Current trends, applications, and challenges of coatings on additive manufacturing based biopolymers: A state of art review

Sharma, Shrutika; Gupta, Vishal; Mudgal, Deepa

doi:10.1002/pc.26809

Cited by 32 publications

(25 citation statements)

References 166 publications

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“…Moreover, the bioinert behavior of PEEK has prompted researchers to tailor its biocompatibility using surface modifications and render it for biomedical applications. [108] Han et al reported coating of pure titanium layer onto PEEK using electron beam deposition. [109] This lowtemperature method deposited crystalized titanium and ensured that the properties of PEEK were not altered.…”

Section: Peek Surface Modificationsmentioning

confidence: 99%

Additive manufacturing of polyetheretherketone and its composites: A review

et al. 2022

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Polyetheretherketone (PEEK) is a high-performance plastic with favorable physical, mechanical, chemical, and biological properties for various industrial applications. Most PEEK substrates/components are manufactured using traditional methods like milling, compression molding, injection molding, pressure sintering, and so forth. With the advent of various additive manufacturing (AM) techniques, researchers have been working on optimizing the processing parameters for AM of PEEK. Furthermore, several PEEK composites with improved properties have also been developed, and efforts have also been made to use these PEEK composites in AM. Since AM of PEEK and its composites is a relatively new area of the advanced manufacturing process, the field faces many challenges. There is a dearth of comprehensive reports on this topic. Keeping this perspective in mind, we have tried to collate the relevant information on the composites and AM of PEEK in this review. The review highlighted the influence of variation in composition on material properties and performance of PEEK and showed the correlation with AM processability of such composites. A detailed analysis of the various reports on fused deposition modeling and selective laser sintering based processing of PEEK composites is included in the review. Critical barriers to the AM of these high-performance polymer composites are pointed out. We have also included the outcome of some interesting studies about the coating of PEEK with various materials/compounds to provide a broader perspective. This review will help the researcher to design and develop additively manufactured PEEK-based structures with improved and customized properties.

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Section: Peek Surface Modificationsmentioning

confidence: 99%

Additive manufacturing of polyetheretherketone and its composites: A review

et al. 2022

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“…These coatings act as a physical barrier to separate metal surfaces from corrosive environments. [5][6][7][8] Due to its high mechanical strength, thermal stability, chemical resistance, hydrophobicity, and excellent electroactive properties, poly(vinylidene fluoride) (PVDF) is being used in a wide range of engineering applications. [9][10][11][12][13] PVDF has also been extensively used in the films and coatings industry.…”

Section: Introductionmentioning

confidence: 99%

Poly(vinylidene fluoride)/molybdenum disulfide nanocomposite coatings: Studying the surface properties and corrosion protection

Ramezani

Seyfi²,

Aghjeh

et al. 2022

Polymer Composites

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Robust nanocomposite coatings based on polyvinylidene fluoride (PVDF) and molybdenum disulfide (MoS 2 ) nanoplatelets were prepared by a spray coating method. To achieve various surface structures, the coatings were dried at room and oven temperatures (20 and 200 C). All the samples dried at room temperature exhibited a highly porous surface structure, attributed to the strong nonsolvent role of water vapor, which triggered the nonsolvent-induced phase separation (VIPS). On the other hand, the oven-dried coatings showed a dense structure with no pores, resulting from eliminating the VIPS process by enhancing the drying temperature. MoS 2 nanoplatelets were localized at the surface layer and the adjacent beneath layers. The formation of α-type PVDF crystals was intensified for the oven-dried samples based on the surface morphology and X-ray diffraction patterns. Roughness analysis demonstrated that MoS 2 nanoplatelets interfere with the phase separation process leading to a lower porosity for the room-dried coatings. The elimination of porosity by increasing the drying temperature caused the hydrophobicity of the coatings to be notably decreased. Polarization and electrochemical impedance spectroscopy results revealed that both polymeric and nanocomposite coatings improved the corrosion resistance of the aluminum substrates, and the ovendried pure PVDF coating exhibited the highest level of corrosion protection.

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“…Additive manufacturing (AM) technology provides the ideal tailor-made solution for different orthopedic applications. [1] This technology offers various merits and functionalities such as precision, [2] ease of the process, [3] less material wastage, [4] personalization, [5] degree of freedom, [6] accuracy, [7] biocompatibility, [8] and customization [9] for the…”

Section: Introductionmentioning

confidence: 99%

Predicting the compressive strength of additively manufactured PLA‐based orthopedic bone screws: A machine learning framework

2022

Self Cite

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Additive manufacturing (AM) technology is an innovative technique that hasshown potential in several surgical innovations such as the fabrication of costeffective orthopedic screws. It is imperative that the process parameters used during the fabrication of bone screws determine the strength of the screw to support the load-bearing fracture sites. In this present work, the application of machine learning (ML) models was leveraged for predicting the compressive strength of additively manufactured orthopedic cortical screws. Different ML models such as k-nearest neighbors, support vector regression, decision trees, and random forest were compared to offer a robust predictive ML model. During the study, fused deposition modeling based additive manufacturing technology is used to fabricate poly(lactic acid) based cortical screws and compressive strength was monitored using the universal testing machine. The predictive ML models were developed by various independent parameters such as infill percentage, layer height, infill pattern and wall thickness. The adequacy and robustness of different ML models were observed at different error metrics. The error metrics of the random forest model were comparatively lower for testing data with a mean absolute error of 2.06 ± 0.91, root mean square error of 2.37 ± 0.9 and coefficient of determination of 0.96 ± 0.042. The results highlight that the random forest is the most adequate ML model for predicting the compressive strength of additively manufactured cortical screws.additive manufacturing, bone screw, compressive strength, machine learning | INTRODUCTIONAdditive manufacturing (AM) technology provides the ideal tailor-made solution for different orthopedic applications. [1] This technology offers various merits and functionalities such as precision, [2] ease of the process, [3] less material wastage, [4] personalization, [5] degree of freedom, [6] accuracy, [7] biocompatibility, [8] and customization [9] for the

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Current trends, applications, and challenges of coatings on additive manufacturing based biopolymers: A state of art review

Cited by 32 publications

References 166 publications

Additive manufacturing of polyetheretherketone and its composites: A review

Additive manufacturing of polyetheretherketone and its composites: A review

Poly(vinylidene fluoride)/molybdenum disulfide nanocomposite coatings: Studying the surface properties and corrosion protection

Predicting the compressive strength of additively manufactured PLA‐based orthopedic bone screws: A machine learning framework

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