water molecules, and a single dye molecule. The presentation of the simulation results was preceded by a brief review of the state of experimental studies. This article consists of three parts. First, despite numerous literature data devoted to modeling the micelles itself, we decided to revisit this issue. The structure and hydration of the surface of micelles of surfactants, first of all of sodium n-dodecylsulfate, SDS, and cetyltrimethylammonium bromide, CTAB, were studied. The values of the electrical potential, Ψ, were estimated as functions of the ionic strength and distance from the surface. The decrease in the Ψ value with distance is gradual. Attempts to consider both DS− and CTA+ micelles in water without counterions result in a decay into two smaller aggregates. Obviously, the hydrophobic interaction (association) of the hydrocarbon tails balances the repulsion of the charged headgroups of these small “bare” micelles. The second part is devoted to the study of seven pyridinium N-phenolates, known as Reichardt’s dyes, in ionic micelles. These most powerful solvatochromic indicators are now used for examining various colloidal systems. The localization and orientation of both zwitterionic and (colorless) cationic forms are generally consistent with intuitive ideas about the hydrophobicity of substituents. Hydration has been quantitatively described for both the dye molecule as a whole and the oxygen atom. A number of markers, including the visible absorption spectra of Reichardt’s dyes, enable assuming a better hydration of the micellar surface of SDS than that of CTAB. However, our data show that it is more correct to speak about the more pronounced hydrogen-bonding ability of water molecules in anionic micelles than about better hydration of the SDS micelles as compared to CTAB ones. Finally, a set of acid–base indicators firmly fixed in the micellar pseudophase were studied by molecular dynamics. They are instruments for estimating electrostatic potentials of micelles and related aggregates as Ψ= 2.303RTF−1 (pKai − pKaapp), where pKai and pKaapp are indices of so-called intrinsic and apparent dissociation constants. In this case, in addition to the location, orientation, and hydration, the differences between values of pKaapp and indices of the dissociation constants in water were estimated. Only a semi-quantitative agreement with the experimental data was obtained. However, the differences between pKaapp of a given indicator in two micellar solutions do much better agree with the experimental data. Accordingly, the experimental Ψ values of ionic micelles, as determined using the pKaapp in nonionic micelles as pKai, are reproduced with reasonable accuracy for the corresponding indicator. However, following the experimental data, a scatter of the Ψ values obtained with different indicators for given micelles is observed. This problem may be the subject of further research.

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Section: Introductionmentioning

confidence: 80%

Solvatochromic and Acid–Base Molecular Probes in Surfactant Micelles: Comparison of Molecular Dynamics Simulation with the Experiment

Mchedlov‐Petrossyan

Farafonov

Lebed

2023

Liquids

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“…In Table , they are shown together with several metrics of the indicator’s hydration: the molar fractions of water χ(water) in the local environment of either the whole molecule (except hydrocarbon tails) or the O atom(s) of its ionizing OH or COOH group(s) of acidic and basic forms. The p K a shifts were calculated via eq (the protocol for finding χ(water) is described in the Supporting Information): normalΔ normalp K normala calc app = normalΔ G deprot ( m ) − normalΔ G deprot ( w ) R T .25em ln nobreak0em.25em⁡ 10 . Here, Δ G deprot(m) and Δ G deprot(w) are the free energies of deprotonation of the indicator in TX-100 micelles and in water, respectively, which were taken from preceding studies. , …”

Section: Resultsmentioning

confidence: 99%

“…Correspondence between the Ψ values found with the indicator method in vitro and in silico (adapted from Paper I, copyright 2022 American Chemical Society). Black squares: DDP, green diamonds: HHC, red circles: DF (filled for neutral, hollow for cationic), and brown triangles: DODR.…”

Section: Resultsmentioning

confidence: 99%

“…Here, ΔG deprot(m) and ΔG deprot(w) are the free energies of deprotonation of the indicator in TX-100 micelles and in water, respectively, which were taken from preceding studies. 21,23 For the case of water fraction around the ionizing groups of the basic forms, a monotonic dependence is observed (Figure 4, eq 5): on average, reducing water content by 10% makes the calculated pK a more negative by ≈0.6 units. The relevance of this metric has a clear physical explanation: within the entire compound, the strongest interaction with water molecules is formed by the charged O − or COO − groups, and these groups are present in the basic forms (the acidic forms have electroneutral OH or COOH groups).…”

Section: ■ Computational Detailsmentioning

confidence: 91%

“…In our recent work, we implemented the described method in silico (we will refer to it as Paper I below in the text). 21 There, we recreated a unique situation: both the "instrumental" parameter (Ψ calc ) and its microscopic origins (the MD trajectories of the systems' evolution in time) belong to the same simulated system and are available at the same time. Hence, they can be matched safely, and the trends discovered in the model systems may then be extrapolated to the real ones.…”

Section: ■ Introductionmentioning

confidence: 99%

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Estimation of Nanoparticle’s Surface Electrostatic Potential in Solution Using Acid–Base Molecular Probes II: Insight from Atomistic Simulations of Micelles

et al. 2023

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Exploiting acid–base indicators as molecular probes is one of the most popular methods for determining the surface electrostatic potential Ψ in hydrophilic colloids like micellar surfactant solutions and related systems. Specifically, the indicator’s apparent acidity constant index is measured in the colloid solution of interest and, as a rule, in a nonionic surfactant solution; the difference between the two is proportional to Ψ. Despite the widespread use of this approach, a major problem remains unresolved, namely, the dissimilarity of Ψ values obtained with different indicators for the same system. The common point of view recognizes the effect of several factors (the choice of the nonionic surfactant, the probe’s localization, and the degree of hydration of micellar pseudophase) but does not allow to quantitatively assess their impact and decide which indicator reports the most correct Ψ value. Here, based on the ability to predict the reported Ψ values in silico, we examined the role of these factors using molecular dynamics simulations for five probes and two surfactants. The probe’s hydration in the Stern layer was found responsible for approximately half of the dissimilarity range. The probe’s localization is found important but hard to quantify because of the irregular structure of the Stern layer. The most accurate indicators among the examined set were identified. Supplementing experiments on measuring Ψ with molecular dynamics simulation is proposed as a way of improving the efficacy of the indicator method: the simulations can guide the choice of the most suitable probe and nonionic surfactant for the given nanoparticles.

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Estimation of Nanoparticle’s Surface Electrostatic Potential in Solution Using Acid–Base Molecular Probes I: In Silico Implementation for Surfactant Micelles

Cited by 2 publications

References 62 publications

Solvatochromic and Acid–Base Molecular Probes in Surfactant Micelles: Comparison of Molecular Dynamics Simulation with the Experiment

Solvatochromic and Acid–Base Molecular Probes in Surfactant Micelles: Comparison of Molecular Dynamics Simulation with the Experiment

Estimation of Nanoparticle’s Surface Electrostatic Potential in Solution Using Acid–Base Molecular Probes II: Insight from Atomistic Simulations of Micelles

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