Tapping into the Past: First Approach to a Diachronic Material Characterization of Mayapán Pottery

The present work is focused on developing and implementing a minimally invasive methodology for material characterization of traditional pottery from Yucatan, México. The developed methodology, which combines elemental (X-ray fluorescence spectroscopy (XRF), inductively coupled plasma-optical emission spectroscopy (ICP-OES), and Laser-Induced Breakdown Spectroscopy (LIBS)) and molecular (fiber optic reflectance spectroscopy (FORS)) spectroscopic analytical techniques, allowed for the characterization of contemporary pottery objects manufactured following traditional recipes in the town of Uayma, Yucatán, México and raw materials associated with the pottery manufacturing process. The results allowed us to detect and estimate the number of selected elements and helped to infer the presence of complex materials such as iron oxides, aluminosilicates, and calcium carbonate. Additionally, the analysis indicated two pottery groups separated by their elemental and molecular composition, corresponding to the sources of raw materials employed by the potters. It confirmed the absence of toxic compounds in ceramic objects, a significant concern for potters, as some objects are intended for domestic use. The research findings provide reassurance about the safety of these products.

Rare earth elements (REEs) hold significant industrial, scientific, and modern technological worth. This study focused on detecting and quantifying REEs in various geological ore samples. These samples were collected from different REE-bearing locations recommended by geological experts. The analysis was conducted using laser-induced breakdown spectroscopy (LIBS) and laser ablation time-of-flight mass spectrometry (LA-TOF-MS). In this work, LIBS methodology was employed using three different configurations: standard LIBS, LIBS with an applied magnetic field, and LIBS with both an applied magnetic field and target sample heating within an optimal temperature range. Elements from the REE group, specifically lanthanum (La), cerium (Ce), and neodymium (Nd), were identified and quantified. To detect, quantify, and validate the results from LIBS and LA-TOF-MS, we utilized an array of analytical techniques—Energy-Dispersive X-ray Spectroscopy (EDX), Energy-Dispersive X-ray Fluorescence Spectrometer (ED-XRF), and Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). Interestingly, the quantitative results for REEs (La, Ce, and Nd) in the ore samples obtained using the LIBS technique with various configurations were found to be in agreement with those from LA-TOF-MS, EDX, XRF, and ICP-OES. In addition, LIBS enables detailed microchemical imaging, allowing the map of the spatial distribution of elements within the mineral–ore matrix. The high-resolution microscale elemental mapping of REEs was accomplished using the emission lines Ce (II) at 446.0 nm, La (II) at 492.1 nm, and Nd (II) at 388.8 nm. By integrating multiple analytical techniques, our study enabled the construction of a complete elemental distribution map, providing new insights into the geochemical processes and mineral composition of rare earth ores, while advancing geochemistry and contributing valuable data for rare earth resource exploration.

Recently, environmental issues continually increased since expanded in industrial development and grown in population. Regarding to this activity, it will cause lack management of waste such as solid waste from wastewater treatment plant called sewage sludge. This research presents the characteristic study of sewage sludge, regardless of whether it is appropriate or not to be applied as building materials. The sewage sludge samples were collected from secondary treatment at Senggarang and Perwira under Indah Water Konsortium (IWK) treatment plant. Raw materials were tested with X-ray Fluorescence (XRF) and Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) in order to determine the composition of sewage sludge and heavy metal concentration contains in sewage sludge. From the study, it was found that sewage sludge contained high amount of Silica Oxide (SiO2) with 13.6%, Sulphur Trioxide (SO3) with 12.64% and Iron Oxide (Fe2O3) with 8.7% which is similar in clay. In addition, sewage sludge also high in Iron (Fe) with 276.2 mg/L followed by Zinc (Zn) with concentration 45.41 mg/L which sewage sludge cannot be directly disposed to landfill. Results from this study demonstrated that sewage sludge has high possibility to be reused as alternative building materials such as bricks and have compatible chemical composition with clay.Recently, environmental issues continually increased since expanded in industrial development and grown in population. Regarding to this activity, it will cause lack management of waste such as solid waste from wastewater treatment plant called sewage sludge. This research presents the characteristic study of sewage sludge, regardless of whether it is appropriate or not to be applied as building materials. The sewage sludge samples were collected from secondary treatment at Senggarang and Perwira under Indah Water Konsortium (IWK) treatment plant. Raw materials were tested with X-ray Fluorescence (XRF) and Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) in order to determine the composition of sewage sludge and heavy metal concentration contains in sewage sludge. From the study, it was found that sewage sludge contained high amount of Silica Oxide (SiO2) with 13.6%, Sulphur Trioxide (SO3) with 12.64% and Iron Oxide (Fe2O3) with 8.7% which is similar in clay. In addition, sewage sludge a...

Laser Induced Breakdown Spectroscopy (LIBS) method is introduced as a novel approach in this work to study catalyst deactivation of V2O5/γ‐‐Al2O3 for gas‐phase dehydration of glycerol and producing acrolein. The LIBS results of V2O5/γ‐Al2O3 samples are compared with those data that are obtained by Inductively Coupled Plasma Optical Emission Spectrometry (ICP‐OES). Experimental data of LIBS data specify that line intensities of vanadium are decreased by deactivation of V2O5/γ‐Al2O3 catalyst. A comparison between the results of LIBS test as well as ICP‐OES analysis shows that the amount of vanadium is decreased in the catalyst. Moreover, coke formation changes the surface of the catalyst. The results of deactivation of V2O5/γ‐Al2O3 are also compared with Pd/C catalyst deactivation.

Imaging the distribution of nutrient elements and the uptake of toxic metals in industrial hemp and white mustard with laser-induced breakdown spectroscopy

Edible mushrooms are excellent food that can be incorporated into well balanced diets due to their low content of fat and energy, high content of dietary fibers and proteins. Proximate composition of mushrooms also varies within and among species due to agro-climate conditions and environmental factors. The current study was designed to analyze proximate composition and mineral profile of one local wild Ganoderma lucidum, two commercial local cultivated mushrooms species i.e. Pleurotus ostreatus and Vovoriella volvacea, and two commercial exotic mushrooms i.e. Lentinus edodes and Hericium erinaceus for their nutritive values. Minerals were analyzed by Inductivity Coupled Plasma Optical Emission Spectrometry (ICP-OES). Selected mushrooms were also analyzed by laser induced break down spectroscopy (LIBS) to identify any harmful element(s) present in these mushrooms. Proximate analysis showed that crude protein ranged from 15.04-24.8%, crude fat 0.53-2.02%, Fiber 6.11-54.12%, Ash 2.0-9.99% and total carbohydrates varied in a range of 65.34-82.47% on dry weight basis. Ca, Mg, Na, Zn, P and K were in elevated concentration. Al, B, Cu, Li and Mn were in the range of 2.5-8.1, 0.4-6.1, 0.9-1.4, 0.2-1.4, 0.4-1.3 mg/100 g on dry weight basis respectively. As, Ba and Se were in lower concentration whereas Pb, Cd, Mo, Be, Sn and Co were below detectable limits. LIBS also revealed some elements like, titanium, barium, calcium, iodine, carbon and hydrogen. The selected local mushrooms are safe for consumption, in accordance with the permissible tolerance limit of the toxic metals.

Pozzolanic materials, known for their superior performance in enhancing the strength and integrity of well cements along with their significantly reduced carbon footprint, have been receiving much attention. The elemental characterization of pozzolanic materials is crucial because it affects the reactivity of cementitious fluids and thus the overall efficiency of a cementing job. This study investigates the elemental analysis correlation between inductively coupled plasma optical emission spectroscopy (ICP-OES) and X-ray fluorescence (XRF) spectrometry techniques using machine learning (ML) algorithms. ICP-OES is known for its high accuracy and low detection limit, but it can be labor-intensive and time-consuming because of the tedious sample preparation involved, which also raises chemical safety concerns. In contrast, XRF requires minimal sample preparation and offers quick analysis. However, the XRF results are subject to matrix effects. The goal of this study is to harness the power of ML to recognize and reduce the matrix interference in XRF, enabling the substitution of ICP-OES with XRF in practical well cementing applications. A comprehensive dataset of over 100 unique pozzolanic materials, sourced from various suppliers worldwide, was compiled using ICP-OES, XRF, and other material characterization techniques. A family of ML regression models was optimized, primarily focusing on the simple and efficient principal component regression (PCR) and partial least squares (PLS) algorithms, while also exploring other linear, nonlinear, kernel-based, and decision tree-based ML models. These models were trained using full XRF spectra (both raw and after preprocessing), with ICP-OES measurements serving as the ground truth. Model predictions on an independent test set were critically evaluated and compared, resulting in the development of an optimal ML workflow. Rigorous reproducibility analysis was also conducted for both analytical techniques. The ML models demonstrated prediction errors of less than 5% (range-normalized root mean square error) for the 12 main elements of interest when applied to the XRF spectra. This suggests that ML-enhanced XRF spectrometry can effectively replace ICP-OES, significantly reducing the labor and time required for the elemental analysis of pozzolanic materials. This study, pioneering the use of ML to enhance the elemental analysis of pozzolanic materials, offers a robust framework for future practical applications of XRF material characterization in the oilfield industry and beyond. The proposed approach will lead to informed decision-making regarding the formulation of pozzolan-based well cementing slurries. Leveraging advanced analytical techniques to ensure their effective use in cementing applications aligns with the industry's ambition to use environmentally benign materials.

Synthetic leather samples from Brazil and Paraguay were evaluated in this study using three spectroscopy techniques: inductively coupled plasma optical emission spectrometry (ICP-OES), laser-induced breakdown spectroscopy (LIBS), and wavelength dispersive X-ray fluorescence (WDXRF). The obtained information from each technique was separately inspected with principal component analysis (PCA). The concentrations of the elements determined in the synthetic leathers using ICP-OES decreased in the following order: Ca > Cr > Mg > Ba > Pb > Al > Fe > Zn > Sb > Ni with a concentration range below the limit of quantification (<LOQ, case of Ni) to 112 233 mg kg-1 (case of Ca). Additionally, Cu, As, Sr, Ti, Cd, Mn, Co, and Ni were present in only few samples in a concentration range from <LOQ to 163 mg kg-1. Principal component analysis was the tool used to evaluate the samples from their chemical content obtained quantitatively using ICP-OES and qualitatively using LIBS or WDXRF spectra. The results showed that the association of PCA with spectroscopic techniques was satisfactory for data inspection of synthetic leathers according to the chemical composition. Laser-induced breakdown spectroscopy and WDXRF were able to identify the presence of toxic elements like Cr (LIBS and WDXRF) and Pb (WDXRF).

Quantitative analysis of oxide materials by laser-induced breakdown spectroscopy with argon as an internal standard

98/04254 Ventilation status and dust-gas conditions in the mines of Pechorskii basin

Presented research aimed to develop an alternative approach for the estimation of biosorption capability of sunflower husk. The acid-pretreated sunflower biomass was characterized by scanning electron microscopy combined with energy dispersive X-Ray spectroscopy (SEM-EDX) analysis and Fourier transform infrared (FTIR) spectroscopy. Biosorption efficiency has been evaluated using inductively coupled plasma optical emission spectroscopy (ICP-OES) and laser-induced breakdown spectroscopy (LIBS). The adsorption capacity of the adsorbent was determined as the function of the pH of the solution, the initial concentration of heavy metal solutions, and contact time. The optimal conditions were achieved after 15 min of contact at pH 6, while the percentage of the removal was from 80.0?98.7 %, depending on the element. The results obtained from the kinetic and isotherm studies show that maximum adsorption of ions was quickly reached and followed the pseudo-second-order kinetic model. Real samples were tested and obtained Ni values by LIBS method were 3100?200 and 1240?100 mg kg-1, while estimated values by the ICP-OES were 2995?20 and 1130?10 mg kg-1, respectively. The obtained results prove that LIBS method can be used as a ?green alternative? for the evaluation of biosorption efficiency.

Direct determination of trace elements in terephthalic acid by laser induced breakdown spectroscopy

Highly accurate determination of Zn and Cu in human hair by ultrasound-assisted alkali dissolution combined with laser-induced breakdown spectroscopy

Spectrochemical analysis of powdered biological samples using transversely excited atmospheric carbon dioxide laser plasma excitation

P analysis in fertilizers using LIBS.