Scalable Microwires through Thermal Drawing of Co-Extruded Liquid Metal and Thermoplastic Elastomer.

This article demonstrates scalable production of liquid metal (LM)-based microwires through the thermal drawing of extrudates. These extrudates were first co-extruded using a eutectic alloy of gallium and indium (EGaIn) as a core element and a thermoplastic elastomer, styrene-ethylene/butylene-styrene (SEBS), as a shell material. By varying the feed speed of the co-extruded materials and the drawing speed of the extrudate, it was possible to control the dimensions of the microwires, such as core diameter and shell thickness. How the extrusion temperature affects the dimensions of the microwire was also analyzed. The smallest microwire (core diameter: 52 ± 14 µm and shell thickness: 46 ± 10 µm) was produced from a drawing speed of 300.1 mm s-1 (the maximum attainable speed of the apparatus used), SEBS extrusion speed of 1.50 mm3 s-1, and LM injection rate of 5 × 105 µL s-1 at 190 °C extrusion temperature. The same extrusion condition without thermal drawing generated significantly large extrudates with a core diameter of 278 ± 26 µm and shell thickness of 430 ± 51 µm. The electrical properties of the microwires were also characterized under different degrees of stretching and wire kinking deformation which proved that these LM-based microwires change electrical resistance as they are deformed and fully self-heal once the load is removed. Finally, the sewability of these microwires was qualitatively tested by using a manual sewing machine to pattern microwires on a traditional cotton fabric.

Towards High Efficiency and Rapid Production of Room-Temperature Liquid Metal Wires Compatible with Electronic Prototyping Connectors.

We present in this work new methodologies to produce, refine, and interconnect room-temperature liquid-metal-core thermoplastic elastomer wires that have extreme extendibility (>500%), low production time and cost at scale, and may be integrated into commonly used electrical prototyping connectors like a Japan Solderless Terminal (JST) or Dupont connectors. Rather than focus on the development of a specific device, the aim of this work is to demonstrate strategies and processes necessary to achieve scalable production of liquid-metal-enabled electronics and address several key challenges that have been present in liquid metal systems, including leak-free operation, minimal gallium corrosion of other electrode materials, low liquid metal consumption, and high production rates. The ultimate goal is to create liquid-metal-enabled rapid prototyping technologies, similar to what can be achieved with Arduino projects, where modification and switching of components can be performed in seconds, which enables faster iterations of designs. Our process is focused primarily on fibre-based liquid metal wires contained within thermoplastic elastomers. These fibre form factors can easily be integrated with wearable sensors and actuators as they can be sewn or woven into fabrics, or cast within soft robotic components.

Machine Learning Algorithms for Predicting Mechanical Stiffness of Lattice Structure-Based Polymer Foam.

Polymer foams are extensively utilized because of their superior mechanical and energy-absorbing capabilities; however, foam materials of consistent geometry are difficult to produce because of their random microstructure and stochastic nature. Alternatively, lattice structures provide greater design freedom to achieve desired material properties by replicating mesoscale unit cells. Such complex lattice structures can only be manufactured effectively by additive manufacturing or 3D printing. The mechanical properties of lattice parts are greatly influenced by the lattice parameters that define the lattice geometries. To study the effect of lattice parameters on the mechanical stiffness of lattice parts, 360 lattice parts were designed by varying five lattice parameters, namely, lattice type, cell length along the X, Y, and Z axes, and cell wall thickness. Computational analyses were performed by applying the same loading condition on these lattice parts and recording corresponding strain deformations. To effectively capture the correlation between these lattice parameters and parts' stiffness, five machine learning (ML) algorithms were compared. These are Linear Regression (LR), Polynomial Regression (PR), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN). Using evaluation metrics such as mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE), all ML algorithms exhibited significantly low prediction errors during the training and testing phases; however, the Taylor diagram demonstrated that ANN surpassed other algorithms, with a correlation coefficient of 0.93. That finding was further supported by the relative error box plot and by comparing actual vs. predicted values plots. This study revealed the accurate prediction of the mechanical stiffness of lattice parts for the desired set of lattice parameters.

Polymer-Based Additive Manufacturing for Orthotic and Prosthetic Devices: Industry Outlook in Canada.

The conventional manufacturing methods for fabricating orthotic and prosthetic (O&P) devices have been in practice for a very long time. Recently, O&P service providers have started exploring different advanced manufacturing techniques. The objective of this paper is to perform a mini review on recent progress in the use of polymer-based additive manufacturing (AM) for O&P devices and to gather insights from the O&P professionals on the current practices and technologies and on the prospect of using AM techniques in this field. In our study, first, scientific articles on AM for O&P devices were studied. Then, twenty-two (22) interviews were conducted with O&P professionals from Canada. The primary focus was on five key areas: cost, material, design and fabrication efficiency, structural strength, functionality, and patient satisfaction. The cost of manufacturing the O&P devices using AM techniques is lower as compared to the conventional methods. O&P professionals expressed their concern over the materials and structural strength of the 3D-printed prosthetic devices. Published articles report comparable functionality and patient satisfaction for both O&P devices. AM also greatly improves design and fabrication efficiency. However, due to a lack of qualification standards for 3D printed O&P devices, 3D printing is being embraced more slowly in the O&P business than in other industries.

Valorization of Hemp Hurds as Bio-Sourced Additives in PLA-Based Biocomposites.

Sourced from agricultural waste, hemp hurds are a low-cost renewable material with high stiffness; however, despite their potential to be used as low-cost filler in natural fiber reinforced polymer biocomposites, they are often discarded. In this study, the potential to add value to hemp hurds by incorporating them into poly(lactic acid) (PLA) biopolymer to form bio-based materials for packaging applications is investigated. However, as with many plant fibers, the inherent hydrophilicity of hemp hurds leads to inferior filler-matrix interfacial interactions, compromising the mechanical properties of the resulting biocomposites. In this study, two chemical treatments, alkaline (NaOH) and alkaline/peroxide (NaOH/H2O2) were employed to treat hemp hurds to improve their miscibility with poly(lactic acid) (PLA) for the formation of biocomposites. The effects of reinforcement content (5, 10, and 15 wt. %), chemical treatments (purely alkaline vs. alkaline/peroxide) and treatment cycles (1 and 3 cycles) on the mechanical and thermal properties of the biocomposites were investigated. The biocomposites of treated hemp hurd powder exhibited enhanced thermal stability in the temperature range commonly used to process PLA (130-180 °C). The biocomposites containing 15 wt. % hemp hurd powder prepared using a single-cycle alkaline/peroxide treatment (PLA/15APHH1) exhibited a Young's modulus of 2674 MPa, which is 70% higher than that of neat PLA and 9.3% higher than that of biocomposites comprised of PLA containing the same wt. % of untreated hemp hurd powder (PLA/15UHH). Furthermore, the tensile strength of the PLA/15APHH1 biocomposite was found to be 62.6 MPa, which was 6.5% lower than that of neat PLA and 23% higher than that of the PLA/15UHH sample. The results suggest that the fabricated PLA/hemp hurd powder biocomposites have great potential to be utilized in green and sustainable packaging applications.