The supramolecular organization of soft materials, such as colloids, polymers, and amphiphiles, results from a subtle balance of weak intermolecular interactions and entropic forces. This competition can drive the self-organization of soft materials at the nano-/mesoscale. Modeling soft-matter self-assembly requires, therefore, considering a complex interplay of forces at the relevant length scales without sacrificing the molecular details that define the chemical identity of the system. This mini-review focuses on the application of a tool known as molecular theory to study self-assembly in different types of soft materials. This tool is based on extremizing an approximate free energy functional of the system, and, therefore, it provides a direct, computationally affordable estimation of the stability of different self-assembled morphologies. Moreover, the molecular theory explicitly incorporates structural details of the chemical species in the system, accounts for their conformational degrees of freedom, and explicitly includes their chemical equilibria. This mini-review introduces the general ideas behind the theoretical formalism and discusses its advantages and limitations compared with other theoretical tools commonly used to study self-assembled soft materials. Recent application examples are discussed: the self-patterning of polyelectrolyte brushes on planar and curved surfaces, the formation of nanoparticle (NP) superlattices, and the self-organization of amphiphiles into micelles of different shapes. Finally, prospective methodological improvements and extensions (also relevant for related theoretical tools) are analyzed.
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http://dx.doi.org/10.1021/acsomega.2c04785 | DOI Listing |
ACS Appl Mater Interfaces
January 2025
Department of Chemistry, College of Sciences, Northeastern University, Shenyang 110819, P. R. China.
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View Article and Find Full Text PDFNanomicro Lett
January 2025
Key Laboratory of Bio-Inspired Smart Interfacial Science and Technology of Ministry of Education, School of Chemistry, Beihang University, Beijing, 100191, People's Republic of China.
The proliferation of wearable biodevices has boosted the development of soft, innovative, and multifunctional materials for human health monitoring. The integration of wearable sensors with intelligent systems is an overwhelming tendency, providing powerful tools for remote health monitoring and personal health management. Among many candidates, two-dimensional (2D) materials stand out due to several exotic mechanical, electrical, optical, and chemical properties that can be efficiently integrated into atomic-thin films.
View Article and Find Full Text PDFMed J Malaysia
January 2025
Universiti Sains Malaysia, School of Medical Sciences, Department of Radiology, Health Campus, Kubang Kerian, Kelantan, Malaysia.
Introduction: Contrast-enhanced ultrasound (CEUS), an in vivo imaging tool for evaluating intraplaque neovascularisation (IPN), is an increasingly researched marker of susceptible atherosclerotic plaque. This study aims to assess the feasibility of quantifying carotid IPN using CEUS and to identify and characterise the neovascularisation in carotid plaques. The hospital's ethical committee approved the study, and the informed individual consent form of CEUS was obtained from all patients before the examination.
View Article and Find Full Text PDFMacromol Rapid Commun
January 2025
Department of Materials Science and Engineering, National University of Singapore (NUS), 9 Engineering Drive 1, Singapore, 117575, Singapore.
The modification of thermoplastic polymers is frequently impeded by the inherent contradiction between their toughness and strength. In this study, an effective strategy to significantly improve the mechanical properties of ductile polymers by simply adding a complimentary rigid polymer is introduced. This work uses a semi-crystalline polymer aliphatic polyketone (POK) as the matrix material and a small quantity of polymethyl methacrylate (PMMA) as the rigid polymer, through establishing molecular chain entanglements at the interface to produce POK/PMMA blends with exceptional mechanical property.
View Article and Find Full Text PDFJ Chem Phys
January 2025
School of Chemistry, Beihang University, Beijing 100191, China.
Dynamic density functional theory (DDFT) is a fruitful approach for modeling polymer dynamics, benefiting from its multiscale and hybrid nature. However, the Onsager coefficient, the only free parameter in DDFT, is primarily derived empirically, limiting the accuracy and broad application of DDFT. Herein, we propose a machine learning-based, bottom-up workflow to directly extract the Onsager coefficient from molecular simulations, circumventing partly heuristic assumptions in traditional approaches.
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