Drying cellulose nanofiber (CNF)-based filaments remains a challenge in scalable production due to the strong water affinity of CNFs and the risk of thermal degradation. In this study, we investigate the structural and mechanical effects of thermal drying at 20, 60, 105, and 160 degrees C on TEMPO-mediated oxidized CNF (TCNF) filaments to determine the optimal drying conditions. Mechanical testing revealed an initial decline in elastic modulus and tensile strength from 20 degrees C to 105 degrees C, followed by a pronounced increase at 160 degrees C, reaching values comparable to those of individual CNFs. Spectroscopic and diffraction analyses (FTIR, XRD) showed a progressive increase in carbonyl content with drying temperature and a moderate decrease in crystallinity indices, while crystal size in the [200] direction increased. SEM and AFM imaging confirmed densification and surface rearrangement at elevated temperatures. These results indicated a dual effect of drying: Moderate heating degraded mechanical performance due to structural disruption, whereas high-temperature treatment enhanced inter-fibril bonding and co-crystallization, leading to superior strength. However, yellowing and partial chemical transformation began at 105 degrees C, suggesting a narrow window between beneficial densification and early degradation. Our findings offer insights into balancing structural integrity and production efficiency for robust, bio-based filament manufacturing

Surface-enhanced Raman scattering (SERS) is a highly advantageous analytical technique for detecting trace biological and chemical compounds. However, significant challenges remain in the cost-effective fabrication of large-area and homogenous SERS substrates. A simple and scalable approach utilizing a layer-by-layer spray deposition followed by thermal annealing is proposed to fabricate cellulose nanofibril (CNF) films loaded with gold nanoparticles (Au NPs) and graphene oxide (GO) hybrids as SERS substrates. These hybrid 3D structures comprising CNF/Au NPs/GO significantly enhance SERS sensitivity by both electromagnetic enhancement and chemical enhancement. Incorporating CNF as a 3D network enables a more uniform distribution of Au NPs/GO. Thermal annealing further induces hotspots. For instance, the annealed CNF/Au NPs/GO hybrid thin films achieve a detection limit of 1.0 x 10^-13 m and a high enhancement factor of 4.97 x 10¹¹ for Rhodamine 6G. Grazing incidence small-angle X-ray scattering combined with nano-Fourier-transform infrared spectroscopy is first used to confirm the combined Raman enhancement mechanism of localized surface plasmon resonance and interface charge transfer with high spatial resolution. Therefore, the proposed methodology establishes a robust framework for the scalable fabrication of ultrasensitive SERS substrates.

The world's strongest bio-based filament is currently produced from the wet spinning of cellulose nanofibrils. Such filaments could provide sustainable alternatives to currently available reinforcement fibers for high performance composites. Finding the weakest point of such filaments is of critical importance to their final application. However, what constitutes the weakest point in these filaments has yet to be determined with any certainty. Laser diffraction in conjunction with the Fraunhofer (single-slit) approximation could provide a rapid, nondestructive defectoscopy technique. Finding the thinnest point is the most accurate estimate of the breakpoint, with a mean distance-to-breakpoint of 1100 +/- 200 mu m, whereas the most precise determination of the weakest point is establishing which point is the least slit-like (48% of all cases). Combining width and propensity to be more or less slit-like was attempted to provide an accurate and precise metric ('the failure factor'). With an accuracy of 1000 +/- 200 mu m, this is the best possible estimate using the methodology presented here. The results indicate a need for further refinement of the method. Incorporating machine learning algorithms would increase reliability by circumventing the need for approximations. Performing high-resolution tomograms of the samples to take into account the cross-sectional circularity could be implemented as an additional in-depth secondary method. With the technique already presenting advantages in terms of speed and cost compared to other methods, e.g., electron microscopy, such instruments could be integrated into a production line, providing real-time defectoscopy and quality control.

X-rays are commonly used in imaging experiments due to their penetration power, which enables non-destructive resolution of internal structures in samples that are opaque to visible light. Time-resolved X-ray tomography is the state-of-the-art method for obtaining volumetric 4D (3D + time) information by rotating the sample and acquiring projections from different angular viewpoints over time. This method enables studies to address a plethora of research questions across various scientific disciplines. However, it has several limitations, such as incompatibility with single-shot experiments, challenges in rotating complex sample environments that restrict the achievable rotation speed or range, and the introduction of centrifugal forces that can affect the sample's dynamics. These limitations can hinder and even preclude the study of certain dynamics. Here, we present an implementation of an alternative approach, X-ray multi-projection imaging (XMPI), which eliminates the need for sample rotation. Instead, the direct incident X-ray beam is split into beamlets using beam splitting X-ray optics. These beamlets intersect at the sample position from different angular viewpoints, allowing multiple projections to be acquired simultaneously. We commissioned this setup at the ForMAX beamline at MAX IV, the first operational diffraction-limited storage ring. We present projections acquired from two different sample systems - fibers under mechanical load and particle suspension in multiphase flow - with distinct spatial and temporal resolution requirements. We demonstrate the capabilities of the ForMAX XMPI setup using the detector's full analog-to-digital converter range for the relevant sample-driven spatiotemporal resolutions: (i) at least 12.5 kHz frame rates with 4 mm pixel sizes (fibers) and (ii) 40 Hz acquisitions with 1.3 mm pixel sizes (multiphase flows). The presented setup and results form the basis for a permanent XMPI endstation at ForMAX, offering flexibility to adapt to the spatiotemporal requirements of the studied dynamics.

Nonwoven fibre networks underpin filtration, insulation and geotextiles, where liquid uptake, redistribution and release govern performance. In needle-punched felts, barbed needles mechanically entangle fibres and partially reorient them towards the thickness direction (z), creating out-of-plane “pillars” and heterogeneity. While mechanical and structural consequences of needling are well documented, dynamic z-direction transport in partly saturated networks remains difficult to access due to opacity and sub-second timescales. Here we combine micro-CT (μCT) of dry structure with time-resolved X-ray radiography during droplet addition to quantify through-thickness transport as a function of saturation and needling intensity, using a compact Washburn-type descriptor for dynamics. Results show an exponential dependence of z-directional liquid transport on saturation, consistent with previous models for in-plane relative permeability of nonwoven networks. Additionally, increased needle-punch intensity reorients fibres towards the z-direction, forming preferential flow pathways that enhance through-thickness transport, even as single-phase permeability decreases. These findings underscore needle-punch as a key design parameter for tuning liquid transport in nonwoven fibre networks. The approach provides an experimental and modelling framework for dynamic, capillarity-driven transport in opaque fibrous materials.

Even at very low concentrations, the rheology of dispersions of charged semi-flexible nanofibers differs from the rheology of the pure liquid, given the fiber charge, morphology and interactions. At the nanoscale, the thermal motion of fibers is driven by the collective motion of the solvent molecules, but to what extent does the fiber presence and motion affect the self-diffusion of the liquid molecules? By studying the self-diffusion of water in dilute nanofiber dispersions using experiments and simulations, we can show that the interplay of fiber charge and motion on water mobility is more significant than the effect of the excluded volume caused by the charged particles.

Cellulose Nanofibrils (CNFs), highly present in nature, can be used as building blocks for future sustainable materials, including strong and stiff filaments. A rheo-optical flow-stop technique is used to conduct experiments to characterize the CNFs by studying Brownian dynamics through the CNFs' birefringence decay after stop. As the experiments produce large quantities of data, we reduce their dimensionality using Principal Component Analysis (PCA) and exploit the possibility of visualizing the reduced data in two ways. First, we plot the principal components (PCs) as time series, and by training LSTM networks assigned for each PC time series with the data before the flow stop, we predict the behavior after the flow stop (Bragone et al., 2024). Second, we plot the first PCs against each other to create clusters that give information about the different CNF materials and concentrations. Our approach aims at classifying the CNF materials to varying concentrations by applying unsupervised machine learning algorithms, such as k-means and Gaussian Mixture Models (GMMs). Finally, we analyze the Autocorrelation Function (ACF) and the Partial Autocorrelation Function (PACF) of the first principal component, detecting seasonality in lower concentrations.

A calculation method has been derived to predict the void volume loss of dynamically loaded structured composites commonly used as press belts in paper manufacturing. The method is based on a viscoelastic model that uses two serial generalised three-parameter Maxwell models and allows for predicting the void volume loss as a function of the applied external load and load rate. Optical verification of the void volume losses revealed that the method accurately calculates these volume losses that appear in the structure due to viscoelastic compression. Applying it to different composite specimen types makes it possible to quantify the influence of matrix material formulation, geometrical structure, temperature and saturation conditions on the void volume loss of dynamically loaded composites. As a result, the matrix material formulation of the polyurethane matrix is identified as the key parameter influencing the void volume loss.

Shoe press belts contribute significantly to the overall dewatering performance in the press section of a paper machine. Within the shoe press nip, the press belt faces a dynamic and multidimensional load that mainly leads to a compression of the structure. As this will cause a loss in void volume, knowledge of the dynamic compression characteristics of shoe press belts is crucial for optimized dewatering. A novel method was developed to examine the dynamic compression characteristics of grooved polyurethane press belts. Therefore, an experimental setup allowing realistic boundary conditions to test specimens was placed in a servo-hydraulic testing machine. Press belt specimens with different matrix material formulations and groove patterns were tested under varying load rates equivalent to different paper machine operational speeds. The results showed an evident sensitivity of the dynamic compression stiffness to the operational speed of the paper machine. This behavior was seen to be more sensitive to changes in the matrix material formulation than to adaptions of the groove pattern. As a result, the compression of the press belt within a shoe press nip is not only influenced by the peak pressure within the shoe press nip but also depends on the operational speed of the paper machine. Application: This study helps readers understand the impact of paper machine speed on the compression of shoe press belts, allowing them to choose a shoe press belt that provides optimized dewatering performance under specific operational conditions.

Lignin nanoparticles (LNPs) are gaining increasing interest for applications in various fields, where the particle homogeneity, morphology, and surface properties are critical for performance. In this study, lignin obtained via kraft process from spruce and eucalyptus was employed as precursor for the fabrication of lignin nanoparticles with tunable physicochemical properties. Linear ester groups with varying chain lengths were introduced to systematically investigate the effects of the hydrophobic moiety distribution on lignin nanoparticle formation via solvent-shifting self-assembly. Results demonstrated that esterification-induced structural changes altered the balance of key noncovalent interactions (hydrogen bonding, π–π stacking, and hydrophobic interactions), which collectively governed the self-assembly process, with longer ester chains promoting compact particles with hydrophobic surfaces. By directly linking molecular-level modification of lignin to alterations in the inter- and intramolecular interactions driving the self-assembly of nanoparticles, this study provides a mechanistic framework for the rational design of lignin nanoparticles through controlled chemical modification, thereby expanding their application flexibility.