6.3 Strukturanalytik
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Gypsum (CaSO₄·2H₂O) is a crucial mineral across sectors such as construction, agriculture, and biomedicine. Despite its potentially full recyclability, a shortage looms due to limited mining in Europe and decreasing production of flue gas desulfurization (FGD) gypsum, a byproduct of coal power plants. With current EU consumption at 24 MT/a (17 MT mined, 7 MT FGD), a deficit of 10-35 MT/a is projected by the 2030s as CaSO₄ becomes a critical raw material [1]. Meanwhile, substantial CaSO₄ waste is produced in various industries (e.g., phosphogypsum, red gypsum), but its recycling remains limited (10% in Germany, 5% in the EU) due to contamination and separation challenges.
This talk introduces a sustainable, efficient wet-chemical method for converting gypsum to bassanite (CaSO₄·0.5H₂O), and thus recycling gypsum, under mild conditions (T < 100 °C) using reusable high-salinity aqueous solutions (brines with c[NaCl] > 4 M) [2]. The wet-chemical process facilitates the physical removal of impurities from gypsum matrices, making it advantageous for recycling gypsum waste from sources such as demolition or urban mining, where it is often mixed with other materials.
The approach presents a sustainable pathway for recovering high-purity bassanite from contaminated gypsum waste, aligning with EU goals for resource conservation and waste reduction.
Calcium sulfate hemihydrate (CaSO4ᐧ0.5H2O), also known as bassanite, has been used as a precursor to produce gypsum (dihydrate, CaSO4ᐧ2H2O) for various construction and decorative purposes since prehistoric times. The main route to obtain hemihydrate is a thermal treatment of gypsum at temperatures typically between 150 °C and 200 °C to remove some of the structural water. In this contribution, we introduce (Fig. 1) a more efficient and sustainable method (T < 100 °C) that enables the direct, rapid, and reversibly conversion of gypsum to bassanite using reusable high salinity aqueous solutions (brineswith c[NaCl] > 4 M). The optimum conditions for the efficient production of bassanite in a short time (< 5 min) involve the use of brines with c(NaCl) > 4 M and maintaining a temperature, T > 80 °C. When the solution containing bassanite crystals is cooled down to around room temperature, eventually gypsum is formed. When the temperature is raised again to T > 80 °C, bassanite is rapidly re-precipitated. This contrasts with the typical behaviour of the bassanite phase in low salt environments. Traditionally, hemihydrate is obtained through a solid state thermal treatment because bassanite is considered to be metastable with respect to gypsum and anhydrite in aqueous solutions, and therefore gypsum-to-bassanite conversion should not occur in water. Its very occurrence actually contradicts numerical thermodynamic predictions regarding solubility of calcium sulfate phases. By following the evolution of crystalline phases with in situ and time-resolved X-ray diffraction/scattering and Raman spectroscopy, we demonstrated that the phase stability in brines at elevated temperatures is inaccurately represented in the thermodynamic databases. Most notably for c(NaCl) > 4 M, and T > 80 °C gypsum becomes readily more soluble than bassanite, which induces the direct precipitation of the latter from gypsum. The fact that these transformations are controlled by the solution provides extensive opportunities for precise manipulation of crystal formation. Our experiments confirmed that bassanite remained the sole crystalline structure for many hours before reverting into gypsum. This property is extremely advantageous for practical processing and efficient crystal extraction in industrial scenarios.
Gypsum (CaSO₄·2H₂O) is a crucial mineral across sectors such as construction, agriculture, and biomedicine. Despite its potentially full recyclability, a shortage looms due to limited mining in Europe and decreasing production of flue gas desulfurization (FGD) gypsum, a byproduct of coal power plants. With current EU consumption at 24 MT/a (17 MT mined, 7 MT FGD), a deficit of 10-35 MT/a is projected by the 2030s as CaSO₄ becomes a critical raw material [1]. Meanwhile, substantial CaSO₄ waste is produced in various industries (e.g., phosphogypsum, red gypsum), but its recycling remains limited (10% in Germany, 5% in the EU) due to contamination and separation challenges.
This contribution introduces a sustainable, efficient wet-chemical method for converting gypsum to bassanite (CaSO₄·0.5H₂O), and thus recycling gypsum, under mild conditions (T < 100 °C) using reusable high-salinity aqueous solutions (brines with c[NaCl] > 4 M) [2]. The optimal conversion conditions (T > 80°C, c[NaCl] > 4 M) enable rapid (<5 min) and reversible transformation (Fig. 1). Upon cooling, gypsum re-forms, offering a temperature-dependent control over phase transition. Unlike conventional thermal dehydration (150-200 °C), this approach promotes the dissolution of gypsum, allowing contaminants to be separated via selective precipitation or adsorption. Additionally, the wet-chemical process facilitates the physical removal of impurities from gypsum matrices, making it advantageous for recycling gypsum waste from sources such as demolition or urban mining, where it is often mixed with other materials.
Our approach presents a sustainable pathway for recovering high-purity bassanite from contaminated gypsum waste, aligning with EU goals for resource conservation and waste reduction.
In this contribution, I present a digital twin-based workflow designed to optimize experimental parameters in X-ray emission spectroscopy (XES), with a focus on reproducibility, data integration, and alignment with FAIR (Findable, Accessible, Interoperable, Reusable) principles in materials science and engineering (MSE). The developed pipeline begins with automated retrieval of crystallographic information from the Materials Project database based on a given sample composition. This structural data is then used to simulate the corresponding XES spectra using FDMNES, allowing for accurate prediction of element-specific emission lines.
The simulated emission lines are fed into an X-ray tracing (XRT) module, which builds a virtual replica of the experimental setup. This digital twin environment enables predictive modeling of spectrometer performance based on geometric configurations. The optimization focuses on two key parameters: the choice of the analyzing crystal and the distance between the sample and crystal (which also defines the crystal–detector distance due to Bragg condition constraints). An active learning algorithm is employed to iteratively adjust these parameters in order to achieve a desired energy-per-pixel (E/pixel) resolution with minimal intensity loss, enabling efficient, data-driven experimental planning.
By integrating data-driven simulations with real-time optimization strategies, this workflow supports efficient experiment planning while minimizing resource consumption and human error. Furthermore, all stages of the process—from data collection and simulation to optimization and visualization—are structured to ensure traceability and interoperability, facilitating future reuse and collaborative research.
I hope this contribution aligns well with the topic “Workflows for FAIR MSE Data” and offers a concrete example of how digital twins can be harnessed to improve the design, execution, and documentation of spectroscopy experiments in the MSE domain.
Kinetics information on the progress of the mechanochemical reactions is key to their understanding and subsequent scale-up. For crystalline materials, the most robust and tested method for obtaining kinetic data is the Quantitative Phase Analysis (QPA) via Rietveld refinement. In this work, we tested the feasibility of the Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) method on powder X-ray diffraction (PXRD) data of mechanochemical processes by studying the system theophylline (TP) and malonic acid (MA) in a 1 : 1 stoichiometric ratio at different milling conditions. We have highlighted the strengths and weaknesses of the MCR-ALS method, and we demonstrated why it may be an alternative route to obtain quantitative information on mechanochemical kinetics.
We present the racemization of an active pharmaceutical ingredient Levetiracetam using a novel approach. We demonstrate the design of a 100% solvent-free process that proceeds by high energy milling inside a regular mixer mill. The kinetics of the racemization process is drastically improved compared to the solution-based approach and illustrates the tremendous potential of mechanochemistry. In this study, we highlight the importance of mixing efficiency regarding data reproducibility, and we show, in particular, that water contamination has a negative impact on the reaction rate. Moreover, in situ X-ray diffraction gives us first insights into the mechanisms involved in the solid state during the mechanochemical racemization process.
Arguably mechanochemistry is one of the oldest, and at the same time one of the newest, areas of chemistry. One of the oldest, because it has been theorized that early hominids were able to develop rapidly due to their ability to heat and mechanically process their food to make it easier to digest. Old, because the ancient Greeks knew that mechanically activating stones (consisting of cinnabar) with vinegar in a copper pestle and mortar caused them to convert into mercury. We might be forgiven for thinking that this could have led our alchemical forbears to wonder if there were other stones that might also be persuaded to convert into gold. Early chemical luminaries such as Michael Faraday and Wilhelm Röntgen dabbled in mechanochemistry. However, in the late 19th and early 20th centuries, the field developed separately in many areas. Perhaps most significantly, synthetic chemists realized that reactions could be carried out with surprisingly high yields and selectivities by shaking them in a ball mill, and that they could even make novel compounds that their colleagues just using heat were not able to. Physicists were mechanically rearranging atoms into new configurations (i.e., doing chemistry) using exotic means such as atomic force microscope tips and optical tweezers. Scientists and engineers studying the formation of lubricious and anti-wear films realized that they were mechanochemically formed. Biochemists found molecular motor proteins, such as myosin and kinesin, that were able to convert chemical energy into motion or, vice versa, mechanical energy into the biochemical energy storage molecule adenosine triphosphate. In 2023, this confluence of advances convinced the Royal Society of Chemistry that the time was ripe to establish a new journal dedicated to the field of mechanochemistry. It is rare that a journal has the privilege of helping to create a new sub-branch of chemistry but, having done so, it has the obligation of helping to define the field and, optimistically, suggesting how the field might develop. This editorial has two major goals. The first is to bring to the attention of the scientific community the challenges faced by the field to set people thinking about how they might contribute and, second, to form the basis for more thorough discussions in the future. The sub-topics below outline current thoughts brought forward from members of our editorial board. We lay out areas and topics here with the intent of establishing a new editorial series, which we invite the community to contribute to, and outline topics and hopefully lay out challenges, which will enable us as a community to come together to move mechanochemistry forward.
The adsorptive performance of divalent manganese onto single-walled carbon nanotubes (SWCNTs) is investigated by X-ray absorption spectroscopy (XAS). The study is focused on the one hand, on the use of SWCNT as adsorbent to remove divalent manganese II) pollutant controlling batch parameters such as pH, adsorbent dose and contact time; and on the other hand, on the characterization of manganese adsorbed by SWCNT (Mn-SWCNT) adsorbent to probe the chemical composition, oxidation state, and local structural environment of Mn absorber. Freundlich adsorption isotherm well fitted the experimental data and suggested the maximum adsorption capacity at pH 2. Ion exchange was proposed as the main adsorption mechanism for removing manganese using SWCNT. XAS results revealed the change in the oxidation state of manganese. The effect of pH, adsorbent dose, and contact time is shown. XAS also showed that Mn-SWCNT material is principally composed of MnCl2, Mn2O3, MnO2, Mn3O4, and MnO in decreasing order with MnCl2 and Mn2O3 as major compounds.
With the global push toward sustainable energy technologies, the development of efficient and durable electrocatalysts has become a research priority. Real-time in situ studies are essential to understand the dynamic behavior of catalysts under operational conditions. X-ray absorption spectroscopy (XAS) offers a unique, element-specific probe of electronic and structural changes at the active sites of electrocatalysts during electrochemical reactions.
At BAM, collaborative research efforts leverage the advanced capabilities of the BAMline at the Berlin Synchrotron BESSY-II to study electrocatalytic materials under realistic working conditions. As a dedicated materials research beamline, the BAMline enables in situ and operando XAS across different time and length scales, making it ideally suited for monitoring catalytic transformations in real time.
This presentation highlights the analytical strengths and sample environments developed for electrochemical cells at BAM, showcasing their application to electrocatalysis for energy conversion (e.g., water splitting, CO₂ reduction). Emphasis will be placed on how these insights contribute to the rational design and real-time optimization of functional materials for a sustainable energy future.
The presentation describes how large language models (LLMs) such as ChatGPT can be integrated with the EPICS control system to improve the automation and usability of synchrotron beamlines like the BAMline at BESSY II.
It explains how LLMs can interpret natural language instructions, translate them into EPICS commands, and interact with experimental tools to perform complex tasks such as moving motors, running scans, or adjusting beamline components. The system, named P.E.T.E.R. (Performance Enhancing Technology for Experimental Research), supports features like multi-step reasoning, Python scripting, feedback loops, multilingual input, and voice control using OpenAI’s ChatGPT and Whisper.