Combined X-ray Fluorescence Research Articles

A novel algorithm combined X-ray fluorescence and Neural Network (XRF-NN) for coal ash content prediction: Algorithm design and performance evaluation

This paper investigated a precise algorithm combining X-ray Fluorescence and Neural Network (XRF-NN) for predicting ash content. The 261 sets of XRF tests show that the 34 elements in the chosen Guqiao coal can be categorized as major, secondary and tiny elements, whose cumulative ratio were ~95%, 4-5% and <1%, respectively. Referring to the machine learning theory, the construction strategy of Element-Ash dataset was determined viz. value determination → standardization → division → optimization of generalization ability. Then, the hyperparameters optimization displays that XRF-NN model with 34 inputs and 1 output was suitable to predict coal ash content, where the activation function, loss function, and optimizer were ReLU, MAE, and Momentum, respectively. After iterative training, the new XRF-NN model provides the precise prediction of coal ash content with the absolute errors between -2.0% and 2%. Moreover, the prediction accuracy rose from 57.69% to 100%, as the expected relative error increased from 1% to 5%. Furthermore, the comparisons between different prediction methods reveal that the minimum MRE of 1.22% can be obtained by XRF-NN with total elements, which was only half of those given by the conventional Multiple Linear Regression and Partial Least Squares Regression. Besides, XRF-NN model presents the root mean squared error 0.797%, the mean absolute error 0.625% and the coefficient of determination 0.999, which were significantly superior to those calculated by Dual-Energy Gamma-ray Transmission, Ploy, RFR, XGBoost and DNN model. The results of this study suggest the excellent performance of the new XRF-NN model in predicting ash content.

Nanoscale elemental and morphological imaging of nitrogen-fixing cyanobacteria.

Nitrogen-fixing cyanobacteria bind atmospheric nitrogen and carbon dioxide using sunlight. This experimental study focused on a laboratory-based model system, Anabaena sp., in nitrogen-depleted culture. When combined nitrogen is scarce, the filamentous prokaryotes reconcile photosynthesis and nitrogen fixation by cellular differentiation into heterocysts. To better understand the influence of micronutrients on cellular function, 2D and 3D synchrotron X-ray fluorescence mappings were acquired from whole biological cells in their frozen-hydrated state at the Bionanoprobe, Advanced Photon Source. To study elemental homeostasis within these chain-like organisms, biologically relevant elements were mapped using X-ray fluorescence spectroscopy and energy-dispersive X-ray microanalysis. Higher levels of cytosolic K+, Ca2+, and Fe2+ were measured in the heterocyst than in adjacent vegetative cells, supporting the notion of elevated micronutrient demand. P-rich clusters, identified as polyphosphate bodies involved in nutrient storage, metal detoxification, and osmotic regulation, were consistently co-localized with K+ and occasionally sequestered Mg2+, Ca2+, Fe2+, and Mn2+ ions. Machine-learning-based k-mean clustering revealed that P/K clusters were associated with either Fe or Ca, with Fe and Ca clusters also occurring individually. In accordance with XRF nanotomography, distinct P/K-containing clusters close to the cellular envelope were surrounded by larger Ca-rich clusters. The transition metal Fe, which is a part of nitrogenase enzyme, was detected as irregularly shaped clusters. The elemental composition and cellular morphology of diazotrophic Anabaena sp. was visualized by multimodal imaging using atomic force microscopy, scanning electron microscopy, and fluorescence microscopy. This paper discusses the first experimental results obtained with a combined in-line optical and X-ray fluorescence microscope at the Bionanoprobe.

Spectroscopic Benchmarks by Machine Learning as Discriminant Analysis for Unconventional Italian Pictorialism Photography.

Up to the 1930s, the Italian pictorialism movement dominated photography, and many handcrafted procedures started appearing. Each operator had his own working method and his own secrets to create special effects that moved away from the standard processes. Here, a methodology that combines X-ray fluorescence and infrared analysis spectroscopy with unsupervised learning techniques was developed on an unconventional Italian photographic print collection (the Piero Vanni Collection, 1889-1939) to unveil the artistic technique by the extraction of spectroscopic benchmarks. The methodology allowed the distinction of hidden elements, such as iodine and manganese in silver halide printing, or highlighted slight differences in the same printing technique and unveiled the stylistic practice. Spectroscopic benchmarks were extracted to identify the elemental and molecular fingerprint layers, as the oil-based prints were obscured by the proteinaceous binder. It was identified that the pigments used were silicates or iron oxide introduced into the solution or that they retraced the practice of reusing materials to produce completely different printing techniques. In general, four main groups were extracted, in this way recreating the 'artistic palette' of the unconventional photography of the artist. The four groups were the following: (1) Cr, Fe, K, potassium dichromate, and gum arabic bands characterized the dichromate salts; (2) Ag, Ba, Sr, Mn, Fe, S, Ba, gelatin, and albumen characterized the silver halide emulsions on the baryta layer; (3) the carbon prints were benchmarked by K, Cr, dichromate salts, and pigmented gelatin; and (4) the heterogeneous class of bromoil prints was characterized by Ba, Fe, Cr, Ca, K, Ag, Si, dichromate salts, and iron-based pigments. Some exceptions were found, such as the baryta layer being divided into gum bichromate groups or the use of albumen in silver particles suspended in gelatin, to underline the unconventional photography at the end of the 10th century.

Uranium mineralization in the Thrace Basin, NW Türkiye: Evidence from radiation-induced defects in detrital quartz and synchrotron XRF/XANES analysis

The Paleogene-Neogene Thrace Basin in northwestern Türkiye has long been known to host economic gas and oil resources and has recently been reported to potentially host sandstone-type uranium deposits in the Oligocene Süloğlu Formation. The latter discovery raises questions about the source and deposition mechanism of uranium mineralization in the basin. This contribution reports on the results of a detailed electron paramagnetic resonance (EPR) spectroscopic study of detrital quartz from four sandstone and one mudstone samples in the Süloğlu Formation and documents the distribution and speciation of uranium using combined microbeam synchrotron X-ray fluorescence maps (μsXRF) and microbeam X-ray near edge structure spectroscopy (μsXANES). The EPR spectra of quartz separates are characterized by the presence of diagnostic radiation-induced defects (i.e., silicon-vacancy hole centers H′3, H′4, and H′7 with gmax = 2.049, 2.034, and 2.018, respectively, and the oxygen-vacancy electron center E′1), formed by the bombardment of alpha particles emitted from uranium, thorium, and their unstable progenies. Moreover, notable decreases in the intensity of silicon-vacancy hole centers in the EPR spectra of quartz separates after partial dissolution with hydrofluoric acid, provide compelling evidence for the circulation of uranium-bearing fluids in the Thrace Basin. The μsXRF and μsXANES data reveal the occurrences of mixed U6+ and U4+ species in hematite partially replacing pyrite aggregates but dominantly U4+ in disseminated pyrite and illite in sandstones of the Süloğlu Formation. These results provide new insights into uranium transport, reduction, and deposition mechanisms, with important implications for better understanding sandstone-type uranium deposits in general and further exploration in the Thrace Basin.

Protocols for preparation of biomineralized samples for computed tomography

Computed tomography spans a versatile set of techniques that range several length scales and modalities. It is common to them all that the sample must be prepared in a way which allows for addressing the scientific question(s) posed as well as being suitable for the specific setup of the experiment. We present two lathe-based sample preparation workflows developed to prepare biomineralized samples (here bone) for two very different experiments in terms of setup, types of questions asked, and sample requirements. The first experiment, involving the measurement of high throughput (synchrotron) micro-computed tomography, required the preparation of many samples with homogeneity in size, shape, and bone site. This was achieved through a particular sequence of cutting and embedding steps finalized by lathe milling. The resulting samples were cylindrical in shape with diameters close to the field of view of the ensuing tomography experiment, which allowed maximizing the investigated sample volumes. The second experiment was a combined ptychography and X-ray fluorescence nano-computed tomography experiment, which required preparation of a few-micrometer-sized sample. Moreover, the scientific interest was in a specific, localized feature in bone. Thus, the sample had to be extracted from a precise location from within the whole bone. Again, the developed workflow comprised many steps, including both lathe milling and focused ion beam milling. Importantly, localized preparation was enabled by measuring in-house X-ray micro-computed tomography at crucial points in the workflow. The presented workflows provide examples of preparation pathways that can be standardized and strongly increase the throughput, quality, and success rate of tomography experiments.

Probing Reaction Heterogeneity in Thick Electrodes: LiFePO4 Versus LiNi0.6Mn0.2Co0.2O2

Introducing thick electrodes is a sound practice for increasing the energy density of lithium-ion batteries by minimizing the ratio of inactive components at device level. However, the inferior rate performance of the thick electrodes, which is believed to be caused by the inhomogeneous reaction, limits their further applications. In this study, we investigate the reaction distribution in LiFePO4 and LiNi0.6Mn0.2Co0.2O2 thick electrodes with combined scanning X-ray fluorescence (XRF) microscopy and X-ray absorption near edge structure (XANES) spectroscopy. 2D XRF-XANES imaging shows discharge reaction is highly non-uniform in the LFP electrode’s depth direction, the degree of which increases with the discharge rate. In contrast, NMC retains a uniform SOC distribution up to 1C (or 1.5C) rate. The XRF-XANES observations are verified by ToF-SIMS measurements. The different reaction distributions observed in LFP and NMC is explained by P2D modeling and has a thermodynamic origin Figure 1

New analytical method for the evaluation of heterogeneity in cation compositions of dolomites by micro-XRF and Raman spectroscopies.

Dolomite (CaMg(CO3)2) is an abundant carbonate mineral contained in sedimentary rocks and plays significant roles in water and carbon cycle in geo/cosmochemical environments. Since the cation compositions of carbonates are sensitive to the aqueous environment where they were precipitated and persisted, quantitative analysis of their cation compositions provides valuable information on the aqueous environments and their changes. The difficulty for the analysis of natural dolomite is that Mg2+ is continuously substituted by Fe2+ or Mn2+, and hence they sometimes possess micrometer-scale heterogeneity. Such heterogeneity carries quite important information on the gradual changes in aqueous environments due to changes in thermodynamic conditions and/or aqueous chemical compositions. In the present study, we explored a new quantitative scale to assess such heterogeneity of cation composition in natural dolomite and ferroan dolomite by combining X-ray fluorescence (XRF) and Raman spectroscopy. While the Fe + Mn content differed spot-by-spot, it was found that the Raman wavenumber and Fe + Mn content linearly correlated with each other. Since the spatial resolution of micro-Raman spectroscopy is as high as 1μm, it does not require vacuum conditions, and is free from so-called matrix effect faced in other methods utilizing X-Rays and electron beams, the proposed qualitative analytical scale can provide a useful tool to assess the cation compositions in dolomites found in nature.

Mineralogical and Structural Analyses of Natural Fluorite from Yantuwaru Mining Site, Nigeria

Experimental studies of natural fluorite have been reported. In this study, combined X-Ray Fluorescence, FTIR and UV-Vis analyses were performed to give mineralogical information about natural fluorspar. The X-ray diffraction technique was also used to determine the crystallographic parameters and structure of the mineral. Results show a variation of Ca contents and low concentration of F, through all fluorite samples due to Ba and Br contents in the samples, causing replacements of impurity ions in the fluorite lattice. REEs in the fluorite samples were to be found responsible for colour. UV-Visible absorption results showed peaks between 209 to 368 nm, which did not affect the fluorite colour. The 224 nm and 365 nm peaks were caused by the electrons and holes trapped in the Ca2+ interstitial and vacancy, respectively. The absorption bands in the visible range relate to the corresponding fluorite samples. The FTIR results showed absorptions causing CO2 and CO32-stretching vibration due to the CaCO3 and OH stretching vibration due to water in the samples. The structural configuration, the lattice parameters, and the planes confirmed a cubic structure. Obtained results confirmed them to be Calcium Fluorite, as expected.

A combined X-ray fluorescence and infrared microspectroscopy study for new insights into elemental-biomolecular obesity-induced changes in rat brain structures

The objective of our research was to determine the brain changes at the molecular and elemental levels typical of early-stage obesity. Therefore a combined approach using Fourier transform infrared micro-spectroscopy (FTIR-MS) and synchrotron radiation induced X-ray fluorescence (SRXRF) was introduced to evaluate some brain macromolecular and elemental parameters in high-calorie diet (HCD)- induced obese rats (OB, n = 6) and in their lean counterparts (L, n = 6). A HCD was found to alter the lipid- and protein- related structure and elemental composition of the certain brain areas important for energy homeostasis. The increased lipid unsaturation in the frontal cortex and ventral tegmental area, the increased fatty acyl chain length in the lateral hypothalamus and substantia nigra as well as the decreased both protein α helix to protein β- sheet ratio and the percentage fraction of β-turns and β-sheets in the nucleus accumbens were revealed in the OB group reflecting obesity-related brain biomolecular aberrations. In addition, the certain brain elements including P, K and Ca were found to differentiate the lean and obese groups at the best extent. We can conclude that HCD-induced obesity triggers lipid- and protein- related structural changes as well as elemental redistribution within various brain structures important for energy homeostasis. In addition, an approach applying combined X-ray and infrared spectroscopy was shown to be a reliable tool for identifying elemental-biomolecular rat brain changes for better understanding the interplay between the chemical and structural processes involved in appetite control.

Effects of elevated temperature on the mechanical properties of concrete with aggregate of waste porcelain tile

The waste porcelain tile can be used as recycled aggregate in concrete, which will reduce the environmental pollution and alleviate the shortage of natural aggregate. The effects of waste porcelain tile of the mechanical properties of concrete at room temperature were positive. However, the properties of concrete with waste porcelain tile exposed to elevated temperature were unclear. In this experimental study, 45 groups of 100mm × 100mm × 100 mm and 15 groups of 100mm × 100mm × 300 mm specimens were prepared, and 180 specimens of concrete were heated to the target temperature. Variables included aggregate substitution rate (0%, 50%), aggregate categories (coarse and fine aggregate), and exposure temperature (25, 200, 400, 600, and 800 °C). Combining X-ray fluorescence spectrometry (XRF), X-ray diffractometry (XRD), scanning electron microscopy (SEM), and thermogravimetric analysis and differential scanning calorimetry (TGA-DSC), the effects of high temperature on the concrete properties with waste porcelain tile recycled aggregate were investigated. The results showed that the mass loss of concrete with porcelain tile aggregate increased with increasing temperature. The compressive strength of concrete with porcelain tile coarse aggregate gradually decreased with rising temperature. The compressive strength of concrete with porcelain tile fine aggregate increased by 0.8% after being heated at 200 °C. The reduction in splitting tensile strength of concrete with porcelain tile aggregate was slight after exposure temperature below 200 °C. The elastic modulus of porcelain tile coarse and fine aggregate concrete decreased with rising temperature. After being heated at 600 °C, the elastic modulus of porcelain tile coarse and fine aggregate concrete decreased by 90.5% and 89.6%, respectively, compared with room temperature. It is recommended that waste porcelain tile fine aggregate should be used in recycled concrete in preference to porcelain tile coarse aggregate.

32-Channel silicon strip detection module for combined X-ray fluorescence spectroscopy and X-ray diffractometry analysis

A compact detection module for the simultaneous measurement of XRF and XRD in portable analytical applications, in particular in the mining sector, is presented. The detector head is based on 32 silicon strip detectors, fabricated with a low-leakage technology by FBK and readout by two 16-channel low-noise CUBE charge-sensitive amplifiers. The design of the module and its characterization are reported. Multiple configurations are experimentally compared in terms of strip length, spacing, collimation and charge sharing effects. The optimal configuration for a strip length of 6 mm and pitch 0.2 mm is thus identified. It offers an energy resolution of better than 200 eV at 5.9 keV with moderate cooling (−10°C) and peaking time of 14 μs.

Development of SiGe Indentation Process Control for Gate-All-Around FET Technology Enablement

Methodologies for characterization of the lateral indentation of silicon-germanium (SiGe) nanosheets using different non-destructive and in-line compatible metrology techniques are presented and discussed. Gate-all-around nanosheet device structures with a total of three sacrificial SiGe sheets were fabricated and different etch process conditions used to induce indent depth variations. Scatterometry with spectral interferometry and x-ray fluorescence in conjunction with advanced interpretation and machine learning algorithms were used to quantify the SiGe indentation. Solutions for two approaches, average indent (represented by a single parameter) as well as sheet-specific indent, are presented. Both scatterometry with spectral interferometry as well as x-ray fluorescence measurements are suitable techniques to quantify the average indent through a single parameter. Furthermore, machine learning algorithms enable a fast solution path by combining x-ray fluorescence difference data with scatterometry spectra, therefore avoiding the need for a full optical model solution. A similar machine learning model approach can be employed for sheet-specific indent monitoring; however, reference data from cross-section transmission electron microscopy image analyses are required for training. It was found that scatterometry with spectral interferometry spectra and a traditional optical model in combination with advanced algorithms can achieve a very good match to sheet-specific reference data.

Combining X-ray Fluorescence and Monte Carlo Simulation Methods to Differentiate between Tumbaga and Gold-Alloy or Gildings.

Depleted metals have been produced since many centuries ago. Probably the most famous examples from ancient times are the so-called Tumbaga gold artifacts, whose production was introduced by the pre-Colombian civilizations. Tumbaga-like structures have been identified also in modern nanotechnological materials. In both cases, but specially for the ancient Tumbaga, due to their preciousness, their characterization should be obtained by non-destructive analysis. Several analytical protocols have been developed, some of them non-destructive, such as those based on X-ray Fluorescence, but the results obtained do not always allow for a reliable identification of Tumbaga with respect to gilding or single alloy samples. Besides the capability to distinguish between different structures of the sample, it is also important to obtain a quantitative estimation of its composition. In order to meet this demand, a new approach based on X-ray Fluorescence coupled to Monte Carlo simulations is proposed. It allows one to distinguish easily between the three manufacturing techniques and to quantify the composition of the sample without any destructive sampling. It constitutes a new tool for the study of complex alloy structures. The protocol is applied here to some ancient Tumbaga gold samples and is described in detail, comparing the results to those obtained with other techniques.

Rational Design and Characterisation of Novel Mono- and Bimetallic Antibacterial Linde Type A Zeolite Materials.

The development of antimicrobial devices and surfaces requires the setup of suitable materials, able to store and release active principles. In this context, zeolites, which are microporous aluminosilicate minerals, hold great promise, since they are able to serve as a reservoir for metal-ions with antimicrobial properties. Here, we report on the preparation of Linde Type A zeolites, partially exchanged with combinations of metal-ions (Ag+, Cu2+, Zn2+) at different loadings (0.1–11.9 wt.%). We combine X-ray fluorescence, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction to monitor the metal-ion contents, distribution, and conservation of the zeolite structure after exchange. Then, we evaluate their antimicrobial activity, using agar dilution and optical-density monitoring of Escherichia coli cultures. The results indicate that silver-loaded materials are at least 70-fold more active than the copper-, zinc-, and non-exchanged ones. Moreover, zeolites loaded with lower Ag+ concentrations remain active down to 0.1 wt.%, and their activities are directly proportional to the total Ag content. Sequential exchanges with two metal ions (Ag+ and either Cu2+, Zn2+) display synergetic or antagonist effects, depending on the quantity of the second metal. Altogether, this work shows that, by combining analytical and quantitative methods, it is possible to fine-tune the composition of bi-metal-exchanged zeolites, in order to maximise their antimicrobial potential, opening new ways for the development of next-generation composite zeolite-containing antimicrobial materials, with potential applications for the design of dental or bone implants, as well as biomedical devices and pharmaceutical products.

Testing XRF identification of marine washover sediment beds in a Coastal Lake in Southeastern Texas, USA

This study tests the ability of a novel approach to identifying washover beds in coastal lakes. Combined X-Ray Fluorescence (XRF) and cluster analysis was used to identify hurricane washover beds in sediment cores from Clam Lake on the McFaddin National Wildlife Refuge in southeastern Texas. The lake is known to contain washover beds from recent hurricanes, but the washover sediment has similar microfossil, loss-on-ignition and textural characteristics to non-washover sediment and is not readily distinguishable. Sediment cores taken from marshes surrounding the lake do contain visually-recognizable sandy washover beds of Hurricanes Ike, Rita, Carla and Audrey. XRF analysis of these washover beds, combined with cluster analysis, was used to construct “elemental fingerprints” with the potential to detect washover beds in the lake. Results are promising: multiple washover beds were detected in the lake and tentatively attributed to recent hurricanes. In some lake cores, washover beds likely to be present were not detected by the XRF/clustering technique; in other lake cores, up to nine washover beds were detected. The variation in the number of washover beds probably resulted from bioturbation, identification of two or more washover beds in a single washover deposit, and washover beds resulting from smaller storms. Valuable outcomes of this study are; 1) it confirms the presence of washover beds in the lake; 2) it provides greater insight into the number, stratigraphic position and thickness of washover deposits; 3) it identifies periods of heightened and diminished overwash activity, and 4) it provides a means of estimating the contribution of washover deposition to sedimentation in the lake. An additional unexpected finding is that long-term sedimentation rates derived from the lake and marsh cores closely match the rate of local sea-level rise, suggesting that sea-level rise may drive sedimentation in the study area.

Polyol-Made Spinel Ferrite Nanoparticles—Local Structure and Operating Conditions: NiFe2O4 as a Case Study

We report the effect of a polyol-mediated annealing on nickel ferrite nanoparticles. By combining X-ray fluorescence spectroscopy, X-ray diffraction, and 57Fe Mössbauer spectrometry, we showed that whereas the as-prepared nanoparticles (NFO) are stoichiometric, the annealed ones (a-NFO) are not, since Ni0-based crystals precipitate. Nickel depletion from the spinel lattice and reduction in the polyol solvent are accompanied with an important cation migration. Indeed, thanks to Mössbauer hyperfine structure analysis, we evidenced that the cation distribution in NFO departs from the thermodynamically stable inverse spinel structure with a concentration of tetrahedrally coordinated Ni2+ of 20 wt-% (A sites). After annealing, and nickel demixing, originated very probably from the A sites of NFO lattice, the spinel phase accommodates with cation and anion vacancies, leading to the (Fe3+0.84□0.16)A[Ni2+0.80Fe3+1.16□0.04]BO4-0.20 formula, meaning that the applied polyol-mediated treatment is not so trivial.

Rapid identification of wood species using XRF and neural network machine learning

An innovative approach for the rapid identification of wood species is presented. By combining X-ray fluorescence spectrometry with convolutional neural network machine learning, 48 different wood specimens were clearly differentiated and identified with a 99% accuracy. Wood species identification is imperative to assess illegally logged and transported lumber. Alternative options for identification can be time consuming and require some level of sampling. This non-invasive technique offers a viable, cost-effective alternative to rapidly and accurately identify timber in efforts to support environmental protection laws and regulations.

Low-Cost Multispectral System Design for Pigment Analysis in Works of Art.

To better understand and preserve works of art, knowledge is needed about the pigments used to create the artwork. Various noninvasive techniques have been used previously to create pigment maps, such as combining X-ray fluorescence and hyperspectral imaging data. Unfortunately, most museums have limited funding for the expense of specialized research equipment, such as hyperspectral reflectance imaging systems. However, many museums have hand-held point X-ray fluorescence systems attached to motorized easels for scanning artwork. To assist museums in acquiring data that can produce similar results to that of HSI systems, while minimizing equipment costs, this study designed and modeled a prototype system to demonstrate the expected performance of a low-cost multispectral system that can be attached to existing motorized easels. We show that multispectral systems with a well-chosen set of spectral bands can often produce classification maps with value on par with hyperspectral systems. This study analyzed the potential for capturing data with a point scanning system through predefined filters. By applying the system and noise modeling parameters to HSI data captured from a 14th-Century illumination, the study reveals that the proposed multispectral imaging system is a viable option for this need.

Imbalance of Mg Homeostasis as a Potential Biomarker in Colon Cancer.

Background: Increasing evidences support a correlation between magnesium (Mg) homeostasis and colorectal cancer (CRC). Nevertheless, the role of Mg and its transporters as diagnostic markers in CRC is still a matter of debate. In this study we combined X-ray Fluorescence Microscopy and databases information to investigate the possible correlation between Mg imbalance and CRC. Methods: CRC tissue samples and their non-tumoural counterpart from four patients were collected and analysed for total Mg level and distribution by X-Ray Fluorescence Microscopy. We also reviewed the scientific literature and the main tissue expression databases to collect data on Mg transporters expression in CRC. Results: We found a significantly higher content of total Mg in CRC samples when compared to non-tumoural tissues. Mg distribution was also impaired in CRC. Conversely, we evidenced an uncertain correlation between Mg transporters expression and colon malignancies. Discussion: Although further studies are necessary to determine the correlation between different cancer types and stages, this is the first report proposing the measurement of Mg tissue localisation as a marker in CRC. This study represents thus a proof-of-concept that paves the way for the design of a larger prospective investigation of Mg in CRC.

The effect of basicity of modified ground granulated blast furnace slag on its denitration performance

Blast furnace slag (BFS), a large amount of industrial solid waste, is currently used to make mainly concrete and building bricks. There is no doubt that it is a waste of rich elements and oxides in the slag. In order to increase the utilization and use value of BFS, this article prepared it as a denitration catalyst. The alkaline oxides CaO, MgO and the acidic oxides Al2O3, SiO2 were used to modify the ground granulated blast furnace slag (GGBS). And it investigated the effect of the modified GGBS and alkalinity on denitration performance. Combining X-Ray fluorescence (XRF), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) and scanning electron microscope (SEM) characterization, the results showed that: Alkaline oxides modified GGBS had good denitration performance, which benefited from –OH generated during the modification process. While acidic oxides modified GGBS hardly improved the denitration performance, because the acidic oxides would absorb the f-CaO in the slag. According to the calculation formula of slag alkalinity, the quaternary, ternary and binary alkalinity of 9 wt% MgO modified GGBS were 0.901, 1.262 and 1.089 respectively, and the denitration performance of the modified GGBS improved with the increase of alkalinity.