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Poly (ether ether ketone) (PEEK) is a high-performance engineering thermoplastic polymer with potential for use in a variety of metal replacement applications due to its high strength to weight ratio. This combination of properties makes it an ideal material for use in the production of bespoke replacement parts for out-of-earth manufacturing purposes, in particular on the International Space Station (ISS). Additive manufacturing (AM) may be employed for the production of these parts, as it has enabled new fabrication pathways for articles with complex design considerations. However, AM of PEEK via fused filament fabrication (FFF) encounters significant challenges, mostly stemming from the semi crystalline nature of PEEK and its associated high melting temperature. This makes PEEK highly susceptible to changes in processing conditions which leads to a large reported variation in the literature on the final performance of PEEK. This has limited the adaption of FFF printing of PEEK in space applications where quality assurance and reproducibility are paramount. In recent years, several research studies have examined the effect of printing parameters on the performance of the 3D-printed PEEK parts. The aim of the current review is to provide comprehensive information in relation to the process-structure-property relationships in FFF 3D-printing of PEEK to provide a clear baseline to the research community and assesses its potential for space applications, including out-of-earth manufacturing.

Material choice is a fundamental consideration when it comes to designing a solid dosage form. The matrix material will ultimately determine the rate of drug release since the physical properties (solubility, viscosity, and more) of the material control both fluid ingress and disintegration of the dosage form. The bulk properties (powder flow, concentration, and more) of the material should also be considered since these properties will influence the ability of the material to be successfully manufactured. Furthermore, there is a limited number of approved materials for the production of solid dosage forms. The present study details the complications that can arise when adopting pharmaceutical grade polymers for fused-filament fabrication in the production of oral tablets. The paper also presents ways to overcome each issue. Fused-filament fabrication is a hot-melt extrusion-based 3D printing process. The paper describes the problems encountered in fused-filament fabrication with Kollidon® VA64, which is a material that has previously been utilized in direct compression and hot-melt extrusion processes. Formulation and melt-blending strategies were employed to increase the printability of the material. The paper defines for the first time the essential parameter profile required for successful 3D printing and lists several pre-screening tools that should be employed to guide future material formulation for the fused-filament fabrication of solid dosage forms.

One of the most promising technologies that is driving digitalization in several industries is Digital Twin (DT). DT refers to the digital replica or model of any physical object (physical twin). What differentiates DT from simulation and other digital or CAD models is the automatic bidirectional exchange of data between digital and physical twins in real-time. The benefits of implementing DT in any sector include reduced operational costs and time, increased productivity, better decision making, improved predictive/preventive maintenance, etc. As a result, its implementation is expected to grow exponentially in the coming decades as, with the advent of Industry 4.0, products and systems have become more intelligent, relaying on collection and storing incremental amounts of data. Connecting that data effectively to DTs can open up many new opportunities and this paper explores different industrial sectors where the implementation of DT is taking advantage of these opportunities and how these opportunities are taking the industry forward. The paper covers the applications of DT in 13 different industries including the manufacturing, agriculture, education, construction, medicine, and retail, along with the industrial use case in these industries.

Stereolithography (SLA)-based 3D printing has proven to have several advantages over traditional fabrication techniques as it allows for the control of hydrogel synthesis at a very high resolution, making possible the creation of tissue-engineered devices with microarchitecture similar to the tissues they are replacing. Much of the previous work in hydrogels for tissue engineering applications have utilised the ultraviolet (UV) chamber bulk photopolymerisation method for preparing test specimens. Therefore, it is essential to directly compare SLA 3D printing to this more traditional approach to elucidate the differences in hydrogels prepared by each fabrication method. Polyethyleneglycol dimethacrylate (PEGDMA) is an ideally suited material for a comparative study of the impact that SLA fabrication has on performance, as the properties of traditional UV chamber-cured hydrogels have been extensively characterised. The present study was conducted to compare the material properties of PEGDMA hydrogels prepared using UV chamber photopolymerisation and SLA 3D printing. From the subsequent testing, SLA-fabricated hydrogels were shown to maintain similar thermal and chemical performance to UV chamber-cured hydrogels but had a higher compressive strength and tensile stiffness, as well as increased hydrophilicity. These differences are attributed to the increased exposure to UV light SLA samples received compared to traditionally UV chamber-cured samples.

Digital Twin (DT) refers to the virtual copy or model of any physical entity (physical twin) both of which are interconnected via exchange of data in real time. Conceptually, a DT mimics the state of its physical twin in real time and vice versa. Application of DT includes real-time monitoring, designing/planning, optimization, maintenance, remote access, etc. Its implementation is expected to grow exponentially in the coming decades. The advent of Industry 4.0 has brought complex industrial systems that are more autonomous, smart, and highly interconnected. These systems generate considerable amounts of data useful for several applications such as improving performance, predictive maintenance, training, etc. A sudden influx in the number of publications related to ‘Digital Twin’ has led to confusion between different terminologies related to the digitalization of industries. Another problem that has arisen due to the growing popularity of DT is a lack of consensus on the description of DT as well as so many different types of DT, which adds to the confusion. This paper intends to consolidate the different types of DT and different definitions of DT throughout the literature for easy identification of DT from the rest of the complimentary terms such as ‘product avatar’, ‘digital thread’, ‘digital model’, and ‘digital shadow’. The paper looks at the concept of DT since its inception to its predicted future to realize the value it can bring to certain sectors. Understanding the characteristics and types of DT while weighing its pros and cons is essential for any researcher, business, or sector before investing in the technology.

Ever since its discovery, the applications of Shape Memory Alloys (SMA) can be found across a range of application domains, from structural design to medical technology. This is based upon the unique and inherent characteristics such as thermal Shape Memory Effect (SME) and Superelasticity (or Pseudoelasticity). While thermal SME is used for shape morphing applications wherein temperature change can govern the shape and dimension of the SMA, Superelasticity allows the alloy to withstand a comparatively very high magnitude of loads without undergoing plastic deformation at higher temperatures. These unique properties in wearables have revolutionized the field, and from fabrics to exoskeletons, SMA has found its place in robotics and cobotics. This review article focuses on the most recent research work in the field of SMA-based smart wearables paired with robotic applications for human-robot interaction. The literature is categorized based on SMA property incorporated and on actuator or sensor-based concept. Further, use-cases or conceptual frameworks for SMA fiber in fabric for ‘Smart Jacket’ and SMA springs in the shoe soles for ‘Smart Shoes’ are proposed. The conceptual frameworks are built upon existing technologies; however, their utility in a smart factory concept is emphasized, and algorithms to achieve the same are proposed. The integration of the two concepts with the Industrial Internet of Things (IIoT) is discussed, specifically regarding minimizing hazards for the worker/user in Industry 5.0. The article aims to propel a discussion regarding the multi-faceted applications of SMAs in human-robot interaction and Industry 5.0. Furthermore, the challenges and the limitations of the smart alloy and the technological barriers restricting the growth of SMA applications in the field of smart wearables are observed and elaborated.

A digital twin (DT) is a virtual/digital model of any physical object (physical twin), interconnected through data exchange. In the context of Industry 4.0, DTs are integral to intelligent automation driving innovation at scale by providing significant improvements in precision, flexibility, and real-time responsiveness. A critical challenge in developing DTs is achieving a model that reflects real-time conditions with precision and flexibility. This paper focuses on evaluating latency and accuracy, key metrics for assessing the efficacy of a DT, which often hinder scalability and adaptability in robotic applications. This article presents a comprehensive framework for developing DTs using Unity and Robot Operating System (ROS) as the main layers of digitalization and communication. The MoveIt package was used for motion planning and execution for the robotic arm, showcasing the framework’s versatility independent of proprietary constraints. Leveraging the versatility and open-source nature of these tools, the framework ensures interoperability, adaptability, and scalability, crucial for modern smart manufacturing applications. Our approach was validated by conducting extensive accuracy and latency tests. We measured latency by timestamping messages exchanged between the physical and digital twin, achieving a latency of 77.67 ms. Accuracy was assessed by comparing the joint positions of the DT and the physical robotic arm over multiple cycles, resulting in an accuracy rate of 99.99%. The results highlight the potential of DTs in enhancing operational efficiency and decision-making in manufacturing environments.

Reinforcement Learning (RL) enables robots to learn and improve from data without being explicitly programmed. It is well-suited for tackling complex and diverse robotic tasks, offering adaptive solutions without relying on traditional, hand-designed approaches. However, RL solutions in robotics have often been confined to simulations, with challenges in transferring the learned knowledge or learning directly in the real world due to latency issues, lack of a standardized structure, and complexity of integration with real robot platforms. While the use of Robot Operating System (ROS) provides an advantage in addressing these challenges, existing ROS-based RL frameworks typically support sequential, turn-based agent-environment interactions, which fail to represent the continuous, dynamic nature of real-time robotics or support robust multi-robot integration. This paper addresses this gap by proposing UniROS, a novel ROS-based RL framework explicitly designed for real-time multi-robot/task applications. UniROS introduces a ROS-centric implementation strategy for creating RL environments that support asynchronous and concurrent processing, which is pivotal in reducing the latency between agent-environment interactions. This study validates UniROS through practical robotic scenarios, including direct real-world learning, sim-to-real policy transfer, and concurrent multi-robot/task learning. The proposed framework, including all examples and supporting packages developed in this study, is publicly available on GitHub, inviting wider use and exploration in the field.

This study investigates the effect of extrusion screw speed and carbon nanotube (CNT) concentration on the thermal, mechanical, and electromagnetic interference shielding effectiveness (EMI SE) properties of Polycarbonate (PC)/acrylonitrile-butadiene-styrene (ABS) and its polymer nanocomposites (PNCs) by means of design of experiments (DoE) approach. A masterbatch method was employed to obtain the best dispersion of the CNTs throughout the polymer matrix. This study evaluates the thermo-mechanical characterisation of the polymers and PNCs at varying screw speeds to assess filler matrix bonding. The results highlight that CNT concentration has a significant effect on all mechanical properties, while screw speed only affects the Charpy impact strength and flexural properties of the samples. Compounding at 200 rpm has the best flexural and tensile strength, which is attributed to the best filler matrix bonding (highest storage modulus) of the PNCs. The best EMI SE results were obtained at 10 wt.% CNTs. This research contributes valuable insights into the effect of CNT concentration and extrusion screw speed on the mechanical, thermal and EMI SE properties of PC/ABS and its PNCs.

Through the control of the molecular weight, water content and monomer concentration, polyethylene glycol dimethacrylate (PEGDMA) based hydrogels have been adapted for numerous applications, including as structural scaffolds, drug delivery vehicles and cell carriers. However, due to the low biodegradability rates, the use of PEGDMA in tissue engineering has been limited. Thiol-based monomers have been shown to improve the degradation rates of several PEG-based hydrogels, though their impact on several material properties has not been as well defined. In this work, several mercaptopropianoates, as well as mercaptoacetates, were mixed with PEGDMA and copolymerized. Following an initial polymerization check, it was determined that mercaptoacetate-based thiol monomers did not polymerize in the presence of PEGDMA, whereas mercaptopropionates were more successful. The wettability, and the compressive and tensile strength, in addition to the thermal properties, were determined for successfully copolymerized samples via a combination of differential scanning calorimetry, dynamic mechanical analysis, unconfined compression, and goniometry. Further study determined that dipentaerythritol hexa(3–mercaptopropionate) (DiPETMP) successfully enhanced the biodegradability of PEGDMA.