Pure Hydrocarbons Research Articles

Nanometer-Scale CO2-Shale Oil Minimum Miscibility Pressure Calculations Based on Modified PR-EOS

CO2 flooding is recognized as an efficient method for enhancing shale oil recovery, while CO2-oil MMP (minimum miscibility pressure) in the micro-nanoscale is a crucial parameter. This paper presents a method for calculating the MMPs of pure hydrocarbons (C4H10, C6H14, C8H18, and C10H22) and CO2 systems in nanopores (3 nm to 10 nm) with temperature ranging from 290.15 K to 373.15 K. Firstly, we modify the Peng-Robinson equation of state (PR-EOS) by considering the influence of confinement effect and capillary pressure in nanopores. Secondly, the flash calculation algorithm is employed to determine whether the oil and gas phases in nanopores have reached an equilibrium state according to the equality of the fugacity of the two phases. Thirdly, we calculate the interfacial tension (IFT) between the two phases using the Macleod-Sugden equation. When the extrapolated IFT is zero, we treat the corresponding pressure as the MMP of the CO2-oil system in nanopores. Simulation results indicate that the calculated MMP using this method has a relative error of about 0.62% compared to the MMP calculated using the multiple mixing cell (MMC) method, indicating high reliability for MMP prediction. Moreover, the measured MMP at the nanoscale is generally smaller than that in the bulk phase due to the influence of the confinement effect. The MMP is positively correlated with the reservoir temperature, the carbon atom number in alkanes, and the nanopore radius.

 MODELLING AND SIMULATION OF THE COMBUSTION OF BIODERIVED FUELS IN A PT6A-27 TURBOPROP ENGINE

The motivation for venturing in alternative jet fuels has partly been due to the elevated level and volatility of the price of Jet A and environmental impacts on global climate change and air quality. The model of the annular combustor for the PT6A-27 engine was created using SOLIDWORKS and exported to ANSYS DESIGN MODELER. Creation of the computational mesh for the geometry using ANSYS MESHING was done in preparation for the setting up of the CFD simulation in ANSYS FLUENT. The simulation included, setting material properties and boundary conditions for a non-premixed combustion problem. Initiating the calculation with residual plotting, calculating the solution using the pressure-based solver and visually examining the flow and temperature fields using the post-processing in ANSYS FLUENT with the Standard k-ε 2 equation turbulence model used. The fuel blend from the range of 30% bioethanol and 70% biodiesel (BE30-BD70) to 70% bioethanol and 30% biodiesel (BE70-BD30) indicated a combustion characteristic consistency with that obtained from the combustion of Jet-A1. Further, from the comparisons of the blends in terms of performance and single biofuel combustion simulation the best blend combination was 40% bioethanol with 60% biodiesel (BE40-BD60) whose adiabatic flame temperature was about 2260 Kelvins. The blend of 40% bioethanol to 60% biodiesel was observed to have a reduced Fuel NOx footprint and the observed production rate values of Thermal NOx were a range of to Whereas a pure JetA-1 hydrocarbon fuel had a production rate of Thermal NOx ranging from to . This was indicative of a reduction in Thermal NOx when the two groups of fuels (Jet-A against 40BE & 60BD blend) were compared. These results showed that reduction of NOx emissions is achievable for a blend of 40% bioethanol and 60% biodiesel in a combustion reaction as a substitute for the hydrocarbon JetA-1 in the PT6A-27 turboprop engine. KEY WORDS—PT6A-27, nonpremixed Combustion, NOx, Turbulence model

Microemulsion phase behavior of live crude oil and revisiting the EACN framework for crude oils

Determination of the EACN of dead, surrogate, and live crude oils are revisited. The main objective of the study was to better understand the EACN of crude oil systems and to find more desirable practices in terms of approximation of crude oils. Microemulsion phase behaviors were measured in a wide range of oil compositions while keeping all formulation variables fixed except the oil. Pure hydrocarbons were used as oil phases or diluents to investigate the effect of nonideal mixing between crude oil and diluents. A synthetic live crude oil was constituted by adding 39.5 mol% of methane to a dead crude oil and then microemulsion phase behavior was investigated to determine the optimum salinity and solubilization ratios at 172 bar (2500 psi) and 90 °C. The results were analyzed based on two existing approaches in EACN framework, i.e., pure n-alkane trends against EACN versus dilution curves against EACN. The method using crude oil dilution curve results in a greater EACN of the crude oil by 2 units than by the method utilizing the pure n-alkane trend as a basis. The apparent EACN of methane was found to be much greater than its alkane carbon number of 9.3 based on the pure n-alkane trend and 11.6 based on the crude oil dilution method, respectively. Through systematic construction and investigation of optimum salinity vs. EACN curves, desirable practices to determine EACN of crude oils are presented. The results could be useful to approximate live crude oil EACN by designing more representative surrogate crude oils.

Prediction of Thermogravimetric Data in Bromine Captured from Brominated Flame Retardants (BFRs) in e-Waste Treatment Using Machine Learning Approaches.

The principal objective in the treatment of e-waste is to capture the bromine released from the brominated flame retardants (BFRs) added to the polymeric constituents of printed circuits boards (PCBs) and to produce pure bromine-free hydrocarbons. Metal oxides such as calcium hydroxide (Ca(OH)2) have been shown to exhibit high debromination capacity when added to BFRs in e-waste and capturing the released HBr. Tetrabromobisphenol A (TBBA) is the most commonly utilized model compound as a representative for BFRs. Our coauthors had previously studied the pyrolytic and oxidative decomposition of the TBBA:Ca(OH)2 mixture at four different heating rates, 5, 10, 15, and 20 °C/min, using a thermogravimetric (TGA) analyzer and reported the mass loss data between room temperature and 800 °C. However, in the current work, we applied different machine learning (ML) and chemometric techniques involving regression models to predict the TGA data at different heating rates. The motivation of this work was to reproduce the TGA data with high accuracy in order to eliminate the physical need of the instrument itself, so that this could save significant experimental time involving sample preparation and subsequently minimizing human errors. The novelty of our work lies in the application of ML techniques to predict the TGA data from e-waste pyrolysis since this has not been conducted previously. The significance of our work lies in the fact that e-waste is ever increasing, and predicting the mass loss curves faster will enable better compositional analysis of the e-waste samples in the industry. Three ML models were employed in our work, namely Linear, random forest (RF), and support vector regression (SVR), out of which the RF method exhibited the highest coefficient of determination (R2) of 0.999 and least error of prediction as estimated by the root mean squared error (RMSEP) at all 4 heating rates for both pyrolysis and oxidation conditions. An 80:20 split was used for calibration and validation data sets. Furthermore, for showing versatility and robustness of the best-predicting RF model, it was also trained using all the data points in the lower heating rates of 5 and 10 °C/min and predicted on all the data points for the higher heating rates of 15 and 20 °C/min to again obtain a high R2 of 0.999. The excellent performance of the RF model showed that ML techniques can be used to eliminate the physical use of TGA equipment, thus saving experimental time and potential human errors, and can further be applied in other real-time e-waste recycling scenarios.

ASTER-B regulates mitochondrial carotenoid transport and homeostasis

The scavenger receptor class B type 1 (SR-B1) facilitates uptake of cholesterol and carotenoids into the plasma membrane (PM) of mammalian cells. Downstream of SR-B1, ASTER-B protein mediates the nonvesicular transport of cholesterol to mitochondria for steroidogenesis. Mitochondria also are the place for the processing of carotenoids into diapocarotenoids by β-carotene oxygenase-2. However, the role of these lipid transport proteins in carotenoid metabolism has not yet been established. Herein, we showed that the recombinant StART-like lipid-binding domain of ASTER-A and B preferentially binds oxygenated carotenoids such as zeaxanthin. We established a novel carotenoid uptake assay and demonstrated that ASTER-B expressing A549 cells transport zeaxanthin to mitochondria. In contrast, the pure hydrocarbon β-carotene is not transported to the organelles, consistent with its metabolic processing to vitamin A in the cytosol by β-carotene oxygenase-1. Depletion of the PM from cholesterol by methyl-β-cyclodextrin treatment enhanced zeaxanthin but not β-carotene transport to mitochondria. Loss-of-function assays by siRNA in A549 cells and the absence of zeaxanthin accumulation in mitochondria of ARPE19 cells confirmed the pivotal role of ASTER-B in this process. Together, our study in human cell lines established ASTER-B protein as key player in nonvesicular transport of zeaxanthin to mitochondria and elucidated the molecular basis of compartmentalization of the metabolism of nonprovitamin A and provitamin A carotenoids in mammalian cells.

Collective Quantum Magnetism in Nitrogen-Doped Nanographenes.

The emergence of quantum magnetism in nanographenes provides ample opportunities to fabricate purely organic devices for spintronics and quantum information. Although heteroatom doping is a viable way to engineer the electronic properties of nanographenes, the synthesis of doped nanographenes with collective quantum magnetism remains elusive. Here, a set of nitrogen-doped nanographenes (N-NGs) with atomic precision are fabricated on Au(111) through a combination of imidazole [2+2+2]-cyclotrimerization and cyclodehydrogenation reactions. High-resolution scanning probe microscopy measurements reveal the presence of collective quantum magnetism for nanographenes with three radicals, with spectroscopic features which cannot be captured by mean-field density functional theory calculations but can be well reproduced by Heisenberg spin model calculations. In addition, the mechanism of magnetic exchange interaction of N-NGs has been revealed and compared with their counterparts with pure hydrocarbons. Our findings demonstrate the bottom-up synthesis of atomically precise N-NGs which can be utilized to fabricate low-dimensional extended graphene nanostructures for realizing ordered quantum phases.

Development of QSPR-ANN models for the estimation of critical properties of pure hydrocarbons

The current work aimed to predict three critical properties: critical temperature (Tc), critical volume (Vc), and critical pressure (Pc) of pure hydrocarbons. A multi-layer perceptron artificial neural network (MLP-ANN) has been adopted as a nonlinear modeling technique and computational approach based on a few relevant molecular descriptors. A set of diverse data points was used to build three QSPR-ANN models, including 223 points for Tc, Vc, and 221 for Pc. The entire database was randomly split into two subsets: 80% for the training set and 20% for the testing set. A large number of 1666 molecular descriptors were calculated and then reduced by a statistical methodology based on several phases to retain them into a reasonable number of relevant descriptors, wherein about 99% of initial descriptors were excluded. Thus, the Quasi-Newton backpropagation (BFGS) algorithm was applied to train the ANN structure. The results of three QSPR-ANN models showed good precision, confirmed by the high values of determination coefficient (R2) ranging from 0.9990 to 0.9945, and the low values of calculated errors, such as the Mean Absolute Percentage Error (MAPE) that ranged from 2.2497 to 0.7424% for the best three models of Tc, Vc, and Pc. The weight sensitivity analysis method was applied to know the contribution of each input descriptor individually or by class on each appropriate QSPR-ANN model. Moreover, the applicability domain (AD) method was also used with a strict limit of standardized residual values (di = ±2). However, the results were promising, with nearly 88% of the data points validated within the AD range. Finally, the results of the proposed QSPR-ANN models were compared with other well-known QSPR or ANN models for each property. Consequently, our three models provided satisfactory results, outperforming most of the models mentioned in this comparison. This computational approach can be applied in petroleum engineering and other related fields to accurately determine the critical properties of pure hydrocarbons: Tc, Vc, and Pc.

Photodegradable polar-functionalized polyethylenes.

The degradation of plastics has attracted much attention from the global community. Polyethylenes (PEs), as the most abundant synthetic plastics, are most frequently studied. PE is non-degradable and non-polar because of the sole presence of the pure hydrocarbon components. Concurrent incorporation of both in-chain cleavable and functional groups into the PE chain is an effective pathway to overcome the non-degradable and non-polar issue; however, the method for achieving this pathway remains elusive. Here, we report a strictly non-alternating (>99%) terpolymerization of ethylene with CO and fundamental polar monomers via a coordination-insertion mechanism using late transition metal catalysts, which effectively prevents the formation of undesired chelates originating from both co-monomers under a low CO concentration. High-molecular-weight linear PEs with both in-chain isolated keto (>99%) and main-chain functional groups are prepared. The incorporation of key low-content isolated keto groups makes PEs photodegradable while retaining their desirable bulk material properties, and the introduction of polar functional groups considerably improves their surface properties.

High pressure behavior of ethylene and water: From clathrate hydrate to polymerization in solid ice mixtures.

Among the ice mixtures that can be found in our universe, those involving ethylene are poorly studied even though ethylene reportedly exists in the presence of water in several astrochemical domains. Here, we report on the chemistry of ethylene and water mixtures in both pressure (0-15GPa) and temperature (300-370K) ranges relevant to celestial bodies conditions. The behavior of the binary mixture has been tracked, starting from the ethylene clathrate hydrate and following its evolution through two different crystalline phases up to 2.10GPa, where it decomposes into a solid mixture of water ice and crystalline ethylene. The pressure and temperature evolution of this mixture has been studied up to the complete transformation of ethylene into polyethylene and compared with that of the pure hydrocarbon, reporting here for the first time its spectroscopic features upon compression. The spectroscopic analysis of the recovered polymers from the ice mixtures provided hints about the reactivity of the monomer under the environmental stress exerted by the water network. The results of this study are expected to be significant in a variety of fields ranging from astrochemistry to material science and also to fundamental chemistry, particularly regarding the study and modelization of the behavior of complex mixtures.

Dibenzotropylium-Capped Orthogonal Geometry Enabling Isolation and Examination of a Series of Hydrocarbons with Multiple 14π-Aromatic Units

A series of six dications composed of pure hydrocarbons with one to six non-substituted 9,10-anthrylene units end-capped with two dibenzotropyliums were designed and synthesized to elucidate the electronic properties of huge oligo(9,10-anthrylene) backbones. Their structures were successfully determined by X-ray analyses even in the case of eight planar 14π-electron units, revealing that all dications adopt almost orthogonally twisted structures between neighboring units. Spectroscopic and voltammetric analyses show that neither the significant overlap of orbitals nor the delocalization of electrons between 14π-electron units occurs due to the orthogonally twisted geometry even in solution. As a result, sequential oxidation processes were observed with the reversible formation of multivalent cations with the release of the same number of electrons as the number of anthrylene units. Upon two-electron reduction, a closed-shell butterfly-shaped form was obtained from the dication containing one anthrylene unit, whereas open-shell twisted biradicals were isolated as stable entities in the cases of derivatives containing three to six anthrylene units. Notably, from the derivative with two anthrylene units, a metastable open-shell isomer was obtained quantitatively and underwent slow thermal conversion to the most stable closed-shell isomer (Ea = 23.1 kcal mol-1). There is a drastic change in oxidation potentials between two neutral species (ΔE = 1.32 V in CH2Cl2). Since the present dications were regenerated upon oxidation of the isolated reduction products, these systems may contribute to the development of advanced response systems capable of switching color, magnetic properties, and oxidative properties by using a "cation-capped orthogonal geometry".

The P-µ-T Cubic Equation of Viscosity for Reservoir Oils

Summary Oil recovery simulation sensitivity increases with heavier oils for the existing viscosity models, driving into higher levels of difficulty when fitting viscosity data for rising oil heaviness, particularly below the saturation pressure. Keeping in view the similarity of trends of viscosity and density with isothermal pressures for reservoir oils, the P-μ-T cubic viscosity model, which was developed for pure hydrocarbon components, was extended to reservoir oils. Two parameters in the P-μ-T cubic viscosity model for mixtures with pure and pseudocomponents are identified for adjusting the viscosity data fitting: Kc for controlling the viscosity gradient with pressure and the “ε” shifting trends for increasing viscosity direction. These two parameters are treated as the adjustable parameters required for fitting the viscosity data. A total of 129 reservoir oils from different sources are used to validate the reliability of the P-μ-T viscosity model. The default model (where ε and Kc are 1 and 45, respectively), extended to 71 light oils, resulted in 31% of average absolute relative deviation (AARD) in viscosity prediction. However, separate adjusted parameters are obtained per oil for more accurate viscosity data fitting. Application of the model in this work results in (post-fitting) AARD% of 2.86% average for 36 low-viscosity oil data, 5.68% for 9 high-viscosity oil data, 9% for five oil blends, and 4.11% for bitumen blends. The model gives an AARD of 3.06% in the undersaturated region and 3.79% in the saturated region for the oil considered. The model predicts better the viscosity above saturation pressure for low-viscosity oils and below saturation pressure for high-viscosity oils. A comparative analysis of the P-μ-T cubic viscosity model vs. other models demonstrates its ability to successfully capture viscosity trends of oil and blends in all viscosity ranges. For simplicity, the P-μ-T cubic viscosity model is proposed with only two optimizing parameters even though using a third parameter improves the matching in heavy oils.

A processable, scalable, and stable full-color ultralong afterglow system based on heteroatom-free hydrocarbon doped polymers.

Although room-temperature phosphorescence (RTP) organic materials are a widely-studied topic especially popular in recent decades, long-lived RTP able to fulfil broad time-resolved application requirements reliably, are still rare. Polymeric materials doped with phosphorescent chromophores generally feature high productivity and diverse applications, compared with their crystalline counterparts. This study proves that pure polycyclic aromatic hydrocarbons (PAHs) may even outperform chromophores containing hetero- or heavy-atoms. Full-color (blue, green, orange and red) polymer-PAHs with lifetimes >5000 ms under ambient conditions are constructed, which provide impressive values compared to the widely reported polymer-based RTP materials in the respective color regions. The polymer-PAHs could be fabricated on a large-scale using various methods (solution, melt and in situ polymerization), be processed into diverse forms (writing ink, fibers, films, and complex 3D architectures), and be used in a range of applications (anti-counterfeiting, information storage, and oxygen sensors). Plus their environmental (aqueous) stability makes the polymer-PAHs a promising option to expand the portfolio of organic RTPs.

Novel Scenedesmus obliquus algae biofuel emission and performance characterise in Si-DLC coated diesel engine

Investigation of the viability of providing biodiesel made from the algae Scenedesmus obliquus in a compression ignition (CI) engine. This research suggests Scenedesmus slick biodiesel (SOBD) as a possible source of energy, as it is found widely in marine, freshwater and aquaculture communities worldwide. SOBD was mixed with neat diesel fossil fuel at multiple volume ratios of 20 %, 30 %, 40 %, and its properties as a biofuel were analyzed according to ASTM standards. The characteristics study towards combustion, performance and emission of biofuel were analyzed by testing it on a single cylinder diesel engine at a 1500 rpm rated speed. The outcomes of the tests reveal that the efficiency of B20 (20 %SOBD + 80 % diesel) blend is comparable to pure diesel thermal efficiency, smoke, hydrocarbons and carbon monoxide. Still, the SOBD blend caused somewhat increased emissions of carbon dioxide and nitrogen oxides. At 100 % load, SOBD when compared with diesel achieves relatively lower cylinder pressures and lower heat release rates. In general, it is possible to deduce that the B20 blend (20 % SOBD 80 % diesel) will be a favourable feedstock variety that will be employed in unaltered combustion engines with minimal exhaust emissions.

Fuel oil from plastic waste

PLASTIC is a revolutionary invention which brought many changes in industrial & daily activities. But in more recent times it has resulted in a major problem due to the increasing usage of landfills which has led to increased pollution due to its high degradation time & and no established disposal method with minimal environmental impact. As the generation of plastic waste is increasing day by day, many engineering processes have been found to convert them to alternative fuels. Pyrolysis is the most useful and prominent method as it has a wide range of uses and helps in the reduction of the large amount of plastic waste. Pyrolysis is a process which converts the large hydrocarbon chains present to smaller hydrocarbon chains by heating the plastics at high temperature (350–400 °C), the products obtained are fuel oil and non-condensable fractions. The fuel oil can be used for heating purposes and non-condensable fractions to reduce air pollution. Polythene, Polypropylene are used as they are pure hydrocarbons and burnt cleanly. These fuels are used as industrial feedstock in many industries like petroleum refineries, alkene production etc.We are now considering plastic as a waste product but upon reprocessing and application of new technologies can yield many valuable products which can lead us to a sustainable and healthy environment in future.

On the use of extended-wavelength FTIR spectra for the prediction of combustion properties of jet fuels and their constituent species

A Fourier transform infrared (FTIR) spectra-based strategy was developed for estimating three important combustion properties of jet fuels and their constituent hydrocarbon species: ignition delay time (IDT), net heat of combustion (NHC), and derived cetane number (DCN). This approach leverages the strong sensitivity of combustion behavior to the different infrared absorption features of hydrocarbon fuels. Gas-phase FTIR spectra of pure hydrocarbons and jet fuels in the 2–15.38 μm wavelength range were used to train elastic-net regularized linear models, with the model parameters optimized separately for each property. The results from these models were compared with the results from previous models, which utilized only a limited spectral region in the wavelength range 3.3–3.55 μm. The new, optimized models developed in this work show significant improvement in predictive performance compared to the previous models for all three properties. The models’ prediction errors on test data (blends of conventional and alternative jet fuels) are found to be comparable to the standard property measurement uncertainties, demonstrating the value of infrared spectral analysis as a low-volume prescreening tool for accurate property estimation of both conventional and alternative jet fuels.

Detection of Polycyclic Aromatic Hydrocarbons in High Organic Carbon Ultrafine Particle Extracts by Electrospray Ionization Ultrahigh-Resolution Mass Spectrometry.

The detection of polycyclic aromatic hydrocarbons (PAHs) by electrospray ionization (ESI) without additional reagents or targeted setup changes to the ionization source was observed in ultrafine particle (UFP) extracts, with high organic carbon (OC) concentrations, generated by a combustion aerosol standard (CAST) soot generator. Particulate matter (PM) was collected on filters, extracted with methanol, and analyzed by ESI Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Next to oxygen-containing species, pure hydrocarbons were found to be one of the most abundant compound classes, detected as [M + Na]+ or [M + H]+ in ESI+ and mostly as [M - H]- in ESI-. The assigned hydrocarbon elemental compositions are identified as PAHs due to their high aromaticity index (AI > 0.67) and were additionally confirmed by MS/MS experiments as well as laser desorption ionization (LDI). Thus, despite the relatively low polarity, PAHs have to be considered in the molecular attribution of these model aerosols and/or fresh emissions with low salt content investigated by ESI.

Discovery of Interstellar 2-Cyanoindene (2-C9H7CN) in GOTHAM Observations of TMC-1

We present laboratory rotational spectroscopy of five isomers of cyanoindene (2-, 4-, 5-, 6-, and 7-cyanoindene) using a cavity Fourier transform microwave spectrometer operating between 6 and 40 GHz. Based on these measurements, we report the detection of 2-cyanoindene (1H-indene-2-carbonitrile; 2-) in GOTHAM line survey observations of the dark molecular cloud TMC-1 using the Green Bank Telescope at centimeter wavelengths. Using a combination of Markov Chain Monte Carlo, spectral stacking, and matched filtering techniques, we find evidence for the presence of this molecule at the 6.3σ level. This provides the first direct observation of the ratio of a cyano-substituted polycyclic aromatic hydrocarbon to its pure hydrocarbon counterpart, in this case indene, in the same source. We discuss the possible formation chemistry of this species, including why we have only detected one of the isomers in TMC-1. We then examine the overall hydrocarbon:CN-substituted ratio across this and other simpler species, as well as compare to those ratios predicted by astrochemical models. We conclude that while astrochemical models are not yet sufficiently accurate to reproduce absolute abundances of these species, they do a good job at predicting the ratios of hydrocarbon:CN-substituted species, further solidifying -CN tagged species as excellent proxies for their fully symmetric counterparts.

Determining the gas accumulation period using fluid inclusion observations: Xiang Zhong Basin, China

Abstract There are a large number of natural gas shows in the Upper Paleozoic of the central Hunan Basin. However, the hydrocarbon accumulation process was complicated due to the strong tectonic reformation in this area. A study of the natural gas accumulation period is of significance for determining gas accumulation models. In this research, the fluid inclusion samples were tested, the fluid inclusion occurrence characteristics, uniform temperature data, and reservoir evolution were analyzed, and four diagenetic periods and four diagenetic periods and three hydrocarbon accumulation periods were identified. (i) For the syntaxial stage, the filling is dark and nonluminous, and the fluid captured by the overgrowing cement around the particles is mainly seawater; (ii) for the (Early) Mesogenetic burial stage, the calcite cement grows around the particles or micritic calcite matrix, and the fluid captured is mainly brine; (iii) for (Late) Mesogenetic burial stage, two sets of decomposed fissures developed in massive calcite colloids with non-luminous gas-rich hydrocarbon inclusions within the crystals; and (iv) for Telogenetic burial stage, weakly fluorescent pure gaseous hydrocarbon inclusions are developed in luminescent calcite veins. The result indicates that the organic inclusions in the Lower Carboniferous of the central Hunan Basin are dominated by weakly fluorescent and nonfluorescent rich gas inclusions and pure gas-phase inclusions, with three stages of hydrocarbon filling. By integrating the average homogenization temperatures on burial curves, the three charging orders correspond to 260–250 Ma during the Late Permian, 249–245 Ma during the Early Triassic, and 208–170 Ma during the Late Triassic. Dense reservoir characteristics reveal deep basin gas reservoir in deep basin.

Solution-Phase Synthesis and Isolation of An Aza-Triangulene and Its Cation in Crystalline Form.

Synthesis of triangulene and its derivatives is challenging due to their intrinsic high spin nature. Herein, we report solution-phase synthesis and isolation of a nitrogen-doped triangulene (i.e., aza-triangulene) (NT) and its cation (NT+ ) in single-crystal form. Notably, the cation NT+ can be regarded as an isoelectronic structure of the corresponding all-carbon triangulene. Both NT and NT+ show reasonable stability due to kinetic blocking by bulky and electron-withdrawing aryl substituents, and intramolecular donor-acceptor interaction. Bond length analysis, magnetic measurements and theoretical calculations reveal that the neutral NT has a doublet ground state with a zwitterionic character, while the cation NT+ exhibits a triplet ground state with a singlet-triplet energy gap of +0.84 kcal mol-1 . This study provides a rational strategy to access high-spin systems by heteroatom doping of pure π-conjugated polycyclic hydrocarbons.

Modeling the solubility of light hydrocarbon gases and their mixture in brine with machine learning and equations of state

Knowledge of the solubilities of hydrocarbon components of natural gas in pure water and aqueous electrolyte solutions is important in terms of engineering designs and environmental aspects. In the current work, six machine-learning algorithms, namely Random Forest, Extra Tree, adaptive boosting support vector regression (AdaBoost-SVR), Decision Tree, group method of data handling (GMDH), and genetic programming (GP) were proposed for estimating the solubility of pure and mixture of methane, ethane, propane, and n-butane gases in pure water and aqueous electrolyte systems. To this end, a huge database of hydrocarbon gases solubility (1836 experimental data points) was prepared over extensive ranges of operating temperature (273–637 K) and pressure (0.051–113.27 MPa). Two different approaches including eight and five inputs were adopted for modeling. Moreover, three famous equations of state (EOSs), namely Peng-Robinson (PR), Valderrama modification of the Patel–Teja (VPT), and Soave–Redlich–Kwong (SRK) were used in comparison with machine-learning models. The AdaBoost-SVR models developed with eight and five inputs outperform the other models proposed in this study, EOSs, and available intelligence models in predicting the solubility of mixtures or/and pure hydrocarbon gases in pure water and aqueous electrolyte systems up to high-pressure and high-temperature conditions having average absolute relative error values of 10.65% and 12.02%, respectively, along with determination coefficient of 0.9999. Among the EOSs, VPT, SRK, and PR were ranked in terms of good predictions, respectively. Also, the two mathematical correlations developed with GP and GMDH had satisfactory results and can provide accurate and quick estimates. According to sensitivity analysis, the temperature and pressure had the greatest effect on hydrocarbon gases’ solubility. Additionally, increasing the ionic strength of the solution and the pseudo-critical temperature of the gas mixture decreases the solubilities of hydrocarbon gases in aqueous electrolyte systems. Eventually, the Leverage approach has revealed the validity of the hydrocarbon solubility databank and the high credit of the AdaBoost-SVR models in estimating the solubilities of hydrocarbon gases in aqueous solutions.