Heterogeneous Structure Research Articles

Direct observation of ultrafast cluster dynamics in supercritical carbon dioxide using X-ray Photon Correlation Spectroscopy

Supercritical fluids exhibit distinct thermodynamic and transport properties, making them of particular interest for a wide range of scientific and engineering applications. These anomalous properties emerge from structural heterogeneities due to the formation of molecular clusters at conditions above the critical point. While the static behavior of these clusters and their effects on the thermodynamic response functions have been recognized, the relation between the ultrafast cluster dynamics and transport properties remains elusive. By measuring the intermediate scattering function in carbon dioxide at conditions near the critical point with X-ray photon correlation spectroscopy, we directly capture the cross-over dynamics between 4 and 13 picoseconds, revealing the transition between ballistic and diffusive motion. Complementary analysis using large-scale molecular dynamics simulations reveals that this behavior arises from collisions between unbound molecules and clusters. This study provides direct evidence of the ultrafast momentum exchange between clusters, which has significant impact on transport properties, solvation processes, and reaction kinetics in supercritical fluids.

NMR-Based Investigation of Pore–Fracture Structure Heterogeneity in Deep Coals of Different Macrolithotypes in the Daning-Jixian Block, Ordos Basin

Deep coalbed methane (CBM) demonstrates significant production potential, and a fervent exploration and development boom is currently underway in China. The permeability of coal reservoirs is heavily influenced by pore–fracture structure heterogeneity. Some researches have been conducted on deep coals’ pore–fracture structure; however, these studies mostly consider coal as a homogeneous material, neglecting the heterogeneity of the macrolithotypes within the coal. In this study, 33 deep coals with burial depths of more than 2000 m were obtained from the Daning-Jixian block of the Ordos Basin, covering all macrolithotypes: bright coal (BC), semi-bright coal (SBC), semi-dull coal (SDC), and dull coal (DC). These samples were subjected to three sets of NMR tests in dry, fully saturated, and irreducible water conditions, with the pore–fracture structure characteristics being analyzed. The results demonstrate that the sampled deep coals’ pore–fracture structure is highly heterogeneous, with transitional pores being dominant, followed by mesopores, “macropores and fractures”, and micropores. The NMR T2C ranges from 0.61 to 2.44 ms, with an average of 1.19 ms; a higher T2C value indicates more developed micropores. The ranges for producible water porosity (φpr) and producible water saturation (Spr) are 0.31–7.24% (avg. 2.42%) and 6.97–71.47% (avg. 31.06%), respectively. Both of them exhibit a high positive correlation with the total volumes of “macropores and fractures” and mesopores. Compared to SDC and DC, the BC and SBC, especially the former, overall contain more “macropores and fractures” and mesopores, fewer transitional pores and micropores, and higher φpr and Spr. These findings suggest that regions with abundant BC and SBC should be prioritized during deep CBM exploration and production due to the inherently superior permeability and gas extraction potential of BC and SBC, and these coals are likely to require less intensive stimulation to achieve higher recovery rates and could provide more sustainable gas production over time.

Active doping controls the mode of failure in dense colloidal gels

Mechanical properties of disordered materials are governed by their underlying free energy landscape. In contrast to external fields, embedding a small fraction of active particles within a disordered material generates nonequilibrium internal fields, which can help to circumvent kinetic barriers and modulate the free energy landscape. In this work, we investigate through computer simulations how the activity of active particles alters the mechanical response of deeply annealed polydisperse colloidal gels. We show that the "swim force" generated by the embedded active particles is responsible for determining the mode of mechanical failure, i.e., brittle vs. ductile. We find, and theoretically justify, that at a critical swim force the mechanical properties of the gel decrease abruptly, signaling a change in the mode of mechanical failure. The weakening of the elastic modulus above the critical swim force results from the change in gel porosity and distribution of attractive forces among gel particles, while below the critical swim force, the ductility enhancement is caused by an increase of gel structural disorder. Above the critical swim force, the gel develops a pronounced heterogeneous structure characterized by multiple pore spaces, and the mechanical response is controlled by dynamical heterogeneities. We contrast these results with those of a simulated monodisperse gel that exhibits a nonmonotonic trend of ductility modulation with increasing swim force, revealing a complex interplay between the gel energy landscape and embedded activity.

Compaction‐Driven Convection in the Growing Inner Core

AbstractThe Earth's inner core (IC) is known to exhibit heterogeneous structures with their origins still unknown. From the onset of nucleation, the IC can grow via sedimentation and compaction of iron crystals freezing out from the fluid outer core. Previous studies of IC growth have shown entrapment of fluid within the solid matrix, and unstable density profiles in 1D can appear depending on the efficiency of fluid percolation. In this study, we perform simulations of IC growth in spherical geometries (assuming axisymmetry). We find that it is possible for the IC to develop large‐scale convective flows under certain conditions and, in some instances, produce small‐scale heterogeneites close to the IC boundary. Assuming representative values for the physical properties of the Earth's IC, we show that it is possible for the IC to exhibit compaction‐driven convection today.

Teleseismic evidence for structural heterogeneity in East Japan forearc from seafloor S-net data

We measure and analyze 4381 P-wave and 4307 S-wave arrival times of 48 teleseismic events recorded at 150 stations of a permanent seafloor seismic network (S-net) installed in the outer-rise and forearc region off East Japan. The obtained relative travel-time residuals amounting to ~3 s at the S-net stations are generally negative on the incoming Pacific and Philippine Sea plates and positive on the continental Okhotsk plate, which reflect high and low seismic velocities, respectively. This pattern is generally consistent with previous results on the seismic velocity structure of the crust and upper mantle beneath the East Japan forearc and the outer-rise area. Large early arrivals (~2.0 s) appear in the southern part of the S-net for the teleseismic events in the southwestern direction, which are mainly due to southwestward steepening of the subducting Pacific slab beneath Kanto. In the study region, the Pacific slab is the most significant anomaly with a thickness of ~90 km and a seismic velocity of 5–6 % higher than that of the surrounding mantle. Early arrivals (~1.5 s) also appear at the S-net stations off South Hokkaido, which are caused by northwestward steepening of the Pacific slab beneath the Tohoku-Hokkaido junction area. These results shed new light on the structural heterogeneity and subduction dynamics of the East Japan arc.

Hierarchical microstructure design to tune the mechanical and corrosion behaviors of a marine structural steel

Marine structural steel with notable strength and ductility is considered as one of the promising construction materials for various offshore applications. However, the harsh marine environment causes a series of issues, e.g., deteriorating ductility and impact toughness, degrading corrosion resistance and inducing stress corrosion cracking. In this work, we propose a novel approach to address these issues by introducing heterogeneous structure and tailoring carbide precipitation in a step quenched and tempered marine structural steel. The step quenched and tempered process not only leads to a heterogeneous structure containing ferrite and tempered martensite zones but also obtains abundant nanoscale VC carbides, resulting in M23C6 refinement. This heterogeneity triggers additional strengthening and strain hardening mechanisms, thereby enhancing strength and ductility. Furthermore, the heterostructure and M23C6 refinement effectively inhibit the microcrack initiation and the formation of galvanic cells during Charpy impact test and electrochemical experiment, respectively, thus improving impact toughness and stress corrosion cracking resistance. This study proposes a hierarchical microstructure design to developing high-performance marine structural steel, which offers an effective avenue for addressing the conflicts between mechanical performance and corrosion resistance.

Box-shaped necklace-like Fe3O4/MoS2-CNFs composite nanofibers with confinement effect enhancing sodium storage performance

A nanofiber necklace with a box-shaped structure has been designed. The box-shaped template can introduce other transition metal compounds, effectively compensating for the intrinsic defects of electrode materials. α-Fe2O3 nano cubes as the template mix with PAN to get α-Fe2O3/PAN. And then the α-Fe2O3 nano cubes calcine to form Fe3O4 with more valence state under high temperature, which get the box-shape necklace-like structure Fe3O4-CNFs. The confined space has formed by high concentrated HCl etching, the box-shaped necklace-like Fe3O4/MoS2 carbon nanofibers (BN Fe3O4/MoS2-CNFs) anode material is obtained by hydrothermal method of confining growth of MoS2 nanosheets. The mixed valence state of Fe3O4 (Fe3+/Fe2+) can effectively improve the conductivity of MoS2 nanosheets. The box-shape necklace structure constructed by α-Fe2O3 nanocube has mesoporous structure and confined space, which can alleviate the volume effect of electrode material. When the electrode material is applied to the SIBs, the reversible capacity is 354 mA h g−1 after 500 cycles at 0.5 A/g, and the specific capacity of 131.5 mA h g−1 can be maintained at 8 A/g. On the one hand, the heterogeneous structure in the confined space alleviates the volume effect of the material, thereby improving the long cycle performance, on the other hand, it effectively enhances the electrical conductivity and increases more lithium/sodium storage sites.

Firm commonality, bank connectedness and portfolio riskiness

We propose a new connectedness measure that addresses heterogeneous multiple borrowing loan structure among banks. Using confidential data from over 44 million commercial loans from Turkish banks during 2007–2016, we construct a bank network that emerges from the banks lending to common firms. While the related literature mostly focuses on systemic risk, our framework allows us to empirically study banks’ loan portfolio riskiness. First, we document that banks’ portfolio riskiness decreases with connectedness, even when controlling for the impacts of loan size and multiple borrowing. Second, we find that the probability of loan default is higher for highly connected banks compared to weakly connected ones. These findings suggest that highly centralized banks seem to manage their overall portfolio risk better.

Sequential Multi-Scale Modeling Using an Artificial Neural Network-Based Surrogate Material Model for Predicting the Mechanical Behavior of a Li-Ion Pouch Cell Under Abuse Conditions

To analyze the safety behavior of electric vehicles, mechanical simulation models of their battery cells are essential. To ensure computational efficiency, the heterogeneous cell structure is represented by homogenized material models. The required parameters are calibrated against several characteristic cell experiments. As a result, it is hardly possible to describe the behavior of the individual battery components, which reduces the level of detail. In this work, a new data-driven material model is presented, which not only provides the homogenized behavior but also information about the components. For this purpose, a representative volume element (RVE) of the cell structure is created. To determine the constitutive material models of the individual components, different characterization tests are performed. A novel method for carrying out single-layer compression tests is presented for the characterization in the thickness direction. The parameterized RVE is subjected to a large number of load cases using first-order homogenization theory. This data basis is used to train an artificial neural network (ANN), which is then implemented in commercial FEA software LS-DYNA R9.3.1 and is thus available as a material model. This novel data-driven material model not only provides the stress–strain relationship, but also outputs information about the condition of the components, such as the thinning of the separator. The material model is validated against two characteristic cell experiments. A three-point-bending test and an indentation test of the cell is used for this purpose. Finally, the influence of the architecture of the neural network on the computational effort is discussed.

Collective effect of self-learning and social learning on language dynamics: a naming game approach in social networks.

Linguistic rules form the cornerstone of human communication, enabling people to understand and interact with one another effectively. However, there are always irregular exceptions to regular rules, with one of the most notable being the past tense of verbs in English. In this work, a naming game approach is developed to investigate the collective effect of social behaviours on language dynamics, which encompasses social learning, self-learning with preference and forgetting due to memory constraints. Two features that pertain to individuals' influential ability and affinity are introduced to assess an individual's role of social influence and discount the information they communicate in the Bayesian inference-based social learning model. Our findings suggest that network heterogeneity and community structure significantly impact language dynamics, as evidenced in synthetic and real-world networks. Furthermore, self-learning significantly enhances the process of language regularization, while forgetting has a relatively minor impact. The results highlight the substantial influence of network structure and social behaviours on the transition of opinions, from consensus to polarization, demonstrating its importance in language dynamics. This work sheds new light on how individual learners adopt language rules through the lenses of complexity science and decision science, advancing our understanding of language dynamics.

Does family culture hamper corporate deceptive green behavior decision-making?

Different categories of cultural traits have acknowledged that culture matters for a multiplicity of decisions made regarding economic outcomes. In response to the increasing awareness of cultural traits and their relationship to corporate sustainable behavior, this paper focused on one specific aspect of the relevance of culture: the association of family culture to green behaviors. This paper explored the nexus between family culture, the deceptive behavior of greenwashing, and firm performance in China, which provided original evidence that family culture firms have a significantly lower likelihood in participating in deceptive green behaviors as measured by greenwashing. By collecting the listed Chinese firms during 2011 to 2021, we estimated empirical models and drew a variety of conclusions accordingly. First, family culture firms have a negative and significant impact on greenwashing behaviors, leading to a decline in deceptive green production decision-making. Second, we further provided mechanisms which hamper family firms’ greenwashing behaviors into two perspectives: financial constraint and agency cost between shareholders and family managers. We recognized that financial constraints motivate family culture firms to greenwash, whereas the low agency cost related to family culture discourages family firms from greenwashing decision-making. Third, we provide very rich dimensions in discussion of heterogeneous effects. Specifically, within the internal family culture structure heterogeneities, family managers without overseas backgrounds, no generational or descendant involvement, and high family-controlled firms are even less involved in greenwashing decision-making. Moreover, with respect to external heterogeneities, family culture in pollution-intensive industries, highly regulated environmental firms, and Confucian social culture intensive regions, can significantly reduce greenwashing behaviors.

High-Performance Photocatalytic Degradation of Aromatic Compounds Using Co-MOF-74/ZnIn2S4/CNF Aerogels with Enhanced Charge Separation and Photothermal Synergy

Although photocatalytic degradation using semiconductor materials has been widely studied, there are still challenges such as slow reaction kinetics and complex synthesis process. To overcome these problems, Co-MOF-74@ZnIn2S4@CNF composite aerogel was developed in this study, which significantly improved the photocatalytic efficiency. This novel structure integrates three key functions: 1) the one-dimensional Co-MOF-74-NTs nanotube enhances carrier mobility based on its high aspect ratio; 2) the Co-MOF-74@ZnIn2S4 heterojunction facilitates charge separation for efficient generation of reactive oxygen species; 3) the porous cellulose aerogel promotes the adsorption of substrates and improves the photothermal effect due to its intrinsic thermal conductivity and insulation, and will facilitate effective charge separation. This combined functionality resulted in highly efficient degradation of paraxylene, with 91.6% of degradation efficiency and 68.79% of mineralization rate within 3h under simulated sunlight. Several experiments demonstrated that the Co-MOF-74@ZnIn2S4@CNF aerogel possessed strong stability and effective catalytic properties for a variety of aromatic compounds. This study introduces a new photocatalytic system combining heterogeneous structure and photothermal effect to enhance charge transfer, providing an efficient solution for photothermal-assisted Aromatic Compounds degradation.

Heterogeneous structure formation of Mg alloy during direct laser deposition with dissimilar alloy

Heterogeneous structure formation of Mg alloy during direct laser deposition with dissimilar alloy

Oxytocin in Human Social Network Cooperation.

Human society is organized in structured social networks upon which large-scale cooperation among genetically unrelated individuals is favored and persists. Such large-scale cooperation is crucial for the success of the human species but also one of the most puzzling challenges. Recent work in social and behavioral neuroscience has linked human cooperation to oxytocin, an evolutionarily ancient and structurally preserved hypothalamic neuropeptide. This review aims to elucidate how oxytocin promotes nonkin cooperation in social networks by reviewing its effects at three distinct levels: individual cooperation, the formation of interpersonal relationships, and the establishment of heterogeneous network structures. We propose oxytocin as a proximate mechanism for fostering large-scale cooperation in human societies. Specifically, oxytocin plays an important role in facilitating network-wide cooperation in human societies by 1) increasing individual cooperation, mitigating noncooperation motives, and facilitating the enforcement of cooperative norms; 2) fostering interpersonal bonding and synchronization; and 3) facilitating the formation of heterogeneous network structures.

Female mice exhibit similar long-term plasticity and microglial properties between the dorsal and ventral hippocampal poles

The hippocampus is a heterogenous structure that exhibits functional segregation along its longitudinal axis. We recently showed that in male mice, microglia, the brain’s resident immune cells, differ between the dorsal (DH) and ventral (VH) hippocampus, impacting long-term potentiation (LTP) mainly through the CX3CL1-CX3CR1 signaling. Here, we assessed the specific features of the hippocampal poles in female mice, demonstrating a similar LTP amplitude in VH and DH in both control and Cx3cr1 knock-out mice. In addition, the expression levels of Cx3cr1 and Cx3cl1 mRNA do not differ between the two poles in control mice. These data support the critical role of the CX3CL1-CX3CR1 signaling in setting the physiological amount of plasticity, equally between poles in females. Although BDNF is higher in DH compared to VH, the expression levels of inflammatory markers involved in plasticity and of phagocytosis markers in microglia are comparable between the two poles. In accordance, microglia soma and arborization area/perimeter, and microglial ultrastructure are similar across regions, with the exception of microglial density, cells arborization solidity and circularity that are higher in DH. Understanding the molecular processes underlying microglial sex differences and their potential implications for plasticity in specific brain regions is of major importance in physiological and pathological conditions.

From micropores to mechanical strength: Fabrication and characterization of edible corn starch-sodium alginate double network hydrogels with Ca2+ cross-linking

This study explores the fabrication and characterization of corn starch‑sodium alginate double network hydrogels using two distinct calcium ion cross-linking methods: the gluconolactone immersed method (GIM) and the calcium chloride immersed method (CCIM). We investigated the ionic cross-linking mechanism of these hydrogels and compared their microstructure and mechanical properties. Our results highlight significant differences between GIM and CCIM hydrogels, with the CCIM method producing a more uniform and compact network. At the same calcium ion concentration, CCIM hydrogel exhibited higher mechanical strength and viscoelasticity properties compared to GIM hydrogel. The rapid release of Ca2+ in CCIM allowed for complete cross-linking with sodium alginate, forming a uniform 3D network structure. In contrast, the slow released Ca2+ in GIM resulted in a heterogeneous structure with a tough outer shell and incomplete internal cross-linking. Specifically, the CCIM hydrogel showed a compact network structure and the highest mechanical strength at a calcium chloride concentration of 1.6% (w/v). This study demonstrates that the Ca2+ release rate significantly impacts the microstructure and mechanical properties of double network hydrogels prepared by the immersion method. With this preparation strategy, corn starch‑sodium alginate edible gels that provided higher strength could be fabricated.

ICT, heterogeneous labor structure and productivity of producer service enterprises: evidence from China

PurposeThis paper explores the impact of information and communications technology (ICT) on the productivity rates of producer service enterprises and its mechanisms.Design/methodology/approachThe core dataset used in this paper is the World Bank’s 2012 China Enterprise Survey. The data on enterprises provided by the World Bank has its unique advantages. First, the questionnaire provides a detailed record of enterprises’ ICT investment and usage. Second, it provides a diversified description of the enterprises’ current labor structures in terms of education, skills and employment latitudes. Building on this dataset, this paper adopts quantitative methods, including the fixed effect model and instrumental variable approach for the study.FindingsOur research shows that ICT application boosts the productivity of producer service enterprises. Employees with a high education background, proficient skills and non-lifelong contracts complement the application of ICT. Heterogeneity analysis reveals significant productivity and a complementary effect of ICT on labor structure in regions with well-developed markets, knowledge-intensive industries and enterprises with a relatively larger scale of operation.Originality/valueIn the context of digital globalization, the rational use of ICT to lead the high-quality development of the service industry is of great significance in achieving structural transformation.

Deciphering spatial domains from spatially resolved transcriptomics through spatially regularized deep graph networks

BackgroundRecent advancements in spatially resolved transcriptomics (SRT) have opened up unprecedented opportunities to explore gene expression patterns within spatial contexts. Deciphering spatial domains is a critical task in spatial transcriptomic data analysis, aiding in the elucidation of tissue structural heterogeneity and biological functions. However, existing spatial domain detection methods ignore the consistency of expression patterns and spatial arrangements between spots, as well as the severe gene dropout phenomenon present in SRT data, resulting in suboptimal performance in identifying tissue spatial heterogeneity.ResultsIn this paper, we introduce a novel framework, spatially regularized deep graph networks (SR-DGN), which integrates gene expression profiles with spatial information to learn spatially-consistent and informative spot representations. Specifically, SR-DGN employs graph attention networks (GAT) to adaptively aggregate gene expression information from neighboring spots, considering local expression patterns between spots. In addition, the spatial regularization constraint ensures the consistency of neighborhood relationships between physical and embedded spaces in an end-to-end manner. SR-DGN also employs cross-entropy (CE) loss to model gene expression states, effectively mitigating the impact of noisy gene dropouts.ConclusionsExperimental results demonstrate that SR-DGN outperforms state-of-the-art methods in spatial domain identification across SRT data from different sequencing platforms. Moreover, SR-DGN is capable of recovering known microanatomical structures, yielding clearer low-dimensional visualizations and more accurate spatial trajectory inferences.

Enhancing strength-ductility synergy by introducing multilattice defects and heterogeneous structures in CoCrNi-based medium-entropy alloys prepared by powder plasma arc additive manufacturing

In the work, cold rolling and annealing were applied to powder plasma arc additively manufactured (CoCrNi)94Al3Ti3 medium-entropy alloy (MEA) to efficiently attain different types of lattice defects and heterogeneous structures, thereby enhancing the strength of the alloy. Tensile tests show that mechanical properties of the MEA were significantly enhanced after cold rolling and annealing treatments compared to the directly deposited alloys. The microstructure and mechanical properties of cold rolled samples (50 % thickness reduction) annealed at 1073–1273 K for 1 h are compared. It has been shown that the MEAs prepared by additive manufacturing accumulate a large amount of deformation energy within the grains during the cold rolling process. This lead to recrystallized grains first nucleating within the original columnar grains, and efficient recrystallization could be realized. At annealing temperatures ≤1173 K, the recrystallized grain size has not been coarsened, the coarse and fine grains formed a heterogeneous grain structure, leading to significant back stress strengthening. TEM observations at different alloys indicate that the formation and increase in the number of multiple lattice defects (SFs, DTs, and L–C locks) is the main reason for the high work-hardening capacity of the alloy. This investigation demonstrates that the combined approach provides a novel means to fabricate high strength and ductile CoCrNi-based MEAs.

Protein-Protein Interaction and Conformational Change in the Alpha-Helical Membrane Transporter BtuCD-F in the Native Cellular Envelope.

Alpha-helical membrane proteins perform numerous critical functions essential for the survival of living organisms. Traditionally, these proteins are extracted from membranes using detergent solubilization and reconstitution into liposomes or nanodiscs. However, these processes often obscure the effects of nanoconfinement and the native environment on the structure and conformational heterogeneity of the target protein. We demonstrate that pulsed dipolar electron spin resonance spectroscopy, combined with the Gd3+-nitroxide spin pair, enables the selective observation of the vitamin B12 importer BtuCD-F in its native cellular envelope. Despite the high levels of non-specific labeling in the envelope, this orthogonal approach combined with the long phase-memory time for the Gd3+ spin enables the observation of the target protein complex at a few micromolar concentrations with high resolution. In the native envelope, vitamin B12 induces a distinct conformational shift at the BtuCD-BtuF interface, which is not observed in the micelles. This approach offers a general strategy for investigating protein-protein and protein-ligand/drug interactions and conformational changes of the alpha-helical membrane proteins in their native envelope context.