Recycling as a Key Enabler for Sustainable Additive Manufacturing of Polymer Composites: A Critical Perspective on Fused Filament Fabrication

Additive manufacturing (AM, aka 3D printing) is generally acknowledged as a “green” technology. However, its wider uptake in industry largely relies on the development of composite feedstock for imparting superior mechanical properties and bespoke functionality. Composite materials are especially needed in polymer AM, given the otherwise poor performance of most polymer parts in load-bearing applications. As a drawback, the shift from mono-material to composite feedstock may worsen the environmental footprint of polymer AM. This perspective aims to discuss this chasm between the advantage of embedding advanced functionality, and the disadvantage of causing harm to the environment. Fused filament fabrication (FFF, aka fused deposition modelling, FDM) is analysed here as a case study on account of its unparalleled popularity. FFF, which belongs to the material extrusion (MEX) family, is presently the most widespread polymer AM technique for industrial, educational, and recreational applications. On the one hand, the FFF of composite materials has already transitioned “from lab to fab” and finally to community, with far-reaching implications for its sustainability. On the other hand, feedstock materials for FFF are thermoplastic-based, and hence highly amenable to recycling. The literature shows that recycled thermoplastic materials such as poly(lactic acid) (PLA), acrylonitrile-butadiene-styrene (ABS), and polyethylene terephthalate (PET, or its glycol-modified form PETG) can be used for printing by FFF, and FFF printed objects can be recycled when they are at the end of life. Reinforcements/fillers can also be obtained from recycled materials, which may help valorise waste materials and by-products from a wide range of industries (for example, paper, food, furniture) and from agriculture. Increasing attention is being paid to the recovery of carbon fibres (for example, from aviation), and to the reuse of glass fibre-reinforced polymers (for example, from end-of-life wind turbines). Although technical challenges and economical constraints remain, the adoption of recycling strategies appears to be essential for limiting the environmental impact of composite feedstock in FFF by reducing the depletion of natural resources, cutting down the volume of waste materials, and mitigating the dependency on petrochemicals

Embedding Function within Additively Manufactured Parts: Materials Challenges and Opportunities

As additive manufacturing (AM), particularly metal and polymer-based 3D printing, progresses from a scientific curiosity to an industry mainstay, there is an increasing desire for parts to take on secondary roles beyond their primary, typically structural or mechanical, function. This may enable unique and broad-ranging functional customization, including monitoring part performance or its local environment, provisions for unique identifiers in tracking, anticounterfeiting, quality control, and even product certification. Many materials and processing compatibility requirements must be addressed to achieve embedded function, as embedded fillers or additives must not compromise either the part's production or its primary function. Herein, the material, technological, and processing challenges are highlighted for embedding function into parts produced by some of the most popular AM techniques, with examples provided from the literature. While it is possible to produce cavities within 3D printed parts and place functional components within them postbuild, approaches, herein, specifically explore direct incorporation of functional agents, fillers, and additives during the build process that imparts ancillary function. It is hoped to inspire exploration of the possibilities and enhancements achievable through functional AM. On account of its versatility, binder jetting is analyzed as a case study, with novel approaches for embedding new functions outlined

Process monitoring and machine learning for defect detection in laser-based metal additive manufacturing

Over the past several decades, metal Additive Manufacturing (AM) has transitioned from a rapid prototyping method to a viable manufacturing tool. AM technologies can produce parts on-demand, repair damaged components, and provide an increased freedom of design not previously attainable by traditional manufacturing techniques. The increasing maturation of metal AM is attracting high-value industries to directly produce components for use in aerospace, automotive, biomedical, and energy fields. Two leading processes for metal part production are Powder Bed Fusion with laser beam (PBF-LB/M) and Directed Energy Deposition with laser beam (DED-LB/M). Despite the many advances made with these technologies, the highly dynamic nature of the process frequently results in the formation of defects. These technologies are also notoriously difficult to control, and the existing machines do not offer closed loop control. In the present work, the application of various Machine Learning (ML) approaches and in-situ monitoring technologies for the purpose of defect detection are reviewed. The potential of these methods for enabling process control implementation is discussed. We provide a critical review of trends in the usage of data structures and ML algorithms and compare the capabilities of different sensing technologies and their application to monitoring tasks in laser metal AM. The future direction of this field is then discussed, and recommendations for further research are provided

Study of novel Love mode surface acoustic wave filters

Novel Love mode filters based on ZnO and SiO<sub>2</sub>/90° rotated ST-cut quartz crystal structure were fabricated. A comprehensive study was carried out to show the capabilities of such filters. The periodicity of the fingers is 50 μm and the thickness of the SiO<sub>2</sub> and ZnO layers ranges from 0.2 to 7.2 μm. Electromechanical coupling coefficient, capacitance per unit wavelengths of finger pairs and temperature coefficient of frequency are studied in terms of thickness of the wave-guiding layers

Love mode SAW sensors with ZnO layer operating in gas and liquid media

Novel layered surface acoustic wave (SAW) sensors, based on a ZnO/90° rotated ST-cut quartz crystal structure, were fabricated. They were employed for liquid and gas sensing applications. Their mass detection limit in liquid media is as low as 100 pg/cm2. Furthermore, these sensors are able to sense oxygen gas concentrations as low as 0.2 ppm in nitrogen gas

Defect detection by multi-axis infrared process monitoring of laser beam directed energy deposition

Laser beam directed energy deposition (DED-LB) is an attractive additive manufacturing technique to produce versatile and complex 3D structures on demand, apply a cladding, or repair local defects. However, the quality of manufactured parts is difficult to assess by inspection prior to completion, and parts must be extensively inspected post-production to ensure conformance. Consequently, critical defects occurring during the build go undetected. In this work, a new monitoring system combining three infrared cameras along different optical axes capable of monitoring melt pool geometry and vertical displacement throughout deposition is reported. By combining multiple sensor data, an automated algorithm is developed which is capable of identifying the formation of structural features and defects. An intersecting, thin-walled geometry is used to demonstrate the capability of the system to detect process-induced porosity in samples with narrow intersection angles, which is validated using micro-CT observations. The recorded results indicate the root cause of this process-induced porosity at the intersection, and it is shown that advanced toolpath planning can eliminate such defects. The presented methodology demonstrates the value of multi-axis monitoring for identifying both defects and structural features, providing an advancement towards automated detection and alert systems in DED-LB

How Can We Provide Additively Manufactured Parts with a Fingerprint? A Review of Tagging Strategies in Additive Manufacturing

Additive manufacturing (AM) is rapidly evolving from “rapid prototyping” to “industrial production”. AM enables the fabrication of bespoke components with complicated geometries in the high-performance areas of aerospace, defence and biomedicine. Providing AM parts with a tagging feature that allows them to be identified like a fingerprint can be crucial for logistics, certification and anti-counterfeiting purposes. Whereas the implementation of an overarching strategy for the complete traceability of AM components downstream from designer to end user is, by nature, a cross-disciplinary task that involves legal, digital and technological issues, materials engineers are on the front line of research to understand what kind of tag is preferred for each kind of object and how existing materials and 3D printing hardware should be synergistically modified to create such tag. This review provides a critical analysis of the main requirements and properties of tagging features for authentication and identification of AM parts, of the strategies that have been put in place so far, and of the future challenges that are emerging to make these systems efficient and suitable for digitalisation. It is envisaged that this literature survey will help scientists and developers answer the challenging question: “How can we embed a tagging feature in an AM part?”

Facilitating the additive manufacture of high-performance polymers through polymer blending: A review

Fused Filament Fabrication (FFF, a.k.a. fused deposition modeling, FDM) is presently the most widespread material extrusion (MEX) additive manufacturing technique owing to its flexibility and robustness. Nonetheless, it remains underutilized in load-bearing applications, as often seen in aerospace, automotive and biomedical industries. This is largely due to the processing challenges associated with high performance polymers (HPPs) like poly-ether-ether-ketone (PEEK) or polyetherimide (PEI). Compared with commercial-grade plastics such as polylactic acid (PLA), parts produced with HPPs have outstanding mechanical properties and thermal stability. However, HPPs have bulkier chemical structures and stronger intermolecular forces than common FFF feedstock materials, and this results in much higher printing temperatures and greater melt viscosities. The demanding processing requirements of HPPs have thus impaired their adoption within FFF. Polymer blending, which consists in properly mixing HPPs with other thermoplastics, makes it possible to alleviate these printing issues, while also providing additional advantages such as improved tensile strength and reduced friction. Further to this, manipulating the crystallisation processes of HPPs mitigates distortion or warping upon printing. This review explores some emerging trends in the field of HPP blends and how they address the challenges of excessive melt viscosity, polymer crystallization, moisture uptake, and part shrinkage in 3D printing. Also, the various structural/mechanical/chemical enhancements that are afforded to FFF parts through HPP blending are critically analysed based on recent examples from the literature. Such insights will not only aid researchers in this field, but also facilitate the development of novel, 3D printable HPP blends

A room temperature polyaniline nanofibre hydrogen gas sensor

Electro-conductive polyaniline (PANI) nanofiber based surface acoustic wave (SAW) gas sensors have been investigated with hydrogen (H 2) gas. A template-free, rapidly mixed method was employed to synthesize polyaniline nanofibers using chemical oxidative polymerization of aniline. The nanofibers were deposited onto a layered ZnO/64° YX LiNbO3 SAW transducer for gas sensing applications. The novel sensor was exposed to various concentrations of H2 gas at room temperature. The sensor response, defined as the relative variation in operating frequency of oscillation due to the introduction of the gas, was 3.04 kHz towards a 1% H2 concentration. A relatively fast response time of 8 sec and a recovery time of 60 sec with good repeatability were observed at room temperature. Due to room temperature operation, the novel gas sensor is promising for environmental and industrial applications

Characterization and testing of Pt/TiO2/SiC thin film layered structure for gas sensing

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