Membranes and separators are crucial components in many processes and devices. The state-of-the-art fossil-based membranes have a high carbon footprint, and polyfluorinated membranes are increasingly phased out. These limitations lead to an inevitable transition that calls for carbon-neutral membranes with the same or even better performance that can be produced at scale and low cost. Cellulose membranes have the potential to fulfill these criteria if they can be tuned for different purposes. A way to tailor cellulose membranes by preparing them from cellulose fibrils of different refining degrees is presented. The membranes’ effective pore size and permeability to PEG, Fluorescein, and different ions were characterized. The membranes were efficiently used as separators in aqueous-based Zn-ion batteries and PEDOT supercapacitors. This work demonstrates a route toward high-performing and versatile cellulose membranes that can be produced at scale in a more sustainable membrane industry.

There are many bioelectronic applications where the additive manufacturing of conductive polymers may be of use. This method is cheap, versatile and allows fine control over the design of wearable electronic devices. Nanocellulose has been widely used as a rheology modifier in bio-based inks that are used to print electrical components and devices. However, the preparation of nanocellulose is energy and time consuming. In this work an easy-to-prepare, 3D-printable, conductive bio-ink; based on modified cellulose fibers and poly(3,4-ethylene dioxythiophene) poly(styrene sulfonate) (PEDOT:PSS), is presented. The ink shows excellent printability, the printed samples are wet stable and show excellent electrical and electrochemical performance. The printed structures have a conductivity of 30 S/cm, high tensile strains (>40%), and specific capacitances of 211 F/g; even though the PEDOT:PSS only accounts for 40 wt% of the total ink composition. Scanning electron microscopy (SEM), wide-angle X-ray scattering (WAXS), and Raman spectroscopy data show that the modified cellulose fibers induce conformational changes and phase separation in PEDOT:PSS. It is also demonstrated that wearable supercapacitors and biopotential-monitoring devices can be prepared using this ink.

This work describes an emulsification-solvent-evaporation method for the preparation of liquid-filled capsules made from cellulose acetate. Two different emulsification techniques were applied: bulk emulsification by high-shear mixing, and droplet generation using microfluidics. The bulk emulsification method resulted in the formation of oil-in-water emulsions composed of an organic mixture of isooctane and cellulose acetate in methyl acetate, and an aqueous phase of high-molecular-weight polyvinyl alcohol (PVA). Upon the solvent evaporation, the emulsion droplets evolved into isooctane-filled cellulose acetate capsules. In contrast, microfluidics led to the formation of monodisperse droplets composed of the aqueous PVA solution dispersed in the organic phase. Upon the solvent evaporation, the emulsion droplets evolved into water-filled cellulose acetate capsules. Owing to the thermoplastic properties of the cellulose acetate, the capsules formed with the bulk mixing demonstrated a significant expansion when exposed to an increased temperature. Such expanded capsules hold great promise as building blocks in lightweight materials.

Phase-separated polymer films are commonly used as coatings around pharmaceutical oral dosage forms (tablets or pellets) to facilitate controlled drug release. A typical choice is to use ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. When an EC/HPC film is in contact with water, the leaching out of the water-soluble HPC phase produces an EC film with a porous network through which the drug is transported. The drug release can be tailored by controlling the structure of this porous network. Imaging and characterization of such EC porous films facilitates understanding of how to control and tailor film formation and ultimately drug release. Combined focused ion beam and scanning electron microscope (FIB-SEM) tomography is a well-established technique for high-resolution imaging, and suitable for this application. However, for segmenting image data, in this case to correctly identify the porous network, FIB-SEM is a challenging technique to work with. In this work, we implement convolutional neural networks for segmentation of FIB-SEM image data. The data are acquired from three EC porous films where the HPC phases have been leached out. The three data sets have varying porosities in a range of interest for controlled drug release applications. We demonstrate very good agreement with manual segmentations. In particular, we demonstrate an improvement in comparison to previous work on the same data sets that utilized a random forest classifier trained on Gaussian scale-space features. Finally, we facilitate further development of FIB-SEM segmentation methods by making the data and software used open access.