Influence of Carbon Content on Element Diffusion in Silicon Carbide-Based TRISO Composite Fuel

The coating layers of Tri-structural Isotropic Particles(TRISO)serve to protect the kernel and act as barriers to fission products.Sintering aids in the silicon carbide matrix variably react with TRISO coating layers,leading to the destruction of the coating layers.Investigating how carbon content affects element diffusion in silicon carbide-based TRISO composite fuel is of great significance for predicting reactor safety.In this study,silicon carbide-based TRISO composite fuels with different carbon contents were prepared by adding varying amounts of phenolic resin to the silicon carbide matrix.X-ray Diffraction(XRD)and Scanning Electron Microscopy(SEM)were employed to characterize the phase composition,morphology,and microstructure of the composite fuels.The elemental content in each coating layer of TRISO was quantified using Energy-Dispersive X-ray Spectroscopy(EDS).The results demonstrated that the addition of phenolic resin promoted the uniform distribution of sintering aids in the silicon carbide matrix.The atomic percentage(at.%)of aluminum(Al)in the pyrolytic carbon layer of the TRISO particles reached its lowest value of 0.55%when the phenolic resin addition was 1%.This is because the addition of phenolic resin caused the Al and silicon(Si)in the matrix to preferentially react with the carbon in the phenolic resin to form a metastable liquid phase,rather than preferentially consuming the pyrolytic carbon in the outer coating layer of the TRISO particles.The findings suggest that carbon addition through phenolic resin incorporation can effectively mitigate the deleterious reactions between the TRISO coating layers and sintering aids,thereby enhancing the durability and safety of silicon carbide-based TRISO composite fuels.

Total organic carbon content logging prediction based on machine learning:A brief review

The total organic carbon content usually determines the hydrocarbon generation potential of a formation.A higher total organic carbon content often corresponds to a greater possibility of generating large amounts of oil or gas.Hence,accurately calculating the total organic carbon content in a formation is very important.Present research is focused on precisely calculating the total organic carbon content based on machine learning.At present,many machine learning methods,including backpropagation neural networks,support vector regression,random forests,extreme learning machines,and deep learning,are employed to evaluate the total organic carbon content.However,the principles and perspectives of various machine learning algorithms are quite different.This paper reviews the application of various machine learning algorithms to deal with total organic carbon content evaluation problems.Of various machine learning algorithms used for TOC content predication,two algorithms,the backpropagation neural network and support vector regression are the most commonly used,and the backpropagation neural network is sometimes combined with many other algorithms to achieve better results.Additionally,combining multiple algorithms or using deep learning to increase the number of network layers can further improve the total organic carbon content prediction.The prediction by backpropagation neural network may be better than that by support vector regression;nevertheless,using any type of machine learning algorithm improves the total organic carbon content prediction in a given research block.According to some published literature,the determination coefficient(R^(2))can be increased by up to 0.46 after using machine learning.Deep learning algorithms may be the next breakthrough direction that can significantly improve the prediction of the total organic carbon content.Evaluating the total organic carbon content based on machine learning is of great significance.

Non-intrusive soil carbon content quantification methods using machine learning algorithms:A comparison of microwave and millimeter wave radar sensors

Agricultural and forestry biomass can be converted to biochar through pyrolysis gasification,making it a significant carbon source for soil.Applying biochar to soil is a carbon-negative process that helps combat climate change,sustain soil biodiversity,and regulate water cycling.However,quantifying soil carbon content conventionally is time-consuming,labor-intensive,imprecise,and expensive,making it difficult to accurately measure in-field soil carbon’s effect on storage water and nutrients.To address this challenge,this paper for the first time,reports on extensive lab tests demonstrating non-intrusive methods for sensing soil carbon and related smart biochar applications,such as differentiating between biochar types from various biomass feedstock species,monitoring soil moisture,and biochar water retention capacity using portable microwave and millimeter wave sensors,and machine learning.These methods can be scaled up by deploying the sensor in-field on a mobility platform,either ground or aerial.The paper provides details on the materials,methods,machine learning workflow,and results of our investigations.The significance of this work lays the foundation for assessing carbon-negative technology applications,such as soil carbon content accounting.We validated our quantification method using supervised machine learning algorithms by collecting real soil mixed with known biochar contents in the field.The results show that the millimeter wave sensor achieves high sensing accuracy(up to 100%)with proper classifiers selected and outperforms the microwave sensor by approximately 10%–15%accuracy in sensing soil carbon content.

Soil Organic Carbon Content and Distribution in a Small Landscape of Dongguan, South China

Global warming has become an increasing concern, and using soil as a carbon sink to sequester carbon dioxide has attracted much attention in recent years. In this study, soil organic carbon (SOC) content and organic carbon density were estimated based on a soil survey of a small landscape in Dongguan, South China, with spatial heterogeneity of SOC distribution and the impacts of land-use patterns on soil organic carbon content assessed. Field sampling was carried out based on a 150 m×150 m grid system overlaid on the topographic map of the study area and samples were collected in three 20-cm layers to a depth of 60 cm. Spatial variability in the distribution of SOC was assessed using the Kruskal-Wallis test. Results showed that SOC in the topsoil layer (0-20 cm) was not much higher or even lower in some sites than the underlying layers, and except for the two sites covered with natural woodland, it did not exhibit a pronounced vertical gradient. The difference in both horizontal and vertical distribution of SOC was not statistically significant. However, in the topsoil layer among land-use/land-cover patterns, significant differences (P≤0.05) in SOC distribution existed, indicating that management practices had great impact on SOC content. SOC storage in the study area to a depth of 20, 40, and 60 cm was estimated as 2.13×106 kg, 3.46×106 kg, and 4.61×106 kg, respectively.

Quantitative Analysis of Carbon Content in Bituminous Coal by Laser-Induced Breakdown Spectroscopy Using UV Laser Radiation

The carbon content of bituminous coal samples was analyzed by laser-induced breakdown spectroscopy. The 266 nm laser radiation was utilized for laser ablation and plasma generation in air. The partial least square method and the dominant factor bused PLS method were used to improve the measurement accuracy of the carbon content of coal. The results showed that the PLS model could achieve good measurement accuracy, and the dominant factor based PLS model could further improve the measurement accuracy. The coefficient of determination and the root-mean-square error of prediction of the PLS model were 0.97 and 2.19%, respectively; and those values for the dominant factor based PLS model were 0.99 and 1.51%, respectively. The results demonstrated that the 266 nm wavelength could accurately measure the carbon content of bituminous coal.

EFFECTS OF CARBON CONTENT AND ROLLING PROCESSING ON RETAINED AUSTENITE FOR HOT-ROLLED TRIP STEELS

The effects of finishing rolling temperature and coiling temperature on retained austen-ite were studied for hot-rolled transformation induced plasticity (TRIP) steels with different carbon content. The experimental results showed that an appropriate volume fraction of retained austenite from 6% to 11% could be obtained according to the different carbon content less than 0.20% by controlled finishing rolling and coiling for the hot-rolled TRIP steels. It can be concluded that carbon content has a significant effect on the fraction of retained austenite and coiling processing plays stronger role on retaining austenite than fishing rolling processing.

Morphology and carbon content of WC-6%Co nanosized composite powders prepared using glucose as carbon source

Pure WC-6%Co nanosized composite powders were synthesized via a low-temperature method.The effects of carbon source on microstructure characteristic of composite powders were investigated,and the effects of heat-treatment parameter on carbon content of composite powders were also discussed.The results of SEM and XRD revealed that the carbon decomposing from glucose was more active than carbon black.Therefore,WC-Co nanosized composite powders could be synthesized at 900°C for 1 h under a hydrogen atmosphere.The individual WC grains were bonded together into a long strip under the action of cobalt.The results of carbon analysis revealed that the total carbon content decreased with the increase of the temperature in the range of 800-1000°C.Moreover,the total carbon content and the compounded carbon increased with the increase of the flow rate of H2 in the range of 1.1-1.9 m3/h.

Effects of carbon content and solidification rate on thermal conductivity of grey cast iron

The thermal conductivity or diffusivity of pearlitic grey irons with various carbon contents is investigated by the laser flash method. The materials are cast in controlled thermal environments and produced in three dissimilar cooling rates. The cooling rate together with the carbon content largely influence the thermal conductivity of grey iron. Linear relationships exist between the thermal conductivity and the carbon content,the carbon equivalent and the fraction of former primary solidified austenite transformed into pearlite. The work shows that optimal thermal transport properties are obtained at medium cooling rates. Equations describing the thermal conductivity of pearlite,solidified as pre-eutectic austenite,and the eutectic of grey iron are derived. The thermal conductivity of pearlitic grey iron is modeled at both room temperature and elevated temperature with good accuracy.

Reduction of Cr(Ⅵ) with a relative high concentration using different kinds of zero-valent iron powders: Focusing on effect of carbon content and structure on reducibility

Reduction of Cr(VI)using zero-valent iron(ZVI)could not only decrease the amounts of chemicals used for reduction,but also decrease the discharge of sludge.In order to find a desirable ZVI material,reduction of Cr(VI)with a relative high concentration using different kinds of ZVI powders(mainly carbon differences)including reduced Fe,grey cast iron,pig iron,nodular pig iron was carried out.Parameters such as ZVI dosage,type and size affecting on Cr(VI)reduction were firstly examined and grey cast iron was selected as a preferable reducing material,followed by pig iron.Additionally,it was found that the parameters had significant influences on experimental kinetics.Then,morphology and composition of the sample before and after reaction were characterized by SEM,EPMA and XPS analyses to disclose carbon effect on the reducibility.In order to further interpret reaction mechanism,different reaction models were constructed.It was revealed that not only the carbon content could affect the Cr(VI)reduction,but also the carbon structure had an important effect on its reduction.

Influence of Carbon Content on S Zorb Sorbent Activity

The reaction activity of S Zorb sorbents with different sulfur contents was investigated, and the structure and composition of carbon-containing sorbents were characterized by XRD, FT-IR and TG-MS in order to delve into the kind and morphology of carbon on the sorbent. Test results have revealed that coke could be deposited on the S Zorb sorbent during the operating process, and the coke content was an important factor influencing the reaction performance of the S Zorb sorbent. Retention of a definite amount of coke on the sorbent while securing the desulfurization activity of the S Zorb sorbent would be conducive to the reduction of octane loss of reaction product.

Effect of carbon content on microstructure of in-situ Al_2O_(3p)-TiC_p/Al composites

The in situ Al 2O 3p TiC p/Al composite was fabricated by XD (exothermic dispersion) process in TiO 2 Al C system, and the effect of carbon content on the microstructure of the fabricated composite and the reactive temperature characteristics had been studied. The results show that carbon content affects the microstructure and reactive temperature of Al 2O 3p TiC p/Al composite greatly. The quantity of TiC phases in the fabricated composites increases, while the Al 3Ti phases reduces with increasing carbon content. And when C/TiO 2 molecular ratio is equal to one, the Al 3Ti phase nearly disappears. High temperature metallurgical field caused by strong exothermic reaction influences the synthetic reaction greatly, and higher synthetic temperature was favorable to the synthesis of Al 2O 3p TiC p reinforce particles.

EFFECT OF CARBON CONTENT ON MICROSTRUCTURE AND PROPERTIES OF HIGH STRENGTH AND HIGH ELONGATION STEELS

The micro structure and mechanical properties of new kind of hot-rolled high strength and high elongation steels with retained austenite were studied by discussing the influence of different carbon content. The research results indicate that carbon content has a significant effect on retaining austenite and consequently resulting in high elongation. Besides, new findings about relationship between carbon content and retained austenite as well as properties were discussed in the paper.

Assessing canopy nitrogen and carbon content in maize by canopy spectral reflectance and uninformative variable elimination

Assessing canopy nitrogen content(CNC) and canopy carbon content(CCC) of maize by hyperspectral remote sensing data permits estimating cropland productivity, protecting farmland ecology, and investigating the nitrogen and carbon cycles in the atmosphere. This study aimed to assess maize CNC and CCC using canopy hyperspectral information and uninformative variable elimination(UVE). Vegetation indices(VIs) and wavelet functions were adopted for estimating CNC and CCC under varying water and nitrogen regimes. Linear, nonlinear, and partial least squares(PLS) regression models were fitted to VIs and wavelet functions to estimate CNC and CCC, and were evaluated for their prediction accuracy.UVE was used to eliminate uninformative variables, improve the prediction accuracy of the models, and simplify the PLS regression models(UVE-PLS). For estimating CNC and CCC, the normalized difference vegetation index(NDVI, based on red edge and NIR wavebands) yielded the highest correlation coefficients(r > 0.88). PLS regression models showed the lowest root mean square error(RMSE) among all models. However, PLS regression models required nine VIs and four wavelet functions, increasing their complexity. UVE was used to retain valid spectral parameters and optimize the PLS regression models.UVE-PLS regression models improved validation accuracy and resulted in more accurate CNC and CCC than the PLS regression models. Thus, canopy spectral reflectance integrated with UVE-PLS can accurately reflect maize leaf nitrogen and carbon status.

Influences of Carbon Content on the Properties and Microstructure of Ultrafine WC-10Co Cemented Carbide

WC-10Co nanocrystalline composite powders prepared by spray pyrogenation-continuous reduction and carburization technology were consolidated by vacuum sintering plus hot isostatic pressing （HIP）. Influences of carbon content on properties and microstructure of ultrafine WC-10Co cemented carbide were investigated. The results show that the relative density of the ultrafine WC-10Co cemented carbides can reach 99.72%, and the transverse rupture strength （TRS） was higher than 3 890 MPa, Rockwell A hardness （HRA） was higher than 92.5, the average grain size was less than 460 nm, when carbon content in nanocrystalline composite powder was 5.54wt% and the ball-milled time was 48 hours, ultrafine WC-10Co cemented carbide with excellent properties and homogeneous microstructure was obtained.

INFLUENCE OF CARBON CONTENT OF MARTENSITE STEELS ON HARDNESS RE-DISTRIBUTION NEAR WORN SURFACE

After three-body abrasion, the hardness re-distribution near the worn surface has a close relationship with the carbon content of martensite steel. It is considered that there is a competition between the work-hardening and the temper softening, which results from deformation and friction heat of material. When the carbon content of martensite steel is below about 0.6%, the subsurface hardness distribution of material is a softened layer sandwiched between two hardened layers, but above 0.6%C, no softened region appears on the hardness re-distribution curve.

Application of a Method for Calculating the Organic Carbon Content by Well Logs to Faulted Basins

The source rock model used in this project was developed by French Petroleum Research Institute. The total organic carbon content was estimated primarily and directly by using continuous conventional logging curves (such as sonic and resistivity curves), which are calibrated through the laboratory analysis data of organic carbon of cores, cuttings or sidewall cores. Regional evaluations have been carried out in downwarping basins abroad. The Haila′er Basin is a faulted basin and the evaluation of such a basin is a new subject. On the basis of a regional evaluation method for the downwarping basins, a new method suitable to faulted basins was developed. The effect is satisfactory when this new method is applied to the Wu′erxun Sag and the Bei′er Sag.

STUDY ON THE VARIATION MECHANISM OF CARBON CONTENT OF LIQUID IRON IN MELTING GASIFIER

This paper studied the changing principles of carbon content in direct reduction iron (DRI) and liquid iron in the COREX melting gasifier. Under the normal working conditions of experimental equipment, liquid nitrogen was poured into the melting gasifier from its tuyere to cool down quickly. And then seven cross sections were made to study the carburization reaction and its characteristics of the solid iron and the liquid iron, and also the reaction of carbon between the slag and the metal. According to the results, the influences of the thickness of the semi-coke layer and the temperature on the carbon content of liquid iron in the COREX melting gasifier were confirmed.

EFFECT OF CARBON CONTENT ON PROPERTIES OF SLACK-QUENCHED RAILS

A comparative investigation was carried out of the routine mechanical properties,fracture toughness,microstructure and hardness of slack-quenched rails containing different carbon contents.After the rails slack-quenched,their strength and toughness,together with ductility, are obviously improved,and the higher the quench hardening is,the more the resistance to wear and shell will be.Discussion was also made of the reason for this improvement and of the effect of carbon content and quench hardening on the properties of rails in combination with the rail-laying trial.

Effect of Melting Iron-Based Alloy Temperature on Carbon Content Observed in Laser-Induced Breakdown Spectroscopy

Our recent work has determined the carbon content in a melting ferroalloy by laser- induced breakdown spectroscopy （LIBS）. The emission spectrum of carbon that we obtained in the laboratory is suitable for carbon content determination in a melting ferroalloy but we cannot get the expected results when this method is applied in industrial conditions： there is always an unacceptable error of around 4% between the actual value and the measured value. By comparing the measurement condition in the industrial condition with that in the laboratory, the results show that the temperature of the molten ferroalloy samples to be measured is constant under laboratory conditions while it decreases gradually under industrial conditions. However, temperature has a considerable impact on the measurement of carbon content, and this is the reason why there is always an error between the actual value and the measured value. In this paper we compare the errors of carbon content determination at different temperatures to find the optimum reference temperature range which can fit the requirements better in industrial conditions and, hence, make the measurement more accurate. The results of the comparative analyses show that the measured value of the carbon content in molten state （1620 K） is consistent with the nominal value of the solid standard sample （error within 0.7%）. In fact, it is the most accurate measurement in the solid state. Based on this, we can effectively improve the accuracy of measurements in laboratory and can provide a reference standard of temperature for the measurement in industrial conditions.

Calculation of carbon content of austenite during heat treatment of cast irons

The austenitizing temperature controls the carbon content of the austenite which,in turn,influences the structure and properties of cast irons after subsequent cooling to room temperature.In this paper,for a cast iron with known silicon content,a formula of calculating austenite carbon content at a certain austenitizing temperature was developed.This relationship can be used to more accurately select carbon content of austenite or austenitizing temperature to produce desired properties after subsequent cooling to room temperature.