4.5 Article

Self-assembly behavior of pH- and thermosensitive amphiphilic triblock copolymers in solution: Experimental studies and self-consistent field theory simulations

期刊

JOURNAL OF PHYSICAL CHEMISTRY B
卷 112, 期 40, 页码 12666-12673

出版社

AMER CHEMICAL SOC
DOI: 10.1021/jp805072t

关键词

-

资金

  1. National Natural Science Foundation of China [50673026, 20574018]
  2. Education Ministry of China [20050251008]
  3. Shanghai Municipality [06SU07002, 0652nm021, 082231, B502]

向作者/读者索取更多资源

We investigated, both experimentally and theoretically, the self-assembly behaviors of pH- and thermosensitive poly(L-glutamic acid)-b-poly(propylene oxide)-b-poly(L-glutamic acid) (PLGA-b-PPO-b-PLGA) triblock copolymers in aqueous solution by means of transmission electron microscopy (TEM), scanning electron microscopy (SEM), dynamic light scattering (DLS), circular dichroism (CD), and self-consistent field theory (SCFT) simulations. Vesicles were observed when the hydrophilic PLGA block length is shorter or the pH value of solution is lower. The vesicles were found to transform to spherical micelles when the PLGA block length increases or its conformation changes from helix to coil with increasing the pH value. In addition, increasing temperature gives rise to a decrease in the size of aggregates, which is related to the dehydration of the PPO segments at higher temperatures. The SCFT simulation results show that the vesicles transform to the spherical micelles with increasing the fraction or statistical length of A block in model ABA triblock copolymer, which corresponds to the increase in the PLGA length or its conformation change from helix to coil in experiments, respectively. The SCFT calculations also provide chain distribution information in the aggregates. On the basis of both experimental and SCFT results, the mechanism of the structure change of the PLGA-b-PPO-b-PLGA aggregates was proposed.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Chemistry, Multidisciplinary

Kinetically Programming Copolymerization-like Coassembly of Multicomponent Nanoparticles with DNA

Tianyun Cai, Shuochen Zhao, Jiaping Lin, Liangshun Zhang

Summary: This study presents a general method of controllable coassembly of bivalent DNA-functionalized nanoparticles into heterostructures via stepwise polymerization, and develops a quantitative model to predict the kinetics and outcomes of coassembly. The strategy can be applied to various regular nanopolymers with complex architectures. The research provides insights for the rational design of supramolecular DNA materials.

ACS NANO (2022)

Article Engineering, Environmental

Design of silicon-containing arylacetylene resins aided by machine learning enhanced materials genome approach

Songqi Zhang, Shi Du, Liquan Wang, Jiaping Lin, Lei Du, Xinyao Xu, Liang Gao

Summary: This study proposed a new approach using a materials genome method to design and screen silicon-containing acetylene resins with excellent processing properties and heat resistance. Through high-throughput screening and machine learning model prediction, a promising silicon-containing acetylene resin was successfully synthesized, confirming improved processing properties.

CHEMICAL ENGINEERING JOURNAL (2022)

Article Polymer Science

Effect of aliphatic segment length and content on crystallization and biodegradation properties of aliphatic-aromatic co-polyesters

Meng Chen, Chunhua Cai, Jie Bao, Yuliu Du, Hongbing Gao, Xiucai Liu

Summary: This work investigates the effects of variations in aliphatic chain length and component content in aliphatic aromatic terpolymers on the properties of the polyesters. The results indicate successful synthesis of the desired co-polyesters and the ability to achieve the coexistence of different crystals by adjusting the chain length and component content, resulting in improved biodegradability.

POLYMER DEGRADATION AND STABILITY (2022)

Article Nanoscience & Nanotechnology

Machine-Learning-Assisted Design of Highly Tough Thermosetting Polymers

Yaxi Hu, Wenlin Zhao, Liquan Wang, Jiaping Lin, Lei Du

Summary: This paper proposes a machine-assisted materials genome (MGA) approach to design novel epoxy thermosets with excellent mechanical properties using machine learning models. A proof-of-concept experiment is conducted to verify the designed structures and gene substructures affecting mechanical properties are extracted, revealing the mechanisms of high-performance polymers.

ACS APPLIED MATERIALS & INTERFACES (2022)

Article Chemistry, Multidisciplinary

Supramolecular Polymerization of Polymeric Nanorods Mediated by Block Copolymers

Yike Yao, Liang Gao, Chunhua Cai, Jiaping Lin, Shaoliang Lin

Summary: Introducing a second component is an effective way to manipulate polymerization behavior. However, this phenomenon has rarely been observed in colloidal systems, such as polymeric nanoparticles. Here, we report the supramolecular polymerization of polymeric nanorods mediated by block copolymers. Experimental observations and simulation results illustrate that block copolymers surround the polymeric nanorods and mainly concentrate around the two ends, leaving the hydrophobic side regions exposed. These polymeric nanorods connect in a side-by-side manner through hydrophobic interactions to form bundles. As polymerization progresses, the block copolymers gradually deposit onto the bundles and finally assemble into helical nanopatterns on the outermost surface, which terminates the polymerization. It is anticipated that this work could offer inspiration for a general strategy of controllable supramolecular polymerization.

ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2023)

Article Chemistry, Multidisciplinary

Hierarchical 2D-1D micelles self-assembled from the heterogeneous seeded-growth of rod-coil block copolymers

Chengyan Zhang, Liang Gao, Jiaping Lin, Liquan Wang

Summary: Precise control of size and dimension is crucial for constructing complex hierarchical nanostructures. Brownian dynamics simulations revealed that 2D-1D hybrid micelles can be formed via liquid-crystallization-driven self-assembly. The structural transition of the micelle core and the sequential generation of cylindrical arms provide explanations to some unaddressed issues in experiments. The hybrid micelles also exhibit high surface area and distinctive suspension behaviors, making them a good stabilizer.

NANOSCALE (2023)

Article Chemistry, Physical

Patterning of Polymer-Functionalized Nanoparticles with Varied Surface Mobilities of Polymers

Shuting Gong, Tianyi Wang, Jiaping Lin, Liquan Wang

Summary: Polymers can be attached to nanoparticles either dynamically or permanently, resulting in polymer-functionalized nanoparticles. The mobility of polymer brushes anchored to nanoparticles can affect surface patterns, but the impact is unclear. This study used self-consistent field theory calculations to investigate the influence of lateral polymer mobility on surface patterning. The results demonstrated that the fraction of mobile brushes significantly influences the surface patterning of polymer-functionalized nanoparticles. This work provides a fundamental understanding of the dependence of surface patterning on lateral polymer mobility.

MATERIALS (2023)

Article Polymer Science

Recent advances in the solution self-assembly of polypeptides

Chunhua Cai, Jiaping Lin

Summary: This article focuses on the recent advances in the solution self-assembly of polypeptides, including new driving forces for polypeptide self-assembly and novel preparation methods. The self-assembly behavior and diversity of structures are studied through liquid crystallization, conformation variation, supramolecular polymerization, substrate-mediated self-assembly, and polymerization-induced self-assembly. In conclusion, the trends in polypeptide solution self-assembly are discussed.

JOURNAL OF POLYMER SCIENCE (2023)

Article Chemistry, Multidisciplinary

Azobenzene Functionalized Organic Covalent Frameworks: Controlled Morphologies and Photo-Regulated Adsorption

Yanli Zhao, Xinfeng Tao, Jiaping Lin, Shaoliang Lin

Summary: A simple and robust template-free solvothermal strategy is reported to obtain azobenzene-dangled COFs. The crystallinity, specific surface area, and morphology of Azo-COFs can be controlled by changing the ratio of amine to aldehyde monomers. The reversible trans-to-cis isomerization of the dangled azobenzene units inside the pores allows for intelligent regulation of surface wettability and enhanced adsorption capacity.

ADVANCED FUNCTIONAL MATERIALS (2023)

Article Polymer Science

Precise Control over Positioning and Orientation of Nanorods in Block Copolymer Nanocomposites via Regulation of Coassembly Pathways

Yutong Tang, Tianyun Cai, Jiaping Lin, Liangshun Zhang

Summary: By regulating the coassembly pathways, the orientation-dependent assembly of nanorods can be achieved in block copolymer nanocomposites, leading to defect-free nanostructures. The preferred orientation of nanorods can be finely tuned by thermodynamic variables, and end-to-end aligned nanorods can enhance the mechanical strength of nanostructured composites.

MACROMOLECULES (2023)

Article Polymer Science

Harnessing Data Augmentation and Normalization Preprocessing to Improve the Performance of Chemical Reaction Predictions of Data-Driven Model

Boyu Zhang, Jiaping Lin, Lei Du, Liangshun Zhang

Summary: In this study, the molecular transformer model is integrated with data augmentation and normalization preprocessing strategies to accomplish three tasks in chemical reactions. The results demonstrate that the prediction accuracy of the molecular transformer model can be significantly improved with the proposed strategies.

POLYMERS (2023)

Article Chemistry, Physical

Discovery of thermosetting polymers with low hygroscopicity, low thermal expansivity, and high modulus by machine learning

Xinyao Xu, Wenlin Zhao, Yaxi Hu, Liquan Wang, Jiaping Lin, Huimin Qi, Lei Du

Summary: Traditional material design principles for thermosetting polymers are inefficient due to conflicting properties. Machine learning combined with limited experimental data and all-atomic simulations can establish robust property estimation models. Virtual candidates are screened and promising polycyanurates are identified through well-trained ML models, verified by theoretical simulations and proof-of-concept experiments. The proposed framework can accelerate the rational design of polymers and reveal underlying physical rules.

JOURNAL OF MATERIALS CHEMISTRY A (2023)

暂无数据