Relativistic Heavy Ion Collider and the Large Hadron Collider for Heavy Ion Fusion

Heavy Ion Fusion makes use of the Relativistic Heavy Ion Collider at Brookhaven National Lab and the Large Hadron Collider in Geneva, Switzerland for Inertial Confinement Fusion. Two Storage Rings, which may or may not initially be needed, added to each of the Colliders increases the intensity of the Heavy Ion Beams making it comparable to the Total Energy delivered to the DT target by the National Ignition Facility at the Lawrence Livermore Lab. The basic Physics involved gives Heavy Ion Fusion an advantage over Laser Fusion because heavy ions have greater penetration power than photons. The Relativistic Heavy Ion Collider can be used as a Prototype Heavy Ion Fusion Reactor for the Large Hadron Collider.

Analysis of Heavy Precipitation Event in Northeast China from August 1 to 5, 2023

This study delves into the multiple weather systems and their interaction mechanisms that caused the severe rainfall event in Northeast China in early August 2023. The analysis reveals that the atmospheric circulation in the mid-to-high latitudes of the Eurasian continent exhibited a significant “two troughs and two ridges” structure, with Northeast China located precisely in the peripheral region of the subtropical high, significantly influenced by its marginal airflows. Additionally, the residual circulation of Typhoon “Doksuri” interacting with the subtropical high and upper-level troughs significantly increased the rainfall intensity and duration in the region. In particular, the continuous and powerful transport of the southwest jet provided the necessary moisture and unstable conditions for the generation and development of convective systems. The rainfall event resulted in nearly 40,000 people affected and crop damage covering an area of approximately 4000 hectares, demonstrating the severity of extreme weather. The study emphasizes that strengthening meteorological monitoring and early warning systems, as well as formulating and improving emergency response mechanisms, are crucial for reducing potential disaster losses caused by heavy rainfall. Future research can further explore the interaction mechanisms among weather systems, limitations of data sources, and the connection between long-term trends of heavy rainfall events and global climate change.

Impacts of Future Changes in Heavy Precipitation and Extreme Drought on the Economy over South China and Indochina

Heavy precipitation and extreme drought have caused severe economic losses over South China and Indochina(INCSC)in recent decades.Given the areas with large gross domestic product(GDP)in the INCSC region are distributed along the coastline and greatly affected by global warming,understanding the possible economic impacts induced by future changes in the maximum consecutive 5-day precipitation(RX5day)and the maximum consecutive dry days(CDD)is critical for adaptation planning in this region.Based on the latest data released by phase 6 of the Coupled Model Intercomparison Project(CMIP6),future projections of precipitation extremes with bias correction and their impacts on GDP over the INCSC region under the fossil-fueled development Shared Socioeconomic Pathway(SSP5-8.5)are investigated.Results indicate that RX5day will intensify robustly throughout the INCSC region,while CDD will lengthen in most regions under global warming.The changes in climate consistently dominate the effect on GDP over the INCSC region,rather than the change of GDP.If only considering the effect of climate change on GDP,the changes in precipitation extremes bring a larger impact on the economy in the future to the provinces of Hunan,Jiangxi,Fujian,Guangdong,and Hainan in South China,as well as the Malay Peninsula and southern Cambodia in Indochina.Thus,timely regional adaptation strategies are urgent for these regions.Moreover,from the sub-regional average viewpoint,over two thirds of CMIP6 models agree that maintaining a lower global warming level will reduce the economic impacts from heavy precipitation over the INCSC region.

Spatio-Temporal Characteristics of Heavy Precipitation Forecasts from ECMWF in Eastern China

This study examines the spatio-temporal characteristics of heavy precipitation forecasts in eastern China from the European Centre for Medium-Range Weather Forecasts(ECMWF) using the time-domain version of the Method for Object-based Diagnostic Evaluation(MODE-TD). A total of 23 heavy rainfall cases occurring between 2018 and 2021 are selected for analysis. Using Typhoon “Rumbia” as a case study, the paper illustrates how the MODE-TD method assesses the overall simulation capability of models for the life history of precipitation systems. The results of multiple tests with different parameter configurations reveal that the model underestimates the number of objects’ forecasted precipitation tracks, particularly at smaller radii. Additionally, the analysis based on centroid offset and area ratio tests for different classified precipitation objects indicates that the model performs better in predicting large-area, fast-moving, and longlifespan precipitation objects. Conversely, it tends to have less accurate predictions for small-area, slow-moving, and shortlifespan precipitation objects. In terms of temporal characteristics, the model overestimates the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. In terms of temporal characteristics, the model tends to overestimate the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. Overall, the model provides more accurate predictions for the duration and dissipation of precipitation objects with large-area or long-lifespan(such as typhoon precipitation) while having large prediction errors for precipitation objects with small-area or short-lifespan. Furthermore, the model’s simulation results regarding the generation of precipitation objects show that it performs relatively well in simulating the generation of large-area and fast-moving precipitation objects. However, there are significant differences in the forecasted generation of small-area and slow-moving precipitation objects after 9 hours.

Characterization of Nutrients,Heavy Metals,Petroleum and Their Impact on Phytoplankton in Laizhou Bay:Implications for Environmental Management and Monitoring

The Laizhou Bay(LB)represents a substantial ecological area that is vulnerable to human activities and confronts diverse environmental challenges.This study provides a comprehensive characterization of nutrients,petroleum,heavy metals,and phytoplankton community structure across seven distinct areas in LB.The results indicate relatively high concentrations of NO_(2)-N,SiO_(4)-Si,and NO_(3)-N in the Southwest Laizhou Bay(SWLB)and Huanghe River Estuary(HRE).In contrast,the East Laizhou bay(ELB)and the North of Huanghe River Estuary(NHRE)exhibit the highest concentrations of heavy metals(As,Cr and Hg).The areas with high phytoplankton density and community diversity are mainly located in the SWLB.After adjusting for basic environmental factors,phytoplankton density and Margalef richness index D are significantly associated with nutrients(NO_(3)-N,NO_(2)-N,NH_(4)-N,SiO_(4)-Si),and heavy metal(Cr)concentrations.We highlight that,in addition to Xiaoqinghe River,nutrients brought by the Mihe River in the SWLB and heavy metal(Cr)pollution in the ELB resulting from industrial and mining activities along the coast significantly influence phytoplankton growth and community structure.Therefore,it is recommended that more monitoring and management efforts be focused on these regions in the future.

Probing the interaction between asphaltene-wax and its effects on the crystallization behavior of waxes in heavy oil via molecular dynamics simulation

High content of asphaltenes and waxes leads to the high pour point and the poor flowability of heavy oil,which is adverse to its efficient development and its transportation in pipe.Understanding the interaction mechanism between asphaltene-wax is crucial to solve these problems,but it is still unclear.In this paper,molecular dynamics simulation was used to investigate the interaction between asphaltenewax and its effects on the crystallization behavior of waxes in heavy oil.Results show that molecules in pure wax are arranged in a paralleled geometry.But wax molecules in heavy oil,which are close to the surface of asphaltene aggregates,are bent and arranged irregularly.When the mass fraction of asphaltenes in asphaltene-wax system(ω_(asp))is 0-25 wt%,the attraction among wax molecules decreases and the bend degree of wax molecules increases with the increase ofω_(asp).Theω_(asp)increases from 0 to 25 wt%,and the attraction between asphaltene-wax is stronger than that among waxes.This causes that the wax precipitation point changes from 353 to 333 K.While theω_(asp)increases to 50 wt%,wax molecules are more dispersed owing to the steric hindrance of asphaltene aggregates,and the interaction among wax molecules transforms from attraction to repulsion.It causes that the ordered crystal structure of waxes can't be formed at normal temperature.Simultaneously,the asphaltene,with the higher molecular weight or the more hetero atoms,has more obvious inhibition to the formation of wax crystals.Besides,resins also have an obvious inhibition on the wax crystal due to the formation of asphalteneresin aggregates with a larger radius.Our results reveal the interaction mechanism between asphaltene-wax,and provide useful guidelines for the development of heavy oil.

The mechanisms of thermal solidification agent promoting steam diversion in heavy oil reservoirs

At high cycles of steam huff&puff,oil distribution in reservoirs becomes stronger heterogeneity due to steam channeling.Thermal solidification agent can be used to solve this problem.Its solution is a lowviscosity liquid at normal temperature,but it can be solidified above 80℃.The plugging degree is up to 99%at 250℃.The sweep efficiency reaches 59.2%,which is 7.3%higher than pure steam injection.In addition,simultaneous injection of viscosity reducer and/or nitrogen foams can further enhance oil recovery.The mechanism of this technology depends on its strong plugging ability,which changes the flowing pattern of steam to effectively mobilize remaining oil.Viscosity reducer and nitrogen foams further expand the sweep range and extends the effective period.Therefore,thermal solidification agent can plug steam channeling paths and adjust steam flowing direction to significantly enhance oil recovery at high cycles of steam huff&puff.

Release characteristics and stabilization of heavy metals in antimony tailings in Yunnan Province,China

The pollution caused by the mining and smelting of heavy metals is becoming an increasingly severe environmental problem.In this study,the environmental risks of mine tailings were explored using typical antimony tailings(the depth of the sample taken from the ground to the deepest position of 120 cm)from the Zuoxiguo mine in Yunnan Province,Southwest China.The tailings were examined to explore the geological background,distribution characteristics,and release characteristics of heavy metals.Additionally,stabilizer treatments for heavy metals were investigated in consideration of waste treatment.The results showed that the contents of Sb and As(8.93×103 and 425 mg/kg,respectively)in the tailings were considerably higher than the local soil background values,suggesting that these metals pose a considerable threat to the surrounding environment.The geological background values of Cr,Cd,Pb,Cu,and Zn were relatively low.The results of static release showed that Sb,As,Cd,and Cr leached from the tailings more easily than Cu,Zn,and Pb under acidic conditions(pH=2.98).Geo-accumulation indices and potential ecological risk indices showed that Sb,As,Cd,and Pb were highly enriched in the tailings,whereas Cu,Cr,and Zn contents were relatively low.The single factor ecological risk index of the mining area showed that Sb and As are high ecological risk factors,whereas Cr,Cu,Zn,Cd,and Pb are not.The results of the orthogonal test results showed that by adding 15.0%(m/m)fly ash and 15.0%(m/m)zeolite powder to the quicklime and curing for 28 d,a significant stabilization effect was observed for Sb,As,and Pb.This study helps determine the priority control components for characteristic heavy metals in antimony tailings,and provides valuable insights regarding the formulation of appropriate mitigation strategies.

Influence of pore structure heterogeneity on channeling channels during hot water flooding in heavy oil reservoir based on CT scanning

Hot water flooding is an effective way to develop heavy oil reservoirs.However,local channeling channels may form,possibly leading to a low thermal utilization efficiency and high water cut in the reservoir.The pore structure heterogeneity is an important factor in forming these channels.This study proposes a method that mixes quartz sand with different particle sizes to prepare weakly heterogeneous and strongly heterogeneous models through which hot water flooding experiments are conducted.During the experiments,computer tomography(CT)scanning identifies the pore structure and micro remaining oil saturation distribution to analyze the influence of the pore structure heterogeneity on the channeling channels.The oil saturation reduction and average pore size are divided into three levels to quantitatively describe the relationship between the channeling channel distribution and pore structure heterogeneity.The zone where oil saturation reduction exceeds 20%is defined as a channeling channel.The scanning area is divided into 180 equally sized zones based on the CT scanning images,and threedimensional(3D)distributions of the channeling channels are developed.Four micro remaining oil distribution patterns are proposed,and the morphology characteristics of micro remaining oil inside and outside the channeling channels are analyzed.The results show that hot water flooding is more balanced in the weakly heterogeneous model,and the oil saturation decreases by more than 20%in most zones without narrow channeling channels forming.In the strongly heterogeneous model,hot water flooding is unbalanced,and three narrow channeling channels of different lengths form.In the weakly heterogeneous model,the oil saturation reduction is greater in zones with larger pores.The distribution range of the average pore size is larger in the strongly heterogeneous model.The network remaining oil inside the channeling channels is less than outside the channeling channels,and the hot water converts the network remaining oil into cluster,film,and droplet remaining oil.

Heavy metal pollution of river water and eco-friendly remediation using potent microalgal species

Pollution of rivers is mainly caused by anthropogenic activities such as discharge of effluent from industrial facilities,maintenance of sewage/effluent treatment plants,and dumping of solid waste on river banks.This study dealt with the pollution issues of the Cooum River in the well-known city of Chennai in South India.Water samples from 27 locations were collected and analyzed for 12 elements,including Ba,B,and Al,as well as heavy metals such as Pb,Cr,Mn,Fe,Co,Ni,Cu,Zn,and Cd.The samples showed levels of these elements that exceeded World Health Organization recommendations.Pearson correlation analysis revealed the inter-dependency among elements,and the contribution of each element based on factor loadings showed its percentage contribution compared to others.Water samples from six significant locations were chosen for remediation with three algae:Chlorella vulgaris,Scenedesmus dimorphus,and Phormedium sp.The uptake of pollutants led to the continuous growth of algae during the incubation period of 15 d,effectively removing heavy metals from the river water.The increasing levels of algal counts and the chlorophyll a content confirmed the algal growth during the incubation period,followed by a declining stage after the incubation period.The scanning electron microscopic images of algae before and after the remediation showed no remarkable modification of morphological patterns.This study showed that the uptake of heavy metals using algae is an effective water pollution remediation measure,making the process practicable in the field on a large scale in the near future.

Microplastic and Heavy Metals Distributions in Urban Rivers Sediments,China

This study investigated the distribution of microplastics and heavy metals,along with the interaction between the two in the sediments of urban rivers in China.Results showed that the abundance of microplastics ranged from 2412±187.5 to 7638±1312items kg^(-1)dry sediment across different survey stations,with an average abundance at(4388±713)items kg^(-1)dry sediment.Upon further categorization,it was found that transparent fragments were the primary color and type of microplastics present.The potential ecological risk index(RI)of heavy metals in sediments suggested a low level of ecological risk within a majority of the urban rivers studied.Cd was identified as the main potential ecological risk factor in the sediments of the studied areas.There was a relatively good significant linear relationship between the RI of heavy metals and the abundance of microplastics,bolstering the linkage between these two environmental pollutants.However,the concentrations of heavy metals in microplastics were not dependent on their corresponding contents in sediments.In fact,the concentration of Cu,Cd,and As in microplastics were higher than those in the sediments.This finding confirmed that microplastics could serve as carriers of heavy metals and introduce potential risks to aquatic wildlife and human through the food chain.

The potassium storage performance of carbon nanosheets derived from heavy oils

As by-products of petroleum refining,heavy oils are characterized by a high carbon content,low cost and great variability,making them competitive precursors for the anodes of potassium ion batteries(PIBs).However,the relationship between heavy oil composition and potassium storage performance remains unclear.Using heavy oils containing distinct chemical groups as the carbon source,namely fluid catalytic cracking slurry(FCCS),petroleum asphalt(PA)and deoiled asphalt(DOA),three carbon nanosheets(CNS)were prepared through a molten salt method,and used as the anodes for PIBs.The composition of the heavy oil determines the lamellar thicknesses,sp3-C/sp2-C ratio and defect concentration,thereby affecting the potassium storage performance.The high content of aromatic hydrocarbons and moderate amount of heavy component moieties in FCCS produce carbon nanosheets(CNS-FCCS)that have a smaller layer thickness,larger interlayer spacing(0.372 nm),and increased number of folds than in CNS derived from the other three precursors.These features give it faster charge/ion transfer,more potassium storage sites and better reaction kinetics.CNS-FCCS has a remarkable K^(+)storage capacity(248.7 mAh g^(-1) after 100 cycles at 0.1 A g^(-1)),long cycle lifespan(190.8 mAh g^(-1) after 800 cycles at 1.0 A g^(-1))and excellent rate capability,ranking it among the best materials for this application.This work sheds light on the influence of heavy oil composition on carbon structure and electrochemical performance,and provides guidance for the design and development of advanced heavy oil-derived carbon electrodes for PIBs.

Nanoscale Zero-Valent Iron(nZVI)for Heavy Metal Wastewater Treatment:A Perspective

Industries such as non-ferrous metal smelting discharge billions of gallons of highly toxic heavy metal wastewater(HMW)worldwide annually,posing a severe challenge to conventional wastewater treatment plants and harming the environment.HMW is traditionally treated via chemical precipitation using lime,caustic,or sulfide,but the effluents do not meet the increasingly stringent discharge standards.This issue has spurred an increase in research and the development of innovative treatment technologies,among which those using nanoparticles receive particular interest.Among such initiatives,treatment using nanoscale zero-valent iron(nZVI)is one of the best developed.While nZVI is already well known for its site-remediation use,this perspective highlights its application in HMW treatment with metal recovery.We demonstrate several advantages of nZVI in this wastewater application,including its multifunctionality in sequestrating a wide array of metal(loid)s(>30 species);its capability to capture and enrich metal(loid)s at low concentrations(with a removal capacity reaching 500 mg·g^(-1)nZVI);and its operational convenience due to its unique hydrodynamics.All these advantages are attributable to nZVI’s diminutive nanoparticle size and/or its unique iron chemistry.We also present the first engineering practice of this application,which has treated millions of cubic meters of HMW and recovered tons of valuable metals(e.g.,Cu and Au).It is concluded that nZVI is a potent reagent for treating HMW and that nZVI technology provides an eco-solution to this toxic waste.

Separation of halogens and recovery of heavy metals from secondary copper smelting dust

The separation of halogens and recovery of heavy metals from secondary copper smelting(SCS)dust using a sulfating roasting−water leaching process were investigated.The thermodynamic analysis results confirm the feasibility of the phase transformation to metal sulfates and to gaseous HF and HCl.Under the sulfating roasting conditions of the roasting temperature of 250℃ and the sulfuric acid excess coefficient of 1.8,over 74 wt.%of F and 98 wt.%of Cl were volatilized into flue gas.Approximately 98.6 wt.%of Zn and 96.5 wt.%of Cu in the roasting product were dissolved into the leaching solution after the water leaching process,while the leaching efficiencies of Pb and Sn were only 0.12%and 0.22%,respectively.The mechanism studies indicate the pivotal effect of roasting temperature on the sulphation reactions from various metal species to metal sulfates and the salting out reactions from various metal halides to gaseous hydrogen halides.

Effects of Initial and Boundary Conditions on Heavy Rainfall Simulation over the Yellow Sea and the Korean Peninsula:Comparison of ECMWF and NCEP Analysis Data Effects and Verification with Dropsonde Observation

This study evaluated the simulation performance of mesoscale convective system(MCS)-induced precipitation,focusing on three selected cases that originated from the Yellow Sea and propagated toward the Korean Peninsula.The evaluation was conducted for the European Centre for Medium-Range Weather Forecasts(ECMWF)and National Centers for Environmental Prediction(NCEP)analysis data,as well as the simulation result using them as initial and lateral boundary conditions for the Weather Research and Forecasting model.Particularly,temperature and humidity profiles from 3D dropsonde observations from the National Center for Meteorological Science of the Korea Meteorological Administration served as validation data.Results showed that the ECMWF analysis consistently had smaller errors compared to the NCEP analysis,which exhibited a cold and dry bias in the lower levels below 850 hPa.The model,in terms of the precipitation simulations,particularly for high-intensity precipitation over the Yellow Sea,demonstrated higher accuracy when applying ECMWF analysis data as the initial condition.This advantage also positively influenced the simulation of rainfall events on the Korean Peninsula by reasonably inducing convective-favorable thermodynamic features(i.e.,warm and humid lower-level atmosphere)over the Yellow Sea.In conclusion,this study provides specific information about two global analysis datasets and their impacts on MCS-induced heavy rainfall simulation by employing dropsonde observation data.Furthermore,it suggests the need to enhance the initial field for MCS-induced heavy rainfall simulation and the applicability of assimilating dropsonde data for this purpose in the future.

Uniformity Control of Scanned Beam in 300 MeV Proton and Heavy Ion Accelerator Complex at SESRI

In recent years,heavy ion accelerator technology has been rapidly developing worldwide and widely applied in the fields of space radiation simulation and particle therapy.Usually,a very high uniformity in the irradiation area is required for the extracted ion beams,which is crucial because it directly affects the experimental precision and therapeutic effect.Specifically,ultra-large-area and high-uniformity scanning are crucial requirements for spacecraft radiation effects assessment and serve as core specification for beamline terminal design.In the 300 MeV proton and heavy ion accelerator complex at the Space Environment Simulation and Research Infrastructure(SESRI),proton and heavy ion beams will be accelerated and ultimately delivered to three irradiation terminals.In order to achieve the required large irradiation area of 320 mm×320 mm,horizontal and vertical scanning magnets are used in the extraction beam line.However,considering the various requirements for beam species and energies,the tracking accuracy of power supplies(PSs),the eddy current effect of scanning magnets,and the fluctuation of ion bunch structure will reduce the irradiation uniformity.To mitigate these effects,a beam uniformity optimization method based on the measured beam distribution was proposed and applied in the accelerator complex at SESRI.In the experiment,the uniformity is successfully optimized from 75%to over 90%after five iterations of adjustment to the PS waveforms.In this paper,the method and experimental results were introduced.

Magnetism, heat capacity, magnetocaloric effect, and magneto-transport properties of heavy fermion antiferromagnet CeGaSi

We synthesize high-quality single crystal of CeGaSi by a Ga self-flux method and investigate its physical properties through magnetic susceptibility,specific heat and electrical resistivity measurements as well as high pressure effect.Magnetic measurements reveal that an antiferromagnetic order develops below T_(m)~10.4 K with magnetic moments orientated in the ab plane.The enhanced electronic specific heat coefficient and the negative logarithmic slope in the resistivity of CeGaSi indicate that the title compound belongs to the family of Kondo system with heavy fermion ground states.The max magnetic entropy change-ΔS_(M)^(max)(μ_(0)H⊥c,μ_(0)H=7 T) around T_(m) is found to reach up to 11.85 J·kg^(-1)·K^(-1).Remarkably,both the antiferromagnetic transition temperature and-ln T behavior increase monotonically with pressure applied to 20 kbar(1 bar=10~5 Pa),indicating that much higher pressure will be needed to reach its quantum critical point.

Preliminary safety analysis for heavy water-moderated molten salt reactor

The heavy water-moderated molten salt reactor(HWMSR)is a newly proposed reactor concept,in which heavy water is adopted as the moderator and molten salt dissolved with fissile and fertile elements is used as the fuel.Issues arising from graphite in traditional molten salt reactors,including the positive temperature coefficient and management of highly radio-active spent graphite waste,can be addressed using the HWMSR.Until now,research on the HWMSR has been centered on the core design and nuclear fuel cycle to explore the viability of the HWMSR and its advantages in fuel utilization.However,the core safety of the HWMSR has not been extensively studied.Therefore,we evaluate typical accidents in a small modular HWMSR,including fuel salt inlet temperature overcooling and overheating accidents,fuel salt inlet flow rate decrease,heavy water inlet temperature overcooling accidents,and heavy water inlet mass flow rate decrease accidents,based on a neutronics and thermal-hydraulics coupled code.The results demonstrated that the core maintained safety during the investigated accidents.

Heavy ion energy influence on multiple-cell upsets in small sensitive volumes:from standard to high energies

The 28 nm process has a high cost-performance ratio and has gradually become the standard for the field of radiation-hardened devices.However,owing to the minimum physical gate length of only 35 nm,the physical area of a standard 6T SRAM unit is approximately 0.16μm^(2),resulting in a significant enhancement of multi-cell charge-sharing effects.Multiple-cell upsets(MCUs)have become the primary physical mechanism behind single-event upsets(SEUs)in advanced nanometer node devices.The range of ionization track effects increases with higher ion energies,and spacecraft in orbit primarily experience SEUs caused by high-energy ions.However,ground accelerator experiments have mainly obtained low-energy ion irradiation data.Therefore,the impact of ion energy on the SEU cross section,charge collection mechanisms,and MCU patterns and quantities in advanced nanometer devices remains unclear.In this study,based on the experimental platform of the Heavy Ion Research Facility in Lanzhou,low-and high-energy heavy-ion beams were used to study the SEUs of 28 nm SRAM devices.The influence of ion energy on the charge collection processes of small-sensitive-volume devices,MCU patterns,and upset cross sections was obtained,and the applicable range of the inverse cosine law was clarified.The findings of this study are an important guide for the accurate evaluation of SEUs in advanced nanometer devices and for the development of radiation-hardening techniques.

A Real-time Prediction System for Molecular-level Information of Heavy Oil Based on Machine Learning

Acquiring accurate molecular-level information about petroleum is crucial for refining and chemical enterprises to implement the“selection of the optimal processing route”strategy.With the development of data prediction systems represented by machine learning,it has become possible for real-time prediction systems of petroleum fraction molecular information to replace analyses such as gas chromatography and mass spectrometry.However,the biggest difficulty lies in acquiring the data required for training the neural network.To address these issues,this work proposes an innovative method that utilizes the Aspen HYSYS and full two-dimensional gas chromatography-time-of-flight mass spectrometry to establish a comprehensive training database.Subsequently,a deep neural network prediction model is developed for heavy distillate oil to predict its composition in terms of molecular structure.After training,the model accurately predicts the molecular composition of catalytically cracked raw oil in a refinery.The validation and test sets exhibit R2 values of 0.99769 and 0.99807,respectively,and the average relative error of molecular composition prediction for raw materials of the catalytic cracking unit is less than 7%.Finally,the SHAP(SHapley Additive ExPlanation)interpretation method is used to disclose the relationship among different variables by performing global and local weight comparisons and correlation analyses.