Natural keratin fibers, such as wool, possess a complex hierarchical structure that governs their mechanical properties and surface energy. However, the extent to which these characteristics are influenced by combined contributions of structural variations (e.g., fiber diameter, intermediate filament (IF) packing) and chemical composition (e.g., disulfide bond density) remains poorly understood. In this study, we investigate wool fibers from five sheep breeds (Merino, Polwarth, Cheviot, Eider, and Devon) to elucidate how these factors influence viscoelasticity and surface interactions. Using a multimodal approach integrating interfacial and bulk characterization methods, including inverse gas chromatography (IGC), atomic force microscopy-infrared spectroscopy (AFM-IR), X-ray photoelectron spectroscopy (XPS), uniaxial tensile testing, and synchrotron small-angle X-ray scattering (SAXS), we show that the nanometer-thick 18-methyleicosanoic acid (18-MEA) layer is consistently present across all wool types and plays a key role in governing hydrophobicity and surface heterogeneity. A controlled isothermal treatment at 200 °C, designed to cleave disulfide bonds, results in a nearly 40% reduction in specific surface area across all fiber types, accompanied by a significant decrease in tensile strength and 80% reduction in elongation at break for Merino and Devon wool, but limited influence on the mechanical properties of Eider fibers. Furthermore, rate-dependent tensile testing within the elastic regime reveals distinct viscoelastic responses among the fiber types, suggesting that the sulfur-rich protein matrix surrounding IFs and its structure contribute actively to stress partitioning. Altogether, when combined with conclusions from SAXS measurements of IF spacing, our work offers compelling insights into the role of the keratin-associated protein (KAP) matrix in shaping wool fiber mechanics. Differences in mechanical behavior among wool types, despite similar IF spacing or sulfur content, highlight the importance of matrix composition and cross-linking density, suggesting that the molecular architecture of the KAP network may be a dominant factor in determining fiber performance.

Bio-inspired all-wool keratin composites: A self-reinforcing strategy toward sustainable high-performance materials.

Wool is one of the most widely used proteinic material for textile products due to its outstanding desirable properties including excellent thermal insulation, breathability, flame retardancy and comfort properties. Moreover, wool has shape memory capability, so it is good candidate for thermo-regulating clothes. However, wool fibers have a surface structure of overlapping cuticle cells known as scales which significantly affect fiber properties. This paper investigated the appearance, strength, extension and the shape memory behavior of the wool yarn and also the wool rib knitted fabric before and after descaling its cuticle cells using calcium carbonate nano powder (CCNP) powder with the concentration of 2 g/l, 5 g/l, and 10g/l in ultrasonic bath. The shape memory behavior of wool yarn, and rib knitted fabric were examined by changing between the warm-humid (temperature of 28°C; humidity of 90%) and the cold-dry condition (temperature of 8oC; humidity of 20%). The results showed that the increase of CCNP concentration improved the descaling effect, which resulted in less sharp morphology of scales on the wool fiber surface. Wool yarn breaking strength and elongation tended to increase due to the increase of CCNP concentration, while the value of CV (%) decreased. Moreover, the results demonstrated that the length of wool yarn did not change much for both original and treated yarns while descaled fabric possessed higher shape memory ability than untreated fabric, especially in vertical direction with 100 % of the original value, and the horizontal shape memory ability was in range of 93.8 % to 97.6 %

A comprehensive monitoring of the status and economic dynamics of the Russian wool complex sectors under the pressure of sanctions and structural market deformation revealed a critical disparity between the high genetic potential of domestic sheep farming and the country’s disproportionately low share of global wool textile market, which exceeded USD 39 billion in 2024 with an annual growth rate of 3.2%. It was established that a disruption in the process chain at the primary processing stage leads to the export of low-value raw materials and a loss of up to 300-400% of the added value generated by foreign processors. The current profitability of wool production, with purchase prices of 15-100 rubles per kg, remains negative without government subsidies, posing a real threat of losing the gene pool of 51 sheep breeds. For the first time in Russian literature, a comparative expert assessment of the development of the industry sectors in Russia and leading countries is presented. It demonstrates the critical lag in the domestic certification and sales segment, which automatically discounts the export price of Russian wool by 20-30% due to quality risks. The economic efficiency of implementing a continuous “raw wool - single-carded sliver” technology without intermediate drying preserves the physical and mechanical properties of the fiber and increases the productivity of the final product by 2-2.5%. The necessity of applying the calculation formulas of international TEAM project for forecasting yarn yield is demonstrated. Strategic priorities for the development of the Russian wool complex include the creation of full-cycle industrial clusters in the Southern and North Caucasus Federal Districts and the launch of an exchange trading mechanism based on mandatory certification. The proposed approach will reduce logistics costs by 15-20% and facilitate large-scale import substitution of finished textile products, transforming the wool industry from a subsidized raw materials sector into a driver of high-value-added light industry.

There is a pressing need to understand the pathways oftextilefibers as anthropogenic pollutants in the environment. Current effortsto understand textile fiber pollution in waterways have relied onsurface-sampling methodologies without consideration for environmentalheterogeneity. Moreover, how nonplastic textile fibers behave in theenvironment is not known. Here, for the first time, we experimentallyquantify the role that fiber type (cotton, wool, polyester, and acrylic)and riverbed roughness (flat, fine gravel, and coarse gravel) haveon the vertical distribution of transported fibers using an experimental,recirculating flume. Analysis of the vertical profile distributionsof 18,793 cotton, wool, polyester, and acrylic fibers indicated thatbed substrate significantly altered fiber transport pathways, whichwas consistent across all tested fiber types. Our findings indicatethat surface-only sampling will substantially under-record fiber fluxes,but such biases did not differ between any tested fiber types. Ourfindings provide key insights into fiber/bed interactions and transportpathways and imply that current monitoring methodologies significantlyunderestimate lotic (and potentially lentic) populations of fibers.We argue that it is crucial to sample for all fiber types, throughoutthe water column in all riverbed types, to understand fully the scaleof riverine textile fiber pollution.

ABSTRACT Bio-based products are leading the way toward a more sustainable future. They are playing a key role in combating climate change and global warming, which are primarily driven by using fossil fuels. This study demonstrates the potential of Finola hemp residues as feedstock for acoustic insulation components to replace synthetic fibers. The use of these residue fibers improves the resource efficiency of the crop and contributes to a circular economy. To enhance the fiber properties, Finola hemp residues were combined with cottonized hemp, crossbred sheep wool and polylactic acid (PLA). Nonwovens were produced using needle punching and thermal bonding techniques. Extensive experiments revealed the correlation of fiber and fabric properties with the acoustic insulation properties of the nonwoven structures. The needle punched samples consisting of Finola hemp and cottonized hemp fibers showed the highest air flow resistances. Thus, a maximum sound absorption coefficient of 0.99 at 9150 Hz was reached. The study highlights that the high sound absorption coefficients were achieved due to the high density of the sample caused by a high proportion of short and fine fibers and strong compression through the needle punching process. Moreover, a high number of layers was correlated with good sound absorption properties.

Abstract This study investigates the development of bio-composites reinforced with sheep wool fibers, aiming to valorize animal-based natural resources for sustainable material applications. Wool fibers were Soxhlet-treated to enhance compatibility with a polypropylene matrix, and composites were fabricated by heated platen pressing followed by injection molding, with fiber loadings ranging from 5 to 30 wt.%. Mechanical characterization revealed a strong reinforcing effect, with the Young’s modulus increasing from 1,000 MPa (neat polypropylene) to 2,720 MPa at 30 wt.% treated fibers (87 % improvement). This stiffness enhancement, however, was accompanied by reduced ductility (from 7.5 % to 1.55 %) and a moderate decrease in tensile strength (22 %). Morphological scanning electron microscopy and chemical Fourier transform infrared analyses confirmed improved but primarily physical interfacial adhesion, while thermogravimetric analysis indicated sufficient thermal stability for industrial processing. These findings highlight the potential of Soxhlet-treated wool fibers as reinforcement for polypropylene, enabling the design of scalable, eco-friendly composites for automotive, construction, and packaging applications.

ABSTRACT Fiber content is one of the key indicators for evaluating fabric quality, and cashmere is much more expensive than wool due to its scarcity and excellent characteristics, leading to frequent adulteration. This study proposes a method that utilizes Near-Infrared (NIR) spectroscopy, and combining the Ivy (IVY) algorithm optimizes the Deep Hybrid Kernel Extreme Learning Machine (DHKELM) to enable the rapid and accurate prediction of multi-component fiber content in cashmere and wool blends. The study first prepared 21 different mixing ratios of cashmere and wool blend samples using the KBr tableting method and collected spectral data using an NIR spectrometer; the Iteratively Variable Subset Optimization (IVSO) algorithm was applied for band selection; Subsequently, the IVY-DHKELM quantitative model was constructed to independently predict the Cashmere Content (CC) and Wool Content (WC). Experimental results demonstrated that the IVY-DHKELM model prediction coefficients of determination (R2 p) of 0.9743 for CC and 0.9625 for WC on the test set, respectively. It has high prediction accuracy and reliability, and has important application value in quantitative analysis of fiber composition and detection of cashmere adulteration.

This study aims to examine the possibility of partially substituting glass fiber (GF) with sheep wool fiber (SWF) with the goal of developing environmentally sustainable hybrid polyester composites. This study investigated the mechanical properties (tensile, flexural, and impact), thermal properties, water absorption, and microstructures of hybrid composites. The targeted composites were fabricated via compression molding and contained a total fiber weight fraction of 10% (with varying proportions of GF and SWF). Initially, the surface chemistry, morphology, tensile properties, and thermal stability of SWFs were analyzed individually. In the case of the composites, the highest tensile strength was recorded for the 9GF1SWF (comprising 9 and 1 wt% GF and SWF, respectively) hybrid composite, which reached 14.09MPa (7.31% higher than 10GF0SWF). The 9GF1SWF sample also presented the highest amount of absorbed flexural energy prior to failure, 166 MJ/m3 (19.42% higher than 10GF0SWF), and the highest impact strength, 11.15 kJ/m2 (11.05% higher than 10GF0SWF). The TGA results revealed that the incorporation of SWF reduced the rate of thermal degradation as well as improved thermal stability of the hybrid composites, especially at high temperatures. The microstructural characteristics of the composites and their correlation with the mechanical properties, along with the various reinforcing mechanisms, were examined through scanning electron microscopy (SEM). In terms of water absorption, both the hybrid and polyester/glass composites exhibited comparable behavior, with similar absorption levels. In brief, the findings of this study suggest that sheep wool fibers may serve as a viable alternative to synthetic glass fibers.

ABSTRACT The accurate identification of wool and cashmere fibers is crucial for textile quality, yet hindered by their visual similarity and the scarcity of annotated microscopic images. While deep learning techniques offer a high-accuracy, cost-effective identification technique, they are still limited by challenges arising from insufficient data scale and the high acquisition costs of obtaining high-quality fiber images. Although data augmentation partially alleviates data scarcity challenges, classical image augmentation techniques remain limited in generating high-fidelity, diverse fiber images, particularly in low-texture regions. This paper proposes a Transformer-based frequency-domain adaptive diffusion model incorporating a novel Dual-Frequency Scaling Tanh layer. The proposed method was evaluated on 1,845 high-quality fiber images (15 classes) provided by a National Fiber Quality Supervision and Inspection Center. The proposed approach demonstrates superior performance, outperforming all state-of-the-art baselines. Compared to classical image augmentation methods, our approach achieves performance gains of +0.02 F1-Confidence and +1.88% mAP@0.5 in detection tasks, along with +0.05 F1-score, +4.83% precision, and +2.51% recall in classification tasks. These improvements demonstrate the method’s efficacy in generating high-fidelity, diverse data samples for intelligent fiber detection, while establishing an effective optimization strategy for deep learning model training. The source code is publicly available at https://github.com/zld-make.

Eco-friendly recovery and upcycling of silver and palladium through in situ adsorption–reduction using wool fibers

This study situates washed sheep-wool fibres as a sustainable reinforcement candidate for epoxy matrices and evaluates their mechanical response under tensile, flexural, compressive, and Charpy impact loading. The objective of this work is to assess whether short, washed sheep-wool fibres can function as a sustainable reinforcement for epoxy matrices, and to identify optimal fibre length–content windows that improve mechanical behaviour for engineering applications. Moulded–machined specimens were produced with fibre lengths of 3, 6, and 10 mm and contents of 1.0–5.0 wt.%, depending on the test; neat epoxy served as the reference. In tension, selected formulations—particularly 10 mm/1.5 wt.%—showed simultaneous increases in ultimate stress and modulus relative to the neat resin, corresponding to gains of about 10% in ultimate tensile stress and 50% in tensile modulus, at the expense of ductility. In flexure, the modulus decreases by roughly 15–35% compared with the matrix, whereas configurations with 3–6 mm at 2.5–5 wt.% raise the fracture stress by about 35–45% and improve post-peak resistance. In compression, reinforcement markedly elevates yield stress, with increases of up to about 160% at 3 mm/2 wt.%, while the ultimate strain decreases moderately. In Charpy impact, all reinforced materials underperform the resin, with absorbed energy reduced by roughly 75–93% depending on fibre length and content, with 3 mm/1 wt.% being the least affected. A two-factor analysis of variance (ANOVA) indicates that fibre length primarily governs tensile and compressive behaviour, while fibre content dominates flexural and impact responses. Overall, the findings support wool fibres as a viable reinforcement when length and content are optimized, pointing to their use in non-structural to semi-structural industrial components such as interior panels, housings, casings, protective covers, and other parts where moderate tensile/compressive performance is sufficient and material sustainability is prioritised.

Sustainable Water-Efficient Dyeing of Wool Fibers: Enhancing Fiber Protection and Maximizing Dye Fixation Rates

Protease Scale Peeling Treatment and Crosslinking Repair of Breaking Strength in Wool Fibers

Asbestos, mineral wool (MW), refractory ceramic fibres (RCF) and silica are among the most common exposures to mineral particles in the workplace. To study the effect of coexposure to asbestos and MW, crystalline silica or RCFs and the risk of lung cancer and mesothelioma. The Asbestos-Related Diseases Cohort is a surveillance programme in retired workers exposed to asbestos during their working life. Complete job histories were collected and occupational exposure to asbestos was assessed by an expert, while occupational exposure to MW, RCFs and silica was assessed using French job-exposure matrices. Cox proportional hazards models were used to estimate HR and 95% CI for lung cancer mortality and lung cancer incidence and for mesothelioma mortality or mesothelioma incidence. In this population of workers exposed to asbestos, in the mortality study, exposures to MW, crystalline silica and RCFs were not found to be associated with lung cancer after adjustment for smoking and asbestos, nor with mesothelioma after adjustment for asbestos. In the incidence study, there was an association between exposure to crystalline silica (ever exposed) and mesothelioma (HRa=1.75, 95% CI 1.17 to 2.62). Crystalline silica is not known to induce mesothelioma but coexposure to asbestos could increase the effect of asbestos on the mesothelial cells.

This article presents the development of nonwoven thermal insulation materials made from natural sheep wool, aimed at enhancing energy efficiency in construction. The study applies a mathematical experiment planning method (KONO-2) to assess the influence of technological parameters, such as fiber type, basis weight, and binder content, on the material properties. As a binder, bicomponent fibers composed of a polyester core and a polyethylene sheath were used, providing effective bonding between fibers and improving the structural integrity of the nonwoven fabric. Key performance indicators, including thermal conductivity, mechanical strength, elongation, and air permeability, were evaluated across a range of basis weights (200–300 g/m²) and bicomponent fiber contents (10–30%). The results demonstrate that materials made from fine wool exhibit lower thermal conductivity (0.0216 W/m·K) compared with those made from coarse wool (0.0312 W/m·K). The best insulation performance was achieved in samples containing 70% wool and 30% bicomponent fiber with a basis weight of 250 g/m². This study introduces an innovative approach to utilizing sheep wool waste for producing sustainable, energy-efficient insulation materials, offering a promising alternative to conventional synthetic insulations in the building industry.

The water vapor and air permeability properties of fabrics are the determining factors for thermal comfort. It is stated in the literature that the hygroscopic structure of wool fibre and the fibre surface properties improve the water vapor permeability property, thus increasing the sense of comfort. In this study water vapor and air permeability of 16 woollen fabric were investigated. It was shown that the effect of finishing process, weave type and raw material on air permeability is significant. In case of water vapor permeability, the effect of finishing process and weave type was found to be significant in the 95% confidence interval, while the effect of raw material was not found to be significant. Furthermore, permeability properties of woollen fabrics were predicted both multiple linear regression and artificial neural network. The R2 values of the models were 0.989 and 0.485 obtained with multiple linear regression and 0.988 and 0.773 obtained with artificial neural network, for air and water vapor permeability, respectively. Results of the artificial neural network were quite good especially for water vapor permeability.

With the continuous increase in global energy consumption and the escalating severity of climate change, the development of high-performance thermal insulation materials is crucial for reducing energy waste and carbon emissions. In this work, a facile method was proposed to prepare thermal-insulating glass fiber wool/methyltrimethoxysilane aerogel (GFWA) composites through vacuum-assisted impregnation. The obtained results indicated that GFWA composites exhibited excellent thermal insulation and hydrophobic properties, with GFWA-30 containing 30 wt.% glass fiber wool having a thermal conductivity of 35.3 mW/m·K and a water contact angle of 125.8°. Additionally, the Young’s modulus of this composite was 21.2% higher than that of MTMS aerogel. In terms of thermal safety performance, compared to methyltrimethoxysilane aerogel, the GFWA-30 composite showed reductions of 21.6%, 18.8%, and 27.95% in peak heat release rate, total heat release, and gross calorific value, respectively. This study offers a simple and feasible approach to fabricating high-performance thermal insulation materials, which display huge potential for widespread application in the fields of building insulation and other fields with thermal insulation requirements.

Mechanical textile recycling presents a sustainable alternative to linear “take–make–waste” models in the fashion industry. This study intended to develop yarns using textile-to-fiber mechanically recycled fibers. ReSpool mechanically recycled wool, cotton, polyester, silk, and rayon fibers from pre-consumer and post-consumer textiles were acquired and blended with new fibers at varying ratios (100% ReSpool fibers, 85% ReSpool fibers, and 65% ReSpool fibers) to make batts, which were spun into yarns. The yarns’ size (Tex), strength (breaking force and tenacity), elongation, and moisture regain were evaluated. ReSpool recycled fibers from both pre-consumer and post-consumer textiles can be used to produce yarns that have appropriate strength for weaving and knitting. It was possible to produce yarns from 100% ReSpool recycled wool, polyester, and silk fibers, but ReSpool recycled cotton and rayon fibers must be blended with new fibers to produce yarns. There was no significant difference among the percentage of ReSpool recycled polyester and cotton fibers in the yarns on the strength and elongation of the yarn. It is recommended to use the higher percentage of ReSpool recycled fibers in yarn development to maximize recycled material utilization.

Sarcoptic mange is one of the most common parasitic diseases in camels, caused by Sarcoptes scabiei var. cameli. Affected animals suffer production losses, and young animals may even die. Although the disease is highly contagious, some animals remain healthy despite being in the same environment as infected ones. The severity of infection also varies among individuals. However, a comprehensive genome-wide study to identify defence-related genes associated with mange resistance in camels has not yet been undertaken. Therefore, the present study was designed to investigate differential gene expression, single nucleotide polymorphisms (SNPs), and insertions/deletions (Indels) associated with natural resistance to Sarcoptes scabiei var. cameli infection in dromedary camels. Skin scrapings were collected from both infected animals and healthy animals within the same herd. RNA isolation and transcriptome analysis were conducted. The parasite-unaligned sequences were further analysed for SNPs, Indels, gene expression quantification, and differential expression. In total, 23,008 genes were analysed. Results showed that gene expression was relatively lower in the infected group (84.94%) compared to the healthy group (87.28%). The number of SNPs/Indels in exonic regions was higher in the infected group (5,538) compared to the healthy group (3,629). Among the upregulated genes, several were associated with inflammatory responses, adipogenesis, fibroblast growth, immune responses, inhibition of TNF-α and C-reactive protein, suppression of high glucose-induced NF-κB activity, apoptosis, autoimmunity, lipid metabolism, adipose lipolysis, blood clotting, cell movement, and tissue remodelling. Downregulated genes in infected animals were involved in processes such as cell cycle progression, locomotion in vertebrates, formation of a rigid and resistant hair shaft, conversion of upstream fatty acids into polyunsaturated fatty acids (PUFAs), renal function and hypertension biomarkers, wool and hair fibre formation, various cellular activities, renal cyst formation, congenital hepatic fibrosis, and immune responses. Further, several differentially expressed genes (DEGs), such as CXCL8, IDO1, IGFBP3, and KRTAP6-2, emerge as promising biomarkers for diagnosis, prognosis, and therapeutic targeting. These findings establish a transcriptomic foundation for future investigations and open avenues for developing molecular tools to improve disease management strategies in camels.