Faculty Publications
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Item Influence of microballoon wall thickness on dynamic mechanical analysis of closed cell foams(Institute of Physics Publishing helen.craven@iop.org, 2019) Doddamani, M.Thermoplastics are most commonly used in industrial and consumer products. The growing interest in making them lightweight is always a priority in industrial practices. Investigations on thermoplastic based closed cell foams wall thickness variations for dynamic mechanical analysis (DMA), and crystallinity are scarce. The present study investigates storage modulus, loss modulus, damping, and % crystallinity as a function of glass microballoon/high-density polyethylene (GMB/HDPE) foam wall thickness and volume fraction variations. Crystallinity percentage variation in HDPE and their foams are analyzed through DSC traces. GMBs are mixed with HDPE in plasticorder, and subsequently, GMB/HDPE composite blend is compression molded. Varying wall thickness (particle density variations) GMB particles across three different volume fractions (20, 40 and 60%) are prepared. Storage modulus, loss modulus, and damping are observed to be increasing with particle wall thickness and volume fraction as compared to HDPE matrix resin. Thick walled GMB particle with the highest GMB content registered enhanced storage modulus compared to thin walled ones at lower temperatures. DMA properties increase with increasing wall thickness. Damping is noted to be less sensitive than the storage and loss modulus. Crystallinity is observed to be decreasing with increasing wall thickness and GMB content. Higher crystalline phase contributes towards DMA properties at lower filler loadings while higher wall thickness plays a vital role at higher filler content. © 2020 IOP Publishing Ltd.Item Extracting elastic modulus at different strain rates and temperatures from dynamic mechanical analysis data: A study on nanocomposites(Elsevier Ltd, 2019) Xu, X.; Koomson, C.; Doddamani, M.; Behera, R.K.; Gupta, N.Viscoelastic nature of polymers makes their properties strongly dependent on temperature and strain rate. Characterization of material properties over a wide range of strain rates and temperatures requires an expensive and time consuming experimental campaign. While viscoelastic properties of materials are widely tested using dynamic mechanical analysis (DMA) method, the frequency dependent component of the measured properties is underutilized due to a lack of correlation between frequency, temperature, and strain rate. The present work develops a method that can extract elastic modulus over a range of strain rates and temperatures from the DMA data for nanocomposites. Carbon nanofiber (CNF) reinforced high-density polyethylene (HDPE) matrix nanocomposites are taken as the study material. Four different compositions of CNF/HDPE nanocomposites are tested using DMA from 40 to 120 °C at 1–100 Hz frequency. First, time-temperature superposition (TTS) principle is used to develop an extrapolation for the results beyond the test parameter range. Then the TTS curve is transformed to a time domain relaxation function using integral relations of viscoelasticity. Finally, the strain rate sensitive elastic modulus is extracted and extrapolated to room temperature. The transform results are validated with tensile test results and the error found to be below 13.4% in the strain rate range 10?5 to 10?3 for all four nanocomposites. Since the materials are tested with the aim of finding a correlation among the test methods, the quality of the material is not a study parameter and the transform should yield accurate results for any material regardless of composition and quality. © 2018 Elsevier LtdItem Effect of surface treatment on quasi-static compression and dynamic mechanical analysis of syntactic foams(Elsevier Ltd, 2019) Doddamani, M.Quasi static compression (10 ?1 , 10 ?2 and 10 ?3 s ?1 strain rates) and dynamic mechanical analysis (temperature sweep of 30–175 °C) of cenosphere/epoxy syntactic foams are investigated. Effect of cenosphere content (20, 40 and 60 vol %) and surface modification are presented. Quasi-static tests reveal lower modulus for neat epoxy samples as compared to all the syntactic foams. With increasing cenosphere content and strain rate, elastic modulus increases for all the tested conditions. Foams reinforced with surface modified cenosphere exhibit higher modulus as compared with untreated ones and neat epoxy. Energy absorption of samples increases with increasing cenosphere content and surface modification. Storage modulus of untreated and treated syntactic foams register higher values with increase in cenosphere content and are higher than the neat epoxy samples. Loss modulus of syntactic foams at room temperature are lower as compared with pure epoxy while damping of untreated and treated foams registered higher values as compared with neat resin. Scanning electron microscopy of the samples are performed for structure property correlations. Finally, property map for quasi-static compression is presented by comparing results of present work with the extracted values from literature. © 2019 Elsevier LtdItem Eco-friendly lightweight filament synthesis and mechanical characterization of additively manufactured closed cell foams(Elsevier Ltd, 2019) Patil, B.; Bharath Kumar, B.R.; Bontha, S.; Balla, V.K.; Powar, S.; Hemanth Kumar, V.H.; Suresha, S.N.; Doddamani, M.Environmentally pollutant fly ash cenospheres (hollow microballoons) are utilized with most widely consumed, relatively expensive high density polyethylene (HDPE) for developing lightweight eco-friendly filament for 3D printing of closed cell foams. Cenospheres (20, 40 and 60 by volume %) are blended with HDPE and subsequently extruded in filament to be used for 3D printing. Cenosphere/HDPE blends are studied for melt flow index (MFI) and rheological properties. MFI decreases with cenospheres addition. Complex viscosity, storage and loss modulus increase with filler loading. DSC results on the filament and printed samples reveal increasing crystallization temperature and decreasing crystallinity % with no appreciable change in peak melting temperature. Cooling rate variations exhibit crystallinity differences between the filament and the prints. CTE decreases with increasing cenosphere content resulting in lower thermal stresses and under diffusion of raster leading to non-warped prints. Micrography on freeze fractured filament and prints show cenospheres uniform distribution in HDPE. Intact cenospheres lower the foam density making it lightweight. Tensile tests are carried out on filaments and printed samples while flexural properties are investigated for 3D prints. Cenospheres addition resulted in improved tensile modulus and decreased filament strength. Tensile and flexural modulus of printed foams increases with filler content. Results are also compared with injection molded samples. Printed foams registered comparable tensile strength. Specific tensile modulus is noted to be increased with cenospheres loading implying weight saving potential of 3D printed foams. Property map reveals printed foams advantage over other fillers and HDPE composites synthesized through injection and compression molding. © 2019 Elsevier LtdItem Tailoring composite materials for nonlinear viscoelastic properties using artificial neural networks(SAGE Publications Ltd, 2021) Xu, X.; Elgamal, M.; Doddamani, M.; Gupta, N.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. © The Author(s) 2020.Item A comprehensive characterization of 3D printable poly ether ketone ketone(Elsevier Ltd, 2024) Ojha, N.; Kumar, S.; Ramesh, M.R.; Balan, A.A.S.; Doddamani, M.The current work focuses on the comprehensive characterization of a 3D printable biomaterial, polyether ketone ketone (PEKK). The PEKK granules are first characterized and then utilized for extrusion of the PEKK filaments. The extruded PEKK filaments are characterized for crystallinity, quality, and printability, wherein they exhibit amorphous nature, good quality, and appropriate printability. Utilizing the filaments, the samples are printed with the appropriate printing parameters, which are further characterized for layer adhesion, voids, and crystallinity, wherein they showed seamless layer adhesion, improper beads consolidation, and the amorphous nature. The as printed samples are further annealed at different temperatures (200 and 250 °C). The scanning electron microscopy (SEM) of the annealed samples (A-200 and A-250) revealed better void consolidation, while the X-ray diffraction (XRD) revealed better crystallinity compared to the un-annealed sample. The printed samples are also investigated for dynamic mechanical analysis (DMA), shape memory, and tensile properties. The storage moduli of the annealed samples are observed to be better than the un-annealed sample. The annealed samples exhibited better shape memory properties: shape fixity and shape recovery ratio of A-200 and A-250 samples, 90.28 and 90.75%, and 99.16 and 94.73%, respectively, compared to the un-annealed samples. The highest shape fixity ratio and the shape recovery ratio are noted for A-250 (90.75%) and A-200 (∼ 100%). The A-200 and A-250 samples showed enhanced tensile modulus and strength, 4.16 and 49.67%, and 36.61 and 35.06%, respectively compared to the un-annealed sample. The highest modulus is noted for A-250, while the strength is comparable (36.61 and 35.06%) for A-200 and A-250. © 2023 Elsevier LtdItem 4D printing of heat-stimulated shape memory polymer composite for high-temperature smart structures/actuators applications(John Wiley and Sons Inc, 2024) Kumar, S.; Ojha, N.; Ramesh, M.R.; Doddamani, M.High temperature shape memory polymers (HT-SMPs) have great utilization in self-deployable hinges/morphing structures for space/aerospace, and high-temperature sensors/actuators for electronics. However, HT-SMPs have many drawbacks, such as low stiffness, strength, thermal stability, and dynamic mechanical properties. This work aims at improving these properties of highly utilized space grade HT-SMP, PEKK (polyether ketone ketone), by reinforcing it with low-cost carbon fibers (CFs), and developing its composite via additive manufacturing. The additively manufactured CF/PEKK composites are annealed at 200 °C (CF/PEKK-A200) and 250 °C (CF/PEKK-A250), and for the first time, investigated for shape memory effect (SME). The shape fixity and the shape recovery of the CF/PEKK-UNA (un-annealed), CF/PEKK-A200, and CF/PEKK-A250 are noted to be 95.97%, 88.95%, and 86.40%, and 88.70%, 92.70%, and 95.19%, respectively with a significant weight saving potential of ?21%. Dispersion of CFs in PEKK and suitability of processing parameters (blending, extrusion, and 3D printing) are confirmed through scanning electron microscopy (SEM). Thermal degradation temperature ((Formula presented.)) of the printed CF/PEKK composite (?568 °C) is found to be ?3.5% higher than PEKK (?549 °C). CF/PEKK-A250 exhibited the highest storage modulus (4438.23 MPa), ~158% higher than PEKK (1722.3 MPa), while CF/PEKK-A200 demonstrated the highest tensile modulus (10.9 GPa), which is 138.5% higher than PEKK (4.57 GPa) and 312.88% higher than CF/PEKK-UNA (2.64 GPa). Moreover, CF/PEKK-A200 exhibited 237.46%, 138.51%, 127.08%, 61.48%, 32.93%, and 50.35% higher tensile modulus than PEEK, PEKK, PEK, CF/PEK, CF/PEEK, and CF/PEKK composites, respectively, showing great potential to replace them. Highlights: Printed CF/PEKK composites are investigated for shape memory behavior. The printed composites exhibited outstanding shape memory properties. Printed-A200 exhibited 138.51% enhanced tensile modulus than pure PEKK. Also, the printed-A200 showed 313% enhanced modulus than printed-UNA. (Formula presented.) (568 °C) of the printed composites is found ?4% greater than pure PEKK. © 2024 Society of Plastics Engineers.