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The detailed ash transformation process during the combustion of agricultural biomass containing moderate to high amounts of P was studied in entrained flow conditions. The selected fuels were grass and brewer’s spent grain (BSG) containing a moderate and high amount of P in the fuel, respectively. The experiments were conducted in a lab-scale drop tube furnace at 1200 and 1450 °C. The residual chars, ashes, and particulate matter (PM) were collected and analyzed by scanning electron microscopy-energy-dispersive X-ray spectroscopy (SEM-EDS), X-ray diffraction (XRD), inductively coupled plasma atomic emission spectroscopy (ICP-AES) and ion chromatography (IC), and CHN-analysis. Additionally, the obtained results were interpreted through thermodynamic equilibrium calculations (TECs). For both fuels, P was primarily identified in the residual coarse ash (>1 μm) fractions. In contrast, a minor to moderate amount of fuel inherent P was detected in the fine particulate (<1 μm) fraction at 1200 and 1450 °C, respectively. For grass, the retained P in the residual coarse ash fractions was mainly identified as amorphous K-Ca-Mg-rich phosphosilicate melt. These phosphosilicates were most likely formed through the initial formation of molten K-rich silicates, with subsequent incorporation of Ca, P, and Mg. For BSG, a P-Si-rich fuel with moderate to minor amounts of Ca, Mg, and K, most P was retained in a Ca-Mg-rich phosphosilicate melt, likely originating from phytate-derived Ca-Mg phosphates interacting with fuel-inherent Si-rich particles. The results obtained from this study could be used to address the ash-related challenges and potential P-recovery routes during pulverized fuel combustion of P-containing biomass.

X-ray microtomography is a non-destructive method that allows for detailed three-dimensional visualisation of the internal microstructure of materials. In the context of using phosphorus-rich residual streams in combustion for further ash recycling, physical properties of ash particles can play a crucial role in ensuring effective nutrient return and sustainable practices. In previous work, parameters such as surface area, porosity, and pore size distribution, were determined for ash particles. However, the image analysis involved binary segmentation followed by time-consuming manual corrections. The current work presents a method to implement deep learning segmentation and an approach for quantitative analysis of morphology, porosity, and internal microstructure. Deep learning segmentation was applied to microtomography data. The model, with U-Net architecture, was trained using manual input and algorithm prediction. 

• The trained and validated deep learning model could accurately segment material (ash) and air (pores and background) for these heterogeneous particles.
• Quantitative analysis was performed for the segmented data on porosity, open pore volume, pore size distribution, sphericity, particle wall thickness and specific surface area.
• Material features with similar intensities but different patterns, intensity variations in the background and artefacts could not be separated by manual segmentation – this challenge was resolved using the deep learning approach.

The present study investigates how three different silicate-based bed materials behave in bubbling fluidized bed combustion of a model agricultural residue with respect to ash composition, namely barley straw. Quartz, natural K-feldspar, and olivine were all used in combustion at 700 °C, and the resulting layer formation and bed agglomeration characteristics were determined. Based on this, a general reaction model for bed ash from agricultural residues was proposed, taking into account the reactivity of the different silicates investigated towards the main ash-forming elements K, Ca, and Si. The proposed reaction model links bed material interaction with K-rich bed ash to the degree of polymerization of the silicate bed material, where addition reactions occur in systems with high polymerization, predominately in quartz, and substitution reactions dominate for depolymerized silicates such as K-feldspar and olivine.

In this work, the fate of the ash-forming elements during bubbling fluidized bed combustion and gasification of P-rich sewage sludge (SS) and mixtures with either Si-K-rich wheat straw (WS) or K-Ca-rich sunflower husks (SH) were investigated. The focus of the study was assessing the feasibility of using fuel blends in fluidized bed systems and potential P recovery from the resulting ashes. The used fuels were pure SS and mixtures including 90 wt.% WS (WSS) and 85 wt.% SH (SHS). The analyzed operating conditions were combustion (930–960 °C, λ: 1.2–1.5) and gasification (780–810 °C, λ: 0.4–0.7) in a 5 kW bench-scale reactor. Residual ash and char fractions were collected from different parts of the 5 kW bubbling fluidized bed (bed, cyclone, filter) and analyzed by CHN, SEM/EDS, XRD, and ICP-AES.

The conversion of the fuel mixtures achieved a steady state under the used process conditions except for the combustion of WSS, which led to the formation of large bed agglomerates with the bed material. The morphology of ash samples after combustion showed that SS fuel pellets mostly maintained their integrity during the experiment. In contrast, the ash and char particles from fuel mixtures were fragmented, and larger quantities were found in the cyclone, the filter, or on interior reactor surfaces. The fate of P was dominated by crystalline Ca-dominated whitlockites in all ash fractions, partially including K for the fuel mixtures SHS and WSS. 76–81 % of ingoing P was found in the bed residue after combustion and gasification of the SS-fuel. After conversion of the fuel mixtures SHS and WSS, the share was lower at 22–48 %, with larger shares of P in the entrained fractions (25–34 %). The quantity of identified crystalline compounds was lower after gasification than combustion, likely due to the limited interaction of ash-forming elements in the residual CHN matrix. Altogether, the results show that fuel mixtures of sewage sludge with agricultural residues could expand the fuel feedstock and enable P recovery. This may be used in the fuel and process design of upscaled fluidized bed processes or systems employing both combustion and gasification.

The purpose of this study was to provide detailed knowledge of the morphological properties of ash particles, including the volumetric fractions and 3D distributions of phosphates that lay within them. The ash particles came from digested sewage sludge co-combusted with K- and Si-rich wheat straw or K-rich sunflower husks. X-ray micro-tomography were combined with elemental composition and crystalline phase information to analyse the ash particles in 3D.

Analyses of differences in the X-ray attenuation enabled calculation of 3D phosphate distributions that showed high heterogeneity in the slag particles. This is underscored by a distinct absence of phosphates in iron-rich and silicon-rich parts. The slag from silicate-based wheat straw mixtures had lower average attenuation than that from sunflower husks mixtures, which contained more calcium. Calculated shares of phosphates between 7 and 17 vol% were obtained, where the highest value for a single assigned phosphate was observed in hard slag from wheat straw with 10 % sewage sludge. The porosity was notably higher for particles from pure wheat straw combustion (62 vol%), compared to the other samples (15–35 vol%). A high open pore volume fraction (60–97 vol%) indicates that a large part of the pores can be accessed by the surroundings. For all samples, more than 60 % of the discrete (closed) pores had an equivalent diameter < 30 μm, while the largest volume fraction consisted of pores with an equivalent diameter > 75 μm. Slag from sunflower husk mixtures had larger pore volumes and a greater relative number of discrete pores >75 µm compared to wheat straw mixtures.

Research infrastructure MAXS offers state-of-the-art X-ray diffraction, totalX-ray scattering, and X-ray reflectometry with several sample environments foradvanced material characterization to users from academy, industry, or public sectors. The platform also offers a comprehensive data evaluation environment with access to extensive reference databases for data collected at MAXS or elsewhere, including compatibility with data from synchrotron light sources.

The available instruments are two independent Bruker D8Advance systems with the possibility to choose from three X-ray wavelengths, X-ray profile, detector configuration with two detector types, and a broad selection of sample stages to match the needs of an experiment. The users can define what they need from an experiment and the instrument can be configured accordingly. An important feature is the automatic sample changer, increasing the sample throughput.

Data evaluation environment is provided locally at MAXS at two workstations, but also via network for internal users permitting local installation within Umeå University. Up to 20 users can simultaneously use the evaluation software with local installations of the crystallographic open database (COD) making it readily accessible for both research and education.