Homogeneous Formation Research Articles

Rethinking primary particulate matter: Integrating filterable and condensable particulate matter in measurement and analysis.

The current definition of primary particulate matter (PM) encompasses filterable PM (FPM) and condensable PM (CPM), which are evaluated using two distinct conventional measurement methods: cooling and dilution. While the cooling method exclusively considers the homogenous formation of CPM, the dilution method, closer to real-world conditions, neglects FPM characterization. To overcome this limitation, we propose a doubled-dilution system that enables the parallel characterization of both FPM and primary PM without diverting FPM from the CPM formation pathway. The doubled-dilution system has been investigated from a laboratory scale to a full-scale coal-fired power plant to facilitate simultaneous, real-time measurements of primary PM and FPM size distributions. Moreover, the formation rates of homogeneous and heterogeneous nucleation were compared. The evolution of the primary PM size revealed a bimodal distribution, and the filter-based mass concentration results demonstrated a pronounced preference for heterogeneous reactions (17.6 times higher than homogeneous nucleation). In particular, primary PM emissions were underestimated by up to 65.3% when only homogeneous CPM formation was considered, underscoring the importance of including FPM during primary PM measurements. Considering these results, we advocate adopting the term "primary PM" over "CPM."

Gradient-boosted spatiotemporal neural network for simulating underground hydrogen storage in aquifers

Underground hydrogen storage (UHS) in aquifers has emerged as a viable solution to address the seasonal mismatch between supply and demand in renewable energy. Numerical simulation of the UHS serves as a crucial foundation for optimizing storage operations and conducting system risk assessments. However, numerical simulation methods employed for these purposes often demand substantial data, making data collection challenging and computationally expensive, especially in scenarios involving the coupling of multiple physical fields. Deep learning serves as an effective tool in resolving this challenge. Here, we proposed a spatiotemporal neural network architecture with gradient enhancement, denoted as gradient-boosted spatiotemporal neural network (GSTNN) and its variant GSTNN-s. The GSTNN combines a convolutional neural network (CNN), a long short-term memory network (LSTM), and an autoencoder architecture. To incorporate physical constraints into the network, the spatiotemporal gradient operators from the gas-water seepage and gas convection-diffusion equations are introduced as regularization terms, imposing physics-informed constraints on the training process in both temporal and spatial dimensions. In predicting the multiphase flow of UHS in both homogeneous and heterogeneous formations, GSTNN outperforms CNN and CNN-LSTM in terms of the accuracy of pressure, saturation and H2 concentration fields. In terms of predicting UHS in formations with different permeabilities and porosities, GSTNN-s demonstrates improved performance as well. The proposed GSTNN architecture is promising in improving the efficiency of UHS numerical simulation, and has great potential to be applied for optimizing UHS operations in the future.

A multi-cycle recursive clustering algorithm for the analysis of social media data streams

Events are usually embedded in latent topics and the extraction of these latent topics are enabled by event detection algorithms. Unsupervised algorithms like Clustering algorithms are very useful for detecting events but with requirements which may not be relevant or easy to determine when using unstructured textual social media data. For instance, some algorithms are required to be used on specific data shapes, but determining the shape of an unstructured data may not be practical aside from the high level of noise in the data. Many of the existing algorithms work well with structured data, however, some of these algorithms can be adapted to unstructured data with the caveat that cluster formations may not contain consistent contextual information. We propose a novel Multi-Cycle Recursive Clustering Algorithm (MCRCA), able to sequentially eliminate noise, resulting in high homogeneous cluster formations. MCRCA does not require the initial specification of clusters numbers as the estimated number of clusters can be deduced at convergence. Our algorithm out-performs the classical LDA and K-Means algorithms in forming highly homogeneous clusters, context-wise.

Plano-radial stationary movements of incompressible oil using various filtration laws in a homogeneous annular formation

The issues of plane-radial movement of incompressible oil in a homogeneous horizontal circular formation are studied in the article. Considering that filtration obeys various laws, researches have been carried out according to linear Darcy’s law, generalized Darcy’s law and the modified Caisson model. The article solved stationary hydrodynamic problems about the hemispherical-radial flow of non-Newtonian oil in a homogeneous reservoir according to various filtration laws. Formulas for all the main indicators of development, well flow rate, filtration rate, and pressure gradient were derived. Considering these formulas, the characteristic features of the development of these deposits are identified, methods for developing and implementing measures to eliminate the complications that occur, as a result of which it is possible to increase the oil recovery of the deposits. Each of the stated problems has been solved using mathematical methods, and corresponding algorithms have been obtained taking into account the forms of oil movement in a porous medium. A plane-parallel simple filtration flow of oil moves from a skid-shaped reservoir to a rectilinear gallery. Such fluid flow is observed when a developing oil field has several parallel rectilinear rows of production wells. In oil-bearing areas between parallel adjacent rows, oil filtration is also plane-parallel. This implies the practical significance of solving the problem of plane-parallel oil flow in this scientific article. For each filtration law, hydrodynamic formulas calculated for well operation parameters and oil reservoir development indicators are derived. It is advisable to use the obtained models of oil flow rate, filtration rate, distribution law of current pressure, current pressure gradient, duration of oil movement in the drainage zone are both when drawing up an optimal reservoir development project, and for regulating and adjusting the process of oil extraction from exploited fields. Three stationary hydrostatic problems have been solved, in which the filtration processes obey only a general nonlinear law, and all the basic calculation formulas characterizing the filtration processes have been derived. By analyzing these formulas, it is possible to identify the nature of the impact of each well parameter and each reservoir development indicator on the development process. Also, the results have been obtained to solve various theoretical problems of developing oil deposits when drawing up projects for the development of new fields. A flat-radial simple filtration flow of oil moves from a circular horizontal reservoir to a central production well. In addition, such simple filtration fluid flow also occurs when a developing oil strip field has several (usually three or four) parallel straight rows of production wells. In the drainage zones of these wells, a simple plane-radial filtration flow also occurs.

Estimating complete migration probabilities from grouped data: A methods protocol for developing a global Human Internal Migration Database.

The majority of migration moves globally are internal within national borders. This makes internal migration intensities an important component for understanding the dynamics of population change according to size, composition and across geographies. While incorporating migration into demography's quantitative framework allows a description of population change across both time and space, and mathematical and conceptual frameworks for migration have been developed, researchers lack a public repository of historical age-origin-destination-specific migration probabilities that is in a common format and spans a range of countries. Addressing this requires a robust method for inferring migration probabilities from census and survey data when there are significant levels of uncertainty from small-sample noise and age aggregation. In this paper we extend the P-TOPALS and P-spline methods for smoothing migration probabilities to apply to grouped data by ages to develop a methods protocol for a harmonised, homogeneous format and multi-nation Human Internal Migration Database. We find our method out-performs a hybrid spline-parametric method in terms of both accuracy and plausibility. We illustrate the method by estimating complete age-origin-destination migration probabilities for more than 50 countries using microdata samples from IPUMS International. This work advances the stock of migration data from which demographers and others can draw from in the analysis and projection of population change.

Research on Propagation Characteristics of Fracture Grouting in Clay Formation

Splitting grouting is a highly effective technique for reinforcing tunnels and underground structures, ensuring their operational stability and facilitating long-term maintenance. It has been widely adopted in the prevention and remediation of geological hazards. However, the theoretical research on the diffusion mechanisms of split grouting lags behind its practical applications. This study addresses several key scientific challenges in understanding the diffusion behavior of split grouting. By integrating experimental design, numerical simulations, and theoretical analysis, we conduct a systematic investigation into the diffusion process and vein morphology of split grouting in both homogeneous and heterogeneous formations. We first employed a self-developed two-dimensional grouting test system to perform diffusion experiments on cohesive strata, focusing on the influence of various factors such as grout density, water/cement ratio, soil consistency, and fracture characteristics. The results provide insights into the diffusion patterns, morphology, soil pressure distribution, and surface uplift behavior of the grout veins. Subsequently, a numerical simulation program, developed in-house, based on the finite element method (FEM) and the volume of fluid (VOF) approach, was employed to model the entire process of fracturing grouting within clay strata. The experimental and numerical results indicate that grout vein diffusion in layered soil follows a Y-shaped pattern with an inclined deflection. In uniform strata, the surface uplift curve displays both symmetrical and asymmetrical “convex” elevations, while in heterogeneous soft and hard strata, the uplift is characterized by distinct “convex” deformations. Finally, based on these findings and the principles of contact mechanics, we analyze the underlying mechanisms. The results suggest that weak contact zones undergo tensile cracking and horizontal deflection prior to the formation of grout veins. Additionally, local stress rotations in the soil can induce tilting and deflection. The theoretical insights derived from this study provide valuable guidance for practical engineering applications.

Molecular Dynamics Simulation of Bubble Formation in Confined Water in Si/SiO2 Nanochannels

Megasonic-based techniques are employed in the etching and cleaning processes in the semiconductor industry since they are gentler than other cleaning techniques and less apt to cause damage. In these processes, sound waves, at a frequency of 1 MHz or higher, are sent into etching or cleaning fluid, which could result in the formation of bubbles inside the fluid, revealing features and producing patterns. The formation and collapse of bubbles in nano-scale features is of interest in the semiconductor industry due to the potential effects on etching performance and surface roughness. Our understanding is still limited, however, because of the dimensions involved. Typically, the bubble size is too small, and the duration of bubble formation/collapse is too short, to allow easy study of the characteristics of bubble formation or collapse through experimental methods. Molecular dynamics (MD) simulation is a powerful tool to simulate such a phenomenon, which can facilitate understanding of bubble behavior in a confined space, and in the vicinity of the surface.In this work we use MD simulations to simulate bubble formation in confined water in silicone (Si) and silicon dioxide (SiO2) nanochannels. Our focus of study is to identify the mechanism type for bubble formation in these nanofeatures, and determine how the surface characteristics, including the wettability, influence bubble formation. Figures 1a and 1b show the simulation results of bubble formation in confined water in the Si and SiO2 nanochannels, respectively. Our results show that the bubble forms on the hydrophobic Si surface, indicating a heterogeneous bubble formation, while for the hydrophilic SiO2 surface, the bubble tends to form away from the surface and in the bulk of the liquid, indicating a homogeneous bubble formation. In a hybrid situation where both the hydrophobic Si and hydrophilic SiO2 surfaces are present (Figure 1c), heterogenous bubble formation is dominant and the bubble forms on the Si surface. Our work provides insights into the mechanism of bubble formation in the confined water in nanofeatures and how surface wettability affects it.

An Arteriovenous Bioreactor Perfusion System for Physiological In Vitro Culture of Complex Vascularized Tissue Constructs.

The generation and perfusion of complex vascularized tissues in vitro requires sophisticated perfusion techniques. For multiscale arteriovenous networks, not only the arterial, but also the venous, biomechanical and biochemical conditions that physiologically exist in the human body must be accurately emulated. For this, we here present a modular arteriovenous perfusion system for the in vitro culture of a multi-scale bioartificial vascular network. The custom-built perfusion system consisted of two circuits: in the arterial circuit, physiological arterial biomechanical and biochemical conditions were simulated using a modular set-up with a pulsatile peristaltic pump, compliance chambers, and resistors. In the venous circuit, venous conditions were emulated accordingly. In the center of the system, a bioartificial multi-scale vascularized fibrin-based tissue was perfused by both circuits simultaneously under biomimetic arteriovenous conditions. Culture conditions were monitored continuously using a multi-sensor monitoring system. The physiological arterial and venous pressure- and flow-curves, as well as the microvascular arteriovenous oxygen partial pressure gradient, were accurately emulated in the perfusion system. The multi-sensor monitoring system facilitated live monitoring of the respective parameters and data-logging. In a proof-of-concept experiment, vascularized three-dimensional fibrin tissues showed sustained cell viability and homogenous microvessel formation after culture in the perfusion system. The arteriovenous perfusion system facilitated the in vitro culture of a multiscale vascularized tissue under physiological pressure-, flow-, and oxygen-gradient conditions. With that, it presents a promising technique for the in vitro generation and culture of complex large-scale vascularized tissues.

Gradient-guided Convolutional AutoEncoder for predicting CO2 storage in saline aquifers with multiple geological scenarios and well placements

CO2 sequestration in saline aquifers is a crucial component of carbon capture, storage, and utilization (CCUS) technology. The subsurface fluid flow of CO2 and brine in porous media involves the coupling of multiple physics fields, featuring complex nonlinear partial differential equations (PDEs). The prevalent approach for studying subsurface fluid flow is to discretize PDEs in spatial and temporal dimensions and solve them numerically. Here, this work proposed a Gradient-guided Convolutional AutoEncoder (GCAE), where the gradient differential operator is incorporated as physical prior knowledge into the loss function of the neural network. The physical prior knowledge guides the training process of the neural networks, enhancing their physical interpretability compared with the purely data-driven Convolutional AutoEncoder (CAE). This work applied GCAE to the CO2 sequestration in the homogeneous formation, the heterogeneous formation, as well as the heterogeneous formation with different well placements to demonstrate the improvement in prediction accuracy, data stability, and generalization capability compared with the CAE approach.

Generalized Homogeneous Formation Control for Unicycle Multi-Agent Systems

In this paper, the formation control problem for unicycle multi-agent systems is considered. The design of a generalized homogeneous leader–follower formation control protocol is studied which shows that such a control protocol can be obtained by “upgrading” from the classical linear control. With this proposed control protocol, a finite-time stability of the formation error is ensured if the acceleration of the leader is bounded by some known value. In addition, if the leader acceleration is unknown but bounded, the robust formation is achieved by ensuring the formation error’s input-to-state stability. Simulations are carried out to verify the effectiveness of the proposed control protocol.

Reconstruction of the surface Bi3+ oxide layer on Bi2O2CO3: Facilitating electron transfer for enhanced photocatalytic degradation performance of antibiotics in water

The advancement and meticulous design of functional photocatalysts exhibiting exceptional photocatalytic redox activity represent a pivotal approach to mitigating the dual challenges of environmental pollution and energy scarcity. In this study, we elucidate the construction of a Bi2O2CO3 catalytic system capable of inhibiting oxidative electron transfer through the attenuation of homogeneous Bi0 particle formation, achieved through the judicious modulation of solvent ratios. This innovative architecture possesses a distinctive active site and enhances interfacial Bi-O electron transfer pathways via exposure to oxidized Bi3+. Upon photoexcitation, the Bi2O2CO3 catalytic system undergoes structural distortions in its excited state that facilitate forbidden radiative relaxation, thereby fostering long-lived charge separation states. Remarkable catalytic activity was demonstrated in the remediation of pollutants, encompassing auto-oxidation and the catalytic degradation of superoxide radicals (•O2−) and holes (h+). Notably, the effective degradation of tetracycline hydrochloride (TCH) in aqueous media reached an impressive 86 % under simulated visible light irradiation, accompanied by a reaction rate constant 3.08 times superior to that of the 5-Bi/Bi2O2CO3 counterpart. Theoretical analyses revealed that the oxidized state of Bi2O2CO3 exhibits a crystal structure with significant electron trapping capability, undergoing pronounced apparent relaxation phenomena on its surface while demonstrating an enhanced adsorption affinity for H2O and O2. The potential degradation mechanisms were rigorously investigated through High-performance liquid chromatography (HPLC-MS), elucidating the photodegradation pathways and intermediates of TC. This work may serve as a distinct paradigm for the rational design of novel photocatalysts aimed at fostering sustainable environmental remediation and advancing energy innovation.

Molecular Dynamics Simulation of Bubble Formation in Confined Water in Si/SiO2 Nanochannels

We used molecular dynamics simulations to study bubble formation in confined water in Si and SiO2 nanochannels. Our simulations showed that surface wettability plays a major role in determining the mechanism type of bubble formation in confined geometry of nanofeatures. Hydrophobic Si surfaces and hydrophilic SiO2 surfaces led to heterogenous and homogenous bubble formation, respectively. Such observations can help in understanding cavitation effects during etching/cleaning processes of features at nano-scale dimensions.

Enhancing spontaneous and continuous liquid directional transport on peristome-mimetic surface with hierarchical microgrooves

Directional liquid transport function discovered on the peristome of Nepenthes alata has attracted considerable attention for its diverse potential applications. Despite the extensive efforts made for the peristome-mimetic surface fabrication and the anisotropic liquid spreading regulation, it remains a daunting challenge to reveal the synergistic effect of hierarchical structures on the liquid spreading and pinning dynamics. Here, we demonstrate the first-tier microgroove morphology, as well as the presence of second-tier microgrooves, play an important role in homogenous film formation and the directional liquid transport control. Through experimental investigation and theoretical analysis, the enhanced spreading and pinning effect is validated. Moreover, the preferential directional liquid spreading will collapse on the peristome-mimetic surface without a rational parameter design, and the threshold value for the transition of liquid propagation dynamics is determined. Spontaneous directional liquid transport from the cold region to the hot region and smart liquid transport regulation was also realized on the peristome-mimetic surface. This work will provide guidance to the design of effective open microfluidic systems, and open a new way for thermal management and lab-on-chip applications.

Pore-scale behaviors of CO2 hydrate formation and dissociation in the presence of swelling clay: Implication for geologic carbon sequestration

Hydrate-based CO2 sequestration (HBCS) under seafloor with huge storage capacity and long-term mechanical stability is attractive for large-scale carbon reduction. However, as representative geochemical constituents of marine sediments, swelling clay minerals still play ambiguous roles in hydrate phase transition and sedimentary structure stability. In this study, pore-scale behaviors of hydrate deposition and reservoir structure evolution in the presence of montmorillonite (MMT), a representative swelling clay, was investigated using low-field nuclear magnetic resonance (LNMR) technique. Total inter-particle interaction energy of 195.4 KbT ensured the dispersion of clay in 0.5 wt% MMT system, which facilitated homogeneous hydrate formation by providing nucleation sites and surface electric fields, improving hydrate conversion from 78.2 % to 89.6 %. Weak water activity caused by strong water absorption of swelling clay resulted in a 14.4 % reduction in CO2 storage capacity of high-concentration (10.0 wt%) MMT reservoir. Hydrate phase transition accompanied by the migration of MMT particles and liquid water synergistically contributed to sedimentary structure evolution. Migration of MMT-rich fluid with high viscosity could cause irreversible geologic damages by exacerbating sedimentary skeleton deformation. This work reveals the interaction between swelling clay and CO2 hydrate at microscopic scale, providing new perspectives for effective implementation of CO2 geologic sequestration in marine sediments.

Hydrothermal carbon reduction in the absence of minerals

Abiotic synthesis of CH4 in seafloor hydrothermal fluids is generally assumed to occur via heterogeneous reactions on mineral surfaces. Stepwise homogeneous reduction of CO2 has, however, been suggested as an alternative (but sluggish) abiotic pathway to CH4, potentially via metastable species of intermediate oxidation states. In this study, we examine the effect of two temperature-dependent methylated species − methanol (CH3OH) and methanethiol (CH3SH), on homogeneous CH4 formation rates under long-term simulated hydrothermal conditions. Aqueous solutions containing formic acid (H13COOH, generating 13CO2 and H2) were heated with and without H2S at 300–325 °C (35 MPa) in a flexible Au reaction cell over several years without added minerals. Substantial 13C-labeled CH4 and CH3OH production from 13CO2 was observed over 4.3 yr, with aqueous CH4 formation varying with CH3OH abundance – a strong function of dissolved H2 abundance and, inversely, temperature. CH4 production was slower at 325 °C with lower CH3OH concentrations (in equilibrium with CO2 and H2), and faster at 300 °C, accompanying an equilibrium-controlled increase in CH3OH. Fastest CH4 production occurred at 300 °C following injection of H2S and H13COOH, which led to rapid formation (<4 days) of 13C-labeled CH3SH that subsequently decomposed over a further 0.8 yr, partly to 13CH4. Heating aqueous 13CH4 to 345–387 °C (33–35 MPa) in the presence of an oxidizing hematite-magnetite-pyrite assemblage, however, yielded no detectable CH3SH after 112 days indicating the reverse reaction is inhibited under favorable thermodynamics. Neither direct reduction of CO2 to CH3SH nor CO2-CH3SH equilibrium were evident at 300 °C, implying CH3SH and CH3OH play disparate roles in homogeneous carbon reduction to CH4. Longer chain hydrocarbons (C2+ alkanes) remained low throughout the experiments.CH3SH abundances previously reported in vent fluids at the Von Damm hydrothermal field correlate strongly with demonstrably abiotic HCOOH there, suggesting the reduction of HCOOH to CH3SH observed in this study may also occur in vent fluids. A comparison of mineral-free 13CH4 production rates reported here with 13CO2 reduction experiments involving minerals indicates that homogeneous reduction proceeds at similar rates to purported transition metal-catalyzed 13CH4 production, and is generally faster than experiments with either added olivine or ultramafic rock. Previous claims of substantial mineral-catalyzed abiogenic CH4 production are therefore not supported by our study. Homogeneous CO2 reduction may be a significant source of methylated compounds and CH4 in hydrothermal fluids characterized by decadal (or longer) residence times, such as those found in mineral-hosted inclusions or occluded fractures in igneous basement, requiring only moderate temperatures and abundant H2 to proceed.

Integrated sources model: A new space-learning model for heterogeneous multi-view data reduction, visualization, and clustering

In machine learning, multi-view data involve multiple distinct sets of attributes (&amp;ldquo;views&amp;rdquo;) for a common set of observations; when each view has the same attributes considered in different contexts, the data are said to contain multiple views of homogeneous format, which can be conceptualized as a tensor. In this article, we describe a novel approach for integrating multiple views of heterogeneous format into a common latent space using a workflow that involves non-negative matrix and tensor factorization (NMF/NTF). This approach, which we refer to as the integrated sources model (ISM), consists of two main steps: Embedding and analysis. In the embedding step, the views are transformed into matrices with common non-negative components. In the analysis step, the transformed views are combined into a tensor and decomposed using NTF. We also present a variant of ISM; the integrated latent sources model (ILSM), which offers significant advantages over ISM in terms of computational power and in cases where the views are highly unbalanced with regard to the number of attributes per view. Noteworthy, ISM can be extended to process multi-omic and multi-view datasets even in the presence of missing views. We provide a proof-of-concept analysis using five examples, including the UCI Digits (the University of California Irvine Pen-Based Recognition of Handwritten Digits) dataset, a public cell-type gene signatures dataset, and a multi-omic single-cell dataset. These examples demonstrate that, in most cases, multi-view clustering is better achieved with ISM or its variant ILSM than with other latent space approaches. We also show how the non-negativity and sparsity of the ISM model components enable straightforward interpretations, in contrast to other approaches that involve latent factors of mixed signs. Finally, we present potential applications to single-cell multi-omics and spatial mapping, including spatial imaging, spatial transcriptomics, and computational biology, which are currently under evaluation. ISM relies on state-of-the-art algorithms invoked through a simple workflow implemented in Python.

Subjective well-being: the problem of analyzing population qualitative heterogeneity (part 1)

The article discusses importance of the methodological problem of analyzing the qualitative heterogeneity of a set of objects in the process of sociological measuring of subjective well-being. It presents the results of an exploratory study aimed at testing a number of tools in procedures of reconstructing social types among the population as qualitatively homogeneous latent formations (according to the nature of subjective well-being). Taking as preconditions, the authors proceed from the existence of five group problems of a theoretical and methodological nature, the formulation and solution of which presumably contribute to developing a methodology for studying qualitative heterogeneity. This part of the article, first, substantiates the existence of a request for methodological reflecting the use of generalized indicators of subjective well-being (life satisfaction, personal happiness) in mass surveys, the importance of the transition to multidimensional models of measurement and analysis implemented within the conceptual framework of the typological method of social knowledge. Second, the complete set of particular indicators and the logic of their selection for typological analysis are offered (the results will be presented in the second part of the article). Third, the problem of studying the relationship between indicators of subjective well-being is raised from the perspective of forming the basis for the typology.

Investigating agglomeration behavior of recycled asphalt mixtures in mixing stage using discrete element method

The inclusion of clusters in recycled asphalt pavement (RAP) materials has a substantial negative impact on the mechanical properties, particularly affecting the homogeneity formation in recycled asphalt mixtures. Hence, it is imperative to gain insight into the agglomeration and dispersion of RAP materials during the mixing stage. Due to experimental limitations, this study opted for the discrete element method (DEM) as an alternative approach to simulate the mixing process of hot recycled asphalt mixtures containing RAP clusters. The impact of RAP cluster sizes and aging degree was examined. Parameters for the parallel bond model were determined through static loading and stacking angle tests, while contact bond number and dispersion coefficients were calculated to assess the agglomeration and dispersion behaviors of hot recycled asphalt mixtures. The results indicated that an increase in total bond number and a decrease in RAP-RAP bonds demonstrated the formation of new clusters during the mixing process. A critical cluster size (7.1 mm in this study) was identified, requiring more mixing effort for dispersion. Although following the same principle, the influence of aging degree on RAP materials was found to be significant.

Removal of Lead Using Novel Composite Synthesized from Rice Husk and Used Tea Leaves Extract

Untreated industrial effluents, particularly from tanneries and heavy industries, are the main source of heavy metal pollution, which poses serious environmental risks. Lead is one of the most toxic heavy metals, adversely affects human functioning and accumulates in the environment. This study presents ACUTLaqE (Activated Carbon-Used Tea Leaves Aqueous Extract) as an effective adsorbent for Pb2+ ion removal from their aqueous solution. The composite was synthesized by blending activated carbon from rice husks with a tea extract solution and characterized using SEM, XRD, and FTIR spectroscopy. Batch tests demonstrated that ACUTLaqE is highly efficient, removing about 99% of Pb2+ ions at an adsorbent dose of 2 g/L within 30 minutes. The adsorption data conformed well to the Langmuir isotherm model, suggesting a homogeneous monolayer formation on the composite surface. The qm was 38.61 mg/g, with an RL value close to 0, indicating highly favourable adsorption. Thermodynamic parameters showed negative Gibbs free energy (ΔG⁰) values, reflecting a spontaneous adsorption process. The enthalpy (ΔH⁰) and entropy (ΔS⁰) changes were 66.86 KJmol-1 and 257.12 JK-1mol-1, respectively. The adsorption mechanism involved electrostatic interactions and surface complexation with the composite's hydroxyl and carboxyl groups. These findings suggest that ACUTLaqE is a promising adsorbent material for Pb2+ and potentially other heavy metals removal from industrial effluents.

Relevance of Platinum Underlayer Crystal Quality for the Microstructure and Magnetic Properties of the Heterostructures YbFeO3/Pt/YSZ(111).

The hexagonal ferrite h-YbFeO3 grown on YSZ(111) by pulsed laser deposition is foreseen as a promising single multiferroic candidate where ferroelectricity and antiferromagnetism coexist for future applications at low temperatures. We studied in detail the microstructure as well as the temperature dependence of the magnetic properties of the devices by comparing the heterostructures grown directly on YSZ(111) (i.e., YbPt_Th0nm) with h-YbFeO3 films deposited on substrates buffered with platinum Pt/YSZ(111) and in dependence on the Pt underlayer film thickness (i.e., YbPt_Th10nm, YbPt_Th40nm, YbPt_Th55nm, and YbPt_Th70nm). The goal was to deeply understand the importance of the crystal quality and morphology of the Pt underlayer for the h-YbFeO3 layer crystal quality, surface morphology, and the resulting physical properties. We demonstrate the relevance of homogeneity, continuity, and hillock formation of the Pt layer for the h-YbFeO3 microstructure in terms of crystal structure, mosaicity, grain boundaries, and defect distribution. The findings of transmission electron microscopy and X-ray diffraction reciprocal space mapping characterization enable us to conclude that an optimum film thickness for the Pt bottom electrode is ThPt = 70 nm, which improves the crystal quality of h-YbFeO3 films grown on Pt-buffered YSZ(111) in comparison with h-YbFeO3 films grown on YSZ(111) (i.e., YbPt_Th0nm). The latter shows a disturbance in the crystal structure, in the up-and-down atomic arrangement of the ferroelectric domains, as well as in the Yb-Fe exchange interactions. Therefore, an enhancement in the remanent and in the total magnetization was obtained at low temperatures below 50 K for h-YbFeO3 films deposited on Pt-buffered substrates Pt/YSZ(111) when the Pt underlayer reached ThPt = 70 nm.