Fusion Characteristics Research Articles

Effects of phosphorus on the fusion characteristics of synthetic ashes with different Al2O3/CaO ratios

In this paper, five series of synthetic ashes with different Al2O3/CaO ratio mass ratios were prepared, and the ash fusion temperatures (AFTs) of the samples with different percentages (5–20 wt%) of phosphorus pentoxide (P2O5) added were measured under a mild reducing atmosphere to study the effect of phosphorus on the fusion characteristics of the ashes in different compositions. X-ray diffraction (XRD), thermodynamic equilibrium calculations, and high-temperature heating stage microscopy (HHSM) were used to investigate the mechanism of phosphorus in changing the fusion characteristics of the ash. The results showed that the addition of P2O5 produced the least effect on AFTs of samples with an Al2O3/CaO ratio of 6:4. For lower Al2O3/CaO ratios (classified as peralkaline), the addition of P2O5 caused a decrease-increase-decrease trend in AFTs, while for higher Al2O3/CaO ratios (classified as peraluminous), the AFTs of samples were decreased by phosphorus. The stronger affinity of P2O5 for CaO and Al2O3, compared to that of SiO2, was noticed and led to a shift of main minerals in the slag from silicates to phosphates and to the isolation of SiO2. In addition, the phosphorus-bearing samples followed the same “melt-dissolution mechanism” as the phosphorus-free samples.

Effecting mechanisms of iron-rich sludge on ash fusion characteristics of coal with high ash fusion temperature under reducing atmosphere

Co-gasification is crucial for large-scale clean conversion of coal and sludge. In this study, the effects of municipal sewage sludge (MSS, Fe2O3:48.11 %) and pharmaceutical sewage sludge (PSS, Fe2O3: 67.80 %) on ash fusion temperature (AFT) of high AFT Xiangyuan coal (XY) were explored using an AFT analysis, X-ray fluorescence spectrometry, X-ray diffraction, scanning electronic microscopy, and thermodynamics FactSage calculation. The results showed that when MSS or PSS ash mass ratios reached 20 % or 16 % (for XY mixtures, the mass ratio of MSS or PSS should be >5.81 wt% or 5.07 wt%), respectively, the AFT met the requirement of liquid-slag discharge for entrained-flow bed gasification. Under a reducing atmosphere (6:4, CO/CO2, volume ratio), Fe2+ destroyed the bridging-oxygen bonds in the network structure and generated low melting-point (MP) hercynite (FeAl2O4). This resulted in the AFT decreases in the XY mixtures with the additions of PSS or MSS. Meanwhile, the high calcium content (CaO: 13.40 %) easily reacted with Al2O3 and SiO2 and formed anorthite (CaAl2SiO8), which inhibited high-MP mullite formation and decreased the mixed XY AFT. With the increasing SS mass ratio, the surface of the ash sample and thermodynamic FactSage calculation were in good agreement with the experimental results.

Study on the lubrication behavior of low molecular weight poly(vinyl chloride‐co‐n‐butyl acrylate‐co‐vinyl acetate) ternary copolymer in rigid PVC

AbstractHerein, low molecular weight poly(vinyl chloride‐co‐n‐butyl acrylate‐co‐vinyl acetate) (PCBV) ternary copolymers with varied copolymer composition was employed as a novel polymeric lubricant in rigid PVC. The lubrication effect of PCBVs on the melting process and mechanical properties of the final PVC products were fully investigated. The results indicated that PCBV can serve either as an internal or as an external lubricant depending on its composition. PCBV‐45.5 terpolymer (PBA% ~ 45.5%) exhibits outstanding balance both internal and external lubricating roles. SEM‐EDS results show that addition PCBV‐45.5 form a film on the surface of PVC grains as similar as that adding both internal and external lubricants. Fusion characteristics and DMTA demonstrate that PCBV‐45.5 prolongs the fusion time (26% extension, 1.5 phr) and reduces the glass transition temperature (4.0 °C, 1.5 phr). Finally, the mechanical properties of rigid PVC have been greatly improved by using 1.5 phr PCBV‐45.5. In detail, the tensile strength increased from 54 to 59 MPa and the elongation at break increased from 10% to 30%, respectively. Meanwhile, the impact strength of PVC/PCBV‐45.5 is 3.6 times that of the blend without addition. The excellent performance of PCBV exhibited great potential as a polymeric lubricant candidate in rigid PVC composites.

CT scan, EBSD and nanoindentation analysis of 3D-printed parts with post-process heat-treatment

Heat treatment is vital for improving the characteristics of Laser Powder Bed Fusion (LPBF) components. The technique has the potential to change the microstructure of the material as well as its mechanical properties, such as yield strength, hardness, and ultimate tensile strength. To avoid undesirable impacts on the microstructure, temperature, heating, and cooling rates must be precisely controlled. Several parts were printed using LPBF from Steel 316L powder and went through post-process heating. The CT scan analysis revealed that heating the 3D printed parts for 40 min at 900 °C and 950 °C increased the porosity level across the parts although the porosity then decreased after 950 °C. From 850 °C to 1050 °C, EBSD analysis resulted in inverted pole figure maps demonstrating a relative increase in grain size. ImageJ software was used to determine the actual grain size and phase, revealing a grain size growth. Furthermore, as heat treatment temperatures increased, the ferrite phase enlarged. The cellular structure and high temperatures had a major impact on mechanical characteristics. Hardness test findings revealed a decreased mechanical characteristic as heat treatment temperature rose represented by increased porosity population and grain size. To increase the mechanical properties of these materials, an effective strategy is to achieve an even distribution of micro grains while limiting the porosity population.

Biomechanical characteristics of a novel interspinous distraction fusion device in the treatment of lumbar degenerative diseases: a finite element analysis

BackgroundA novel interspinous distraction fusion (ISDF) device has been used to treat lumbar degenerative diseases. As a minimally invasive technique, ISDF differs from the traditional interspinous process distraction devices. Currently, biomechanical studies on ISDF are rare.ObjectiveTo investigate the biomechanical properties of the ISDF device (BacFuse) which is used to treat lumbar degenerative diseases.MethodsThree-dimensional L3-L5 models were created. The models were divided into four groups: intact (M1), local decompression alone (M2), internal fixation alone (M3) and local decompression combined with internal fixation (M4), based on different surgical procedures. Local laminectomy was performed to resect the lower part of the L4 lamina and the upper part of the L5 lamina at the right lamina of L4/5 in the M2 and M4 groups. After meshing the models elements, Abaqus were used to perform the finite element (FE) analysis. The intervertebral range of motion (ROM) was measured during flexion, extension, left lateral bending, right lateral bending, left rotation and right rotation under a follower load of 400 N with a 7.5Nm moment. The distributions of disc and facet joint stresses were observed and recorded. Spinal vertebral stress was compared, and internal fixation device stress was observed.ResultsThe ROM of L4/5 in M2 increased in flexion, extension, left lateral bending, right lateral bending, left rotation and right rotation compared with that in M1. In all motion directions, the ROM at L4/5 decreased, and the ROM at L3/4 increased after implantation of the ISDF device in M3 and M4 groups. The disc stress and facet joint stresses in the instrumented segment decreased after implantation of the ISDF device. The spinous process loaded a certain amount of stress in M3 and M4 groups. The spikes of the internal fixation device were loaded with the maximum stress.ConclusionBacFuse exhibited a reduction in intervertebral ROM, as well as decreased stress on the intervertebral disc and facet joint, while also demonstrating a discernible impact on the upper adjacent segment.

Ash fusion characteristics of iron‐rich coal in Xinjiang under different atmospheres and the influence mechanism of adding red mud and pipeline scale

AbstractTo realize the high‐efficiency utilization of iron‐rich coal, it is necessary to conduct in‐depth research on the ash fusion characteristics and regulation mechanism. In this paper, the ash fusion temperature test of iron‐rich coal in Xinjiang (ZC) under different atmospheres was first carried out. Then, red mud (HJ) from Huajin Aluminum Industry and black water pipe scale (GDG) were selected as the additives. After the same ashing procedure, the two additives were mixed with iron‐rich coal ash in different proportions to realize the regulation of the chemical composition of the coal ash to improve the ash fusion characteristic. The ash fusion temperature (AFT) experiment was carried out in the automatic ash melting point analyzer, and high‐temperature ash melting slags at different temperatures were prepared. The mineral phases of coal ash and slag were characterized by XRD and compared with the Factsage simulation calculation results to reveal the influence mechanism of coal ash fusion temperature. The result shows that the fusion temperature of ZC iron‐rich coal ash is significantly different between oxidizing atmosphere and weak reducing atmosphere. Compared with the oxidizing atmosphere, the four characteristic temperatures of ZC iron‐rich coal ash are significantly lower under weak reducing conditions, and the difference is about 150°C. The addition of red mud and pipeline scale increased the fusion temperature of ZC coal ash to varying degrees. The addition of HJ ash has little effect on the deformation temperature of ZC coal ash, while the addition of different proportions of HJ ash significantly increases the flow temperature of ZC coal ash. When the addition ratio of HJ ash is 40%, the flow temperature FT of ZC coal ash increases most obviously, which is about 50°C. The addition of HJ ash and GDG ash will lead to an increase in the content of iron‐containing spinel, thereby increasing the ash flow temperature.

Investigation on ash fusion characteristics during the co-gasification of coal and textile dyeing sludge

Investigation on ash fusion characteristics during the co-gasification of coal and textile dyeing sludge

Experimental study of particle deposition characteristics in a gasifier: Effect of slag wall temperature

Based on the visualization system, the particle tracking method was used to study the influence of slag wall temperature on the deposition characteristics of coal particles under gasification conditions. The results show that particle deposition can be divided into five types: rebound, rebound after blocking for a distance, crushing, rolling, and adhesion. When slag wall temperature is lower than the deformation temperature, the probability of rebound is over 70%. With the increase of slag wall temperature, the global coefficient of restitution remains constant and then decreases with 1100 °C as the dividing line and the tangential coefficient of restitution concentrates around 0.65. It is proved that the fusion characteristics of slag wall are the main cause of the change in particle deposition on the wall. The collision theory is introducted in the study of deposition characteristics of particles. The collision process is classified into “elastic-plastic collision” and “wet collision”.

Rolling bearing fault diagnosis method based on multi-information fusion characteristics under complex working conditions

To address the problem of low accuracy of traditional neural network models for rolling bearing fault diagnosis under complex working conditions, a novel method based on the multi-information fusion axis attention mechanism (MFA) and improved multi-scale convolutional neural network (MFA-IMSCNN) is proposed. Firstly, a multi-information fusion axis attention mechanism is presented to accurately extract the feature channel information and the number axis location information at various scales. Secondly, a multi-scale dense cyclic feature extraction module (MSDC) is built to improve the feature extraction ability of the MFA-IMSCNN under small sample conditions. The module better captures the potential feature information of time series and ensures the integrity of the information. Finally, two different datasets are imported into the MFA-IMSCNN model to evaluate its effectiveness, and the experimental results verify that the MFA-IMSCNN obtains better classification performance and stronger robustness under various experimental conditions.

Regulation Mechanism of Solid Waste on Ash Fusion Characteristics of Sorghum Straw under O2/CO2 Atmosphere

Co-combustion of solid waste and biomass can alleviate biomass ash-related problems. To investigate the effects of solid waste on the ash fusion characteristics of biomass and its variation mechanisms under an oxidation atmosphere, an X-ray diffraction, thermogravimetric analyzer (TG), scanning electron microscope (SEM), and FactSage calculation were used to examine the ash fusion behaviors of sorghum straw (SS) with the addition of textile dyeing sludge (TDS) or chicken manure (CM). The ash fusion temperature (AFT) of SS increased gradually with the TDS ash addition; with CM ash addition, the AFT of SS mixtures increased rapidly (0–20%), decreased slightly (20–30%), and finally increased slowly (30–60%). The generations of high melting point (MP) minerals (e.g., KAlSi2O6, Fe2O3, and Fe3O4) led to an increase in the AFT of TDS-SS mixtures. The K+ in silicate was gradually replaced by Mg2+ or Ca2+, which caused the generations of high-MP minerals (e.g., Ca3MgSi2O8, Ca2MgSi2O7, and CaMgSiO4). The TG analysis showed that the additions of TDS or CM ash slowed down the weight loss of SS mixed ash due to the formation of high-MP minerals. The SEM and FactSage calculations were also explained with the AFT change and their variation mechanisms. The result provided effective references for the AFT regulation during the co-combustion of biomass and solid waste.

Investigation and Optimization of Co-Combustion Efficiency of Food Waste Biochar and Coal

Among the alternative recycling methods for food waste, its utilization as a renewable biomass resource has demonstrated great potential. This study presents empirical findings pertaining to the cofiring of solid biomass fuel and coal for power generation. Various co-combustion ratios involving food waste biochar (FWB) and coal (100:0, 85:15, 90:10, 95:5, and 0:100) were tested to optimize combustion efficiency, monitor the emissions of NOX, CO, and unburned carbon (UBC), assess ash deposition tendencies, and evaluate grindability. Two types of FWB and sewage sludge were selected as biomass fuels. The results demonstrated that co-combustion involving FWB reduced NOX and UBC emissions compared to coal combustion alone. In particular, the 10% FWB_A blend exhibited the best combustion efficiency. Notably, FWB demonstrated lower tendencies for ash deposition. The ash fusion characteristics were monitored via thermomechanical analysis (TMA), and the corresponding shrinkage levels were measured. Furthermore, FWB exhibited superior grindability compared to both coal and sewage sludge, reducing power consumption during fuel preparation. This study suggests that FWB is a valuable co-combustion resource in coal-fired power plants, thereby facilitating the efficient recycling of food waste while concurrently advancing clean energy generation. Nevertheless, further research is required to validate its practical applicability and promote its use as a renewable resource.

Study on effect of furfural residue addition on fusion characteristics of gasification coal ash

The co-gasification of furfural residue with coal is a feasible way to realize its clean and efficient utilization, but there is a high content of alkaline components in the furfural residue ash. Therefore, the effect of furfural residue addition on the fusion temperature of gasification coal ash was investigated, in which a typical furfural residue and two gasification coals with different ratios of silicon to aluminum (Si/Al) were selected. X-ray diffraction instrument (XRD) was used to measure the mineral evolution of co-gasification ash at different temperatures. The phase change in equilibrium state was calculated by the software FactSage. The results show that with the increase in furfural residue addition ratio, the fusion temperatures of both gasification coal ashes first increase and then decrease, while the increase trend of fusion temperatures for the coal with a high Si/Al ratio is more significant. When the furfural residue is added, the resulting high melting point mineral of gasification slag is changed from anorthite (CaAl2Si2O8) to leucite (KAlSi2O6) that is still present as a solid phase at 1300 °C, resulting in an increase of AFTs. The coal ash with more amount of SiO2 can react with K2O to produce more leucite (KAlSi2O6) with a higher fusion point, thus causing the ash fusion temperatures to rise. However, as the ratio of furfural residue addition continues to increase, the ash fusion temperatures decrease, which is attributed to the formation of kaliophilite (KAlSiO4) with a low fusion point that is generated in the presence of higher content of K2O.

Novel insights into molecular patterns of ROS1 fusions in a large Chinese NSCLC cohort: a multicenter study.

ROS proto-oncogene 1, receptor tyrosine kinase (ROS1) rearrangements are a crucial therapeutic target in non-small cell lung cancer (NSCLC). However, there is limited comprehensive analysis of the molecular patterns of ROS1 fusions. This study aimed to address this gap by analysing 135 ROS1 fusions from 134 Chinese NSCLC patients using next-generation sequencing (NGS). The fusions were categorized into common and uncommon based on their incidence. Our study revealed, for the first time, a unique distribution preference of breakpoints within ROS1, with common fusions occurring in introns 31-33 and uncommon fusions occurring in introns 34 and 35. Additionally, we identified previously unknown breakpoints within intron 28 of ROS1. Furthermore, we identified a close association between the distribution patterns of fusion partners and breakpoints on ROS1, providing important insights into the molecular landscape of ROS1 fusions. We also confirmed the presence of inconsistent breakpoints in ROS1 fusions between DNA-based NGS and RNA-based NGS through rigorous validation methods. These inconsistencies were attributed to alternative splicing resulting in out-of-frame or exonic ROS1 fusions. These findings significantly contribute to our understanding of the molecular characteristics of ROS1 fusions, which have implications for panel design and the treatment of NSCLC patients with ROS1 rearrangements.

Transformation behavior of potassium-containing minerals during co-gasification of petroleum coke and biomass

Interactions between alkali metals in biomass and silicon and aluminum minerals in petroleum coke (PC) are closely related to the gasification reactivity and the deactivation of active K-catalyst during co-gasification. This study comprehensively investigated the evolution of K-containing minerals and their impact on the gasification reactivity and ash fusion characteristics during the co-gasification of PC and wheat straw (WS). The results showed that the addition of WS improved the gasification reactivity of PC, but only up to a certain point due to the K-containing mineral evolutions at high temperatures. Adding WS below 20 wt% resulted in the deactivation of K and the formation of inert kaliophilite and nepheline. However, when WS addition exceeded 20 wt%, a substantial amount of K acted as an active K-catalyst, significantly increasing gasification reactivity. The shrinking core model was found to be more appropriate than the homogeneous model when considering gasification kinetics during co-gasification.

Short-Term Prediction of Time-Varying Passenger Flow for Intercity High-Speed Railways: A Neural Network Model Based on Multi-Source Data

The accurate prediction of passenger flow is crucial in improving the quality of the service of intercity high-speed railways. At present, there are a few studies on such predictions for railway origin–destination (O-D) pairs, and usually only a single factor is considered, yielding a low prediction accuracy. In this paper, we propose a neural network model based on multi-source data (NN-MSD) to predict the O-D passenger flow of intercity high-speed railways at different times in one day in the short term, considering the factors of time, space, and weather. Firstly, the factors that influence time-varying passenger flow are analyzed based on multi-source data. The cyclical characteristics, spatial and temporal fusion characteristics, and weather characteristics are extracted. Secondly, a neural network model including three modules is designed based on the characteristics. A fully connected network (FCN) model is used in the first module to process the classification data. A bi-directional Long Short-Term Memory (Bi-LSTM) model is used in the second module to process the time series data. The results of the first module and the second module are spliced and fused in the third module using an FCN model. Finally, an experimental analysis is performed for the Guangzhou–Zhuhai intercity high-speed railway in China, in which three groups of comparison experiments are designed. The results show that the proposed NN-MSD model can predict many O-D pairs with a high and stable accuracy, which outperforms the baseline models, and multi-source data are very helpful in improving the prediction accuracy.

Multi-dataset fusion for multi-task learning on face attribute recognition

The goal of face attribute recognition(FAR) is to recognize the attributes of face images, such as gender, race, etc. Multi-dataset fusion aims to train a network with multiple datasets simultaneously, which has significant advantages in deep learning. For example, in FAR, the attribute labels differ with the datasets. When using multi-dataset fusion on FAR, training data and attribute labels can be increased so that the network performance can be improved and more attributes can be recognized simultaneously. Currently, most related researchers take the multi-task learning approach on FAR, where each attribute is treated as a recognition task. However, the existing multi-task learning framework cannot be applied when using multi-dataset fusion on FAR. That is because multi-task learning requires the training data to contain the labels of all tasks, but no data contains all the attribute labels of multiple datasets. A Multi-Dataset and Multi-Task Framework(MDMTF) that takes knowledge distillation as the core is proposed in this paper to deal with the problem above. Three distillation strategies are designed in the MDMTF according to the characteristics of multi-dataset fusion on FAR. Experimental results on CelebA and MAAD-Face datasets demonstrate the effectiveness of our framework and strategies. Compared to training two networks on both datasets, respectively, that is, single dataset training, our method has significant advantages in accuracy, parameters, and computational complexity.

The effects of Na2O/K2O flux on ash fusion characteristics for high silicon-aluminum coal in entrained-flow bed gasification

Composite additives are widely used to regulate coal ash fusion characteristics to meet the requirement of entrained-flow bed gasification. In this paper, the effects and corresponding mechanisms of the Na2O/K2O ratio on ash fusion behavior of high silicon-aluminum coal (Jincheng coal, JC) were investigated. The results showed that at the same total mass fractions of Na2O and K2O (15%), the JC ash fusion temperatures (AFTs) decreased quickly and then increased slowly with increasing Na2O/K2O ratio, the lowest AFT reached when Na2O/K2O ratio was at 9/6. The variations in volume and morphology of mixed JC ashes during heating indicated the AFT variation. The mineral change from KAlSi2O6 (MP: 1686 °C) to NaAlSiO4 (MP: 1100 °C) with increasing Na2O/K2O mass ratio mainly resulted in a decrease in the AFT. This indicated that the Na2O/K2O synergy flux effect was related to the formation of a NaAlSiO4–KAlSiO4 eutectic structure. The AFT variation with increasing Na2O/K2O ratio was also explained by the fact that a quick increase and then a slow decrease in the temperature at which all solid phase changes into liquid-phase was calculated by FactSage.

Graph Convolutional-Based Deep Residual Modeling for Rumor Detection on Social Media

The popularity and development of social media have made it more and more convenient to spread rumors, and it has become especially important to detect rumors in massive amounts of information. Most of the traditional rumor detection methods use the rumor content or propagation structure to mine rumor characteristics, ignoring the fusion characteristics of the content and structure and their interaction. Therefore, a novel rumor detection method based on heterogeneous convolutional networks is proposed. First, this paper constructs a heterogeneous map that combines both the rumor content and propagation structure to explore their interaction during rumor propagation and obtain a rumor representation. On this basis, this paper uses a deep residual graph convolutional neural network to construct the content and structure interaction information of the current network propagation model. Finally, this paper uses the Twitter15 and Twitter16 datasets to verify the proposed method. Experimental results show that the proposed method has higher detection accuracy compared to the traditional rumor detection method.

The Reinventing of public administration in the new hybrid world

The turbulent environment pushes public administration to its limits, resulting in revolutionary changes. When the pandemic hit the world in early 2020, public administration was faced not only with complex problems, but also tumultuous challenges marked by the emergence of unpredictable events. In the new hybrid world, public administration has evolved into a distinct model that enables organizations to use new and emerging technologies. By redefining the characteristics of speed, ethics, and fusion, this article aims to contribute to the discussion of how a hybrid approach to public administration may contribute to ongoing debates.

Acid gas emission and ash fusion characteristics of multi-component leather solid waste incineration in bubbling fluidized bed

The tanning sludge (TS) and other tanning solid wastes are produced in significant quantities by the leather industry. To evaluate the combustion properties, acid gaseous pollutant conversion, and ash management, co-firing of TS with various wastes was investigated in a bubbling fluidized bed. TG-FTIR test indicated that tanning solid wastes had superior combustion properties and include more gaseous pollutants than TS. The leather mixed solid waste (LMSW) formed by mixing had better fuel characteristics than TS. The conversion rates of SO2 and HCl of LMSW incineration were 67% and 40%, respectively. The co-combustion of TS and solid wastes reduces the conversion rate of acid gas. Increasing the proportion of high-inorganic chlorine raw material could further reduce the conversion rate and increase the ash fusion temperature appropriately. Because ash and slag were primarily composed of Ca and Fe elements, the addition of calcium carbonate (CaCO3) can increase ash melting point while reducing acid gas emissions. When CaCO3 was added at a calcium to sulfur (Ca/S) ratio of 2, the acid gas emission was reduced by more than 80% and the softening temperature was raised by 90 °C. When Ca/S is greater than 2, the economics of adding CaCO3 decreased.