Search Results (16)

Silicate glasses containing silicon, sodium, phosphorous, and calcium have the ability to promote bone regeneration and biodegrade as new tissue is generated. Recently, it has been suggested that adding SrO can benefit tissue growth and silicate glass dissolution. Motivated by these recent developments, the effect of SrO/CaO–CaO/SrO substitution on the local structure and dynamics of Si-Na-P-Ca-O oxide glasses has been studied in this work. Differential thermal analysis has been performed to determine the thermal stability of the glasses after the addition of strontium. The local structure has been studied by neutron diffraction augmented by Reverse Monte Carlo simulation, and the local dynamics by neutron Compton scattering and Raman spectroscopy. Differential thermal analysis has shown that SrO-containing glasses have lower glass transition, melting, and crystallisation temperatures. Moreover, the addition of the Sr²⁺ ions decreased the thermal stability of the glass structure. The total neutron diffraction augmented by the RMC simulation revealed that Sr played a similar role as Ca in the glass structure when substituted on a molar basis. The bond length and the coordination number distributions of the network modifiers and network formers did not change when SrO (x = 0.125, 0.25) was substituted for CaO (25-x). However, the network connectivity increased in glass with 12.5 mol% CaO due to the increased length of the Si-O-Si interconnected chain. The analysis of Raman spectra revealed that substituting CaO with SrO in the glass structure dramatically enhances the intensity of the high-frequency band of 1110–2000 cm⁻¹. For all glasses under investigation, the changes in the relative intensities of Raman bands and the distributions of the bond lengths and coordination numbers upon the SrO substitution were correlated with the values of the widths of nuclear momentum distributions of Si, Na, P, Ca, O, and Sr. The widths of nuclear momentum distributions were observed to soften compared to the values observed and simulated in their parent metal-oxide crystals. The widths of nuclear momentum distributions, obtained from fitting the experimental data to neutron Compton spectra, were related to the amount of disorder of effective force constants acting on individual atomic species in the glasses. Full article

The relationship between slag structure and viscosity is studied, employing Raman spectroscopy for the five-component slag system of MnO-SiO₂-CaO-Al₂O₃-MgO and its subsystems. This study aims to investigate the influence of variations in slag composition on viscosity, which is crucial for optimizing industrial processes. Based on industrial slag compositions produced in a silicomanganese submerged arc furnace, 17 slags with a fixed content of MnO of 10 wt% are synthesized with varying contents of SiO₂ of 33 to 65 wt%; CaO within the range of 14 to 40 wt%; and fixed contents of Al₂O₃ and MgO of 17 and 6 wt%, respectively. The slag compositions are divided into four groups, ranging from low basicity (0.38) to high basicity (0.80), with each group containing the four slag systems of MnO-SiO₂-CaO, MnO-SiO₂-CaO-Al₂O₃, MnO-SiO₂-CaO-MgO, and MnO-SiO₂-CaO-Al₂O₃-MgO, with fixed basicity. Additionally, a five-component composition with the lowest basicity of 0.28 is considered. Raman spectroscopy measurements are performed in the wavenumber range of 200 to 1200 ${\mathrm{cm}}^{-1}$ using a green source laser with a 532 nm wavelength. The high-wavenumber region of the Raman spectra (800 to 1200 ${\mathrm{cm}}^{-1}$) is deconvoluted to quantitatively investigate the effect of each oxide on the slag structure and the degree of polymerization (DOP) of the silicate network. Results indicate that measured NBO/T increases with increasing basicity, demonstrating a reduction in DOP of the silicate structure. This depolymerization effect is more pronounced in slags containing Al₂O₃ compared to those without it. In a group of slags with similar basicity, the substitution of SiO₂ with Al₂O₃ leads to further depolymerization. In contrast, substituting CaO with MgO has little effect on the silicate structure in slags without Al₂O₃ but causes depolymerization in slags containing Al₂O₃. To study the relationship between structure and viscosity, viscosity data obtained from FactSage are used as reference values. The predictions of slag viscosity using the Raman-structure model and the NBO/T viscosity model are then compared to the FactSage results. The adjustable parameters of the Raman-structure model are re-determined using the FactSage data for the studied slag compositions. The NBO/T viscosity model employs both calculated NBO/T values from the slag compositions and measured NBO/T values from the deconvolution results. The findings of this study reveal good agreement between the predictions of the Raman-structure model and the FactSage viscosity data. Full article

The primary objective of neuromorphic electronic devices is the implementation of neural networks that replicate the memory and learning functions of biological synapses. To exploit the advantages of electrolyte gate synaptic transistors operating like biological synapses, we engineered electric double-layer transistors (EDLTs) using phosphorus-doped silicate glass (PSG). To investigate the effects of phosphorus on the EDL and synaptic behavior, undoped silicate spin-on-glass-based transistors were fabricated as a control group. Initially, we measured the frequency-dependent capacitance and double-sweep transfer curves for the metal-oxide-semiconductor (MOS) capacitors and MOS field-effect transistors. Subsequently, we analyzed the excitatory post-synaptic currents (EPSCs), including pre-synaptic single spikes, double spikes, and frequency variations. The capacitance and hysteresis window characteristics of the PSG for synaptic operations were verified. To assess the specific synaptic operational characteristics of PSG-EDLTs, we examined EPSCs based on the spike number and established synaptic weights in potentiation and depression (P/D) in relation to pre-synaptic variables. Normalizing the P/D results, we extracted the parameter values for the nonlinearity factor, asymmetric ratio, and dynamic range based on the pre-synaptic variables, revealing the trade-off relationships among them. Finally, based on artificial neural network simulations, we verified the high-recognition rate of PSG-EDLTs for handwritten digits. These results suggest that phosphorus-based EDLTs are beneficial for implementing high-performance artificial synaptic hardware. Full article

Membrane technology is a promising method for gas separation. Due to its low energy consumption, environmental safety, and ease of operation, membrane separation has a distinct advantage over the cryogenic distillation conventionally used to capture light inert gases. For efficient gas recovery and purification, membrane materials should be highly selective, highly permeable, thermally stable, and low-cost. Currently, many studies are focused on the development of high-tech materials with specific properties using industrial waste. One of the promising waste products that can be recycled into membrane materials with improved microstructure is cenospheres—hollow aluminosilicate spherical particles that are formed in fly ash from coal combustion during power generation. For this purpose, based on narrow fractions of fly ash cenospheres containing single-ring and network structure globules, silicate glass/mullite composites were prepared, characterized, and tested for helium–neon mixture separation. The results indicate that the fragmented structure of the cenosphere shells with areas enriched in SiO₂ without modifier oxides, formed due to the crystallization of defective phases of mullite, quartz, cristobalite, and anorthite, significantly facilitates the gas transport process. The permeability coefficients He and Ne exceed similar values for silicate glasses; the selectivity corresponds to a high level even at a high temperature: αHe/Ne—22 and 174 at 280 °C. Full article

To address the challenges in real-time process diagnosis within the semiconductor manufacturing industry, this paper presents a novel machine learning approach for analyzing the time-varying 10th harmonics during the deposition of low-k oxide (SiOF) on a 600 Å undoped silicate glass thin liner using a high-density plasma chemical vapor deposition system. The 10th harmonics, which are high-frequency components 10 times the fundamental frequency, are generated in the plasma sheath because of their nonlinear nature. An artificial neural network with a three-hidden-layer architecture was applied and optimized using k-fold cross-validation to analyze the harmonics generated in the plasma sheath during the deposition process. The model exhibited a binary cross-entropy loss of 0.1277 and achieved an accuracy of 0.9461. This approach enables the accurate prediction of process performance, resulting in significant cost reduction and enhancement of semiconductor manufacturing processes. This model has the potential to improve defect control and yield, thereby benefiting the semiconductor industry. Despite the limitations imposed by the limited dataset, the model demonstrated promising results, and further performance improvements are anticipated with the inclusion of additional data in future studies. Full article

Polyethylene oxide (PEO)-based composite polymer electrolytes (CPEs) containing in situ SiO₂ fillers are prepared using an electrostatic spinning method at room temperature. Through the in situ hydrolysis of tetraethyl silicate (TEOS), the generated SiO₂ nanospheres are uniformly dispersed in the PEO matrix to form a 3D ceramic network, which enhances the mechanical properties of the electrolyte as a reinforcing phase. The interaction between SiO₂ nanospheres and PEO chains results in chemical bonding with a decrease in the crystallinity of the PEO matrix, as well as the complexation strength of PEO chains with lithium ions during the hydrolysis process. Meanwhile, the addition of SiO₂ nanospheres can disturb the orderliness of PEO chain segments and further suppress the crystallization of the PEO matrix. Therefore, improved mechanical/electrochemical properties can be obtained in the as-spun electrolyte with the unique one-dimensional high-speed ion channels. The electrospun CPE with in situ SiO₂ (10 wt%, ca. 45 nm) has a higher ionic conductivity of 1.03 × 10⁻³ S cm⁻¹ than that of the mechanical blending one. Meanwhile, the upper limit of the electrochemical stability window is up to 5.5 V versus Li⁺/Li, and a lithium-ion migration number can be of up to 0.282 at room temperature. In addition, in situ SiO₂ electrospun CPE achieves a tensile strength of 1.12 MPa, elongation at the break of 488.1%, and it has an excellent plasticity. All in all, it is expected that the electrospun CPE prepared in this study is a promising one for application in an all-solid-state lithium-ion battery (LIB) with a high energy density, long life cycle, and high safety. Full article

In the aluminum industry, one of the most sensitive economic and environmental problems is the management of resulting waste such as slag, ash and sludge, which become potential sources of pollution. Red sludge, which results from the aluminum industry, is a mixture made up of different forms of iron and aluminum oxides, sodium and aluminum silicates, various titanium compounds, constituted in the residue left after the alkaline solubilization of alumina. The Purpose of this research is to quantify the environmental aspects involved in the storage of sludge in a landfill that has an area of 381,189 square meters and is located in the hearth of a former ballast tank in the western industrial area of the town of Oradea, Romania. The objective of the research was to determine the impact of red sludge dumps, which originated from industrial activity, on the soil and groundwater. The degree of degradation of the soil cover was highlighted by analyzing a number of 12 soil samples (4 collection points, at 3 depths). A total of 14 samples (7 samples on 2 depths) were investigated to monitor the migration mode of the sludge in the structure of the dam. In order to monitor the quality of groundwater, samples from 3 observation boreholes were analyzed. Soil monitoring results did not indicate values of the analyzed parameters above the values imposed by the national legislation on soil quality. Since the dumps were not waterproofed, the quality parameters of the water from the observation boreholes were exceeded, and gravity caused the water to drain into the underground water network in the area. Based on the samples from the observation boreholes, several measurements exceeded allowable values: pH values of the water sample taken from upstream of the dump exceeded the value limits by about 7%, and both upstream and downstream, water samples indicate an excess of 13.60% in the aluminum indicator, 267% in the sulfate ion, and 417% in the sodium ion. This shows a risk of pollution which requires additional monitoring. Full article

The symmetry of an interconnection network plays a key role in defining the functioning of a system involving multiprocessors where thousands of processor-memory pairs known as processing nodes are connected. Addressing the processing nodes helps to create efficient routing and broadcasting algorithms for the multiprocessor interconnection networks. Oxide interconnection networks are extracted from the silicate networks having applications in multiprocessor systems due to their symmetry, smaller diameter, connectivity and simplicity of structure, and a constant number of links per node with the increasing size of the network can avoid overloading of nodes. The fault tolerant partition basis assigns unique addresses to each processing node in terms of distances (hops) from the other subnets in the network which work in the presence of faults. In this manuscript, the partition and fault tolerant partition resolvability of oxide interconnection networks have been studied which include single oxide chain networks ($SOXCN$), rhombus oxide networks ($RHOXN$) and regular triangulene oxide networks ($RTOXN$). Further, an application of fault tolerant partition basis in case of region-based routing in the networks is included. Full article

The utilization of ordinary Portland cement (OPC) in conventional concretes is synonymous with high carbon emissions. To remedy this, an environmentally friendly concrete, alkaline-activated slag concrete (AASC), where OPC is completely replaced by ground granulated blast-furnace slag (GGBFS) industrial waste, is one of the currently pursued research interests. AASC is not commonly used in the construction industry due to limitations in experience and knowledge on the mix proportions and mechanical properties. To circumvent great labour in the experimental works toward the determination of the optimal properties, this study, therefore, presents the compressive strength prediction of AASC by employing the back-propagation artificial neural network (ANN) modelling technique. To construct this model, a sufficiently equipped experimental databank was built from the literature covering varied mix proportion effects on the compressive strength of AASC. For this, four model variants with different input parameter considerations were examined and the ideal ANN architecture for each model with the best input number–hidden layer neuron number–output number format was identified to improve its prediction accuracy. From such a setting, the most accurate prediction model with the highest determination coefficient, R², of 0.9817 was determined, with an ANN architecture of 8-18-1 containing inputs such as GGBFS, a fine to total aggregate ratio, sodium silicate, sodium hydroxide, mixing water, silica modulus of activator, percentage of sodium oxide and water–binder ratio. The prediction accuracy of the optimal ANN model was then compared to existing ANN-based models, while the variable selection was compared to existing AASC models with other machine learning algorithms, due to limitations in the ANN-based model. To identify the parametric influence, the individual relative importance of each input variable was determined through a sensitivity analysis using the connection weight approach, whose results indicated that the silica modulus of the activator and sodium silicate greatly affected the AASC compressive strength. The proposed methodology demonstrates that the ANN-based model can predict the AASC compressive strength with a high accuracy and, consequently, aids in promoting the utilization of AASC in the construction industry as green concrete without performing destructive tests. This prediction model can also accelerate the use of AASC without using a cement binder in the concrete matrix, leading to produce a sustainable construction material. Full article

Plasma electrolytic oxidation coatings were prepared in aluminate, phosphate, and silicate-based electrolytic solutions using a soft-sparking regime in a multi-frequency stepped process to compare the structure, corrosion, and wear characteristics of the obtained coatings on AZ31 magnesium alloy. The XRD results indicated that all coatings consist of MgO and MgF₂, while specific products such as Mg₂SiO₄, MgSiO₃, Mg₂P₂O₇, and MgAl₂O₄ were also present in specimens based on the selected solution. Surface morphology of the obtained coatings was strongly affected by the electrolyte composition. Aluminate-containing coating showed volcano-like, nodular particles and craters distributed over the surface. Phosphate-containing coating presented a sintering-crater structure, with non-uniform distributions of micro-pores and micro-cracks. Silicate-containing coating exhibited a scaffold surface involving a network of numerous micro-pores and oxide granules. The aluminate-treated sample offered the highest corrosion resistance and the minimum wear rate (5 × 10⁻⁵ mm³ N⁻¹ m⁻¹), owing to its compact structure containing solely 1.75% relative porosity, which is the lowest value in comparison with other samples. The silicate-treated sample was degraded faster in long-term corrosion and wear tests due to its porous structure, and with more delay in the phosphate-containing coating due to its larger thickness (30 µm). Full article

In glass materials, Poisson’s ratio (ν) has been proposed to be correlated with a variety of features, including atomic packing density (C_g), liquid fragility (m), and network connectivity. To further investigate these correlations in oxide glasses, here, we study cesium borate and cesium silicate glasses with varying modifier/former ratio given the difference in network former coordination and because cesium results in relatively high ν compared to the smaller alkali modifiers. Within the binary glass series, we find positive correlations between ν on one hand and m and C_g on the other hand. The network former is found to greatly influence the correlation between ν and the number of bridging oxygens (n_BO), with a negative correlation for silicate glasses and positive correlation for borate glasses. An analysis based on topological constraint theory shows that this difference cannot be explained by the effect of superstructural units on the network connectivity in lithium borate glasses. Considering a wider range of oxide glasses from the literature, we find that ν generally decreases with increasing network connectivity, but with notable exceptions for heavy alkali borate glasses and calcium alumino tectosilicate glasses. Full article

Plasma electrolytic oxidation (PEO) coatings were grown on AZ31 Mg alloy in a silicate-based electrolyte containing KF using unipolar and bipolar (usual and soft-sparking) waveforms. The coatings were dual-layered consisting of MgO, MgF₂ and Mg₂SiO₄ phases. Surface morphology of the coatings was a net-like (scaffold) containing a micro-pores network, micro-cracks and granules of oxide compounds. Deep pores were observed in the coating produced by unipolar and usual bipolar waveforms. The soft-sparking eliminated the deep pores and produced the lowest porosity in the coatings. It was found that the corrosion performance of the coatings evaluated using EIS in 3.5 wt. % NaCl solution is mostly determined by the inner layer resistance, because of its higher compactness. After 4 days of immersion, the inner layer resistances were almost the same for all coatings. However, the coatings produced by unipolar and usual bipolar waveforms showed sharp decays in inner layer resistances after 1 week and even the barrier effect of outer layer was lost for the unipolar-produced coating after 3 weeks. The low-frequency inductive loops appeared after a 3-week immersion for all coatings indicated that the substrate was under local corrosion attack. However, both coatings produced by soft-sparking waveforms provided the highest corrosion performance. Full article

Topological indices are numeric quantities that describes the topology of molecular structure in mathematical chemistry. An important area of applied mathematics is the chemical reaction network theory. Real-world problems can be modeled using this theory. Due to its worldwide applications, chemical networks have attracted researchers since their foundation. In this report, some silicate and oxide networks are studied, and exact expressions of some newly-developed neighborhood degree-based topological indices named as the neighborhood Zagreb index ( $M_N$ ), the neighborhood version of the forgotten topological index ( $F_N$ ), the modified neighborhood version of the forgotten topological index ( $F_N^{\ast }$ ), the neighborhood version of the second Zagreb index ( $M_2^{\ast }$ ), and neighborhood version of the hyper Zagreb index ( $H{M}_N$ ) are obtained for the aforementioned networks. In addition, a comparison among all the indices is shown graphically. Full article

There is a high iron content in nickel slag that mainly exists in the fayalite phase. Basic oxide can destroy the stable structure of fayalite which is beneficial to the treatment and comprehensive utilization of nickel slag. The research was based on the composition of the raw nickel slag, taking the CaO-SiO₂-FeO-MgO system as the object and CaO as a modifier. The effect of basicity on the melting characteristics, viscosity and structure of the CaO-SiO₂-FeO-MgO system was studied. The relationship between the viscosity and structure of the CaO-SiO₂-FeO-MgO system was also explored. The results show as follows: (1) When the basicity is lower than 0.90, the primary phase of the slag system is olivine phase. When the basicity is greater than 0.90, the primary phase of the slag system transforms into monoxide. When the basicity is 0.90, olivine and monoxide precipitate together as the temperature continues to decrease. At the same time, the liquidus temperature, softening temperature, hemispherical temperature, and flow temperature all reach the lowest value. (2) With the increase of basicity, the critical viscosity temperature of the CaO-SiO₂-FeO-MgO system decreases first and then increases. Critical viscosity temperature is the lowest at the basicity of 0.90, which is 1295 °C. (3) When the slag system is heterogeneous, the viscosity of the molten slag increases rapidly because of the quantity of solid phase precipitated from the CaO-SiO₂-FeO-MgO system. (4) When the slag system is in a homogeneous liquid phase, the molar fraction of O⁰ decreases with the increase of basicity and the mole fraction of O⁻, and O²⁻ increases continuously at the basicity of 0.38~1.50. The silicate network structure is gradually depolymerized into simple monomers, resulting in the degree of polymerization, and the viscosity, being reduced. The mole fraction of different kinds of oxygen atoms is converged to a constant value when the basicity is above 1.20. Full article

With a view to satisfying the requirements of environmental protest and efficient usage of resources, a novel process for efficiently extracting vanadium (V), titanium (Ti), and iron (Fe) from vanadium-bearing titanomagnetite concentrate was developed. In the new process, vanadium is pre-extracted by additive-free roasting under the air atmosphere and alkaline leaching technologies. In this paper, transformation of vanadium-bearing titanomagnetite concentrate in the roasting is investigated based on thermodynamic analyses and experimental discussion. Thermodynamic analyses show that oxidation of V(III) into V(V) would happen in the roasting experiment over the range of 327–1327 °C and vanadium-iron spinel phase (FeV₂O₄) can be oxidized more easily than magnetite (Fe₃O₄) when the temperature is higher than 861 °C. Experimental results show that some compounds (V₂O₅, Fe₂Al₄Si₅O₁₈, and Fe₂SiO₄) with low melting temperature were obtained by solid reactions at low temperature and melted as a binding phase at elevated temperature. Liquids were generated due to some chemical reactions or phase transformation reaction (Fe₂V₂O₄(s) → Fe₂O₃(s) + liquid) at elevated temperature. Main phases of Fe₂O₃ and Fe₂TiO₅ are connected and sintered with the binding phases of the compounds with low melting temperature or the mixtures with low liquidus temperature. In addition, higher roasting temperature leads to higher vanadium leaching efficiency over the range of 800–1200 °C. However, over-burning would happen at 1250 °C, some of vanadium oxide was wrapped by silicate network, and the conversion of V(III) into V(V) was prevented from occurring. Therefore, the vanadium leaching efficiency decreased from 59.1% (T_roa. = 1200 °C) to 57% (T_roa. = 1250 °C). Full article