Mechanical and electrical properties of three‐dimensional printed polylactic acid–graphene–ca<scp>rbon</scp> nanofiber composites

Santo, Jose; Penumakala, Pavan Kumar; Adusumalli, Ramesh Babu

doi:10.1002/pc.26053

Cited by 32 publications

(22 citation statements)

References 30 publications

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“…[48] These variables are defined by the material used, the nozzle dimension, and the printer type. Polylactic acid (PLA) [49][50][51][52] and acrylonitrile butadiene styrene (ABS) are the most widely utilized materials with this technology, along with polyethylene terephthalate glycol (PETG) [53][54][55][56] and other composites. To utilize multimaterials in FDM with multi-purpose products, it needs to be optimized for the mentioned variables.…”

Section: Extrusion-basedmentioning

confidence: 99%

Additive manufacturing of smart polymeric composites: Literature review and future perspectives

2022

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The latest developments in smart systems for improved human lives with advanced biomedical devices have evolved out of multi‐disciplinary scientific studies, including medicine, biology, material sciences, design, manufacturing, artificial intelligence, microelectronics, and so forth. The growth of such intelligent systems is primarily possible with innovative materials, which demonstrate the response to various external stimuli like temperature, heat, moisture, light, electromagnetic field, and chemical alteration. Such materials have been recently fabricated using different additive manufacturing techniques to devise personalized unique, complex, and novel structures that can adjust to external conditions over time and are specifically attributed to 4D printing. Novel materials that can further improve such systems continued to be explored and employed. This review paper investigates the additive manufacturing of functional polymer nanocomposites, which offer compliant structures with flexible manufacturing processes with high strength, low cost, and long‐term stability. This study aims to deliver a comprehensive and deep understanding of the latest developments in materials, design, manufacturing, fundamental mechanisms involved, and future possibilities in this area of research.

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Section: Extrusion-basedmentioning

confidence: 99%

Additive manufacturing of smart polymeric composites: Literature review and future perspectives

2022

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“…Furthermore, the conductivity of printed conductive filament is highly dependent on the internal alignment of the conductive microparticles. 38 The effects of printing along a curve rather than in a straight line on this alignment are not fully understood. The model of Op-Amp is LM741, which is the most used model.…”

Section: A4 Curved Sensorsmentioning

confidence: 99%

Neuromorphic metamaterials for mechanosensing and perceptual associative learning

Riley,

Koner,

Osorio

et al. 2022

Preprint

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Physical systems exhibiting neuromechanical functions promise to enable structures with directly encoded autonomy and intelligence. We report on a class of neuromorphic metamaterials embodying bioinspired mechanosensing, memory, and learning functionalities obtained by leveraging mechanical instabilities and flexible memristive materials. Our prototype system comprises a multistable metamaterial whose bistable units filter, amplify, and transduce external mechanical inputs over large areas into simple electrical signals using piezoresistivity. We record these mechanically transduced signals using non-volatile flexible memristors that remember sequences of mechanical inputs, providing a means to store spatially distributed mechanical signals in measurable material states. The accumulated memristance changes resulting from the sequential mechanical inputs allow us to physically encode a Hopfield network into our neuromorphic metamaterials. This physical network learns a series of external spatially distributed input patterns. Crucially, the learned patterns input into our neuromorphic metamaterials can be retrieved from the final accumulated state of our memristors. Therefore, our system exhibits the ability to learn without supervised training and retain spatially distributed inputs with minimal external overhead. Our system's embodied mechanosensing, memory, and learning capabilities establish an avenue for synthetic neuromorphic metamaterials enabling the learning of touch-like sensations covering large areas for robotics, autonomous systems, wearables, and morphing structures.The nervous systems of animals comprise networks of distributed sensory, memory, and control elements that enable perception, reaction and adaptation in response to varied external stimuli. The coevolution of the nervous system and body morphology is thought to reduce the complexity of sensed signals due to morphological computing and short neuronal connections. This results in a form of neuromechanical control that requires few inputs to fulfil complex functions. 1, 2 Some organisms, such as comb jellies (phylum Ctenophora 3 ), perform complex tasks even without a central nervous system. This capability stems from coevolved neuromechanical systems that exploit morphological and sensory couplings to create autonomic responses, 4 which constitute one of the simplest forms of learned behavior. Typical autonomic behaviors include reflexes, 5 preflexes, and central pattern generators, 6 all of which leverage fast, decentralized sense-compute-actuate control loops. 7 At the most basic level, this is achieved through the synergy of morphology, sensing, computation, and actuation systems that perceive stimuli, 8 filter noise, 9 and store valuable information in the physical state of the systems. Achieving similar capabilities in synthetic systems is important for realizing the next generation of autonomic, multifunctional, power-efficient materials, devices, and systems. Single artificial neuromechanical functions encoded into material systems ha...

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“…As mentioned above, the use of different kind of GMB and different technics of composites preparation can lead to different results. The reduction of tensile strength, due to the interfacial defects, was observed in 3D‐printed PLA filament after addition of graphene and carbon nanofibers 12 . Nevertheless the strength and toughness changed with orientation of the layer with possible enhancement of toughness 13 .…”

Section: Introductionmentioning

confidence: 99%

“…The reduction of tensile strength, due to the interfacial defects, was observed in 3D-printed PLA filament after addition of graphene and carbon nanofibers. [14] Nevertheless the strengh and toughness changed with orientation of the layer with possible enhancement of toughness. [14] On the other hand, positive mechanical reponses were achieved with 3D-printed PLA-based graphene composites manufactured by fused filament fabrication, also orientation dependent.…”

Section: Introductionmentioning

confidence: 99%

Great enhancement of mechanical features in PLA based composites containing aligned few layer graphene (FLG), the effect of FLG loading, size, and dispersion on mechanical and thermal properties

Marouazi

Schueren

Favier

et al. 2021

J of Applied Polymer Sci

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Four series of polylactide (PLA) based composite films containing horizontally aligned few layer graphene (FLG) flakes of high aspect ratio and adsorbed albumin are prepared. The mechanical and thermal properties varies with percentage, dispersion degree and size of FLG flakes. Great improvement up to 290% and 360% of tensile modulus and strength respectively were obtained for the composite containing high lateral size of FLG at 0.17% wt, and up to 60% and 80% for the composite with very well dispersed 0.02% wt FLG. The composites of PLA and PEG‐PLLA containing very well dispersed FLG flakes at 0.07% wt are ductile showing enhancement of elongation at break up to respectively 80% and 88%. Relatively high electrical conductivity, 5 × 10−3 S/cm, is measured for PLA film charged with 3% of FLG.

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Mechanical and electrical properties of three‐dimensional printed polylactic acid–graphene–carbon nanofiber composites

Cited by 32 publications

References 30 publications

Additive manufacturing of smart polymeric composites: Literature review and future perspectives

Additive manufacturing of smart polymeric composites: Literature review and future perspectives

Neuromorphic metamaterials for mechanosensing and perceptual associative learning

Great enhancement of mechanical features in PLA based composites containing aligned few layer graphene (FLG), the effect of FLG loading, size, and dispersion on mechanical and thermal properties

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