A Stochastic FRET Study on the Core Dimension of Polystyrene--Poly(Polyethylene Glycol Monomethyl Ether Acrylate) Micelles.

Langmuir

Department of Chemistry, Faculty of Science, Nara Women's University, Kitauoyanishi-machi, Nara 630-8506, Japan.

Published: October 2024

Polystyrene--poly(polyethylene glycol monomethyl ether acrylate) (PSt--PPEGA) copolymers featuring pyrene and perylene as the Förster resonance energy transfer (FRET) donor (denoted as D-BCP) and acceptor (denoted as A-BCP), respectively, were synthesized via the reversible addition and fragmentation chain transfer (RAFT) polymerization. These copolymers were then used to form DA-mixed micelles via a dialysis method. The micelles consisted of D-BCP (mole fraction = 0.04), A-BCP ( = 0.04), and label-free PSt--PPEGA ( = 0.92). The decrease in fluorescence intensity of pyrene in the micelles confirmed the occurrence of FRET, with an observed efficiency of 0.32. A Monte Carlo approach was employed to estimate the expected FRET efficiency, assuming the random fractional distribution of D-BCP and A-BCP, along with the random spatial distribution of pyrene and perylene within the micellar core. The observed FRET efficiency suggested a core radius () of 0.95, where was the Förster critical distance. With calculated to be 3.2 nm based on Förster theory, was determined to be approximately 3.0 nm, aligning closely with the dried-out core radius estimated from aggregation number and polystyrene density. This stochastic FRET methodology was further applied to investigate the swelling behavior of the polymer micelles in a mixture of ,-dimethylformamide (DMF) and water. Dynamic light scattering analysis revealed minimal change in core dimension below 60 vol % DMF content. However, FRET analysis provided a deeper insight, showing an increase in core radius with DMF content up to 20 vol %, followed by saturation up to 50 vol %, offering a more comprehensive understanding of the micelle swelling behavior.

Download full-text PDF

Source
http://dx.doi.org/10.1021/acs.langmuir.4c02374DOI Listing

Publication Analysis

Top Keywords

core radius
12
stochastic fret
8
core dimension
8
polystyrene--polypolyethylene glycol
8
glycol monomethyl
8
monomethyl ether
8
ether acrylate
8
pyrene perylene
8
fret efficiency
8
swelling behavior
8

Similar Publications

Objectives: To predict and characterize the three-dimensional (3D) structure of protein arginine methyltransferase 2 (PRMT2) using homology modeling, besides, the identification of potent inhibitors for enhanced comprehension of the biological function of this protein arginine methyltransferase (PRMT) family protein in carcinogenesis.

Materials And Methods: An method was employed to predict and characterize the three-dimensional structure. The bulk of PRMTs in the PDB shares just a structurally conserved catalytic core domain.

View Article and Find Full Text PDF

Significant progress has been made through the optimization of modelling and device architecture solar cells has proven to be a valuable and highly effective approach for gaining a deeper understanding of the underlying physical processes in solar cells. Consequently, this research has conducted a two-dimensional (2D) perovskite solar cells (PSCs) simulation to develop an accurate model. The approach utilized in this study is based on the finite element method (FEM).

View Article and Find Full Text PDF

Multi-layer conductive structures, especially those with features like bolt holes, are vulnerable to hidden corrosion and cracking, posing a serious threat to equipment integrity. Early defect detection is vital for implementing effective maintenance strategies. However, the subtle signals produced by these defects necessitate highly sensitive non-destructive testing (NDT) techniques.

View Article and Find Full Text PDF

Wastewater contamination by organic dyes, especially Rhodamine B (RhB), possess a significant environmental challenge. This study explores a novel bio sorbent for the removal of RhB dye from contaminated water, using chitosan trisodium citrate-modified magnetic nanoparticles (Fe₃O₄@CSTSC@PANI) coated with polyaniline. The nanocomposite was characterized by FT-IR, XRD, HRTEM, SEM, BET surface analysis.

View Article and Find Full Text PDF

Medical image processing has been highlighted as an area where deep-learning-based models have the greatest potential. However, in the medical field, in particular, problems of data availability and privacy are hampering research progress and, thus, rapid implementation in clinical routine. The generation of synthetic data not only ensures privacy but also allows the drawing of new patients with specific characteristics, enabling the development of data-driven models on a much larger scale.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!