Quantifying the effects of cooperative hydrogen bonds between vicinal diols on polymer dynamics

氢键 聚合物 邻接 分子间力 化学物理 材料科学 分子动力学 结晶学 化学 高分子化学 分子 计算化学 有机化学 复合材料
作者
Shintaro Nakagawa,Jun Xia,Naoko Yoshie
出处
期刊:Soft Matter [Royal Society of Chemistry]
卷期号:18 (6): 1275-1286 被引量:2
标识
DOI:10.1039/d1sm01747k
摘要

Transient cross-links such as hydrogen bonds (H-bonds) are a central concept for creating polymers with mechanical functionalities, including toughness and self-healing properties. While conventional strong H-bonding groups are based on rigid and planar molecular motifs with multidentate intermolecular interactions, we recently discovered that a structurally simple and flexible vicinal diol (VDO) could serve as a robust yet dynamic cross-link with multiple intermolecular H-bonds between hydroxy groups. In this work, we investigated the effects of cooperativity of H-bonds in VDOs on polymer dynamics. We synthesized model polybutadienes with either VDO or monool (MO) side groups by a radical-mediated thiol-ene click reaction. The oscillatory shear rheology data were analyzed by using the sticky Rouse model. The characteristic time of a single modified segment (δτ0) was significantly longer for the VDO-modified polymers than for the MO-modified polymers, even when they had the same number density of hydroxy groups. The increase in δτ0 with increasing degree of modification was much more drastic for the VDO-modified polymers than for the MO-modified polymers. Moreover, the characteristic time of an unmodified Rouse segment (τ0) was found to increase upon increasing the number of VDOs in the chain, while it was unchanged against the number of MOs. These observations highlight the cooperative effects of placing two hydroxy groups in a close vicinal arrangement. The multiplicity of H-bonds and the structural flexibility of VDOs led to efficient retardation of the chain dynamics.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
3秒前
可爱的函函应助zihanShen采纳,获得10
3秒前
4秒前
4秒前
4秒前
4秒前
4秒前
4秒前
陈坤完成签到,获得积分10
4秒前
4秒前
4秒前
4秒前
李健应助科研通管家采纳,获得10
4秒前
yy32323完成签到,获得积分10
5秒前
5秒前
liu关注了科研通微信公众号
5秒前
6秒前
专一的弱完成签到,获得积分10
7秒前
勤奋的科研小白完成签到,获得积分10
8秒前
8秒前
10秒前
130发布了新的文献求助10
10秒前
脑洞疼应助1010采纳,获得10
10秒前
molihuakai应助YangZhang采纳,获得10
11秒前
斯文的万恶完成签到,获得积分10
11秒前
冷酷的亦绿完成签到,获得积分10
11秒前
cyh完成签到,获得积分10
13秒前
kdf发布了新的文献求助10
13秒前
14秒前
14秒前
14秒前
安久发布了新的文献求助10
14秒前
FashionBoy应助斯文的万恶采纳,获得10
16秒前
学林书屋发布了新的文献求助10
17秒前
雨一直下完成签到,获得积分10
17秒前
19秒前
打打应助清爽的柜子采纳,获得30
19秒前
谓风发布了新的文献求助10
21秒前
洁净的怀绿完成签到,获得积分10
22秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
CLSI M100 Performance Standards for Antimicrobial Susceptibility Testing 36th edition 400
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6361593
求助须知:如何正确求助?哪些是违规求助? 8175396
关于积分的说明 17222316
捐赠科研通 5416388
什么是DOI,文献DOI怎么找? 2866330
邀请新用户注册赠送积分活动 1843584
关于科研通互助平台的介绍 1691450