We perform extensive molecular dynamics simulations of a charged polymer in a good solvent in the regime where the chain is collapsed. We analyze the dependence of the gyration radius R_{g} on the reduced Bjerrum length ℓ_{B} and find two different regimes. In the first one, called a weak electrostatic regime, R_{g}∼ℓ_{B}^{-1/2}, which is consistent only with the predictions of the counterion-fluctuation theory. In the second one, called a strong electrostatic regime, we find R_{g}∼ℓ_{B}^{-1/5}. To explain the novel regime we modify the counterion-fluctuation theory.
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http://dx.doi.org/10.1103/PhysRevLett.117.147801 | DOI Listing |
J Chem Theory Comput
January 2025
Advanced Artificial Intelligence Theoretical and Computational Chemistry Laboratory, School of Chemistry, University of Hyderabad, Hyderabad, Telangana 500046, India.
We present a directed electrostatics strategy integrated as a graph neural network (DESIGNN) approach for predicting stable nanocluster structures on their potential energy surfaces (PESs). The DESIGNN approach is a graph neural network (GNN)-based model for building structures of large atomic clusters with specific sizes and point-group symmetry. This model assists in the structure building of atomic metal clusters by predicting molecular electrostatic potential (MESP) topography minima on their structural evolution paths.
View Article and Find Full Text PDFEnviron Res
January 2025
Department of Environmental and Sustainable Engineering, Faculty of Engineering, Chulalongkorn University, 254 Phayathai Road, Pathumwan, Bangkok, 10330, Thailand; Professor Aroon Sorathesn Center of Excellence in Environmental Engineering, Department of Environmental and Sustainable Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand.
Microplastics (MPs) pose significant risks to aquatic life and human health. Conventional water treatment is ineffective in removing MPs, demanding alternative technologies. Biochar exhibits a potential for removing MPs through adsorption and filtration.
View Article and Find Full Text PDFSmall Methods
January 2025
Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, TN 37830, USA.
Understanding ferroelectric domain wall dynamics at the nanoscale across a broad range of timescales requires measuring domain wall position under different applied electric fields. The success of piezoresponse force microscopy (PFM) as a tool to apply local electric fields at different positions and imaging their changing position, together with the information obtained from associated switching spectroscopies has fueled numerous studies of the dynamics of ferroelectric domains to determine the impact of intrinsic parameters such as crystalline order, defects and pinning centers, as well as boundary conditions such as environment. However, the investigation of sub-coercive reversible domain wall vibrational modes requires the development of new tools that enable visualizing domain wall motion under varying applied fields with high temporal and spatial resolution while also accounting for spurious electrostatic effects.
View Article and Find Full Text PDFCarbohydr Polym
March 2025
Department of Chemical Engineering, Waterloo Institute for Nanotechnology, University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, Canada. Electronic address:
Research on the interaction between surfactants and cellulose nanocrystals (CNC) has mainly focused on the interaction between CNC and conventional surfactants, and there are no reported studies on the interaction between CNC and gemini surfactants. The interactions between CNC and conventional surfactant (tetradecyltrimethylammonium bromide, termed as TTAB), asymmetric gemini surfactant ([CH(CH)N(CH)N(CH)CH]Br (14-6-6)) or symmetric gemini surfactant ([CH(CH)N(CH)N(CH)CH]Br (14-6-14)) were examined. With increasing surfactant concentration, interaction of TTAB/CNC was described by three regions, i.
View Article and Find Full Text PDFLangmuir
January 2025
Materials Science and Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, Pennsylvania 19104, United States.
The functional performance of a particulate thin film depends greatly on the particle distribution that forms during drying. In situ methods for monitoring the impact of different processing parameters on the distribution of particles currently require expensive and specialized equipment. This work addresses this gap by miniaturizing a geophysical prospecting method to thin-film applications.
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