High stiffness polymer composite with tunable transparency

Owuor, Peter Samora; Chaudhary, Varun; Woellner, Cristiano F.; Ramanujan, R.V.; Stender, Anthony S.; Soto, Matias; Özden, Şehmus; Barrera, Enrique V.; Vajtai, Róbert; Galvão, Douglas S.; Lou, Jun; Tiwary, Chandra Sekhar; Ajayan, Pulickel M.

doi:10.1016/j.mattod.2017.12.004

Cited by 30 publications

(24 citation statements)

References 29 publications

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“…The recent reports show that liquid metal reinforcement (gallium, wax, etc.) in the polymer can enhance the stiffness and toughness of the composite . The liquid reinforcements also show a better interface between matrix and reinforcement.…”

Section: Comparison Of Experimental and Theoretical Values For Effectmentioning

confidence: 99%

Bioinspired Aluminum Composite Reinforced with Soft Polymers with Enhanced Strength and Plasticity

et al. 2020

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Composites have played a key role in revolutionizing the automobile, marine, and aerospace industries. There is a constant attempt for the development of low‐density composite materials with superior mechanical and corrosion‐resistant properties for elevated temperature applications. Herein, an attempt is made to develop a nature‐inspired unique aluminum‐based composite with low‐density polymer (polyethylene terephthalate, i.e., soft material) reinforcement, which shows an enhancement in strength and toughness. The composite is processed using the easily scalable and simple friction stir processing technique. Mechanical properties of the uniformly reinforced aluminum composite show double ultimate strength and fivefold improvement in plasticity. The ultimate strength of the composite increases at elevated temperatures. The experimental observations are further supported by theoretical calculations and molecular dynamics simulations.

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Section: Comparison Of Experimental and Theoretical Values For Effectmentioning

confidence: 99%

Bioinspired Aluminum Composite Reinforced with Soft Polymers with Enhanced Strength and Plasticity

et al. 2020

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“…The relaxation function can be used to predict the stress-strain curve with given strain history. For thermal equilibrium process, the stress-strain relation with specific strain history can be found using equation (2). 44 The strain rate (_ e) is considered constant for standard quasi-static tensile test and the time dependent stress history can be found as…”

Section: Transformation To Elastic Modulusmentioning

confidence: 99%

“…The ability to tailor the properties of composite materials is their most important asset. 1,2 Due to their viscoelastic nature, the properties of thermoplastic matrix composite materials are strongly dependent on the test strain rate and temperature. [3][4][5] The viscoelasticity in thermoplastics is often nonlinear [6][7][8] and this complexity makes it very challenging and time consuming for characterization studies.…”

Section: Introductionmentioning

confidence: 99%

Tailoring composite materials for nonlinear viscoelastic properties using artificial neural networks

Elgamal

Doddamani

et al. 2020

Journal of Composite Materials

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Polymer matrix composites exhibit nonlinear viscoelastic behavior over a wide range of temperatures and loading frequencies, which requires an elaborate experimental characterization campaign. Methods are now available to accelerate the characterization process and recover elastic modulus from storage modulus ( E′). However, these methods are limited to the linear viscoelastic region and need to be expanded to nonlinear viscoelastic problems to enable materials design. The present work aims to build a general machine learning based architecture to accelerate the characterization and materials design process for nonlinear viscoelastic materials using the E′ results. To expand outside the linear viscoelastic region, general relations of viscoelasticity are first developed so the master relation of E′ considering nonlinear viscoelasticity can be transformed to time domain relaxation function. The transform starts with building the master relation by optimizing the artificial neural network (ANN) formulation using Kriging model and genetic algorithm. Then the master relation is transformed to a relaxation function, which can be used to predict the stress response with a given strain history and to further extract the elastic modulus. The transform is tested on high density polyethylene matrix syntactic foams and the accuracy is found by comparing the predicted materials properties with those obtained from tensile tests. The good agreements indicate the transform can predict the elastic modulus under a wide range of temperatures and strain rates for any composition of the composite and can be used for material design problems.

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“…If magnetic nanoparticles are dispersed in a solution and subjected to an alternating magnetic field (AMF), they can convert electromagnetic energy into heat. This property of magnetic nanoparticles can be used for several applications, including biomedicine, smart windows, and other applications for which local heating is advantageous . Hence, magnetic nanoparticles that exhibit high heating efficiency at a reasonable frequency and a low alternating magnetic field strength are of high interest.…”

Section: Introductionmentioning

confidence: 99%

“…This propertyo fm agnetic nanoparticles can be used for several applications, including biomedicine, [16,17] smart windows,a nd other applications for which local heating is advantageous. [18] Hence, magnetic…”

Section: Introductionmentioning

confidence: 99%

Mechanochemical Synthesis of Iron and Cobalt Magnetic Metal Nanoparticles and Iron/Calcium Oxide and Cobalt/Calcium Oxide Nanocomposites

et al. 2018

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We report an environmentally benign and cost‐effective method to produce Fe and Co magnetic metal nanoparticles as well as the Fe/Cao and Co/CaO nanocomposites by using a novel, dry mechanochemical process. Mechanochemical milling of metal oxides with a suitable reducing agent resulted in the production of magnetic metal nanoparticles. The process involved grinding and consequent reduction of low‐costing oxide powders, unlike conventional processing techniques involving metal salts or metal complexes. Calcium granules were used as the reducing agent. Magnetometry measurements were performed over a large range of temperatures, from 10 to 1273 K, to evaluate the Curie temperature, blocking temperature, irreversibility temperature, saturation magnetization, and coercivity. The saturation magnetizations of the iron and cobalt nanoparticles were found to be 191 and 102 emu g−1, respectively. The heating abilities of these nanoparticles suspended in several liquids under alternating magnetic fields were measured and the specific loss power was determined. Our results suggest that the dry mechanochemical process is a robust method to produce metallic nanoparticles and nanocomposites.

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High stiffness polymer composite with tunable transparency

Cited by 30 publications

References 29 publications

Bioinspired Aluminum Composite Reinforced with Soft Polymers with Enhanced Strength and Plasticity

Bioinspired Aluminum Composite Reinforced with Soft Polymers with Enhanced Strength and Plasticity

Tailoring composite materials for nonlinear viscoelastic properties using artificial neural networks

Mechanochemical Synthesis of Iron and Cobalt Magnetic Metal Nanoparticles and Iron/Calcium Oxide and Cobalt/Calcium Oxide Nanocomposites

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