Lithium aluminum oxide has previously been identified to be a suitable compound to recover lithium (Li) from Li-ion battery recycling slags. Its formation is hampered in the presence of high concentrations of manganese (9 wt.% MnO₂). In this study, mock-up slags of the system Li₂O-CaO-SiO₂-Al₂O₃-MgO-MnO_x with up to 17 mol% MnO₂-content were prepared. The manganese (Mn)-bearing phases were characterized with inductively coupled plasma optical emission spectrometry (ICP-OES), X-ray diffraction (XRD), electron probe microanalysis (EPMA), and X-ray absorption near edge structure analysis (XANES). The XRD results confirm the decrease of LiAlO₂ phases from Mn-poor slags (7 mol% MnO₂) to Mn-rich slags (17 mol% MnO₂). The Mn-rich grains are predominantly present as idiomorphic and relatively large (>50 µm) crystals. XRD, EPMA and XANES suggest that manganese is present in the form of a spinel solid solution. The absence of light elements besides Li and O allowed to estimate the Li content in the Mn-rich grain, and to determine a generic stoichiometry of the spinel solid solution, i.e., (Li_(2x)Mn²⁺_(1−x))_1+x(Al_(2−z),Mn³⁺_z)O₄. The coefficients x and z were determined at several locations of the grain. It is shown that the aluminum concentration decreases, while the manganese concentration increases from the start (x: 0.27; z: 0.54) to the end (x: 0.34; z: 1.55) of the crystallization.

A highlight this year was the construction of elemental maps of microalgae cells at the organelle level using XRF-CT with a beam size of just 15 nm. These probably represent the highest ever spatial resolution achieved for XRF-CT images. An innovative approach for reconstruction algorithms used a deep convolutional neural network to correct for the self-absorption effects in the XRF-CT sinogram domain. Such corrections will enable the use of conventional tomographic reconstruction algorithms for XRF-CT analysis. A remarkable advantage of the proposed method was that it could correct for self-absorption effects without any prior knowledge of the scanning setups. A particularly innovative dual-energy X-ray-beam ptycho-fluorescence imaging method combined XRF spectrometry and X-ray ptychography scanning with simultaneous data-collection. To overcome the incompatibility of the different excitation and scanning conditions required for fast ptychography and high spatial resolution XRF spectrometry, two coaxial beams of different sizes were used on the sample simultaneously. In comparison to sequential scans, this combined approach has the potential to reduce the data collection time by a factor of 25. The very good performance of laboratory 2D-XRF spectrometry for the analysis of minute amounts of radioactive material has made it a potential alternative to TXRF spectrometry. Reconstruction algorithms are now capable of significantly enhancing imaging resolution in μXRF spectrometry. The forensic classification of incredibly small amounts of samples such as single fibres was accomplished using elemental profiles determined by TXRF spectrometry. Although characterisation of the low-Z matrix in milk and polymers by conventional TXRF spectrometry is challenging, it was successfully achieved by studying the Compton and Rayleigh scatter with both univariate and multivariate approaches. Portable XRF spectrometry is a well-established technique for a wide range of applications. Emphasis continues to be placed on improving calibration and reducing matrix and inter-element effects. The sample type remains a challenge for portable XRF analysis. Computer vision and statistical methods such as spectral angle mapper are being increasingly applied to maximise the information that can be extracted from the data. For example, an innovative approach exploited the elemental features from XRF spectra to improve the interpretation of molecular information provided by reflectance spectroscopy, and vice versa.

Due to the increasing demand for electromobility, the recovery of technologically relevant elements from spent Li-ion batteries is becoming increasingly important. Pyrometallurgical processing can deal with a broad range of input materials. Unfortunately, ignoble elements such as Li and Mn enter the slag. A novel approach to facilitate this processing is the Engineered Artificial Minerals (EnAM) strategy for the recovery of critical elements. The aim of this study is to investigate whether it is possible to stabilize Li in Li-manganates as the first crystallizate. For this purpose, synthetic oxide slags (Li, Mg, Al, Si, Ca, Mn) of varying compositions were made. The constituting compounds were identified using inductively coupled plasma optical emission spectrometry, powder X-ray diffraction, X-ray absorption near-edge structure analysis, and electron probe microanalysis. These results provide an understanding of the solidification process and the behavior of the elements of concern. Lithium-manganate(III) (LiMnO₂) crystallized first, next to hausmannite (Mn²⁺Mn³⁺₂O₄) in a matrix consisting of wollastonite (CaSiO₃) and larnite (Ca₂SiO₄). Within the structure of LiMnO₂, Li and Mn can replace each other in certain proportions. By adding Al and Mg spinel, solid solutions between Mn²⁺Mn³⁺₂O₄, MnAl₂O₄, MgAl₂O₄ and LiMnO₂ are expected and described by the stoichiometry formula: (Li_(2x),Mg_(1x),Mn_(2+(1–x)))_1+x(Al_(2–z),Mn³⁺_(z))₂O₄.

Polyurethane (PUR) soft foams release malodorous and potentially toxic compounds when exposed to oxidative conditions. Current chamber test methods cannot distinguish between pre-existing volatiles and those formed during oxidation, nor can they assess the formation rates of oxidation products. We subjected PUR soft foam to oxidative treatment in a continuous air flow at 120 °C. Emissions were convectively transferred from the foam to an exhaust port and analyzed using a thermodesorption–gas chromatography–mass spectrometry (TD-GC-MS) system, with external calibration employed for the quantification of selected analytes. The study identified hydroperoxide formation and degradation as key mechanisms in the breakdown of the polyether soft segments. This process predominantly produces volatiles, such as carboxylic acids, formates, acetates, alpha-hydroxy-ketones, (unsaturated) aldehydes, substituted dioxolanes and dioxanes, glycols, and allyl ethers. Volatiles associated with the degradation of the hard segments include aniline, benzoxazole, 2-methylbenzoxazole, and benzaldehyde. This experimental setup enables reproducible qualitative and quantitative analysis of volatiles formed during the oxidative degradation of PUR soft foams, providing new insights into the segment-dependent chemical pathways of the polymer’s molecular breakdown.