Migration Model Research Articles

A Mathematical Model for Collective Behaviors and Emergent Patterns Driven by Multiple Distinct Stimuli Produced by Multiple Species

Collective migration underlies key developmental and disease processes in vertebrates. Mathematical models describing collective migration can shed light on emergent patterns arising from simple mechanisms. In this paper, a mathematical model for collective migration is given for arbitrary numbers and types of individuals using principles outlined as a set of assumptions, such as the assumed preference for individuals to be “close but not too close" to others. The model is then specified to the case of two species with arbitrary numbers of individuals in each species. A particular form of signal response is used that may be parameterized based on experiments involving two or three agents. In its simplest form, the model describes two species of individuals that emit distinct signals, distinguishes between them, and exhibits responses unique to the type by moving according to signal gradients in various planar regions, a situation described as "mixotaxis". Beyond this simple form, initial conditions and boundary conditions are altered to simulate specific, additional in vitro as well as in vivo dynamics. The behaviors that were specifically accounted for include motility, directed migration, and a functional response to a signal. Ultimately, the paper’s results highlight the ability of a single framework for signal and response to account for patterns seen in multi-species systems, in particular the emergent self-organization seen in the embryonic development of placodal cells, which display chase-and-run behavior, flocking behavior, herding behavior, and the splitting of a herd, depending on initial conditions. Numerical experiments focus around the primary example of neural crest and placodal cell “chase-and-run” and “flocking” behaviors; the model reproduces the separation of placodal cells into distinct clumps, as described in the literature for neural crest and placodal cell development. This model was developed to describe a heterogeneous environment and can be expanded to capture other biological systems with one or more distinct species.

Effects of Fines Migration and Reservoir Heterogeneity on Well Productivity: Analytical Model and Field Cases

Abstract Formation damage due to fines migration after water breakthrough during oil and gas production results in significant well productivity decline. A recent study derived an analytical model for fines migration during commingled water–oil production in homogeneous reservoirs. Yet, reservoir heterogeneity highly affects formation damage and well productivity. This article develops an analytical model for layer-cake reservoirs. We develop a novel methodology for characterizing productivity decline by considering the impedance as a function of water-cut, two quantities that are commonly measured throughout the production life of the well. The methodology is based on a new analytical model for inflow performance in layer-cake reservoirs under fines migration. The new model integrates pseudo-phase-permeability functions for commingled water–oil production with equations for fines release and induced permeability damage. The analytical model reveals linear well impedance growth versus water-cut increase, where the slope is determined by a modified form of the mobility ratio which includes the extent of formation damage. This linear form is shown to arise when the formation damage factor is constant, regardless of the distribution of reservoir permeabilities. The model is validated by comparison with production histories of five wells from three fields, which exhibit good agreement with the linear trend predicted by the new model. The explicit formulae allows for the prediction of productivity at abandonment, determining the optimal well stimulation time, as well as reconstructing skin values during the early stages of production to better estimate the influences of other formation damage factors, like those induced during drilling and completion.

Agricultural and Non-Agricultural College Students' Attitudes Towards Undocumented Migration

An estimated 4,350,000 immigrants reside in Texas, comprising 20% of the workforce and wielding a spending power of up to $112.8 billion. Negative sentiment towards migrants has created a hostile environment, despite their substantial socio-economic contributions. Efforts to mitigate this sentiment involve youth education, targeting younger generations to reshape perceptions about immigrants and emphasize diversity's significance. This research assesses undergraduates' attitudes toward undocumented migration and compares agricultural (AGNR) and non-agricultural (non-AGNR) students' stances. In this quantitative study, 452 participants completed the 20-item Attitude Toward Illegal Immigration survey, assessing constructs like cost-benefit, free flow, and human rights. Descriptive statistics, Mann-Whitney U tests, and multiple regressions were employed to analyze and compare Free flow (Model 1), Cost-Benefits (Model 2), Human Rights (Model 3), and the average attitude towards undocumented migration (Model 4). Results revealed a significant difference in undocumented migration scores. AGNR students slightly leaned against undocumented migration versus non-AGNR peers. Multiple regressions showed gender, ethnicity, and political inclination as significant predictors in both AGNR and non-AGNR models (cost-benefit, free flow, human rights, and undocumented migration). Further research should delve into these predictors' underlying reasons and replicate analyses in other US universities US using different approaches, such as a qualitative design.

Implementation of actin polymerization and depolymerization in a two-dimensional cell migration model and its implications on mammalian cell morphology and velocity

Cell migration, a pivotal process in wound healing, immune response, and even cancer metastasis, manifests through intricate interplay between morphology, speed, and cytoskeletal dynamics. Mathematical modeling emerges as a powerful tool to dissect these complex interactions. This work presents a two-dimensional immersed boundary model for mammalian cell migration, incorporating both filamentous actin (F-actin) and monomeric actin (G-actin) to explicitly capture polymerization and depolymerization. This model builds upon our previous one-dimensional efforts, now enabling us to explore the impact of G-actin on not just cell velocity but also morphology. We compare predictions from both models, revealing that while the one-dimensional model captures core dynamics along the cell’s axis, the two-dimensional model excels in portraying cell shape evolution and transverse variations in actin concentration and velocity. Our findings highlight the crucial role of including G-actin in shaping cell morphology. Actin velocity aligned with migration direction elongates the cell, while velocity normal to the membrane promotes spreading. Importantly, the model establishes a link between these microscopic aspects and macroscopic observables like cell shape, offering a deeper understanding of cell migration dynamics. This work not only provides a more comprehensive picture of cell migration but also paves the way for future studies exploring the interplay of actin dynamics, cell morphology, and biophysical parameters in diverse biological contexts.

Research and application of migration and plugging mechanism of temporary plugging balls in multicluster fracturing of horizontal wells

Plugging and diverting stimulation technology using temporary plugging balls (PDSTB) in horizontal wells is one of the effective measures to enhance production in heterogeneous carbonate reservoirs. However, the migration and plugging mechanism of temporary plugging balls in horizontal wells remain unclear, leading to suboptimal field application. Based on the Lagrangian method, the migration and plugging models of temporary plugging balls were established. The study investigated the migration and plugging mechanism of temporary plugging balls. It analyzed the effects of parameters such as displacement on the plugging efficiency. The results show that the flow field in the perforation section is significantly affected by the displacement. Temporary plugging balls show three states of plugging: one ball plugging one shot-hole, multiple balls plugging one shot-hole, and balls remaining in the wellbore. The plugging efficiency initially increases, and then, decreases with the increase in displacement and the ball diameter. The plugging efficiency initially increases, and then, stabilizes with the increase in the viscosity of the carrying fluid and the usage ratio of balls. Plugging efficiency decreases with increasing density of balls. The greater the pressure difference at the outlet of the perforation section, the higher the plugging efficiency in the advantageous inlet section. Based on these results, the field construction of Well M was guided. The gas production was 142.66 × 104 m3/d after stimulation, and the production increase was significant. This study provides a theoretical basis for optimizing and designing the parameters of PDSTB in carbonate long horizontal wells.

Triple junction benchmark for multiphase-field models combining capillary and bulk driving forces

Abstract A benchmark problem is formulated which is well suited for the validation of mesoscopic phase-field models for grain-boundary migration in polycrystals. First, an analytical steady-state solution of the sharp moving boundary problem is derived for a symmetric lamellar structure, which is valid for arbitrary bulk driving forces and triple junction angles. Characteristic quantities are identified to reduce the parameter space which in turn allows a systematic comparison of simulations and analytical results. Various multiphase-field (MPF) formulations are compared which approximate the sharp interface problem in terms of a diffuse regularization. An interfacial thickness convergence study reveals that the model error is largely dependent on the ratio of bulk to interfacial stabilizing force as well as the underlying model formulation. An additional grid convergence study highlights the efficiency of a more advanced discretization scheme. The results can be used to guide the selection of appropriate models and to estimate the interface thickness and spatial resolution required to achieve a given accuracy target. The post-processing framework consists of a fully automated determination of well-defined metrics from the phase field simulation data, eliminating human bias and facilitating reproducibility. The corresponding code is made openly available to assist the materials science and engineering community in validating MPF, multi-order parameter and similar model developments. We believe that this work provides a reliable benchmark procedure to better understand the potentials and limitations of current multiphase-field models as well as alternative approaches.

Solution of the problem with a small parameter in suspension filtration in a porous medium

Relevance. The necessity to calculate the changes in filtration properties during injection of suspensions for subsequent forecasting of technological parameters of wells. This calculation is complicated by the presence of different-scale effects, since the penetration depth of dispersed particles is orders of magnitude smaller than the characteristic dimensions of the formation. These effects have not been studied in detail before. Aim. To analyze the effect of a small parameter on the behavior of flow characteristics using a mathematical model of suspension filtration in a porous medium. Objects. Colmatation coefficient, filtration coefficient, distribution of concentration of dispersed particles in the formation, porosity, mathematical model of deep-bed suspension migration into a porous medium. Methods. Numerical modeling, explicit finite-difference scheme, solution of a problem with a small parameter, introduction of dimensionless parameters, method of characteristics. Results and conclusions. It is shown that the processes of conformance control and colmatation of a porous medium are described within the framework of a unified system of equations of deep-bed suspension migration into a porous medium. It is identified that the concentration of retained particles is a small parameter that allows reducing the complete system of equations of deep-bed suspension migration into a porous medium to a simplified form, in which the solution can be obtained analytically using the method of characteristics. The authors compared the solutions of the complete and simplified systems of equations of deep-bed suspension migration into a porous medium, indicating their compliance with an error of less than 4 %. They obtained the distributions of the concentration of dispersed particles and porosity in the reservoir during colmatation, showing that over time the colmatation front propagates at a constant rate. It is shown that the colmatation coefficient is a small parameter that significantly determines the nature of oil displacement by water, and a decrease in the colmatation coefficient leads to a decrease in the rate of colmatation and the appearance and growth of the size of the stabilized zone near the displacement front.

Modeling Population Mobility Flows: A Hybrid Approach Integrating a Gravity Model and Machine Learning

Population mobility between cities significantly affects traffic congestion, disease spread, and societal well-being. As globalization and urbanization accelerate, understanding the dynamics of population mobility becomes increasingly important. Traditional population migration models reveal the factors influencing migration, while machine learning methods provide effective tools for creating data-driven models to handle the nonlinear relationships between origin and destination characteristics and migration. To deepen the understanding of population mobility issues, this study presents GraviGBM, an expandable population mobility simulation model that combines the gravity model with machine learning, significantly enhancing simulation accuracy. By employing SHAPs (SHapley Additive exPlanations), we interpret the modeling results and explore the relationship between urban characteristics and population migration. Additionally, this study includes a case analysis of COVID-19, extending the model’s application during public health emergencies and evaluating the contribution of model variables in this context. The results show that GraviGBM performs exceptionally well in simulating inter-city population migration, with an RMSE of 4.28, far lower than the RMSE of the gravity model (45.32). This research indicates that distance emerged as the primary factor affecting mobility before the pandemic, with economic factors and population also playing significant roles. During the pandemic, distance remained dominant, but the significance of short distances gained importance. Pandemic-related indicators became prominent, while economics, population density, and transportation substantially lost their influence. A city-to-city flow analysis shows that when population sizes are comparable, economic factors prevail, but when economic profiles match, living conditions dictate migration. During the pandemic, residents from hard-hit areas moved to more distant cities, seeking normalcy. This research offers a comprehensive perspective on population mobility, yielding valuable insights for future urban planning, pandemic response, and decision-making processes.

Investigating immersion and migration decisions for agent-based modelling: Acautionary tale.

Agent-based modelling provides an appealing methodological choice for simulating human behaviour and decisions. The currently dominant approaches based on static transition rates or unverified assumptions are restrictive, and could be enhanced with insights from cognitive experiments on actual decision making. Here, one common concern is that standard surveys or experiments may lack ecological validity, limiting the extent to which research findings can be generalised to real-life settings. For complex, highly emotive decision-making scenarios, such as those related to irregular migration, the typically used short, methodical survey questions may not appropriately map onto complex real-world decisions of interest. Immersive contexts may offer more accurate representations of reality, potentially enhancing the usefulness of experimental information in multi-disciplinary modelling endeavours. This preregistered study, aimed directly at examining the effect of immersion on risk-taking in the context of migration decisions, and indirectly at informing a multi-disciplinary construction of an agent-based model of migration, presents a choice-based interactive fiction game in which players make migration decisions to advance through a story. (N = 1000 Prolific users) took part in one of four experimental conditions, three involving different renditions of the game attempting to create immersion, with the last condition presenting the decisions in standard survey format. Although addressing the lack of ecological validity in survey data is important for improving agent-based modelling methodology, the experimental design used to tackle this issue, while responding directly to modelling needs, proved too complex. The created experimental conditions ended up too distinct from each other, involving stimuli that differed in quantity and content. This introduced several unintended and uncontrolled confounds, making it impossible to meaningfully interpret the results of this experiment on its own. Our results act as a cautionary tale for agent-based modellers, highlighting that the modelling needs should not override the principles of experimental design, and provide motivation for more rigorous research on this topic.

Agricultural carbon emissions in China: measurement, spatiotemporal evolution, and influencing factors analysis

IntroductionThe agricultural sector is the second largest emitter of greenhouse gases, accounting for 23% of global anthropogenic carbon emissions. Analysis of the basic state of carbon emissions from China's agriculture is helpful to achieve carbon reduction targets.MethodsAgricultural carbon emissions were calculated using the emission factor method, based on data from the China Rural Statistical Yearbook and various provincial statistical yearbooks. To analyze spatial patterns, the standard deviation ellipse method and the center of gravity migration model were employed, uncovering the migration path of agricultural carbon emissions. Regional disparities and the driving factors of agricultural carbon emissions were further examined using the Theil index and the Logarithmic Mean Divisia Index (LMDI) model.ResultsThe analysis indicated that the emissions center has gradually shifted towards the central and western regions, reflecting changes in agricultural production activity areas. Intraregional differences are the primary contributors to the imbalance in agricultural carbon emissions, with pronounced disparities in grain production and consumption balance regions. Key influencing factors include agricultural production efficiency, adjustments in agricultural industrial structure, economic structure and output, and urbanization levels. The economic output effect and urbanization effect are identified as the main drivers of increased carbon emissions, while declining production efficiency has hindered emission reduction efforts.ConclusionThe findings provide valuable insights for regional management and policymaking in China's agricultural sector, highlighting the need to enhance production efficiency and optimize agricultural structure to reduce emissions.

Exploring the Temporal, Spatial and Characteristic Trends and Key Influencing Factors of Tianjin’s Industrial Heritage

Tianjin is currently in the phase of urban stock renewal, yet its industrial heritage encounters significant challenges, including constrained spatial development, a misalignment between industrial progress and the reuse of industrial heritage, and an understated cultural representation. This study utilized geospatial analysis methods, including kernel density analysis, standard deviation ellipse analysis, and gravity migration model analysis, to elucidate the distribution characteristics of Tianjin’s industrial heritage across temporal, spatial, and typological dimensions. Moreover, a geographic detector was employed to assess the impact of various factors on the development of Tianjin’s industrial heritage, ultimately elucidating the correlations between existing challenges and objective patterns. The conclusion of this paper presents three strategic approaches for the renewal of industrial heritage, emphasizing historical culture, environmental space, and sustainable development. These strategies are designed to provide a solid research foundation for protecting and revitalizing Tianjin’s industrial heritage resources.

Dynamic cluster field modeling of collective chemotaxis

Collective migration of eukaryotic cells is often guided by chemotaxis, and is critical in several biological processes, such as cancer metastasis, wound healing, and embryogenesis. Understanding collective chemotaxis has challenged experimental, theoretical and computational scientists because cells can sense very small chemoattractant gradients that are tightly controlled by cell-cell interactions and the regulation of the chemoattractant distribution by the cells. Computational models of collective cell migration that offer a high-fidelity resolution of the cell motion and chemoattractant dynamics in the extracellular space have been limited to a small number of cells. Here, we present Dynamic cluster field modeling (DCF), a novel computational method that enables simulations of collective chemotaxis of cellular systems with O(1000)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {O}}(1000)$$\\end{document} cells and high-resolution transport dynamics of the chemoattractant in the time-evolving extracellular space. We illustrate the efficiency and predictive capabilities of our approach by comparing our numerical simulations with experiments in multiple scenarios that involve chemoattractant secretion and uptake by the migrating cells, cell migration in confined spaces, regulation of the attractant distribution by cell motion, and interactions of the chemoattractant with an enzyme. The proposed algorithm opens new opportunities to address outstanding problems that involve collective cell migration in the central nervous system, immune response and cancer metastasis.

Modeling urbanization dynamics by labor force migration.

Individual participants in human society collectively exhibit aggregation behavior. In this study, we present a simple microscopic model of labor force migration based on the active Brownian particles framework. In particular, agent-based simulations show that the model produces clusters of agents from a random initial distribution. Furthermore, two empirical regularities called Zipf's and Okun's laws were observed. To reveal the mechanism underlying the reproduced aggregation phenomena, we use our microscopic model to derive an extended Keller-Segel system, which is a classic model describing the aggregation behavior of biological organisms called taxis. The obtained macroscopic system indicates that the concentration of the workforce in the real world can be explained through a new type of taxis central to human behavior, highlighting the relevance of urbanization to blow-up phenomena in the derived PDE system. We then characterize the transition between the aggregation and diffusion regimes both analytically and computationally. The predicted long-term dynamics of urbanization-originating in the asymmetric natures of employed and unemployed agents-are compared with global empirical data, particularly in the realms of labor statistics and urban indicators.

Analyzing the Spatiotemporal Dynamics of Drought in Shaanxi Province

Drought, as a natural disaster with wide-ranging impacts and long duration, has an adverse effect on the global economy and ecosystems. In this paper, four remote sensing drought indices, namely the Crop Water Stress Index (CWSI), Vegetation Supply Water Index (VSWI), Temperature Vegetation Dryness Index (TVDI), and Normalized Difference Water Index (NDWI), are selected for drought analysis. The correlation analysis is carried out with the self-calibrated Palmer Drought Severity Index (sc-PDSI), and based on the optimal index (CWSI), the spatiotemporal characteristics of drought in Shaanxi Province from 2001 to 2021 were studied by SEN trend analysis, Mann–Kendall test, and a center of gravity migration model. The results show that (1) the CWSI performs best in drought monitoring in Shaanxi Province and is suitable for drought studies in this region. (2) Drought in Shaanxi Province shows a decreasing trend from 2001 to 2021; the main manifestation of this phenomenon is the decrease in the occurrence of severe drought, with severe drought covering less than 10% of the area in 2010 and subsequent years. The most severely affected regions in the province are the northern Loess Plateau region and Guanzhong Plain region. In terms of the overall trend, only 0.21% of the area shows an increase in drought, primarily concentrated in the Guanzhong Plain region and the outskirts of the Qinling–Bashan mountainous region. (3) Drought conditions are generally improving, with the droughts’ center of gravity moving northeastward at a rate of 3.31 km per year. The results of this paper can provide a theoretical basis and a practical reference for drought control and decision-making in Shaanxi Province.

Development of a source-term migration model for a large bubble formed in a core disruptive accident

Because sodium-cooled fast reactors are designed with high inherent safety in mind, the probability of a core disruptive accident (CDA) is extremely low. However, from a defense-in-depth perspective, the study of CDA sequences is still worthwhile to assure the safety and reliability of reactors. During a CDA, a large bubble rapidly expands inside the sodium pool, rises from the core, and covers the gas region, providing a potential migration path for source terms (radioactive materials present within the containment barriers). Source terms released initially within the cover-gas region after a few hundred milliseconds are called instantaneous source terms. We propose here an instantaneous source-term migration model that provides a simplified evaluation of the amount of source terms absorbed by coolant sodium during the ascent of the CDA bubble. In the model, the particle motion within the CDA bubble obtained from the basic momentum equation is used to calculate the amount of source terms escaping from the bubble interface. In addition, a model analogous to aerosol scavenging by precipitation is used to assess the amount of source terms absorbed by droplets present in the bubble, especially the entrained sodium droplets that form during rapid expansion of the CDA bubble. The model is further validated by a previous source term migration experiment in which a large high-pressure bubble expands and rises in a sodium pool. Good agreement with the measured retention factor of a source term demonstrates the reliability of the developed model. Given these results, some key parameters are selected for a sensitivity analysis.

VERMEER FCM: A tool integrating exposure and hazard modelling for chemicals migrating from food contact materials

A new tool, VERMEER FCM, was developed to support the risk assessment of single organic chemicals migrating from plastic food contact materials (FCM). The freely available tool is integrated into MERLIN-Expo and has been designed in line with Regulation (EU) No 10/2011 for plastic FCM. Overall, the tool consists of three modules that allow (i) to model the migration of chemicals into food, (ii) to predict toxicological endpoints relevant to risk assessment of FCM chemicals, and (iii) to automatically check whether the chemical of interest is included in Regulation (EU) No 10/2011. To apply the VERMEER FCM tool, users need to provide information regarding the chemical(s) of interest, the FCM, the food and other parameters (e.g. contact time and temperature). The three modules can be run either separately or in combination. Migration is predicted by a recently developed migration model, whereas hazard predictions for genotoxicity, subchronic toxicity, reproductive and developmental toxicity and carcinogenicity are provided by QSAR models selected from the publicly available VEGA HUB. The major novelty of the tool is that it combines information on hazard and exposure (i.e. migration) with regulatory information. Several case studies were performed to demonstrate the application of the tool.

Molecular insights into the binding mechanism of strontium and cesium on phyllosilicates with different expandability

The environmental fate of strontium (Sr) and cesium (Cs), as the critical radioactive fission products, have raised significant concerns regarding radioactive waste disposal and environmental protection. The current study investigated the distinction in the binding configurations of Sr2+ and Cs+ on various 2:1 phyllosilicate (illite, vermiculite, and montmorillonite) by combining batch adsorption, sequential extraction, and spectroscopic analyses. The results show that strontium adsorption is strongly influenced by pH as well as ionic strength, while there is no significant variability in strontium adsorption by different types of clay minerals. EXAFS analysis confirms the outer complexation of strontium on the planar sites of the clay minerals, i.e., Sr2+ is surrounded by ~8.0 O atoms, RSr-O ≈ 2.6 Å, and that process is mainly realized by ion exchange. In contrast, Cs+ adsorption was markedly influenced by the variety of clay minerals but less by pH and ionic strength, the presence of humic acid (HA) inhibited Cs+ adsorption. The inner-sphere complexation formed mainly at the frayed edge sites on illite, and interlayer sites on vermiculite and montmorillonite, was the dominant mechanism for Cs+ adsorption. In addition, the collapse of the interlayer space of vermiculite induced by Cs+ adsorption on the interlayer sites was responsible for the more stable and irreversible immobilization. The findings in present work highlighted the significance of prevailed mineral in governing environmental migration risk of radionuclides, the revealed adsorption mechanism and binding configuration of Sr2+ and Cs+ on typical phyllosilicates would be referable in constructing a reliable migration model of Sr2+ and Cs+ in natural media.

Spatial and temporal evolution patterns and driving mechanisms of rural settlements: a case study of Xunwu County, Jiangxi Province, China

Urbanization and industrialization have driven rapid socio-economic development, leading to a significant population shift from rural areas to cities. This demographic transition has resulted in substantial changes in rural settlements, presenting considerable challenges for rural revitalization. Given the spatial differentiation, it is crucial to analyze the spatiotemporal evolution patterns and driving mechanisms of rural settlements under various development scenarios and at multiple scales within a county. Such analysis is essential for rational planning and sustainable development. This study analyzes the spatial and temporal evolution patterns and driving mechanisms of rural settlements in Xunwu County, Jiangxi Province, China, using land use dynamics, hot and cold spot analysis, and center of gravity migration models. The Multiscale Geographically Weighted Regression Model (MGWR) is employed to explore their transformation driving mechanisms. The results show that during 2010–2020 in the study area, the total change rate of rural settlements was 39.82%, with a dynamic degree of 2.87%. The average centroid of the settlements is located in Wenfeng Township, gradually migrating southeastward by 3.7 km. Cold spots are shrinking northward, while hotspots are gathering in Chengjiang Town. Socio-economic conditions dominate the evolution of rural clusters in this region, showing obvious spatial heterogeneity. This is followed by locational conditions that are weakening in influence, while the impact of natural geographical conditions exists in the northeast region. The research findings offer a scientifically rigorous and well-founded analysis of the evolution and driving mechanisms of rural settlements. This analysis provides a solid theoretical basis for policy planning in urban-rural integrated development and supports the sustainable growth of rural communities.

Synergistic effect of ceramic filler in polymer salt complex for improved ion dissociation and migration mechanism

Abstract Use of Ceramic filler is one of the most common approaches to improve the conductivity and stability properties of a solid polymer electrolyte (SPE) cum separator. Among them, active fillers like Garnet have been extensively used to enhance the stability and conductivity of SPE. However, SPE suffers from limited ion migration at room temperature acting as a bottleneck for their application in all solid-state batteries. An extensive study on these fillers' role in ion dissociation and migration can be a stepping stone for advanced SPE. In the present work, an FTIR analysis has primarily been used to identify and evaluate cation coordinate site-cation, and ion pair interactions in a Li6.5La3Zr1.75Te0.25O12 loaded polyethylene oxide-LiCF3SO3 matrix with varying ceramic concentrations. Further, the Trukhan model has been used to calculate diffusion coefficient, mobility, and charge carrier density to interpret relaxation parameters, conductivity, and FTIR results in the SPE samples. Finally, an ion migration model has been proposed based on the results obtained in experimental studies.

Forced migration in wartime: decision-making and trajectory

Russia’s full-scale war against Ukraine has caused a new wave of mass forced migrants. We conducted in-depth interviews with Ukrainians forced to relocate to Finland, to understand the differences in their migration decision-making and migration trajectories. The study showed that there are two models of forced migration. The first one is spontaneous and fast, where respondents didn’t consider the positive and negative consequences of migration. The second one includes a longer process of decision-making: respondents considered mainly the characteristics of their household and the conditions in the country of residence. They were motivated by the loss of security in Ukraine, and the inability to find sources of income or provide education for their children. But there were also factors that made decision-making more difficult and longer. Specifically, the need to be separated from the family, the lack of access to information about the support system abroad, and the high risks to life during the journey (caused by the danger of leaving the occupied territory and lack of other trajectories except to go to Finland through Russia).