Effect of graphene on the key electrical, optical, and magnetic properties of polymethylmethacrylate: a study based on molecular modeling

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Ernesto López-Chávez, Alberto Garcia-Quiroz, José Antonio Irán Díaz-Góngora, J. Antonio López-Barrera, José Alberto Mendoza-Espinoza, Yesica Antonia Peña-Castañeda, Fray de Landa Castillo-Alvarado
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引用次数: 0

Abstract

Context

In this work, a new polymeric structure was designed consisting of a nanometric sheet of graphene (G) and a polymethylmethacrylate (PMMA) repeat unit, which was designated as PMMA-G. Three degrees of polymerization of PMMA-G were considered: monomer (PMMA-G1), dimer (PMMA-G2), and trimer (PMMA-G3). The effect of incorporating a nanometric sheet of graphene into the molecular structure of PMMA on the modification of some of its main optical, magnetic, and electrical properties was investigated. Currently, the study presented here is of great relevance since various areas of technology require new materials with specific properties for the development of new devices. The results of our study reveal that the dielectric constant of PMMA is reduced when graphene is incorporated. However, a percentage increase of 14.48% in the refractive index of PMMA when graphene is inserted to form the nanocomposite is observed. It is found that the absolute value of molar magnetic susceptibility of PMMA increases considerably when reinforced with graphene. Finally, when reinforcing PMMA with graphene to obtain the PMMA-G nanocomposite, the electrical resistivity increases by almost an order of magnitude.

Methods

We used computational tools under Materials Studio (MS) software. We built a PMMA molecule with three degrees of polymerization, graphene sheet, and polymethylmethacrylate-graphene composite (PMMA-G) was built also with three degrees of polymerization using a concentration of 50% graphene over the PMMA polymer. For each structure, we used computational code DMol3 of MS, which is based on the Density Functional Theory, and the geometry optimization process was carried out to obtain the most stable structures. Finally, using the connectivity indices method together with topological properties of the molecular structures, implemented in Synthia computational code of MS software, we calculated the dielectric constant, magnetic susceptibility, refractive index, and electrical resistivity, for pure PMMA and PMMA-G structures for their three degrees of polymerization. The results were analyzed, and the changes in these properties were discussed in terms of the effect of an electric and magnetic field on the molecular structures of PMMA-G with respect to PMMA.

石墨烯对聚甲基丙烯酸甲酯关键电气、光学和磁学特性的影响:基于分子建模的研究
背景在这项研究中,我们设计了一种新的聚合物结构,它由纳米级石墨烯(G)薄片和聚甲基丙烯酸甲酯(PMMA)重复单元组成,命名为 PMMA-G。考虑了 PMMA-G 的三种聚合度:单体(PMMA-G1)、二聚体(PMMA-G2)和三聚体(PMMA-G3)。研究了在 PMMA 分子结构中加入纳米级石墨烯薄片对改变其某些主要光学、磁学和电学特性的影响。目前,由于各个技术领域都需要具有特定性能的新材料来开发新设备,因此本研究具有重要意义。我们的研究结果表明,加入石墨烯后,PMMA 的介电常数会降低。然而,当加入石墨烯形成纳米复合材料时,PMMA 的折射率增加了 14.48%。研究发现,用石墨烯增强 PMMA 时,其摩尔磁感应强度的绝对值会显著增加。最后,当用石墨烯增强 PMMA 以获得 PMMA-G 纳米复合材料时,电阻率几乎增加了一个数量级。我们构建了具有三种聚合度的 PMMA 分子、石墨烯薄片和聚甲基丙烯酸甲酯-石墨烯复合材料(PMMA-G),同样具有三种聚合度,石墨烯浓度为 PMMA 聚合物的 50%。对于每种结构,我们都使用了基于密度泛函理论的 MS 计算代码 DMol3,并进行了几何优化,以获得最稳定的结构。最后,我们利用 MS 软件 Synthia 计算代码实现的连接指数法和分子结构的拓扑特性,计算了纯 PMMA 和 PMMA-G 结构在三种聚合度下的介电常数、磁感应强度、折射率和电阻率。我们对结果进行了分析,并根据电场和磁场对 PMMA-G 分子结构的影响讨论了这些特性的变化。
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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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