Molecular dynamics simulations of liquid nitrogen monoxide

作者
Cillian Cockrell,Kostya Trachenko,Thomas F. Headen,Alan K. Soper,Panagiotis Hadjidoukas,Georgia Katsidima,Sarantos Marinakis
出处
期刊:Journal of Molecular Liquids [Elsevier BV]
卷期号:437: 128434-128434
标识
DOI:10.1016/j.molliq.2025.128434
摘要

Molecular dynamics (MD) simulations have been employed to study the thermodynamics, microscopic structure, and dynamics of liquid nitrogen monoxide. Calculations were conducted at various temperatures ranging from 120 to 144 K and densities corresponding to the liquid coexistence density along the boiling line between 1.1 and 9 bar. Emphasis was placed on the study of dimerization and clustering. The self-diffusion coefficient was calculated using the mean-squared displacement, while the shear and bulk viscosities, as well as thermal conductivity were derived from the respective time-dependent correlation functions. Our calculations are compared with previous classical simulations and corresponding experimental measurements. The model successfully replicates specific nitric oxide properties, such as its microscopic structure and shear viscosity. A significant novel finding is the non-Arrhenius temperature dependence of the (NO) 2 diffusion coefficient, alongside the demonstration of a complex temperature dependence for thermal conductivity. • Molecular Dynamics (MD) simulations were conducted for the NO/N 2 O 4 system. • A classical fully atomic interaction potential was employed to model the system in the liquid phase. • The results for microscopic structure, shear viscosity, and thermal conductivity showed good agreement with previous experimental work. • Self-diffusion coefficients and bulk viscosity were also calculated, although no related experimental data are available for comparison. • These findings are crucial for advancing the understanding of NOx species in condensed matter.
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
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
tyu完成签到 ,获得积分10
1秒前
1秒前
JaneBing发布了新的文献求助10
1秒前
1秒前
1秒前
liang发布了新的文献求助10
2秒前
2秒前
deepermoon发布了新的文献求助10
3秒前
勿明发布了新的文献求助10
4秒前
4秒前
Farz发布了新的文献求助10
4秒前
多味花生完成签到,获得积分10
4秒前
5秒前
Ov5发布了新的文献求助10
5秒前
小二郎应助皮皮鲲er采纳,获得10
7秒前
钱都来发布了新的文献求助10
7秒前
多味花生发布了新的文献求助10
8秒前
忐忑的八宝粥完成签到,获得积分10
8秒前
9秒前
9秒前
9秒前
yyyyy发布了新的文献求助30
10秒前
10秒前
aajhajkahna应助优雅的砖头采纳,获得10
10秒前
华仔应助s申采纳,获得10
11秒前
11秒前
迷路冬卉发布了新的文献求助10
11秒前
12秒前
妞妞发布了新的文献求助10
12秒前
西风月完成签到,获得积分10
12秒前
Jasper应助橘子采纳,获得10
13秒前
撸撸大仙发布了新的文献求助10
14秒前
14秒前
zhoushuqi完成签到,获得积分10
14秒前
Akim应助文具盒采纳,获得10
15秒前
科研通AI6.2应助放学早采纳,获得10
15秒前
深情安青应助王学生采纳,获得10
15秒前
啊啊啊啊啊完成签到 ,获得积分10
15秒前
乐空思应助chengjiali采纳,获得200
15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
Principles of town planning: translating concepts to applications 1000
内視鏡的に摘除しえた十二指腸乳頭部腫瘍の2例 660
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Interpolation and Regression Models for the Chemical Engineer: Solving Numerical Problems 400
The Neuroscience of Language 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 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 7686923
求助须知:如何正确求助?哪些是违规求助? 9250039
关于积分的说明 19960761
捐赠科研通 7259914
什么是DOI,文献DOI怎么找? 3289681
关于科研通互助平台的介绍 2446618
邀请新用户注册赠送积分活动 2294198