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.

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.

Efficient mechanical dewatering in paper manufacturing is essential for reducing energy consumption and enhancing operational efficiency. Practical observations indicate that press felt and roll cover structures significantly influence dewatering performance. While previous studies have focused on micro-scale stress variations at the paper web-press felt interface, this study extends the analysis to the press felt-roll cover interface. Using a custom dynamic compression setup, we investigate how different groove patterns impact press felt dewatering. The results show that macro-scale stress variations play a crucial role, with controlled mechanical inhomogeneities enhancing felt permeability. Through multivariate regression analysis, an optimized groove pattern is identified that improves dewatering by approximately 7 % under highly dynamic pressing conditions. These findings offer valuable insights into optimizing press felt and roll cover interactions, providing a methodology to enhance nip dewatering efficiency. The study highlights the need to tailor groove patterns to specific press felts to ensure optimal water flow under saturated conditions. This research contributes to improving paper machine performance by maximizing water removal while reducing energy consumption, supporting both economic and environmental sustainability in the industry.

Properties and functions of materials assembled from nanofibrils critically depend on alignment. A material with aligned nanofibrils is typically stiffer compared with a material with a less anisotropic orientation distribution. In this work, we investigate nanofibril alignment during flow focusing, a flow case used for spinning of filaments from nanofibril dispersions. In particular, we combine experimental measurements and simulations of the flow and fibril alignment to demonstrate how a numerical model can be used to investigate how the flow geometry affects and can be used to tailor the nanofibril alignment and filament shape. The confluence angle between sheath flow and core flow, the aspect ratio of the channel and the contractions in the sheath and/or core flow channels are varied. Successful spinning of stiff filaments requires: (i) detachment of the core flow from the top and bottom channel walls and (ii) a high and homogeneous fibril alignment. Somewhat expected, the results show that the confluence angle has a relatively small effect on alignment compared with contractions. Contractions in the sheath flow channels are seen to be beneficial for detachment, and contractions in the core flow channel are found to be an efficient way to increase and homogenise the degree of alignment.

The assertion of intrinsic material properties based on measured experimental data is being challenged by emerging sample synthesis protocols, which opens new avenues for discovering novel functionalities. In this study, we revisit one of the most widely studied strongly correlated materials of the early 2000s, NaxCoO2 (NCO). Leveraging the sensitivity of muon spin rotation and relaxation (μ+SR) measurements, we discern significant differences between NCO samples synthesized via conventional solid-state reaction (SSR) and our electrochemical reaction (ECR) approach. Contrary to SSR-synthesized Na0.7CoO2, which exhibits a nonmagnetic ground state, our ECR-derived sample showcases an antiferromagnetic (AF) order from x≥0.7, challenging established phase boundaries. We attribute the observed magnetic phenomena in ECR-NCO to long-range order of Na-ions and/or vacancies, as well as the inherent flexibility of the crystal framework. Our study holds implications for tailoring and optimization of next-generation devices based on layered materials.

The complex architecture of wood motivates studies of bioinspired materials that combine strength, toughness, and mechanical integrity. We explore the interplay between nanofiber alignment and molecular interactions in composite filaments formed from cellulose nanofibers (CNFs) and a dendritic polyampholyte, Helux. Helux enhances strength by 60% and increases toughness 5-fold through ionic bonding and thermal covalent cross-linking. However, wide-angle X-ray scattering (WAXS) reveals reduced nanofiber alignment in Helux-containing samples, resulting in a 25% decrease in stiffness-highlighting a trade-off between structural order and cohesion. Polarized optical microscopy (POM) and in situ small-angle X-ray scattering (SAXS) attribute this reduced alignment to enhanced rotary diffusion, driven by carboxylate groups of the Helux. With Helux, multivalent links across the nanofibers give a denser and tougher network with fewer voids. This behavior resembles lignin and hemicellulose interactions in wood, where flexibility and cohesion govern the performance.

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.

An experimental method was developed to examine the dynamic compression properties of structured polyurethane composites used as press belts within a shoe press of a paper machine. The objective was to investigate the influences of the geometrical surface structure and the matrix material composition on the compression properties. Two polyurethane formulations were tested under varying specimen conditions. The results show that the dynamic compression modulus increases with the applied load rate and that temperature and water saturation reduce the influence of dynamic effects on the compression modulus. Furthermore, it was observed that modifications of the matrix material have a more significant impact on the dynamic compression modulus than adaptions in the geometrical structure. This is addressed to the relatively small variations in possible surface designs. Finally, a rate-sensitivity index is introduced to quantify the tested specimens’ rate-sensitive behaviour.