Phase Quantification Research Articles

From STEM-EDXS data to phase separation and quantification using physics-guided NMF

Abstract We present the development of a new algorithm which combines state-of-the-art energy-dispersive X-ray (EDX) spectroscopy theory and a suitable machine learning formulation for the hyperspectral unmixing of scanning transmission electron microscope EDX spectrum images. The algorithm is based on non-negative matrix factorization (NMF) incorporating a physics-guided factorization model. It optimizes a Poisson likelihood, under additional simplex constraint together with user-chosen sparsity-inducing and smoothing regularizations, and is based on iterative multiplicative updates. The fluorescence of X-rays is fully modeled thanks to state-of-the-art theoretical work. It is shown that the output of the algorithm can be used for a direct chemical quantification. With this approach, it is straightforward to include a priori knowledge on the specimen such as the presence or absence of certain chemical elements in some of its phases. This work is implemented within two open-source Python packages, espm and emtables, which are used here for data simulation, data analysis and quantification. Using simulated data, we demonstrate that incorporating physical modeling in the decomposition helps retrieve meaningful components from spatially and spectrally mixed phases, even when the data are very noisy. For synthetic data with a higher signal, the regularizations yield a tenfold increase in the quality of the reconstructed abundance maps compared to standard NMF. Our approach is further validated on experimental data with a known ground truth, where state-of-the art results are achieved by using prior knowledge about the sample. Our model can be generalized to any other scanning spectroscopy techniques where underlying physical modeling can be linearized.

A Review of Principles, Analytical Methods, and Applications of SEM‐EDS in Cementitious Materials Characterization

AbstractScanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM‐EDS) is an indispensable and versatile technique that provides detailed 2D spatial insights into the microstructure of heterogenous cementitious systems. To foster clear and systematic understanding of SEM‐EDS analysis in advancing research on cementitious materials, the state‐of‐the‐art principles, analytical approaches, and applications of SEM‐EDS analysis in cementitious systems are reviewed. This review aims to assist researchers in selecting the most appropriate strategy for SEM‐EDS analysis to quantify phase assemblage, elucidate environmental interactions, and investigate microstructure evolution in cementitious systems. The fundamental concepts related to equipment, signal generation, acquisition of diverse EDS data are first presented. Subsequently, various analysis approaches, including point analysis, grid analysis, and mapping analysis are discussed. This review then emphasizes the practical significance and potential value of SEM‐EDS analysis in addressing phase quantification challenges pertaining to cementitious systems. It is posited that the SEM‐EDS analysis holds the promise of becoming the characterization backbone for quantitative research on cementitious systems.

Method Development and Comprehensive Study of Matrix Effects for the Determination of Trace Organic Contaminants in Lake Sediments

The presence of trace organic contaminants (TrOCs), such as pharmaceuticals, personal care products, additives, and polar pesticides in sediments of rivers and lakes highly impacted by anthropogenic activities makes sediments a secondary source of contamination for aquatic ecosystems. Considering this, a method for analyzing 44 TrOCs of diverse nature (including five transformation products, 13 pharmaceuticals, five personal care products, 14 pesticides, and seven additives) was developed and validated. It is based on extraction by pressurized liquid extraction (PLE), followed by purification and pre-concentration by solid phase extraction (SPE) and quantification by liquid chromatography coupled to a triple quadrupole mass spectrometer (LC-QqQMS). The method was optimized according to dispersant type, temperature, and extraction solvent. The influence of organic matter in sediments on quantitative analysis was also investigated in detail. Matrix effects were highly and significantly correlated (r=-0.9146, p < 0.0001) with retention time. Using internal standards showed the best results for effectively correcting matrix effects without affecting method sensitivity. The method was then validated according to key figures of merit: linearity (R2 > 0.990), extraction recoveries (> 60% for 34 compounds), trueness (bias % < 15%), precision (relative standard deviation < 20%) and matrix effects (between -13.3% and 17.8%). This method can be applied for routine analysis of TrOCs in different sediment matrices. The method was applied to ten lake sediment samples collected in Québec, Canada. Results demonstrated the presence of 17 compounds in at least one lake at concentrations between 0.07 to 1531 ng g-1. The reported concentrations provide a first picture of the occurrence of chemical stressors in sediments of small lake highly anthropized ecosystems in Eastern Canada.

Background phase induced steady-state effects in velocity quantification using phase-contrast MRI.

Flow quantification using phase-contrast (PC) MRI is based on steady-state gradient echo (GRE) sequences and is hampered by spatially varying background phase offsets. The purpose of this work was to investigate the effect of steady-state disruptions during PC-MRI GRE sequences on these background phases. Based on these findings, a specific sequence and timing is suggested, and caution is expressed when using typical correction algorithms. Steady-state responses in stationary tissue were investigated in different prospectively triggered through-plane phase-contrast MRI sequence. Different spoiling methods (gradient spoiling/FISP versus gradient+RF spoiling/FLASH) and interleaving of flow encoding gradients (every TR vs. every ECG cycle) were investigated using simulations, in phantoms and in vivo. Additionally, the effect of relaxation times on the phase offsets was simulated and measured. The impact on image- and phantom-based background phase correction was studied. Good agreement between simulation and phantom measurements were observed. Different sequences lead to different spatiotemporal and tissue dependent background phases. Average flow rates in the popliteal artery were over- and underestimated for ECG-interleaved and TR-interleaved FISP acquisitions compared to FLASH, respectively. Background phase measurements are influenced by steady-state effects leading to potentially false background phase quantification. Current background phase correction methods cannot correct for the disturbance.

Phase quantification in a duplex stainless steel welds using NDT techniques

ABSTRACT Duplex stainless steels are composed of ferrite and austenite in equal volume fractions of these phases, which provides an excellent combination of mechanical properties and corrosion resistance, especially when compared with conventional stainless steel grades. When these steels are welded, there are significant changes in the austenite-to-ferrite ratio therefore in their final properties. Nowadays, the ferritoscope is the unique non-destructive technique used to quantify these two phases content in situ. This tester instrument is limited to the evaluation of large areas, is not suitable for the heat affected zone and is also very sensitive to the surface finish, being considered an intermediate precision technique. So, it is necessary to develop more reliable field techniques. In this research, thermoelectric power measurements and induced current techniques are proposed to evaluate the phase quantification in S32205 welds. According to the results, both techniques are reliable and highly sensitive to phase changes in the weld bead, heat affected zone and base metal. For the thermoelectric power technique, a probe with nickel tip should be used to obtain the highest sensitivity and for the induced current technique, a probe type-pencil with a central frequency of 6 MHz should be used.

Phase quantification analysis in cement-blended slag system with the PONKCS method

The Partial Or No Known Crystal Structure (PONKCS) method, an XRD analysis technique, is widely employed for phase quantification in cement-blended supplementary cementitious materials (SCMs). This study emphasized unsolved factors in applying this method to SCMs blends, including obtaining accurate SCM structure information, accounting for chemical composition variation, and identifying suitable C–S–H profiles. Ground granulated blast furnace slag was chosen as the representative SCM. Results show that four fundamental parameter (FP) type peaks were sufficient to index slag pseudo-structure without Pawley fitting. Slag weight fraction quantification was minimally impacted by slag pseudo-structures from slag with SiO2 content variations up to 3.03%. The C–S–H profile, with negligible clinker residue and a Lorentzian crystallite size of approximately 6.9 nm, was found suitable for PONKCS method application. Combining selective dissolution method with PONKCS method improved its accuracy. This study enhances improving quantification precision and extending the applications of PONKCS method in variable SCMs systems.

AI-enhanced X-ray diffraction analysis: towards real-time mineral phase identification and quantification.

The use of convolutional neural networks can revolutionize XRD analysis by significantly reducing processing times. Demonstration against synthetic and real mineral mixture data provide a first assessment of the accuracy of such methods.

Effects of phosphatization on the mineralogical and geochemical composition of marine ferromanganese crusts from the JiaXie Guyot in the Western Pacific: Constraints from high resolution analysis

The marine crusts comprise ferromanganese sediments formed through the precipitation of dissolved elements in seawater. These crusts serve as a record elements signal from paleo-ocean and are extensively utilized in paleo-oceanography. Previous researches have examined the chemical composition of the phosphatized crust layers using powder chemistry and leaching experiments. However, there exist divergent viewpoints regarding the influence of phosphatization on element behavior. In this study, we employed a combination of analytical techniques including scanning electron microscope (SEM), powder X-ray diffractometer (XRD), TESCAN Integrated Mineral Analyzer (TIMA), laser ablation and inductively coupled plasma time of flight mass spectrometry combined system (LA-ICP-TOF), laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). These methods were utilized to achieve mineral phase quantification, precise depiction of element distribution, and in-situ profile analysis of elements within the phosphatized crust layers from the JiaXie Guyot in the Western Pacific. The mineral phase analysis shows enormous carbonate fluorapatite (CFA) precipitate, which replace calcite in the old phosphatized layer. Additionally, vernadite experiences partial dissolution. Furthermore, a small amount of hematite, goethite, todorokite, zeolite, barite, as well as trace amounts chalcopyrite, sphalerite, galena, ilmenite, and pyrite are formed. The element distributions suggest potential outward migration of Fe, V, Zr, Zn and Cu, while Ce and Pb are locally enriched. In the phosphatized crust, some elements exhibit depletion in the old crust layer compared to the young crust layer, with Fe > Si > V>Zn > Ti ≥ Pb, while others are enriched in the order crust layer, such as Y>Pd > Ce > Pt. The study proposes that FeOOH·nH2O and associated adsorbed elements like Si, Ce, Y, V, Zn, Ti and Pb dissolve in vernadite and migrate outward during phosphatization, with weak phosphatization influence on Mn oxide. In addition, the phosphate-rich seawater might contribute additional elements such as Y, Ce and Pd to the crust layers. Thus, this study highlights the elemental distributions, migration patterns observed, and significance of presence for critical metals between old and young crust layers from the influence of phosphatization based on high resolution analysis. Particularly, it acknowledges the contribution of phosphate-rich seawater to the elemental composition of crust layers.

Phase quantification of anhydrous CSA cements: a combined X-ray diffraction and Raman imaging approach

Calcium sulfoaluminate (CSA) cements are known for their special properties, such as shrinkage compensation and high early-age strength. These properties are dependent on the hydrated phase assemblage, which in turn is governed by the phases present in the initial anhydrous cement. However, the anhydrous CSA phase quantification by X-ray diffraction (XRD) Rietveld can be challenging due to the presence of overlapping peaks, polymorphs and preferred orientation. To overcome this problem, an approach involving high-resolution large-area Raman imaging (5 mm × 5 mm, 250 000 pixels, with 10 μm/pixel resolution) complemented by XRD analysis is introduced. This integrated approach of combined XRD and Raman imaging is found to be crucial in the initial identification of phases that are present in a CSA system. Most importantly, quantitative analysis shows a strong correlation (R2 &gt; 0.99) and agreement (variation &lt;5 wt%) between the two independent methods, adding confidence and reliability to the phase assemblage obtained by this dual-technique approach.

Synthesis of the acidic/magnetic catalyst x-MoO3/Ni0.5Zn0.5Fe2O4 by combustion reaction and evaluation of its catalytic potential/reuse in biodiesel production

The objective of this work was to synthesize a new catalyst x-MoO3/Ni0.5Zn0.5Fe2O4 using the combustion reaction method and to evaluate its catalytic potential and reuse in biodiesel production from waste oil, optimizing the process through experimental design. The catalysts were characterized in terms of structure by X-ray diffraction and phase quantification by Rietveld refinement, surface area by the Brunauer-Emmett-Teller technique, experimental density by helium pycnometry, acidity tests by ammonia desorption at programmed temperature, chemical analysis by X-ray fluorescence, morphology by scanning and transmission electron microscopy, and catalytic properties. The products of the simultaneous transesterification and esterification reactions were characterized by gas chromatography and acidity index. The results indicate the formation of catalysts with surface area ranging from 1.5 to 1.7 m2/g and density ranging from 4.5 to 5.1 g/cm3, composed of major crystalline phases of MoO3 in the orthorhombic configuration and cubic Ni0.5Zn0.5Fe2O4 ferrite, with total acidity ranging from 70 to 182 μmol/g of NH3. Morphological characterization revealed that the catalyst comprises irregular plates of various sizes and shapes with a wide range of cluster sizes. In the simultaneous transesterification and esterification reactions of residual oil, the catalysts were active under all conditions tested, with emphasis on the catalyst containing 50 % Mo ions and 50 % Ni0.5Zn0.5Fe2O4 presenting the best catalytic performance with a conversion of 95 % in ethyl esters and a reduction of 71 % in acidity, with a service life of 6 cycles, an average conversion of 90 % and good thermal and structural stability after use. The experimental design was significant and predictive, with a confidence level of 95 %. Statistical analysis identified that all input variables (temperature, time, and amount of catalyst) were significant for the adopted design. The new catalyst composed of molybdenum, iron, nickel, and zinc has a positive impact on biodiesel synthesis from frying oil and ethanol.

Phase quantification using deep neural network processing of XRD patterns.

Mineral identification and quantification are key to the understanding and, hence, the capacity to predict material properties. The method of choice for mineral quantification is powder X-ray diffraction (XRD), generally using a Rietveld refinement approach. However, a successful Rietveld refinement requires preliminary identification of the phases that make up the sample. This is generally carried out manually, and this task becomes extremely long or virtually impossible in the case of very large datasets such as those from synchrotron X-ray diffraction computed tomography. To circumvent this issue, this article proposes a novel neural network (NN) method for automating phase identification and quantification. An XRD pattern calculation code was used to generate large datasets of synthetic data that are used to train the NN. This approach offers significant advantages, including the ability to construct databases with a substantial number of XRD patterns and the introduction of extensive variability into these patterns. To enhance the performance of the NN, a specifically designed loss function for proportion inference was employed during the training process, offering improved efficiency and stability compared with traditional functions. The NN, trained exclusively with synthetic data, proved its ability to identify and quantify mineral phases on synthetic and real XRD patterns. Trained NN errors were equal to 0.5% for phase quantification on the synthetic test set, and 6% on the experimental data, in a system containing four phases of contrasting crystal structures (calcite, gibbsite, dolomite and hematite). The proposed method is freely available on GitHub and allows for major advances since it can be applied to any dataset, regardless of the mineral phases present.

Structural Characterization of Mixed Metal Cathodes via in Operando X-Ray Diffraction

Complex metal oxides used in lithium-based energy storage technologies undergo distinct crystallographic changes based on chemical composition, specific voltage and current states, degree of lithiation, and more. Crystallographic studies via X-ray diffraction (XRD) are a critical part of understanding structure-property relationships and engineering devices to meet specific performance requirements. For the raw electrode materials, XRD provides information about exact crystal structure (e.g. symmetry, unit cell parameters, atomic site mixing) as well as the presence of impurity phases that might arise from a poor sintering process or non-stoichiometric starting reagents. For formed devices such as button- or pouch-cells, XRD can be used in operando to measure changes in phase composition, phase quantification, and crystal lattice expansion/contraction as a function of charge state. This can provide useful information such as the level of reversibility of a device or the onset of impurity phases during aging and long cycling.In this presentation, we will review diffraction data for case studies based on NMC electrodes and highlight key insights into reversible structural changes during device cycling. The figure attached to this abstract shows diffraction data as a function of charge state during a single charge/discharge cycle. The observed peaks show modifications to the crystalline lattice (expansion in one direction, contraction in another orthogonal direction). Figure 1

Doping Induced Enhancement of Activity and Stability for Oxygen Evolution Reaction with Isomaterially Heterostructured MnO2

A “Non-Native” phase (NNP) differs from the thermodynamically most stable bulk Native in its discrete translational symmetry. The relative difference in surface and bulk energy with respect to the native phase (NP)determines the stability of NNP. The isomaterial hetero-structured NP-NNP composite provides a pathway to assemble structures that have optimal properties of NNP and NP. The surface and sub-surface energies can also be modulated by doping as the dopants may segregate and stabilize grain boundaries. This study demonstrates that the isomaterial heterostructure of the NP, β-N MnO2, and Ramsdellite, r-NN1 MnO2, known as γ-N-NN1-MnO2 intergrowth, enhances the OER activity and stability.The hydrothermal route was used to synthesize isomaterial heterostructured γ/N-NN1-MnO2 with varying concentrations of dopants (10%, 15%, and 20% Ni and Co). X-ray diffraction was used to characterize the material, and after Rietveld refinement, phase quantification revealed that as the dopant concentration increased, the amount of the thermodynamically stable β-N MnO2 phase increased. Planes identified in XRD were also confirmed using high-resolution transmission electron microscopy (HRTEM) and the analysis of selective area electron diffraction (SAED) patterns. It appears that doping was successful based on the shifting of peaks in XRD and differences in unit cell volume and crystallite size calculated using the Debye-Scherrer equation before and after doping. With an increase in dopant concentration and thus improved OER activity, the average oxidation state as determined by X-ray photoelectron spectroscopy followed a downward trend, which is known to improve OER activity. The peaks shifted to lower frequency values as seen by Raman spectroscopy, which implies a weakening of Mn—O bond strength, indicating that dopants Ni and Co may have replaced part of the Mn atoms in the MnO2 intergrowth structure. Scanning electron microscopy (SEM) revealed spherical-shaped nanoparticles with spike-like overgrowths, which were further confirmed by HRTEM. The uniform dispersion of dopants was demonstrated by SEM and energy dispersive spectroscopy (EDS). Elemental quantification of the samples was done using EDS and scanning transmission electron microscopy (STEM). Using HRTEM, the presence of grain boundaries was confirmed.The study of dopants segregating to the grain boundary is conducted through DFT simulations. In many instances, the dopants actively contribute to the OER activity, except for the case of Ni in the NN1 sub-phase of the γ-N-NN1-MnO2 intergrowth, which is apparent by the slightly lower activity of Ni-doped samples compared to Co. This is because Ni remains in the bulk while Co segregates to the surface. A three-electrode setup (Ag/AgCl as the reference electrode, Pt mesh as the counter electrode, and catalyst as the working electrode) was used in 1M KOH to conduct electrochemical experiments. To achieve 10 mA/cm2, the 15% Co-doped electrocatalyst used the least amount of overpotential, 320 mV. According to electrochemical measurements and analysis, the doped samples show low Tafel slope, high specific activity, roughness factor, and charge transfer resistance from electrochemical impedance spectroscopy, all of which suggest improved overall activity for the oxygen evolution process (OER) for the doped over undoped samples. DFT simulations rationalize the enhancement of OER using the Bader charge analysis, the associated Gibbs free energy of the Sabatier principle plotted as the volcano plot.

Hybrid kidney stones physicochemical and morphological characterization: A spectroscopic study analysis

This study was designed to scrutinize the practical health index of uroliths for investigating composition, structural characterization, phase quantification and shape of kidney stone patients with respect to socioeconomically status in territory of Bahawalpur, southern Punjab, Pakistan. Morphology of the kidney stones were determined using SEM. The Ultra violet spectra of kidney stones in narrow range of 220–280 nm. Quantitative phase analysis of stones indicates as oxalate, calcium oxalate monohydrate, calcium oxalate dehydrates, calcium phosphate, cysteine and uric acid with 40.51 %, 26.24 %, 14.24 %, 36.45 %,13.18 % and 9.86 % respectively. A survey analysis also supports the vitro data showing patient age with 30–40 years with more predominance in males than females. Metabolic abnormalities were detected in 75 % patients with stone recurrence 15 % complained of having digestive disease. The overall concludes from qualitative and quantitative results suggested the community for preventive measures in reducing the risk of pervasiveness and relapse of urolithiasis.

Quantification of Super Duplex Steel Phases by Processing of Backscattered Electron Images

Quantification of Super Duplex Steel Phases by Processing of Backscattered Electron Images

Red mud and bismuth oxide based X-ray shielding tiles for upcoming hospitals: A comprehensive study on phase quantification and physical properties

Red mud (RM) is a solid alumina industry waste generated in millions of tonnes and is stockpiled across the globe. From the environmental perspective, research and innovation strategies are utmost necessary for the minimization and utilization of red mud. In an attempt to develop an environmentally friendly technology, RM was utilized with Bi2O3 for the development of radiation shielding tiles. RM is a source of many metal oxides, which react with Bi2O3 during sintering and form various high-dense phases. The Rietveld refinement of the tiles sintered from 600 to 1100°C confirms the formations and transformations of several high-dense phases like Bi24Ti2O40, BiFeO3, and Na0.5Bi0.5TiO3. The RM-Bi2O3 mixture sintered at 1100°C (RMBi1100) exhibited high density (3.64 ×103 kg m−3), less porosity (10 %), and flexural strength of 24 MPa. The results showed that the developed sample has a half-value layer (HVL) of 1.15 mm at 140 kV. The 15.5 mm, 13.5 mm, and 7 mm thick RMBi1100 tiles can effectively replace 2.3 mm, 2 mm, and 1 mm thick lead sheets respectively, that are used to establish radiation shielding structures in computed tomography, radiography & fluoroscopy, and dental infra oral radiography installations, respectively. It can promote the utilization of red mud and thereby reduce the environmental pollution associated with lead and red mud.

Neural networks for rapid phase quantification of cultural heritage X-ray powder diffraction data

Recent developments in synchrotron radiation facilities have increased the amount of data generated during acquisitions considerably, requiring fast and efficient data processing techniques. Here, the application of dense neural networks (DNNs) to data treatment of X-ray diffraction computed tomography (XRD-CT) experiments is presented. Processing involves mapping the phases in a tomographic slice by predicting the phase fraction in each individual pixel. DNNs were trained on sets of calculated XRD patterns generated using a Python algorithm developed in-house. An initial Rietveld refinement of the tomographic slice sum pattern provides additional information (peak widths and integrated intensities for each phase) to improve the generation of simulated patterns and make them closer to real data. A grid search was used to optimize the network architecture and demonstrated that a single fully connected dense layer was sufficient to accurately determine phase proportions. This DNN was used on the XRD-CT acquisition of a mock-up and a historical sample of highly heterogeneous multi-layered decoration of a late medieval statue, called `applied brocade'. The phase maps predicted by the DNN were in good agreement with other methods, such as non-negative matrix factorization and serial Rietveld refinements performed with TOPAS, and outperformed them in terms of speed and efficiency. The method was evaluated by regenerating experimental patterns from predictions and using the R-weighted profile as the agreement factor. This assessment allowed us to confirm the accuracy of the results.

A comparative analytical study for the different water pools present in alginate hydrogels: Qualitative vs. quantitative approaches

Alginate hydrogels have garnered significant attention due to their promising applications in the food, biomedical, and pharmaceutical industries. The detection and quantification of distinct water phases within these hydrogels offer valuable insights into their dynamic, absorptive, and mechanical properties. Despite being comprised solely of 2 wt % polymeric materials, the alginate hydrogels exhibit a highly porous morphology, characterized by distinct water pools exhibiting varying mobility and dynamic behaviors. These phases can be delineated as largely free water phase with high mobility, which occupies the macropores, and bound water with restricted mobility, which interacts with the fibrous polymeric structure. Water pools interacting with their surrounding environments possess variable crystal structures on variable freezing points, this could be easily detected using X-ray scattering techniques. A comparative study was conducted based on the information derived from each technique, with differential scanning calorimetry (DSC) yielding quantitative information for the water phases in alginate hydrogels (i.e., 58 % free and 42 % bound water in 0.75 wt % - 6 h aging sample), whereas cryogenic scanning electron microscopy (Cryo-SEM), wide and small-angle X-ray scattering (WAXS and SAXS), Fourier Transform Infrared (FT-IR), and rheology provided valuable qualitative insights. In this study, deep insights into the molecular structure of alginates were obtained including the alteration in morphology and macropore distribution, increase in the wall thickness, density, and mechanical properties upon increasing the Ca2+ concentration and aging period.

Mechanochemically Induced Solid-State Transformations of Levofloxacin.

Levofloxacin hemihydrate (LVXh) is a complex fluoroquinolone drug that exists in both hydrated and anhydrous/dehydrated forms. Due to the complexity of such a compound, the primary aim of this study was to investigate the amorphization capabilities and solid-state transformations of LVXh when exposed to mechanical treatment using ball milling. Spray drying was utilized as a comparative method for investigating the capabilities of complete LVX amorphous (LVXam) formation. The solid states of the samples produced were comprehensively characterized by powder X-ray diffraction, thermal analysis, infrared spectroscopy, Rietveld method, and dynamic vapor sorption. The kinetics of the process and the quantification of phases at different time points were conducted by Rietveld refinement. The impact of the different mills, milling conditions, and parameters on the composition of the resulting powders was examined. A kinetic investigation of samples produced using both mills disclosed that it was in fact possible to partially amorphize LVXh upon mechanical treatment. It was discovered that LVXh first transformed to the anhydrous/dehydrated form γ (LVXγ), as an intermediate phase, before converting to LVXam. The mechanism of LVXam formation by ball milling was successfully revealed, and a new method of forming LVXγ and LVXam by mechanical forces was developed. Spray drying from water depicted that complete amorphization of LVXh was possible. The amorphous form of LVX had a glass transition temperature of 80 °C. The comparison of methods highlighted that the formation of LVXam is thus both mechanism- and process-dependent. Dynamic vapor sorption studies of both LVXam samples showed comparable stability properties and crystallized to the most stable hemihydrate form upon analysis. In summary, this work contributed to the detailed understanding of solid-state transformations of essential fluoroquinolones while employing greener and more sustainable manufacturing methods.

Anomalous magnetization induced by local chemistry fluctuations in Mn-containing α’-martensite

An anomalous increase in magnetization was investigated in a cold-rolled high-Mn TRIP steel (16.8 wt% Mn) annealed at 350°C for times varying from 5 to 120 min, before the start of austenite reversion (α’ → γ). Besides in-situ and ex-situ magnetic measurements, the full characterization of this phenomenon was also performed with the aid of X-ray diffraction (XRD), Mössbauer spectroscopy, and microstructural characterization using electron backscatter diffraction (EBSD) and atom probe tomography (APT). Based on XRD measurements, the volume fraction of austenite and α’-martensite was estimated as a function of annealing time, as well as their lattice strain. Phase quantification confirmed the absence of newly-fresh α’-martensite in the material during annealing at 350°C. Short annealing up to 15 min promoted the increase of Ms (saturation magnetization) due to stress relief in α’-martensite (Villari effect). Further annealing to 30 min promotes the decrease in Ms driven by short-range solute reorganization within the lattice. After 60 min annealing, the creation of long-range solute-depleted zones (i.e. confined zones highly enriched in Fe) causes a new increase in Ms. In comparison, for 120 min of annealing time, Ms tends to remain unaltered. These findings revealed that short- and long-range chemical fluctuations strongly affect the saturation magnetization of the steel and brought new insights on the use of magnetic probing as a tool for phase quantification in Mn-bearing steels.