Mixing Properties Research Articles

Enhancing dry mix mortar strength with natural fillers and polymers

Dry mix mortars are becoming more and more popular in the world’s building materials market. Therefore, the issue of increasing the technological and mechanical properties of stucco mixes is relevant. The aim of the paper is modification of lightweight dry stucco mixes with fine limestone and perlite as well as with hydroxyethyl methyl cellulose and dispersible polymer. In order to investigate the different mixes, an 18-point experiment was designed. Density, compressive strengths and crack resistance of dry plaster mixes were studied using requirements of standard. Mathematical models were obtained for the compositions as a result of processing the experimental data. The regularities of the fillers’ and additives’ influence on the properties of the mixes were established, depending on their amount and combination. It was observed that methyl hydroxyethyl cellulose improves the crack resistance and compression strength, and contributes to a slight decrease in density. The crack resistance of plaster mortars changes more than 1.5 times, the most crack-resistant compositions have an average amount of porous fillers.

The use of granite powder waste in cementitious composites

This paper focuses on literature analyses of the impact of granite powder waste on the properties of cementitious mixes and composites. The influence of weather conditions on the properties of granite rocks is also analysed. The grains of granite powder waste are characterized. It was noticed that the results of the literature do not answer the question of whether granite powder has a positive or negative effect on cementitious mixes. Typically, granite powder allows for increasing the mechanical and functional properties of composites. The article also describes the literature gaps related to the topic and indicates future research perspectives on the functionalization of granite powder waste. The author discusses correlations and the impact of granite powder on the properties of cementitious composites and compares it with the literature. This paper compares the results of different authors using standard testing procedures but with the application of different modifications of compositions of cementitious mixes. The possibility of reducing the production costs and CO2 emissions of cement composites with the use of granite powder waste was indicated. An increase in packing density connected with using of granite powder as an admixture in cementitious systems is described. Recommendations related to the use of granite powder in cementitious composites are listed.

Use of Waste Material as Filler in Bituminous Mix Design

Abstract: Bituminous concrete is a costlier and highest payment flexible payment layer. For satisfy the design requirements of stability and durability the bituminous mixes should be designed effectively. The ingredients of the mixture include dense grading of coarse aggregates, fine aggregates, fillers and bitumen binder. In this Study an attempt was made to find the effect of filler on the behavior of bituminous mixes. Fillers play an important role in the filling of voids and hence change the physical and chemical properties. Thus their effect is of utter importance. Bitumen in combination with filler forms mastic. This mastic can be seen as a constituent of mixture of asphalt that holds the aggregates together. An important role is played by the fillers that pass through 0.075mm sieve. With the increase in the amount of filler, Marshall Stability of the bitumen mix increases directly. Use of 4-8% filler in asphalt concrete is recommended by the Asphalt Institute. In India, waste concrete dust and brick dust are considered to be cheaper and are available in plenty. In this study an attempt was made to find the effect of fillers on the bitumen mixes. In this study, concrete dust and brick dust was used as filler. The properties of bituminous mixes containing these fillers were studied and compared with each other. For the purpose of comparison Marshall Method of mix design was used. In this study various tests were also conducted on aggregates and bitumen and the results were compared with the specifications. The study revealed that use of concrete dust and brick dust as filler improves the physical characteristics of bitumen. Marshall Stability and flow value of bitumen mix also improved.

Characterizing acidified and renneted gels with different soy milk and skim milk proportions

To understand the properties of differently acidified and renneted gels with different soy milk and skim milk proportions, mixed milks were prepared and treated using sequenced renneting then acidification at 4 °C, and the formation, spontaneous whey separation, and microstructure of the gels were monitored. The results showed that both acidification and renneting promoted gel formation in mixed milk and increased gel strength. In gels, the pH range was narrow (pH ≤ 5.2) at low soy milk proportion (25%) and low renneting degrees (0%, 25% and 50%), and the pH range was extended such that gels were formed with increasing soy milk proportion and renneting degree. When compared with pH, soy milk proportion and renneting degree influenced whey separation percentages more strongly. Soy milk significantly reduced whey separation percentages in gels, and gel strength was highest at 50% soy milk. Protein aggregates sizes increased with increasing soy milk proportion at the 75% renneting degree, and the pore sizes of skim milk-dominated gels was strongly influenced by acidification. These results help us understand mixed gel properties and provide valuable information for the manufacture of mixed fermented dairy products.

Mixing Properties of Cu-Mg Liquid Alloy Using Exponential Model

The Redlich-Kister (R-K) polynomial has been generally used to model the mixing properties of binary and higher order alloys. The interaction energy parameters of the R-K polynomial are assumed to be either linear or exponentially temperature-dependent. When these parameters are assumed to be linear temperature-dependent, the computed thermodynamic functions sometimes show unusual trends. But when they are assumed to be exponential temperature-dependent, such trends do not appear in the theoretical calculations. Therefore, the mixing properties of Cu-Mg liquid alloy have been studied using the exponential temperature-dependent parameters of the above-mentioned model. These parameters for excess Gibb’s free energy of mixing have been optimised using the experimental values of enthalpy of mixing and excess entropy of mixing. The study of thermodynamic properties involves the measurement of excess Gibb’s free energy of mixing, enthalpy of mixing and activities of monomers at different temperatures. Likewise, the assessment of surface property includes surface tension and surface concentration. Similarly, the structural properties have been studied by computing concentration fluctuation in long wave-length limit and short-range order parameter at different temperatures. The investigation revealed that the exponential model can explain mixing behavior of Cu-Mg liquid alloy and the system is found to have strong compound forming tendency at its melting temperature. This mixing tendency has been observed to decrease with the increase in temperature above its melting temperature.

Dissolution thermodynamics and polymorphic transformation behaviors of glutathione

Glutathione (GSH) is a bioactive oligopeptide which was widely used in sports, pharmaceutical and food industry. This paper compared the properties of two crystalline forms of GSH (Form α and Form β) in thermodynamics and explored the transformation of corresponding polymorph. The solubility data of GSH were determined by using the dynamic method in binary mixed solvents (methanol + water, ethanol + water, isopropanol + water, ethylene glycol + water) at temperatures ranging from 278.15 to 313.15 K. The solubilities of the two forms both increased with the increasing of mole fraction of water and temperature. The modified Apelblat equation, the CNIBS/R-K model and the Jouyban-Acree model were used to correlate the experimental solubility. The mixing thermodynamic properties of GSH in the binary mixed solvents were calculated by Van’t Hoff equation. Form β was supposed to be the stable crystalline form based on the thermodynamics analysis, which corresponded to the solvent-mediated transformation from Form α to Form β.

Application of curcumin in mixed properties of quaternary N-alkyl tropine-based ionic liquid surfactant with nonionic, anionic and zwitterionic surfactants

Curcumin has been found to be sensitive to the solution environment and has aroused great interest. Based on this, UV spectrophotometry with curcumin as a probe was employed to investigate the solution properties of surfactants. The reliability of UV spectrophotometry using curcumin as a probe was confirmed by comparing the outcomes with those obtained by surface tension method. The micellization behaviors of surfactant mixtures of tropine-based ionic liquid surfactant (TILS) with anionic surfactant sodium dodecyl sulfate (SDS), nonionic surfactant Triton X-100 (TX-100), and zwitterionic surfactant N-dodecyl-N,N-dimethylglycine (BS-12) were investigated, respectively. Based on the theory of regular solutions, the interaction parameters between the two surfactants and their corresponding thermodynamic parameters were analyzed. The negative βm and |βm| > |ln(CMC1/CMC2)| suggest intense attraction between two different surfactants. Thermodynamic parameters indicate that micelle formation is an exothermic and entropy-increasing process. Comparing the interaction parameters of the three systems, it is evident that TILS exhibits stronger synergistic effects in the formation of mixed micelles with SDS as compared to TX-100 and BS-12. These results demonstrate the feasibility of using curcumin for the study of surfactant compounding properties and broaden the application range of curcumin.

Impact of pomegranate fruit powder on dough, textural and functional properties of fresh noodle.

Polyphenols are important functional food ingredients due to good performance in the prevention of chronic diseases and elongation of shelf-life. Numerous studies have shown that the addition of polyphenols of natural origin to wheat flour tends to have a contradictory effect on the physicochemical properties of the dough in the presence of different doses of polyphenols, also known as biphasic regulation. In the meantime, a promising and economic flour enhancer of natural origin is needed because of the short stability time of the dough. In this study, the impact of pomegranate fruit powder (PFP) on mixing and rheological properties of the dough and texture as well as nutritional characteristics of cooking noodles was studied. The mixing and tensile properties as well as viscoelasticity of the dough were improved with the addition of 4%, 8% or 12% PFP; correspondingly, a more compact and ordered microstructure was observed in the dough. The addition of PFP maintained the best cooking time and water absorption of noodles. Moreover, the hardness, tensile strength and resilience of noodles were improved with the addition of 4% or 8% PFP. Furthermore, the antioxidant capacities of noodles with the addition of PFP were increased via quantification of iron ion reduction, DPPH and ABTS scavenging capacity. The noodles added with PFP showed a dose-dependent inhibitory effect on glucose release. PFP improved the textural properties and nutrition value of noodles. The addition of PFP to the wheat four dough and noodles was suggested to be below 12%. © 2023 Society of Chemical Industry.

Enhancing Properties of Concrete Mix Using Different Types of Waste Materials: A Review Paper

The proliferation of civilization, industry, and urbanization, along with population growth, has contributed significantly to the generation of waste materials, and this trend continues to this day. Such waste has far-reaching impacts on both human health and the environment, leading to environmental degradation and rendering it non-environmentally friendly. To address these concerns, many scientists have directed towards the possibility of using waste materials as a substitute for some components of the concrete mixture. Numerous studies have demonstrated the effectiveness of incorporating such materials such as (coal bottom ash (CBA), waste plastic and fibers, wood waste, and soft drink bottle caps) in enhancing concrete's properties, including durability, compressive and tensile strength, water content, slump flow, and suitability for reuse in engineering projects. The use of such materials not only provides an economic solution but also promotes environmental preservation by mitigating environmental problems.

Determination and Simulation of the Solubility of Bifonazole in 14 Pure Solvents at 283.15–323.15 K

Bifonazole is a derivative of imidazoles with a wide antibacterial spectrum and is widely used for treating various fungi infections. However, in the open literature, the solubility data of bifonazole are rarely reported. Considering the importance of the solubility of bifonazole in its manufacture and applications, the solubility of bifonazole in 8 alcohols and 4 n-alkyl acetates as well as acetonitrile and N, N-dimethylformamide in the temperatures ranging from 283.15 to 323.15 K has been measured with the assistance of a dynamic laser solubility monitoring device in this paper. The measured solubility of bifonazole follows the order of DMF > alcohols > esters > acetonitrile. The relationship between the solubility of bifonazole and temperature was correlated using three semi-empirical and two activity coefficient solubility models. In addition, the thermodynamic mixing properties (ΔmixG, ΔmixH, ΔmixS, γ1∞, and H1E, ∞) of the bifonazole solutions were evaluated in terms of experimental data and Wilson model parameters.

A spectral approach to quenched linear and higher-order response for partially hyperbolic dynamics

AbstractFor smooth random dynamical systems we consider the quenched linear and higher-order response of equivariant physical measures to perturbations of the random dynamics. We show that the spectral perturbation theory of Gouëzel, Keller and Liverani [28, 33], which has been applied to deterministic systems with great success, may be adapted to study random systems that possess good mixing properties. As a consequence, we obtain general linear and higher-order response results, as well as the differentiability of the variance in quenched central limit theorems (CLTs), for random dynamical systems (RDSs) that we then apply to random Anosov diffeomorphisms and random U(1) extensions of expanding maps. We emphasize that our results apply to random dynamical systems over a general ergodic base map, and are obtained without resorting to infinite-dimensional multiplicative ergodic theory.

Numerical study on the mixing enhancement induced by the interaction between the hydrogen/air coaxial jets and oblique shock wave at Mach 3 supersonic crossflow

The comprehensive performance of the scramjet is greatly influenced by the supersonic fuel mixing process. In the research, the mixing properties of the combination between the hydrogen/air coaxial jets and oblique shock at Mach 3 supersonic crossflow are investigated. The focus of the investigation is to reveal the mixing enhancement mechanism of coaxial jets and the impact of oblique shock on the mixing process. The numerical simulation is based on three-dimensional compressible RANS equations combined with the SST k-ω turbulence model. The hydrogen spatial distribution, flow features, vortex structure, penetration depth, stagnation pressure loss and mixing efficiency with different working conditions are evaluated and studied. Our computational results demonstrate that the coaxial jets enhance mixing through the intense shear action between the annular fuel jet with the inner and outer air layers, and the oblique shock contributes to the mixing process by strengthening the interaction between jet and airflow, improving fuel distribution and inducing streamwise vorticity. In addition, the hydrogen distribution and mixing properties are affected by the action position of the incident shock. According to the achieved results, the coaxial jets combined with the oblique shock impinging downstream of the jet have the highest mixing efficiency, which is improved by 63.27% compared to the reference case.

Performance evaluation of dense graded emulsion mixes with rejuvenated reclaimed asphalt pavement

The current investigation presents a comparative study on the laboratory performance of dense graded emulsion mixes prepared with 100% virgin aggregates and 100% Recycled Asphalt Pavement (RAP) with and without a rejuvenator. Waste Engine Oil (WEO) was used as the rejuvenator in the current study. Cold mix design was carried out using a slow-setting type II (SS-2) emulsion. Further, the mechanical and performance properties of various cold emulsion mixes were evaluated. The mechanical properties of cold mixes such as the Indirect Tensile Strength and Resilient Modulus were determined. Rutting and cracking performance were evaluated in terms of the dynamic creep test and indirect tensile asphalt cracking test (IDEAL-CT) respectively. It was observed that the mix prepared with 100% RAP without rejuvenator exhibited a similar rutting performance, a much higher cracking tolerance and low moisture susceptibility compared to the mix with 100% fresh aggregates. The addition of the rejuvenator resulted in improved moisture resistance and cracking tolerance of the cold mix and decreased the rut resistance.

Large stochastic volatility in mean VARs

Bayesian vector autoregressions with stochastic volatility in both the conditional mean and variance (SVMVARs) are widely used for studying the macroeconomic effects of uncertainty. Despite their popularity, intensive computational demands when estimating such models has constrained researchers to specifying a small number of latent volatilities, and made out-of-sample forecasting exercises impractical. In this paper, we propose an efficient Markov chain Monte Carlo (MCMC) algorithm that facilitates timely posterior and predictive inference with large SVMVARs. In a simulation exercise, we show that the new algorithm is significantly faster than the state-of-the-art particle Gibbs with ancestor sampling algorithm, and exhibits superior mixing properties. In two applications, we show that large SVMVARs are generally useful for structural analysis and out-of-sample forecasting, and are especially useful in periods of high uncertainty such as the Great Recession and the COVID-19 pandemic.

Interpretable auto-tune machine learning prediction of strength and flow properties for self-compacting concrete

Self-compacting concrete (SCC) is a promising building material, particularly in developed countries, due to its excellent flowability achieved through a relatively high binder content. To reduce cement usage and carbon footprint, supplementary cementitious materials (SCMs) such as fly ash and limestone powder are utilized. However, traditional concrete design relies on empirical trial-and-error methods, which pose challenges when dealing with SCC due to conflicting mechanical and workability requirements. Thus, leveraging the value of existing data, particularly with the aid of machine learning (ML) techniques, becomes essential. The purpose of this study is to establish highly nonlinear relationships between SCC mix proportions and properties that cannot be expressed by explicit mathematical equations. To address these issues, this study developed interpretable ML technologies, to predict 28-day compressive strength (SC) and slump flow (SF) of SCC containing SCMs, aiming to guide SCC design. The proposed models exhibit high accuracy in predicting the key properties of SCC through careful feature engineering, model training, and hyper-parameter optimization. Experimental verification shows that the proposed models can accurately predict the properties of C45, C50, and C55 SCC, with prediction errors of 0.6%, 6.8%, −13.5% for 28-day SC and −2.8%, 3%, 5.4% for SF, respectively. The combination of ML and SHAP interpretable algorithm provides physical rationality, allowing engineers to predict and design SCC by adjusting proportions according to the parameter analysis.

Asymptotic Optimality of Semi-Open-Loop Policies in Markov Decision Processes with Large Lead Times

A generic way to verify asymptotic optimality of semi-open-loop policies for a wide class of MDPs with large lead times. In many real-life inventory models, order lead times can result in uncertain effects of inventory decisions. However, as the lead time grows large, one would naturally postulate that the effect of the delayed order depends weakly on the current inventory level and, thus, intuit that decoupling the delayed order with the current inventory level may provide good heuristics. Motivated by these examples, in “Asymptotic Optimality of Semi-open-Loop Policies in Markov Decision Processes with Large Lead Times,” Bai et al. consider a generic Markov decision process (MDP) with one delayed control and one immediate control. For MDPs defined on general spaces with uniformly bounded cost functions and a fast mixing property, they construct a periodic semi-open-loop policy for each lead time value and show that these policies are asymptotically optimal as the lead time goes to infinity. For MDPs defined on Euclidean spaces with linear dynamics and convex structures, they impose another set of conditions under which constant delayed-control policies are asymptotically optimal.

Green Routes for Bio-Fabrication in Biomedical and Pharmaceutical Applications.

In the last decade, significant advances in nanotechnologies, rising from increasing knowledge and refining of technical practices in green chemistry and bioengineering, enabled the design of innovative devices suitable for different biomedical applications. In particular, novel bio-sustainable methodologies are developing to fabricate drug delivery systems able to sagely mix properties of materials (i.e., biocompatibility, biodegradability) and bioactive molecules (i.e., bioavailability, selectivity, chemical stability), as a function of the current demands for the health market. The present work aims to provide an overview of recent developments in the bio-fabrication methods for designing innovative green platforms, emphasizing the relevant impact on current and future biomedical and pharmaceutical applications.

Asymptotic Optimality of Semi-Open-Loop Policies in Markov Decision Processes with Large Lead Times

A generic way to verify asymptotic optimality of semi-open-loop policies for a wide class of MDPs with large lead times. In many real-life inventory models, order lead times can result in uncertain effects of inventory decisions. However, as the lead time grows large, one would naturally postulate that the effect of the delayed order depends weakly on the current inventory level and, thus, intuit that decoupling the delayed order with the current inventory level may provide good heuristics. Motivated by these examples, in “Asymptotic Optimality of Semi-open-Loop Policies in Markov Decision Processes with Large Lead Times,” Bai et al. consider a generic Markov decision process (MDP) with one delayed control and one immediate control. For MDPs defined on general spaces with uniformly bounded cost functions and a fast mixing property, they construct a periodic semi-open-loop policy for each lead time value and show that these policies are asymptotically optimal as the lead time goes to infinity. For MDPs defined on Euclidean spaces with linear dynamics and convex structures, they impose another set of conditions under which constant delayed-control policies are asymptotically optimal.

Development of framework in the selection and reuse of concrete waste and brick waste powder as pozzolanic material in cement concrete application using analytical hierarchy process technique

The utilization of construction and demolition waste (C&DW) for sustainability is a promising area. Globally, there is a growing potential interest in the reuse of waste powder from recycled concrete and bricks in concrete applications. In the current study, the pozzolana criteria were evaluated for three materials: Fly ash (FA), Concrete waste powder (CWP), and Brick waste powder (BWP). Chemical, Physical, and Pozzolanic tests, i.e., Frattini test, Lime Saturation test (LST), Strength Activity Index (SAI) and Electrical conductivity test (ECT), were carried out on the raw material. A framework was developed to select and reuse CWP and BWP in cement concrete applications. An Analytical Hierarchy Process (AHP) was carried out to study the priorities of pozzolana materials based on the road map criteria. One-way sensitivity analysis was performed to check the sensitivity of the properties. Microstructural characteristics such as scanning electron microscopy (SEM), X-ray diffraction (XRD), and thermal gravimetric analysis (TGA) were performed to investigate the morphology, amorphous content, and consumption of portlandite in the pozzolana. In addition, chemical activators; Lime, Sodium Silicate, and Sodium Hydroxide were investigated for their ability to enhance the pozzolanic activity of CWP, and statistical analysis was performed to validate the chemical enhancement. CWP and BWP cleared the road map criteria of pozzolanic activity. Adding (5–7.5%) lime improves the later strength, whereas (2.5–7.5%) NaOH & Sodium Silicate improve the early and later mechanical properties of the CWP-based mix.

Asphalt Concrete Mix Design Optimization Using Autoencoder Deep Neural Networks

Asphalt concrete (AC) balanced mix design (BMD) is based on the selection of aggregate gradation, component volumetrics, and binder content to control pavement cracking and rutting potential. The Illinois Flexibility Index Test (I-FIT) and the Hamburg Wheel Tracking Test (HWTT) results, used to predict cracking and rutting potential, respectively, are used in the BMD approach. However, BMD generally relies on a trial-and-error process to identify the aggregate gradation and binder content needed to meet volumetrics and optimize I-FIT and HWTT results. Minimizing or eliminating the trial-and-error process would increase productivity and accuracy. Therefore, this study proposes an autoencoder deep neural network (ADNN) to develop optimized AC mix design alternatives that can meet a prescribed flexibility index (FI) and rut depth (RD). Autoencoders are a type of neural network designed for representation learning composed of an encoder and a decoder. The encoder detects a structured pattern in the original input data to create a compressed representation of the AC mix design. The decoder reconstructs the compressed representation. The proposed autoencoder is composed of an encoder of five hidden layers, a latent space of one node, and a five-hidden-layer decoder. Models were created from a database of 5,357 data sets that include mix properties, I-FIT FI, and HWTT RD (after data preprocessing was conducted). An autoencoder was then trained to predict the total binder content, and aggregate gradation based on a target mix type, FI, and RD.