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Article

Design and Optimization of NR-Based Stretchable Conductive Composites Filled with MoSi2 Nanoparticles and MWCNTs: Perspectives from Experimental Characterization and Molecular Dynamics Simulations

by
Ruifeng Jiang
1,
Yanbin Ma
1,
Zhuojun Fan
2,
Yongping Chen
1,
Tingting Zheng
3,
Rentong Yu
1,* and
Jianhe Liao
1,*
1
School of Materials Science and Engineering, Hainan University, Haikou 570228, China
2
School of Mathematics and Statistics, Hainan University, Haikou 570228, China
3
School of Science, Qiongtai Normal University, Haikou 571127, China
*
Authors to whom correspondence should be addressed.
Polymers 2024, 16(11), 1444; https://doi.org/10.3390/polym16111444
Submission received: 30 April 2024 / Revised: 15 May 2024 / Accepted: 17 May 2024 / Published: 21 May 2024
(This article belongs to the Special Issue Advances in Functional Polymer Nanocomposites)
Browse Figures
Versions Notes

Abstract

:
Stretchable conductive composites play a pivotal role in the development of personalized electronic devices, electronic skins, and artificial implant devices. This article explores the fabrication and characterization of stretchable composites based on natural rubber (NR) filled with molybdenum disilicide (MoSi2) nanoparticles and multi-walled carbon nanotubes (MWCNTs). Experimental characterization and molecular dynamics (MD) simulations are employed to investigate the static and dynamic properties of the composites, including morphology, glass transition temperature (Tg), electrical conductivity, and mechanical behavior. Results show that the addition of MoSi2 nanoparticles enhances the dispersion of MWCNTs within the NR matrix, optimizing the formation of a conductive network. Dynamic mechanical analysis (DMA) confirms the Tg reduction with the addition of MWCNTs and the influence of MoSi2 content on Tg. Mechanical testing reveals that the tensile strength increases with MoSi2 content, with an optimal ratio of 4:1 MoSi2:MWCNTs. Electrical conductivity measurements demonstrate that the MoSi2/MWCNTs/NR composites exhibit enhanced conductivity, reaching optimal values at specific filler ratios. MD simulations further support experimental findings, highlighting the role of MoSi2 in improving dispersion and mechanical properties. Overall, the study elucidates the synergistic effects of nanoparticles and nanotubes in enhancing the properties of stretchable conductive composites.

1. Introduction

Although traditional rigid electronic products dominate the consumer electronics market, over the past decade, stretchable electronics have become a crucial market segment, particularly for personalized electronic devices, electronic skins [1,2,3,4], artificial implant devices [5,6,7,8], lightweight mobile electronic devices [9,10,11], and so on. Stretchable conductive composites are typically fabricated via two methods [12]. The first entails embedding non-ductile conductive materials, such as metal wires, into an elastic matrix; these originally rigid materials will be designed into a buckled structure to obtain stretchability [13,14]. Alternatively, a thin conductive film consisting of metal, carbon nanotubes, or graphene can be deposited on an elastomer surface; electronic conductivity, stretchability, and transparency can be improved by this elastomer–film structure [15,16].
Second, conductive fillers can be introduced to the insulating elastic matrix to achieve nanocomposites. Nanoscale conductive fillers are typically classified into zero-dimensional nanoparticles [17,18], one-dimensional nanowires/nanotubes [19,20,21], and two-dimensional nanoflakes [22,23]. For the purpose of low production cost and outstanding mechanical properties, zero-dimensional nanoparticles, such as carbon black, Au nanoparticles, and Ag nanoparticles, have been adopted
Carbon nanotubes (CNTs) and silver nanowires are extensively employed in stretchable conductive composites, owing to their high aspect ratios [12,14,15]. However, the conductivity associated with percolation is highly strain-sensitive, declining sharply under high strain and then undermining their cycle stability. Nevertheless, nanoparticles can result in the integrity of the conductive network under high-strain conditions.
The selection of a suitable flexible substrate is crucial to fabricate stretchable conductive materials. Polydimethylsiloxane (PDMS) has been predominantly used as a substrate material for stretchable electronic devices, owing to its stable chemical properties, high thermal stability, optical transparency, and biocompatibility [24,25,26,27]. However, its inherent low surface energy reduces adhesion and interfacial bonding strength between conductive fillers and the PDMS matrix and also reduces elongation at break for PDMS. Consequently, the inter-phase of the composite would deteriorate under high strain or repeated stretching, having a negative effect on the performance of the stretchable electronic devices [28]. As a renewable bio-synthetic polymer in comparison to fossil resources, natural rubber (NR) agrees with the principle of eco-friendly and sustainable development. Moreover, its inherent chain flexibility and ultra-high molecular weight endow it with superior resilience under prolonged strain conditions [29,30,31,32]. In addition, the NR processing methodology facilitates the continuous production of large-area stretchable conductive films utilizing NR latex as the primary raw material.
Among the conductive fillers, carbon nanotubes, which are recognized as a novel carbon-based material, exhibit remarkable electrical and mechanical properties, characterized by a high aspect ratio and conductivity. Consequently, they facilitate the formation of a conductive network in the polymeric matrix composite. Notable enhancements in the electromagnetic shielding effectiveness and mechanical properties of polymer composites can be achieved with a marginal increase in the content of these carbon-based materials [33,34,35].
In general, carbon nanotubes can be synthesized via three different routines, i.e., electric arc discharge (Arc-Discharge) [36,37,38], laser ablation [39,40,41], and chemical vapor deposition (CVD) methods, and the microwave irradiation method [42,43,44,45,46]. Of them, the arc discharge method is characteristic of scaled production and cost-efficiency. Nevertheless, the raw CNTs necessitate further purification, and the CNTs are hard to be characterized explicitly. In contrast, high-level CNTs can be produced at room temperature by the laser ablation method. Raid et al. [39] reported the preparation of high-level CNTs without purification. However, CNTs cannot be synthesized on a large scale by this mean. Fortunately, high-grade CNTs can be achieved with the advantages of high efficiency, continuous production, and low production cost [47,48]. Nowadays, the CVD method has been widely approached in the laboratory and in industrial production [49]. In addition, as a novel and cost-efficient method to synthesize CNTs, microwave irradiation is advantageous, due to its ability to provide a rapid and uniform heating rate, which can be selectively directed to a specific area [42,43,44]. Meanwhile, rather than the majority of the existing methods, which is using carbon in the form of graphite, methane, ethylene, or acetylene as the starting material, microwave irradiation can provide a more plentiful choice of carbon sources, such as coal [45] and biochar [46].
Moreover, the incorporation of multidimensional fillers, including zero-dimensional nanoparticles and one-dimensional nanotubes, elicits a synergistic effect, further augmenting the mechanical and electrical properties of the composites [50,51,52]. Some conductive nanoparticles, such as Ag [53], Ni [54], and Cu [52], have been approached in many researches of stretchable conductive materials. However, metal filler will be corroded with oxygen on account of the high oxygen diffusion coefficient in the elastomer. molybdenum disilicide (MoSi2) exhibits an excellent high-temperature oxidation resistance and low electrical resistivity (about 15 μΩcm at room temperature) [55]. In addition, MoSi2 has been widely used to reinforced polymer composites. Zhang et al. [56] reported a carbon fiber/boron phenolic resin composite modified by MoSi2 and mica with high mechanical, thermal, and ablation properties.
Although some measurement methods, such as in-situ transmission electron microscopy (in-situ TEM) and atomic force microscope (AFM), can be employed to clearly observe the dynamic process of materials at the atomic scale, the stability of the sample during the testing process and the difficulty of ultrafast imaging at the nano-second scale limit the widespread application of these in-situ imaging technologies [57,58,59]. Fortunately, at an atomic scale, molecular dynamics (MD) simulations provide distinct advantages in investigating both static and dynamic properties of polymer composites, compared with conventional experimental approaches [60]. Moreover, micro-structure evolution can be revealed in detail. In this way, complex models and ideal well-dispersed systems can be created [61]. MD simulations facilitate visualization together with quantitative analysis in a dynamic process at the micro-scale. In the past 30 years, extensive research on polymer materials [62,63,64,65,66,67,68,69] and conductive composites [70,71,72,73] have been conducted using MD simulations, owing to the rapid development of computer technology. MD simulation can measure and statistically analyze the glass transition [62,63], mechanical properties [64,65], rheological properties [66,67], and microscopic dynamic structure [68,69] of polymers and their composite materials. In addition to the method mentioned above, the statistical conductive network model developed by Fang et al. [74] was adopted to calculate the change in conductive pathways in the tensile process of MD simulations in this research.
In this study, we focused on NR-based composites containing MoSi2 nanoparticles and multi-walled carbon nanotubes (MWCNTs) and studied the effects of nanoparticles/nanotubes on the properties of the composites through morphology analysis, glass transition temperature analysis, mechanical testing, and electrical conductivity testing. Moreover, coarse-grained MD (CGMD) simulations employing an all-atom force field fitting were conducted to construct six sets of models for different filler mass ratios (m(MoSi2):m(MWCNTs) = 5:0, 4:1, 3:2, 2:3, 1:4, 0:5). Subsequently, the glass transition temperature (Tg) and radial distribution function (RDF) were calculated. Simulated tensile testing was performed based on the state of equilibration, followed by an analysis of the conductive network change in the simulation of the tensile process.

2. Materials and Methods

2.1. Preparation of the NR Vulcanizates

NR with the grade V was supplied by the Jinfu Plant of Hainan Rubber Industry Group Co., Ltd., Haikou, China. The 97% multi-walled carbon nanotubes (MWCNTs) with an inner diameter of 3–5 nm, outer diameter of 8–15 nm, and specific surface area ≥ 250 m2/g and that were synthesized by the CVD method were purchased from Shenzhen Guosen Pilot Technology Co., Ltd., Shenzhen, China. MoSi2 with the size of 1000 nm was purchased from Suzhou Yuante New Material Co., Ltd., Suzhou, China. NR was masticated and then cured according to ISO 1658:2015 [75] and GB/T 15340-2008 [76]. The vulcanizates formulation is shown in Table S1. MoSi2 and MWCNTs were compounded as fillers to prepare the MoSi2/NR, MWCNTs/NR, and MoSi2/MWCNTs/NR composites. The conductive composites formulations are shown in Table S2. After mixing for 2–4 h at room temperature (about 25 °C), 4–6 g of the compound was taken and placed in a moving die rheometer for testing. The test temperature was 145 °C, and the test time was approximately 60 min. Finally, the vulcanization was performed using a flat vulcanization instrument. The vulcanization temperature was 145 °C, the vulcanization time was the optimum vulcanization time (t90), and the vulcanization template thickness was 2 mm. The thickness of the sample was kept at 2 mm.

2.2. Molecular Dynamics Simulations

All of the non-bonded interactions were modeled using the expanded truncated and shifted Lennard–Jones potential (LJ potential):
E = 4 ε σ r − Δ 12 − σ r − Δ 6 r < r c u t o f f + Δ 0 r ≥ r c u t o f f + Δ
where ε represents the pair interaction energy parameter; r represents the distance between each two interaction sites; ∆ accounts for the effect of the excluded volumes of different interaction sites, representing the rigid volume of coarse particles; and rcutoff represents the pair cut-off distance at which the LJ potential is truncated and shifted so that the energy is equal to zero at this distance.
The interactions between adjacent bonded beads and three consecutive beads were modeled using the harmonic potential formula and illustrated in Equations (2) and (3), respectively:
E b o n d = K b o n d r − r 0 2
E a n g l e = K a n g l e θ − θ 0 2
where r0 is the equilibrium bond distance, and Kbond and Kangle represent the strength factors.
The coarse-grained force field used for the MoSi2/MWCNTs/NR systems was attained using the VOTCA software (v2023) [77,78,79] based on the OPLS–AA force field [80] via the iterative Boltzmann inversion (IBI) [81]. The force field parameters are shown in Table 1, and the criterion to construct the coarse-grained model is presented in Table S3. The bead number of the polyisoprene (PI) chain for each system was 1000, the bead number of the MWCNTs chain was 159, and the mass ratio of MoSi2 and MWCNTs was based on the amount of the MoSi2/MWCNT components listed in Table S2.
All the MD simulations were conducted using the large-scale atomic/molecular massively parallel simulator (LAMMPS) software (lammps-8Feb2023) developed by Sandia National Laboratories [82]. Throughout the MD simulations, the following settings were used: the NPT ensemble was executed for all the systems, the velocity Verlet algorithm was employed to integrate the equations of motion with a time step of 0.001 τ, and the Nose–Hoover thermostat, as well as barostat and periodic boundary conditions, was used in all three directions.
In the balancing process, we used the method proposed by Auhl et al. [83] to model the well-equilibrated melts of long-chain polymers. The systems were run for 10,000 τ, with a time step of 0.001 τ, and P* = 1.0; T* was oscillated from 1.0 to 5.0.
After the balancing process, all the equilibrium structure data were copied into two groups: One was the trajectory data continuously simulated for 1000 τ with T* = 1.0 and P* = 1.0, including static and dynamic structural information in the equilibrium state. These trajectory data will be discussed in the interphase topology analysis. The other group, based on the free volume theory, started from a gradient cooling simulation process with a T* from 5.0 to 0.04 for 36,000 τ. The cooling process was divided into two parts: First, temperature was decreased from 5.0 to 1.0 in 25 loops, each loop consisting of a decreasing temperature process with 400 τ and a constant temperature process with 400 τ. Second, temperature was decreased from 1.0 to 0.04 in 32 loops, each loop consisting of a decreasing temperature process with 250 τ and a constant temperature process with 250 τ. As a result, the glass transition temperature (Tg) of each system was determined by identifying the temperature at which the specific volume changed from a rubber state to a glass state. The Tg was indicated by the highest point of the second derivative curve calculated from the temperature–volume curve.
Mechanical properties such as tensile stress were computed by applying uniaxial deformation via the SLLOD equations of motion [84]. The tensile strain rate was set to be 0.001/τ, which was believed to be sufficiently slow to approach the limiting behavior for the equilibrium deformation process. The volume of the simulation box was maintained at a constant during the deformation process.

2.3. Characterization

2.3.1. Static Mechanical Properties

According to GB/T 528-1998 [85], the stress–strain curves of the samples were measured using a tensile testing machine (AL-7000-SU2, Qingdao Kangping High-speed Railway Technology Co., Ltd., Qingdao, China) with a strain rate of 500 mm/min at 25 °C. The samples were prepared to be a standard dumbbell-shaped sheet.

2.3.2. Dynamic Thermomechanical Performance

Dynamic mechanical analysis (DMA; TA Q800, TA Instruments, New Castle, DE, USA) was performed to obtain the curve of tan δ as a function of temperature in a nitrogen atmosphere. DMA measurements were conducted at a heating rate of 3 °C/min and a frequency of 1 Hz. The temperature range was −100 °C–100 °C. In all cases, a preload of 0.01 N was applied.

2.3.3. Differential Scanning Calorimetry (DSC) Measurements

Tg was measured using a Q2000 (TA Instruments, New Castle, DE, USA) differential scanning calorimeter. Under the protection of a nitrogen atmosphere, the samples were heated from −85 °C to 25 °C at a ramp rate of 10 °C/min. The specific Tg was measured by the differentiation method.

2.3.4. Scanning Electron Microscopy (SEM)

The surface morphology of different NR-based composites also observed was observed with a ZEISS Sigma 300 scanning electron microscope (Oberkochen, Germany), which was made in Germany. The vulcanized rubber was cut into a thin sheet with uniform thickness and then adhered to the conductive rubber. After spraying gold, the morphologies of composites were observed with an acceleration voltage of 5 kV.

2.3.5. Conductivity Measurements

The resistance of composite films was measured using a digital multimeter (Tektronix DMM6500, Beaverton, OR, USA). Electrical conductivity was calculated according to the following equation:
σ = L S R
where L is the length of the test sample, S is the cross-sectional area of the sample, and R is the conductive resistance of the sample.

3. Results

3.1. Morphology of Different NR-Based Composites

Figure S1 shows the SEM image of pure filler, including MoSi2 and MWCNTs. Figure 1 shows the SEM image of the MWCNTs/NR system. When the MWCNT filler content ranged from 1 to 3 phr, a uniform dispersion within the NR matrix was achieved. However, when increasing the filler content, the agglomeration of MWCNTs can be observed. As a consequence, the uniform dispersion of MWCNTs in the NR matrix cannot be achieved, which would give rise to the deterioration of the mechanical properties of the MWCNTs/NR composite. Figure 2 depicts the SEM image of the nanoparticles/NR composites (MoSi2/NR), exhibiting a dispersion pattern of the fillers in the matrix, which is consistent with that of the MWCNT filler, as the added amount varies. Notably, at the filler content of 4 phr or 5 phr, nanoparticle aggregation can be observed. As shown in Figure 3, the addition of MoSi2 effectively enhanced the dispersion of MWCNTs while maintaining the total filler fraction. Particularly, at a MoSi2/MWCNTs ratio of 2:3, the filler dispersion within the NR matrix was optimized. This observation supports the synergistic effect of nanoparticles and nanotubes in promoting the formation of a conductive network within the matrix, thereby enhancing its electrical conductivity.
Furthermore, the radius distribution function (RDF) of the MoSi2/MWCNTs/NR system was calculated by means of MD and depicted in Figure 4. Figure 4a,b illustrates the dispersion of the two fillers (MoSi2 and MWCNTs), respectively. It can be found that the dispersion of fillers in the NR matrix was perfect, even without surface modification. Figure 4c,d displays the radius distribution between the MWCNTs/NR and MoSi2/NR, respectively. The first peak presented in the RDF results (r = 2.07 in Figure 4c, r = 4.5 in Figure 4d) both agreed with the ideal distance between NR and fillers based on force field parameters, indicating that a well-balance state was achieved.

3.2. Analysis of Glass Transition

Figure 5a illustrates the variation in Tg for the MWCNTs/NR system. Upon the addition of 2 to 3 phr of MWCNTs, a slight increase in Tg can be observed, relative to the Tg, which MWCNTs added up to 1 phr. However, the overall trend revealed a gradual decrease in Tg (from −53.53 °C to −54.2 °C) as the filler concentration increased. This phenomenon may be attributed to the hollow structure of MWCNTs, which provides additional free volume, enhancing the molecular chain mobility. Figure 5b depicts the Tg variation for the MoSi2/NR system. With increasing filler content, Tg underwent a slight decline, followed by an increasing trend, suggesting that a limited quantity of filler particles enhanced the chain segment mobility at low temperatures. In addition, as shown in Figure 5c, the incorporation of MoSi2 dominated the increasing trend of Tg in MoSi2/MWCNTs/NR systems. Hence, excessive MoSi2 content is adverse to keeping a low Tg in composites.
To further understand the reinforcement mechanism of the nanoparticles/nanotubes within the NR matrix, dynamic mechanical tests were conducted from −80 °C to 0 °C. Figure 6 illustrates the relationship of the loss angle tan δ and the fillers content in MWCNTs/NR, MoSi2NR, and MoSi2/MWCNTs/NR composites (Figure 6a, Figure 6b, and Figure 6c, respectively), with the temperature spanning from −80 °C to 0 °C. Notably, α transition temperature was found to be a decreasing trend with the increase in MWCNTs content, which agrees with the results of DSC, indicating a reduction in Tg, which agrees with the results of DSC. A similar trend was observed for the MoSi2/NR system, where the lowest Tg was observed for the composite containing 3 phr of MoSi2, followed by a continuous increase in Tg as the filler fraction increased to 5 phr. Within the MoSi2/MWCNTs/NR system, the addition of 1 phr of MoSi2 considerably increased Tg, which then decreased until the mass fraction of MoSi2 reached 3 phr. Subsequently, when the increase in the MoSi2 fraction reached 5 phr, Tg increased gradually. Moreover, as depicted in Figure 7, Tg variations measured for the MoSi2/MWCNTs/NR system measured via DMA closely aligned with those obtained from MD simulations, as indicated by the red dashed line. This concordance highlights the capability of MoSi2 to enhance system dispersion; however, excessive MoSi2 filler loading is not beneficial. The lowest Tg was achieved for the MoSi2/MWCNTs/NR system with an approximately 3 phr MoSi2 addition. To elucidate the influence of MoSi2/MWCNTs on Tg in depth, MD simulation was performed, and the Tgs of the composites are shown in Figure 7. By comparing the results of the simulation and DMA, a similar relationship between the mass fraction of fillers and Tg can be ascertained. Tg showed a rapid increase when MoSi2 attained 1 phr. Then, Tg continually decreased to the lowest point when MoSi2 added up to 3 phr. This phenomenon implies that the content of MoSi2 could dominate the change in Tg in MoSi2/MWCNTs/NR systems.

3.3. Mechanical Properties

The mechanical properties of the composites were evaluated using a universal tensile tester. Figure 8 illustrates the tear strength and tensile strength of the MoSi2/NR, the MWCNTs/NR, and the MoSi2/MWCNTs/NR systems. In Figure 8a, there is almost no enhancement of tear strength with just the incorporation of MoSi2 in composites, as depicted by the blue curve. Conversely, the MWCNTs/NR that included highly linear one-dimensional MWCNTs (orange curve) notably improved tear resistance; tear strength was remarkedly enhanced, especially when 2–3 phr of MWCNTs was added. Furthermore, when MWCNTs added up to a mass fraction of 5 phr, a downward trend was observed; it is possibly attributed to poor compatibility between the MWCNTs and NR. These characteristics can be observed in MoSi2/MWCNTs/NR systems. With the decrease in MWCNTs and increase in MoSi2, tear strength showed a continuous downward trend. Thus, MoSi2 has a negative influence on the tear strength of composites. MoSi2 has a negative influence on the tear strength of composites.
Figure 8b illustrates the variation in tensile strength. Although the MWCNTs/NR system demonstrated remarkable tensile resistance, displaying the best tensile strength performance at a mass fraction equal to 3 phr, its tensile strength was eventually surpassed by MoSi2 at higher mass fractions (4–5 phr). However, the MoSi2/MWCNTs/NR system exhibited a progressive increase in tensile strength, outperforming the former two systems at a mass fraction of 4 phr, possibly owing to synergistic effects. Spherical MoSi2 particles effectively inhibited the formation of cracks perpendicular to the tensile direction, enhancing the overall tensile strength of the composite.
The results of MD simulations further support the findings depicted in Figure 8. As shown in Figure 9, the mechanical properties of the MoSi2/MWCNTs/NR system obtained using MD simulations are presented with those of mechanical testing. The tensile strength increased with increasing MoSi2 filler quantities across the first five mass ratios (the m(MoSi2): m(MWCNTs) ratio equal to 0:5, 1:4, 2:3, 3:2, 4:1), yielding the best mechanical property when the ratio of the two reached 4:1. However, the tensile strength of the composite containing MoSi2/MWCNTs resulting from MD simulation was much higher than that measured by experimental tensile testing when the mass ratio of MoSi2/MWCNTs was 5:0. This can be explained by the fact that MD simulations are always performed in a small scale of time and space; in order to obtain simulation results in a limited computational time, the tensile simulation will be performed at a very high tensile rate. Compared with the experimental tensile rate, it may extend the increasing trend of the tensile strength in the MD simulation result. Furthermore, the simulation models of composites will have a more ideal structure than experimental composites. Thus, the tensile strength of the simulation was still increasing when the mass ratio of MoSi2/MWCNTs was 5:0.

3.4. Electrically Conducting Properties

Electrical conductivity serves as a key parameter that reflects materials’ ability to conduct electric current. The results of conductivity tests for all the systems are presented in Figure 10. As shown in Figure 10, the utilization of MWCNTs as conductive fillers increased the conductivity of MWCNTs/NR composites concomitant with filler content augmentation, indicating the formation of a conductive network structure within NR. With the incorporation of 3 phr of MWCNTs, the composite conductivity exceeded that of the matrix (control sample) by 6 orders of magnitude, indicating that the 2–3 phr filler content met with the formation of the three-dimensional conductive network, i.e., the 2–3 phr filler was higher than the percolation threshold in the NR-based composite.
By altering the filler composition, a blend of zero-dimensional nanoparticles and one-dimensional nanotubes was incorporated into the NR matrix. At a 5 phr MWCNTs content, MWCNTs/NR composites exhibited a conductivity of 2.67 × 10−2 S/m. Interestingly, for the MoSi2/MWCNTs/NR composites, the conductivity exhibited a slight increase after the addition of 1 phr of MoSi2 (i.e., with a MoSi2: MWCNTs mass ratio of 1:4), as depicted in Figure 10b. Furthermore, at a MoSi2: MWCNTs mass ratio of 2:3, high conductivity (1.05 × 10−2 S/m) was sustained, indicating that the introduction of an appropriate quantity of nanoparticles improves the dispersion of MWCNTs within the NR matrix, which facilitates the establishment of a relatively comprehensive free-electron transfer pathway and thus enhances material conductivity. Further, at a MoSi2: MWCNTs mass ratio of 2:3, the composite conductivity surpassed that of the MoSi2: MWCNTs mass ratio of 3:2 by 5 orders of magnitude, indicating that the percolation threshold of the MoSi2/MWCNTs/NR system occurs within the mass ratio range of 2:3 to 3:2. Furthermore, at a MoSi2: MWCNTs mass ratio of 1:4, MoSi2/MWCNTs/NR composites exhibited the highest conductivity.
According to the trajectory data derived during the stretching simulations, the number of conductive pathways along the stretching direction was calculated. The information of conductive pathways across different composite systems during stretching along the z-axis is shown in Figure 11. At zero strain, the conductive pathways of the MoSi2/MWCNTs/NR-5:0 and MoSi2/MWCNTs/NR-4:1 systems were insignificant (always 0). Upon reaching a CNT content of 2 phr, a substantial change in the number of conductive pathways was observed from approximately 0 to about 250. When the mass fraction of MWCNTs ranged from 2 phr to 3 phr, there was a significant increase in the conductive pathways number, implying that the percolation threshold of the MoSi2/MWCNTs/NR system under non-tensile conditions lies between 2 and 3 phr. Under tensile strain ranging from 0 to 300% along the z-axis, both the MoSi2/MWCNTs/NR-3:2 and MoSi2/MWCNTs/NR-1:4 systems exhibited an augmentation in the number of conductive pathways after stretching, followed by a plateau, indicative of the stretching-induced formation of conductive pathways within the system. At a strain of 50–100%, an obvious increase in the number of conductive pathways was observed in the MoSi2/MWCNTs/NR-2:3 system, followed by a subsequent decline in proximity to the number observed in the MoSi2/MWCNTs/NR-1:4 system.
This phenomenon may be ascribed to the fact that the 2:3 filler mass ratio of the MoSi2/MWCNTs was near the value of the percolation threshold of the composite system. In this sense, minor disturbances can amplify the formation process of the conductive network, remarkably increasing the number of conductive pathways. Furthermore, the pure CNT system exhibited a downward trend in the number of conductive pathways after stretching, indicating the synergistic effects of nanoparticles and MWCNTs in the stretching-induced orientation for constructing conductive pathways.

4. Conclusions

In summary, the investigation into NR-based stretchable composites filled with MoSi2 nanoparticles and MWCNTs provides valuable insights into the design and optimization of advanced materials for flexible electronics. The combination of experimental characterization and molecular dynamics simulations offers a comprehensive understanding of the structure–property relationships in these composites. A comparison of performance with other similar conductive composite is indicated in Table 2.
The morphological analysis reveals the importance of achieving uniform dispersion of fillers within the polymer matrix for optimal mechanical and electrical performance. Both MoSi2 nanoparticles and MWCNTs contribute synergistically to the formation of a conductive network, enhancing electrical conductivity and mechanical strength. However, careful consideration of filler content and ratio is necessary to avoid detrimental effects, such as agglomeration and decreased tear strength.
Furthermore, dynamic mechanical analysis and molecular dynamics simulations elucidate the impact of filler composition on the glass transition temperature, highlighting the role of MoSi2 in modulating the polymer chain mobility and enhancing the overall mechanical properties of the composites.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/polym16111444/s1, Table S1. Rubber compound formulation; Table S2. Natural-rubber-based composite compound formulation; Table S3. All-atom and coarse-grain models of PI and CNT; Figure S1. SEM images of MoSi2 (a) and MWCNTs (b).

Author Contributions

Conceptualization, J.L., Y.C. and R.Y.; methodology, Y.C. and R.J.; software, R.J. and Z.F.; validation, R.J. and Y.M.; formal analysis, R.J.; investigation, R.J., Y.M. and Z.F.; data curation, R.J., Z.F. and T.Z.; writing—original draft preparation, R.J. and T.Z.; writing—review and editing, J.L., R.Y. and Y.C.; visualization, R.J.; supervision, J.L., R.Y. and Y.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key Research and Development Program of China (grant number: 2022YFD230120201), National Natural Science Foundation of China (grant number: 52063013), Foundation of Guangdong Provincial Key Laboratory of Natural Rubber Processing, P.R. China (grant number: 2019B121203004), and The Key Research and Development Project of Hainan Province (grant number: ZDYF2022XDNY209).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Feng, Q.; Wen, Y.; Sun, F.; Xie, Z.; Zhang, M.; Wang, Y.; Liu, D.; Cheng, Z.; Mao, Y.; Zhao, C. Recent Advances in Self-Powered Electronic Skin Based on Triboelectric Nanogenerators. Energies 2024, 17, 638. [Google Scholar] [CrossRef]
  2. Yokota, T.; Zalar, P.; Kaltenbrunner, M.; Jinno, H.; Matsuhisa, N.; Kitanosako, H.; Tachibana, Y.; Yukita, W.; Koizumi, M.; Someya, T. Ultraflexible organic photonic skin. Sci. Adv. 2016, 2, e1501856. [Google Scholar] [CrossRef] [PubMed]
  3. Cao, Y.; Tan, Y.J.; Li, S.; Lee, W.W.; Guo, H.; Cai, Y.; Wang, C.; Tee, B.C.-K. Self-healing electronic skins for aquatic environments. Nat. Electron. 2019, 2, 75–82. [Google Scholar] [CrossRef]
  4. Aragona, M.; Sifrim, A.; Malfait, M.; Song, Y.; Van Herck, J.; Dekoninck, S.; Gargouri, S.; Lapouge, G.; Swedlund, B.; Dubois, C. Mechanisms of stretch-mediated skin expansion at single-cell resolution. Nature 2020, 584, 268–273. [Google Scholar] [CrossRef] [PubMed]
  5. Kang, K.; Jung, H.; An, S.; Baac, H.W.; Shin, M.; Son, D. Skin-like transparent polymer-hydrogel hybrid pressure sensor with pyramid microstructures. Polymers 2021, 13, 3272. [Google Scholar] [CrossRef] [PubMed]
  6. Boutry, C.M.; Nguyen, A.; Lawal, Q.O.; Chortos, A.; Rondeau-Gagné, S.; Bao, Z. Pressure Sensors: A Sensitive and Biodegradable Pressure Sensor Array for Cardiovascular Monitoring (Adv. Mater. 43/2015). Adv. Mater. 2015, 27, 6953. [Google Scholar] [CrossRef]
  7. Ebrahimi Takalloo, S.; Fannir, A.; Nguyen, G.T.; Plesse, C.; Vidal, F.; Madden, J.D. Impermeable and compliant: SIBS as a promising encapsulant for ionically electroactive devices. Robotics 2019, 8, 60. [Google Scholar] [CrossRef]
  8. Ronca, A.; Rollo, G.; Cerruti, P.; Fei, G.; Gan, X.; Buonocore, G.G.; Lavorgna, M.; Xia, H.; Silvestre, C.; Ambrosio, L. Selective laser sintering fabricated thermoplastic polyurethane/graphene cellular structures with tailorable properties and high strain sensitivity. Appl. Sci. 2019, 9, 864. [Google Scholar] [CrossRef]
  9. Tehrani, Z.; Korochkina, T.; Govindarajan, S.; Thomas, D.; O’Mahony, J.; Kettle, J.; Claypole, T.; Gethin, D. Ultra-thin flexible screen printed rechargeable polymer battery for wearable electronic applications. Org. Electron. 2015, 26, 386–394. [Google Scholar] [CrossRef]
  10. Xu, X.; Luo, M.; He, P.; Yang, J. Washable and flexible screen printed graphene electrode on textiles for wearable healthcare monitoring. J. Phys. D Appl. Phys. 2020, 53, 125402. [Google Scholar] [CrossRef]
  11. Chang, W.-Y.; Fang, T.-H.; Lin, H.-J.; Shen, Y.-T.; Lin, Y.-C. A large area flexible array sensors using screen printing technology. J. Disp. Technol. 2009, 5, 178–183. [Google Scholar] [CrossRef]
  12. Wang, Y.; Zhu, C.; Pfattner, R.; Yan, H.; Jin, L.; Chen, S.; Molina-Lopez, F.; Lissel, F.; Liu, J.; Rabiah, N.I. A highly stretchable, transparent, and conductive polymer. Sci. Adv. 2017, 3, e1602076. [Google Scholar] [CrossRef] [PubMed]
  13. Webb, R.C.; Bonifas, A.P.; Behnaz, A.; Zhang, Y.; Yu, K.J.; Cheng, H.; Shi, M.; Bian, Z.; Liu, Z.; Kim, Y.-S.; et al. Ultrathin conformal devices for precise and continuous thermal characterization of human skin. Nat. Mater. 2013, 12, 938–944. [Google Scholar] [CrossRef] [PubMed]
  14. Yan, C.; Lee, P.S. Stretchable energy storage and conversion devices. Small 2014, 10, 3443–3460. [Google Scholar] [CrossRef] [PubMed]
  15. Lipomi, D.J.; Vosgueritchian, M.; Tee, B.C.; Hellstrom, S.L.; Lee, J.A.; Fox, C.H.; Bao, Z. Skin-like pressure and strain sensors based on transparent elastic films of carbon nanotubes. Nat. Nanotechnol. 2011, 6, 788–792. [Google Scholar] [CrossRef] [PubMed]
  16. Kim, K.S.; Zhao, Y.; Jang, H.; Lee, S.Y.; Kim, J.M.; Kim, K.S.; Ahn, J.-H.; Kim, P.; Choi, J.-Y.; Hong, B.H. Large-scale pattern growth of graphene films for stretchable transparent electrodes. Nature 2009, 457, 706–710. [Google Scholar] [CrossRef] [PubMed]
  17. Park, M.; Im, J.; Shin, M.; Min, Y.; Park, J.; Cho, H.; Park, S.; Shim, M.-B.; Jeon, S.; Chung, D.-Y. Highly stretchable electric circuits from a composite material of silver nanoparticles and elastomeric fibres. Nat. Nanotechnol. 2012, 7, 803–809. [Google Scholar] [CrossRef]
  18. Kim, Y.; Zhu, J.; Yeom, B.; Di Prima, M.; Su, X.; Kim, J.-G.; Yoo, S.J.; Uher, C.; Kotov, N.A. Stretchable nanoparticle conductors with self-organized conductive pathways. Nature 2013, 500, 59–63. [Google Scholar] [CrossRef] [PubMed]
  19. Weng, C.; Dai, Z.; Wang, G.; Liu, L.; Zhang, Z. Elastomer-free, stretchable, and conformable silver nanowire conductors enabled by three-dimensional buckled microstructures. ACS Appl. Mater. Interfaces 2019, 11, 6541–6549. [Google Scholar] [CrossRef]
  20. Hong, S.; Lee, H.; Lee, J.; Kwon, J.; Han, S.; Suh, Y.D.; Cho, H.; Shin, J.; Yeo, J.; Ko, S.H. Highly stretchable and transparent metal nanowire heater for wearable electronics applications. Adv. Mater. 2015, 27, 4744–4751. [Google Scholar] [CrossRef]
  21. Zhang, S.; Li, Y.; Tian, Q.; Liu, L.; Yao, W.; Chi, C.; Zeng, P.; Zhang, N.; Wu, W. Highly conductive, flexible and stretchable conductors based on fractal silver nanostructures. J. Mater. Chem. C 2018, 6, 3999–4006. [Google Scholar] [CrossRef]
  22. Zhu, L.; Wang, Y.; Mei, D.; Ding, W.; Jiang, C.; Lu, Y. Fully elastomeric fingerprint-shaped electronic skin based on tunable patterned graphene/silver nanocomposites. ACS Appl. Mater. Interfaces 2020, 12, 31725–31737. [Google Scholar] [CrossRef]
  23. Madhavan, R. Network crack-based high performance stretchable strain sensors for human activity and healthcare monitoring. New J. Chem. 2022, 46, 17596–17609. [Google Scholar] [CrossRef]
  24. Larmagnac, A.; Eggenberger, S.; Janossy, H.; Vörös, J. Stretchable electronics based on Ag-PDMS composites. Sci. Rep. 2014, 4, 7254. [Google Scholar] [CrossRef]
  25. Shao, J.; Yu, L.; Skov, A.L.; Daugaard, A.E. Highly stretchable conductive MWCNT–PDMS composite with self-enhanced conductivity. J. Mater. Chem. C 2020, 8, 13389–13395. [Google Scholar] [CrossRef]
  26. Chen, J.; Zhu, Y.; Jiang, W. A stretchable and transparent strain sensor based on sandwich-like PDMS/CNTs/PDMS composite containing an ultrathin conductive CNT layer. Compos. Sci. Technol. 2020, 186, 107938. [Google Scholar] [CrossRef]
  27. Wu, S.; Zhang, J.; Ladani, R.B.; Ravindran, A.R.; Mouritz, A.P.; Kinloch, A.J.; Wang, C.H. Novel electrically conductive porous PDMS/carbon nanofiber composites for deformable strain sensors and conductors. ACS Appl. Mater. Interfaces 2017, 9, 14207–14215. [Google Scholar] [CrossRef]
  28. Qi, D.; Zhang, K.; Tian, G.; Jiang, B.; Huang, Y. Stretchable electronics based on PDMS substrates. Adv. Mater. 2021, 33, 2003155. [Google Scholar] [CrossRef]
  29. Torres, G.B.; Hiranobe, C.T.; da Silva, E.A.; Cardim, G.P.; Cardim, H.P.; Cabrera, F.C.; Lozada, E.R.; Gutierrez-Aguilar, C.M.; Sánchez, J.C.; Carvalho, J.A.J. Eco-Friendly Natural Rubber–Jute Composites for the Footwear Industry. Polymers 2023, 15, 4183. [Google Scholar] [CrossRef] [PubMed]
  30. Pang, H.; Jiang, T.; Dai, J.; Yang, Y.; Bai, W. Experimental Study of the Mechanical Properties of Full-Scale Rubber Bearings at 23 °C, 0 °C, and −20 °C. Polymers 2024, 16, 903. [Google Scholar] [CrossRef] [PubMed]
  31. Intiya, W.; Hatthapanit, K.; Thaptong, P.; Sae-Oui, P. Application of Tamarind Shell as a Green Additive in Natural Rubber. Polymers 2024, 16, 493. [Google Scholar] [CrossRef]
  32. Candau, N.; Zimny, A.; Vives, E.; Maspoch, M.L. Elastocaloric waste/natural rubber materials with various crosslink densities. Polymers 2023, 15, 2566. [Google Scholar] [CrossRef]
  33. Gnanasekaran, K.; Grimaldi, C.; de With, G.; Friedrich, H. A unified view on nanoscale packing, connectivity, and conductivity of CNT networks. Adv. Funct. Mater. 2019, 29, 1807901. [Google Scholar] [CrossRef]
  34. Tamayo-Vegas, S.; Muhsan, A.; Liu, C.; Tarfaoui, M.; Lafdi, K. The effect of agglomeration on the electrical and mechanical properties of polymer matrix nanocomposites reinforced with carbon nanotubes. Polymers 2022, 14, 1842. [Google Scholar] [CrossRef]
  35. Mora, A.; Verma, P.; Kumar, S. Electrical conductivity of CNT/polymer composites: 3D printing, measurements and modeling. Compos. Part B Eng. 2020, 183, 107600. [Google Scholar] [CrossRef]
  36. Arora, N.; Sharma, N. Sustained arc temperature: Better marker for phase transformation of carbon black to multiwalled carbon nanotubes in arc discharge method. Mater. Res. Express 2016, 3, 105030. [Google Scholar] [CrossRef]
  37. Singh, K.; Chaudhary, S.; Venugopal, R.; Gaurav, A. Bulk synthesis of multi-walled carbon nanotubes by AC arc discharge method. Proc. Inst. Mech. Eng. Part N J. Nanomater. Nanoeng. Nanosyst. 2017, 231, 141–151. [Google Scholar] [CrossRef]
  38. Zhao, S.; Hong, R.; Luo, Z.; Lu, H.; Yan, B. Carbon nanostructures production by AC arc discharge plasma process at atmospheric pressure. J. Nanomater. 2011, 2011, 14. [Google Scholar] [CrossRef]
  39. Ismail, R.A.; Mohsin, M.H.; Ali, A.K.; Hassoon, K.I.; Erten-Ela, S. Preparation and characterization of carbon nanotubes by pulsed laser ablation in water for optoelectronic application. Phys. E Low-Dimens. Syst. Nanostruct. 2020, 119, 113997. [Google Scholar] [CrossRef]
  40. Mwafy, E.A.; Mostafa, A.M. Multi walled carbon nanotube decorated cadmium oxide nanoparticles via pulsed laser ablation in liquid media. Opt. Laser Technol. 2019, 111, 249–254. [Google Scholar] [CrossRef]
  41. Radhakrishnan, G.; Adams, P.; Bernstein, L. Room-temperature deposition of carbon nanomaterials by excimer laser ablation. Thin Solid Film. 2006, 515, 1142–1146. [Google Scholar] [CrossRef]
  42. Vivas-Castro, J.; Rueda-Morales, G.; Ortega-Cervantez, G.; Moreno-Ruiz, L.; Ortega-Aviles, M.; Ortiz-Lopez, J. Synthesis of carbon nanostructures by microwave irradiation. In Carbon Nanotubes—Synthesis, Characterization, Applications; Yellampalli, S., Ed.; In Tech Open: London, UK, 2011; pp. 47–60. [Google Scholar]
  43. Vasudev, H.; Singh, G.; Bansal, A.; Vardhan, S.; Thakur, L. Microwave heating and its applications in surface engineering: A review. Mater. Res. Express 2019, 6, 102001. [Google Scholar] [CrossRef]
  44. Shchegolkov, A.V.; Shchegolkov, A.V. Synthesis of Carbon Nanotubes Using Microwave Radiation: Technology, Properties, and Structure. Russ. J. Gen. Chem. 2022, 92, 1168–1172. [Google Scholar] [CrossRef]
  45. Reddy, B.R.; Ashok, I.; Vinu, R. Preparation of carbon nanostructures from medium and high ash Indian coals via microwave-assisted pyrolysis. Adv. Powder Technol. 2020, 31, 1229–1240. [Google Scholar] [CrossRef]
  46. Hidalgo, P.; Navia, R.; Hunter, R.; Camus, C.; Buschmann, A.; Echeverria, A. Carbon nanotube production from algal biochar using microwave irradiation technology. J. Anal. Appl. Pyrolysis 2023, 172, 106017. [Google Scholar] [CrossRef]
  47. Pant, M.; Singh, R.; Negi, P.; Tiwari, K.; Singh, Y. A comprehensive review on carbon nano-tube synthesis using chemical vapor deposition. Mater. Today Proc. 2021, 46, 11250–11253. [Google Scholar] [CrossRef]
  48. Hou, P.X.; Zhang, F.; Zhang, L.; Liu, C.; Cheng, H.M. Synthesis of carbon nanotubes by floating catalyst chemical vapor deposition and their applications. Adv. Funct. Mater. 2022, 32, 2108541. [Google Scholar] [CrossRef]
  49. Dong, L.; Park, J.G.; Leonhardt, B.E.; Zhang, S.; Liang, R. Continuous synthesis of double-walled carbon nanotubes with water-assisted floating catalyst chemical vapor deposition. Nanomaterials 2020, 10, 365. [Google Scholar] [CrossRef]
  50. Choi, S.; Han, S.I.; Kim, D.; Hyeon, T.; Kim, D.-H. High-performance stretchable conductive nanocomposites: Materials, processes, and device applications. Chem. Soc. Rev. 2019, 48, 1566–1595. [Google Scholar] [CrossRef]
  51. Park, M.; Park, J.; Jeong, U. Design of conductive composite elastomers for stretchable electronics. Nano Today 2014, 9, 244–260. [Google Scholar] [CrossRef]
  52. Shchegolkov, A.V.; Shchegolkov, A.V.; Zemtsova, N.V.; Vetcher, A.A.; Stanishevskiy, Y.M. Properties of Organosilicon Elastomers Modified with Multilayer Carbon Nanotubes and Metallic (Cu or Ni) Microparticles. Polymers 2024, 16, 774. [Google Scholar] [CrossRef]
  53. Kwon, C.; Seong, D.; Ha, J.; Chun, D.; Bae, J.H.; Yoon, K.; Lee, M.; Woo, J.; Won, C.; Lee, S. Self-Bondable and Stretchable Conductive Composite Fibers with Spatially Controlled Percolated Ag Nanoparticle Networks: Novel Integration Strategy for Wearable Electronics. Adv. Funct. Mater. 2020, 30, 2005447. [Google Scholar] [CrossRef]
  54. Leng, J.; Huang, W.; Lan, X.; Liu, Y.; Du, S. Significantly reducing electrical resistivity by forming conductive Ni chains in a polyurethane shape-memory polymer/carbon-black composite. Appl. Phys. Lett. 2008, 92, 204101. [Google Scholar] [CrossRef]
  55. Petrovic, J.J. MoSi2-based high-temperature structural silicides. Mrs Bull. 1993, 18, 35–41. [Google Scholar] [CrossRef]
  56. Zhang, S.; Zhang, J.; Yang, S.; Shi, M.; Li, J.; Shen, Q. Enhanced mechanical, thermal and ablation properties of carbon fiber/BPR composites modified by mica synergistic MoSi2 at 1500 °C. Ceram. Int. 2023, 49, 21213–21221. [Google Scholar] [CrossRef]
  57. LaGrange, T.; Campbell, G.H.; Reed, B.; Taheri, M.; Pesavento, J.B.; Kim, J.S.; Browning, N.D. Nanosecond time-resolved investigations using the in situ of dynamic transmission electron microscope (DTEM). Ultramicroscopy 2008, 108, 1441–1449. [Google Scholar] [CrossRef]
  58. Liu, X.H.; Liu, Y.; Kushima, A.; Zhang, S.; Zhu, T.; Li, J.; Huang, J.Y. In situ TEM experiments of electrochemical lithiation and delithiation of individual nanostructures. Adv. Energy Mater. 2012, 2, 722–741. [Google Scholar] [CrossRef]
  59. Zhang, Z.; Said, S.; Smith, K.; Jervis, R.; Howard, C.A.; Shearing, P.R.; Brett, D.J.; Miller, T.S. Characterizing batteries by in situ electrochemical atomic force microscopy: A critical review. Adv. Energy Mater. 2021, 11, 2101518. [Google Scholar] [CrossRef]
  60. Hollingsworth, S.A.; Dror, R.O. Molecular dynamics simulation for all. Neuron 2018, 99, 1129–1143. [Google Scholar] [CrossRef]
  61. Li, C.; Strachan, A. Molecular scale simulations on thermoset polymers: A review. J. Polym. Sci. Part B Polym. Phys. 2015, 53, 103–122. [Google Scholar] [CrossRef]
  62. Barrat, J.-L.; Baschnagel, J.; Lyulin, A. Molecular dynamics simulations of glassy polymers. Soft Matter 2010, 6, 3430–3446. [Google Scholar] [CrossRef]
  63. Yu, K.q.; Li, Z.s.; Sun, J. Polymer structures and glass transition: A molecular dynamics simulation study. Macromol. Theory Simul. 2001, 10, 624–633. [Google Scholar] [CrossRef]
  64. Frankland, S.; Harik, V.; Odegard, G.; Brenner, D.; Gates, T. The stress–strain behavior of polymer–nanotube composites from molecular dynamics simulation. Compos. Sci. Technol. 2003, 63, 1655–1661. [Google Scholar] [CrossRef]
  65. Nouri, N.; Ziaei-Rad, S. A molecular dynamics investigation on mechanical properties of cross-linked polymer networks. Macromolecules 2011, 44, 5481–5489. [Google Scholar] [CrossRef]
  66. Jabbarzadeh, A.; Atkinson, J.; Tanner, R. Effect of molecular shape on rheological properties in molecular dynamics simulation of star, H, comb, and linear polymer melts. Macromolecules 2003, 36, 5020–5031. [Google Scholar] [CrossRef]
  67. Kröger, M.; Hess, S. Rheological evidence for a dynamical crossover in polymer melts via nonequilibrium molecular dynamics. Phys. Rev. Lett. 2000, 85, 1128. [Google Scholar] [CrossRef]
  68. Bennemann, C.; Paul, W.; Binder, K.; Dünweg, B. Molecular-dynamics simulations of the thermal glass transition in polymer melts: α-relaxation behavior. Phys. Rev. E 1998, 57, 843. [Google Scholar] [CrossRef]
  69. Shen, J.; Lin, X.; Liu, J.; Li, X. Effects of cross-link density and distribution on static and dynamic properties of chemically cross-linked polymers. Macromolecules 2018, 52, 121–134. [Google Scholar] [CrossRef]
  70. Deng, H.; Skipa, T.; Zhang, R.; Lellinger, D.; Bilotti, E.; Alig, I.; Peijs, T. Effect of melting and crystallization on the conductive network in conductive polymer composites. Polymer 2009, 50, 3747–3754. [Google Scholar] [CrossRef]
  71. Gong, S.; Zhu, Z.; Meguid, S. Anisotropic electrical conductivity of polymer composites with aligned carbon nanotubes. Polymer 2015, 56, 498–506. [Google Scholar] [CrossRef]
  72. Zamani, S.M.M.; Behdinan, K. A molecular dynamics study of the mechanical and electrical properties of Polydimethylsiloxane-Ni conductive nanocomposites. Compos. Sci. Technol. 2020, 200, 108463. [Google Scholar] [CrossRef]
  73. Shahrokh, A.; Fakhrabadi, M.M.S. Effects of copper nanoparticles on elastic and thermal properties of conductive polymer nanocomposites. Mech. Mater. 2021, 160, 103958. [Google Scholar] [CrossRef]
  74. Fang, W.; Jang, H.W.; Leung, S.N. Evaluation and modelling of electrically conductive polymer nanocomposites with carbon nanotube networks. Compos. Part B Eng. 2015, 83, 184–193. [Google Scholar] [CrossRef]
  75. ISO 1658; Natural Rubber (NR)—Evaluation Procedure. ISO: Geneva, Switzerland, 2005.
  76. GB/T 15340; Rubber, Raw Natural and Raw Synthetic-Sampling and Further Preparative Procedures. China Standard of the People’s Republic of China: Beijing, China, 2008.
  77. Mashayak, S.; Jochum, M.N.; Koschke, K.; Aluru, N.; Rühle, V.; Junghans, C. Relative entropy and optimization-driven coarse-graining methods in VOTCA. PLoS ONE 2015, 10, e0131754. [Google Scholar] [CrossRef] [PubMed]
  78. Rühle, V.; Junghans, C. Hybrid Approaches to Coarse-Graining using the VOTCA Package: Liquid Hexane. Macromol. Theory Simul. 2011, 20, 472–477. [Google Scholar] [CrossRef]
  79. Ruhle, V.; Junghans, C.; Lukyanov, A.; Kremer, K.; Andrienko, D. Versatile object-oriented toolkit for coarse-graining applications. J. Chem. Theory Comput. 2009, 5, 3211–3223. [Google Scholar] [CrossRef] [PubMed]
  80. Kaminski, G.A.; Friesner, R.A.; Tirado-Rives, J.; Jorgensen, W.L. Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides. J. Phys. Chem. B 2001, 105, 6474–6487. [Google Scholar] [CrossRef]
  81. Tschöp, W.; Kremer, K.; Batoulis, J.; Bürger, T.; Hahn, O. Simulation of polymer melts. I. Coarse-graining procedure for polycarbonates. Acta Polym. 1998, 49, 61–74. [Google Scholar] [CrossRef]
  82. Plimpton, S. Fast parallel algorithms for short-range molecular dynamics. J. Comput. Phys. 1995, 117, 1–19. [Google Scholar] [CrossRef]
  83. Auhl, R.; Everaers, R.; Grest, G.S.; Kremer, K.; Plimpton, S.J. Equilibration of long chain polymer melts in computer simulations. J. Chem. Phys. 2003, 119, 12718–12728. [Google Scholar] [CrossRef]
  84. Evans, D.J.; Morriss, G.P. Statistical Mechanics of Nonequilbrium Liquids; ANU Press: Canberra, ACT, Australia, 2007. [Google Scholar]
  85. GB/T 528; Rubber, Vulcamized or Thermoplastic—Determination of Tensile Stress-Strain Properties. China Standard of the People’s Republic of China: Beijing, China, 1998.
  86. George, N.; Chandra, J.; Mathiazhagan, A.; Joseph, R. High performance natural rubber composites with conductive segregated network of multiwalled carbon nanotubes. Compos. Sci. Technol. 2015, 116, 33–40. [Google Scholar] [CrossRef]
  87. Krainoi, A.; Kummerlöwe, C.; Vennemann, N.; Nakaramontri, Y.; Pichaiyut, S.; Nakason, C. Effect of carbon nanotubes decorated with silver nanoparticles as hybrid filler on properties of natural rubber nanocomposites. J. Appl. Polym. Sci. 2019, 136, 47281. [Google Scholar] [CrossRef]
  88. Pazhooh, H.N.; Bagheri, R.; Adloo, A. Fabrication of semi-conductive natural rubber nanocomposites with low copper nanoparticle contents. Polymer 2017, 108, 135–145. [Google Scholar] [CrossRef]
  89. Salaeh, S.; Thitithammawong, A.; Salae, A. Highly enhanced electrical and mechanical properties of methyl methacrylate modified natural rubber filled with multiwalled carbon nanotubes. Polym. Test. 2020, 85, 106417. [Google Scholar] [CrossRef]
Polymers 16 01444 g001
Figure 1. SEM images of the MWCNTs/NR composites with different MWCNT loadings: (a) 0 phr, which is the control group; (b) 1 phr; (c) 2 phr; (d) 3 phr; (e) 4 phr; and (f) 5 phr.
Figure 1. SEM images of the MWCNTs/NR composites with different MWCNT loadings: (a) 0 phr, which is the control group; (b) 1 phr; (c) 2 phr; (d) 3 phr; (e) 4 phr; and (f) 5 phr.
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Polymers 16 01444 g002
Figure 2. SEM images of the MoSi2/NR composites: (a) 1 phr of MoSi2; (b) 2 phr of MoSi2; (c) 3 phr of MoSi2; (d) 4 phr of MoSi2; and (e) 5 phr of MoSi2.
Figure 2. SEM images of the MoSi2/NR composites: (a) 1 phr of MoSi2; (b) 2 phr of MoSi2; (c) 3 phr of MoSi2; (d) 4 phr of MoSi2; and (e) 5 phr of MoSi2.
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Polymers 16 01444 g003
Figure 3. SEM images of the MoSi2/MWCNTs/NR composites with MWCNTs/MoSi2 mass ratios: (a) 1:4; (b) 2:3; (c) 3:2; and (d) 4:1.
Figure 3. SEM images of the MoSi2/MWCNTs/NR composites with MWCNTs/MoSi2 mass ratios: (a) 1:4; (b) 2:3; (c) 3:2; and (d) 4:1.
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Polymers 16 01444 g004
Figure 4. Radial distribution function (RDF) of MoSi2/MWCNTs/NR systems between (a) MWCNT beads and MWCNT beads; (b) MoSi2 beads and MoSi2 beads; (c) MWCNT beads and NR beads; and (d) MoSi2 beads and NR beads.
Figure 4. Radial distribution function (RDF) of MoSi2/MWCNTs/NR systems between (a) MWCNT beads and MWCNT beads; (b) MoSi2 beads and MoSi2 beads; (c) MWCNT beads and NR beads; and (d) MoSi2 beads and NR beads.
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Polymers 16 01444 g005
Figure 5. DSC curves of the composites: (a) MWCNTs/NR; (b) MoSi2/NR; (c) MoSi2/MWCNTs/NR.
Figure 5. DSC curves of the composites: (a) MWCNTs/NR; (b) MoSi2/NR; (c) MoSi2/MWCNTs/NR.
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Polymers 16 01444 g006
Figure 6. DMA curves of composites: (a)MWCNTs/NR; (b) MoSi2/NR; (c) MoSi2/MWCNTs/NR.
Figure 6. DMA curves of composites: (a)MWCNTs/NR; (b) MoSi2/NR; (c) MoSi2/MWCNTs/NR.
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Polymers 16 01444 g007
Figure 7. Comparison of Tg values obtained from DMA measurements (blue solid line) and simulated (red dashed line) Tg values.
Figure 7. Comparison of Tg values obtained from DMA measurements (blue solid line) and simulated (red dashed line) Tg values.
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Polymers 16 01444 g008
Figure 8. Mechanical properties of the inorganic fillers/NR composites: (a) tear strength and (b) tensile strength of MoSi2/NR (blue solid line), MWCNTs/NR (orange solid line), and MoSi2/MWCNTs/NR (green dashed line).
Figure 8. Mechanical properties of the inorganic fillers/NR composites: (a) tear strength and (b) tensile strength of MoSi2/NR (blue solid line), MWCNTs/NR (orange solid line), and MoSi2/MWCNTs/NR (green dashed line).
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Polymers 16 01444 g009
Figure 9. Comparison of the tensile strengths obtained from experiments (blue line) and the simulated (red line) tensile strengths.
Figure 9. Comparison of the tensile strengths obtained from experiments (blue line) and the simulated (red line) tensile strengths.
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Polymers 16 01444 g010
Figure 10. (a) Conductivities of NR–MoSi2 (blue solid line), MWCNTs/NR (orange solid line), and MoSi2/MWCNTs/NR (green dashed line); (b) conductivity bar plots ofMWCNTs/NR (blue) and MoSi2/MWCNTs/NR (orange).
Figure 10. (a) Conductivities of NR–MoSi2 (blue solid line), MWCNTs/NR (orange solid line), and MoSi2/MWCNTs/NR (green dashed line); (b) conductivity bar plots ofMWCNTs/NR (blue) and MoSi2/MWCNTs/NR (orange).
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Polymers 16 01444 g011
Figure 11. Number of conducting pathways of the model with varied strains in the z-axis direction (simulation).
Figure 11. Number of conducting pathways of the model with varied strains in the z-axis direction (simulation).
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Table 1. Coarse-graining process and force field parameters for IBI calculations.
Table 1. Coarse-graining process and force field parameters for IBI calculations.
Atomic Force FieldCoarse-Graining Force Field
PIMWCNTsMoSi2PIMWCNTsMoSi2
ε
(kJ/mol)		0.759.890.84113.201.12
σ
(nm)		0.61.88250.4313.140.72
Kbond
(kJ/mol/nm2)		402936,353-193448,417-
r0
(nm)		0.4950.967-0.8251.612-
Kangle
(kJ/mol/rad2)		11.9639,201-9.852,268-
Θ0
(kJ/mol/degree2)		135180-135180-
Mass
(Ar)		68230450,480133.8742.35
∆---004
Table 2. Comparison with results of other authors about the NR-based conductive composites.
Table 2. Comparison with results of other authors about the NR-based conductive composites.
Conductivity (S/m)Tensile Strength (MPa)Ref.
MWCNTs/NR10−423.3[86]
CNT-Ag/NR10−5-[87]
Cu_NPs/NR1.4 × 10−212.79[88]
MWCNTs/MGNR10−217.4[89]
MoSi2/MWCNTs/NR3.18 × 10−216.42 this work
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MDPI and ACS Style

Jiang, R.; Ma, Y.; Fan, Z.; Chen, Y.; Zheng, T.; Yu, R.; Liao, J. Design and Optimization of NR-Based Stretchable Conductive Composites Filled with MoSi2 Nanoparticles and MWCNTs: Perspectives from Experimental Characterization and Molecular Dynamics Simulations. Polymers 2024, 16, 1444. https://doi.org/10.3390/polym16111444

AMA Style

Jiang R, Ma Y, Fan Z, Chen Y, Zheng T, Yu R, Liao J. Design and Optimization of NR-Based Stretchable Conductive Composites Filled with MoSi2 Nanoparticles and MWCNTs: Perspectives from Experimental Characterization and Molecular Dynamics Simulations. Polymers. 2024; 16(11):1444. https://doi.org/10.3390/polym16111444

Chicago/Turabian Style

Jiang, Ruifeng, Yanbin Ma, Zhuojun Fan, Yongping Chen, Tingting Zheng, Rentong Yu, and Jianhe Liao. 2024. "Design and Optimization of NR-Based Stretchable Conductive Composites Filled with MoSi2 Nanoparticles and MWCNTs: Perspectives from Experimental Characterization and Molecular Dynamics Simulations" Polymers 16, no. 11: 1444. https://doi.org/10.3390/polym16111444

APA Style

Jiang, R., Ma, Y., Fan, Z., Chen, Y., Zheng, T., Yu, R., & Liao, J. (2024). Design and Optimization of NR-Based Stretchable Conductive Composites Filled with MoSi2 Nanoparticles and MWCNTs: Perspectives from Experimental Characterization and Molecular Dynamics Simulations. Polymers, 16(11), 1444. https://doi.org/10.3390/polym16111444

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