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Insight to the Microstructure Analysis of a HP Austenitic Heat-Resistant Steel Under Short-Term High-Temperature Exposure
No full textThe HP40Nb alloy, commonly used in the petrochemical industry as a heatresistant material, undergoes significant microstructural changes at high temperatures. This study examined samples from the HP40Nb radiant tube used in a reformer furnace, exposed to 950, 1050, and 1150 ◦C for 2 and 8 h. Metallographic analysis, including optical microscopy, SEM, EDS, and XRPD, revealed that the as-cast alloy has an austenitic dendritic matrix with primary eutectic-like carbides (M23C6 and MC types). Prolonged exposure to high temperatures transformed the primary carbides into coarse M23C6 forms, losing their lamellar shape. The number of secondary carbides decreased with increasing temperature, and at 1150 ◦C for 480 min, secondary Cr23C6 carbides nearly decomposed, and Nb carbides dissolved into the austenitic matrix
Modified Silica Particles Coated with Cu-Al Layered Double Hydroxide for Phosphate and Arsenate Removal in Water Treatment
No full textEnvironmental pollution remains one of the most pressing challenges facing modern society, with the removal of toxic substances from water sources being of particular concern. In this study, a composite material was synthesized by combining Cu-Al layered double hydroxides (CuAl-LDHs) with modified silica particles, aiming to develop an efficient and environmentally friendly adsorbent for the removal of phosphate and arsenate ions from water. CuAl-LDH, with a Cu2+/Al3+ molar ratio of 2:1, was synthesized using the co-precipitation method in the presence of modified silica maintaining an LDH/SiO2 mass ratio of 2:1. The silica particles were functionalized with 3-glycidyloxypropyltrimethoxysilane (GLYMO) followed by modification with polyethyleneimine (PEI) to enhance their adsorption properties. X-ray diffraction (XRD) confirmed the successful deposition of CuAl-LDH on the silica surface, while scanning electron microscopy (SEM) revealed the porous structure of the silica and the uniform deposition of LDH. Adsorption experiments were performed to evaluate the removal efficiency of phosphate and arsenate ions under varying conditions. Equilibrium adsorption capacities, based on the Langmuir isotherm model, were determined to be 44.6 mg·g−1 for phosphate (PO43−) and 32.3 mg·g−1 for arsenate (As(V)) at 25 °C. The sorption behavior was better described by the Freundlich isotherm model, which yielded KF values of 15.4 L·mg−1 for phosphate and 13.9 L·mg−1 for arsenate. Both batch and kinetic experiments confirmed the high adsorption efficiency of the composite, demonstrating its potential as a promising material for water treatment applications
Ab-Initio study of water molecule adsorption on monoclinic Scheelite-Type BiVO4 surfaces
No full textHerein, we present a study on the adsorption of one water molecule (bonded to either Bi or V sites) and two water molecules (bonded to both Bi and V sites) onto seven low-index surfaces (001), (010), (011), (100), (101), (110), and (111) as well as one high-index surface (211) of a monoclinic scheelite-type BiVO4 crystal structure using ab initio calculations. By predicting the adsorption energies for different facets, we find that water adsorption is more likely to occur on Bi sites. However, for the (001) and (211) surfaces, water adsorption is more likely on the V sites. Furthermore, we find that the studied low-index facets can be grouped into four distinct categories. Facets within the same group exhibit similar water adsorption energies. These groups are ((001)), ((010), (100)), ((110)), and ((011), (101), (111)). For low-index surfaces, favorable adsorption occurs on the (001) surface on the V sitesThis is the peer-reviewed version of the article: Toprek, D., Koteski, V., Belošević-Čavor, J., Ivanovski, V., & Umićević, A. (2025). Ab-Initio study of water molecule adsorption on monoclinic Scheelite-Type BiVO4 surfaces. Computational Materials Science, 246, 113412. [http://dx.doi.org/10.1016/j.commatsci.2024.113412]
Multifractal analysis of heart dynamics after running with PPG sensor
No full textHeart dynamics changes markedly at increased effort, which is used routinely to assess the heart condition, for example via electrocardiographic (ECG) stress test. However, the intricate nonlinear changes in heart dynamics are not easy to measure during short routine tests, but the ECG holter recordings are used instead [1]. Thereby, heart-rate variability is used as a base biomarker. The problem is that it requires annotation of heartbeats, which can be a cumbersome process in a noisy out-of-hospital measurement, such as holter around-the-clock measurement or in fitness rooms. Moreover, while the market is saturated by new wearables measuring mechanical function of the cardiovascular system, little attention has been paid to exploit them in assessment of complex heart dynamic. To overcome these limitations, we perform a multifractal analysis on 30-second recordings of photoplethysmogram (PPG), ECG, accelerometer (ACC), and phonocardiogram (PCG) signals. The data stem from the SensSmartTech study [2,3], involving synchronized multimodal physiological recordings collected at rest, immediately after treadmill exercise, and during recovery. We focus here on the PPG signal due to its suitability for wearable cardiovascular monitoring. As a benchmark of fitness level, we adopt the Heart Rate Recovery (HRR) index, a clinically validated marker of autonomic reactivation following exertion [4]. The multifractal spectrum was used to extract key features related to cardiovascular complexity—namely, the position of the spectral peak, spectrum width, and asymmetry. These features were used to classify fitness states via supervised logistic regression. Classification results are presented for the PPG sensor, with and without K-fold cross-validation and class balancing. Cross-validation improves stability and generalizability of the model, yielding better separation between physiological states. Our results demonstrate that short-term, optically acquired PPG signals—when analyzed via multifractal dynamics—can serve as a compact, non-invasive tool for characterizing post-exercise heart adaptation and individual fitness levels.X International School and Conference on Photonics : PHOTONICA2023 : book of abstracts; 25 - 29 August 2025 Belgrade, Serbia
Wavelength demultiplexers based on coupled waveguide arrays with nonuniform lengths
No full textWe propose a demultiplexer based on linearly coupled waveguide array, implemented through a simple photonic lattice layout. Straight waveguides minimize propagation losses then bent waveguides, while choosing appropriate distances between waveguides enables us to tune the output wavelength and bandwidth. For two input wavelengths, spatial divide is achieved when a shorter wavelength perfectly transfers it’s power from first to last, then back to the first waveguide, while longer wavelength’s power perfectly transfers from the first to last waveguide for the same length of waveguide array. Any waveguide array which supports periodic propagation and perfect transfer of light supports such multiplexing [1]. However, by selecting Clebsch–Gordan coupling coefficients, bandwidth can be controlled simply by changing the number of waveguides in an array, with the full-width at half-maximum narrowing with the square root of the waveguide number. An experimental proof of this concept was provided by fabricating the demultiplexers in borosilicate glass using femtosecond laser writing [2, 3]. Building upon these designs, we propose a more elaborate structure that introduces non-uniform waveguide lengths to enhance spectral separation for multiple wavelengths. In this configuration, only the input waveguide and its nearest neighbour retain equal lengths, while each subsequent waveguide is progressively shorter. We show results for a 3-wavelength demultiplexer with the maximum insertion loss of 1.22 and the minimum cross talk of −22.02. For a 4-wavelength demultiplexer the maximum insertion loss is 2.76 and the minimum cross talk is −17.43.X International School and Conference on Photonics : PHOTONICA2023 : book of abstracts; 25 - 29 August 2025 Belgrade, Serbia
New Electromagnetic Interference Shielding Materials: Biochars, Scaffolds, Rare Earth, and Ferrite-Based Materials
No full textIn this review, a comprehensive systematic study of the research background, developments, classification, trends, and advances over the past few years in research on new electromagnetic interference (EMI) shielding materials will be described. The following groups of new materials for EMI shielding will be discussed: biochars, scaffolds, rare earth, and ferrite-based materials. We selected two novel, organic, lightweight materials (biochars and scaffolds) and compared their shielding effectiveness to inorganic materials (ferrite and rare earth materials). This article will broadly discuss the EMI shielding performance, the basic principles of EMI shielding, the preparation methods of selected materials, and their application prospects. Biochars are promising, eco-friendly, sustainable, and renewable materials that can be potentially used as a filter in polymer composites for EMI shielding, along with scaffolds. Scaffolds are new-generation, easy-to-manufacture materials with excellent EMI shielding performance. Rare earth (RE) plays an important role in developing high-performance electromagnetic wave absorption materials due to the unique electronic shell configurations and higher ionic radii of RE elements. Ferrite-based materials are often combined with other components to achieve enhanced EMI shielding, mechanical strength, and electrical and thermal conductivity. Finally, the current challenges and future outlook of new EMI shielding materials will be highlighted in the hope of obtaining guidelines for their future development and application. © 2025 by the authors
Domain-specific Word2vec-based trained models - Chem300, Phys300, MatSci200, MatSci300, and Mixed300
No full textThe repository contains materials science, chemistry, and physics-specialized unsupervised trained models. Word embeddings are generated by means of the Word2vec, a natural language processing technique comprised of language model architectures for fast and efficient learning of distributed representations of words. Continuous Skip-gram model architecture with a negative sampling strategy, as implemented in the Gensim library, is employed for model training. The word embeddings consisting of 200 and 300 vectorial components for materials science and 300 vectorial components for chemistry, physics, and mixed domain are here provided.This digital object is hosted on the Figshare server due to its size and is available under the Creative Commons Attribution 4.0 International License
Carbonized almond shells as a sustainable material for electrochemical applications
No full textThe properties of carbon derived from biowaste were investigated to develop environmentally and economically viable electrochemical sensors. Biowaste carbon was obtained by carbonizing almond shells at 800 °C in an inert nitrogen atmosphere. Two batches were prepared: the first contained only almond shells, while the second was enriched with a Bi2O3 composite doped with 5% mass of Sm to enhance the electrochemical properties of the material. The structural and morphological characteristics were analyzed using X-ray diffraction (XRD), Diffuse Reflectance Infrared Fourier Spectroscopy (FTIR-DRIFT), and field emission scanning electron microscopy (FE-SEM). Electrochemical properties were examined by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). A three-electrode system was used, consisting of a carbon paste electrode (CPE) as the working electrode, an Ag/AgCl reference electrode, and a Pt-wire counter electrode. Two different pastes for CPE were prepared: bare almond carbon (BAC) and Bi2O3-Sm-doped almond carbon (AC/Bi2O3-Sm) from the second batch. XRD patterns confirmed the amorphous nature of carbon in both samples, with low-intensity peaks corresponding to Sm-doped Bi2O3 [1,2]. DRIFT spectroscopy further verified the presence of characteristic functional groups, including O-H (hydroxyl group), C-O (phenol group), C=O (carboxylic group), and C=C (alkene group) [3]. FE-SEM analysis revealed an uneven, porous carbon structure. EIS analysis showed a lower charge transfer resistance for the AC/Bi2O3-Sm, correlating with more defined and intense CV peaks, indicating enhanced electron transfer kinetics [4]. The findings demonstrate that carbon derived from almond shells biowaste is a sustainable and eco-friendly option for use in carbon paste electrodes, showcasing good electrochemical characteristics. Future research efforts will concentrate on developing sensors and assessing their performance.Programme and the Book of Abstracts / 8th Conference of The Serbian Society for Ceramic Materials, 8CSCS-2025, June 14-16, 2025, Belgrade, Serbia
Cancers of the oesophagus and stomach: Additional insight from the oral cavity: Mini review
No full textPeriodontitis as a chronic infection that affects between 10 and 15 percent of the world's population. It is characterized by the loss of connective tissue attachment and alveolar bone. Periodontitis and the resulting systemic inflammation are associated with numerous systemic diseases such as cardiovascular disease, diabetes, chronic kidney disease, rheumatoid, arthritis, respiratory diseases, impairment of cognitive function. The exact mechanism of the association between periodontitis and UGI cancers is not known, but may include direct bacterial ingestion, chronic inflammation, and immune modulation. Considering that about 15% of tumors are the result of chronic inflammation, it is necessary to examine in detail the relationship between chronic periodontal disease and UGI cancer. Specifically, keystone periodontal pathogens, including Porphyromonas gingivalis and Treponema denticola may react with the molecular hallmarks of gastrointestinal cancers, triggering mutations, and generate a permissive immune microenvironment by impairing anti-tumor checkpoints
Synchronous post-exercise electrocardiogram, phonocardiogram, photoplethysmograms and seismocardiogram
No full textNoninvasive electromechanical assessment of cardiovascular function is emerging as a cost-effective method for diagnosis of heart failure and arterial diseases, and for telemedical monitoring of blood pressure and neural disorders. It encompasses simultaneous acquisition of electrocardiographic, phonocardiographic, arterial-pulse, chest-vibration, bioimpedance and other waveforms. The phases and amplitudes of these waveforms are used for construction of disease biomarkers. The procedure includes corrections of biomarker values to daily variation and excursions of heart rate. However, datasets that enable a systematic study of the effects of heart rate on mechanical waveforms are currently not available. Here, we describe SensSmartTech - the first dataset of multiparametric cardiovascular signals systematically measured in a large span of heart rates from 52 to 182 beats per minute, achieved by running on a treadmill. Besides providing the data for biomarker correction, the dataset enables new insights into the cardio-respiratory and electro-mechanical couplings in the cardiovascular system.Data for the article available at: Lazović, A., Tadić, P., Đorđević, N., Atanasoski, V., Tiosavljevic, M., Ivanovic, M., Hadzievski, L., Ristic, A., Vukcevic, V., & Petrovic, J. (2024). SensSmartTech database of cardiovascular signals synchronously recorded by an electrocardiograph, phonocardiograph, photoplethysmograph and accelerometer (version 1.0.0). PhysioNet. RRID:SCR_007345. [https://doi.org/10.13026/fy9p-n277