Synergistic influence of hydrophobic and hydrophilic ends on the primary dielectric relaxation rate of methanol

Zhu Jian-Zhuo; Cao Jia-Yi; Yang Sen; Zhang Qian; Cao Xiao-Yu; Ma Ying; Duan Xiang-Yi; Feng Shi-Dong

doi:10.7498/aps.73.20241261

Abstract

The primary dielectric relaxation process of monoalcohols typically exhibits characteristic Debye behavior, and the factors influencing its rate have become a research focus in recent years. It is generally believed that the hydrophilic end (i.e. the hydroxyl group) of alcohol molecule plays a major role in the primary dielectric relaxation process through a hydrogen bonding network, while the hydrophobic end mainly exerts an indirect effect by influencing the formation of intermolecular hydrogen bonds. In this work, the factors influencing the primary dielectric relaxation process of methanol are systematically investigated by using molecular dynamics simulations. Studying methanol, a simplest alcohol molecule, can provide insights into the common characteristics of monohydroxy alcohols and even alcohols in general. The well-known “wait-and-switch” model currently emphasizes the influence of hydrogen bond partner concentration on the primary dielectric relaxation rate of the system. In this work, we systematically investigate the factors influencing the primary dielectric relaxation rate of methanol by adjusting the O—H bond length (d_OH), the C—O bond length (d_CO), and the methyl diameter (σ_methyl) of methanol molecules, respectively, and significantly extend the “wait-and-switch” model. 1) By adjusting d_OH, we find that stronger total hydrogen bond energy (U_HB) in the system can enhance the correlation of molecular motion, slow down the reorientation rate of molecules and, consequently, the primary dielectric relaxation process of the system. 2) By adjusting d_CO, we discover that a longer hydrophobic end not only slows down the primary dielectric relaxation process by stabilizing the intermolecular hydrogen bond network but also directly reduces the rate of this process. 3) By adjusting σ_methyl, we find that an excessively small σ_methyl is detrimental to the stability of the hydrogen bond network, while an excessively large σ_methyl hinders thehydrogen bonds from forming. Both of these situations will have a negative influence on the correlation of molecular motion. When σ_methyl is at a moderate level, the main dielectric relaxation process of the system is the slowest. Ultimately, it is found that factors such as U_HB and related motion volume (V_CM), as well as the concentration of hydrogen bond partners in the system, collectively constitute the key factors affecting the primary dielectric relaxation rate of the system. Our results can reasonably explain experimental phenomena that the original “wait-and-switch” model cannot explain. This study contributes to a more in-depth understanding of the relaxation processes of alcohol molecules and their physical origins.

Keywords:

Authors and contacts

1.
Key Laboratory for Microstructural Material Physics of Hebei Province, School of Science, Yanshan University, Qinhuangdao 066004, China
2.
Center for Advanced Structural Materials, State Key Laboratory of Metastable Materials Science and Technology, Yanshan University, Qinhuangdao 066004, China

Corresponding author: Zhu Jian-Zhuo, zhujz@ysu.edu.cn ; Feng Shi-Dong, shidongfeng@ysu.edu.cn

Funds: Project supported by the National Natural Science Foundation of China (Grant No. 52271154) and the Central Guidance Fund for Local Science and Technology Development of Hebei Province, China (Grant No. 246Z1505G).

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References

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图 1 不同d_OH下体系的介电损耗谱, 蓝色曲线为采用原始TraPPE-UA力场仿真得到的介电损耗谱, 橙色虚线为使用(1)式对其进行拟合的结果, 其中$ {\tau _1} $= 41.5 ps, $ \alpha $= 0.9946, $ {\tau _{2}} $= 1.98 ps, $ {\tau _{3}} $= 0.352 ps

Figure 1. Dielectric loss spectra of the system with different d_OH, the blue curve represents the dielectric loss spectrum obtained from simulations using the original TRAPPE-UA force field, while the orange dashed line shows the fitting results using Eq. (1), where $ {\tau _1} $= 41.5 ps, $ \alpha $= 0.9946, $ {\tau _{2}} $= 1.98 ps, and $ {\tau _{3}} $= 0.352 ps.

DownLoad: Full-Size Img PowerPoint

图 2 (a) 不同d_OH系统中, 甲醇分子中氧原子和羟基氢原子围绕甲醇氧原子的径向分布函数; (b) 不同d_OH, d_CO和σ_methyl系统中的平均氢键能 (蓝色和黑色虚线分别表示采用原始TraPPE-UA力场参数得到的平均氢键能和体系B的平均氢键能)

Figure 2. (a) Radial distribution functions of oxygen and hydroxy hydrogen atoms of methanol around the methanol oxygen atoms in systems with different d_OH; (b) the average hydrogen bond energy for systems with varying d_OH, d_CO, and σ_methyl values (the blue and black dashed lines representing the average hydrogen bond energy derived from the original TraPPE-UA force field parameters and the average hydrogen bond energy of system B, respectively).

DownLoad: Full-Size Img PowerPoint

图 3 (a)不同d_OH体系中, 氢键寿命的分布; (b) 不同d_OH体系中, 甲醇分子的偶极取向自相关函数; (c) 不同d_OH体系中, 四点关联函数

Figure 3. (a) Distribution of hydrogen bond lifetimes of the systems with different d_OH; (b) dipole orientation autocorrelation function of methanol molecules of the systems with different d_OH; (c) time-dependent four-point susceptibilities of the systems with different d_OH

DownLoad: Full-Size Img PowerPoint

图 4 (a)不同d_CO体系中, 介电损耗谱; (b)不同d_CO体系中, 氢键寿命的分布; (c)不同d_CO体系中, 甲醇分子的偶极取向自相关函数; (d)不同d_CO体系中, 四点关联函数

Figure 4. (a) Dielectric loss spectra of the system at different d_CO values; (b) distribution of hydrogen bond lifetimes of the system at different d_CO values; (c) dipole orientation self-correlation function of methanol molecules of the system at different d_CO values; (d) time-dependent four-point susceptibilities of the system at different d_CO values.

DownLoad: Full-Size Img PowerPoint

图 5 (a)不同σ_methyl体系的介电损耗谱; (b)不同σ_methyl体系氢键寿命的分布, 插图为σ_methyl为0.325 nm和0.375 nm时氢键寿命的分布; (c)不同σ_methyl体系, 甲醇分子的偶极取向自相关函数; (d)不同σ_methyl体系, 四点关联函数

Figure 5. (a) Dielectric loss spectra of the system at different σ_methyl values; (b) distribution of hydrogen bond lifetimes of the system at different σ_methyl values, the inset shows the distribution of hydrogen bond lifetimes at σ_methyl values of 0.325 nm and 0.375 nm; (c) dipole orientation self-correlation function of methanol molecules of the system at different σ_methyl values; (d) time-dependent four-point susceptibilities of the system at different σ_methyl values.

DownLoad: Full-Size Img PowerPoint

表 1 不同d_OH值体系中N_HB, N_pair和N_chain的值

Table 1. Values of N_HB, N_pair, and N_chain for the systems with varying d_OH values.

d_OH/nm N_HB N_pair N_chain

0.0800 1.31 1.76 6.13
0.0850 1.58 1.94 11.96
0.0900 1.80 2.05 28.21
0.0945 1.91 2.08 70.91
0.0960 1.94 2.08 98.67

DownLoad: CSV

表 2 不同d_CO体系中N_HB, N_pair和N_chain的值

Table 2. Values of N_HB, N_pair, and N_chain for the systems with varying d_CO values.

d_CO/nm N_HB N_pair N_chain

0.100 1.74 2.12 16.67
0.122 1.86 2.10 37.28
0.143 1.91 2.08 70.91
0.170 1.94 2.06 128.64

DownLoad: CSV

表 3 不同σ_methyl体系中N_HB, N_pair和N_chain的值

Table 3. Values of N_HB, N_pair, and N_chain for the systems with varying σ_methyl values.

σ_methyl/nm N_HB N_pair N_chain

0.225 1.87 3.81 63.34

0.275 1.90 2.82 81.65

0.325 1.92 2.29 96.77

0.375 1.91 2.08 70.91

0.425 1.82 1.95 23.69

0.475 1.41 1.62 4.94

DownLoad: CSV

map

[1]	Rafikul Islam M, Rehan Alam M, Rayhan U, Khan F, Aldossari S A, Mohammad Wabaidur S, Rana S, Anamul Hoque M 2024 J. Mol. Liq. 393 123621 Google Scholar
[2]	Chen B L, Liu K, Wang L, Zhang X X, Qu K G, Kong Y X, Liu M 2022 J. Chem. Eng. Data 67 3414 Google Scholar
[3]	Jia W, Sutanto I R, Ndiaye M, Keppler J K, van der Goot A J 2022 Food Struct. 33 100274 Google Scholar
[4]	Moraveji M K, Sajjadi B, Davarnejad R 2011 Chem. Eng. Technol. 34 465 Google Scholar
[5]	杨静, 韩晓静, 刘冬雪, 石标, 王鹏阳, 许盛之, 赵颖, 张晓丹 2024 73 158401 Google Scholar Yang J, Han X J, Liu D X, Shi B, Wang P Y, Xu S Z, Zhao Y, Zhang X D 2024 Acta Phys. Sin. 73 158401 Google Scholar
[6]	赵振越, 张晓丹, 王奉友, 姜元建, 杜建, 高海波, 赵颖, 刘彩池 2014 63 136802 Google Scholar Zhao Z Y, Zhang X D, Wang F Y, Jiang Y J, Du J, Gao H B, Zhao Y, Liu C C 2014 Acta Phys. Sin. 63 136802 Google Scholar
[7]	赵兴宇, 王丽娜, 韩宏博, 尚洁莹 2024 73 147701 Google Scholar Zhao X Y, Wang L N, Han H B, Shang J Y 2024 Acta Phys. Sin. 73 147701 Google Scholar
[8]	王丽娜, 赵兴宇, 尚洁莹, 周恒为 2023 72 037701 Google Scholar Wang L N, Zhao X Y, Shang J Y, Zhou H W 2023 Acta Phys. Sin. 72 037701 Google Scholar
[9]	Sato T, Buchner R 2003 J. Chem. Phys. 118 4606 Google Scholar
[10]	Sato T, Buchner R 2004 J. Phys. Chem. A 108 5007 Google Scholar
[11]	Sato T, Buchner R 2005 J. Mol. Liq. 117 23 Google Scholar
[12]	Kaatze U, Behrends R, Pottel R 2002 J. Non-Cryst. Solids. 305 19 Google Scholar
[13]	Petong P, Pottel R, Kaatze U 1999 J. Phys. Chem. A 103 6114 Google Scholar
[14]	Cardona J, Sweatman M B, Lue L 2018 J. Phys. Chem. B 122 1505 Google Scholar
[15]	Li X, Chen Z M, Gao Y Q, Tu W K, Wang L M 2015 Front. Mater. 2 41 Google Scholar
[16]	Xu D, Feng S, Wang J Q, Wang L M, Richert R 2020 J. Phys. Chem. Lett. 11 5792 Google Scholar
[17]	Patil S, Sun R, Cheng S, Cheng S 2023 Phys. Rev. Lett. 130 098201 Google Scholar
[18]	Pabst F, Helbling A, Gabriel J, Weigl P, Blochowicz T 2020 Phys. Rev. E 102 010606(R Google Scholar
[19]	Gainaru C, Meier R, Schildmann S, Lederle C, Hiller W, Rössler E A, Böhmer R 2010 Phys. Rev. Lett. 105 258303 Google Scholar
[20]	Gabriel J, Pabst F, Helbling A, Böhmer T, Blochowicz T 2018 Phys. Rev. Lett. 121 035501 Google Scholar
[21]	Koperwas K, Paluch M 2022 Phys. Rev. Lett. 129 025501 Google Scholar
[22]	Fragiadakis D, Roland C M, Casalini R 2010 J. Chem. Phys. 132 144505 Google Scholar
[23]	Soszka N, Hachuła B, Tarnacka M, Kaminska E, Pawlus S, Kaminski K, Paluch M 2021 J. Phys. Chem. B 125 2960 Google Scholar
[24]	Hecksher T 2016 J. Chem. Phys. 144 161103 Google Scholar
[25]	Jurkiewicz K, Kołodziej S, Hachuła B, Grzybowska K, Musiał M, Grelska J, Bielas R, Talik A, Pawlus S, Kamiński K, Paluch M 2020 J. Mol. Liq. 319 114084 Google Scholar
[26]	Kalinovskaya O E, Vij J K, Johari G P 2001 J. Phys. Chem. A 105 5061 Google Scholar
[27]	Zhang N, Li W Z, Chen C, Zuo J G, Weng L D 2013 Mol. Phys. 111 939 Google Scholar
[28]	Zhang N, Shen Z L, Chen C, He G H, Hao C 2015 J. Mol. Liq. 203 90 Google Scholar
[29]	Hiejima Y, Kajihara Y, Kohno H, Yao M 2001 J. Phys. : Condens. Matter 13 10307 Google Scholar
[30]	Stubbs J M, Potoff J J, Siepmann J I 2004 J. Phys. Chem. B 108 17596 Google Scholar
[31]	Chen B, Potoff J J, Siepmann J I 2001 J. Phys. Chem. B 105 3093 Google Scholar
[32]	Wu Y, Tepper H L, Voth G A 2006 J. Chem. Phys. 124 024503 Google Scholar
[33]	Abraham M J, Murtola T, Schulz R, Páll S, Smith J C, Hess B, Lindahl E 2015 SoftwareX 1-2 19 Google Scholar
[34]	Hoover W G 1985 Phys. Rev. A 31 1695 Google Scholar
[35]	Nosé S, Klein M L 1983 Mol. Phys. 50 1055 Google Scholar
[36]	Darden T, York D, Pedersen L 1993 J. Chem. Phys. 98 10089 Google Scholar
[37]	Carlson S, Brünig F N, Loche P, Bonthuis D J, Netz R R 2020 J. Phys. Chem. A 124 5599 Google Scholar
[38]	Ono T, Horikawa K, Maeda Y, Ota M, Sato Y, Inomata H 2016 Fluid Phase Equilibr. 420 30 Google Scholar
[39]	Kalinovskaya O E, Vij J K 2000 J. Chem. Phys. 112 3262 Google Scholar

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