Superplasticizer Research Articles

An improved prediction of high-performance concrete compressive strength using ensemble models and neural networks

Traditional methods for proportioning of high-performance concrete (HPC) have certain shortcomings, such as high costs, usage constraints, and nonlinear relationships. Implementing a strategy to optimize the mixtures of HPC can minimize design expenses, time spent, and material wastage in the construction sector. Due to HPC's exceptional qualities, such as high strength (HS), fluidity and resilience, it has been broadly used in construction projects. In this study, we employed Generalized Regression Neural Network (GRNN), Nonlinear AutoRegressive with exogenous inputs (NARX neural network), and Random Forest (RF) models to estimate the Compressive Strength (CS) of HPC in the first scenario. In contrast, the second scenario involved the development of an ensemble model using the Radial Basis Function Neural Network (RBFNN) to detect inferior performance of standalone model combinations. The output variable was the 28 Days CS in MPa, while the input variables included slump (S), water-binder ratio (W/B) %, water content (W) kg/m3, fine aggregate ratio (S/a) %, silica fume (SF)%, and superplasticizer (SP) kg/m3. An RF model was developed by using R Studio; GRNN and NARX-NN models were developed by using the MATLAB 2019a toolkit; and the pre- and post-processing of data was carried out by using E-Views 12.0. The results indicate that in the first scenario, the Combination M1 of the RF model outperformed other models, with greater prediction accuracy, yielding a PCC of 0.854 and MAPE of 4.349 during the calibration phase. In the second scenario, the ensemble of RF models surpassed all other models, achieving a PCC of 0.961 and MAPE of 0.952 during the calibration phase. Overall, the proposed models demonstrate significant value in predicting the CS of HPC.

CO2-sequestering ability of M20 grade concrete with bio-char and iron ore tailing powder

<p style="line-height:200%;margin-bottom:.0001pt;text-align:justify;"><span style="font-family:"Times New Roman","serif";font-size:12.0pt;line-height:200%;">The research aims to investigate the CO<sub>2</sub>-sequestering ability of M20 grade concrete with biochar and Iron ore Tailing Powder (ITP). The biochar was prepared by slow pyrolysis of corn stover. The obtained biochar were categorized in two series as untreated biochar and biochar subjected to pre-treatment by heating until it catches fire. The fine aggregate in the concrete was replaced with biochar at 0%, 5%, 10% and 15%. The iron ore tailing powder obtained by crushing and sieving of iron ore waste products. The cement was replaced with ITP at 0%, 25% and 50% by its weight. Water to binder ratio was maintained at 0.45, the workability of the concrete was maintained with the help of super plasticizer. The compressive strength test, CO<sub>2</sub> uptake, porosity and mercury intrusion porosimetry test were conducted to understand the effect of biochar and ITP in concrete. The test result indicate that the mix containing pre-treated biochar with 25% ITP substitution has the maximum CO<sub>2</sub> sequestration capacity without compromising its strength characteristics.</span></p>

Carbon Nanotubes in Cement-A New Approach for Building Composites and Its Influence on Environmental Effect of Material.

An addition of carbon nanostructures to cement paste is problematic due to the difficulties in obtaining homogenous mixtures. The paper reports on a more effective way of mixing carboxylated multi-walled carbon nanotubes (MWCNT-COOH) in cement pastes. The additional biological impact of the studied nanomodified cement was analyzed in the case of two moss species' vitality. The applied approach of obtaining a homogeneous mixture is based on intense mechanochemical mixing of MWCNT-COOH together with polycarboxylate superplasticizer (SP). As a result, a more homogenous suspension of MWCNT-COOH within a liquid superplasticizer, suitable for addition to hydrophilic cement paste, was obtained. FT-IR/Raman spectroscopy was used for materials' characterization. To explain the mixing process at the molecular level, systematic theoretical studies using density functional theory (DFT) were performed. The structures, interaction energies and IR/Raman vibrational spectra of model carboxylic acids, mixed with functionalized SWCNTs as simplified models of real MWCNTs, were obtained. Due to the controversial opinions on the environmental hazards of carbon nanostructures, additional in vivo studies were performed. In this case, effects of cement modified by the addition of small amounts of MWCNT-COOH with SP in comparison to the composite without carbon nanostructures and control subsoil on the vitality of mosses Polytrichum formosum and Pseudoscleropodium purum were studied.

Effect of agitation during the early-age hydration on thixotropy and morphology of cement paste

The effect of agitation during the early-age hydration on thixotropy and morphology of cement paste prepared with and without superplasticizers (SP) is investigated by applying penetration test, small amplitude oscillatory shear sweep test (SAOS), isothermal calorimetric test, scanning electron microscopy (SEM) and energy dispersive X-ray analyses (EDX). The results show that the agitation of cement paste during the induction period increases the heat flow rate and destroys existing structures of samples without changing the mineral composition of samples. Yet, if the agitation is applied during the acceleration period, the heat flow rate is significantly lowered and the morphology and mineral composition of samples undergo irreversible change, freshly formed syngenite is destroyed and no longer restored. The penetration force and the static yield stress grow linearly during the induction period and exponentially during the acceleration period. Agitation during the induction period destroys the structure, which causes the static yield stress and the penetration force values becoming nearly equal to zero. However, during the acceleration period, even after agitation the static yield stress and the penetration force exhibit high residual values, which indicates the impact of hydration to the structural build-up.

Experimental Study On Self-Compacting Concrete Mix Design By Using Yucca Zeolite

This report aims to present the experimental investigation on mix proportioning of normal concrete and self-compacting concrete with yucca zeolite. The study area comprises of ordinary portland cement of grade 53,mix proportioning of normal concrete for grade of concrete M40, M30 and M20 whereas mix proportioning for self-compacting concrete for grade of concrete M40, M30 ,M20.The parameters considered are cement content, Water cement ratio i.e. for normal concrete 0.4, 0.42, 0.45 and for self-compacting concrete 0.62, 0.44, 0.43 respectively. To reduce the risk of shrinkage, frost attack and corrosion of concrete, yucca zeolite as a mineral admixture and to increase the bond strength techno plast S 300 as a super plasticizer is added. The responses of material testing, normal concrete tests that includes slump flow test and compressive strength test recorded. Also, tests on self-compacting concrete recorded from slump flow test, J ring test, V funnel test, L box test, U box test, Rheological parameters, Compressive strength at 7 and 28 days. The various properties of SCC are ascertained with the IS code 1199:2018 [part 6] IS code 456:2000, IS code 10262:2019.

Self-Compacting Mixtures of Fair-Faced Concrete Based on GGBFS and a Multicomponent Chemical Admixture—Technological and Rheological Properties

The use of superplasticizers in a self-compacting concrete mix without the addition of a foaming agent in practice leads to a well-known problem associated with increased air entrainment and promotes the formation of harmful large bubbles, high-void content, and ununiform appearance. This paper presents research on the properties of cement paste consisting of Ordinary Portland Cement (OPC), powder based on ground granulated blast furnace slag (GBBS), and superplasticizer. The methodology of this study was the estimation of flow diameter and flow time, as well as the evaluation of the rheological characteristics. The influence of ground granulated blast furnace slag and polycarboxylate plasticizer on the flowability and viscosity of cement paste was studied. The effect of superplasticizer (SP) based on polycarboxylate esters (PCE) anti-foaming agent (AFA) based on a glycol ester and air-entraining admixture (AEA) based on an amphoteric surfactant on flowability, viscosity, rheological properties and the strength of the cement paste was evaluated. It was found that the increase of slag content in cement paste (25%) with the presence of superplasticizer (0.64%) significantly changes the flowability and viscosity. It was stated that the addition of 0.04% anti-foaming agents increases flowability (20%) and reduces viscosity (44%) of cement paste. It was stated that the addition of small dosages of glycol ester-based anti-foaming agent (0.02 and 0.04%) significantly changes the rheological properties, decreases the shear yield stress by 2.1–2.8 times, the plastic viscosity by 2.4–2.6 times and apparent viscosity 1.6–2.5 times, improves the compressive strength at the age of 1 and 7 days by 2.5 and 1.4 times, respectively. The addition of air-entraining admixture led to a decrease in the plastic viscosity by 1.2–1.4 times. It was stated that the presence of air-entraining admixture assists in increasing the apparent viscosity by 1.7–2.4 times. It was shown that the presence of complex admixtures of various origins, purposes, and mechanisms of action would assist in predicting the behavior of concrete mixtures under the conditions of the building site and reduce the consumption of polycarboxylate esters due to the enhancing plasticizing effect of anti-foaming agent and air-entraining admixture.

Machine Learning Driven Fluidity and Rheological Properties Prediction of Fresh Cement-Based Materials.

Controlling workability during the design stage of cement-based material mix ratios is a highly time-consuming and labor-intensive task. Applying artificial intelligence (AI) methods to predict and optimize the workability of cement-based materials can significantly enhance the efficiency of mix design. In this study, experimental testing was conducted to create a dataset of 233 samples, including fluidity, dynamic yield stress, and plastic viscosity of cement-based materials. The proportions of cement, fly ash (FA), silica fume (SF), water, superplasticizer (SP), hydroxypropyl methylcellulose (HPMC), and sand were selected as inputs. Machine learning (ML) methods were employed to establish predictive models for these three early workability indicators. To improve prediction capability, optimized hybrid models, such as Particle Swarm Optimization (PSO)-based CatBoost and XGBoost, were adopted. Furthermore, the influence of individual input variables on each workability indicator of the cement-based material was examined using Shapley Additive Explanations (SHAP) and Partial Dependence Plot (PDP) analyses. This study provides a novel reference for achieving rapid and accurate control of cement-based material workability.

Study on the fluid-solid transition mechanism of natural hydraulic lime pastes: Consider the water to binder ratio and polycarboxylate superplasticizer

Natural hydraulic lime (NHL) is used as a grouting material in the restoration of ancient buildings, the formation and evolution of its early workability are crucial for the reliability of the restoration effects. This paper conducts an in-depth study on the effects of water to binder (w/b) ratio and polycarboxylate superplasticizer (SP) dosage on the viscoelastic properties of fluid-solid transition process in NHL paste through tests on the fluidity, rheological characteristics, micro-rheology, hydration heat release, and early phase composition. The results show that the fluidity of NHL paste significantly increases with increasing w/b ratio and SP dosage, while its yield stress and plastic viscosity show downward trend, and it has shear thinning characteristics. In the initial stage, elevated w/b ratio leads to the significant reduction in both macroscopic viscosity index (MVI) and elastic index (EI) of NHL paste, along with delayed rapid increases, the effect is even more pronounced by adding SP. High w/b ratio or adding SP are able to enhance the dispersed state of solid particle in NHL pastes, the viscoelastic transition point of NHL paste is delayed and the viscoelastic transition time is prolonged. Increasing the w/b ratio and adding SP both inhibit the early dissolution and hydration of NHL paste, affecting the fluid-solid transition process. Overall, as the spatial network gradually develops by the solid particles dissolve and continue to hydrate, NHL paste undergoes a transition from a viscous fluid to an elastic semi-fluid state, exhibiting low strength and noticeable plasticity characteristics. With further hydration, NHL paste initiates consolidation and hardening processes, progressively transforming from a plastic semi-fluid into hardened paste.

A qualitative approach to describe the viscosity of flowable concrete made with manufactured sand containing different microfines

The concrete made with different manufactured sands can exhibit complex rheological properties. The prediction of viscosity is crucial in concrete placement, but remains challenging given the varied content and characteristics of microfines in the sands. This paper studies the influence of tuff (TF) and limestone (LS) microfines with disparate particle size distributions on the pseudo-Newtonian viscosity of concrete prepared with crushed sand. The concrete had a fixed water-to-binder mass ratio of 0.32 and polycarboxylate ether superplasticizer (PCE) dosage of 0.14 % by mass of biner. Test results showed that the microfines in manufactured sand can reduce the aggregate-to-excess cement paste ratio, leading to lower contact interactions between the aggregate grains. But the ratio of total powder particles and entrained air to excess interstitial solutions increased for the fluid paste matrix of the concrete, which caused greater flow resistance related to the powder contacts and air bubble deformations. A qualitative approach correlating the volume ratio of aggregate grains to excess cement pastes and that of total powder particles and entrained air to excess interstitial solutions was proposed to describe the pseudo-Newtonian viscosity of concrete, regardless of the different microfine additions in manufactured sand.

Compressive Strength Prediction of Fly Ash-Based Concrete Using Single and Hybrid Machine Learning Models

The compressive strength of concrete is a crucial parameter in structural design, yet its determination in a laboratory setting is both time-consuming and expensive. The prediction of compressive strength in fly ash-based concrete can be accelerated through the use of machine learning algorithms with artificial intelligence, which can effectively address the problems associated with this process. This paper presents the most innovative model algorithms established based on artificial intelligence technology. These include three single models—a fully connected neural network model (FCNN), a convolutional neural network model (CNN), and a transformer model (TF)—and three hybrid models—FCNN + CNN, TF + FCNN, and TF + CNN. A total of 471 datasets were employed in the experiments, comprising 7 input features: cement (C), fly ash (FA), water (W), superplasticizer (SP), coarse aggregate (CA), fine aggregate (S), and age (D). Six models were subsequently applied to predict the compressive strength (CS) of fly ash-based concrete. Furthermore, the loss function curves, assessment indexes, linear correlation coefficient, and the related literature indexes of each model were employed for comparison. This analysis revealed that the FCNN + CNN model exhibited the highest prediction accuracy, with the following metrics: R2 = 0.95, MSE = 14.18, MAE = 2.32, SMAPE = 0.1, and R = 0.973. Additionally, SHAP was utilized to elucidate the significance of the model parameter features. The findings revealed that C and D exerted the most substantial influence on the model prediction outcomes, followed by W and FA. Nevertheless, CA, S, and SP demonstrated comparatively minimal influence. Finally, a GUI interface for predicting compressive strength was developed based on six models and nonlinear functional relationships, and a criterion for minimum strength was derived by comparison and used to optimize a reasonable mixing ratio, thus achieving a fast data-driven interaction that was concise and reliable.

Effects of C-S-H Seed Prepared by Wet Grinding on the Properties of Cement Containing Large Amounts of Silica Fume

This study aimed to utilize the hydration characteristics of cement through wet grinding techniques to efficiently and conveniently prepare a stable C-S-H seed suspension, providing key parameters and a scientific basis for their large-scale production, which ensures the stability of the C-S-H suspension during production, transportation, and application. This preparation aimed to mitigate the adverse effects of high-volume silica fume on the early mechanical properties of high-performance cement concrete. The properties of C-S-H seed were characterized in detail by SEM, XRD, and TD. In the concrete performance test, silica fume was used to replace part of the cement, and different contents of C-S-H seed were added to test its effect on the compressive strength of concrete, with XRD and SEM used to analyze the performance differences. The results show that the particle size and hydration degree of cement no longer developed after 90 min of wet grinding. Polycarboxylate ether (PCE) superplasticizer can increase the fluidity of the crystal C-S-H seed suspension when the content exceeds 1.5%. When the content of PCE exceeded 2%, the C-S-H seed suspension precipitated. Adding 5% C-S-H seed can increase the compressive strength of cement concrete by 10% under the condition of reducing the amount of cement and increasing the amount of silica fume. And Ca(OH)2 (CH) was produced by cement hydration consumed by silica fumes to generate C-S-H gel, by which the concrete became denser with more strength. However, when the amount of C-S-H seed exceeded 7%, the compressive strength of the concrete decreased.

Evaluating performance characteristics of recycled aggregate concrete: A study through experimentation

This study surveys the display characteristics of Recycled Aggregate Concrete (RAC) through experimentation, focusing on key material properties and mix degrees. The RAC blends, signified as R-0 and R-45 addressing various rates of Recycled Concrete Aggregate (RCA) substitution, were examined for new properties, compressive strength, and solidness. The blend extents included concrete (C), fine aggregate (FA), natural coarse aggregate (NCA), RCA, silica fume, water, and superplasticizer (SP). New properties, for example, compaction factor, alongside 28 days compressive strength, were determined for all RAC blends. Sturdiness tests included corrosive opposition, scraped area obstruction, and water penetrability tests. Results showed that RAC displayed decreased compressive strength and expanded weight reduction contrasted with traditional concrete (R-0) when exposed to corrosive assault. Be that as it may, the compressive strength decrease was less articulated in RAC exposed to sulfate assault, credited to the arrangement of ettringite. Scraped area obstruction tests uncovered that R-45 had higher normal misfortune in thickness contrasted with R-0 however remained inside adequate cutoff points. Water porousness tests showed higher profundity of entrance in RAC contrasted with R-0, conceivably because of stuck mortar. Nonetheless, both RAC and R-0 showed satisfactory water assimilation values. The study suggests that RAC could offer viable alternatives in construction applications while addressing sustainability concerns. Further research is recommended to explore RAC's performance under elevated temperatures and correlate split tensile strength with corresponding results.

An explainable machine learning approach to predict the compressive strength of graphene oxide-based concrete

Graphene oxide (GO) has shown promise in improving concrete strength. Despite its frequent use in cement composites, its effect on concrete properties is less explored. The influence of GO on concrete remains unclear due to various interactions among constituents such as GO type and percentage, Superplasticiser (SP) type and percentage, dispersion technique, and curing age. Therefore, making prediction of compressive strength using simple mathematical formation is challenging. This study represents the first-ever attempt at developing a comprehensively validated machine learning model to predict GO-concrete's compressive strength characteristics by considering all key variable parameters. A comprehensive laboratory experiment program was conducted to collect the data required for training the machine learning (ML) models. Once the ML models were trained, they were used to predict the relationship of each of those input variables towards the compressive strength properties. Four machine learning models—(a) multiple linear regression (MLR), (b) k-nearest neighbour (KNN), (c) random forest (RF) and (d) extreme gradient boost (XGB)—were utilised to model the relationship between input parameters and compressive strength. Also, explainable machine learning (XML) methods were employed to elucidate the impact of mixed constituents on the compressive strength of GO concrete. The results from test predictions showcase that the XGB has attained a coefficient of determination (R2) of 0.981, coefficient of correlation (R) of 0.99, mean square error (MSE) of 0.9, mean normalised bias (MNB) of 0.004, scatter index (SI) of 0.2 with mean absolute error (MAE) of 0.8 MPa for the predictions, outperforming the remaining models. XML highlighted the true impact of GO and the remaining variables, emphasising that the presence of GO significantly improves compressive strength. The optimum GO content and optimum superplasticiser content observed from the experimental work agreed with results obtained from the XML analysis, showing the consistency of the explanation with the experimental results. This implies the superiority of using XML methods in concrete mix design applications in industry.

On the action mechanism of phosphate-based superplasticizers in one-part alkali-activated slag

The mechanisms responsible for the compromised or lost dispersing capability of polycarboxylate ether (PCE) superplasticizers in two-part alkali-activated slag (AAS) have been extensively studied, but limited scientific understanding is available on how PCEs function or lose their dispersing efficiency in one-part AAS systems, particularly those prepared using greener carbonate -based solid activators. This study investigates the dispersing and adsorption behaviors of phosphate-based PCE in one-part AAS activated by K2CO3 or a combination of K2CO3 and CaO. Our findings indicate that in K2CO3-activated slag systems, the loss of phosphate-based PCE efficiency primarily results from the conformational contraction of PCE molecules, which deteriorates steric repulsion in the alkaline activating solution, rather than the insolubility of PCEs in alkaline solution or competitive adsorption between PCEs and carbonate anions on dissolving slag grains. In K2CO3-CaO-activated slag systems, when PCE dosage is below 5 mg/g, the consumption of PCE by early precipitates (e.g., C-A-S-H, gaylussite, calcite) contributes substantially to its lost efficiency; however, once the PCE dosage surpasses this threshold, the dominant factor influencing PCE efficiency shifts to the conformational change of PCE.

Effect of Different Concentration of CO2 Gas Injected into Fresh Cement Paste Along with the Addition of Superplasticizer on the Mechanical Properties of Cement

This paper focused on examining the impact of injecting varying concentrations of carbon dioxide (CO2) gas on the mechanical characteristics of both the fresh and hardened states of cement paste. This study also considered the influence of the presence or absence of polycarboxylate superplasticizer in cement mixture on these properties. Many researchers discovered the benefit of CO2 gas utilization in cement mixture to accelerate the early strength of cement or concrete hydration by its carbonation that form calcium carbonate (CaCO3). The application method is to directly inject CO2 gas in a curing chamber for air-curing of precast concrete. Alternatively, carbonated water is mixed with cement during concrete mixing. However, the use of CO2 gas does not significantly improve the 28-day strength of concrete. This study explores how to improve the carbonation impact on mechanical properties of cement paste and apply it to ground improvement. In this study, the method adopted is direct injection of CO2 gas during cement slurry mixing with different injection duration. The influence of CO2 in the presence of superplasticizer (SP) in cement slurry was also studied as SP is generally used for grouting. The results showed that the carbonation of cement paste with additional of superplasticizer significantly affect its flow, viscosity and bleeding properties. Unlike samples with SP addition, the samples without SP addition showed higher compressive strength after 28 days of curing up to certain CO2 injection time. For all CO2 gas injection time, smaller porosity rates were observed for 7-day cured samples with SP addition compared to those without SP addition. This is due to accelerated carbonation due to SP presence in cement mixture. From the results, the optimum of CO2 gas injection time for one liter mixture of cement paste to improve its compressive strength (up to 123% increase) have been discovered. It can be inferred that the addition of superplasticizer in cement slurry reduces the amount of CO32- ions and Ca2+ ions during carbonation process of cement hydration products, which are strongly related to the pH level in pore solution. These ions play a significant roles in determining the mechanical properties of cement slurry.

Nanocrystalline Cellulose to Reduce Superplasticizer Demand in 3D Printing of Cementitious Materials.

One challenge for 3D printing is that the mortar must flow easily through the printer nozzle, and after printing, it must develop compressive strength fast and high enough to support the layers on it. This requires an exact and difficult control of the superplasticizer (SP) dosing. Nanocrystalline cellulose (CNC) has gained significant interest as a rheological modifier of mortar by interacting with the various cement components. This research studied the potential of nanocrystalline cellulose (CNC) as a mortar aid for 3D printing and its interactions with SPs. Interactions of a CNC and SP with cement suspensions were investigated by means of monitoring the effect on cement dispersion (by monitoring the particle chord length distributions in real time) and their impact on mortar mechanical properties. Although cement dispersion was increased by both CNC and SP, only CNC prevented cement agglomeration when shearing was reduced. Furthermore, combining SP and CNC led to faster development of compressive strength and increased compressive strength up to 30% compared to mortar that had undergone a one-day curing process.

Factorial analysis and modeling of chemical admixtures’ influence on Portland cement paste rheology

The influence of the amount of superplasticizer (SPA) and air-entraining (AEA) admixtures on the rheological properties of a Portland cement paste was investigated based on a statistical approach. The factorial design had the yield stress (YS) and flow as response variables, while the factors of 0.5 ml/kg-cem < SPA < 1.5 ml/kg-cem and 1.2 ml/kg-cem < AEA < 3.6 ml/kg-cem were evaluated, considering main effects, factor interactions, correlation analysis and modelling. The main effects analyses showed that the flow decreased as the AEA or the SPA increased, while the opposite was observed for the YS. The interactions analyses showed that the AEA promoted a reduction trend using the lowest SPA for the flow, but the highest SPA nullified the effect of AEA on flow, which maintained the highest value of 113.7%. Similarly, the AEA favored an increasing trend for the YS due to the interaction with the low SPA content, but a high SPA changed this trend, which decreased to the lowest value of 2652.6 Pa. The flow model (R2 = 84.9%) indicated that the linear effect of the SPA was the most significant, but the linear effect of the AEA and the SPA*AEA interaction were similar in terms of their significance (p-value < 0.001), while the YS model (R2 = 99.6%) showed that the AEA’s linear effect and the AEA*SPA interaction were similar and the most significant (p-value < 0.001). This research provides insights that could facilitate modeling, prediction, and optimization of efficient mixture designs while also gaining clarity considering potential inhibitory effects or synergies, which promotes the responsible consumption and production of construction materials.Graphical

Strength and workability of one-part sodium carbonate activated mortar incorporated with silicomanganese slag

This research utilized sodium carbonate (Na2CO3) as an alkaline activator to produce one-part alkali-activated mortar (AAM) with silicomanganese (SiMn) slag as the aluminosilicate precursor. In the experiment, the effect of Na2CO3 dosage (4 %, 6 %, 8 %, 10 %, 12 %) and binder replacement with ordinary Portland cement (OPC) (10 %, 30 %, 50 %) on the compressive strength and workability of AAM was investigated. To improve the workability, several types of superplasticizer (SP), including MasterGlenium ACE 389 (MG) and sodium naphthalene sulfonate formaldehyde (SNSF), and retarder, including REAL SET 231 (RS231) and vinegar (acetic acid), were incorporated. The relationship between strength and workability of one-part AAM was also established. The results showed that increasing the Na2CO3 content from 4 % to 10 % improved the strength by about 2 times but reduced workability by 7.8 % due to the increased alkalinity and OH− concentration. The incorporation of up to 50 % OPC further increased the strength by 3.2–5.3 times due to the synergetic effect of alkali activation of SiMn slag and cement hydration. In addition, SNSF-type SP outperformed MG-type SP in terms of workability and compressive strength. Both the RS231 retarder and acetic acid enhanced the workability by 8%–48 % and strength by 10.5 %–28.3 %. A quadratic regression equation with R2 values of 0.58–0.81 was developed to correlate the strength and workability of one-part AAM.

Investigation of properties of SCC with perlite as a partial replacement of coarse and fine aggregate

Abstract Self-compacted concrete, is an extremely flowable concrete that can spread readily into formwork without any void and solidify without showing signs of bleeding or segregation when there is no vibration. The effects of using Perlite material as a partial replacement of aggregate on the fresh and hardened characteristics of self-compacting concrete have been examined in this study. Perlite material, is alumino-siliceous amorphous volcanic material that occurs naturally and is derived from crude perlite rock is utilized in construction Its high porosity and low density make it a great option for a lightweight mineral filler in a variety of applications. In order to do this, the mixing procedures maintained at constant ratio of water to cement and super plasticizer, and perlite was substituted at varying volume percentage (20, 40, and 50) %. Concrete’s flow ability, passage ability, and resistance to separation were examined using performance tests such the V- funnel, Slump flow, L- box tests and Segregation Index. The findings revealed that when perlite was substituted for coarse aggregate and fine aggregate in the observe concrete, the workability reduced. This study has looked into the mechanical characteristics of hard self-compacting concrete as well. For this reason, a series of tests were conducted, including ones measuring thermal conductivity and density at 28 days. compressive, splitting, and flexural strength at ages 7, 28, and 56 days. By increasing the percentage of perlite the values of (compressive strength, flexural strength and splitting tensile strength) decreased significantly compared with reference mixture (0% perlite replacement). The highest decreased was at 50% perlite replacement of aggregate.

Effect of Activated Siliceous Wastes Incorporated as Mineral Admixtures on the Rheological Properties of Cement Paste: Insights into Their Physicochemical Interactions in Suspension.

Mechanical grinding is a common method used to enhance the pozzolanic activity of tailings, and these activated tailings can be used as supplementary cementitious materials in cement production. However, the addition of activated tailings usually reduces the workability of cement paste, and the mechanism of influence of different minerals in tailings on workability varies. In this study, three kinds of principal silicate minerals in tailings-quartz, feldspar, and mica-were mechanically activated. The influence of these activated minerals on the rheological properties of cement paste were studied in the absence or presence of PCE (polycarboxylate ether) superplasticizers, and the influence mechanism was investigated using rheology, TOC, contact angles, zeta potential, XPS, ICP-OES, and XRD. The results showed that quartz has the highest fluidity, and mica has the lowest. An increase in hydrophilicity decreased the flowability of the blended cement paste. The increase in the metal cation dissolution rate was the main reason for the decrease in the fluidity of PCE-blended cement pastes. The knowledge gained provides a valuable reference for the utilization of activated tailings in cement production.