Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

This study investigates the molecular interactions and self-assembly behaviors in microemulsions formed by alkanes, alcohols, a nonionic surfactant (C12E5), and anionic surfactants (SDBS, SDS). Utilizing quantum mechanical weak interaction analysis and molecular dynamics simulations, we explore the weak interaction forces, thermal stability, and conformation of surfactant molecules at the interface membrane. Radial distribution function (RDF) and molecular polar surface area (MPSA) analyses reveal how hydrophilic group structures influence water molecules, while reduced density gradient (RDG) diagrams provide insights into microscopic interactions. Molecular dynamics simulations demonstrate that the surfactant concentration significantly affects the interaction energies between microemulsion components. As the surfactant concentration increases, the interaction energies between pentanol, water, and alkanes also increase. Specifically, C12E5 shows a gradual decrease in the interaction energy between water and pentanol at higher concentrations, with only a 1.79% increase at 9% concentration compared to a 65.03 and 23.38% decrease for SDBS and SDS, respectively. These findings suggest that C12E5 contributes to a more stable microemulsion system, while anionic surfactants lead to more pronounced energy fluctuations and structural changes in the interface membrane. This work establishes a comprehensive framework for analyzing weak interactions and microemulsion formation, offering valuable insights into the molecular mechanisms that govern the surfactant behavior in microemulsion systems.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12163830PMC
http://dx.doi.org/10.1021/acsomega.5c01425DOI Listing

Publication Analysis

Top Keywords

molecular dynamics
12
interactions molecular
8
nonionic surfactant
8
anionic surfactants
8
sdbs sds
8
weak interaction
8
dynamics simulations
8
interface membrane
8
surfactant concentration
8
interaction energies
8

Similar Publications

Passivating detrimental defects is essential for improving perovskite solar cells (PSCs) performance. While hydrogen interstitials are often considered harmful, their role in defect passivation remains unclear. Using nonadiabatic molecular dynamics, we uncover a self-passivation mechanism between hydrogen (H) and bromine (Br) interstitials in all-inorganic CsPbBr perovskites.

View Article and Find Full Text PDF

Macroautophagy/autophagy is an evolutionarily conserved process through which cells degrade cytoplasmic substances via autophagosomes. During the initiation of autophagosome formation, the ULK/Atg1 complex serves as a scaffold that recruits and regulates downstream ATG/Atg proteins and ATG9/Atg9-containing vesicles. Despite the essential role of the ULK/Atg1 complex, its components have changed during evolution; the ULK complex in mammals consists of ULK1 (or ULK2), RB1CC1, ATG13, and ATG101, whereas the Atg1 complex in the yeast lacks Atg101 but instead has Atg29 and Atg31 along with Atg17.

View Article and Find Full Text PDF

Molecular Plasmonic Cavities.

Nano Lett

September 2025

Department of Physics, Columbia University, New York, New York 10027, United States.

Graphene-based photonic structures have emerged as fertile ground for the controlled manipulation of surface plasmon polaritons (SPPs), providing a two-dimensional platform with low optoelectronic losses. In principle, nanostructuring graphene can enable further confinement of nanolight─enhancing light-matter interactions in the form of SPP cavity modes. In this study, we engineer nanoscale plasmonic cavities composed of self-assembled C arrays on graphene.

View Article and Find Full Text PDF

The discovery of solute precursors of crystalline materials, such as biominerals, recently challenged the classical nucleation theory (CNT). One emerging method for investigating these early-stage intermediates in solution is dissolution dynamic nuclear polarization (dDNP)-enhanced nuclear magnetic resonance (NMR) spectroscopy. Recent applications of dDNP to calcium carbonate (CaC) and calcium phosphate (CaP) mineralization have demonstrated the feasibility of identifying and tracing very early-stage prenucleation clusters (PNCs).

View Article and Find Full Text PDF

Machine learning (ML) and deep learning (DL) methodologies have significantly advanced drug discovery and design in several aspects. Additionally, the integration of structure-based data has proven to successfully support and improve the models' predictions. Indeed, we previously demonstrated that combining molecular dynamics (MD)-derived descriptors with ML models allows to effectively classify kinase ligands as allosteric or orthosteric.

View Article and Find Full Text PDF