醇类有机物热传导的分子动力学模拟及微观机理研究

doi:10.11949/0438-1157.20200252

化工学报 ›› 2020, Vol. 71 ›› Issue (11): 5159-5168.DOI: 10.11949/0438-1157.20200252

醇类有机物热传导的分子动力学模拟及微观机理研究

刘万强(),杨帆(),袁华,张远达,易平贵,周虎()

湖南科技大学化学化工学院，理论有机化学与功能分子教育部重点实验室，湖南省高校QSAR/QSPR重点实验室，功能膜材料湖南省工程研究中心，湖南湘潭 411201

收稿日期:2020-03-12 修回日期:2020-06-08 出版日期:2020-11-05 发布日期:2020-11-05
通讯作者: 周虎
作者简介:刘万强(1971—)，男，博士，副教授，wanqiangliu@hnust.edu.cn|杨帆(1996—)，男，硕士研究生，13638425918@163.com
基金资助:
国家自然科学基金项目(21776067);湖南省教育厅科学研究项目(17A065);湖南省杰出青年基金项目(2020JJ2014);湖南省自然科学基金项目(2019JJ40078);2020年湖南省大学生创新创业训练计划项目(2930)

Molecular dynamics simulation and mechanism study on thermal conductivity of alcohols

Wanqiang LIU(),Fan YANG(),Hua YUAN,Yuanda ZHANG,Pinggui YI,Hu ZHOU()

Functional Film Materials Engineering Research Center of Hunan, Hunan Province College Key Laboratory of QSAR/QSPR, Key Laboratory of Theoretical Organic Chemistry and Function Molecule of Ministry of Education, School of Chemistry and Chemical Engineering, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China

Received:2020-03-12 Revised:2020-06-08 Online:2020-11-05 Published:2020-11-05
Contact: Hu ZHOU

摘要/Abstract

摘要：

传热是化工生产的基本问题之一，热导率是化工产品生产工艺设计中一类重要的热力学数据。通过非平衡分子动力学方法模拟了8种液态醇类有机物在不同温度下的导热过程。热导率计算值与实验值的平均相对偏差为3.77%。通过对热流的分解发现，分子动能、分子间库仑相互作用和分子内的二面角对醇类有机物的热传导影响较大。同时随着分子链增长，通过分子内相互作用进行的热传导逐渐占主导作用，表明醇类有机物的热能传输机理与分子结构有显著关系。此外，随着温度的升高，通过分子的动能、分子间库仑作用和分子内键角、键伸缩作用项传输的热流增大，表明温度对液态醇类有机物的热传导也有一定影响。本工作从微观分子间和分子内作用分析了液态醇类有机物结构和温度对热导率的影响，为液态有机物的热传导研究提供了微观依据。

关键词: 传热, 热导率, 导热机理, 分子动力学模拟, 醇

Abstract:

Heat transfer is one of the basic issues in chemical production, and thermal conductivity is an important thermodynamic data in the design of chemical product production processes. In this paper, nonequilibrium molecular dynamics methods are used to simulate the heat transfer of liquid alcohols at four different temperatures, and the thermal conductivity of the corresponding conditions is obtained. The average relative deviation between the calculated value and the experimental value was 3.77%. Through the decomposition of heat flux, it was found that molecular kinetic energy, Coulomb interaction and intramolecular dihedral angle contribute the most to the heat conduction of alcohols. At the same time, as the molecular volume increases, the thermal conduction pathway of the intramolecular interaction term gradually dominates, indicating that the thermal conduction mechanism of alcohols has a significant relationship with the molecular structure. In addition, as the temperature elevates, the heat flux transmitted through the molecular kinetic energy, intermolecular Coulomb interaction, and the intramolecular angle bending and bond stretching term increases, while the heat flux transmitted through the molecular potential energy decreases significantly. This work provides a microscopic explanation for the effects of the structure and temperature of liquid alcohols on thermal conductivity, and provides a micro foundation for the study of heat conduction of liquid alcohols.

Key words: heat transfer, thermal conductivity, thermal conduction mechanism, molecular dynamics simulation, alcohol

中图分类号:

O 639

刘万强,杨帆,袁华,张远达,易平贵,周虎. 醇类有机物热传导的分子动力学模拟及微观机理研究[J]. 化工学报, 2020, 71(11): 5159-5168.

Wanqiang LIU,Fan YANG,Hua YUAN,Yuanda ZHANG,Pinggui YI,Hu ZHOU. Molecular dynamics simulation and mechanism study on thermal conductivity of alcohols[J]. CIESC Journal, 2020, 71(11): 5159-5168.

图/表 8

参考文献 40

1	Vargaftik N B. Handbook of Thermal Conductivity of Liquids and Gases[M]. Boca Raton FL: CRC press, 1994.
2	Algaer E A, Müller-Plathe F. Molecular dynamics calculations of the thermal conductivity of molecular liquids, polymers, and carbon nanotubes[J]. Soft Materials, 2012, 10(1/2/3): 42-80.
3	Bao H, Chen J, Gu X, et al. A review of simulation methods in micro/nanoscale heat conduction[J]. ES Energy & Environment, 2018, 1: 16-55.
4	Assael M J, Antoniadis K D, Wakeham W A. Historical evolution of the transient hot-wire technique[J]. International Journal of Thermophysics, 2010, 31(6): 1051-1072.
5	Nagvekar M, Daubert T E. A group contribution method for liquid thermal conductivity[J]. Industrial & Engineering Chemistry Research, 1987, 26(7): 1362-1365.
6	Rodenbush C M, Viswanath D S, Hsieh F. A group contribution method for the prediction of thermal conductivity of liquids and its application to the prandtl number for vegetable oils[J]. Industrial & Engineering Chemistry Research, 1999, 38(11): 4513-4519.
7	Tsotsas E, Schluender E U. Numerical calculation of the thermal conductivity of two regular bidispersed beds of spherical particles[J]. Computers & Chemical Engineering, 1990, 14(9): 1031-1038.
8	Liu W, Lu H, Cao C, et al. An improved quantitative structure property relationship model for predicting thermal conductivity of liquid aliphatic alcohols[J]. Journal of Chemical and Engineering Data, 2018, 63(12): 4735-4740.
9	Lu H, Yang F, Liu W, et al. A robust model for estimating thermal conductivity of liquid alkyl halides[J]. SAR and QSAR in Environmental Research, 2020, 31(2): 73-85.
10	Ohara T. Contribution of intermolecular energy transfer to heat conduction in a simple liquid[J]. Journal of Chemical Physics, 1999, 111(21): 9667-9672.
11	Ohara T. Intermolecular energy transfer in liquid water and its contribution to heat conduction: a molecular dynamics study[J]. Journal of Chemical Physics, 1999, 111(14): 6492-6500.
12	Zhang M, Lussetti E, de Souza L E S, et al. Thermal conductivities of molecular liquids by reverse nonequilibrium molecular dynamics[J]. Journal of Physical Chemistry B, 2005, 109(31): 15060-15067.
13	李嘉辰, 俞斌, 王琦, 等. 分子模拟研究壳聚糖-氮化硼纳米管封装及输运阿霉素[J]. 化工学报, 2020, 71(1): 354-360.
	Li J C, Yu B, Wang Q, et al. Molecular simulation on doxorubicin encapsulation and transport by chitosan-boron nitride nanotubes[J]. CIESC Journal, 2020, 71(1): 354-360.
14	王韬, 刘向阳, 何茂刚. 离子液体[bmim][Tf2N]的分子动力学模拟[J]. 化工学报, 2019, 70: 258-264.
	Wang T, Liu X Y, He M G. Molecular dynamics simulation of ionic liquid [bmim][Tf2N][J]. CIESC Journal, 2019, 70: 258-264.
15	杨慧芳, 关海莲, 李平, 等. 煤颗粒燃烧过程氧化机理及有机氮转化的分子模拟: 以宁东红石湾煤为例[J]. 化工学报, 2020, 71(2): 799-810.
	Yang H F, Guan H L, Li P, et al. Molecular modeling of oxidation mechanism and organic nitrogen conversion in coal particle combustion: a case study on HSW coal of Ningdong[J]. CIESC Journal, 2020, 71(2): 799-810.
16	张博, 何依然, 刘迎春, 等. 异喹啉类生物碱和G-四链体结合的分子动力学研究[J]. 化工学报, 2020, 71(1): 344-353.
	Zhang B, He Y R, Liu Y C, et al. Molecular dynamics study of binding of isoquinoline alkaloids to G-quadruplex[J]. CIESC Journal, 2020, 71(1): 344-353.
17	邹瀚影, 冯妍卉, 邱琳, 等. 十八烷酸热传导机制的尺度效应研究[J]. 化工学报, 2019, 70: 155-160.
	Zou H Y, Feng Y H, Qiu L, et al. Size effect of heat conduction mechanism on stearic acid[J]. CIESC Journal, 2019, 70: 155-160.
18	Matsubara H, Kikugawa G, Bessho T, et al. Understanding the chain length dependence of thermal conductivity of liquid alcohols at 298 K on the basis of molecular-scale energy transfer[J]. Fluid Phase Equilibria, 2017, 441: 24-32.
19	Guevara-Carrion G, Nieto-Draghi C, Vrabec J, et al. Prediction of transport properties by molecular simulation: methanol and ethanol and their mixture[J]. Journal of Physical Chemistry B, 2008, 112(51): 16664-16674.
20	Petravic J. Thermal conductivity of ethanol[J]. Journal of Chemical Physics, 2005, 123: 174503.
21	Lin Y, Hsiao P, Chieng C. Constructing a force interaction model for thermal conductivity computation using molecular dynamics simulation: ethylene glycol as an example[J]. Journal of Chemical Physics, 2011, 134(15): 154509.
22	Fan Z, Pereira L F C, Wang H, et al. Force and heat current formulas for many-body potentials in molecular dynamics simulations with applications to thermal conductivity calculations[J]. Physical Review B, 2015, 92(9): 94301.
23	Torii D, Nakano T, Ohara T. Contribution of inter- and intramolecular energy transfers to heat conduction in liquids[J]. Journal of Chemical Physics, 2008, 128(4): 44504.
24	Matsubara H, Kikugawa G, Bessho T, et al. Effects of molecular structure on microscopic heat transport in chain polymer liquids[J]. Journal of Chemical Physics, 2015, 142(16): 164509.
25	Lv W, Henry A. Direct calculation of modal contributions to thermal conductivity via Green-Kubo modal analysis[J]. New Journal of Physics, 2016, 18(1): 13028.
26	Sun H, Mumby S J, Maple J R, et al. An ab initio CFF93 all-atom force field for polycarbonates[J]. Journal of the American Chemical Society, 1994, 116(7): 2978-2987.
27	Zhu W, Wang X, Xiao J, et al. Molecular dynamics simulations of AP/HMX composite with a modified force field[J]. Journal of Hazardous Materials, 2009, 167(1): 810-816.
28	Sun Y, Chen L, Cui L, et al. Molecular dynamics simulation of cross-linked epoxy resin and its interaction energy with graphene under two typical force fields[J]. Computational Materials Science, 2018, 143: 240-247.
29	Ikeshoji T, Hafskjold B. Non-equilibrium molecular dynamics calculation of heat conduction in liquid and through liquid-gas interface[J]. Molecular Physics, 1994, 81(2): 251-261.
30	Jund P, Jullien R. Molecular-dynamics calculation of the thermal conductivity of vitreous silica[J]. Physical Review B, 1999, 59(21): 13707.
31	Brown W M, Yamada M. Implementing molecular dynamics on hybrid high performance computers—three-body potentials[J]. Computer Physics Communications, 2013, 184(12): 2785-2793.
32	Brown W M, Kohlmeyer A, Plimpton S J, et al. Implementing molecular dynamics on hybrid high performance computers—particle-particle particle-mesh[J]. Computer Physics Communications, 2012, 183(3): 449-459.
33	Brown W M, Wang P, Plimpton S J, et al. Implementing molecular dynamics on hybrid high performance computers—short range forces[J]. Computer Physics Communications, 2011, 182(4): 898-911.
34	Nguyen T D. GPU-accelerated Tersoff potentials for massively parallel molecular dynamics simulations[J]. Computer Physics Communications, 2017, 212: 113-122.
35	Nguyen T D, Plimpton S J. Accelerating dissipative particle dynamics simulations for soft matter systems[J]. Computational Materials Science, 2015, 100: 173-180.
36	Plimpton S. Fast parallel algorithms for short-range molecular dynamics[J]. Journal of Computational Physics, 1995, 117(1): 1-19.
37	Boone P, Babaei H, Wilmer C E. Heat flux for many-body interactions: corrections to LAMMPS[J]. Journal of Chemical Theory and Computation, 2019, 15(10): 5579-5587.
38	Wirnsberger P, Frenkel D, Dellago C. An enhanced version of the heat exchange algorithm with excellent energy conservation properties[J]. Journal of Chemical Physics, 2015, 143(12): 124104.
39	Hoover W G. Canonical dynamics: equilibrium phase-space distributions[J]. Physical Review A, 1985, 31(3): 1695-1697.
40	Ohara T, Chia Yuan T, Torii D, et al. Heat conduction in chain polymer liquids: molecular dynamics study on the contributions of inter- and intramolecular energy transfer[J]. Journal of Chemical Physics, 2011, 135(3): 34507.

Method	Compound	Deviation/%	Ref.
NEMD	alcohols	18—30	[18]
BD-NEMD	methanol and ethanol	5	[19]
Green-Kubo	ethanol	10	[20]
Green-Kubo	ethylene glycol	20—30	[21]

Method	Compound	Deviation/%	Ref.
NEMD	alcohols	18—30	[18]
BD-NEMD	methanol and ethanol	5	[19]
Green-Kubo	ethanol	10	[20]
Green-Kubo	ethylene glycol	20—30	[21]

Compound	λ_273K/(W·m^-1·K^-1)			λ_288K/(W·m^-1·K^-1)			λ_298K/(W·m^-1·K^-1)			λ_323K/(W·m^-1·K^-1)
Compound	Cal.	Exp.	RD/%	Cal.	Exp.	RD/%	Cal.	Exp.	RD/%	Cal.	Exp.	RD/%
ethanol	0.172	0.175	-1.71	0.169	0.171	-1.17	0.170	0.168	1.19	0.167	0.162	3.09
propanol	0.163	0.162	0.62	0.159	0.158	0.63	0.163	0.156	4.49	0.150	0.151	-0.66
butanol	0.160	0.158	1.27	0.157	0.155	1.29	0.150	0.153	-1.96	0.149	0.148	0.67
pentanol	0.155	0.157	-1.27	0.152	0.154	-1.30	0.156	0.153	1.96	0.152	0.149	2.01
hexanol	0.164	0.159	3.14	0.151	0.156	-3.21	0.154	0.154	0.00	0.146	0.148	-1.35
heptanol	0.165	0.162	1.85	0.158	0.159	-0.63	0.150	0.157	-4.46	0.148	0.151	-1.99
octanol	0.166	0.166	0.00	0.170	0.162	4.94	0.159	0.160	-0.63	0.155	0.154	0.65
nonanol	0.160	0.166	-3.61	0.161	0.163	-1.23	0.161	0.161	0.00	0.155	0.155	0.00

Compound	λ_273K/(W·m^-1·K^-1)			λ_288K/(W·m^-1·K^-1)			λ_298K/(W·m^-1·K^-1)			λ_323K/(W·m^-1·K^-1)
Compound	Cal.	Exp.	RD/%	Cal.	Exp.	RD/%	Cal.	Exp.	RD/%	Cal.	Exp.	RD/%
ethanol	0.172	0.175	-1.71	0.169	0.171	-1.17	0.170	0.168	1.19	0.167	0.162	3.09
propanol	0.163	0.162	0.62	0.159	0.158	0.63	0.163	0.156	4.49	0.150	0.151	-0.66
butanol	0.160	0.158	1.27	0.157	0.155	1.29	0.150	0.153	-1.96	0.149	0.148	0.67
pentanol	0.155	0.157	-1.27	0.152	0.154	-1.30	0.156	0.153	1.96	0.152	0.149	2.01
hexanol	0.164	0.159	3.14	0.151	0.156	-3.21	0.154	0.154	0.00	0.146	0.148	-1.35
heptanol	0.165	0.162	1.85	0.158	0.159	-0.63	0.150	0.157	-4.46	0.148	0.151	-1.99
octanol	0.166	0.166	0.00	0.170	0.162	4.94	0.159	0.160	-0.63	0.155	0.154	0.65
nonanol	0.160	0.166	-3.61	0.161	0.163	-1.23	0.161	0.161	0.00	0.155	0.155	0.00

Compound	ρ_273K/(g?cm^-3)		ρ_288K/(g?cm^-3)		ρ_298K/(g?cm^-3)		ρ_323K/(g?cm^-3)
Compound	Exp.	Cal.	Exp.	Cal.	Exp.	Cal.	Exp.	Cal.
ethanol	0.808	0.751	0.795	0.741	0.786	0.722	0.763	0.706
propanol	0.822	0.755	0.809	0.744	0.800	0.736	0.778	0.709
butanol	0.826	0.763	0.814	0.745	0.806	0.747	0.785	0.713
pentanol	0.831	0.768	0.820	0.757	0.812	0.747	0.792	0.724
hexanol	0.834	0.772	0.823	0.757	0.816	0.749	0.798	0.727
heptanol	0.838	0.772	0.827	0.759	0.820	0.746	0.801	0.726
octanol	0.841	0.770	0.830	0.762	0.823	0.752	0.804	0.734
nonanol	0.841	0.769	0.831	0.762	0.825	0.751	0.808	0.738

醇类有机物热传导的分子动力学模拟及微观机理研究

Molecular dynamics simulation and mechanism study on thermal conductivity of alcohols

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Compound	J_str/ (MW·m^-2)	J_ang/ (MW·m^-2)	J_tor/ (MW·m^-2)	J_inv/ (MW·m^-2)	J_vdW/ (MW·m^-2)	J_Cl/ (MW·m^-2)	J_pot/ (MW·m^-2)	J_kin/ (MW·m^-2)
273 K
ethanol	82.35061	105.5749	173.2012	1.166184	93.33839	286.4405	371.678	248.0089
propanol	95.427	130.7635	196.4533	0.585375	93.64934	412.9896	140.9174	280.7405
butanol	102.2969	144.5943	230.6405	0.25144	90.01795	331.163	160.8052	295.7485
pentanol	107.868	154.3851	253.6832	0.000517	87.71279	291.5588	152.6921	307.3169
hexanol	111.1385	161.5822	272.2318	0.192211	85.97666	262.5442	149.1838	314.8754
heptanol	114.1706	166.809	285.5701	0.332879	83.79046	238.7217	143.6668	320.7745
octanol	116.1588	170.8392	295.6281	0.456438	81.58639	220.2334	138.452	324.2486
nonanol	118.2226	174.2786	304.655	0.546975	80.09264	204.8891	135.421	328.5367
288 K
ethanol	88.59901	113.6205	174.6725	1.23144	93.83133	267.6399	356.5573	267.6399
propanol	99.90495	136.3767	194.1579	0.605893	91.07394	417.0604	118.3188	294.1697
butanol	107.0843	150.4192	226.3646	0.262161	85.5488	333.7362	133.8917	309.7504
pentanol	113.2669	161.7038	250.8701	0.006098	83.09045	296.5954	125.7172	322.7532
hexanol	116.3273	168.5521	268.0233	0.19607	81.54108	265.5234	122.2882	329.8472
heptanol	119.7637	174.7064	281.0965	0.356169	79.75569	241.4785	116.8366	336.7934
octanol	118.6948	174.2466	293.9069	0.474525	80.82509	221.6068	128.2734	331.6131
nonanol	123.9406	182.1128	301.084	0.569318	77.058	207.7246	111.1315	344.7189
298 K
ethanol	87.98672	112.9572	168.2807	1.206443	88.32364	293.7441	331.1771	266.7173
propanol	102.5047	139.5892	192.5958	0.615713	89.51541	419.0179	105.4844	301.6295
butanol	110.7437	155.6268	226.0706	0.264945	86.09783	338.6185	121.7853	320.4123
pentanol	112.9239	160.9453	241.8836	0.004015	79.95448	323.2599	109.6565	323.2599
hexanol	119.3759	172.3581	265.5312	0.207462	79.42465	267.028	107.6302	338.3892
heptanol	122.6607	177.7654	278.0849	0.36209	76.12581	243.1349	100.1216	344.334
octanol	125.058	182.0887	289.8456	0.483914	75.27087	224.3338	99.52106	348.9841
nonanol	126.9109	186.5117	297.3773	0.587973	73.19684	208.9527	93.39459	354.1787
323 K
ethanol	94.44256	121.7495	164.777	1.270205	86.1226	304.3557	294.614	289.2095
propanol	109.4977	148.8176	187.5502	0.645945	83.78129	425.1214	64.5793	323.3033
butanol	117.2486	164.5488	218.7043	0.269378	78.09459	343.464	76.82576	340.5539
pentanol	123.3485	175.3366	242.1652	0.007284	75.84128	303.4792	71.65321	353.422
hexanol	128.1472	183.9092	258.5265	0.214408	72.87701	272.8254	63.01978	363.5166
heptanol	131.455	190.117	270.929	0.387389	69.7516	248.777	55.96572	370.4024
octanol	134.7473	195.9925	282.6226	0.526943	69.26389	230.4936	53.36009	377.35
nonanol	136.9088	199.7251	291.0947	0.631816	67.9927	214.095	51.09756	381.8325

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