The use of the three-dimensional (3D) printing technique is gaining popularity due to its ability to produce products with minimum waste. 3D printing can be used to add polymers onto woven fabrics to produce novel structures. This research work concentrated on the study of the fabric properties affecting the adhesion of Polylactic Acid (PLA) polymer onto selected fabrics. Different fabrics made from cotton, polyester and acrylic, were selected and using 3D printing, PLA polymer was printed onto the fabric surface. Regression models were used to study the effect of selected fabric properties on the adhesion of PLA polymer onto the woven fabrics. The results obtained in this research work indicated that fabric areal density, warp count (Tex), weft count (Tex), fabric thickness and fabric handle indicated a positive correlation with adhesion of PLA onto woven fabrics. On the other hand, warp ends/inch and weft picks/inch showed a negative correlation with the adhesion of PLA polymer onto woven fabrics.

Various electrospinning techniques can be used to produce nanofiber mats with randomly oriented or aligned nanofibers made of different materials and material mixtures. Such nanofibers have a high specific surface area, making them sensitive as sensors for health monitoring. The entire nanofiber mats are very thin and lightweight and, therefore, can be easily integrated into wearables such as textile fabrics or even patches. Nanofibrous sensors can be used not only to analyze sweat but also to detect physical parameters such as ECG or heartbeat, movements, or environmental parameters such as temperature, humidity, etc., making them an interesting alternative to other wearables for continuous health monitoring. This paper provides an overview of various nanofibrous sensors made of different materials that are used in health monitoring. Both the advantages of electrospun nanofiber mats and their potential problems, such as inhomogeneities between different nanofiber mats or even within one electrospun specimen, are discussed.

Very well into the dawn of the fourth industrial revolution (industry 4.0), we hardly distinguish between what is artificial and what is natural (e.g. man-made virus and natural virus). Thus, the level of discombobulation among people, companies or countries is indeed unprecedented. The fact that industry 4.0 is explosively disrupting or retrofitting each and every industrial sector, makes industry 4.0 the famous buzzword amongst researchers today. However, the insight of industry 4.0 disruption in the industrial sectors remains ill-defined in both academic and non-academic literature. The present study aimed at identifying industry 4.0 neologisms, understanding the industry 4.0 disruption and illustrating the disruptive technologies convergence in the major industrial sectors. A total of 99 neologisms of industry 4.0 were identified. Industry 4.0 disruption in Education industry (Education 4.0), Energy industry (Energy 4.0), Agriculture industry (Agriculture 4.0), Healthcare industry (Healthcare 4.0), and Logistics industry (Logistics 4.0) are described. The convergence of 12 disruptive technologies including 3D printing, Artificial intelligence, Augmented reality, Big Data, Blockchain, Cloud computing, Drones, Internet of things, Nanotechnology, Robotics, Simulation and Synthetic biology in agriculture, healthcare and logistics industries are illustrated.

Textile materials have been combined with polymers using 3D printing technology, thus producing structures with novel properties. The aim of this study was to use statistical methods to determine the effect of 3D printing machine parameters on the mechanical properties of cotton fabrics combined with polylactic acid. Polylactic acid was printed on a cotton fabric using an Athena Fused Deposition Modelling 3D printer. The effect of extrusion temperature, printing speed, fill density and model height on adhesion force before and after washing was investigated. A study of the tensile strength was also undertaken using a central composite rotatable design and regression analysis. The experimental data were used to develop regression models to predict the properties of the cotton/ polylactic acid structures. The model for adhesion force before washing yielded a coefficient of determination (R²) value of 0.75 and an optimum adhesion force of 50.06 N/cm. The model for adhesion force had an R² value of 0.84 and an optimum adhesion force of 42.91 N/cm and showed that adhesion force reduced after washing. Adhesion forces before and after washing were both positively correlated to extrusion temperature. However, they reduced with an increase in printing speed and model height. A positive correlation exists between tensile strength and temperature, while a negative correlation exists between tensile strength and printing speed and model height. From the results of this study, it was concluded that 3D printing parameters have an effect on the properties of the structures.

The functionalization of textiles with nanomaterials through green synthesis offers a promising pathway for sustainable material innovation. This study explores the in situ green synthesis of silver nanoparticles (AgNPs) onto cotton fabrics using Solanum tuberosum (potato) peel extract as a natural reducing and stabilizing agent. The synthesis conditions were optimized by varying silver nitrate concentration, extract volume, temperature, pH, and reaction time, after which the optimized protocol was applied for fabric treatment. The presence and distribution of AgNPs were confirmed through UV-Visible spectroscopy, Fourier-transform infrared spectroscopy, scanning electron microscopy and dynamic light scattering. The treated fabrics demonstrated strong and durable antibacterial performance, with inhibition zones of 23 ± 0.02 against Escherichia coli and 16 ± 0.01 against Staphylococcus aureus. Notably, antibacterial activity was retained even after 20 washing cycles, demonstrating the durability of the treatment. Mechanical testing revealed a 32.25% increase in tensile strength and a corresponding 10.47% reduction in elongation at break compared to untreated fabrics, suggesting improved durability with moderate stiffness. Air permeability decreased by 8.8%, correlating with the rougher surface morphology observed in Scanning Electron Microscopy images. Thermal analysis showed a decrease in thermal stability relative to untreated cotton, highlighting the influence of AgNPs on degradation behavior. Overall, this work demonstrates that potato peel waste, an abundant and underutilized biomass, can be used as a sustainable source for the green synthesis of AgNP-functionalized textiles. The approach provides a cost-effective and environmentally friendly strategy for developing multifunctional fabrics, while supporting circular economy goals in textile engineering.

The idea of 3D printing on textile fabrics was first mentioned around 10 years ago and has been investigated in detail since. Originally aimed at opening new design possibilities, combining 3D printing with textile substrates has shifted towards a new method to prepare composites with defined mechanical and other physical properties. The main problem of fused deposition modelling (FDM; also referred to as material extrusion (MEX) according to ISO/ASTM 52900) is printing on textile fabrics, where the frequently insufficient adhesion between both materials has not been fully resolved. For this reason, a few attempts have been made to combine other additive manufacturing methods with textile fabrics. While the principle possibility of using stereolithography (SLA) on textile fabrics was demonstrated a few years ago, PolyJet modelling (PJM) has only recently proven to be applicable for direct printing on textile materials. Here, we present the first study of printing MED610 medical resin on different fabrics. We show that a higher textile fabric surface roughness generally increases the adhesion of the printed material, while a higher hydrophobicity is disadvantageous. We also tested the influence of textile substrates on the porosity of the MED610 surface, as this parameter can influence a material’s potential use in tissue engineering and other biomedical applications.