Textile Research Institute

Purpose The COVID-19 pandemic revealed the acute vulnerability of the global apparel supply chain. While the industry showed capacity to recover, resilience practices often protected some actors while shifting risks onto others. This research examines how resilience practices were perceived across brands, manufacturers, and suppliers, and how these affected workers in developing countries. By analysing vulnerability factors, resilience capabilities, and strategies, the article contributes to building an apparel supply chain that is not only resilient but also equitable and sustainable. Design/methodology/approach We adopted a qualitative, interpretive case study. Semi-structured interviews were conducted with 12 influential stakeholders representing brands, manufacturers, sector associations, and international organisations. Data were inductively coded to explore perceptions of vulnerabilities, responses, and resilience practices during and after COVID-19. Findings The impacts of COVID-19 were unevenly distributed. Brands and retailers absorbed shocks by cancelling orders, deferring payments, or demanding discounts, creating severe consequences for apparel manufacturers and workers. Manufacturers demonstrated adaptability, diversification, and digital innovation, yet these capabilities only partially offset cascading vulnerabilities. Findings emphasise that resilience for one tier often becomes vulnerability for another. Practical implications The research provides guidance for managers and policymakers. Brands and retailers must strengthen collaborative governance, responsible sourcing, and end-to-end visibility while manufacturers and suppliers should pursue digitalisation, diversification and agility to sustain operations. Originality/value Unlike previous studies centred on workers' experiences, this research captures expert perspectives across tiers, offering systemic insights into resilience as a relational and distributive process. It advances a framework where resilience is measured not only by recovery but also by equity and justice.

Textiles and the textile industry play a specialized, rehabilitation-focused role in combating addiction, primarily by offering vocational training, fostering creative expression, and promoting social reintegration.While they do not directly treat the chemical dependency, they provide essential structural support for recovery.Key roles of textiles in this context include Vocational Training and Skill DevelopmentPrograms like the "Blixtjobb" (Flash Jobs) in Sweden, in collaboration with Stadsmission, utilize tailor shops as part of a "work-first" approach.Individuals recovering from addiction, such as those transitioning from street life, are trained in sewing and garment repair, providing them with a routine and marketable skills.

Lead-free halide perovskites have drawn considerable interest, owing to their low-toxicity and favorable photophysical characteristics. However, achieving efficient near-infrared (NIR) emission often suffers from a trade-off between the red shift and quantum yield. Herein, we report a synergistic host-dopant strategy in zero-dimensional Cs2-xRbxInBr5·H2O perovskites. Controlled Rb+ alloying induces lattice contraction, which unexpectedly weakens electron–phonon coupling and suppresses nonradiative decay, leading to a high photoluminescence quantum yield (PLQY) of 53.2%. Subsequently Mn2+ doping further passivates defect states, boosting the PLQY to 67.5%. Density functional theory calculations and temperature-dependent spectroscopy elucidate the role of the lattice strain in regulating self-trapped exciton emission. A prototype NIR phosphor-converted light-emitting diode (pc-LED) fabricated from the optimized material demonstrates a promising performance in night-vision imaging and plant growth applications. This work provides a viable design strategy for efficient and stable NIR phosphors via a coupled lattice and defect engineering.

Structural colors have attracted significant attention due to their unique advantages, including high color saturation, resistance to fading and environmental friendliness. However, most current fabrication strategies rely on tuning nanoscale features, typically by preparing nanospheres of varying sizes to achieve different structural colors, resulting in complex and laborious processes. To address this challenge, this study employs the principle of additive color mixing to simply and effectively fabricate structural-color textiles with a low angular dependency across the entire visible spectrum. Specifically, this goal was achieved by pairwise mixing three distinct sizes of silica (SiO2) nanospheres─each size corresponding to a structural-color output of red, green, or blue─in predetermined ratios, followed by their deposition onto textile substrates via gravitational sedimentation. Precise control over the nanosphere size directly determines the final primary-color output. However, excessive differences in the particle size between nanospheres can lead to poor color saturation. To optimize the low saturation resulting from mixed nanospheres, the process for producing high-saturation structural-color textiles based on multicomponent nanosphere synergy was refined by incorporating carbon black (CB) and introducing a fourth SiO2 nanosphere size that exhibits yellow color. Furthermore, to enhance the practicality of the nanostructured-color layer, a waterborne polyurethane (WPU) solution was introduced to strengthen the adhesion of the SiO2 nanospheres to the textile surface. This significantly improved the color fastness and color stability of the fabrics while preserving the integrity of the nanoscale structural arrangement of the SiO2 nanospheres. The developed nanoscale structural-color coatings exhibit promising application potential in eco-friendly nanocomposite materials and optical anticounterfeiting based on nanophotonic effects.

Complex wastewater containing oils and dyes poses significant ecological threats. Conventional membrane separation processes often suffer from limited permeability-selectivity trade-offs, susceptibility to fouling, and inability to degrade soluble organic pollutants. To address these critical challenges, multifunctional membranes were engineered through a synergistic combination of centrifugal spinning and interfacial assembly. Core–sheath polyacrylonitrile/zein fibrous membranes were first fabricated via one-step centrifugal spinning, serving as a robust and hierarchically structured support layer. Subsequently, bayberry-like Ag/BiOCl/Bi2WO6 ternary heterojunction photocatalysts were in situ grown onto this layer, achieving seamless integration of the substrate and photocatalytic layer through the unique interfacial interactions mediated by the zein sheath. This ingenious design not only endowed the membrane with ultrahigh flux and satisfactory separation efficiency for both oil–water mixtures (11970 L·m–2·h–1, 99.5%) and emulsions (2148 L·m–2·h–1, 99.3%) but also enabled rapid and efficient photocatalytic degradation of organic contaminants. Furthermore, the composite membrane exhibits good chemical stability and recycling performance, maintaining high efficiency even after multiple cycles or under harsh chemical conditions. This work proposes a scalable strategy that integrates oil/water separation and pollutant degradation, providing a viable technological platform for wastewater treatment.

<h2>Abstract</h2><h3>Background</h3> Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, increases risks of stroke, heart failure, and mortality. Short-term electrocardiographic (ECG) monitoring often misses paroxysmal or asymptomatic AF, underscoring the value of textile ECG platforms for continuous real-world rhythm assessment. <h3>Objective</h3> To develop and clinically validate a lightweight, interpretable algorithm for AF detection and burden estimation using textile ECG recordings acquired during daily life. <h3>Methods</h3> We developed Textile AF-Tracker (TAF-Tracker), an RR-interval-based machine learning pipeline using entropy, Lorenz-plot, statistical, and fragmentation features with ECG quality metrics to detect AF in 60-beat segments. Multiple classifiers (Random Forest, XGBoost, Support Vector Machine, logistic regression, and a threshold-based method) were trained on public AF datasets and long-term 3-lead textile ECG recordings (SKIIN™). Data were split by subject into training, validation, and test sets to ensure unseen data were tested. <h3>Results</h3> Across public long-term AF datasets, Random Forest and XGBoost achieved 96%-99% accuracy, 95%-99% sensitivity, and 96%-99% specificity. In 14-day textile ECG recordings from 47 AF patients, XGBoost reached 98.4% accuracy (sensitivity 96.1%, specificity 98.7%). AF burden showed a median absolute error of 1.3% (IQR 0.7%-1.8%). In healthy and noise-stress data, specificity remained ≥99%, even during activity. <h3>Conclusions</h3> A lightweight RR‐interval-based machine learning algorithm on textile ECG accurately detects AF and quantifies burden in long-term recordings with minimal error. Combined with a comfortable multi-lead textile platform, it provides a practical alternative to Holter monitors and implantable devices for continuous AF surveillance and treatment assessment.

This research presents a comprehensive investigation into cost-effective optimization strategies for yarn sizing, with a primary focus on enhancing process efficiency and reducing operational costs within the textile manufacturing sector. Through a combination of field surveys, in-depth interviews with industry professionals, and comparative analyses of both traditional and contemporary sizing methodologies, the study systematically identifies the critical factors influencing sizing performance and fabric quality. Key parameters under scrutiny include the selection of sizing materials, size pick-up percentage, viscosity of sizing baths, and the uniformity of application, all of which directly impact yarn strength, smoothness, hairiness, and weaving efficiency. The research further evaluates the increasingly important role of artificial intelligence (AI), automation, and data analytics in optimizing sizing processes. These technologies are shown to enable more precise control over process variables, reduce waste, and support data-driven decision-making for continuous improvement. In addition, the study explores sustainable alternatives to conventional sizing agents, highlighting the environmental and economic benefits of adopting eco-friendly materials and reducing chemical consumption without compromising yarn performance. Findings demonstrate that optimizing sizing formulations and process parameters can significantly enhance weaving efficiency exemplified by a notable reduction in machine stops and warp breaks while simultaneously lowering production costs and minimizing environmental impact. The study concludes with actionable recommendations for textile manufacturers to adopt advanced optimization strategies, leverage AI and automation, and integrate sustainable practices into their sizing operations. These insights provide a roadmap for future research aimed at further improving textile manufacturing efficiency and sustainability.

Abstract The increasing reliance on X-rays and gamma radiation in healthcare has given rise to a demand for shielding materials that are lightweight, flexible, and free from toxicity. These materials are being developed as substitutes for conventional lead aprons, which are bulky, rigid, and hazardous. In this research, woven textiles produced from hybrid yarns containing Haynes 25/L625 alloy wires and recycled cotton/polyester blends were investigated as a candidate solution, focusing on both radiation attenuation and user comfort. Three weave structures-plain, 3/1 twill, and 5-harness satin-were manufactured by interlacing alloy wires with cotton/polyester yarns. The gamma-ray shielding capability of the materials was examined across a range of 15 photon energies, from 32 to 1408 keV, utilizing a NaI(Tl) scintillation detector. The evaluation encompassed various parameters, including transmission, absorption, linear and mass attenuation coefficients, half-value layer, and shielding effectiveness. A comprehensive characterization of the material’s comfort-related properties was conducted, encompassing parameters such as air permeability, which was measured in accordance with the ISO 9237 standard, porosity, and thermal behavior. The satin weave, which incorporates the highest proportion of alloy, exhibited enhanced attenuation, particularly at lower photon energies, with a mass attenuation coefficient of 6.649 cm 2 /g at 32 keV. The twill fabric demonstrated improved performance at intermediate and higher energies, exhibiting a linear attenuation coefficient of 0.291 cm −1 at 356 keV. In comparison, the plain weave provided the least effective protection. In terms of comfort, the satin and twill structures exhibited higher breathability and porosity, with values of 22% and 19%, respectively, attributable to their more open geometries. In contrast, the plain weave demonstrated reduced air permeability, with 12% porosity, but enhanced thermal dissipation efficiency. The satin weave is optimal for achieving maximum attenuation, while the twill weave provides a balanced compromise with high performance.

The development of high-performance biodegradable polymers that simultaneously achieve petrochemical-plastic-like mechanical properties and controlled environmental degradability remains an unsolved challenge in sustainable materials science. We present an [(A)xB]n alternating copolyester platform engineered through a precision cascade polycondensation-ring-opening polymerization (PROP) strategy, featuring (i) ultrashort succinic acid (SA) soft segments (B), (ii) architecturally tuned hard-segment ((A)x) lengths, and (iii) spherulite-size-modulated semicrystalline morphology. This triple-design strategy yields unprecedented property combinations: 61 MPa yield strength and 428% elongation at break, matching PET’s elastic-plastic behavior (<300% strain) while exhibiting superior marine degradability (60% mass loss in 90 days across lake/seawater). The material further enables closed-loop chemical recycling to high-purity glycolic acid, establishing a new paradigm for circular polymer design that addresses both microplastic generation and end-of-life management challenges.