Separate Streams Research Articles

Hydrodynamics of liquid–liquid parallel flow in novel microextractors: Review

Parallel flows on microfluidic platforms enable continuous liquid–liquid operations and inline separation of effluent streams, bearing immense scope in integration of miniaturized separation processes. However, these flows face major challenges including low mass transfer efficiency due to lack of transverse convection and flow instability at low flow rates, which undermine their operating range and utility. The limitations have inspired dedicated research, delving into the fundamentals of fluid flow and transport mechanism and exploring novel configurations of microextractors. The current article summarizes the hydrodynamics of parallel flows and relevant process intensification strategies in microfluidic extractors, evolving from the use of straight to curved and helical geometries, besides elucidating unique secondary flow patterns observed in-state-of-the-art designs. It includes exclusive sections addressing various aspects of parallel flows: (i) flow inception and theoretical modeling of flow fields and phase hold up, (ii) challenges concerning interfacial stability and flow intensification, (iii) curvature effects in planar curved geometries, and (iv) curvature cum torsional effects in unique multi-helical configurations. The theoretical perspective of this review presents a roadmap that can provide further insights into design modifications for developing improved integrated microextractors based on parallel flows.

Individual, household and institutional level predictors of waste sorting: Evidence for Ecuador.

The rapid increase in waste generation in developing countries presents significant challenges, necessitating effective waste management strategies. This study examines the influence of individual, household and institutional factors on waste sorting behaviours in Ecuador, employing an ordered logistic regression model. Data were sourced from the 2019 National Multipurpose Household Survey (NMHS) and the Census of Economic Environmental Information in Decentralised Autonomous Governments (CEEIGAD). The NMHS uses a two-stage probabilistic sampling methodology, with census sectors as the primary sampling units and households as the secondary units. After excluding outliers and selecting individuals aged 15-65 years, the final sample consisted of 8601 households, including 26,175 individuals. The findings reveal that personal attributes such as gender, ethnicity, age, marital status and environmental concern significantly influence waste sorting behaviours. Household characteristics, including urban or rural location, are also critical. Institutional factors, such as municipal regulations, waste collection fees and waste separation at source, play essential roles in promoting waste separation. The study highlights the necessity for targeted governmental policies. Recommendations include improving environmental education, increasing sorting infrastructure in urban areas and ensuring waste collection systems maintain the separation of waste streams.

The loss of riparian vegetation along streams causes morphological divergences in functional traits of semiaquatic insects (Heteropteran: Gerromorpha) in the eastern Amazon.

Understanding the effects of mining activities on Amazonian streams and their impact on aquatic communities is of paramount importance in the current context of resource overexploitation in society. In this study, we assessed the significance of the environment and interspecific interactions on the organization patterns of semiaquatic insect species in a mineral extraction region in the eastern Amazon. We utilized the morpho functional characteristics of 22 species from the suborder Gerromorpha (Heteropteran), considering both the abundance and sexual dimorphism of these species. Additionally, we quantified the density of riparian vegetation surrounding each stream to categorize sampling points and evaluate whether there are differences in species distribution patterns among categories. We sampled 16 sites, categorized into two treatments based on the percentage of riparian vegetation in forested and deforested areas located in the Capim River Basin. We did not find the action of environmental filters on the total assembly; however, we found significant morphological divergence for all the traits analyzed. On the other hand, the separation of streams into treatments with different portions of riparian vegetation showed that there are significant differences between them regarding species distribution patterns. Forested streams within a 500-m radius have species distributed over a larger area, indicating that these streams have greater resource availability or that species can use these resources more efficiently. Our results demonstrate the importance of riparian vegetation for the studied communities, as well as for mitigating the impacts caused by mining activities.

Scenario Analysis of Food Phosphorus Footprint in Kisumu, a Lakeside East African City in Lake Victoria (Kenya).

Increased food production and consumption patterns have resulted in higher urban food phosphorus footprints, leading to a series of resource and environmental problems worldwide. We quantified the food phosphorus footprint of the African city of Kisumu using substance flow analysis. Our aim was to develop Kisumu's sustainable phosphorus management framework so that the city would reduce phosphorus losses into the food system. Our results show that in the year 2023, the import and export of food phosphorus in the Kisumu food system was 2730.26 ± 2.7% t P yr-1 and 3297.05 ± 2.4% t P yr-1, respectively. There was -566.79 ± -18% t P yr-1 food phosphorus deficit in the Kisumu food system. Crop planting subsystem runoff/leaching/erosion loss, household consumption subsystem waste loss, and pit latrine subsystem blackwater loss are the major pathways of phosphorus losses into the environment and the main contributors to the food phosphorus footprint in the city. The 2030 scenario analysis shows that implementing a comprehensive scenario scheme throughout the entire lifecycle process from phosphorus input to waste disposal is the best choice for reducing phosphorus losses and suppressing the growth of food phosphorus footprint in the future. Our study shows that the food phosphorus footprint in the Kisumu food system was 0.67 kg P cap-1yr-1 in 2023, which is still at a low level but may enter a continuous upward trend with the improvement of socio-economic development of the city. In our framework, we have proposed a few essential measures that include urine separation, installation of septic tank, adjustment of dietary structure, flexible layout of sanitary disposal facilities, and separation of organic waste streams to reduce food phosphorus footprints in Kisumu. Given the similarity of cities along the shores of Lake Victoria, our calculation methods and management strategies can be applied to other cities in the region.

A familiar face and person processing area in the human temporal pole

How does the brain process the faces of familiar people? Neuropsychological studies have argued for an area of the temporal pole (TP) linking faces with person identities, but magnetic susceptibility artifacts in this region have hampered its study with fMRI. Using data acquisition and analysis methods optimized to overcome this artifact, we identify a familiar face response in TP, reliably observed in individual brains. This area responds strongly to visual images of familiar faces over unfamiliar faces, objects, and scenes. However, TP did not just respond to images of faces, but also to a variety of high-level social cognitive tasks, including semantic, episodic, and theory of mind tasks. The response profile of TP contrasted with a nearby region of the perirhinal cortex that responded specifically to faces, but not to social cognition tasks. TP was functionally connected with a distributed network in the association cortex associated with social cognition, while PR was functionally connected with face-preferring areas of the ventral visual cortex. This work identifies a missing link in the human face processing system that specifically processes familiar faces, and is well placed to integrate visual information about faces with higher-order conceptual information about other people. The results suggest that separate streams for person and face processing reach anterior temporal areas positioned at the top of the cortical hierarchy.

Separation of ventilation and perfusion of electrical impedance tomography image streams using multi-dimensional ensemble empirical mode decomposition

Objective. In the future, thoracic electrical impedance tomography (EIT) monitoring may include continuous and simultaneous tracking of both breathing and heart activity. However, an effective way to decompose an EIT image stream into physiological processes as ventilation-related and cardiac-related signals is missing.Approach. This study analyses the potential of Multi-dimensional Ensemble Empirical Mode Decomposition by application of the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and a novel frequency-based combination criterion for detrending, denoising and source separation of EIT image streams, collected from nine healthy male test subjects with similar age and constitution.Main results. In this paper, a novel approach to estimate the lung, the heart and the perfused regions of an EIT image is proposed, which is based on the Root Mean Square Error between the index of maximal respiratory and cardiac variation to their surroundings. The summation of the indexes of the respective regions reveals physiologically meaningful time signals, separated into the physiological bandwidths of ventilation and heart activity at rest. Moreover, the respective regions were compared with the relative thorax movement and photoplethysmogram (PPG) signal. In linear regression analysis and in the Bland–Altman plot, the beat-to-beat time course of both the ventilation-related signal and the cardiac-related signal showed a high similarity with the respective reference signal.Significance. Analysis of the data reveals a fair separation of ventilatory and cardiac activity realizing the aimed source separation, with optional detrending and denoising. For all performed analyses, a feasible correlation of 0.587 to 0.905 was found between the cardiac-related signal and the PPG signal.

Simulation of Flow and Pressure Loss in the Example of the Elbow

One of the most basic issues in fluid mechanics is the description of flow in closed flows; more precisely, the calculation of pressure drops and the description of the flow form. Therefore, in this paper, the numerical simulation of the flow through the elbow was presented. This case was used to comprehensively describe the most important phenomena that should be taken into account during closed flows. The elbow was chosen as one of the most frequently used fittings in practice. The simulation was made with ANSYS Fluent, with the use of the turbulent model k-ω, SIMPLE simulation method, and at Reynolds number . The minor and major pressure loss were presented and discussed in the paper. The minor loss coefficient at the high Reynolds number was equal to around 0.2, which is close to the value of 0.22 used in engineering calculations. The influence of the Reynolds number on the shift of the stream separation point in the elbow was described. The secondary flow in the elbow was observed and the vortex structure was discussed and shown with the use of the Q-criterion (Q iso surface for level 0.005). This analysis allowed us to better visualize and describe the complex flow structure observed in the investigated case.

A PINN-DeepONet framework for extracting turbulent combustion closure from multiscalar measurements

In this study, we develop a novel framework to extract turbulent combustion closure, including closure for species chemical source terms, from multiscalar and velocity measurements in turbulent flames. The technique is based on a physics-informed neural network (PINN) that combines models for velocity and scalar measurements and a deep operator network (DeepONet) to accommodate spatial measurements and experimental parameters as separate input streams. An additional key innovation is the estimate of the unconditional means of the species’ chemical source terms as additional “observations” to constrain the prediction of these rates. This estimate is based on a convolution of the means of species reaction rates conditioned on principal components of the multiscalar data and the joint probability density functions of these principal components. The PINN-DeepONet method is implemented on the so-called Sydney flames, where training is carried out on 3 flames and validated on 4 flames. The results show that, despite the limited samples of experimental parameters, including the inlet flow and the fuel jet recess length within the air flow, the PINN-DeepONet approach can construct velocity and scalar fields along with important closure terms for turbulent transport and reaction rates.

Stagnation and the Natural Rate of Interest: Tracing the Roots of Lawrence Summers’s Theory of Secular Stagnation

ABSTRACT Over the past decade, Lawrence Summers has argued that stagnation cannot be rectified by monetary policy because it is the result of a negative natural rate of interest. This analysis brings together two separate streams of thought: traditions in which stagnation has been connected to excessive saving linked to income distribution, or to diminishing investment demand; and a tradition centred on the natural rate of interest and its relationship to the market rate. However, they remained largely separated until Summers brought them together. Modern discussions of the natural rate stem from Knut Wicksell’s Interest and Prices (1898). However, although he came close to arguing that the natural rate might be negative during cyclical depressions, it was mainly under-consumptionists who argued for the possibility of stagnation. These two strands of thinking came closer in the interwar period but they remained separate. The main advocate of secular stagnation, Alvin Hansen, drew on the American Institutionalist tradition, not Wicksell. Postwar Keynesians did not pursue the idea of a negative natural rate even though Samuelson had provided a theoretical explanation. It was not until Summers that a negative natural rate, income distribution and the possibility of secular stagnation were brought together.

Perceptual authentication hashing for digital images based on multi-domain feature fusion

In recent decades, numerous perceptual authentication hashing schemes have been proposed for image content authentication. However, most of these schemes are based on a single spatial or transform domain, and they fail to provide satisfactory robustness and discrimination capability when facing complex image manipulations in real scenarios. In this work, we present a perceptual authentication hashing scheme based on Convolutional Neural Network (CNN) that leverages both spatial and frequency domains. Specifically, we construct two separate streams for spatial and transform domains. Then, we introduce a feature fusion module to merge the features of these two domains to generate a hash sequence. Besides, we design a frequency domain channel filter and a frequency attention module for the frequency domain, and introduce a frequency domain loss function to optimize model training. Based on large-scale testing datasets, our scheme demonstrates superior performance compared to state-of-the-art schemes, as evidenced by Receiver Operating Characteristic (ROC) curves.

ALACEN: A Holistic Herbaceous Biomass Fractionation Process Attaining a Xylose-Rich Stream for Direct Microbial Conversion to Bioplastics.

Lignocellulose biorefining is a promising technology for the sustainable production of chemicals and biopolymers. Usually, when one component is focused on, the chemical nature and yield of the others are compromised. Thus, one of the bottlenecks in biomass biorefining is harnessing the maximum value from all of the lignocellulosic components. Here, we describe a mild stepwise process in a flow-through setup leading to separate flow-out streams containing cinnamic acid derivatives, glucose, xylose, and lignin as the main components from different herbaceous sources. The proposed process shows that minimal degradation of the individual components and conservation of their natural structure are possible. Under optimized conditions, the following fractions are produced from wheat straw based on their respective contents in the feed by the ALkaline ACid ENzyme process: (i) 78% ferulic acid from a mild ALkali step, (ii) 51% monomeric xylose free of fermentation inhibitors by mild ACidic treatment, (iii) 82% glucose from ENzymatic degradation of cellulose, and (iv) 55% native-like lignin. The benefits of using the flow-through setup are demonstrated. The retention of the lignin aryl ether structure was confirmed by HSQC NMR, and this allowed monomers to form from hydrogenolysis. More importantly, the crude xylose-rich fraction was shown to be suitable for producing polyhydroxybutyrate bioplastics. The direct use of the xylose-rich fraction by means of the thermophilic bacteria Schlegelella thermodepolymerans matched 91% of the PHA produced with commercial pure xylose, achieving 138.6 mgPHA/gxylose. Overall, the ALACEN fractionation method allows for a holistic valorization of the principal components of herbaceous biomasses.

To profit or not to profit: Founder identity at the intersection of religion and entrepreneurship

For more than a century, discussion of the connections between religion and entrepreneurship has pointed to what we would now label questions of identity. Our study of 25 participants in a program in Northern Kenya that aimed to introduce and stimulate capitalist entrepreneurship within extremely poor pastoralist communities shows that differences in participants' religious social identities strongly shaped whether or not they adopted new roles and role identities as capitalist entrepreneurs. This process also shifted the domains in which their religious and collectivist social identities were salient and helped to explain the emergence of important and contested changes in social and economic relations. We contribute to the development of founder identity theory by building research at the intersection of entrepreneurship and religion and at the intersection of entrepreneurship and poverty alleviation.

A New Strategy for a Separate Manufacture of Arabinooligosaccharides and Oligogalacturonides by Hydrothermal Treatment of Sugar Beet Pulp

Sugar beet pulp (SBP) samples were subjected to a two-step non-isothermal autohydrolysis process in order to obtain mixtures enriched in oligogalacturonides (OGalA) and arabinooligosaccharides (AOS) in separate streams. Operating at a maximum temperature of 130 °C, mixtures containing up to 30.4% oven-dry basis (o.d.b.) of OGalA with an OGalA/AOS ratio of 5.0 g/g were obtained during the first stage. Then, the treated solids were subjected to a second treatment at temperatures in the range 160–175 °C. When those solids were treated up to 175 °C, a mixture mainly made up of AOS (37.5% o.d.b.) with an AOS/OGalA ratio of 3.91 g/g was obtained as an effluent from the reactor. In order to increase their purity, both streams were then subjected to different refining steps. A product enriched in highly methylated and partially acetylated OGalA (42.5% o.d.b., degree of methylation (DM) = 69.2% mol/mol and degree of acetylation (DA) = 36.4% mol/mol), containing 17.2% o.d.b. of non-volatile non-identified compounds, was obtained by membrane filtration of the first-stage liquors, whereas a second one, mainly made up of AOS and galactooligosaccharides (GalOS) (55.0% AOS o.d.b., 13.8% GalOS o.d.b., and 13.3% non-volatile non-identified compounds, o.d.b.), was manufactured after an ion exchange treatment followed by membrane filtration of the second-stage liquors. This strategy was demonstrated to be a suitable and scalable alternative for the separate production of refined mixtures rich in OGalA or neutral pectic-oligosaccharides. Both types of products can result in different effects on the intestinal microbiota: AOS and GalOS show a significant bifidogenic effect and they could be consumed alone or combined with selected probiotic strains of Bifidobacteria for improving an unbalanced microbiota, whereas OGalA has been demonstrated to have a variety of biological properties and can promote the growing of some bacteria such as Faecalibacterium prausnitzii, a butyrate-producing microorganism underrepresented in patients with active IBD and infectious colitis.

Neural Generative Models and the Parallel Architecture of Language: A Critical Review and Outlook.

According to the parallel architecture, syntactic and semantic information processing are two separate streams that interact selectively during language comprehension. While considerable effort is put into psycho- and neurolinguistics to understand the interchange of processing mechanisms in human comprehension, the nature of this interaction in recent neural Large Language Models remains elusive. In this article, we revisit influential linguistic and behavioral experiments and evaluate the ability of a large language model, GPT-3, to perform these tasks. The model can solve semantic tasks autonomously from syntactic realization in a manner that resembles human behavior. However, the outcomes present a complex and variegated picture, leaving open the question of how Language Models could learn structured conceptual representations.

Rozwiązanie problemu tworzenia się zatorów w rurociągach podczas transportu gazu poprzez proces automatycznego strumieniowania

The article presents the application of autoejection process to ensure efficient operation of pipeline systems and gas separation installations when it is impossible to remove and utilize the condensate from the pipelines. Thus, in the suggested ejector, a single common stream is separated into two streams, i.e., an active and a passive stream, as opposed to two separate independent streams in existing ejection devices. As a result, we refer to such an ejection process as autoejection, or a self-ejection process. Such a procedure is run in the pipeline with the goal of blowing and dusting the liquid phase through the central high-velocity nozzle in circumstances of mass blocking and coating rather than expelling the liquid from the pipes. On the cross-sectional area of the belts, the velocity profiles of flows in laminar and turbulent regimes are known to differ greatly from one another. The adhesion forces acting from the tube's central axis outwards, towards its walls cause the flow rate to decrease. There is a cross-sectional interaction of flows in this mode, according to experimental studies of turbulent flows. As a result, compared to the laminar domain, the flow velocities in this regime are more equally distributed across the cross-section of the flow, and their values are roughly equal to the flow's average value. In this case, based on the dependences of the flow ∆p = f(W), it is known from the calculations and the table that at such velocity limits of the flows, the “braking” pressure (p0) of the liquid coating on the pipe walls corresponds to the maximum velocity of the central gas flow. The autoejection process can occur due to the difference between the static pressures. Unsaturated absorbent coatings can be blasted off the tube absorber's walls using this technique and blended back into the main gas stream. Gas-liquid autoejectors installed along the pipe absorber's length make it possible to use this method. The purpose and principles of autoejectors’ operation are considered and a perspective of their application in tube absorbers is noted.

Effect of Ni/SiO2 catalyst preparation method on methane decomposition and CO2 gasification cycles

Catalytic methane decomposition is a promising reaction to produce CO2-free hydrogen from methane-rich feedstock with solid carbon as a by-product. Significant research conducted on this reaction to find ways to manage and utilize this solid carbon. In this work, the methane decomposition reaction is followed by Reverse Boudouard Reaction using CO2 feedstock to convert the solid carbon to carbon monoxide, which is a valuable starting component for many chemical applications. Realizing this promising concept would require a catalyst that is efficient for both reactions. Herein, we explored the potential of using solution combustion synthesis (SCS) to make a 5 wt% of Ni supported SiO2 catalyst and benchmarked it versus the conventional impregnation method. The catalyst prepared by SCS showed an improved performance at different temperatures, space velocities, and catalyst pellet sizes. The SCS catalyst successfully completed five repeated cycles reaching up to 38.1 h of stable time on stream operation, whereas the impregnated catalyst was not able to complete the second testing cycle with only 14 h of time on stream operation. A thorough characterization using XRD, H2 and O2 TPR, TEM, SEM, XPS, and Raman spectroscopy were conducted to provide an adequate explanation for the observed performances for both catalysts. The Ni nanoparticles size and distribution, the strength of the metal support interaction, and the nature of graphitic carbon were the key factors affecting the catalytic performance. Insights on how to make an optimal catalyst for this promising process is identified which is a step forward toward making separated H2 and CO streams from methane feedstock and CO2, respectively.

Separated or Combined Treatment of Dye Wastewater Streams: A Case Study with Coagulation and Flocculation Process

This study compared the treatment conditions and efficiencies of the coagulation and flocculation process (CFP) on mixed and separated dye wastewater. The CFP, which employed Poly Aluminium Chloride (PAC) as coagulant and mucilage extracted from the peel of dragon fruit (Hylocereus undatus) (DFPM) as flocculant, was investigated based on Jar-tests. The suitable coagulation and flocculation conditions were found similar at pH (4-7), settling time (30-60 min.), and flocculant dosage (2-5 mg/L) for both type of wastewaters. However, the optimal PAC dosage was determined to be significantly higher for separated dye wastewater stream (330 mg/L PAC) than for the mixed one (260 mg/L PAC) to ensure same treatment efficiencies. The treatment efficiencies were similar for TSS and turbidity of both wastewater types; However, much less for color and COD of separated dye wastewater stream in comparison to those of the mixed one (78% and 68% vs 90% and 76%, respectively). This study provides a scientific basis for the consideration of separated or combined treatment of dye wastewater streams by CFP.
 
 

Detection of Forged Images Using a Combination of Passive Methods Based on Neural Networks

In the current era of social media, the proliferation of images sourced from unreliable origins underscores the pressing need for robust methods to detect forged content, particularly amidst the rapid evolution of image manipulation technologies. Existing literature delineates two primary approaches to image manipulation detection: active and passive. Active techniques intervene preemptively, embedding structures into images to facilitate subsequent authenticity verification, whereas passive methods analyze image content for traces of manipulation. This study presents a novel solution to image manipulation detection by leveraging a multi-stream neural network architecture. Our approach harnesses three convolutional neural networks (CNNs) operating on distinct data streams extracted from the original image. We have developed a solution based on two passive detection methodologies. The system utilizes two separate streams to extract specific data subsets, while a third stream processes the unaltered image. Each net independently processes its respective data stream, capturing diverse facets of the image. The outputs from these nets are then fused through concatenation to ascertain whether the image has undergone manipulation, yielding a comprehensive detection framework surpassing the efficacy of its constituent methods. Our work introduces a unique dataset derived from the fusion of four publicly available datasets, featuring organically manipulated images that closely resemble real-world scenarios. This dataset offers a more authentic representation than other state-of-the-art methods that use algorithmically generated datasets based on image patches. By encompassing genuine manipulation scenarios, our dataset enhances the model’s ability to generalize across varied manipulation techniques, thereby improving its performance in real-world settings. After training, the merged approach obtained an accuracy of 89.59% in the set of validation images, significantly higher than the model trained with only unaltered images, which obtained 78.64%, and the two other models trained using images with a feature selection method applied to enhance inconsistencies that obtained 68.02% for Error-Level Analysis images and 50.70% for the method using Discrete Wavelet Transform. Moreover, our proposed approach exhibits reduced accuracy variance compared to alternative models, underscoring its stability and robustness across diverse datasets. The approach outlined in this work needs to provide information about the specific location or type of tempering, which limits its practical applications.

Two-Level Spatio-Temporal Feature Fused Two-Stream Network for Micro-Expression Recognition.

Micro-expressions, which are spontaneous and difficult to suppress, reveal a person's true emotions. They are characterized by short duration and low intensity, making the task of micro-expression recognition challenging in the field of emotion computing. In recent years, deep learning-based feature extraction and fusion techniques have been widely used for micro-expression recognition, particularly methods based on Vision Transformer that have gained popularity. However, the Vision Transformer-based architecture used in micro-expression recognition involves a significant amount of invalid computation. Additionally, in the traditional two-stream architecture, although separate streams are combined through late fusion, only the output features from the deepest level of the network are utilized for classification, thus limiting the network's ability to capture subtle details due to the lack of fine-grained information. To address these issues, we propose a new two-level spatio-temporal feature fused with a two-stream architecture. This architecture includes a spatial encoder (modified ResNet) for learning texture features of the face, a temporal encoder (Swin Transformer) for learning facial muscle motor features, a feature fusion algorithm for integrating multi-level spatio-temporal features, a classification head, and a weighted average operator for temporal aggregation. The two-stream architecture has the advantage of extracting richer features compared to the single-stream architecture, leading to improved performance. The shifted window scheme of Swin Transformer restricts self-attention computation to non-overlapping local windows and allows cross-window connections, significantly improving the performance and reducing the computation compared to Vision Transformer. Moreover, the modified ResNet is computationally less intensive. Our proposed feature fusion algorithm leverages the similarity in output feature shapes at each stage of the two streams, enabling the effective fusion of multi-level spatio-temporal features. This algorithm results in an improvement of approximately 4% in both the F1 score and the UAR. Comprehensive evaluations conducted on three widely used spontaneous micro-expression datasets (SMIC-HS, CASME II, and SAMM) consistently demonstrate the superiority of our approach over comparative methods. Notably, our approach achieves a UAR exceeding 0.905 on CASME II, making it one of the few frameworks in the published micro-expression recognition literature to achieve such high performance.

A conceptual design of two-stream alkali-activated materials

To properly control the reaction kinetics and fresh properties evolution in conventional alkali-activated materials (AAMs), a conceptual design of two-stream AAMs has been proposed in this study. This is achieved by dividing the solid and liquid components in AAMs, including blast furnace slag (BFS) and electric arc furnace slag (EFS) precursors, as well as aqueous sodium hydroxide and silicate activators into two separate streams A and B, where a very limited reactivity is expected in individual streams to ensure sufficient workability retention. Moreover, a final-stage intermixing is required to combine individual stream mixtures and trigger the major activation reaction. Fresh and hardened properties of combined mixtures were checked at different stages. The microstructure and reaction products were investigated to understand the strength development. Low dynamic rheological parameters and good workability retention have been detected in all individual stream mixtures, accompanied by limited exothermic heat flows after the initial dissolution confirmed by calorimetry tests. Further, Portland cement (PC) is partially blended into stream A to alter the early stiffening process in combined mixtures and meet various setting demands after intermixing. However, this might lead to a reduction in mechanical properties, associated with the formation of porous microstructures and an increase in the Ca/Si ratio in reaction products. Eventually, the conceptual design is validated in different scenarios including self-compacting and 3D-printing concrete applications.