In this study, a two-stage, low-consistency (LC) refining process at the Holmen Braviken paper mill in Sweden was examined to evaluate the relationship between energy input, fibre distributions, and pulp properties, including handsheet properties. The LC refiners used thermo-mechanical pulp based on 100 % Norway spruce, with two specific energy levels: "low" (approximate to 80 kWh/adt) or "high" (approximate to 100 kWh/adt). All four permutations of these settings were examined. Overall, higher refining efficiency (measured by the increase in tensile index per applied energy) was observed in the first LC refiner stage than in the second. To further explore the impact of LC refining, pulp particle distributions were investigated. Samples from before, between and after the two LC stages were analysed using an optical fibre analyser, which provided detailed data on length-width-curl-fibrillation distributions. The impact of LC refining on these distributions was quantified using Kolmogorov-Smirnov statistics, highlighting statistically significant changes observed in the length and curl distributions. We investigated the correlation between energy input into the LC refiners and the impact on fibre distributions and handsheet properties. These insights underscore the effectiveness of our analytical approach and its potential for refining process control in mechanical pulping, offering a method for more targeted and efficient adjustments.

Water-soluble polymers are materials rapidly growing in volume and in number of materials and applications. Examples include synthetic plastics such as polyacrylamide, polyacrylic acid, polyethylene glycol, polyethylene oxide and polyvinyl alcohol, with applications ranging from cosmetics and paints to water purification, pharmaceutics and food packaging. Despite their abundance, their environmental concerns (e.g., bioaccumulation, toxicity, and persistence) are still not sufficiently assessed, especially since water soluble plastics are often not biodegradable, due to their chemical structure. This review aims to overview the most important water-soluble and biodegradable polymers, their applications, and their environmental impact. Degradation products from water-insoluble polymers designed for biodegradation can also be water soluble. Most water-soluble plastics are not immediately harmful for humans and the environment, but the degradation products are sometimes more hazardous, e.g. for polyacrylamide. An increased use of water-soluble plastics could also introduce unanticipated environmental hazards. Therefore, excessive use of water-soluble plastics in applications where they can enter the environment should be discouraged. Often the plastics can be omitted or replaced by natural polymers with lower risks. It is recommended to include non-biodegradable water-soluble plastics in regulations for microplastics, to make risk assessments for different water-soluble plastics and to develop labels for flushable materials.

This study examined the high-temperature stability of polyether ether ketone (PEEK) and polyphenylene sulfide (PPS) in an oxygenated environment. Both polymers were extrusion-coated onto copper wires for electrical insulation in traction motors. Accelerated testing using thermogravimetry and calorimetry showed that copper catalyzed thermal oxidation of PEEK (at very high temperature), which was accelerated by a lower molar mass of the PEEK and an increased copper-polymer contact area. Both techniques indicated a complex thermal oxidation pattern for both polymers. Notably, the presence of copper seemed to reduce/retard the degradation of PPS. Overall, both polymers demonstrated high oxidation resistance at elevated temperature in an air environment, indicating long service life in electric motor, excluding factors like moisture, oil spray cooling and Joule heating.

The study demonstrates a scalable and reproducible method for synthesising graphene oxide (GO) nanosheets from commercial carbon fibres derived from carbonised polyacrylonitrile (PAN) polymer. An exfoliation route with nitric acid allows for the preparation of monolayer GO nanosheets with a consistent thickness of 0.9 ± 0.2 nm, identical to the commercially available GO from mined graphite. The GO nanosheets exhibit distinct circular and elliptical shapes, in contrast to the polygonal and sharp-edged morphology of commercial GO. An extensive evaluation of acidic solutions and electrical potentials identified a narrow processing window critical for obtaining GO nanosheets sized 0.1–1 µm. An unexpectedly low 5% acid concentration was found to be the most effective, providing a balance between efficient exfoliation through synergistic acidic and electrochemical oxidation. The process provides a high yield of 200 mg of GO per gram of carbon fibre. Advanced characterisation using high-resolution electron and atomic force microscopy (HR-TEM/SEM/AFM), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and infrared spectroscopy (FTIR) provided detailed insights into the morphology, thickness, surface functionalisation, and chemical composition of the nanosheets. With its high yield, environmentally sound production, and versatility, the synthesised GO offers transformative potential for large-scale applications, including energy storage, advanced coatings, high-performance composites, water purification, and electronic devices.

This study focuses on the development of a compact model with improved interpretability compared to similar approaches, relating thermomechanical pulp (TMP) properties, quantified using a fiber analyzer, to Canadian standard freeness and handsheet properties. The data used in this study are obtained from TMP produced by a conical disc refiner. Utilizing the LASSO-regularized Latent Variable Regression (LASSO-LVR) model, we identified three key latent variables – representing shives content, fibrillation, and slender fines content – that accurately predict eight distinct handsheet properties. In a subsequent analysis, we investigated the linkage between refiner settings and Specific Refining Energy (SRE) to these key analyzer readings and, consequently, to handsheet properties. The inclusion of SRE as an internal state variable in the model significantly enhanced predictive accuracy, providing a foundation for more precise and energy-efficient control strategies in refining processes.

This study introduces a new semi-empirical power-law model for predicting electrospun fiber diameter (D), addressing key processing parameters. Polycaprolactone (PCL) fibers were produced using a solvent mixture of Trichloromethane (TCM), Dimethyl Formamide (DMF), and ethanol (EtOH). Systematic experiments validated an existing theoretical model and led to the development of a novel model: D ∼ (c1/2η1/3Q1/5X2/3)/(U2/3ω1/4I1/5). This model incorporates seven crucial parameters: viscosity (η), concentration (c), voltage (U), spinning distance (X), flow–rate (Q), current (I) and collector wheel rotation speed (ω). The model was validated through a partial factorial design experiment, proving to be a valuable and reliable tool for predicting fiber diameters and optimizing electrospinning processes. The ability to control fiber diameter is essential for tailoring electrospun fibers for various applications, including biomedicine, filtration, sensors, and lightweight materials.

Thermoplastic properties in cellulosic materials can be achieved by opening the glucose rings in cellulose and introducing new functional groups. Using molecular dynamics, we simulated amorphous cellulose and eight modified versions under dry and moist conditions. Modifications included ring openings and functionalization with hydroxy, aldehyde, hydroxylamine, and carboxyl groups. These modifications were analyzed for density, glass transition temperature, thermal expansivity, hydrogen bond features, changes in energy term contributions during deformation, diffusivity, free volume, and tensile properties. All ring-opened systems exhibited higher molecular mobility, which, consequently, improved thermoplasticity (processability) compared to that of the unmodified amorphous cellulose. Dialcohol cellulose and hydroxylamine-functionalized cellulose were identified as particularly interesting due to their combination of high molecular mobility at processing temperatures (425 K) and high stiffness and strength at room temperature (300 K). Water and smaller side groups improved processability, indicating that both steric effects and electrostatics have a key role in determining the processability of polymers.

In light of advancements in electronic skins (E-skins), their application in extreme environments poses significant challenges. Inspired by real human skin, we have developed a hierarchical structured electronic skin that utilizes flexible carbon fiber fabric as a framework. Copper nanoflakes and embedded sensors function as the neural layer, while Ethylene Vinyl Acetate acts as the dermal layer, and Polytetrafluoroethylene is employed as the epidermal layer. The reported E-skin demonstrates outstanding flexibility, excellent heat resistance, robust mechanical properties (fracture strength of 1600 MPa, Young's modulus approximately 3.8 GPa), exceptional bending/compression strain performance, excellent hydrophobicity (water contact angle of 120°), effective electromagnetic shielding performance (approximately 45 dB total shielding effectiveness for X-band), and electromagnetic wave absorption capability. Additionally, this E-skin possesses self-healing properties, capable of restoring to its original hydrophobic state within 30 s under a 9V voltage through the Joule heating effect, complemented by corresponding theoretical and mathematical modeling. This E-skin introduces a novel, environmentally friendly, and operationally simple strategy for enhancing the extreme environment resistance and durability of flexible devices.

In the pulp and paper industry, pulp testing is typically a labor-intensive process performed on hand-made laboratory sheets. Online quality control by automated image analysis and machine learning (ML) could provide a consistent, fast and cost-efficient alternative. In this study, four different supervised ML techniques—Lasso regression, support vector machine (SVM), feed-forward neural networks (FFNN), and recurrent neural networks (RNN)—were applied to fiber data obtained from fiber suspension micrographs analyzed by two separate image analysis software. With the built-in software of a commercial fiber analyzer optimized for speed, the maximum accuracy of 81% was achieved using the FFNN algorithm with Yeo–Johnson preprocessing. With an in-house algorithm adapted for ML by an extended set of particle attributes, a maximum accuracy of 96% was achieved with Lasso regression. A parameter capturing the average intensity of the particle in the micrograph, only available from the latter software, has a particularly strong predictive capability. The high accuracy and sensitivity of the ML results indicate that such a strategy could be very useful for quality control of fiber dispersions.

For wearable smart textile sensors, stability, accuracy and multi-functionality are key objectives. Achieving the optimal application requires delicately balancing the crucial physical properties of strain sensors, presenting a key technological challenge. This study addresses these challenges by presenting several properties and potential applications of a triple hierarchic polymeric knitted fabric. The fabric incorporates an internal conductive network constructed with silver nanowires (AgNWs) and polydopamine (PDA) coating on its outer surface. This innovative textile successfully strikes a balance between strain sensing and electromagnetic interference shielding while concurrently exhibiting biocompatibility and antimicrobial properties. Significantly, acknowledging the susceptibility of measurements from polymer-based strain sensor materials to time drift, we introduce both a modeling approach and a novel calibration technique. This advancement facilitates the generation of stable cyclic sensing signals, even under substantial deformations of up to 80 % at a high stretching speed. Importantly, it provides a practical solution for addressing signal drift observed in flexible sensors when utilized in environments characterized by long-term and large deformations.