Local Structure Research Articles

Investigation on temperature effect of local structural stress during non-uniform cross-section steel bridge deck pavement paving

During the process of gussasphalt concrete paving on the orthotropic steel bridge deck of a non-uniform cross-section box girder bridge, the high-temperature asphalt mixture often produces temperature stresses that can affect bearings safety. In this study, a refined model of a steel box girder bridge with a 660 m scale was developed and numerical simulations were conducted using the finite element software. The temperature field was applied to the orthotropic steel bridge deck in a quasi-dynamic fashion, leading to the determination of a safe width for concrete paving. To assess the accuracy of the computational predictions, field paving was performed under the safe width condition determined from the calculations, and the temperature and local stress data were measured in the field. The results demonstrate that the finite element predictions are in good agreement with the yield strength of the bearing’s local structure, and the measurements also show a close correspondence with the structural yield strength, validating the reliability of the quasi-static simulation approach. The proposed method offers a computational tool and a reliability criterion for future finite element analyses of large-span non-uniform cross-section steel box girder bridges, as well as a safe width example for subsequent gussasphalt mixture paving on orthotropic steel bridge decks.

Adaptive parameter local consistency automatic outlier removal algorithm for area-based matching

Abstract. Due to the influence of image differences and matching methods, geometric calibration of remote sensing images often results in the extraction of control points with inevitable outliers. Moreover, it is susceptible to limitations imposed by locally constrained outlier rejection methods, making it challenging to automatically remove relatively small gross errors. This paper introduces an adaptive parameter local consistency automatic outlier removal algorithm, referred to as APLC. Initially, we construct k-nearest neighbors for each pair of matching points, deriving distance and topological uncertainty based on the accuracy of point matching. Subsequently, we conduct cross-validation on the uncertainty between the two pairs of vectors formed by points within the neighborhood, aiming for parameter adaptation. Finally, a cost-defined function is introduced to assess the consistency of local structures. Through a two-stage outlier removal strategy, matching points that do not maintain local structural consistency are eliminated. To assess the effectiveness of the proposed algorithm, we conduct experimental comparisons using region-based initial matching results from the FY-3D remote sensing dataset, demonstrating its superiority compared to three state-of-the-art methods.

Oxygen Vacancies Trigger Rapid Charge Transport Channels at the Engineered Interface of S-scheme Heterojunction for Boosting Photocatalytic Performance.

Although oxygen vacancies (Ovs) have been intensively studied in single semiconductor photocatalysts, exploration of intrinsic mechanisms and in-depth understanding of Ovs in S-scheme heterojunction photocatalysts are still limited. Herein, a novel S-scheme photocatalyst made from WO3-Ov/In2S3 with Ovs at the heterointerface is rationally designed. The microscopic environment and local electronic structure of the S-scheme heterointerface are well optimized by Ovs. Femtosecond transient absorption spectroscopy (fs-TAS) reveals that Ovs trigger additional charge movement routes and therefore increase charge separation efficiency. In addition, Ovs have a synergistic effect on the thermodynamic and kinetic parameters of S-scheme photocatalysts. As a result, the optimal photocatalytic performance is significantly improved, surpassing that of single component WO3-Ov and In2S3 (by 35.5 and 3.9 times, respectively), as well as WO3/In2S3 heterojunction. This work provides new insight into regulating the photogenerated carrier dynamics at the heterointerface and also helps design highly efficient S-scheme photocatalysts.

Oxygen Vacancies Trigger Rapid Charge Transport Channels at the Engineered Interface of S‐scheme Heterojunction for Boosting Photocatalytic Performance

Although oxygen vacancies (Ovs) have been intensively studied in single semiconductor photocatalysts, exploration of intrinsic mechanisms and in‐depth understanding of Ovs in S‐scheme heterojunction photocatalysts are still limited. Herein, a novel S‐scheme photocatalyst made from WO3‐Ov/In2S3 with Ovs at the heterointerface is rationally designed. The microscopic environment and local electronic structure of the S‐scheme heterointerface are well optimized by Ovs. Femtosecond transient absorption spectroscopy (fs‐TAS) reveals that Ovs trigger additional charge movement routes and therefore increase charge separation efficiency. In addition, Ovs have a synergistic effect on the thermodynamic and kinetic parameters of S‐scheme photocatalysts. As a result, the optimal photocatalytic performance is significantly improved, surpassing that of single component WO3‐Ov and In2S3 (by 35.5 and 3.9 times, respectively), as well as WO3/In2S3 heterojunction. This work provides new insight into regulating the photogenerated carrier dynamics at the heterointerface and also helps design highly efficient S‐scheme photocatalysts.

Metallic Ru─Ru Interaction in Ruthenium Oxide Enabling Durable Proton Exchange Membrane Water Electrolysis.

Developing efficient and robust electrocatalysts toward the oxygen evolution reaction (OER) is critical for proton exchange membrane water electrolysis (PEMWE). RuO2 possesses intrinsically high OER activity, but the concurrent electrochemical dissolution leads to rapid deactivation. Here a unique RuO2 catalyst containing metallic Ru─Ru interactions (m-RuO2) is reported, which maintains stability in practical PEMWE for 100h at 60 °C and 1 A cm-2. Experimental and theoretical investigations suggest that the presence of Ru─Ru interactions significantly increases the energy barrier for the formation of RuO2(OH)2, which is a key intermediate for Ru dissolution, and hence substantially mitigates the electrochemical corrosion of m-RuO2. Meanwhile, the Ru4d band center downshifts, accordingly, ensuring the high OER activity, and the participation of lattice oxygen in the OER is also suppressed at the Ru─Ru sites, further contributing to the enhanced durability. Interestingly, such enhanced stability is also dependent on the size of metallic Ru─Ru cluster, where the energy barrier is further increased for Ru3, but is decreased for Ru5. These results highlight the significance of local coordination structure modulation on the electrochemical stability of RuO2 and open a feasible avenue toward the development of robust OER electrocatalysts for high-performance PEMWE.

Bond Structure Engineering Induced the Mn Redox Stabilization Toward High‐Energy Mn‐Based Phosphate Cathode

AbstractManganese (Mn) ‐based phosphate is poised for commercial applications driven by its cost‐effectiveness, robust NASICON framework, and multi‐dimensional Na+ pathways. However, it encounters insufficient redox reactions and rapid structural collapse with severe lattice distortion as the culprit. Herein, one meticulously engineered substitutional solid solution cathode (integrating Na4MnCr(PO4)3 and Na3MnTi(PO4)3, denoted NMCTP) is proposed to regulate the local crystal structure of Mn─O bond to stabilize and promote the Mn redox reaction for optimizing the electrochemical performance. It is uncovered that the bulk framework with structural stability is constructed by strongly symmetric Mn─O bond lengths of MnO6 octahedrons and strengthened Mn─O covalency. In addition, the sufficient utilization of Mn redox is tightly correlated with redistributed Na2 occupancy and enhanced diffusion kinetics with accelerated electron transportation. By virtue of the above merits, The NMCTP performs ultra‐high capacity (150.3 mAh g−1 at 0.1 C) and appealing cycling stability (84.7% retention over 1000 cycles). Sodium storage mechanisms and potential factors at high potentials are unveiled in NMCTP materials. This work sheds light on fire‐new solid solution strengthening in view of the Mn─O bond structure for high‐performance Mn‐based phosphate cathodes.

Cascaded maximum median-margin discriminant projection with its application to face recognition

This paper introduces a novel method called cascaded maximum median-margin discriminant projection (CMMDP) for robust face recognition. Initially, we introduce the maximum median-margin discriminant projection (MMDP) method, which aims to maximize the distances between class medians and their inter-class neighbors, while simultaneously minimizing the distances between class medians and their intra-class samples. To extract features at multiple levels, we extend the MMDP method to its deep version, known as CMMDP. The CMMDP algorithm incorporates the MMDP technique to learn multistage filter banks specifically designed for facial images. Afterward, we utilize straightforward binary hashing techniques for efficient indexing, along with block histograms for effective feature pooling. The CMMDP model is simple and easy to train, while taking full account of the global and local structure of the samples by maximizing the distances between samples that are dissimilar and minimizing the distances between samples that are similar after projection. This results in a low-dimensional data representation with better discriminative performance. We evaluate the performance of CMMDP on face datasets including AR, ORL, ExtYaleB and CMU PIE databases. The results indicate that CMMDP achieves superior performance than most advanced methods.

An overview of ion-acoustic solitary and shock waves in a magnetized nonthermal plasma: influence of trapped positrons and electrons

A magnetized nonthermal electron–positron-ion (e-p-i) plasma is considered to study the propagation properties of ion-acoustic solitary and shock waves in the presence of trapped positrons and electrons for the first time. The Schamel-κ (kappa) distribution function that describes plasma nonthermality and particle trapping is assumed to consider electrons and positrons. The diffusive effect of ion plasma fluid, which is responsible for shock dynamics, is taken into account. A nonlinear Schamel-Korteweg–de Vries-Burgers’ (SKdVB) equation is derived by employing the reductive perturbation approach, and the solitary and shock wave solutions of the SKdVB equation have also been derived for different limiting cases. It is found that only positive potential nonlinear structures (for both solitary and shock waves) are formed in the proposed plasma system. The condition for stable solitons in the absence of dissipation is analyzed, and the nature of arbitrary amplitude solitary waves (obtained via the Sagdeev potential approach) is discussed. It is found through theoretical and numerical investigation that different plasma compositional parameters (such as the trapping effect of electrons (β e ) and positrons (β p ), the obliquity effect (θ), electron-to-ion number density ratio (µ e ), the magnetic field effect (via Ω) and the viscous effect (via η)) have a significant influence on the dynamics of ion-acoustic solitary and shock waves. The theoretical and numerical investigations in this study may be helpful in describing the nature of localized structures in different plasma contexts, e.g. space and astrophysical plasmas and experimental plasmas where electron–positron-ion plasmas exist.

To copy verbatim, paraphrase or summarize – listeners’ methods of discourse representation while recalling academic lectures

Abstract It is unanimously agreed that comprehension of academic lectures is cognitively demanding; however, few studies have focused on a listener’s real-time discourse representation of a lecture. Based on the qualitative analysis of the verbal protocols, the present study investigated sixteen Chinese university students’ verbal recall of an academic mini-lecture to explore how they made sense of the lecture and represented its discourse when they recalled it episode by episode, and to what extent they differed in discourse representation. The results show that listeners’ discourse representation involved a range of cognitive processes such as paraphrasing, summarizing, and verbatim copying. Paraphrasing and summarizing were the main methods of discourse representation used by the participants when they verbally recalled the lecture. Those who correctly paraphrased more idea units recalled more content of the lecture. They were able to select and retain more idea units in their short-term memory, build more associations between the selected idea units, integrate them with the existing discourse structures and ensure contextual coherence in the construction of the local discourse structures. The findings of the study contribute to a better understanding of how listeners comprehend academic lectures and confirm that improving students’ paraphrasing skills and hierarchical discourse construction in recall are conducive to better comprehension of academic lectures.

Assessing Demographics, Perceptions, and Participation: A Study on Sangguniang Kabataan (SK) Effectiveness and Improvement Suggestions

The Sangguniang Kabataan is an important institution in the Philippines that represents the interests of youth and engages them in local governance. This study examines the perceptions of young Filipinos regarding the Sangguniang Kabataan’s (SK) participation in local government, focusing on understanding how youth perspectives influence the efficacy of SK initiatives. The research integrated a descriptive quantitative research design. A total of 32 participants were involved in the study, providing insights into their demographic profiles, perceptions of SK duties and functions, levels of participation in SK activities, and suggestions for improving SK officials and their activities. The findings reveal that while respondents generally recognize the importance of the SK in representing youth in local government, there are areas where its effectiveness can be enhanced, such as in implementing youth-focused programs and initiatives. The study also highlights barriers to youth participation in SK activities, including lack of awareness and time constraints. Recommendations for improving youth engagement in the SK include prioritizing advocacy for youth-related issues, enhancing communication with young individuals, and focusing on initiatives that address critical issues like poverty, education, and mental health. By implementing these recommendations, the SK can better serve the needs and aspirations of the youth population and create a more responsive and inclusive local governance structure.

Interfacial Spinel Local Interlocking Strategy Toward Structural Integrity in P3 Oxide Cathodes.

P3-layered transition oxide cathodes have garnered considerable attention owing to their high initial capacity, rapid Na+ kinetics, and less energy consumption during the synthesis process. Despite these merits, their practical application is hindered by the substantial capacity degradation resulting from unfavorable structural transformations, Mn dissolution and migration. In this study, we systematically investigated the failure mechanisms of P3 cathodes, encompassing Mn dissolution, migration, and the irreversible P3-O3' phase transition, culminating in severe structural collapse. To address these challenges, we proposed an interfacial spinel local interlocking strategy utilizing P3/spinel intergrowth oxide as a proof-of-concept material. As a result, P3/spinel intergrowth oxide cathodes demonstrated enhanced cycling performance. The effectiveness of suppressing Mn migration and maintaining local structure of interfacial spinel local interlocking strategy was validated through depth-etching X-ray photoelectron spectroscopy, X-ray absorption spectroscopy, and in situ synchrotron-based X-ray diffraction. This interfacial spinel local interlocking engineering strategy presents a promising avenue for the development of advanced cathode materials for sodium-ion batteries.

α-Hydrazino Acid Insertion Governs Peptide Organization in Solution by Local Structure Ordering

α-Hydrazino Acid Insertion Governs Peptide Organization in Solution by Local Structure Ordering

Subnanometer‐sized CuOx Clusters on TiO2 as Active Photocatalysts for Ammonia Production from Photocatalytic Nitration Reduction Reaction

The Haber‐Bosch process is commonly used to produce ammonia while consuming energy and yielding huge emissions of carbon dioxide. Finding an alternative way to produce ammonia sustainably is a promising research direction with less CO2 emission. Photochemical nitrate reduction reaction (NtRR) to ammonia (NH3) could solve the nitrate pollutant problem in water and approach to produce ammonia with a more environmentally friendly process and lower energy consumption. In this work, the subnanometer‐sized copper oxide clusters decorated on titanium oxide nanoparticles (CuOx‐TiO2) were synthesized through the hydrothermal method and calcination treatment. CuOx‐TiO2 demonstrated impressively conversion rate of NO3‐ to NH3 with a yield of 153.09 μg‐gcat‐1‐h‐1 in KNO3 solution. The characteristic structure analysis revealed CuOx clusters with ~less than 1 nm decorated on TiO2 nanoparticles. From in‐situ X‐ray absorption fine structure (XAFS) spectroscopic technique, the transformation of the oxidation state of Cu clusters and the changes of local structure in the CuOx‐TiO2 were observed. The photocatalytic reaction mechanism of nitrate reduction on the CuOx‐TiO2 was successfully revealed. These discoveries have broad implications for the functional advancement of catalysts based on subnanometer‐sized clusters. Our findings may pave the way for exploring advanced ammonia synthesis routes with reduced energy consumption and carbon emissions.

Inflection Point in Pressure Dependence of Ionic Conductivity as a Fingerprint of Local Structure Formation.

In this study, we employed dielectric spectroscopy to investigate the effect of temperature and pressure on the ion dynamics of phosphonium ionic liquids (ILs) differing by the length of an alkyl chain, [P666,n][TFSI] (n = 2, 6, 8, 12). We found that both temperature and pressure dependence of dc-conductivity (σdc) determined for all examined ILs herein exhibit unique characteristics, unusual for aprotic ILs. Two regions differing by ion self-organization have been identified from the derivative analysis of σdc(T-1) data. On the other hand, isothermal measurements performed at elevated pressure revealed a unique concave-convex character of σdc(P) dependences, resulting in a clear minimum in the pressure behavior of activation volume. Such an inflection point characterizing the pressure dependence of σdc in [P666,n][TFSI] ILs can be considered an inherent feature of ion dynamics governed by structural self-assembly. Our results offer a unique perspective to link the ion mobility at various T-P conditions to the nanostructural organization of ionic systems.

Ultrafast Formation of Charge Transfer Trions at Molecular‐Functionalized 2D MoS2 Interfaces

In this work, we investigate trion dynamics occurring at the heterojunction between organometallic molecules and a monolayer transition metal dichalcogenide (TMD) with transient electronic sum frequency generation (tr‐ESFG) spectroscopy. By pumping at 2.4 eV with laser pulses, we have observed an ultrafast hole transfer, succeeded by the emergence of charge‐transfer trions. This observation is facilitated by the cancellation of ground state bleach and stimulated emission signals due to their opposite phases, making tr‐ESFG especially sensitive to the trion formation dynamics. The presence of charge‐transfer trion at molecular functionalized TMD monolayers suggests the potential for engineering the local electronic structures and dynamics of specific locations on TMDs and offers the potential for transferring unique electronic attributes of TMD to the molecular layers.

Ultrafast Formation of Charge Transfer Trions at Molecular-Functionalized 2D MoS2 Interfaces.

In this work, we investigate trion dynamics occurring at the heterojunction between organometallic molecules and a monolayer transition metal dichalcogenide (TMD) with transient electronic sum frequency generation (tr-ESFG) spectroscopy. By pumping at 2.4 eV with laser pulses, we have observed an ultrafast hole transfer, succeeded by the emergence of charge-transfer trions. This observation is facilitated by the cancellation of ground state bleach and stimulated emission signals due to their opposite phases, making tr-ESFG especially sensitive to the trion formation dynamics. The presence of charge-transfer trion at molecular functionalized TMD monolayers suggests the potential for engineering the local electronic structures and dynamics of specific locations on TMDs and offers the potential for transferring unique electronic attributes of TMD to the molecular layers.

Intercalated Water Drives Anomalous Thermal Expansion in the Tetragonal Zircon Structured Bismuth Vanadate BiVO4 Photocatalyst.

The thermal transformation of zircon to scheelite in BiVO4 was studied by in-situ Synchrotron X-ray diffraction and TGA/FTIR analysis. Upon heating, the tetragonal zircon polymorph of BiVO4 (tz-BiVO4) transitioned to the tetragonal scheelite (ts-)polymorph between 693-773 K, then to monoclinic fergusonite (mf) polymorph upon cooling. An anomaly in thermal expansion was observed between 400-500 K, associated with loss of H2O/NH4+. Heating tz-BiVO4 resulted in contraction of the V-O bond distance and VO4 polyhedra volume due to rotation of the VO4. Attempts to study this by neutron diffraction failed due to the large incoherent scatter from the hydrogenous species. Efforts to remove these species while maintaining the tz-BiVO4 structure were unsuccessful, suggesting they play a role in stabilizing the zircon polymorph. The local structure of both mf-BiVO4 and tz-BiVO4 were investigated by X-ray Pair Distribution Function analysis.

Simple and efficient methods for local structural analysis in polydisperse hard disk systems.

In nonequilibrium statistical physics, quantifying the nearest (and higher-order) neighbors and free volumes of particles in many-body systems is crucial to elucidating the origin of macroscopic collective phenomena, such as glass/granular jamming transitions and various aspects of the behavior of active matter. However, conventional techniques (based on a fixed-distance cutoff or the Voronoi construction) have mainly been applied to equilibrated, homogeneous, and monodisperse particle systems. In this paper, we implement simple and efficient methods for local structure analysis in nonequilibrium, inhomogeneous, and polydisperse hard disk systems. We show how these novel methods can overcome the difficulties encountered by conventional techniques as well as demonstrate some applications.

Automorphisms of projective structures

We study the problem of classifying local projective structures in dimension two having non trivial Lie symmetries. In particular we obtain a classification of foliated projective structures having positive dimensional Lie algebra of projective vector fields.

Local spatial and temporal relation discovery model based on attention mechanism for traffic forecasting

Recognizing the evolution pattern of traffic condition and making accurate prediction play a vital role in intelligent transportation systems (ITS). With the massive increase of available traffic data, deep learning-based models have attracted considerable attention for their impressive performance in traffic forecasting. However, the majority of existing approaches neglect to model of asynchronously dynamic spatio-temporal correlation and fail to consider the impact of historical traffic data on future condition. Additionally, the attribute of deep learning method presents challenges in interpreting the explicit spatiotemporal relationships. In order to enhance the accuracy of traffic prediction as well as extract comprehensive and explainable spatial–temporal relevance in traffic networks, we propose a novel attention-based local spatial and temporal relation discovery (ALSTRD) model. Our model firstly implements feature representation learning to effectively express latent input traffic information. Then, a local attention mechanism structure is established to model asynchronous dependencies of historical input data. Finally, another attention network and the Pearson Correlation Coefficient method are introduced to extract the elaborate influence of the historical traffic condition of neighboring roads on the future condition of the target road. The experiment results on several datasets demonstrate that our model achieves significant improvements in prediction accuracy compared to other baseline methods, which can be attributed to its ability to extract the fine-grained correlation among historical traffic data and capture the dynamic association between past and future data. In addition, the incorporation of attention mechanism and Pearson Correlation Coefficient promotes the model’s ability to elucidate spatiotemporal correlations among traffic data, thereby providing a more robust explanation.