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 [The Royal Society of Chemistry]
卷期号:16 (1): 237-248 被引量:4
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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
CCC发布了新的文献求助10
1秒前
1秒前
喻鞅完成签到,获得积分10
1秒前
1秒前
toto发布了新的文献求助10
2秒前
hsvysh发布了新的文献求助10
2秒前
4秒前
cyclone完成签到,获得积分10
4秒前
知有发布了新的文献求助10
5秒前
6秒前
黄晓杰2024完成签到 ,获得积分10
7秒前
8秒前
GGGG发布了新的文献求助10
9秒前
10秒前
英姑应助mio采纳,获得10
12秒前
ke研白完成签到,获得积分10
12秒前
小杨发布了新的文献求助10
14秒前
小二郎应助蜜CC采纳,获得10
14秒前
15秒前
优秀的叫兽完成签到,获得积分10
16秒前
自信谷冬完成签到 ,获得积分10
16秒前
16秒前
16秒前
18秒前
gyigvljhuo完成签到,获得积分10
18秒前
18秒前
Owen应助GGGG采纳,获得10
18秒前
田様应助包容绯采纳,获得10
19秒前
Jasper应助小杨采纳,获得10
20秒前
Akim应助科研通管家采纳,获得10
20秒前
852应助科研通管家采纳,获得10
20秒前
深情安青应助科研通管家采纳,获得10
21秒前
深情安青应助科研通管家采纳,获得30
21秒前
FashionBoy应助科研通管家采纳,获得10
21秒前
miamia77应助科研通管家采纳,获得10
21秒前
所所应助科研通管家采纳,获得10
21秒前
21秒前
hmh完成签到,获得积分10
21秒前
乐乐应助科研通管家采纳,获得10
21秒前
南音发布了新的文献求助10
21秒前
高分求助中
歯科矯正学 第7版(或第5版) 1004
Semiconductor Process Reliability in Practice 1000
Smart but Scattered: The Revolutionary Executive Skills Approach to Helping Kids Reach Their Potential (第二版) 1000
GROUP-THEORY AND POLARIZATION ALGEBRA 500
Mesopotamian divination texts : conversing with the gods : sources from the first millennium BCE 500
Days of Transition. The Parsi Death Rituals(2011) 500
The Heath Anthology of American Literature: Early Nineteenth Century 1800 - 1865 Vol. B 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3233820
求助须知:如何正确求助?哪些是违规求助? 2880284
关于积分的说明 8214616
捐赠科研通 2547734
什么是DOI,文献DOI怎么找? 1377175
科研通“疑难数据库(出版商)”最低求助积分说明 647789
邀请新用户注册赠送积分活动 623197