The thermoelastic properties of monolayer covalent organic frameworks studied by machine-learning molecular dynamics

热弹性阻尼 单层 材料科学 分子动力学 共价键 动力学(音乐) 热的 化学物理 纳米技术 热力学 计算化学 物理 化学 有机化学 声学
作者
Bing Wang,Penghua Ying,Jin Zhang
出处
期刊:Nanoscale [Royal Society of Chemistry]
卷期号:16 (1): 237-248 被引量:8
标识
DOI:10.1039/d3nr04509a
摘要

Two-dimensional (2D) covalent organic frameworks (COFs) are emerging as promising 2D polymeric materials with broad applications owing to their unique properties, among which the mechanical properties are quite important for various applications. However, the mechanical properties of 2D COFs have not been systematically studied yet. Herein, a machine-learned neuroevolution potential (NEP) was developed to study the elastic properties of two representative monolayer 2D COFs, namely COF-1 and COF-5. The trained NEP enables one to study the elastic properties of 2D COFs in realistic situations (e.g., finite size and temperature) and possesses greatly improved computational efficiency when compared with density functional theory calculations. With the aid of the obtained NEP, molecular dynamics (MD) simulations together with a strain-fluctuation method were employed to evaluate the elastic constants of the considered 2D COFs at different temperatures. The elastic constants of COF-1 and COF-5 monolayers were found to decrease with an increase in the temperature, though they were almost isotropic irrespective of the temperature. The thermally induced softening of 2D COFs below a critical temperature was observed, which is mainly attributed to their inherent ripple configurations at finite temperatures, while above the critical temperature, the damping effect of anharmonic vibrations became the dominant factor. Based on the proposed mechanisms, analytical models were developed for capturing the temperature dependence of elastic constants, which were found to agree with the MD simulation results well. This work provides an in-depth insight into the thermoelastic properties of monolayer COFs, which can guide the development of 2D COF materials with tailored mechanical behaviors for enhancing their performance in various applications.

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
刚刚
科研通AI6.3应助PP采纳,获得10
刚刚
无花果应助美满鸽子采纳,获得10
1秒前
1秒前
2秒前
PengqianGuo完成签到,获得积分10
3秒前
在水一方应助酷酷采纳,获得10
4秒前
田様应助甜美乘云采纳,获得10
5秒前
5秒前
6秒前
明亮紫易发布了新的文献求助10
6秒前
NexusExplorer应助冷静剑鬼采纳,获得10
7秒前
共享精神应助医学僧采纳,获得10
7秒前
niniyiya完成签到,获得积分10
7秒前
好久不见发布了新的文献求助10
9秒前
桐桐应助自由万声采纳,获得10
10秒前
肆万八千发布了新的文献求助10
11秒前
11秒前
英俊的铭应助拖拖拖拖拖采纳,获得10
13秒前
14秒前
16秒前
Zoe完成签到,获得积分10
16秒前
科研通AI6.2应助阿梨采纳,获得10
16秒前
16秒前
871004188完成签到,获得积分10
17秒前
18秒前
CNuo发布了新的文献求助10
19秒前
20秒前
xupei0606发布了新的文献求助10
20秒前
BinSir完成签到 ,获得积分10
21秒前
NexusExplorer应助巯基乙醇采纳,获得10
21秒前
思源应助kai采纳,获得10
21秒前
22秒前
阳光的樱完成签到,获得积分10
22秒前
22秒前
22秒前
23秒前
落后乐天发布了新的文献求助10
24秒前
嘟嘟嘟发布了新的文献求助10
26秒前
NatureScience完成签到,获得积分10
26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
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Introducing the Learning Sciences 600
Resiliency Scale for Adolescents--Chinese Version 600
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7322225
求助须知:如何正确求助?哪些是违规求助? 8937664
关于积分的说明 18948791
捐赠科研通 6980041
什么是DOI,文献DOI怎么找? 3214923
关于科研通互助平台的介绍 2382478
邀请新用户注册赠送积分活动 2194151