Anna Strandberg

Image reconstruction is fundamental to advanced imaging systems, transforming large datasets into interpretable representations that facilitate a deeper understanding of material structures. High‐resolution imaging techniques, such as synchrotron X‐ray microtomography, operate over a wide dynamic range and are susceptible to noise, thereby requiring advanced reconstruction strategies beyond conventional approaches. Recent integration of iterative optimization with deep‐learning architectures, including convolutional neural networks and U‐Nets, has advanced this field by enabling accelerated image enhancement, artifact mitigation, and segmentation. Advanced neural‐network architectures can improve structural detail recovery and segmentation accuracy while supporting efficient analysis of large volumetric datasets. The application of AI‐enhanced deep learning for reconstruction, denoising, segmentation, and quantitative analysis of synchrotron microtomography datasets from biomass‐derived materials such as biochar and ash remains relatively unexplored. Deep learning‐guided segmentation enables quantitative characterization of pore networks, interfacial features, phase distributions, porosity, and other microstructural descriptors. These developments support applications in materials characterization, energy‐storage systems, environmental engineering, and biomass‐derived materials research. Future developments may enable the resolution of previously inaccessible structural features, integrate multimodal datasets, and develop adaptive experimental processes. Together, advances in imaging physics, deep learning, and data‐driven analysis are expected to enhance reconstruction quality, quantitative interpretation, and the versatility of synchrotron tomography.

This review aims to prospect the development and utilization of proton‐conducting biopolymers as sustainable matters. Its focal point is a move to sustainable materials of environment‐friendly alternatives to conventional plastics. The review explores the properties and development techniques related to proton conduction in biopolymers and highlights their practical applications. Proton conductivity, mechanical strength, thermal stability, and chemical compatibility are pivotal features for creating advanced materials where biomaterials offer a sustainable production pathway for such materials. Methods for enhancing these properties include blending with similar biomaterials, making chemical modifications, creating nanostructures, and employing hybrid fabrication techniques. Improved proton conductivity is possible by forming proton pathways, attributed to chains of water molecules. These enhanced conductive materials have applications in fuel cells, sensors, ion separation membranes, and biomedical devices. Nature‐derived biomimetic materials may offer such adaptable solutions that could also be eco‐friendly and support a circular economy. This study has implications for industry professionals and researchers in the fields of energy and consumer electronics, highlighting the potential of biopolymers as key elements in sustainable product development.

The effect of mechanical screening of severely contaminated forest fuel chips was investigated, focusing on main ash-forming elements and slagging tendency and other properties with relevance for thermal conversion. In this study, screening operations were performed according to practice on an industrial scale by combining a star screen and a supplementary windshifter in six different settings and combinations. Mechanical screening reduced the amount of ash and fine particles in the accept fraction. However, the mass losses for the different screening operations were substantial (20–50 wt %). Fuel analyses of the non-screened and the screened fuels showed that the most significant screening effect was a reduction of Si and Al, indicating an effective removal of sand and soil contaminations. However, the tested fuel’s main ash-forming element’s relative concentration did not indicate any improved combustion characteristics and ash-melting behavior. Samples of the accept fractions and non-screened material were combusted in a single-pellet thermogravimetric reactor, and the resulting ashes’ morphology and elemental composition were analyzed by scanning electron microscopy–energy dispersive X-ray spectrometry and the crystalline phases by powder X-ray diffraction. Results from both these analyses confirmed that screening operations had no, or minor, effects on the fuels’ ash chemistry and slagging tendencies, i.e., the fuels’ proneness to ash melting was not improved. However, the reduction of ash and fine particles can reduce slagging and other operational problems in smaller and more sensitive combustion units.

Phosphorus has been identified as a critical element by the European Union and recycling efforts are increasingly common. An important phosphorus-containing waste stream for recycling is municipal sewage sludge (MSS), which is used directly as fertilizer to farmland. However, it contains pollutants such as heavy metals, pharmaceutical residues, polychlorinated bi-phenyls (PCBs) and nano-plastics. The interest in combustion of MSS is continuously growing, as it both reduces the volume as well as destroys the organic materials and could separate certain heavy metals from the produced ashes. This results in ashes with a potential for either direct use as fertilizer or as a suitable feedstock for upgrading processes. The aim of this study was to investigate co-combustion of MSS and biomass to create a phosphorus-rich bottom ash with a low heavy metal content. A laboratory-scale fixed-bed reactor in addition to an 8 MWth grate-boiler was used for the experimental work. The concentration of phosphorus and selected heavy metals in the bottom ashes were compared to European Union regulation on fertilizers, ash application to Swedish forests and Swedish regulations on sewage sludge application to farmland. Element concentrations were determined by ICP-AES complemented by analysis of spatial distribution with SEM-EDS and XRD analysis to determine crystalline compounds. The results show that most of the phosphorus was retained in the bottom ash, corresponding to 9–16 wt.% P₂O₅, while the concentration of cadmium, mercury, lead and zinc was below the limits of the regulations. However, copper, chromium and nickel concentrations exceeded these standards.