Large Clusters Research Articles

GALEON: a comprehensive bioinformatic tool to analyse and visualize gene clusters in complete genomes.

Gene clusters, defined as a set of genes encoding functionally related proteins, are abundant in eukaryotic genomes. Despite the increasing availability of chromosome-level genomes, the comprehensive analysis of gene family evolution remains largely unexplored, particularly for large and highly dynamic gene families or those including very recent family members. These challenges stem from limitations in genome assembly contiguity, particularly in repetitive regions such as large gene clusters. Recent advancements in sequencing technology, such as long reads and chromatin contact mapping, hold promise in addressing these challenges. To facilitate the identification, analysis, and visualization of physically clustered gene family members within chromosome-level genomes, we introduce GALEON, a user-friendly bioinformatic tool. GALEON identifies gene clusters by studying the spatial distribution of pairwise physical distances among gene family members along with the genome-wide gene density. The pipeline also enables the simultaneous analysis and comparison of two gene families and allows the exploration of the relationship between physical and evolutionary distances. This tool offers a novel approach for studying the origin and evolution of gene families. GALEON is freely available from https://www.ub.edu/softevol/galeon and https://github.com/molevol-ub/galeon.

Host behaviour driven by awareness of infection risk amplifies the chance of superspreading events.

We demonstrate that heterogeneity in the perceived risks associated with infection within host populations amplifies chances of superspreading during the crucial early stages of epidemics. Under this behavioural model, individuals less concerned about dangers from infection are more likely to be infected and attend larger sized (riskier) events, where we assume event sizes remain unchanged. For directly transmitted diseases such as COVID-19, this leads to infections being introduced at rates above the population prevalence to those events most conducive to superspreading. We develop an interpretable, computational framework for evaluating within-event risks and derive a small-scale reproduction number measuring how the infections generated at an event depend on transmission heterogeneities and numbers of introductions. This generalizes previous frameworks and quantifies how event-scale patterns and population-level characteristics relate. As event duration and size grow, our reproduction number converges to the basic reproduction number. We illustrate that even moderate levels of heterogeneity in the perceived risks of infection substantially increase the likelihood of disproportionately large clusters of infections occurring at larger events, despite fixed overall disease prevalence. We show why collecting data linking host behaviour and event attendance is essential for accurately assessing the risks posed by invading pathogens in emerging stages of outbreaks.

Eksplorasi Tren Penelitian Cloud Accounting melalui Analisis Bibliometrik

This research aims to understand the mapping and development of studies on cloud accounting by examining various articles from journals and proceedings. The method used in this research is qualitative with bibliometric analysis using R Studio and Biblioshiny. The data used consists of 100 articles published between 1994-2022, extracted from the Scopus database. The results indicate that the research cluster on this topic is very broad, but there are two relatively large clusters related to big data and cloud computing. There is a diverse distribution of author countries, with China being the most active in publishing articles, followed by Jordan, Turkey, the United States, and Bangladesh. Although this research provides valuable insights into the trends in cloud accounting research, limitations in data and methodology should be considered. However, overall, this study provides a comprehensive view of the development of cloud accounting research over the studied period.

Explosion characteristics of AlH3 dust cloud with varying micron particle sizes

The explosion characteristics of AlH3 dust clouds with varying micron particle sizes are investigated in this paper. The explosion mechanism of AlH3 dust clouds is initially explored. The results indicate that the activation energy for hydrogen evolution shows an increasing trend with the AlH3 particle size, and both of these values are comparable to the 30 kJ/mol desorption energy of hydrogen from large AlH3 clusters. Due to the rapid dehydrogenation rate and small-size residual aluminum core, fine AlH3 particles exhibit a continuous gas-phase flame and fast propagation velocity. With increasing particle size, the lower dehydrogenation rate, reduced specific surface area, and higher volume heat capacity contribute to a higher level of incomplete reaction. Consequently, large micro-sized AlH3 particles display a discrete flame, slower flame velocity, and lower explosion pressure. The flame delamination phenomenon is not observed in our experiments on AlH3 dust clouds.

Distortions of the Hubble diagram: Line-of-sight signatures of local galaxy clusters

The Universe expansion rate is modulated around local inhomogeneities due to their gravitational potential. Velocity waves are then observed around galaxy clusters in the Hubble diagram. This paper studies them in a ∼738 Mpc-wide, 20483-particle cosmological simulation of our cosmic environment (a.k.a. CLONE: Constrained LOcal & Nesting Environment Simulation). For the first time, the simulation shows that velocity waves that arise in the lines of sight of the most massive dark matter halos agree with those observed in local galaxy velocity catalogs in the lines of sight of Coma and several other local (Abell) clusters. For the best-constrained clusters such as Virgo and Centaurus – that is, those closest to us – secondary waves caused by galaxy groups, further into the non-linear regime, also stand out. This match was not utterly expected given that before being evolved into a fully non-linear z = 0 state, assuming ΛCDM, CLONE initial conditions are constrained solely with linear theory, the power spectrum, and highly uncertain and sparse local peculiar velocities. Additionally, Gaussian fits to velocity wave envelopes show that wave properties are tightly tangled with cluster masses. This link is complex, though, and involves the environment and formation history of the clusters. A proposed metric, measuring the distance between the observed and several re-centred simulated lines of sight, waves included, is shown to be capable of providing a tight mass range estimate for massive local clusters. Using machine learning techniques to grasp more thoroughly the complex wave-mass relation, velocity waves could in the near future be used to provide additional and independent mass estimates from galaxy dynamics within large cluster radii.

Muscle satellite cells and fibro‐adipogenic progenitors from muscle contractures of children with cerebral palsy have impaired regenerative capacity

AbstractAimTo evaluate the mechanosensitivity of muscle satellite cells (MuSCs) and fibro‐adipogenic progenitors (FAPs) in cerebral palsy (CP) and the efficacy of the drug verteporfin in restoring cells' regenerative capacity.MethodMuscle biopsies were collected from six children with CP and six typically developing children. MuSCs and FAPs were isolated and plated on collagen‐coated polyacrylamide gels at stiffnesses of 0.2 kPa, 8 kPa, and 25 kPa. Cells were treated with verteporfin to block mechanosensing or with dimethyl sulfoxide as a negative control. MuSC differentiation and FAP activation into myofibroblasts were measured using immunofluorescence staining.ResultsSurprisingly, MuSC differentiation was not affected by stiffness; however, stiff substrates resulted in large myonuclear clustering. Across all stiffnesses, MuSCs from children with CP had less differentiation than those of their typically developing counterparts. FAP activation into myofibroblasts was significantly higher in children with CP than their typically developing peers, but was not affected by stiffness. Verteporfin did not affect differentiation or activation in either cell population, but slightly decreased myonuclear clustering on stiff substrates.InterpretationCells from children with CP were less regenerative and more fibrotic compared to those of their typically developing counterparts, with MuSCs being sensitive to increases in stiffness. Therefore, the mechanosensitivity of MuSCs and FAPs may represent a new target to improve differentiation and activation in CP muscle.

AMICO galaxy clusters in KiDS-DR3: Measuring the splashback radius from weak gravitational lensing

Context. Weak gravitational lensing offers a powerful method to investigate the projected matter density distribution within galaxy clusters, granting crucial insights into the broader landscape of dark matter on cluster scales. Aims. In this study, we make use of the large photometric galaxy cluster data set derived from the publicly available Third Data Release of the Kilo-Degree Survey, along with the associated shear signal. Our primary objective is to model the peculiar sharp transition in the cluster profile slope, that is what is commonly referred to as the splashback radius. The data set under scrutiny includes 6962 galaxy clusters, selected by AMICO (an optimised detection algorithm of galaxy clusters) on the KiDS-DR3 data, in the redshift range of 0.1 ≤ z ≤ 0.6, all observed at a signal-to-noise ratio greater than 3.5. Methods. Employing a comprehensive Bayesian analysis, we model the stacked excess surface mass density distribution of the clusters. We adopt a model from recent results on numerical simulations that capture the dynamics of both orbiting and infalling materials, separated by the region where the density profile slope undergoes a pronounced deepening. Results. We find that the adopted profile successfully characterizes the cluster masses, consistent with previous works, and models the deepening of the slope of the density profiles measured with weak-lensing data up to the outskirts. Moreover, we measure the splashback radius of galaxy clusters and show that its value is close to the radius within which the enclosed overdensity is 200 times the mean matter density of the Universe, while theoretical models predict a larger value consistent with a low accretion rate. This points to a potential bias of optically selected clusters preferentially characterized by a high density at small scales compared to a pure mass-selected cluster sample.

Ionization of small atmospheric acid–base clusters and its prospective role in seeding the growth of aqueous clusters

In the present study, we have examined the ionization of a set of small atmospheric acid–base clusters. The calculated ionization energy (IE) ranges from ∼660 kJ mol−1 to ∼1120 kJ mol−1, with clusters consisting of just the bases yielding the smallest IEs, while those of the acids yield the largest. For neutral clusters that form most readily, the IEs range from ∼790 kJ mol−1 to ∼880 kJ mol−1. These values are generally smaller than those of other chemicals with significant atmospheric presence. Thus, the radical cations of the acid–base clusters are not likely to ionize other atmospheric species. Charged atmospheric species have been hypothesized to facilitate the growth of large clusters. We have carried out a case study of the sequential hydration of an acid–base cluster and compared our results with previous studies of forming pure water clusters. The neutral acid–base cluster binds water more strongly than pure water clusters. Further strengthening of the binding can be seen for the radical cationic acid–base cluster. The resulting acid–base–water clusters may further represent a source of H3O+, which may proceed to facilitate cloud formation.

Effectiveness, Safety, and Acceptability of Primaquine Mass Drug Administration in Low-Endemicity Areas in Southern Thailand: Proof-of-Concept Study.

A challenge in achieving the malaria-elimination target in the Greater Mekong Subregion, including Thailand, is the predominance of Plasmodium vivax malaria, which has shown extreme resilience to control measures. This proof-of-concept study aimed to provide evidence for implementing primaquine mass drug administration (pMDA) as a strategy for P. vivax elimination in low-endemicity settings. The study employed a mixed-methods trial to thoroughly evaluate the effectiveness, safety, acceptability, and community engagement of pMDA. The quantitative part was designed as a 2-period cluster-crossover randomized controlled trial. The intervention was pMDA augmented to the national prevention and control standards with directly observed treatment (DOT) by village health volunteers. The qualitative part employed in-depth interviews and brainstorming discussions. The study involved 7 clusters in 2 districts of 2 southern provinces in Thailand with persistently low P. vivax transmission. In the quantitative part, 5 cross-sectional blood surveys were conducted in both the pMDA and control groups before and 3 months after pMDA. The effectiveness of pMDA was determined by comparing the proportions of P. vivax infections per 1000 population between the 2 groups, with a multilevel zero-inflated negative binomial model adjusted for cluster and time as covariates and the interaction. The safety data comprised adverse events after drug administration. Thematic content analysis was used to assess the acceptability and engagement of stakeholders. In the pre-pMDA period, the proportions of P. vivax infections in the pMDA (n=1536) and control (n=1577) groups were 13.0 (95% CI 8.2-20.4) and 12.0 (95% CI 7.5-19.1), respectively. At month 3 post-pMDA, these proportions in the pMDA (n=1430) and control (n=1420) groups were 8.4 (95% CI 4.6-15.1) and 5.6 (95% CI 2.6-11.5), respectively. No statistically significant differences were found between the groups. The number of malaria cases reduced in all clusters in both groups, and thus, the impact of pMDA was inconclusive. There were no major safety concerns. Acceptance among the study participants and public health care providers at local and national levels was high, and they believed that pMDA had boosted awareness in the community. pMDA was associated with high adherence, safety, and tolerability, but it may not significantly impact P. vivax transmission. As this was a proof-of-concept study, we decided not to scale up the intervention with larger clusters and samples. An alternative approach involving a targeted primaquine treatment strategy with primaquine and DOT is currently being implemented. We experienced success regarding effective health care workforces at point-of-care centers, effective collaborations in the community, and commitment from authorities at local and national levels. Our efforts boosted the acceptability of the malaria-elimination initiative. Community engagement is recommended to achieve elimination targets. Thai Clinical Trials Registry TCTR20190806004; https://www.thaiclinicaltrials.org/show/TCTR20190806004.

The Origin of Young Stellar Populations in NGC 1783: Accretion of External Stars

The presence of young stellar populations in the Large Magellanic Cloud cluster NGC 1783 has caught significant attention, with suggestions ranging from it being a genuine secondary stellar generation to a population of blue straggler stars or simply contamination from background stars. Thanks to multiepoch observations with the Hubble Space Telescope, proper motions for stars within the field of NGC 1783 have been derived, thus allowing accurate cluster membership determination. Here, we report that the younger stars within NGC 1783 indeed belong to the cluster and their spatial distribution is more extended compared to the bulk of the older stellar population, consistent with previous studies. Through N-body simulations, we demonstrate that the observed characteristics of the younger stars cannot be explained solely by blue straggler stars in the context of the isolated dynamical evolution of NGC 1783. Instead, accretion of the external, low-mass stellar system can better account for both the inverse spatial concentration and the radial velocity isotropy of the younger stars. We propose that NGC 1783 may have accreted external stars from low-mass stellar systems, resulting in a mixture of external younger stars and blue straggler stars from the older bulk population, thereby accounting for the characteristics of the younger sequence.

Is Management and Organizational Studies divided into (micro-)tribes?

Many claims have been made in the past that Management and Organization Studies (MOS) is becoming increasingly fragmented, and that this fragmentation is causing it to drift into self-reference and irrelevance. Despite the weight of this claim, it has not yet been subjected to a systematic empirical test. This paper addresses this research gap using the tribalization approach and diachronic co-citation analyses. Based on 22,430 papers published in 14 MOS journals between 1980 and 2019, we calculate local and global centrality measures and the flow of cited articles between co-citation communities over time. In addition, we use a node-removal strategy to test whether only ritualized citations ensure MOS cohesion. Rather than tribalization, our results suggest a center–periphery structure. Furthermore, more peripheral papers are integrated into the central co-citation communities, but the lion's share of the flow of cited papers occurs over time to only a small number of large clusters. An increase of fragmentation and crowding-out of smaller clusters in MOS in seen in the polycentrically organized core 2014–2019.

Structural characteristics and spatiotemporal changes of a reticular river network based on complex network theory

eticular river networks, characterized by a dense pattern of rivers and loop structures, are primarily found in lower river delta plains and are being modified due to rapid population growth and urbanization. This change impacts the distribution of water resources and could result in more frequent and severe floods. Therefore, accurately characterizing the structure of river networks is crucial. In this study, the structure and its changes of a typical plain reticular river network in the Lixia River hinterland area (LRHA), China, were evaluated in the 1960s, 1970s, 1980s, 2009, and 2016 using complex network theory tools at global and local scales. First, we constructed a complex network model by generalizing river sources, outlets, and confluences as nodes and channels as edges. By comparing with the equivalent random networks, it is found that the river networks of LRHA have large clustering coefficients and short characteristic path lengths. These characteristics classify it as a small-world network within complex networks, which is notably efficient for water and material transportation. Second, at the global scale, the global efficiency in complex network theory considers the interconnectivity between nodes and assesses the potential paths between them, effectively reflecting the connectivity status of the river network. At the local scale, the betweenness centrality of a complex network can reflect the control ability of water and material transportation at river nodes. After the 1970s, constructing several new mainstem rivers gradually shifted nodes with high betweenness centrality towards the north–south flowing rivers. In addition, we used Moran’s I to quantify the spatial clustering of the network’s indicators and found that degree and betweenness centrality exhibited higher spatial clustering, with mean Moran’s I values of 0.398 and 0.300, respectively. Finally, we compared the structure of river networks in urban versus rural areas and the mainstem versus tributary streams. We found that urban river networks and mainstem rivers exhibit a higher degree of betweenness centrality, resulting in a greater capacity to regulate water and material cycles within the river network. According to the research findings, complex network theory has been proven to effectively evaluate the structure of reticular river networks at various scales. It enhances our comprehension of the river network’s structure and assists managers in gaining a deeper understanding of how the river network structure influences the distribution of water resources.

Discovery of runs-of-homozygosity diplotype clusters and their associations with diseases in UK Biobank.

Runs-of-homozygosity (ROH) segments, contiguous homozygous regions in a genome were traditionally linked to families and inbred populations. However, a growing literature suggests that ROHs are ubiquitous in outbred populations. Still, most existing genetic studies of ROH in populations are limited to aggregated ROH content across the genome, which does not offer the resolution for mapping causal loci. This limitation is mainly due to a lack of methods for the efficient identification of shared ROH diplotypes. Here, we present a new method, ROH-DICE (runs-of-homozygous diplotype cluster enumerator), to find large ROH diplotype clusters, sufficiently long ROHs shared by a sufficient number of individuals, in large cohorts. ROH-DICE identified over 1 million ROH diplotypes that span over 100 single nucleotide polymorphisms (SNPs) and are shared by more than 100 UK Biobank participants. Moreover, we found significant associations of clustered ROH diplotypes across the genome with various self-reported diseases, with the strongest associations found between the extended human leukocyte antigen (HLA) region and autoimmune disorders. We found an association between a diplotype covering the homeostatic iron regulator (HFE) gene and hemochromatosis, even though the well-known causal SNP was not directly genotyped or imputed. Using a genome-wide scan, we identified a putative association between carriers of an ROH diplotype in chromosome 4 and an increase in mortality among COVID-19 patients (p-value = 1.82 × 10-11). In summary, our ROH-DICE method, by calling out large ROH diplotypes in a large outbred population, enables further population genetics into the demographic history of large populations. More importantly, our method enables a new genome-wide mapping approach for finding disease-causing loci with multi-marker recessive effects at a population scale.

Tracking Prenucleation Molecular Clustering of Salicylamide in Organic Solvents.

Crystal nucleation shapes the structure and product size distribution of solid-state pharmaceuticals and is seeded by early-stage molecular self-assemblies formed in host solution. Here, molecular clustering of salicylamide in ethyl acetate, methanol, and acetonitrile was investigated using photon correlation spectroscopy. Cluster size steadily increased over 3 days and with concentration across the range from undersaturated to supersaturated solutions. Solute concentration normalized by solubility provided more sensitive characterization of molecular-level conditions than concentration alone. In saturated solution, cluster size is independent of solvent, while at equal supersaturation, solvent-dependent cluster size increases as methanol < acetonitrile < ethyl acetate, commensurate with increasing nucleation propensity. In ethyl acetate, with largest prenucleation clusters, the driving force required for nucleation is lowest, compared to methanol with smallest clusters and highest driving force. To understand solvent-solute effects, we performed IR spectroscopy supported by molecular simulations. We observe solute-solvent interaction weakening in the same order: methanol < acetonitrile < ethyl acetate, quantifying the weaker solvent-solute interactions that permit the formation of larger prenucleation clusters. Our results support the hypothesis that nucleation is easier in weaker solvents because weak solute-solvent interactions favor growth of large clusters, as opposed to relying solely on ease of desolvation.

Simulation of calcium carbonate nucleation processes in confined C-S-H nanopores with different calcium-silicon ratios

Carbonation curing technology plays an important role in carbon cycling and improving the properties of cement-based materials, while the nucleation and growth mechanism of calcium carbonate (CaCO3) is still unclear. Based on molecular dynamics simulation, the formation process and nucleation mechanism of CaCO3 in confined C-S-H nanopores with different calcium-silicon ratios were studied. The results show that the clustering behavior of CaCO3 in C-S-H nanopores filled with saturated CaCO3 solution can be divided into three phases, rapid agglomeration stage, slow cluster stage, and stable cluster stage. The aggregation is mainly dependent on ionic bonding for nucleation growth and is consistent with the prenucleation mechanism. The Ca/Si ratio of C-S-H has a direct influence on the clustering of CaCO3. The anchoring mechanism of CaCO3 clusters is determined by ionic bonds and hydrogen bonds, and large clusters are preferentially adsorbed at the C-S-H interface through ionic bonds. The Ca/Si ratio of 1.5 can provide more nucleation sites by ionic bonds and hydrogen bonds for the formation of CaCO3, which is more conducive to the growth of clusters. And the calcium source from C-S-H in cluster bodies can be as high as 33 %. This study helps to understand the early formation process of CaCO3 in cement-based materials and lays a theoretical foundation for the development of carbonization curing technology.

Effect of network structure on the accuracy of resilience dimension reduction

Dimension reduction is an effective method for system’s resilience analysis. In this paper, we investigate the effect of network structure on the accuracy of resilience dimension reduction. First, we introduce the resilience dimension reduction method and define the evaluation indicator of the resilience dimension reduction method. Then, by adjusting node connections, preferential connection mechanisms, and connection probabilities, we generate artificial networks, small-world networks and social networks with tunable assortativity coefficients, average clustering coefficients, and modularities, respectively. Experimental results for the gene regulatory dynamics show that the network structures with positive assortativity, large clustering coefficient, and significant community can enhance the accuracy of resilience dimension reduction. The result of this paper indicates that optimizing network structure can enhance the accuracy of resilience dimension reduction, which is of great significance for system resilience analysis and provides a new perspective and theoretical basis for selecting dimension reduction methods in system resilience analysis.

A unique Fe-based soft magnetic alloy and its magnetic softening mechanism

Fe-based amorphous alloys with good glass-forming ability (GFA), superior soft magnetic properties, low cost, and a wide heat treatment window have long been pursued in the field of soft magnetic materials due to their importance for mass production and broad applications. In the present study, by strategically adjusting the composition of a low-cost Fe-Si-B-P-Cu-C alloy, we achieved a saturation magnetization (Ms) of approximately 186 emu/g and a coercivity (Hc) of about 6 A/m for the Fe82.5 alloy with a good GFA. Specifically, the limited Cu content and suitable contents of metalloid elements played pivotal roles in enhancing the nuclei barrier and stabilizing the amorphous matrix. This, in turn, facilitated the formation of a finely uniform nanocrystalline structure dispersed within the amorphous matrix, enhancing soft magnetic properties during annealing. Notably, this magnetic softening behavior occurred at a lower heating rate. Structural characterizations revealed that a transient metalloid-rich shell and a stable amorphous matrix contributed to the slow growth of the α-Fe (Si) during prolonged isothermal annealing. This is in contrast to the agglomeration of small nanograins into larger clusters at high heating rates, which enhances the versatility and potential applicability of the alloy. The successful development of this novel nanocrystalline alloy offers promising guidance for addressing the challenges associated with the mass production of soft magnetic materials.

Towards including super-sample covariance in the unbinned likelihood for cluster abundance cosmology

ABSTRACT The measurement of the abundance of galaxy clusters in the Universe is a sensitive probe of cosmology, which depends on both the expansion history of the Universe and the growth of structure. Density fluctuations across the finite survey volume add noise to this measurement, this is often referred to as super-sample covariance (SSC). For an unbinned cluster analysis, such noise has not been included in the cluster likelihood, since the effect of SSC was small compared to the Poisson shot-noise for samples of a few hundred clusters. For upcoming large cluster surveys such as the Rubin LSST, which will deliver catalogues of tens of thousands of clusters, this effect will no longer be negligible. In this paper, we propose a new hybrid likelihood based on the Gauss-Poisson Compound model (GPC), by using infinitesimal mass bins and standard redshift bins. This likelihood has the advantages of an unbinned Poisson likelihood while successfully incorporating the effects of SSC. Using a simulated dark matter halo catalogue, we find that the hybrid likelihood, accounting for both Poisson noise and SSC, increases the dispersion of the parameter posteriors by 20 per cent when using 100 000 clusters compared to the standard unbinned likelihood, based on Poisson statistics only.

Grain boundary migration and mechanical properties altering in Fe – 10Ni – 20Cr alloy under irradiation

Mechanisms of ∑5(210)[001] and ∑5(310)[001] symmetrical tilled grain boundaries migration in bicrystall Fe – 10Ni – 20Cr samples under irradiation were investigated by means of molecular dynamics. The density of radiation defects grows quite quickly up to a dose of ~0.02 dpa and then reaches saturation. This is due to balancing of the radiation defects generation and annihilation rates. It is shown that at the early stage of irradiation, grain boundaries began to deviate stochastically from their initial positions due to interaction with cascades of atomic displacements and absorption of structural defects. During irradiation, the grain boundary region thickened and became rough. With an increase in the radiation dose, size of the clusters of point defects (tetrahedrons of stacking faults and dislocation loops) increased. Interaction with large clusters of point defects led to the formation of bends on initially flat surfaces of grain boundaries. At small distances between the boundaries, the high driving force between the curved surfaces of grain boundaries significantly increased the rates of their approach. The average migration rates of grain boundaries before their direct interaction with each other were approximately 0.8 m/s. As a result of their approach, the grain boundaries were annihilated, the potential energy of the sample decreased abruptly, and the grains merged. The annihilation of grain boundaries ∑5(310)[001] required twice the radiation dose compared to the grain boundary ∑5(210)[001]. The direct interaction of grain boundaries with each other abruptly increased the velocity of their migration due to the emergence of a driving force from the curved sections of the grain boundary surfaces. Influence of the radiation dose on deformation behavior features of the samples under uniaxial strains was studied. With an increase in the radiation dose, the elastic limit decreased rapidly and reached saturation at an irradiation dose of ~0.01 dpa.

Exploring asphaltene aggregation: Model systems based on toluene-heptane mixtures

This work evaluates how chemical characteristics, such as polarity and aromaticity, can affect asphaltene aggregation. The asphaltene fraction was extracted from two different crude oils by precipitation in n-heptane, and these extracted asphaltenes were named A and B. Based on infrared spectroscopy (FTIR) and nuclear magnetic resonance (NMR) analyses, we found that asphaltenes B present greater aromaticity. According to X-ray photoelectron spectroscopy (XPS), asphaltene B showed higher heteroatom content. Model systems based on toluene/n-heptane/asphaltene (0.05 g/L) were prepared to evaluate the aggregation/precipitation of asphaltenes. Dynamic light scattering (DLS) analysis of aggregation kinetics revealed that aromatic asphaltenes with higher heteroatom content tend to form larger aggregates. Moreover, hydroxyl content exhibits a greater impact on aggregation compared to diffusivity. Furthermore, once the aggregates reach a critical size, the suspension stability is reduced, and the aggregates sediment. The atomic force microscopy (AFM) and DLS results revealed a wide range of particle size distribution. The larger clusters likely consisted of smaller aggregates that adhered together. Still, we highlight that the sizes of these aggregates determined by AFM are not directly comparable to the measurements obtained from DLS. The drying of the samples for the AFM measurements probably affects the asphaltene aggregation process. For this reason, the results obtained from the AFM and DLS techniques are not comparable.