Multicomponent Modeling Research Articles

Multicomponent mass transfer modeling of antagonistic binary adsorption of metallic pollutants from water using helical fixed-bed columns

A multicomponent advection-dispersion model was proposed to simulate the breakthrough curves of antagonistic adsorption of zinc, nickel and cadmium cations from water using helical fixed-bed columns packed with bone char. It was formulated using a linear driving force model, empirical multicomponent Langmuir-based isotherm and retardation coefficient to correlate the experimental breakthrough curves obtained for different binary (metal 1 + metal 2) aqueous solutions, which showed a higher asymmetry degree because of the antagonistic adsorption and axial dispersion impact in this complex fixed-bed configuration. Several parameters of this model were handled as column feed concentration dependent to improve the results of data fitting. The experimental results indicated the presence of a strong antagonistic adsorption effect of zinc and cadmium cations, causing the nickel breakthrough curves to show a clear desorption process (i.e., a displacement effect of the ions already adsorbed on the bone char surface commonly known as roll up) during helical column operation. Experimental bed adsorption capacities ranged from 0.03 to 0.74 mmol/g. The proposed advection-dispersion model fitted the experimental breakthrough profiles satisfactorily for the tested binary adsorption systems, including the desorption zone where the mean modeling errors were lower than 10 % for tested mixtures. Several column operation and mass transfer parameters were calculated and discussed to analyze the separation performance of the tested helical fixed-bed bone char columns. These results suggest that the proposed advection-dispersion model can simulate the multicomponent antagonistic adsorption of relevant water pollutants using intensified adsorption equipment such as helical fixed-bed columns.

Photoionization analysis of chemodynamical dwarf galaxies simulations. II. Detailed calculation of diffuse ionizing radiation

ABSTRACT Active star formation in dwarf galaxies shapes the morphology of the surrounding nebular environment and ensures the non-uniformity of the chemical elements spatial distribution in it due to the superwind region expansion. Ionizing radiation within the nebular gas produces observed emission lines used for modelling and diagnostics. We introduce a multicomponent photoionization modelling (MPhM) approach that incorporates detailed calculation of diffuse ionizing radiation (DCDIR) based on chemodynamical simulations (ChDSs). Our models aim to replicate crucial emission line intensity ratios within the observed range, employing a thin dense shell between the superwind region and the outer nebular environment to address ChDSs resolution limitations, which render them insensitive to the presence of a superwind shock. MPhM-generated emission line spectra within a small central synthetic aperture and a thin long-slit exhibit excellent agreement with observations, confirming the accuracy of the ionization structure of the nebular environment obtained using the MPhM + DCDIR approach. However, the outward-only approximation fails to reproduce the dwarf galaxies ionization structure. We determined the oxygen abundance using the $T_e$- and $R_{23}$-methods based on emission lines from MPhM + DCDIR. The resulting abundances align well with values obtained by averaging over the ‘observed’ volume within synthetic apertures, weighted by mass. The escape fraction of ionizing photons from the dwarf galaxy was found to be larger than that obtained using the outward-only approximation. Employing Kennicutt’s calibration corrected for near-UV data, the star formation rate (SFR) was calculated using the ${\rm H}\,\alpha$ luminosity from MPhM + DCDIR. The resulting SFR value is nearly 33 per cent higher than the true one.

Pure Hydrogen and Methane Permeation in Carbon-Based Nanoporous Membranes: Adsorption Isotherms and Permeation Experiments.

This paper presents the results of adsorption and permeation experiments of hydrogen and methane at elevated temperatures on a carbon-based nanoporous membrane material provided by Fraunhofer IKTS. The adsorption of pure components was measured between 90 °C and 120°C and pressures up to 45 bar. The Langmuir adsorption isotherm shows the best fit for all data points. Compared to available adsorption isotherms of H2 and CH4 on carbon, the adsorption on the investigated nanoporous carbon structures is significantly lower. Single-component permeation experiments were conducted on membranes at temperatures up to 220 °C. After combining the experimental results with a Maxwell-Stefan surface diffusion model, Maxwell-Stefan surface diffusion coefficients Dis were calculated. The calculated values are in line with an empirical model and thus can be used in future multi-component modeling approaches in order to better analyze and design a membrane system. The published adsorption data fill a gap in the available adsorption data for CH4 and H2.

Evaluating black wattle bark industrial residue as a new feedstock for bioenergy via pyrolysis and multicomponent kinetic modeling

This work presents an evaluation of the industrial residue from exhausted black wattle bark after the extraction of tannin for use as a new feedstock for biofuel production, without competing with food production. The physicochemical and thermodynamic properties, the influence of temperature on pyrolysis products and multicomponent kinetics were evaluated. Principal component analysis showed that sugars, carboxylic acids, ethers/esters, furans and aldehydes were formed as primary products of pyrolysis at 450 °C. At 550 °C, phenols and mainly ketones were favored, especially acetone and 2,3-butanedione. Pyrolysis at 650 °C favored the production of aldehydes, alcohols, and 1-alkene, polyene and alkane hydrocarbons. After an upgrade, the series of 1-alkenes produced, with carbons C7 to C16, could be suitable for a range of gasoline and jet fuels. Kinetic modeling was based on the deconvolution of the mass loss of three events of the pseudo-components: hemicellulose (DE-HC), cellulose (DE-CL) and lignin (DE-LG). The activation energy for kinetic models Friedman, Flynn-Wall-Ozawa, Kissinger-Akahira-Sunose and Starink presented average values of ∼141.4–149.4 for DE-HC, ∼190.5–200.9 for DE-CL and ∼237.2–252.3 kJ mol−1 for DE-LG. This study encourages using agro-industrial waste to produce second-generation drop-in biofuels and bio-based chemicals, aiming at industrial decarbonization.

Integrated pharmacokinetic-pharmacodynamic modeling and metabolomic research on polyphenol-rich fraction of Thymus quinquecostatus Celak. Alleviating cerebral ischemia-reperfusion injury

Ethnopharmacological relevanceThymus quinquecostatus Celak., a member of thymus genus in Lamiaceae family, has been used as a folk medicine for relieving exterior syndrome and alleviating pain in China. The polyphenol-rich fraction (PRF) derived from Thymus quinquecostatus Celak. had been validated that it can protect cerebral ischemia-reperfusion injury (CIRI) by activating Keap1/Nrf2/HO-1 signaling pathway.Aim of this study: To explore effective components and their pharmacokinetic and pharmacodynamic characteristics as well as possible mechanisms of PRF in treating CIRI. Materials and methodsNormal treated group (NTG) and tMCAO model treated group (MTG) rats were administrated PRF intragastrically. The prototype components and metabolites of PRF in plasma and brain were analyzed by the UPLC-Q-Exactive Orbitrap MSn method. Subsequently, the pharmacokinetics properties of indicative components were performed based on HPLC-QQQ-MS/MS. SOD and LDH activities were determined to study the pharmacodynamic (PD) properties of PRF. The PK-PD relationship of PRF was constructed. In addition, the effect of PRF on endogenous metabolites in plasma and brain was investigated using metabolomic method. ResultsSalvianic acid A, caffeic acid, rosmarinic acid, scutellarin, and apigenin-7-O-glucuronide were selected as indicative components based on metabolic analysis. The non-compartmental parameters were calculated for indicative components in plasma and brain of NTG and MTG rats. Furthermore, single-component and multi-component PK-PD modeling involved Emax, Imax PD models for effect indexes were fitted as well as ANN models were established, which indicated that these components can work together to regulate SOD and LDH activities in plasma and SOD activity in brain tissue to improve CIRI. Additionally, PRF may ameliorate CIRI by regulating the disorder of endogenous metabolites in lipid metabolism, amino acid metabolism, and purine metabolism pathways in vivo, among which lipid metabolism and purine metabolism are closely related to oxidative stress. ConclusionThe PK-PD properties of effect substances and mechanisms of PRF anti-CIRI were further elaborated. The findings provide a convincing foundation for the application of T. quinquecostatus Celak. in the maintenance of human health disorders.

Multicomponent image-based modeling of water flow in heterogeneous wet shale nanopores

Shale contains abundant multicomponent nanopores with different wettability. Water flow in multicomponent nanoporous systems is still unclear due to the effects of mineral composition, complex pore-throat topology, and heterogeneous wettability. This work develops a contact angle-dependent numerical model for nanoconfined water flow considering heterogeneous wettability, slip effect, and effective viscosity. Water flow in single-component (i.e., clay, organic, inorganic) and multicomponent nanoporous media reconstructed utilizing image fusion techniques is systematically investigated. Results show that the enhancement factor increases exponentially, and the tortuosity increases with increasing contact angle. Water flow is inhibited under strongly hydrophilic conditions, with the enhancement factor linearly negatively correlated with specific surface area. Under hydrophobic conditions, the throat aspect ratio is inversely related to the enhancement factor, which is suppressed in quasi-circular pores. Water flow is restricted in clay pores and enhanced in organic pores due to the differences in pore-throat size and wettability. For the heterogeneous wetting system, the global flow is enhanced compared to no slip and homogeneous wetting conditions. Affected by clay and organic pores with different wettability, the velocity is non-uniformly enhanced, and the effect diminishes as water flows. This work provides a numerical perspective for water flow in heterogeneous wet nanoporous systems.

Combined leaching and steam explosion pretreatment of lignocellulosic biomass for high quality feedstock for thermochemical applications

A novel pretreatment approach was developed in the present study to simultaneously reduce the content of inorganic troubling elements (TEs) and improve biomass energy density, i.e., combined leaching and steam explosion (SE) pretreatment with mechanical pressing. Three different high-ash-containing biomass feedstocks were studied – wheat straw (WS), spruce bark (SB), and empty fruit bunches of oil palm (EFB). Before studying the combined pretreatment, the impact of individual pretreatment was determined in-depth on biomass composition and ash-transformation behaviour. In leaching pretreatment, the effect of leaching with steam explosion condensate (SEC), dilute acetic acid and water was studied comprehensively. The solid (raw and treated) and liquid samples (leachate, SEC, hydrolysate) were characterized for a detailed comparative analysis. The ash-fusion and −transformation behaviour of raw and pretreated biomass was studied in-depth using advanced multicomponent thermodynamic equilibrium modelling (TEM) and push-rod dilatometry. After combined pretreatment, a considerably high reduction in TEs content was noted: 82–98 % K, 93–99 % Na, 80–99 % Cl, 34–90 % S, 3–77 % Mg, ash 43–63 %, 26–67 % P, and 19–63 % Ca. Simultaneously, heating values of all three feedstocks increased by 1.3–2.3 MJ/kg, reaching up to 20–22 MJ/kg. TEM results reveal that much lesser amounts of molten slag and volatile inorganic compounds were formed in pretreated samples compared to raw and SE biomass, such as K2Si5MgO12, KCl, KPMgO4, K2Si2O5, CaSiO3, and MgSiO3 in WS; Na2CO3, K2CO3, K2CaC2O6, KPMgO4, and CaCO3 in SB. Due to higher energy density and lower propensity towards ash-related issues, combined pretreated WS and SB have a high potential to be used in large-scale thermochemical applications.

Multicomponent steady-state modeling, performance optimization and prediction of cleaning frequency for treatment of cellulosic manmade fibre industry stream using polysodium 4- styrenesulfonate (PSS) incorporated nanofiltration membrane

Effect of polysodium 4-styrenesulfonate (PSS) in the skin layer on performance of nanofiltration (NF) membrane was analyzed for treatment of saline stream from manmade fiber industry. The NF membrane with 0.05 % (w/w) PSS concentration in aqueous phase had better hydrophilicity (contact angle: 330) and water flux of 27 L.m−2.h−1 along with significant salt rejection (Na2SO4: 90 %, CaSO4: 85 % and NaCl: 80 %) at transmembrane pressure 8.3 bar and crossflow rate 100 L.h−1. A long-term study with the wastewater showed that the intermittent cleaning of the membrane every 6 h led to 16 L.m−2.h−1 average permeate flux and sulfate rejection above 95 %.A two-component, steady-state model was used to quantify the performance of the selected membrane. Based on the fouling study, a semi-empirical theory was proposed to identify the cleaning frequency. The theory developed is useful for the operation, maintenance and recovery of the divalent salts from reject stream of such industry.

Impact of multi-component description of hydrophilic fuel droplets in propagating spray flames

The need for an accurate description of the fuel composition is emerging in recently published studies on the interaction of droplets and flames. In this context, hydrophilic fuels are of particular importance, since they are expected to interact with the water formed during combustion reactions. The impact of such interactions onto the reaction process is still not explored enough. This work aims to contribute to the understanding of such interactions by investigating the impact of accurately describing the heat and mass transfers on hydrophilic fuel droplets interacting with flames. For that, a recently proposed phase change model is employed, demonstrated to be one of the few capable of characterizing the differential diffusion of vapor into the gas phase for hydrophilic fuels interacting with reacting flows. Numerical simulations of freely propagating flames in quiescent droplet mists are conducted with a detailed chemistry description. Different scenarios focus on the impact of water addition in the gaseous or liquid phase. Results demonstrated the multi-component phase change significantly impacts the flame speed in humid air and/or with hydrous ethanol, and neglecting this effect leads to strong miscalculation in flame speed. This is shown to be a consequence of the hydrophilic property of the chosen fuel, which allows the conversion from single-component to multi-component droplets, thus modifying the flame structure.Novelty and significance statement•Differential diffusion is rigorously accounted for with a new phase change model in flames propagating in droplet mists of a hydrophilic fuel, i.e., ethanol.•The multi-component modeling is necessary even when considering the injection of pure hydrophilic fuel.•When the multi-component description of the liquid fuel is enabled, flame speeds become higher than those values achieved with the single-component approach.•Air humidity interacts with hydrophilic fuel droplets delivering higher flame speed values.•A novel justification is presented for the observed higher flame speed values of flames propagating in droplet mists when compared to single-phase flames.

Advective and diffusive gas phase transport in vadose zones: Importance for defining vapour risks and natural source zone depletion of petroleum hydrocarbons

Quantifying the interlinked behaviour of the soil microbiome, fluid flow, multi-component transport and partitioning, and biodegradation is key to characterising vapour risks and natural source zone depletion (NSZD) of light non-aqueous phase liquid (LNAPL) petroleum hydrocarbons. Critical to vapour transport and NSZD is transport of gases through the vadose zone (oxygen from the atmosphere, volatile organic compounds (VOCs), methane and carbon dioxide from the zone of LNAPL biodegradation). Volatilisation of VOCs from LNAPL, aerobic biodegradation, methanogenesis and heat production all generate gas pressure changes that may lead to enhanced gas fluxes apart from diffusion. Despite the importance of the gaseous phase dynamics in the vadose zone processes, the relative pressure changes and consequent scales of advective (buoyancy and pressure driven) / diffusive transport is less studied. We use a validated multi-phase multi-component non-isothermal modelling framework to differentiate gas transport mechanisms. We simulate a multicomponent unweathered gasoline LNAPL with high VOC content to maximise the potential for pressure changes due to volatilisation and to enable the joint effects of methanogenesis and shallower aerobic biodegradation of vapours to be assessed, along with heat production. Considering a uniform fine sand profile with LNAPL resident in the water table capillary zone, results suggest that biodegradation plays the key role in gas phase formation and consequent pressure build-up. Results suggest that advection is the main transport mechanism over a thin zone inside the LNAPL/capillary region, where the effective gaseous diffusion is very low. In the bulk of the vadose zone above the LNAPL region, the pressure change is minimal, and gaseous diffusion is dominant. Even for high biodegradation rate cases, pressure build-up due to heat generation (inducing buoyancy effects) is smaller than the contribution of gas formation due to biodegradation. The findings are critical to support broader assumptions of diffusive transport being dominant in vapour transport and NSZD assessments.

Multicomponent solvent extraction modelling of lithium, cobalt, nickel, and manganese from simulated black mass leachate

The role of lithium-ion batteries in facilitating the global shift towards renewable energy is paramount. Managing the responsible lifecycle of these batteries, including their disposal and recycling at the end of their operational life, holds considerable importance. These practices not only mitigate the environmental impact but also address the supply vulnerability of battery metals sourced from primary natural reserves. The major compositions of batteries, notably lithium, nickel, and cobalt, are typically concentrated within a material known as black mass, a vital commodity in the battery recycling sector. Solvent extraction is a proficient method for the simultaneous recovery of these materials, to produce a feedstock for new battery manufacturing, aligning with the principles of a circular economy. The separation and purification of these metals, while still challenging, are comparatively less difficult than the requirement posed by primary resource extraction. The co-extraction of multiple compositions in a single step holds tremendous potential for reducing the cost associated with the separation process. Nevertheless, this approach is an unconventional solvent extraction method, necessitating advanced multicomponent extraction models. The present study employed the equilibrium status iteration (ESI) model to describe and predict the extraction performance of battery metals in aqueous solutions. This model is instrumental to the design and optimisation of scaled-up solvent extraction facilities. To illustrate the model, ESI was applied to resolve equilibrium data related to a three-stage counter-current extraction scheme. This removes the laborious trial-and-error phase of experimental inquiry when designing the process involving multiple target metals.

Multi-component multiphase lattice Boltzmann modeling of water purging during supercritical carbon dioxide extraction from geothermal reservoir pores

Carbon dioxide becomes supercritical and purges subcritical liquid water in the rock channels as extracted from geothermal reservoir pores. A pseudopotential multi-component multiphase lattice Boltzmann method is presented to simulate the dynamic behavior of the water droplets under the purge of the supercritical carbon dioxide. The model is verified by thermodynamic consistency, surface tension independence regulation, the coexistence of the two components at different viscosities, and surface contact angle distribution laws. The results show that the stronger the hydrophobicity of the wall with uniform adhesion, the faster the motion of the droplet, and when the wall adhesion is not uniform, the stronger the hydrophobicity of the upstream, the faster the purge. When there are two droplets, the volume of the first one rapidly becomes larger because of the absorption of moisture and encounters enhanced shear force to obtain greater velocity. The second droplet receives the shear force weakened by the first, so its growth rate and movement do not change significantly and will gradually be caught up, leading to the coalescence of the two droplets. As the droplets move and grow, the obstruction to flow increases and the pressure drop will increase.

Multiphase Multicomponent Transport Modeling of Cyclic Solvent Injection in Shale Reservoirs

Summary A thorough understanding of fluid transport in ultratight shale reservoirs is crucial for designing and optimizing cyclic solvent injection processes, known as huff ’n’ puff (HnP). We develop a two-phase multicomponent numerical model to investigate hydrocarbon and solvent transport and species mixing during HnP. Unlike the conventional modeling approaches that rely on bulk fluid (advective) transport frameworks, the proposed model considers species transport within nanopores. The chemical potential gradient is considered the driving force for the movement of nonideal fluid mixtures. A binary friction concept is adopted that considers friction between different fluid molecules and between fluid molecules and pore walls. After validating the developed model against analytical solutions and experimental data, the model examines solvent HnP enhanced oil recovery (EOR) mechanisms by considering four-component oil and Eagle Ford crude oil systems. The impacts of injection pressure, primary production duration, soaking time, and solvent type on the oil recovery are examined. The results reveal that the formation of a solvent-oil mixing zone during the huff period and oil swelling and vaporization of oil components during the puff period are key mechanisms for enhancing oil recovery. Furthermore, the incremental recovery factor (RF) increases with injection pressure, even when the injection pressure exceeds the minimum miscibility pressure (MMP), implying that MMP may not play a critical role in the design of HnP in ultratight reservoirs. The results suggest that injecting solvents after a sufficient primary production period is more effective, allowing reservoir pressure depletion. Injecting the solvent without enough primary production may result in significant production of the injected solvent. The results show that the solvent-oil mixing zone expands, and the solvent recycling ratio decreases as soaking time increases. However, short soaking periods with higher HnP cycles are recommended for improving oil recovery at a given time frame. Finally, CO2 HnP outperforms CH4 or N2 HnP due to the higher ability of CO2 to extract a larger amount of intermediate and heavy components into the vapor phase, which has higher transmissibilities as compared with the liquid phase.

Semi-Supervised Deep Learning-Based Multi-component Spectral Calibration Modeling for UV-vis and Near-Infrared Spectroscopy without Information Loss.

Spectral analysis is an important method for characterizing and identifying chemical species. However, quantitative spectral analysis of multiple chemical properties in the real world has always been a challenging problem due to the strong correlation, massive noise, and serious information overlapping of the spectral features. Here, we present a new semi-supervised spectral calibration method based on information lossless decoupling of spectral features named NICEM. To realize the separation and extraction of key latent features, the method uses the flow-based model non-linear independent component estimation (NICE) to learn the sample distribution. The spectral data information is transformed into independent latent variables obeying Gaussian distribution by the reversible structure of deep network without information loss, so as to find the essential properties and realize the feature nonlinear decomposition. Moreover, the association between the input latent feature variables and attributes is evaluated by the maximum mutual information coefficient to eliminate the adverse effects of irrelevant information in the latent variable space and mine key information. Since the latent variables are independent in each dimension, the NICEM method is easier to establish an accurate semi-supervised multi-component calibration model even for high overlapping and complex spectral data. The applicability of the proposed spectral modeling method is demonstrated by using three ultraviolet-visible and near-infrared spectral data sets with 15 physical and chemical properties including diesel fuels, corn, and multi-metal ions solution. Results show that the proposed NICEM method has the highest determination coefficient (R2) and significantly improves extrapolation compared with the seven state-of-the-art methods. The proposed method is intuitive because it obviates complex feature engineering and prior knowledge and is a promising spectral calibration tool for quantitative analysis in other spectroscopy applications.

Controls on Barite (BaSO4) Precipitation in Unconventional Reservoirs.

Barite (BaSO4) precipitation is one of the most ubiquitous examples of secondary sulfate mineral scaling in shale oil and gas reservoirs. Often, a suite of chemical additives is used during fracturing operations to inhibit the accumulation of mineral scales, though their efficacy is widely varied and poorly understood. This study combines experimental data and multi-component numerical reactive transport modeling to offer a more comprehensive understanding of the geochemical behavior of barite accumulation in shale matrices under conditions typical of fracturing operations. A variety of additives and conditions are individually tested in batch reactor experiments to identify the factors controlling barite precipitation. Our experimental results demonstrate a pH dependence in the rate of barite precipitation, which we use to develop a predictive model including a pH-dependent term that satisfactorily reproduces our observations. This model is then extended to consider the behavior of three major shale samples of highly variable mineralogy (Eagle Ford, Marcellus, and Barnett). This data-validated model offers a reliable tool to predict and ultimately mitigate against secondary mineral accumulation in unconventional shale reservoirs.

Synthesis and strengthening mechanism of (Ti0.9Nb0.03Ta0.03W0.03)3SiC2/Al2O3 composite ceramics by doping NbC, TaC and WC powders

Multi-component solid solution composite ceramics (Ti0.9Nb0.03Ta0.03W0.03)3SiC2/Al2O3 were fabricated with a high yield by doping NbC, TaC and WC powders via in-suit synthesis, which demonstrated that using metallic carbide as dopants is more efficient than using metal powders to synthesize the desired products. The optimized hardness and flexural strength of (Ti0.9Nb0.03Ta0.03W0.03)3SiC2/Al2O3 were measured to be 16.6 ± 0.5 GPa and 695 ± 29 MPa, respectively, which represents significant improvements compared to Ti3SiC2/Al2O3 composite ceramics. To deeply understand the influence of dopants, the crystal structure of multi-component solid solutions and interface modeling of composite ceramics were built and evaluated by first-principle calculations. The results indicated that the strengthening effects derived from both intragranular improvements in solid solutions and intergranular enhancement of crystal interfaces.

Insight into nettle straw pyrolysis: Multicomponent kinetics, gas emissions and machine learning models

This study aimed to comprehensively investigate the pyrolysis process of nettle straw by analyzing its multicomponent kinetics modeling, kinetics and thermodynamic parameters, pyrolysis performance, reaction mechanisms, gas emissions, correlation and statistical analysis, as well as feasibility for industrial application. The average apparent activation energies for pseudo-hemicellulose (PS-HEC), cellulose (PS-CEL) and lignin (PS-LIG) were estimated as 147.41, 182.66, and 197.12 kJ/mol, respectively, using four model-free methods: Ozawa-Flynn-Wall, Kissinger-Akahira-Sunose, Starink, and Tang. The pyrolysis reaction mechanisms were best described by diffusional and order-based models, with reaction mechanism functions of f(α) = [3/2(1-α)2/3]/[1-(1-α)1/3], f(α) = (1-α)1.5, and f(α) = (1-α)3 for PS-HEC, PS-CEL, and PS-LIG, respectively. TGA-FTIR analysis revealed that the gas emissions during nettle straw pyrolysis followed the order of CO > CO2 > C-O(H) > H2O > SO2 > CO > CH4 > NH3 > HCN. Best learning rate and artificial neural network (ANN) structure model were optimized. The optimal learning rate and ANN model structure were 0.0013 and ANN (5 *9 *1), respectively. NS has the potential to serve as a viable alternative to biofuel due to its certain energy, low price, abundant reserves, good pyrolysis performance, high volatile content, and low nitrogen and sulfur levels.

Fast 3D forward modeling of a potential field based on spherical symmetry of gravitational potential

A novel approach is developed to implement the forward modeling of a potential field caused by prismatic grids on gridded observations with higher efficiency and less memory. Based on the spherical symmetry of gravitational potential, we summarize the parity, symmetry, and interconversion relations from derivatives and higher derivatives of gravitational potential, which reveal that there are vast repetitive calculation and storage redundancies in conventional forward modeling of a potential field for prismatic grids, especially for cubic grids. These properties help to reduce not only the size of a single kernel matrix but also the number of necessary kernels in multicomponent forward modeling of a potential field, such as a gradient tensor field or joint inversion of a potential field. Several experiments on the synthetic and the realistic Bishop models are presented to illustrate how these properties are used in the forward modeling of gravity and magnetic gradient tensors. Based on the proposed properties, a 2D fast Fourier transform is performed to accelerate the discrete deconvolution of the kernel and the model parameters. With the new method, one single kernel can be reduced to half the number of model parameters, and the memory requirement and time cost of our method can be reduced by 1/8 and 1/2, respectively, compared with previous works. In forward modeling of six gravity gradient tensor components, only two kernels need to be computed and stored, which are 1/3 of the conventional method. These examples indicate that, with high precision, our method requires less memory and less time than conventional methods. It shows potential in the fast large-scale inversion of gravity, magnetic, and gradient tensors with limited hardware resources.

Competitive Adsorption in a Multicomponent Diesel System Using Nickel Oxide/Activated Carbon

Nickel oxide, which acts as an intermediate Lewis acid, was loaded onto activated carbon (AC) to enhance the adsorption selectivity of AC in the desulfurization of model diesel. The total sulfur adsorption capacity increased from 2.46 to 4.42 mg-S·g adsorbent–1 and the total sulfur removal increased from 46.8 to 84.5% using the AC and Ni(10%)O/AC adsorbents, respectively. Multicomponent isothermal modeling showed that the incorporation of NiO onto AC significantly improved the synergistic interactions between the thiophenic compounds while mitigating competitive interactions between the more steric 4,6-dimethyl dibenzothiophene (4,6-DMDBT) and 4-methyl-dibenzothiophene (4-MDBT) compounds. The mitigation was attributed to new adsorbate-specific sites created by loading NiO on AC. Spent adsorbent characterization and pyridine adsorption-IR analysis suggested that higher desulfurization performance of the Ni(10%)O/AC adsorbent was attributed to an increase in the adsorbent’s Lewis acidity upon loading with NiO, leading to increased Ni–S acid–base interactions, in addition to π-complexation.

Clay authigenesis in carbonate-rich sediments and its impact on carbonate diagenesis

The Mg (δ26Mg), Ca (δ44Ca), and Sr (87Sr/86Sr) isotopic compositions of pore fluids, bulk carbonates, planktonic foraminiferal tests, and bulk clays from ODP Site 762 Hole B are presented, as are pore fluid and bulk carbonate δ26Mg and 87Sr/86Sr from ODP Site 806 Hole B and pore fluid δ26Mg from ODP Site 807 Hole A. The primary objective of the study is to elucidate the major processes controlling marine pore fluid δ26Mg, specifically the effects of calcite recrystallization and authigenic clay precipitation in sedimentary sections with relatively high carbonate contents. Such studies are critical for evaluating the potential of pore fluids in carbonate section to drive diagenetic alteration, which can compromise applications of geochemical proxies to the past. Pore fluid δ26Mg values at all three sites range from −0.83 to −0.13‰ and exhibit a systematic increase with depth. Bulk carbonate δ26Mg generally decrease with depth, ranging from −3.60 to −5.27‰, at Sites 762 and 806, while mixed species foraminiferal tests (∼250–500 μm) from Site 762 range between −5.08 and −4.36‰. Residual siliciclastics at depths of ∼105 to 145 mbsf at Site 762 have δ26Mg values (−0.09 to 0.27‰) that are markedly higher than carbonate and pore fluid δ26Mg values. Simple 1-D reactive transport modeling suggests that the general increase in pore fluid δ26Mg with depth, accompanied by a decrease in carbonate δ26Mg, is a result of calcite recrystallization (assuming an isotopic fractionation factor of ∼0.9955). However, subtle but significant deviations from the carbonate recrystallization-only scenario suggest that another process impacts δ26Mg at all three sites. Scanning electron microscope images document clay particles embedded in nannofossils and foraminiferal tests at Site 762, which suggest that clay authigenesis is active in carbonate sediments and could affect pore fluid δ26Mg. The formation of secondary clays preferentially sequesters isotopically heavy Mg (αclay-Mg2+≈1.0005), driving pore fluid δ26Mg to lower values. An increase in carbonate δ26Mg within the clay-rich layer at Site 762 and an increase in bulk carbonate Na/Ca supports the hypothesis that clay authigenesis also impacts the preservation of proxy archives. Multi-component reactive transport modeling suggests that authigenic rates of ∼1·10−13 mol/m3/s (∼3.15 µmol/m3/a; assuming that the authigenic clay is sepiolite) can generate deviations from the carbonate recrystallization-only case by several tenths of a permil, indicating that carbonate sediment-associated clay authigenesis (CSCA) may be more relevant in deep-sea carbonate sections than has been previously considered.