A brief introduction to recent applications of several sediment-analysis techniques in palaeolimnological studies-dry bulk density and water content, mineral magnetism, carbonate content, and content of total organic carbon,nitrogen content and carbon/ni

Determination of dry bulk density and water content measurement of magnetic susceptibility (x) and saturation isothermal remanent magnetization (SIRM), determination of carbonate content, and determination of total organic carbon (TOC) content nitrogen content (N%) and carbon/nitrogen (C/N) ratio are some of the techniques which have been widely applied to lacustrine-sediment analyses. The techniques,complemented by others, are usually useful for revealing characteristics of lacustrine-sediments and thus for postulating hydrological regimes in the lake and environmental conditions and human activity around it in palaeolimnological studies. A very brief review is presented on recent applications of these techniques in palaeolimnological work with English literatures published mainly since 1985 and focus given on interpretations of results of these analyses related to palaeoenvironmental reconstructions. Low dry bulk density and high water content often imply relatively warm and wet conditions. High X and SIRM are usually resulted from reduced dilutions in the lake and intensified erosions on its catchment. both of which can be in turn attributed to environmental changes. While variations in patterns of X and SIRM may give further insight on mineral magnetism and thus implications on environmental conditions. Increased carbonate content seems likely to associate to warm and dry conditions.Increased TOC content is virtually used as one of indicators of warm and wet conditions and variations in C/N ratio may hint variations in relative contributions of different sources, aquatic and terrestrial, to the total organic matter in lake sediments and hence to lake-level fluctuations and climate changes.

Stratal Carbonate Content Inversion Using Seismic Data and Its Applications to the Northern South China Sea

On the basis of the relationship between the carbonate content and the stratal velocity and density, an exercise has been attempted using an artificial neural network on high-resolution seismic data for inversion of carbonate content with limited well measarements as a control. The method was applied to the slope area of the northern South China Sea near ODP Sites 1146 and 1148, and the results are satisfaetory. Before inversion calculation, a stepwise regression method was applied to obtain six properties related most closely to the carbonate content variations among the various properties on the seismic profiles across or near the wells. These include the average frequency, the integrated absolute amplitude, the dominant frequency, the reflection time, the derivative instantaneous amplitude, and the instantaneous frequency. The results, with carbonate content errors of mostly ±5 % relative to those measured from sediment samples, show a relatively accurate picture of carbonate distribution along the slope profile. This method pioneers a new quantitative model to acquire carbonate content variations directly from high-resolution seismic data. It will provide a new approach toward obtaining substitutive high-resolution sediment data for earth system studies related to basin evolution, especially in discussing the coupling between regional sedimentation and climate change.

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.

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.

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.

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.

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.

Validating the deep time carbonate carbon isotope records: effect of benthic flux on seafloor carbonate

It is a consensus that marine carbonate archives the isotopic composition of seawater dissolved inorganic carbon(DIC,δ13Csw),the largest active C reservoir in the hydrosphere.Carbonate carbon isotope(δ13Ccarb)excursions have been used to reflect perturbations of the global carbon cycle and related environmental change.However,the deep timeδ13Ccarb records indicate faster and more pronounced perturbations of the carbon cycle compared to the present day.Here,we reportδ13Ccarb and elemental compositions of Late Paleozoic carbonate sections from South China,showing negative correlations betweenδ13-Ccarb and Fe^(2+)content of carbonate(Fecarb).We suggest that,because Late Paleozoic carbonate was mainly produced by benthic carbonate-secreting organisms,δ13Ccarbrecorded the isotopic composition near the seafloor,where benthic flux derived from anaerobic organic matter degradation delivers both Fe2+and 13C-depleted DIC from porewater.The binary mixing between seawater and benthic flux would result in the deviation ofδ13Ccarb fromδ13Csw.The negative correlation implies thatδ13Ccarb is influenced by benthic flux and is affected by the seafloor redox and sedimentation rate.The deep time spatially heterogeneous and temporally oscillatoryδ13Ccarb records in the basin-scale could be alternatively attributed to the variations of local environmental factors rather than aδ13Csw depth-gradient.Thus,the seafloor carbonate precipitation is continuously affected by diagenetic reactions in sediments,suggesting thatδ13Ccarb recording the seawater DIC composition is conditional.Our study urges that the interpretation ofδ13Ccarb should also consider the sedimentary process and depositional environment of marine carbonate.

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 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.

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.

Paleoenvironmental records from the northern South China Sea since the Last Glacial Maximum

Core ZHS-176 contains the paleoenvironmental records from the northern South China Sea （NSCS） since the Last Glacial Maximum （LGM）. A coupled approach based on clay mineral assemblages, planktonic foraminiferal oxygen and carbon isotopes, and calcium carbonate content is used to trace the sources of the fine-grained sediment and to investigate the paleoenviornmental evolution in this area. Clay mineral assemblages are dominated by illite （average about 39%） and chlorite （about 27%）, which comes mainly from Taiwan and the East China Sea. Kaolinite, which accounts for about 13%, comes mainly from the Zhujiang （Pearl） River, and Luzon Island is the main source for smectite （about 21%）. The planktonic foraminiferal oxygen isotopic oscillations during the last glacial period are coeval with climate variations recorded in the Greenland ice core and Western Pacific sediment. These variations include the LGM, Heinrich event 1, Bφlling-Allerφd （B/A）, and Younger Dryas. For the Holocene, three periods of strong precipitation （S1-S3） and three periods of weak precipitation （W1-W3） are identified. The oxygen isotopic record exhibits corre-lation with climate records from distant regions, including the high-latitude Northern Hemisphere, providing evidence for global tele-connection among regional climate. A brief, negative planktonic foraminiferal carbon isotopic excursion during B/A reflects increased methane released from marine gas hydrate due to the rapid warming of the water. By comparing calcium carbonate content curves of the core ZHS-176 with these of other five boreholes lying above the lysocline, a remarkable low calcium carbonate event is found during the early Holocene in NSCS.

Soil carbon pool in China and its global significance

Soil organic carbon density and its related characteristics of 41 soil types all over China were analyzed by using data of 745 soil profiles , and size of soil carbon pool was estimated. As a result, area-weighted averages of these 41 soil types for bulk density, profile depth, organic carbon content and profile carbon were 1. 24 tC/m3, 86. 2 cm, 3. 04% and 19. 7 kg C/m2 respectively. Total size of soil carbon pool was 185. 68 × 1009tC, which is 29 times of that in terrestrial biomass of China and 12. 6% of global soil carbon pools. Because of its huge carbon pool, soil of China plays an important role in global carbon cycle.

EFFECT OF CHEMICAL COMPOSITION ON RETAINED AUSTENITE IN TRIP STEEL

The systematic chemical compositions including common C, Si, Mn, Al, and micro-alloying elements of Ti and Nb were designed for high volume fraction of retained austenite as much as possible. The thermo-cycle experiments were conducted by using Gleeble 2000 thermo-dynamic test machine for finding the appropriate composition. The experimental results showed that chemical composition had a significant effect on retained austenite, and the appropriate compositions were determined for commercial production of TRIP steels.

Characterization of the Songhua River sediments and evaluation of their adsorption behavior for nitrobenzene

The explosion at a plant of the Jilin Petrochemical Corporation on 13 November,2005,and the spill of an estimated 100 t of toxic substances (nitrobenzene as the main component) into the Songhua River received worldwide attention.This study has focused on the adsorption behavior of nitrobenzene that spilled onto sediments along the Songhua River,which was one of the efforts to evaluate the fate of nitrobenzene after the spillage event.The organic carbon contents of these sediments along the Songhua River var...