Editorial Feature

Finite Element Analysis of Polymer Nanocomposites

A quantitative understanding of nanomaterials has become critical to unlocking future nanotechnologies. This article covers the role of finite element analysis in polymer nanocomposite analysis.

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Using novel theoretical and modeling tools such as finite element analysis can greatly accelerate widespread applications in many areas of nanotechnology.

Polymer reinforcement using fillers is a widespread practice in polymer manufacturing and processing. The use of nanoscale fillers to improve the characteristics of polymers has resulted in the creation of polymer nanocomposites (PNCs), which provide a radical alternative to traditional polymer composites.

Polymer nanocomposites are typically characterized as a mixture of a polymer matrix resin and inclusions with at least one dimension (length, breadth, or thickness) in the nanoscale range.

Several advantages of polymer nanocomposites allow them to compete commercially with traditional materials. Such properties include improved abrasion resistance, reduced shrinkage and residual stress, and enhanced thermal, electrical, and optical properties; however, understanding their mechanical behavior is critical to raising application confidence and design efficiency.

To study the mechanical properties of polymer nanocomposites, different simulation and mathematical techniques are used and finite element analysis is one of them.

Finite element analysis (FEA) predicts how a material will react to forces, vibrations, heat, fluid flow, and other physical effects. Finite element analysis is used to test a material's durability and functionality, which can help predict what will happen when used.

 By reducing the number of physical prototypes and experiments and optimizing components in the design phase, engineers can create better products faster and cheaper using finite element analysis.

Because nanomaterials have a smaller grain size than conventional materials, they have the potential to increase fatigue life. Understanding the mechanical behavior of these materials under mechanical loading is critical to improving application confidence and design efficiency.

Benefits of Applying FEA to Polymer Nanocomposites

The use of FEA in the field of nanotechnology is making a significant contribution to a wide range of sectors, including electronics, material science, quantum science, engineering, and biotechnology. Computational nanotechnology and related applications are also reaping the benefits of its use.

This method has long been a favorite of mathematicians due to the advent of FEA software like NASTRAN, ANSYS, ABAQUS, MATLAB, OpenFoam, and SimScale. As nanoscience developed, researchers struggled to fund nano-related projects. The FEA has evolved as an affordable methodology that solves all complex research systems.

Finite element method (FEM) has been used to solve problems in many common engineering fields, where experimental analysis is not feasible and affordable.

How Does FEA Help Improve the Properties of Polymer Nanocomposites?

The mechanical strength of polymer nanocomposites is determined by the matrix-nanofiber interface and stress transfer, an initially strong interaction.

Nucleation, initiation, growth, and tolerance are harmed by stress concentrations at the matrix/nanofiber interface.

Prolonged contact between nanocomposites and their polymers can cause damage to nucleation. Polymer-rich nanocomposite parts with low-stress failure in both cases

Researchers found that high interfacial stress can debond nanofiber/matrix and determines the final nanocomposite material strength. When combined with a matrix, high stiffness nanofibers should outperform resin. Finite element analysis is used to investigate matrix and reinforcement stresses which can help enhance their properties.

The finite element method can help control the nanofiber or matrix interface properties which can help optimize the strength of the matrix interface to produce an optimum stress transfer. Through FEA, researchers have found that the formation of stress concentrations at the interface between the fiber and the matrix can indicate the effective matrix to nanofiber stress transfer.

Applications of FEA in Polymer Nanocomposites

Finite element analysis has several applications in the field of nanocomposites. The FEA can be used to find maximum principal stresses, von mises, and normal stresses at the short interface and cross-section of nanofiber. This study helps investigate the magnitudes of stresses that can initiate damage to the polymer nanocomposites.

Finite element analysis can be used to model and simulate the arrangements of polymer nanocomposites and nanotubes. This would help enhance their mechanical properties by arranging thousands of nanotubes in a defined pattern.

FEA tools are used to simulate the polymer nanocomposites-based structures designed for the aerospace industry to investigate their fatigue life, thermal strength, corrosion resistance, and structural strength.

Several manufacturing industries are using finite element analysis to synthesize polymer nanocomposites of desired properties to be used in packaging and coating applications.

Challenges and Future

Despite the several applications and benefits of finite element analysis in polymer nanocomposites, it has specific challenges.

Finite element analysis is not very accurate at stress concentration testing, especially for nanocomposites. Stress concentration occurs due to frequent variations in nanoscale geometry and increases the stress on a small area of a material. The stress in these areas may exceed the material's yield strength.

Analysis of polymer nanocomposites requires too many parameters to produce results and improvements. Finite element analysis is a complex process that takes longer to compile than other similar methods.

Similarly, various factors like material property, stress and fatigue property of the material, and many others affect the test result.

Innovative techniques, tools, and infrastructure will be required to support commercial nanomanufacturing.

Existing nanometrological tools are reaching their resolution and accuracy limits, and thus will not meet future nanotechnology or nanomanufacturing requirements.

Continue reading: Finite Element Analysis in Nanotechnology Research.

References and Further Reading

Baccouch, M. (2021) Finite Element Methods and Their Applications. https://doi.org/10.5772/intechopen.83274.

Bitinis, N. et al. (2011) 'Recent advances in clay/polymer nanocomposites, Advanced Materials, 23(44), pp. 5229–5236. https://doi.org/10.1002/adma.201101948.

Bourchak, M. et al. (2009) 'Nanocomposites damage characterization using finite element analysis', International Journal of Nanoparticles, 2(1–6), pp. 467–475. https://doi.org/10.1504/ijnp.2009.028782.

Gupta, C. and Bhardwaj, A. (2020) Summary and future perspectives of nanomaterials and technologies, Nanomaterials for Sustainable Energy and Environmental Remediation. Elsevier Inc. https://doi.org/10.1016/b978-0-12-819355-6.00011-x.

Htira, T. et al. (2021) 'Finite element analysis of gas diffusion in polymer nanocomposite systems containing rod-like nanofillers', Polymers, 13(16). https://doi.org/10.3390/polym13162615.

Müller, K. et al. (2017)' Review on the processing and properties of polymer nanocomposites and nanocoatings and their applications in the packaging, automotive and solar energy fields', Nanomaterials, 7(4). https://doi.org/10.3390/nano7040074.

Musa, S. M. (2013) Computational Finite Element Methods in Nanotechnology. https://doi.org/10.5772/intechopen.94590.

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Muhammad Adeel Ahsan

Written by

Muhammad Adeel Ahsan

Adeel is an aerospace engineer and a robotics enthusiast. He has been providing services related to aerospace on Upwork and Fiverr for more than 2 years. Being passionate about control engineering, machine learning and AI, he wants to pursue his career in these fields. He loves to travel around the world and make new friends worldwide. He has just started his research journey and will soon publish research papers related to control engineering, robotics and AI.

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