Diesel Yield Research Articles

Experimental Study and Prospects of Valorization of Jatropha Curcas Seeds into Biodiesel

Jatropha curcas L. is a promising oilseed plant for biodiesel given its oil content and its tendency to grow in harsh environmental conditions. In this study, we conducted experiments on the valorization of jatropha seeds into biodiesel in order to estimate the key parameters of the process and the properties of the obtained biodiesel. The results revealed that the molar ratio between triglycerides and methanol, catalyst concentration, and reaction temperature played an important role in the diesel yield. The biodiesel produced had physicochemical characteristics in line with international standards for diesel fuels, with combustion properties comparable to those of conventional diesel. This study shed light on the optimization of the process of valorization of jatropha curcas seeds into biodiesel and on the support of the potential as a renewable fuel source.

Integrated Hybrid Modelling and Surrogate Model-Based Operation Optimization of Fluid Catalytic Cracking Process

Fluid Catalytic Cracking (FCC) is one of the most important conversion processes in oil refineries, widely used to convert high-boiling, high-molecular-weight hydrocarbon components from crude oil into more valuable products like gasoline and diesel. Advanced simulation and optimization technologies are critical for improving the operational efficiency and economic performance of the FCC process. First-principles-based simulators rely on parameter estimation and are computationally intensive, making them unsuitable for online optimization. In recent years, with the development of deep learning, data-driven models have made significant progress in FCC modeling. However, due to their black-box nature and difficulty with extrapolation, they are rarely used for optimization. To bridge this gap, we propose an integrated framework that combines hybrid modeling and surrogate model-based optimization. This approach combines plant and simulation data to train a multi-task learning prediction model, which then serves as a surrogate for operational optimization. Validated on a large-scale FCC unit in southern China, the model predicts product yields with an error margin of under 4.84% for all products. Following optimization, yields of LNG, gasoline, and diesel rose by an average of 0.10 wt%, 1.58 wt%, and 1.05 wt%, respectively, resulting in a 3.67% increase in product revenues. This highlights the substantial potential of this framework for industrial applications.

Green Diesel Production Through Deoxygenation Reaction with Natural Zeolite-supported Nickel and Copper Catalyst

The depletion of fossil fuels and their environmental impact necessitate sustainable alternatives. Green diesel, a biofuel with a chemical structure similar to conventional diesel, has gained traction as a viable alternative. This study explores the development of a cost-effective catalyst for green diesel production using deoxygenation. Deoxygenation refers to a broad class of chemical reactions where oxygen atoms are stripped from a molecule. This research employed abundant Indonesian natural zeolite (NZ) as a catalyst support, impregnated with non-noble metals, nickel (Ni), and copper (Cu). The investigation revealed that the NiCu/NZ catalyst achieved the highest oleic acid conversion (90.40%) and green diesel yield. The product distribution, ranging from C15 to C18 hydrocarbons, reflects the moderate acidity of the catalyst, promoting diverse cracking patterns compared to highly acidic catalysts. Additionally, the high specific surface area of NZ facilitates the conversion and good product distribution. Furthermore, the optimization process demonstrated that increasing hydrogen pressure during deoxygenation enhances both conversion rate and green diesel production.

Simulation analysis of gas-solid two-phase flow and reaction in a novel catalytic cracking reactor

A gas-solid two-phase flow reaction model was developed to evaluate the performance of a novel catalytic cracking reactor in the residue-to-chemicals (RTC) process. Coupled TFM, EMMS drag, and 12-lump kinetic models were employed to simulate the flow reaction process. The reaction temperature and product yields at the reactor exit aligned well with real industrial RTC reactor test results, indicating the reliability and effectiveness of the coupling model. Catalyst particles formed an internal circulation structure in the reactor, increasing the instantaneous catalyst-to-oil ratio. The reactor exhibited low axial and radial temperature gradients with higher reaction temperatures, accelerating the catalytic cracking rate and enhancing the selectivity for high-value products. The effects of the catalyst-to-oil ratio, catalyst inlet temperature, and feedstock mass flow rate on the flow reaction process were optimized. Results showed that both the catalyst-to-oil ratio and catalyst inlet temperature influenced the overall catalyst velocity distribution. Within the limit range, increasing the catalyst-to-oil ratio increased feedstock conversion, gasoline, LPG, dry gas, and coke yields, but decreased diesel yield. Conversely, increasing the feedstock mass flow rate showed opposite trends. Different trends in product yields were observed with varying inlet catalyst temperatures, with optimal product distribution at 973.15 K.

The catalytic deoxygenation reaction temperature and N2 gas flow rate influence the conversion of soybean fatty acids into Green Diesel

BackgroundGreen diesel is a promising alternative as a petroleum replacement given the worldwide demand for petroleum fuel. Environmental issues have drawn public attention and concerns towards advancing renewable energy development. A catalytic deoxygenation (deCOx) was carried out to produce green diesel from soybean oil (SO) using a low-cost NiO-doped calcined dolomite (NiOCD) catalyst. MethodThe structure, chemical composition and morphology of NiOCD were comprehensively characterized by XRF, BET, TPD-CO2, SEM and TEM. In this study, the effect of two operating parameters, reaction temperature and flow rate of nitrogen, was discovered using a one-factor-at-a-time (OFAT) optimisation study. In addition, the life cycle cost analysis (LCCA) of stepwise catalyst preparation and green diesel production has been performed. Significant findingsAn optimal reaction temperature of 420 °C was found to provide the highest yield of green diesel (47.13 wt.%) with an 83.51% hydrocarbon composition. The ideal nitrogen flow rate, however, was found to be 50 cm3/min, which produced 41.80 wt.% of green diesel with an 88.63% hydrocarbon composition. The deoxygenation reaction was significantly impacted by both reaction temperature and nitrogen flow rate. According to LCCA, NiOCD catalyst has potential to lower the overall cost of producing green diesel compared to commercial zeolite catalysts.

A multiscale adaptive framework based on convolutional neural network: Application to fluid catalytic cracking product yield prediction

Since chemical processes are highly non-linear and multiscale, it is vital to deeply mine the multiscale coupling relationships embedded in the massive process data for the prediction and anomaly tracing of crucial process parameters and production indicators. While the integrated method of adaptive signal decomposition combined with time series models could effectively predict process variables, it does have limitations in capturing the high-frequency detail of the operation state when applied to complex chemical processes. In light of this, a novel Multiscale Multi-radius Multi-step Convolutional Neural Network (MsrtNet) is proposed for mining spatiotemporal multiscale information. First, the industrial data from the Fluid Catalytic Cracking (FCC) process decomposition using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) extract the multi-energy scale information of the feature subset. Then, convolution kernels with varying stride and padding structures are established to decouple the long-period operation process information encapsulated within the multi-energy scale data. Finally, a reconciliation network is trained to reconstruct the multiscale prediction results and obtain the final output. MsrtNet is initially assessed for its capability to untangle the spatiotemporal multiscale relationships among variables in the Tennessee Eastman Process (TEP). Subsequently, the performance of MsrtNet is evaluated in predicting product yield for a 2.80 × 106 t/a FCC unit, taking diesel and gasoline yield as examples. In conclusion, MsrtNet can decouple and effectively extract spatiotemporal multiscale information from chemical process data and achieve a approximately reduction of 30% in prediction error compared to other time-series models. Furthermore, its robustness and transferability underscore its promising potential for broader applications.

Sustainable synthesis: High-efficiency ZrO2/KIT-6 catalyst to hydroprocess waste plastics into fuels

Synthetic plastic pollution devastates the environment, human health, biodiversity, and economics of livelihood. Amid various emerging strategies, pyrolysis and subsequent catalytic hydroprocess stand out as promising methods. This upgradation path presents a practical and sustainable approach to transforming plastic waste into valuable resources, and lessening environmental impact. This study aims to produce a higher yield of diesel from mixed plastic trash that satisfies regulatory requirements. The ZrO2/KIT-6 catalyst for hydroprocess accomplished this task and provided the highest yield of chemically equivalent diesel. HDPE, LDPE, and PP waste plastics were independently pyrolyzed using a ZSM-5 catalyst and the pyrolyzed oil of each constituent was mixed to obtain mixed plastic pyrolysis oil. The mixed plastic pyrolysis oil was further upgraded through hydroprocess. Gas chromatography and mass spectroscopy of the obtained fuel revealed a composition comprising aromatics, n-alkanes, and isoalkanes, with each constituent displaying a 95% correlation with commercial diesel. The produced fuel is blended with diesel, followed by comprehensive engine performance assessments to gauge combustion efficiency, overall functionality, and emissions. The evaluation of engine performance outcomes revealed a 93% similarity in emissions. The viability of obtaining clean energy from waste plastics while adhering to legal constraints is presented in this study.

Effect of polypropylene pyrolyzate as the solvent on hydrodeoxygenation of palm oil using Ni-Cu/ZrO2 catalyst

Green diesel is a biofuel that can be used directly in diesel engines and can be synthesized by hydrodeoxygenation (HDO) reaction of triglyceride (TG). Generally, this reaction requires a high hydrogen pressure (40–150 bar) and a high composition of organic solvent to facilitate a higher hydrogen solubility in the liquid phase. In many cases, long carbon-chain alkanes, mostly n-dodecane, have been used as solvents. The present work aims to investigate the potential of hydrogenated and non-hydrogenated polypropylene (PP) pyrolyzate as solvents in an effort to utilize plastic wastes in HDO reaction of palm oil. The reaction was carried out using bimetallic catalyst Ni-Cu/ZrO2 in a reactor with a hydrogen gas self-inducing impeller to facilitate a higher load-up hydrogen gas in the liquid phase. The effect of reaction time in HDO involving two solvents, i.e., PP pyrolyzate and hydrogenated PP pyrolyzate, was elucidated in this work. The results showed that hydrogenated PP pyrolyzate facilitates a higher deoxygenation activity than PP pyrolyzate. In addition, the synthesized bimetallic catalyst promoted the decarbonylation/decarboxylation route over the hydrodeoxygenation route at reaction temperatures of 280–350 °C. The conversion of TG increased from 51 % to 93 % by increasing the reaction temperature from 280 °C to 350 °C, with the corresponding highest yield of green diesel was 82 %. Therefore, the hydrogenated PP pyrolyzate can substitute the usual long carbon-chain alkanes.

Thermal conversion performance, kinetic mechanism, and products of electric vehicle lithium battery diaphragms

The proliferation of waste lithium batteries is on the rise; however, the thermal treatment attributes of these batteries are largely overlooked, and the conversion mechanism of lithium battery separators remains unclear. This study marks the first comprehensive to compare the thermal degradation characteristics, kinetic parameters and mechanisms, thermal degradation products, and degradation pathways of polypropylene (PP) and polyethylene (PE) lithium battery diaphragms. The pyrolysis temperatures for the PP and PE were 340–500 and 440–530 °C, respectively. PP and PE exhibited average activation energies of 65.19–73.04 and 207.62–209.40 kJ/mol, respectively. At 600–800 °C, the yields of PP and PE pyrolysis gases and gasoline products increased with increasing temperature, while the yields of diesel and paraffin products decreased. The most dominant products generated from the pyrolysis of PP and PE were olefins, and the amount of olefin products from PE increased with increasing pyrolysis temperature. CH3 fracture was the first reaction step that occurred during PP pyrolysis. Our study provides useful information for industrial recycling, disposal, and utilization of electric vehicle lithium battery separators as well as data on the pyrolysis behaviours and transformation mechanisms of polyolefin wastes.

Fischer–Tropsch Synthesis Catalysts for Selective Production of Diesel Fraction

The Fischer–Tropsch process is considered one of the most promising eco-friendly routes for obtaining synthetic motor fuels. Fischer–Tropsch synthesis is a heterogeneous catalytic process in which a synthesis gas (CO/H2) transforms into a mixture of aliphatic hydrocarbons, mainly linear alkanes. Recently, an important direction has been to increase the selectivity of the process for the diesel fraction. Diesel fuel synthesized via the Fischer–Tropsch method has a number of advantages over conventional fuel, including the high cetane number, the low content of aromatic, and the practically absent sulfur and nitrogen impurities. One of the possible ways to obtain a high yield of diesel fuel via the Fischer–Tropsch process is the development of selective catalysts. In this review, the latest achievements in the field of production of diesel via Fischer–Tropsch synthesis using catalysts are reviewed for the first time. Catalytic systems based on Al2O3 and mesoporous silicates, such as MCM-41, SBA-15, and micro- and mesoporous zeolites, are observed. Together with catalytic systems, the main factors that influence diesel fuel selectivity such as temperature, pressure, CO:H2 ratio, active metal particle size, and carrier pore size are highlighted. The motivation behind this work is due to the increasing need for alternative processes in diesel fuel production with a low sulfur content and better exploitation characteristics.

Mansonia altisima residue ash (MARA): A precursor for a Nano catalytic (CaO- SiO2-K2O) base employed for the production of JS.22 green diesel

JS.22 seed oil was transesterified into green diesel in an effort to create a nontoxic and environmentally friendly fuel. Mansonia altisima residual ash (MARA) was used to create an alkaline base catalyst, which was then evaluated using SEM, FTIR, BET, XRF, and qualitative analysis. Three factors (EtOH/OMR, reaction duration, catalyst quantity, and reaction temperature) were taken into account during process optimization utilizing the Stat Ease 360 optimizer.The catalyst reusability test was used to gage the strength of the utilized catalyst. The physical and chemical characteristics of oil made it suitable for transesterification. CaO-K2O-SiO2 is recognized as a catalyst composition by catalyst analysis. At the following conditions: reaction duration of 50 min, catalyst quantity of 2.0 (%wt), and E-OH/OMR of 4.0 (vol/vol), process optimization predicted a green diesel yield of 98.99% (vol/vol). Process optimization predicted a 98.99% (vol./vol.) green diesel yield under the following conditions: reaction time of 50 min; catalyst amount of 2.0 (%wt); and E-OH/OMR of 4.0 (vol./vol.). However, statistical analysis was validated, and the average means of 98.78% (vol./vol.) were obtained with p-values of 0.0001. The catalyst reusability test was suspended after the eighth cycle since the yield had significantly dropped.The green diesel qualities complied with the suggested green diesel standard.

High Acidity and Low Carbon-Coke Formation Affinity of Co-Ni/ZSM-5 Catalyst for Renewable Liquid Fuels Production through Simultaneous Cracking-Deoxygenation of Palm Oil

This study investigates the effect of chemically doped Co and Ni metals on ZSM-5 catalyst with respect to the catalysts’ characteristics and performance for palm oil cracking. Some characterization methods have been conducted to identify the physicochemical properties of the synthesized catalysts, including X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), N2-physisorption, NH3- and CO2-probed Temperature Programmed Desorption (NH3-TPD and CO2-TPD) methods. The deposited carbon-coke on the spent catalysts is analysed using simultaneous thermal gravimetric – differential scanning calorimetry (TG-DTG-DSC) analysis. The performance of catalysts was evaluated on palm oil cracking process in a continuous fixed-bed catalytic reactor at 450 °C. To determine the liquid product composition functional group and components, we used Attenuated Total Reflectance Fourier-transform Infrared Spectroscopy (ATR-FTIR) and batch distillation methods, respectively. We found that the Co metal chemically-doped on Ni/SM-5 catalyst, resulting the increase in the catalysts acidity and the decrease in catalysts basicity. The conversion of palm oil increases as the increase of the ratio of catalysts’ acidity to basicity. The highest triglyceride conversion (76.5%) was obtained on the 3Co-Ni/ZSM-5 with the yield of gasoline, kerosene, and diesel of 2.61%, 4.38%, and 61.75%, respectively. It was also found that the chemically doping Co metal on Ni/ZSM-5 catalyst decreased carbon-coke formation due to the low catalysts’ basicity. Overall, it is proven that the combination of Co and Ni, which chemically doped, on ZSM-5 catalyst has a good activity in palm oil conversion with low carbon-coke formation affinity and high acidity of catalyst.

Design and validation of a microalgae biorefinery using machine learning-assisted modeling of hydrothermal liquefaction

A new microalgae biorefinery system adopts an integration of the hydrothermal liquefaction (HTL) of (wet) microalgae and hydrodeoxygenation (HDO) of biocrude oil to produce green products of green diesel, naphtha, and heavy oil, where the HTL and HDO processes are validated through Aspen Plus® simulator. A hybrid model of HTL of microalgae, which consists of the machine learning-assisted model and the GAMS®-assisted RYield reactor, is used to predict the yield, higher heating value (HHV), and yield component distribution of biocrude oil according to the experimental records of the HTL process from 16 species of microalgae. Three types of machine learning (ML)-assisted modeling of the HTL process are illustrated, where the LSBoost model is validated to be better than other ML-assisted models through the testing procedure for measuring R2 and root mean square error (RMSE).To evaluate the performance of the microalgae biorefinery system, it is noted that the green diesel yield is up to 33 wt% and the energy recovery of HTL of Nannochloropsis sp. is estimated at 75 % higher than around 60 % of the HTL of Trentepohlia.

Mo promoted Ni-ZrO2 co-precipitated catalysts for green diesel production

The promoting action of Mo-species was studied for Ni-ZrO2 co-precipitated catalysts with high nickel loading used in the transformation of sunflower oil into green diesel. The catalysts were thoroughly characterized and evaluated using a high-pressure semi-batch reactor. The significant promoting action of molybdenum species was clearly demonstrated concerning the Ni-ZrO2 catalysts as Mo addition resulted in almost duplication of green diesel yield (from 35.2 to 68.4 %). This is manifested through the acceleration of the hydrodeoxygenation pathway of the reaction network. The increase of the activation temperature increases further the catalytic efficiency of the promoted catalysts resulting in 70.1 % green diesel yield. The promoting action of molybdenum was partly attributed to the increase of the specific surface area and the metallic nickel surface brought about by molybdenum but, principally, to a synergy between the oxygen vacancies developed on the very well dispersed Mo-species - and the nickel surface sites.

Study on efficient utilization of light cycle oil with combined process

ABSTRACT A combined process of hydrotreating, fractionating, solvent extraction, and fluid catalytic cracking (FCC) was proposed to improve the added value of light cycle oil (LCO). In the process, hydrotreating LCO (HLCO) was divided into light and heavy fractions by fractionating. The bicyclic and tricyclic aromatics in the heavy fraction of HLCO were extracted to produce chemical products by solvent extraction. The raffinate oil and the light fraction of HLCO, rich in saturated hydrocarbons and monocyclic aromatic hydrocarbons, were processed to produce high-octane gasoline by FCC. According to the results, the combined process solved the problem of polycyclic aromatic hydrocarbons of HLCO being challenging to be cracked in FCC reaction, reduced the yield of dry gas and coke by 43.01 wt%, reduced the yield of diesel with low added value by 32.33 wt%, and optimized the product structure. In other words, the process makes efficient use of the aromatic and nonaromatic components in LCO.

Deep Bayesian Slow Feature Extraction With Application to Industrial Inferential Modeling

Inferential modeling has been of significance for modern manufacturing in estimating the quality-related process variables. As an effective inferential model, probabilistic slow feature analysis (PSFA) has gained attention in regression tasks to interpret dynamic properties with a slowness preference. However, PSFA is often challenged by the nonlinear sequential data due to its linear state-space structure. In this article, a new nonlinear extension of PSFA is proposed under the deep learning framework to enhance the dynamic feature extraction with limited labels, incorporating variational inference and Monte Carlo inference to derive the objective function. The proposed model considers the relevance of inputs with outputs as the input weights to upgrade prediction performance. The proposed model is verified through an industrial hydrocracking process to predict diesel yield with missing labels ranged from 0% to 50%, and the root mean squared error is reduced by at least 8.78% compared to PSFA.

Production of Biodiesel from Jatropha Curcas by using Heterogenous Dopped Zinc Oxide

Heterogenous copper based nano catalyst was synthesized by Co-precipitation method. The effect of nano catalyst particle size from 0.5 to 52 nm was investigated. The Cupper dopped zinc oxide the nano particle size was used from 0.5 to 52 nm, and Transesterification method was used to produce the biodiesel. The optimum yield of bio-biodiesel was obtained 92% from Jatropha Curcas seed oil. SEM shows the surface morphology, topography, composition, crystallographic and structural shape of synthesized Cu-ZnO nano catalyst. XRD and EDX results depicted good morphology of prepared catalyst. XRD and EDX also displays the pattern of a model Cu-ZnO. FTIR results showed the major functional groups identified were alkanes , aromatics and carboxylic acid . Among these functional groups, alkanes were qualitatively noted to be the main constituents which indicate the good catalytic cracking activity of the catalyst.The UV, absorbance peak indicated the presence of ZnO nanoparticles, which is in accordance of UV absorbance result shown by previous studies. The effect of temperature on biodiesel yield showed from higher yield with 45 o C from 64.33 to 80 ml of ethanol concentration at 45 o C. On further rise in temperature resulted 92% product yield. Furthermore, effect of methanol on bio- diesel yield showed that, as the methanol ratio subsequently increased from 1: 05 to 1: 12increased the product yield. Besides this, the heterogeneous nano catalyst showed good catalytic activity in transforming Jatropha seed oil up to 92% of biodiesel yield.

Characterization Studies for Derived Biodiesel from the Fluid Catalytic Cracking (FCC) of Waste Cooking Oil through a Fixed Fluidized Bed (FFB)

Biodiesel production through transesterification or catalytic hydrogenation using vegetable oil is a sustainable method, but it has the downsides of by-product generation and a higher cost. Therefore, in this study, waste cooking oil was selected as a raw material, and fluidized catalytic cracking was carried out on the catalyst (LDO-75) through a fixed-fluidized-bed (FFB) reactor. The effects of the reaction temperature, catalyst–oil ratio and weight hourly space velocity (WHSV) on the yield of pyrolysis gas, gasoline, diesel and heavy oil fractions were studied. The composition of the pyrolysis gas was determined by gas chromatography (GC), the composition of the gasoline fraction was analyzed by gas chromatography-mass spectrometry (GC-MS), and the characteristics of the diesel and heavy oil fractions were determined by nuclear magnetic resonance (NMR). The results show that light olefins are the main products of pyrolysis gases, and the liquid products are mainly composed of aromatic compounds. In addition, the catalytic cracking process of waste cooking oil fluid is proposed, indicating that the process of the catalytic cracking of waste cooking oil fluid includes deoxygenation, oligoaromatization and hydrodeoxygenation. The results of this study will provide a basis for the high value-added utilization of waste cooking oil.

Effect of FCC light diesel blending ratio on properties of refined products in diesel hydrofining unit

Under the background of product oil market surplus and Double carbon target, reducing refined oil and increasing chemical feedstock can speed up the adjustment of industrial structure and improve the core competitiveness of enterprises. In order to reduce diesel and gasoline ratio and increase naphtha production to extend chemical industrial chain, the influence of FCC light diesel blending ratio on properties and yield of refined products was studied in this paper. The experiment result showed naphtha yield decreased and diesel yield increased with increasing of the blending ratio of FCC light diesel in straight run diesel. The desulfurization effect of refined diesel is better, and diesel CI decreased but it still can meet the quality requirements of products. The content of alkane in naphtha decreased while the aromatic latencies increased, so naphtha is suitable for catalytic reforming. The optimum blending ratio of FCC light diesel is 12%. While naphtha is used as cracking feedstock FCC light diesel blending ratio should be reduced. The experimental results can lay a foundation for further research on straight-run diesel blending with other oils, and provide technical support and reference data for feedstock adjustment of similar units.

Bio‐fuels production through waste tires pyrolytic oil upgrading over Ni‐W/zeolite composites derived from blast furnace slag

Waste tires is one of the solid residuals that can have serious impacts environmentally. Therefore, controlling this waste through conversion into value-added products such as bio-fuels is highly recommended. Consequently, this work reports catalytic-hydrocracking of waste tire pyrolytic oil (WTPO) to fuels over Ni-W supported on zeolite X and A. The zeolites were hydrothermally synthesized from another type of waste, namely blast furnace slag (BFS). The prepared samples were characterized by X-ray diffraction (XRD) analysis. The successive synthesis of zeolites A and X could be detected through observing cubic and octahedral particles via scanning electron microscopy (SEM). The two prepared catalysts presented mesoporous natures with reasonable specific surface area, as acquired from nitrogen adsorption-desorption analysis. The catalysts activity toward upgrading of WTPO was investigated under different operating conditions. Particularly, both catalysts have exhibited high activity through producing reasonable yields of gasoline (35% and 40%) and high yields of diesel (45% and 30%) by Ni-W loaded zeolite A and X, respectively. Additionally, zeolite X supported catalyst showed a higher selectivity toward catalytic HDS of WTPO than the zeolite A. The former optimum findings were collected at the following operating conditions: 80 bar, 450°C and LHSV of 1.2 h−1.