Sand Ratio Research Articles

Experimental Study and Machine Learning-Based Prediction of the Abrasion Resistance of Manufactured Sand Concrete

To systematically analyze the impact of manufactured sand on the abrasion resistance of concrete, this paper investigates the correlation between sand type, sand ratio, stone powder content, compressive strength, and the abrasion resistance of manufactured sand concrete. Grey correlation analysis was conducted to assess the impact priority of each factor affecting the abrasion resistance, and prediction models for the abrasion resistance were developed using XGBoost, random forest, AdaBoost, and gradient boosting. The results indicate that compared to river sand concrete, C30 and C40 concrete prepared with limestone and diabase manufactured sand has 20% higher abrasion resistance due to the presence of stone powder and higher roughness and solidity. Within the range of 0.40 to 0.44, a lower sand ratio leads to higher abrasion resistance. For concrete prepared with manufactured sand containing 5% to 11% stone powder, the best abrasion resistance can be attained at a stone powder content of 9%, and microscopic analysis suggests the highest concrete density at this level. According to grey system theory, the influence of each affecting factor on the abrasion resistance follows the order: sand ratio > crushing value > roughness > compressive strength > stone powder content > 0.6. Compared to gradient boosting, random forest, and AdaBoost models, the XGBoost model adopted in this study showed relatively higher R2 and lower RMSE in both the training and testing sets, which proved its higher accuracy in predicting the abrasion loss of manufactured sand concrete. The machine learning models offer some guidance for predicting and enhancing the abrasion resistance of manufactured sand concrete in practical engineering.

Multi-Task Learning Network-Based Prediction of Hydraulic Fracturing Effects in Horizontal Wells Within the Ordos Yanchang Formation Tight Reservoir

Accurate prediction of fracture volume and morphology in horizontal wells is essential for optimizing reservoir development. Traditional methods struggle to capture the intricate relationships between fracturing effects, geological variables, and operational factors, leading to reduced prediction accuracy. To address these limitations, this paper introduces a multi-task prediction model designed to forecast fracturing outcomes. The model is based on a comprehensive dataset derived from fracturing simulations within the Long 4 + 5 and Long 6 reservoirs, incorporating both operational and geological factors. Pearson correlation analysis was conducted to assess the relationships between these factors, ranking them according to their influence on fracturing performance. The results reveal that operational variables predominantly affect Stimulated Reservoir Volume (SRV), while geological variables exert a stronger influence on fracture morphology. Key operational parameters impacting fracturing performance include fracturing fluid volume, total fluid volume, pre-fluid volume, construction displacement, fracturing fluid viscosity, and sand ratio. Geological factors affecting fracture morphology include vertical stress, minimum horizontal principal stress, maximum horizontal principal stress, and layer thickness. A multi-task prediction model was developed using random forest (RF) and particle swarm optimization (PSO) methodologies. The model independently predicts SRV and fracture morphology, achieving an R2 value of 0.981 for fracture volume predictions, with an average error reduced to 1.644%. Additionally, the model’s fracture morphology classification accuracy reaches 93.36%, outperforming alternative models and demonstrating strong predictive capabilities. This model offers a valuable tool for improving the precision of fracturing effect predictions, making it a critical asset for reservoir development optimization.

Determination of Settling Velocity for Cohesive Sediments Using a Settling Column Experiment—Case Study: Ca Mau, Vietnam

The settling velocity (Ws) is a fundamental parameter in sediment dynamics, particularly in the coastal zones as estuarine and mangrove ecosystems, where various physical processes interact to influence sediment transport and deposition. Determining settling velocity is essential for understanding and predicting sediment transport, erosion–deposition processes in coastal environments. This study aims to determine the settling velocity and examines how sediment concentration affects settling velocity, using empirical models. The study applies these methods to compute the settling velocity of fine sediments in Ca Mau, Vietnam, which were collected in the Song Doc area (Western) in August 2014 and Rach Goc area (Eastern) in August 2015. The particle size analysis results indicate that the sediment samples from Western Ca Mau are coarser than those from Eastern Ca Mau, with sand ratios of 42.78% and 7.08% at the outer station, and 19.09% and 4.39% at the mangroves, respectively. The results also show that the average settling velocity of the sediment samples from Western Ca Mau is higher than that of the samples from Eastern Ca Mau. Specifically, the settling velocity in Western Ca Mau is 2.80 × 10−4 m s–1 at the outer station and 1.68 × 10−4 m s–1 at the mangroves. Meanwhile, in Eastern Ca Mau, the settling velocity of the sediment samples is 1.99 × 10−4 m s–1 at the outer station and 1.42 × 10−4 m s–1 at the mudflat-mangrove. Hence, it can be seen that the settling velocity of cohesive sediments corresponds well with the sediment’s particle size.

The mechanism of proppant transport dynamic propagation in rough fracture for supercritical CO2 fracturing

Supercritical CO2 fracturing technology has shown great potential for enhancing production in unconventional reservoirs. It is essential to clarify the transport mechanism of proppant under the dynamic propagation conditions within rough fractures. A realistic rough fracture model is reconstructed, and Computational Fluid Dynamics simulations are conducted to track proppant movement during fracture propagation. The typical transport characteristics of proppant within rough fractures are revealed, and the effects of fracture propagation rate, proppant density, mass flow rate, particle size, sand ratio, and temperature on the support effect are discussed. The results show that the flow channels formed by sand carrying fluid in rough fractures are complex, with fracture propagation changing some flow channels. The proppant forms an irregular sand bed interspersed with unfilled areas, and complex flow characteristics are generated. The increase in fractal dimension increases the resistance in the fluid flow process and affects the movement of the proppant, which tends to create unfilled areas. Low density and size of proppant can improve the proppant placement length. In a certain temperature range, high temperature injection of sand carrying fluid can improve the proppant placement effect. In addition, the low sand ratio and high mass flow rate pumping can be used to form the dominant channel, followed by pumping with a high sand ratio and low mass flow rate for effective support.

Investigating the Long-Term Effects of Anthropogenic Practices on Soil Features

Anthropogenic practices have been increasingly conducted on the rise in addressing the escalatingdemands for socioeconomic development, resulting in significant impacts on land ecosystems. This research seeks toevaluate the influence of anthropogenic activities on soil features in mountainous regions of Vietnam by focusing 84samples collected from 12 locations across Lam River Basin at seven soil profiles (0-10, 10-20, 20-30, 30-40, 40-60, 60-80 and 80-100 cm).The findings reveal notable differences in soil texture among land use types (LUTs). Forest cover lands (FCLs),showed the least amount of sand content, varying from 29.7% to 37.6%, while unplanted and bare lands (UBLs) had thehighest sand ratios, up to 53.9%. FCLs exhibited lowest bulk density (BD), soil porosity (SP) and soil electricalconductivity (EC) and C:N ratio with respective ranges of 0.93-1.29 g.cm-3, 32.7-36.5%, 0.526-0.743 mS.m-1 and6.74 -8.52, respectively.In contrast, crop cultivation lands (CCLs) demonstrated higher values for BD (1.17-1.25 g/cm3), SP (39.25-43.19%), EC (0.583-0.792 mS.m-1) and C:N ratio (11.27-15.77). UBLs, on the other hand, exhibited even highest valuesup to 1.23-1.36 g.cm-1, 43.19-49.62%, 0.437-0.619 mS.m-1 and 11.68-16.58% and displayed high levels of exchange ironsand soil organic content compared to FCLs. Other factors such as pH varied little in space between the sampled soillocations and along the soil profiles. Overall, the study indicates that anthropogenic practices have impacts on the soilfeatures across the study area.

Water Turbine Guide Blades Effect of Quartz Sand on Abrasion Rate

Abstract Hydroelectric power plants with the aim of being used to generate electrical energy are mostly operated in areas with sedimentation content which can cause wear and tear on the components of the hydropower plant. This activity is emphasized to determine the effect of quartz sand on the rate of abrasion on the guide vanes of the Francis type water turbine. This activity was carried out using a water turbine guide blade abrasion test tool with a guide blade test object made of SUS 304 stainless steel material. The results are presented quantitatively and qualitatively, the greater the concentration and diameter of the quartz sand particles, the water pressure and the angle given at the same time, the greater the rate of abrasion that occurs in the francis type water turbine guide vane. The highest abrasion rate was 5.10 (g/cm2 x hour) in the angle variation test with a constant Q and a water: sand ratio of 70%: 30%.

Eco-Friendly Shield Muck-Incorporated Grouting Materials: Mix Optimization and Property Evaluation for Silty Clay Tunnel Construction

As shield tunnels increase, managing shield muck strains construction and the environment. To mitigate this problem, shield muck replaced bentonite in silty clay to improve synchronous grouting slurry. Initially, the physical attributes and microstructural composition of shield muck were obtained, alongside an analysis of the effects of the muck content, particle size, and general influencing factors on the slurry properties through standardized tests and regression models. Subsequently, leveraging three-dimensional response surface methodology, admixture interactions and multiple factor impacts on the slurry were explored. Finally, utilizing the SQP optimization technique, an optimal slurry blend ratio tailored for actual project needs was derived for improved muck slurry. The findings reveal with the decreasing bleeding rates as the muck content rises, the particle size diminishes. An inverse relationship exists between the muck content and slurry fluidity. At soil–binder ratios below 0.6, a decrease in the soil–binder ratio intensifies the influence of the water–binder ratio on the slurry density, bleeding rate, and setting time. The fly flash–cement ratio inversely correlates with the slurry bleeding rate, while the ratio greater than 0.6 is positively correlated. For muck particle sizes under 0.2 mm, the fly flash–cement ratio inversely impacts the density, while over 0.2 mm, it correlates positively. The optimal proportion for silty clay stratum synchronous grouting slurry, substituting muck for bentonite, includes a water–binder ratio of 0.559, binder–sand ratio of 0.684, fly flash–cement ratio of 2.080, soil–binder ratio of 0.253, particle size under 0.075 mm, and water-reducing admixture of 0.06.

Effects of aggregates and fibers on the strength and permeability of concrete exposed to low vacuum environment

The performance and regulation of concrete in low vacuum environments are receiving increasing attention. This study investigates the effects of aggregates and fibers on the strength and permeability of concrete in a low vacuum environment, using varying gradients of sand ratios (37.5 %, 40 %, and 42 %) and aggregate-to-binder ratios (3.27, 3.92, and 4.14). Three types of non-metallic fibers are utilized: polyethylene (PE), polyvinyl alcohol (PVA), and glass fibers. Evaluations focus on concrete strength, mass loss, gas permeability, capillary water absorption, and porosity. Results indicate that higher sand and aggregate-to-binder ratios enhance both flexural and compressive strength. Fiber incorporation improves flexural and compressive toughness, with PE fibers showing the most significant toughening effect. The low vacuum environment increases the strength of the concrete but reduces its axial compression toughness ratio and increases brittleness, while fiber incorporation helps improve the compression toughness of the concrete. Higher sand and aggregate-to-binder ratios reduce mass loss and accelerate drying equilibrium, while fibers increase mass loss and prolong drying equilibrium, with PVA fibers causing greater mass loss. The pattern of concrete mass loss can be explained by the tortuosity of the moisture diffusion path. Additionally, low vacuum significantly increases the gas permeability of concrete. Enhancing the sand and aggregate-to-binder ratios reduces permeability both before and after low vacuum treatment. Although fibers increase the gas permeability, they help mitigate this increase under low vacuum condition. Capillary water absorption tests reveal that concrete under low vacuum condition has a significantly higher water absorption rate compared to air-drying condition. Increasing sand and aggregate-to-binder ratios reduces water absorption and capillary water content, whereas fibers have the opposite effect. Porosity tests show that moisture migration in a low vacuum environment is mainly related to permeable porosity, while total porosity is more closely related to compressive strength.

Material Design and Performance Study of a Porous Sound-Absorbing Sound Barrier

A new type of porous sound-absorbing sound barrier was developed with quartz sand and self-developed polysiloxane resin. The forming process of the material was studied. The test specimens of the porous sound-absorbing sound barrier were prepared with different mesh numbers of quartz sand and different proportions of resin, and the void properties, compressive strength, durability, and acoustic performance were investigated. Based on the mix design results, it is suggested that 20-mesh quartz sand and a 10:1 mass ratio of quartz sand are used to prepare the porous sound-absorbing sound barrier. The durability study showed that the porous sound-absorbing sound-barrier material had good salt and alkali resistance, poor acid resistance, good water stability, and freeze–thaw stability. The laboratory acoustic test and practical engineering application results showed that the porous sound-absorbing sound barrier had excellent acoustic performance and good noise-reduction effects.

Soil texture analysis using controlled image processing

Soil texture analysis is crucial for crop selection, fertilizer recommendation, and production. Traditional soil testing in the lab using chemicals is highly time-consuming, expensive, and risky harmful chemicals; proper equipment and trained professionals are required to get the readings and to conduct the analysis. These issues can be resolved using image processing. In this study, we proposed a Blackbox prototype machine to take images in a controlled environment under the fixed intensity of light, distance, and standard dry conditions to analyze soil texture. This innovative machine, with its efficient and precise image processing capabilities, has the potential to revolutionize soil texture analysis. Also, we marked the center points of each type of soil texture as defined in the USDA texture triangle. Hundreds of soil samples were prepared for each type according to the center point's sand, silt, and clay ratio. The image processing-based model is trained for texture analysis. This research aims to reduce the soil texture analysis time and provide a system that can do extensive analyses automatically and with accuracy. The proposed Blackbox prototype machine has proven effective in providing a controlled environment for taking images. Also, the proposed model detects soil texture with a maximum accuracy of 99.5 %. A proposed model trained on the soil samples of different texture classes available in the USDA texture triangle accurately performed texture analysis. The results benefit the recommendation of appropriate crops and fertilizers based on a given soil sample in a very short time and cost-effectively.

Experimental Study on the Transport Behavior of Micron-Sized Sand Particles in a Wellbore

In the process of natural gas hydrate extraction, especially in offshore hydrate extraction, the multiphase flow inside the wellbore is complex and prone to flow difficulties caused by reservoir sand production, leading to pipeline blockage accidents, posing a threat to the safety of hydrate extraction. This paper presents experimental research on the migration characteristics of micrometer-sized sand particles entering the wellbore, detailing the influence of key parameters such as sand particle size, sand ratio, wellbore deviation angle, fluid velocity, and fluid viscosity on the sand bed height. It establishes a predictive model for the deposition height of micrometer-sized sand particles. The model’s predicted results align well with experimental findings, and under the experimental conditions of this study, the model’s average prediction error for the sand bed height is 12.47%, indicating that the proposed model demonstrates a high level of accuracy in predicting the bed height. The research results can serve as a practical basis and engineering guidance for reducing the risk of natural gas hydrate and sand blockages, determining reasonable extraction procedures, and ensuring the safety of wellbore flow.

Multi-angle research on the performance of self-foaming filling materials and analysis of engineering applications

Utilizing self-foaming filling material to fill the hollow area is an effective way to settle the issues of low rate and poor effect of filling and roofing in the large stope. There are fewer studies related to the expansion rate, hydration exotherm and strength properties of self-foaming fillers in mines. Based on this, this paper investigates the expansion characteristics, hydration exothermic characteristics and compressive strength characteristics of the self-foaming filler under different cement-tailings ratios (1:4, 1:6, 1:8), reveals the hydration reaction mechanism of the material and its microscopic characteristics through XRD, TG and SEM tests, and evaluates the application effect and economy of the self-foaming filler in practical engineering with the background of Mashong Iron Ore Mine. The main findings are as follows: (1) The volumetric expansion of self-foaming filling material can be divided into the initial stage Ⅰ (0–1.5 h), the rapid reaction stage Ⅱ (1.5–8 h) and the stabilization stage, and as the cement-tailings ratio grows, the expansion rate of the filling body increases, and the expansion rate of the filling material with 1:4 ratio is as high as 20.4 %. (2) The hydration process of a self-foaming filled body does not contain induction and acceleration stages; under the same conditions, the self-foaming filled body has more exothermic heat of hydration than that of a self-foaming filled body by about 50 J/g, and the bigger the cement-tailings ratio, the bigger the hydration exothermic rate and exothermic quantity. (3) The compressive strength of self-foaming filler is inferior to the strength of conventional filler, the higher the cement-tailings ratio, the greater the degree of hydration, the more hydration products are produced, and the greater the compressive strength. (4) The bigger the ratio of gray sand, the greater the proportion of macropores and the actual engineering of self-foaming filling materials to catch the top rate of up to 98 %, directly saving the total cost of 11.6 %. The above research results can offer theoretical support and scientific guidance for the utilization of spontaneous foam materials to fill the goaf and control the roof rate, temperature, and strength of the stope.

Investigation on compressive strength and splitting tensile strength of manufactured sand concrete: Machine learning prediction and experimental verification

Due to experimental constraints, traditional strength prediction models for manufactured sand concrete (MSC) exhibit significant limitations and have a narrow range of applicability. To overcome these limitations and enhance prediction accuracy, this paper, based on the widespread application of machine learning in concrete performance research, employed four algorithms: Support Vector Regression (SVR), Random Forest Regression (RFR), Gradient Boosting (GB), and Extreme Gradient Boosting (XGB) to develop highly accurate and strongly generalizable models for predicting the compressive strength (CS) and splitting tensile strength (STS) ofMSC. The predictive performance of each model was evaluated, the influence laws of various factors were analyzed, and finally, macroscopic experiments were conducted to validate the models' prediction accuracy and generalization ability. The development of these models and the analysis of the influence laws of various factors on the strength of MSC provide a valuable reference for the mix design. The conclusions are as follows: (1) The XGB model demonstrates the highest prediction accuracy and strongest generalization ability for both the CS and STS of MSC, achieving R2 values of 0.98 and 0.94 on the testing set, respectively. (2) The CS and STS of MSC are primarily influenced by four factors: water-binder ratio (W/B), curing age (AGE), cement (C), and coarse aggregate (RI≥0.08869, RI: relative importance), showing a positive correlation with AGE and C, and a negative correlation with W/B. As the fly ash content, stone powder content, maximum particle size of coarse aggregate, and sand ratio increase, the CS and STS initially increase and then decrease. Appropriately increasing the fineness modulus of manufactured sand is beneficial to both CS and STS, while the addition of slag is beneficial to CS and harmful to STS. (3) The prediction accuracy and generalization ability of the XGB model are verified through three sets of macroscopic experiments: C30, C35, and C40. The relative errors of each set's predictions are less than 8 %. (4) A graphical user interface is constructed based on the XGB model, enhancing its practicality.

Effects of recycled sand and shell sand as sand replacement on the dynamic properties of seawater sea-sand recycled aggregate concrete

This study utilizes recycled sand and shell sand to replace sea-sand in seawater sea-sand recycled aggregate concrete (SSRAC) and explores their dynamic compressive properties. A total of 28 sets of specimens were designed, and their stress-strain curves under different strain rates were analyzed. The findings indicated that the dynamic increasing factor (DIF) of peak stress in SSRAC reached its peak at a 50% replacement ratio of recycled sand, exhibiting a 3.9% to 7.7% increase compared to a 0% replacement ratio. Conversely, there was an overall decreasing trend in the DIF when the replacement ratio of shell sand increased. Using recycled sand resulted in an average reduction of approximately 45% in the elastic modulus of the interfacial transition zone (ITZ), while the introduction of shell sand slightly increased that of it. Finally, considering strain rate effects, a dynamic compressive prediction model for SSRAC with different types of fine aggregates was established.

Study on Freeze–Thaw Resistance of Cement Concrete with Manufactured Sand Based on BP Neural Network

In this study, experiments were conducted on the freeze–thaw performance of manufactured sand cement concrete with different sand ratios and fly ash contents. The research found that during 200 freeze–thaw cycles, as the fly ash content increased, the concrete exhibited a higher mass loss rate and a decline in the relative dynamic modulus of elasticity. This was due to the lower activity of SiO2 and Al2O3 in the fly ash, which reduced the hydration products. Incorporating an optimal amount of manufactured sand can increase the density of concrete, thereby improving its resistance to freeze–thaw cycles. However, when the content of manufactured sand was high, its large surface area could interfere with the hydration process and reduce strength, thereby diminishing the freeze–thaw resistance of the concrete. Given that studying the freeze–thaw resistance of manufactured sand concrete is time-consuming and influenced by many factors, a prediction model based on a BP (back propagation) neural network was developed to estimate the mass loss rate and the relative dynamic modulus of elasticity following freeze–thaw cycles. After validation, the model was found to be highly reliable and could serve as a foundation for mix design decisions and freeze–thaw performance prediction of manufactured sand cement concrete.

Harnessing hazardous wastes: the production, characterization, and performance of controlled low strength materials using common effluent treatment plant sludge

India's rapid industrialization has led to an increase in waste generation, necessitating efficient disposal methods. This research addresses this challenge by exploring the use of Common Effluent Treatment Plant (CETP) sludge, a hazardous waste, in the production of Controlled Low-Strength Materials (CLSM). The study aims to mitigate the environmental impacts associated with CETP sludge disposal while providing a sustainable solution. To assess the feasibility of this approach, an experimental program was conducted with variations in the mix ratio of CETP sludge and slag sand, a byproduct of steel production. The properties of the produced CLSM, such as flowability and unconfined compressive strength (UCS), were thoroughly examined using Scanning Electron Microscopy, X-ray Diffraction, and X-ray Fluorescence analyses. The results reveal that the CLSM produced with CETP sludge and slag sand exhibits promising performance, with excellent flowability and UCS values ranging from 1.8 to 5.5 MPa. This research underscores the potential of waste materials in creating sustainable and environmentally friendly construction materials, contributing to effective waste management practices and sustainable industrial growth.

Secondary utilization of self-suspending proppant's coating polymer: Enhance oil recovery

Fracturing is associated with significant economic costs, and the loss of the utility of the self-suspending proppants' coating polymer after fracturing appears highly wasteful. To enhance the utilization of the self-suspending proppant's coating polymer, we propose a novel concept: the secondary utilization of coating polymer, enabling the coating polymer to gel-breaking within the reservoir and generate surface-active substances, thereby enhancing the oil recovery efficiency. To realize this concept, this study designed and synthesized a hydrophobic associative polymer, which was combined with ceramic proppant to form self-suspending proppant. Using the surface-active monomer octadecyl dimethyl allyl ammonium chloride (DMDAAC-18), acrylamide (AM), acrylic acid (AA), and 2-acrylamido-2-methylpropane sulfonic acid (AMPS) via aqueous free-radical copolymerization synthesized the PAAAD (Polymer (AM/AA/AMPS/DMDAAC-18)). PAAAD has demonstrated excellent thickening properties, with a viscosity of 240.01 mPa s at a concentration of 6 g/L in shear rate 170s−1. Its solution exhibits high viscoelasticity, and a loss factor (tan δ) < 1 over the frequency range of 0–20 Hz at a shear stress of 0.56 Pa indicates that it behaves like a viscoelastic solid with gel-like characteristics, which is beneficial for proppant suspension. The gel-breaking solution of PAAAD reduced surface tension (29.33 mN/m at a PAAAD concentration of 6 g/L), converted oil-wet rocks to water-wet conditions (reducing the contact angle of oil-wet shale to 46.7° and of oil-wet sandstone to 19.9°), and enhanced shale imbibition oil recovery efficiency in 16.5%. The basic properties of self-suspending proppants meet the Chinese Petroleum Industry Standard SY/T 5108-2014 and exhibit good suspension properties, with sedimentation of 1.7 mm in 40 min at a sand ratio of 15%. This study is the first to propose the secondary utilization of the self-suspending proppant's coating polymer, significantly enhancing their utilization value.

Experimental Investigation on Pervious Recycled Aggregate Concrete Made of Waste Porcelain

The current study examines the physical, mechanical, and durability of eco-efficient pervious concrete produced with partial and complete substitutions of natural aggregate (NA) by recycled aggregate (RA) waste from demolished concrete and porcelain. The experimental investigation assessed the workability (slump test), compressive strength, flexural strength, and tensile strength along with the concrete's water permeability, impact, and abrasion resistance. Seven mixes were examined; the first is a control mix with natural aggregate, and the other six are made with various RA ratios, including 30%, 70%, and 100%. The sand was also fully replaced by waste porcelain, even though the ratio of sand used in pervious concrete was low. The results revealed that using waste concrete and porcelain adversely affected the workability of fresh pervious concrete mixes, reducing it by approximately 14%. Furthermore, a decrease in the strength of pervious concrete was noticed, especially in the splitting tensile strength, where the reduction reached 32%. Moreover, the impact resistance of pervious concrete made with RA reduced by 29% compared to that made with NA; the same applies to durability, with an increase of 20% in weight loss. On the other hand, using both recycled concrete and recycled porcelain improved the permeability of the pervious concrete, which reached 30%. Pervious concrete made with waste concrete and porcelain can be an acceptable alternative to that made from natural aggregate due to its improved water permeability and positive environmental impact. However, further investigation is important to consider strength and durability enhancement. Doi: 10.28991/CEJ-2024-010-09-08 Full Text: PDF

Optimisation of TiO2 synthesis from ilmenite sand and its application in the photocatalytic process

ABSTRACT Iron sand, a mineral, can be extracted to produce titanium dioxide (TiO2). TiO2 is a semiconductor material that is commonly used in photocatalytic applications, as well as electronics, colour pigments, paint manufacturing, and semiconductors. In this study, TiO2 was extracted from Banten ilmenite sand using caustic fusion and hydrometallurgical methods. The TiO2 extraction process was carried out by varying the mole ratio of ilmenite sand to NaOH, which was 1:0, 1:3, and 1:5, and the fusion temperatures were 700°C and 850°C, with time variations of 30, 60, and 90 min. XRF analysis revealed that the highest TiO2 composition was 91.64% in samples with a mole ratio of 1:3 during 30 min of fusion time and 91.14% in samples with a mole ratio of 1:5 during 90 min of fusion time. The XRD data revealed that TiO2 has a rutile phase with a tetragonal structure, while scanning electron microscopy (SEM) analysis revealed that the particle distribution in the sample is not uniform. The UV-Vis measurements revealed that TiO2 has a band gap of 3.10 at 700°C and 3.13 at 850°C. Furthermore, TiO2 degraded Rhodamine B dyes at a rate of 28.266%.

Microstructural behavior of mortars containing thermo-activated crushed demolition residue (TCDR)

The construction industry has been constantly expanding and is, consequently responsible for a high consumption volume of natural raw materials and for generating large amounts of waste. In detriment of this scenario, this research proposes the reuse of Construction and Demolition Waste (CDW), especially that from plaster for making mortars. The residue was thermo-activated at 650 °C for a period of 2h, a heating rate of 10 °C/min, it was crushed in a jaw crusher and passed through an ABNT N° 16 sieve. The mortars were prepared with a (cement:sand) ratio of 1:6 by mass, the sand was partially replaced by the residue in proportions of 0, 10, 20 and 30%, using Ordinary Portland Cement (OPC). Tests were carried out on consistency index, mass density, incorporated air content, isothermal calorimetry, water retention, mass density in the hardened state, flexural strength, compressive strength, water absorption and void index, in addition to testing techniques characterization, such as laser granulometry, pozzolanic activity using the Modified Chapelle method and Lúxan method, X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) as well as Mercury Intrusion Porosimetry (MIP). It was possible to observe that the residue has amorphous phases, through XRD and heterogeneous nucleation of smaller particles, proven by the calorimetry test, contributing to the increase in mechanical strength. The results indicate that the mixture with 30% replacement achieved a greater increase in mechanical strength, lower absorption rates and consequently, a reduction in the distribution of pore sizes.