Analysis on Microstructure-Property Linkages of Filled Rubber Using Machine Learning and Molecular Dynamics Simulations

A better understanding of the microstructure–property relationship can be achieved by sampling and analyzing a microstructure leading to a desired material property. During the simulation of filled rubber, this approach includes extracting common aggregates from a complex filler morphology consisting of hundreds of filler particles. However, a method for extracting a core structure that determines the rubber mechanical properties has not been established yet. In this study, we analyzed complex filler morphologies that generated extremely high stress using two machine learning techniques. First, filler morphology was quantified by persistent homology and then vectorized using persistence image as the input data. After that, a binary classification model involving logistic regression analysis was developed by training a dataset consisting of the vectorized morphology and stress-based class. The filler aggregates contributing to the desired mechanical properties were extracted based on the trained regression coefficients. Second, a convolutional neural network was employed to establish a classification model by training a dataset containing the imaged filler morphology and class. The aggregates strongly contributing to stress generation were extracted by a kernel. The aggregates extracted by both models were compared, and their shapes and distributions producing high stress levels were discussed. Finally, we confirmed the effects of the extracted aggregates on the mechanical property, namely the validity of the proposed method for extracting stress-contributing fillers, by performing coarse-grained molecular dynamics simulations.

Sulfur-Modified Carbon Nanotubes for the Development of Advanced Elastomeric Materials

The outstanding properties of carbon nanotubes (CNTs) present some limitations when introduced into rubber matrices, especially when these nano-particles are applied in high-performance tire tread compounds. Their tendency to agglomerate into bundles due to van der Waals interactions, the strong influence of CNT on the vulcanization process, and the adsorptive nature of filler-rubber interactions contribute to increase the energy dissipation phenomena on rubber-CNT compounds. Consequently, their expected performance in terms of rolling resistance is limited. To overcome these three important issues, the CNT have been surface-modified with oxygen-bearing groups and sulfur, resulting in an improvement in the key properties of these rubber compounds for their use in tire tread applications. A deep characterization of these new materials using functionalized CNT as filler was carried out by using a combination of mechanical, equilibrium swelling and low-field NMR experiments. The outcome of this research revealed that the formation of covalent bonds between the rubber matrix and the nano-particles by the introduction of sulfur at the CNT surface has positive effects on the viscoelastic behavior and the network structure of the rubber compounds, by a decrease of both the loss factor at 60 °C (rolling resistance) and the non-elastic defects, while increasing the crosslink density of the new compounds.

Spatially Engraving Morphological Structure on a Polymeric Surface by Ion Beam Milling

Polymer surface patterning and modification at the micro/nano scale has been discovered with great impact in applications such as microfluidics and biomedical technologies. We propose a highly efficient fabricating strategy, to achieve a functional polymer surface, which has control over the surface roughness. The key development in this fabrication method is the polymer positive diffusion effect (PDE) for an ion-bombarded polymeric hybrid surface through focused ion beam (FIB) technology. The PDE is theoretically explored by introducing a positive diffusion term into the classic theory. The conductivity-induced PDE constant is discussed as functions of substrates conductivity, ion energy and flux. The theoretical results agree well with the experiential results on the conductivity-induced PDE, and thus yield good control over roughness and patterning milling depth on the fabricated surface. Moreover, we demonstrate a controllable surface wettability in hydrophobic and superhydrophobic surfaces (contact angles (CA) range from 108.3° to 150.8°) with different CA hysteresis values ranging from 31.4° to 8.3°.

Influence of Coalescence on the Anisotropic Mechanical and Electrical Properties of Nickel Powder/Polydimethylsiloxane Composites

Multifunctional polymer-based composites have been widely used in various research and industrial applications, such as flexible and stretchable electronics and sensors and sensor-integrated smart structures. This study investigates the influence of particle coalescence on the mechanical and electrical properties of spherical nickel powder (SNP)/polydimethylsiloxane (PDMS) composites in which SNP was aligned using an external magnetic field. With the increase of the volume fraction of the SNP, the aligned SNP/PDMS composites exhibited a higher tensile strength and a lower ultimate strain. In addition, the composites with aligned SNP showed a lower percolation threshold and a higher electrical conductivity compared with those with randomly dispersed SNP. However, when the concentration of the SNP reached a certain level (40 vol. %), the anisotropy of the effective material property became less noticeable than that of the lower concentration (20 vol. %) composites due to the change of the microstructure of the particles caused by the coalescence of the particles at a high concentration. This work may provide rational methods for the fabrication of aligned composites.

Effects of plasticization and shear stress on phase structure development and properties of soy protein blends

In this study, soy protein concentrate (SPC) was used as a plastic component to blend with poly(butylene adipate-co-terephthalate) (PBAT). Effects of SPC plasticization and blend composition on its deformation during mixing were studied in detail. Influence of using water as the major plasticizer and glycerol as the co-plasticizer on the deformation of the SPC phase during mixing was explored. The effect of shear stress, as affected by SPC loading level, on the phase structure of SPC in the blends was also investigated. Quantitative analysis of the aspect ratio of SPC particles was conducted by using ImageJ software, and an empirical model predicting the formation of percolated structure was applied. The experimental results and the model prediction showed a fairly good agreement. The experimental results and statistic analysis suggest that both SPC loading level and its water content prior to compounding had significant influences on development of the SPC phase structure and were correlated in determining the morphological structures of the resulting blends. Consequently, physical and mechanical properties of the blends greatly depended on the phase morphology and PBAT/SPC ratio of the blends.

Compósitos de Borracha Natural com Compostos Condutivos à Base de Negro de Fumo e Polímero Condutor

Neste trabalho foram desenvolvidos compósitos condutores elétricos de borracha natural contendo negro de fumo e compostos condutivos baseados em polímeros condutores (Eenomer®). Os compósitos foram processados a quente num reômetro de torque HAAKE e moldados por prensagem. Foram obtidas placas homogêneas, flexíveis e com ótimo acabamento superficial. Os compósitos foram analisados pelas medidas de torque no processamento, medidas de condutividade elétrica, análise termogravimétrica (TGA), calorimetria diferencial de varredura (DSC) e ensaios de tração. Estes compósitos apresentaram valores de condutividade elétrica entre 10-7 a 10-1 S/cm, dependendo do tipo de negro de fumo ou composto condutivo utilizado e da quantidade destes no compósito. A análise térmica demonstrou que os compósitos são termicamente estáveis até cerca de 300°C. Os compostos condutivos atuam como reforço para a borracha natural melhorando suas propriedades mecânicas sem perder significativamente sua flexibilidade.

S. Condutividade elétrica de misturas de poliestireno/polibutadieno e poliestireno/copolímero em bloco de estireno-butadieno contendo negro de fumo

RESUMO: A condutividade elétrica de compósitos contendo negro de fumo extra condutor em sistemas envolvendo poliestireno/ polibutadieno (PS/PBD) e poliestireno/copolímero em bloco de estireno-butadieno (PS/SB) foi investigada. A mistura PS/SB apresentou menores limiares de percolação do que misturas PS/PBD. Análises através de microscopia eletrônica de varredura indicaram que, no caso das misturas PS/PBD, as partículas de negro de fumo estão aglomeradas e não formam um caminho contínuo, característico de condução elétrica. Investigações a respeito da formação de interações físicas entre polímero-negro de fumo (bound rubber) indicaram também maior adesão entre polímero-NF quando se utilizou o sistema PS/PBD.