Fine-grained Area Research Articles

Prediction and optimisation of solidification structure growth and transformation behaviour in microalloy chamfered continuous casting slab

The solidification structure of complex chamfered slabs of microalloyed steel was analysed and controlled. A computational model of solidified structures was applied and the model was verified. The research results show that there are differences in the solidification structure inside the slab. The slab successively produces fine-grained areas, large-size columnar grain areas, CET (columnar to equiaxed grain transition), and equiaxed grain areas. The effects of different carbon contents on the solidification structure were analysed. As the c content decreases from 0.23% to 0.20%, the tip growth fitting coefficient a3 increases from 4.077172e-06 to 5.403274e-06, which increases the grain growth rate. Considering the different sensitivities of grain growth in the lateral direction, a lateral zoning water supply strategy is used to flexibly control the uniformity of grain growth. By simulating different water flow ratios in the corners and centre areas, the optimal nozzle water flow density ratio is 0.840. Superheat can effectively control grain distribution. The proportion of central equiaxed grains increases with decreasing superheat. The study found that the proportion of equiaxed grains has different sensitivities affected by different degrees of superheat. The superheat degree ranges of strong sensitivity and weak sensitivity were obtained. In the production practice of superheat adjustment to control particle distribution, the adjustment effect is better within the strong sensitivity range.

Nanocrystallization and precipitation behavior evolution of AZ80 magnesium alloy during multi-directional compression

In response to the growing demand for high-performance magnesium alloys in the aerospace and transportation industries, researchers conducted a study on the AZ80 magnesium alloy. The primary objective was to achieve a nanocrystalline structure in the alloy through severe plastic deformation using low-strain multi-directional compression at room temperature. Subsequently, an aging treatment was performed to induce the transformation of the structure into a stable state. The study aimed to investigate the morphology and mode of the second phase precipitation in the magnesium alloy after undergoing severe plastic deformation. The research findings revealed that the application of multi-directional and multi-pass compression during room temperature deformation of the magnesium alloy effectively prevented instability and fracture. Moreover, this process facilitated the accumulation of larger true strain. As the number of compression passes increased, deformation twins became increasingly denser, particularly in the intersecting areas. Consequently, ultrafine high-angle grain structures were preferentially formed in these regions. Furthermore, the number of fine-grained areas gradually increased with each deformation pass. After ΣΔε 5.12, the grain size was refined to a range of 100–200 nm. Additionally, the aging treatment following severe plastic deformation brought about a significant change in the traditional lamellar precipitation mode of the second phase Mg17Al12 in the magnesium alloy. Instead, spherical precipitation occurred.

Superior strength and ductility in a C-containing CoCrFeNiMn high-entropy alloy with heterogeneous microstructure

The present study is focused on the beneficial effects of adding few amounts of carbon (0.76 at. %) and adopting microstructure engineering by a simple thermomechanical treatment to form a heterogeneous microstructure in a CoCrFeNiMn high-entropy alloy. The results demonstrate that the addition of carbon results in significantly higher strength and improved thermal stability when compared to carbon-free alloy under identical conditions. In fact, the addition of carbon results in strengthening through the solute drag effect and solid solution strengthening. Thermodynamic predictions and XRD patterns indicate that carbon addition enhances the tendency of carbide precipitation in the alloy instead of forming an undesirable σ phase. The microstructural observation reveals that the deformed microstructure remains nearly stable during annealing at temperatures up to 750 °C and complete recrystallization occurs after annealing at 1000 °C, resulting in the formation of a fine-grained microstructure. Post-deformation annealing at 800 and 900 °C leads to the formation of heterogeneous microstructures comprising regions with high dislocation density grains alongside recrystallized fine-grained areas. The results suggest a superior synergy between strength and ductility in the annealed sample at 800 and 900 °C, exhibiting the ultimate-tensile strength of ∼1000 and ∼835 MPa. Additionally, these samples demonstrate decent uniform elongation values of ∼10 and 20%, respectively.

Spatial transcriptomics analysis of gene expression prediction using exemplar guided graph neural network

Spatial transcriptomics (ST) is essential for understanding diseases and developing novel treatments. It measures the gene expression of each fine-grained area (i.e., different windows) in the tissue slide with low throughput. This paper proposes an exemplar guided graph network dubbed EGGN to accurately and efficiently predict gene expression from each window of a tissue slide image. We apply exemplar learning to dynamically boost gene expression prediction from nearest/similar exemplars of a given tissue slide image window. Our framework has three main components connected in a sequence: (i) an extractor to structure a feature space for exemplar retrievals; (ii) a graph construction strategy to connect windows and exemplars as a graph; (iii) a graph convolutional network backbone to process window and exemplar features, and a graph exemplar bridging block to adaptively revise the window features using its exemplars. Finally, we complete the gene expression prediction task with a simple attention-based prediction block. Experiments on standard benchmark datasets indicate the superiority of our approach when compared with past state-of-the-art methods. We release our code at https://github.com/Yan98/EGN.

A hierarchical constraint-based graph neural network for imputing urban area data

Urban area data are strategically important for public safety, urban management, and planning. Previous research has attempted to estimate the values of unsampled regular areas, while minimal attention has been paid to the values of irregular areas. To address this problem, this study proposes a hierarchical geospatial graph neural network model based on the spatial hierarchical constraints of areas. The model first characterizes spatial relationships between irregular areas at different spatial scales. Then, it aggregates information from neighboring areas with graph neural networks, and finally, it imputes missing values in fine-grained areas under hierarchical relationship constraints. To investigate the performance of the proposed model, we constructed a new dataset consisting of the urban statistical values of irregular areas in New York City. Experiments on the dataset show that the proposed model outperforms state-of-the-art baselines and exhibits robustness. The model is adaptable to numerous geographic applications, including traffic management, public safety, and public resource allocation.

A study on overlapping effect of melt pools in powder bed fusion based on a novel prediction method

The unique advantages distinguishing additive manufacturing from other processing technologies, such as casting, forging, powder metallurgy and laser remelting originate from multiple melting and resulting overlapping of melt pools. However, it is difficult to predict or reconstruct the state of melt pool overlapping because melt pools are affected in each processing stage (deposition, melting, and solidification). Moreover, the impact of melt pool overlapping on microstructure and properties is still unclear . Here, a novel reconstruction model was established for melt pool overlapping by using Python during laser powder bed fusion. Melt-pool dimensions used in this model can be derived using experiments or predicted through normalized enthalpy. The “overlapping unit” was proposed to be a result of the periodic regulation of deposition, which helps in simplifying the microstructure formed through multiple melting and layer-wise deposition. Subsequently, the overlapping effect and its impact on elemental losses, defect formation, and microstructure evolution were investigated; the results were elucidated based on the average number of melting cycles (NMC) of the “overlapping unit” and the calculated thermal history. It can be concluded that the loss of elements with low boiling points (Mg in our alloy) is positively correlated with NMC due to repeated vaporization. Most incomplete defects are formed in regions melted less than twice, while hole defects are found predominantly in regions melted more than six times. Furthermore, the fine-grained area (average diameter ≤ 1 µm) tends to vary with both melt pool overlapping and heat accumulation. Moreover, an increase in sample temperature due to overlapping can augment the number and size of precipitates. Overall, this work offers a new way to improve the microstructure and mechanical properties of materials by optimizing overlapping conditions.

Buchnerillo atlanticus sp. nov., a new halophilic woodlouse (Isopoda: Oniscidea: incertae sedis) from the Atlantic coast of the Iberian Peninsula, with ecological remarks

A new woodlouse species of the genus Buchnerillo Verhoeff, 1942 is described and illustrated from the Cantabrian Coast of Asturias (Eastern Atlantic Ocean of the Iberian Peninsula). Buchnerillo atlanticus sp. nov. is a halophilic woodlouse that lives under embedded rocks in fine-grained sand areas of its type locality beach. Its morphological features, including secondary sexual characteristics, allow it to be distinguished from the other three known species of the genus Buchnerillo. Biological, ecological and ethological data of the new species are commented. To facilitate the separation of the four known species of Buchnerillo, the main diagnostic features are summarized and their known distribution is commented.

Fundus Retinal Vessels Image Segmentation Method Based on Improved U-Net

ObjectivesAlthough the segmentation of retinal vessels in the fundus is of great significance for screening and diagnosing retinal vascular diseases, it remains difficult to detect the low contrast and the information around the lesions provided by retinal vessels in the fundus and to locate and segment micro-vessels in the fine-grained area. To overcome this problem, we propose herein an improved U-Net segmentation method NoL-UNet. Material and methodsThis work introduces NoL-UNet. First of all, the ordinary convolution block of the U-Net network is changed to random dropout convolution blocks, which can better extract the relevant features of the image and effectively alleviate the network overfitting. Next, a NoL-Block attention mechanism added to the bottom of the encoding-decoding structure expands the receptive field and enhances the correlation of pixel information without increasing the number of parameters. ResultsThe proposed method is verified by applying it to the fundus image datasets DRIVE, CHASE_DB1, and HRF. The AUC for DRIVE, CHASE_DB1 and HRF is 0.9861, 0.9891 and 0.9893, Se for DRIVE, CHASE_DB1 and HRF is 0.8489, 0.8809 and 0.8476, and the Acc for DRIVE, CHASE_DB1 and HRF is 0.9697, 0.9826 and 0.9732, respectively. The total number of parameters is 1.70M, and for DRIVE, it takes 0.050s to segment an image. ConclusionOur method is statistically significantly different from the U-Net method, and the improved method shows superior performance with better accuracy and robustness of the model, which has good practical application in auxiliary diagnosis.

Effect of microstructure on fatigue crack propagation in additive manufactured nickel-based superalloy Haynes 282: an experiment and crystal plasticity study

Haynes 282 is a $$\gamma ^{\prime}$$ precipitation-strengthened nickel-based superalloy known for its exceptional high-temperature creep resistance and excellent fabricability. Recent advancements in powder-bed fusion-based additive manufacturing (PBF-AM) have enabled the fabrication of Haynes 282 with accurate, site-specific control of the grain orientation and morphology at the microscale. This ability opens up new avenues for microstructure design, to improve the material’s fatigue crack resistance and service life. This paper investigates the fatigue crack growth behavior of hybrid microstructure Haynes 282 fabricated via PBF-AM. Previous experiments revealed a higher crack propagation rate in the coarse columnar-grained microstructural regions when compared against fine-grained areas. Here, a strain gradient crystal plasticity model was adapted to study the fracture-related mechanical fields at the crack tip in the two microstructures. The simulation results showed a consistent influence of grain structure and texture on crack propagation, as was seen in the experiment. The model analysis revealed higher crack propagation driving force along crack direction in the coarse-grained sharply textured microstructure and higher driving force for crack kinking in fine-grained more diffusely textured microstructure, which is ascribed to the combined effect of yield stress, hardening rate, texture and grain morphology. The presented modeling approach will facilitate the development of the AM-based accurate microstructure design by deepening the fundamental study in AM-specific microstructure-properties relations.

Coupled effects of banded structure and carbide precipitation on mechanical performance of Cr–Ni–Mo–V steel

Effects of austenitizing temperature on microstructure evolution and mechanical performance of banded structured Cr–Ni–Mo–V steel were studied in this research. It is indicated that the banded structure is characterized by alternately distributed fine and coarse prior austenite grains, and alloying elements like V, Cr, Mo and Ni are segregated within fine-grained areas. Austenitizing temperature has a significant effect on the relative amount of alloying elements between fine-grained and coarse-grained areas, as well as the carbide precipitates upon tempering treatment. With the increase in austenitizing temperature, the tensile strength, ductility and toughness of Cr–Ni–Mo–V steel are improved simultaneously. Delaminated cracks can be readily found in the fracture surface, which is consistent with the observed banded structure. The interface between the fine-grained and coarse-grained areas are places where the delamination cracks are prone to initiate. Both the blunting of crack tip and transformation of stress state are suggested to be responsible for the improvement of ductility and toughness.

Size effect due to contour laser scanning in 316L stainless steel produced by laser powder bed fusion

In this work, effect of sample size on mechanical properties in the net-shaped 316 L alloys produced by laser powder bed fusion (LPBF) was studied. Tensile specimens with four different geometries, having the same total cross-sectional areas but with different tension beam widths of 0.75, 1.5, 3 and 6 mm, were produced by the LPBF and subjected to the tests. The experimental results indicated that there is a strong influence of the sample size of the mechanical properties in the as-built state. The yield strength increased and the ductility decreased pronouncedly with decreasing the sample size. Fine grain structures near the surface of the net-shaped samples due to the additional laser contour scanning is believed to be responsible to the strong sample size effect. The experiments also revealed that the sample size effect can be effectively reduced with the annealing heat treatments. The local strength of the fine-grained area near the surface was quantitatively characterized by an inverse finite element analysis. The local strength near the surface was found stronger in the direction parallel to the LPBF building direction than in the direction parallel to the LPBF transverse direction, leading to more significant size effect along this direction.

Effect of laser cladding on microstructural transformation and mechanical properties of heat affected zone of EA4T steel

In this study, laser cladding on EA4T steel was carried out. The Composition of HAZ of the EA4T steel was analyzed by OM and SEM. The effect of laser cladding on microstructural transformation of HAZ of EA4T steel was discussed. The distribution of alloying elements and the micromechanical properties of the interface were tested. The results show that the microstructures of the laser cladding heat-affected zone of the EA4T steel are mainly lath martensite. The homogenization of austenite and the dissolution of carbides near the interface are not sufficiently developed, and coarse grains are observed. In the fine-grained area of the HAZ, the microstructure is mainly composed of martensite and a small amount of sorbite with a certain orientation. In addition, among all laser cladding conditions, the highest temperature experienced in the HAZ of the EA4T steel plays a decisive role in the evolution of the microstructure and mechanical properties. A sudden change in alloying elements occurs at the junction site, and the grain orientation is clearly found. Moreover, the shear strength of the HAZ increases, whereas the degree of packing decreases.

Microstructure and Mechanical Properties of a Combination Interface between Direct Energy Deposition and Selective Laser Melted Al-Mg-Sc-Zr Alloy

Selective laser melting (SLM) and direct energy deposition (DED) are two widely used technologies in additive manufacturing (AM). However, there are few studies on the combination of the two technologies, which can synthetically combine the advantages of the two technologies for more flexible material design. This paper systematically studies the Al-Mg-Sc-Zr alloy by combination of SLM and DED with emphasis on its bonding properties, microstructure, and metallurgical defects. It is found that the aluminum alloy prepared by the two methods achieves a good metallurgical combination. The microstructure of aluminum alloy prepared by DED is composed of equiaxed crystals, and there are a large number of Al3(Sc, Zr) precipitated phase particles rich in Sc and Zr. The microstructure of SLM aluminum alloy is composed of equiaxed crystals and columnar crystals, and there is a fine-grained area at the boundary of the molten pool. With the decrease of laser volumetric energy density (VED), the width and depth of the molten pool at the interface junction gradually decrease. The porosity gradually increases with the decrease of VED, and the microhardness shows a downward trend. Tensile strength and elongation at fracture of the SLM printed sample at 133.3 J/mm3 are about 400 MPa and 9.4%, while the direct energy depositioned sample are about 280 MPa and 5.9%. Due to the excellent bonding performance, this research has certain guiding significance for SLM–DED composite aluminum alloy.

Toward Combatting COVID-19: A Risk Assessment System.

The coronavirus disease 2019 (COVID-19) has rapidly become a significant public health emergency all over the world since it was first identified in Wuhan, China, in December 2019. Until today, massive disease-related data have been collected, both manually and through the Internet of Medical Things (IoMT), which can be potentially used to analyze the spread of the disease. On the other hand, with the help of IoMT, the analysis results of the current status of COVID-19 can be delivered to people in real time to enable situational awareness, which may help mitigate the disease spread in communities. However, current accessible data on COVID-19 are mostly at a macrolevel, such as for each state, county, or metropolitan area. For fine-grained areas, such as for each city, community, or geographical coordinate, COVID-19 data are usually not available, which prevents us from obtaining information on the disease spread in closer neighborhoods around us. To address this problem, in this article, we propose a two-level risk assessment system. In particular, we define a “risk index.” Then, we develop a risk assessment model, called MK-DNN, by taking advantage of the multikernel density estimation (MKDE) and deep neural network (DNN). We train MK-DNN at the macrolevel (for each metro area), which subsequently enables us to obtain the risk indices at the microlevel (for each geographic coordinate). Moreover, a heuristic validation method is further designed to help validate the obtained microlevel risk indices. Simulations conducted on real-world data demonstrate the accuracy and validity of our proposed risk assessment system.

Analysis of Cracking Causes of P91 Welding Seam of High Pressure Steam Guide Pipe of Supercritical Unit

A 600MW supercritical unit in a thermal power plant has been in operation for 63,000 hours, and a P91 weld leak occurred between the high-pressure steam guide pipe and the high-pressure governor valve. After macroscopic morphology analysis, alloy composition analysis, metallographic structure observation, and microhardness test analysis, it is found that the cracking of the base metal and weld on the high-pressure speed control valve is caused by structural stress and welding stress, which leads to cracking due to creep. The crack originated in the fine-grained area of the heat-affected zone, and it has been operating in a high-temperature operating environment for a long time. The P91 weld on the high-pressure steam guide tube produces creep holes in the fine-grained heat-affected zone, which gradually grow to form creep cracks, and eventually lead to cracks and leakage. Therefore, the failure of pipeline cracking is caused by the joint action of tensile stress and type IV crack.

Microstructure and mechanical properties of bimetallic copper/brass laminates fabricated via accumulative press bonding

Abstract An accumulative press bonding (APB) process up to three cycles was used to fabricate copper/brass multi-layered composites. The resulting composites were characterized using scanning electron microscopy (SEM), electron backscattered diffraction (EBSD), and energy-dispersive X-ray spectroscopy (EDS) techniques. Three cycles of the APB process yielded mean grain sizes of 3.1 and 1.5 μm for the press-bonded copper and brass layers, respectively. A detailed EBSD study of the microstructure comprising the copper layer revealed a bimodal grain structure where a coarse-grained region was sandwiched between fine-grained areas. The adiabatic heat generated by the severe plastic deformation may have provided the conditions for grain growth in the coarse-grained part. The yield strength and ultimate tensile strength of the composite improved continually with strain reaching values of 401 and 523 MPa, respectively, after three cycles of the APB process. The values were about ~2.3 and 6.0 times higher than the corresponding values of initial pure copper material.

Designing (Ultra)Fine-Grained High-Entropy Alloys by Spark Plasma Sintering and Equal-Channel Angular Pressing

Single-phase, face-centered cubic (FCC) high-entropy alloys (HEA) are promising materials for future applications. In order to improve the mechanical properties, especially the tensile strength of these materials, this study focuses on the combination of spark plasma sintering (SPS) and equal-channel angular pressing (ECAP). The initial fine-grained microstructure produced by SPS is further refined by ECAP in a 90°-die. Optical microscopy and electron backscatter diffraction (EBSD) confirm this considerable grain refinement, leads to a grain size below 1 µm after 1 ECAP pass. An alternating arrangement of fine-grained areas and much coarser regions, aligned under an angle of approximately 27°, is found. Moreover, a first microstructural investigation of the twin structure is conducted. The mechanical behavior was investigated by hardness measurements and tensile testing. Both the hardness and tensile strength are remarkably increased after ECAP. In contrast, the uniform elongation and elongation at fracture are significantly reduced due to the strengthening mechanisms of strain hardening and grain refinement. It is concluded that the combination of SPS and ECAP is an attractive approach for designing (ultra)fine-grained HEAs with superior properties. The investigated techniques could be applied to understand the underlying microstructural mechanisms.

Distribution, sources and burial flux of sedimentary organic matter in the East China Sea

Distribution of total organic carbon (TOC), total nitrogen (TN), stable isotope ratio of organic carbon and nitrogen (δ13C and δ15N) in 31 surface sediments were examined to quantitatively discriminate the source and burial of sedimentary organic matter (SOM) in the East China Sea (ECS). Results show that high content of TOC and TN occurred in the southern inner shelf and the northeast area due to the transport of organic matter (OM) from the Changjiang (Yangtze) River southwards by the Zhejiang Fujian Coastal Current (ZFCC) and the delivery from the old Huanghe (Yellow) River estuary by the Subei Coastal Current (SbCC), respectively. The significant relationship of TOC to clay provided evidence that the fine-grained sediment was the primary carrier for SOM from the inner shelf to open sea. The TN varied proportionally to the TOC with the neglected intercept, suggesting that most of nitrogen measured was related to the SOM and the influence of the sorption of inorganic nitrogen was insignificant. The seaward enrichment of δ13C and seaward depletion of C/N and δ15N illustrated the decrease of terrestrial OM (TOM) and the increase of marine OM (MOM). The close of average C/N ratio to the Redfield ratio indicated the minor role of terrestrial plant debris in the SOM. Distribution of bulk OM properties was ascribed to the terrestrial and marine input by the shelf circulation and phytoplankton with the contributions of 76.1% MOM and 23.9% TOM to SOM, respectively. The burial flux of OC ranged within 0.34-7.56 mg/(cm2·a) (averaged 2.80 mg/(cm2·a)) and enriched along the shore and in the fine-grained area, manifesting the significant input of the land-based sources and the effect of shelf mud depositional process on the fate of SOM. The sharp seaward decrease of burial fluxes of terrestrial and marine OC gave evidences that the majority of organic carbon were settled in the inner shelf with the small fraction of them further transported eastwards.

Seasonal variations in the surficial sediment grain size in the East China Sea continental shelf and their implications for terrigenous sediment transport

This study discusses the seasonal variations in surficial sediment grain size and their implications for sediment transport driven by the hydrodynamics in the East China Sea, based on grain size analysis of surficial sediments and salinity data collected from the East China Sea continental shelf during two cruises in 2011. The results show that the grain size distribution on the East China Sea continental shelf presents apparent spatial and seasonal variations. The mud area exhibits more variation than the sand area, which indicates that the sediment supply is the main factor controlling the surficial sediment grain size distribution on the East China Sea continental shelf. The grain size near the Yangtze River Estuary is relatively coarse in summer, because of the inherited characteristics from the previous winter, whereas it is much finer in autumn, due to the input of fine-grained materials during the flood period of the Yangtze River. A high fine-grained sediment concentration was found along the Zhejiang-Fujian coast in autumn when the Zhejiang-Fujian Coastal Current forms. The sediments in the northeast of the study region (the mud patch southwest of Cheju Island) are much coarser, and the fine-grained area is narrower in autumn than in summer because of seasonal variations in the Yellow Sea Coastal Current and the frequency of storms. Simultaneously, the tongue-shaped fine-grained cross shelf front located along the Zhejiang-Fujian coast occurs farther to the south in autumn than in summer. However, the surficial grain size distribution patterns on the middle and outer shelf are similar in the two seasons.

Fine-grained tourism prediction: Impact of social and environmental features

Accurate predictions about future events is essential in many areas, one of them being the Tourism Industry. Usually, cities and countries invest a huge amount of money for planning and preparation in order to welcome (and profit from) tourists. The success of many businesses depends largely or totally on the state of tourism demand. Estimation of tourism demand can be helpful to business planners in reducing the risk of decisions regarding the future since tourism products are, generally speaking, perishable (gone if not used). Prior studies in this domain focus on forecasting for a whole country and not for fine-grained areas within a country (e.g., specific touristic attractions) mainly because of lack of data. Our article tackles exactly this issue. With the rapid popularity growth of social media applications, each year more people interact within online resources to plan and comment on their trips. Motivated by such observation, we here suggest that accessible data in online social networks or travel websites, in addition to environmental data, can be used to support the inference of visitation count for either indoor or outdoor touristic attractions. To test our hypothesis we analyze visitation counts, environmental features and social media data related to 27 museums and galleries in U.K as well as 76 national parks in the U.S. Our experimental results reveal high accuracy levels (above 92%) for predicting tourism demand using features from both social media and environmental data. We also show that, for outdoor attractions, environmental features have better predictive power while the opposite occurs for indoor attractions. In any case, best results, in all scenarios, are obtained when using both types of features jointly. Finally, we perform a detailed failure analysis to inspect the cases in which the prediction results are not satisfactory.