C4 Olefins Research Articles

ECERIFERUM1-6A is required for the synthesis of cuticular wax alkanes and promotes drought tolerance in wheat.

Cuticular waxes cover the aerial surfaces of land plants and protect them from various environmental stresses. Alkanes are major wax components and contribute to plant drought tolerance, but the biosynthesis and regulation of alkanes remain largely unknown in wheat (Triticum aestivum L.). Here, we identified and functionally characterized a key alkane biosynthesis gene ECERIFERUM1-6A (TaCER1-6A) from wheat. The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9)-mediated knockout mutation in TaCER1-6A greatly reduced the contents of C27, C29, C31, and C33 alkanes in wheat leaves, while TaCER1-6A overexpression significantly increased the contents of these alkanes in wheat leaves, suggesting that TaCER1-6A is specifically involved in the biosynthesis of C27, C29, C31, and C33 alkanes on wheat leaf surfaces. TaCER1-6A knockout lines exhibited increased cuticle permeability and reduced drought tolerance, whereas TaCER1-6A overexpression lines displayed reduced cuticle permeability and enhanced drought tolerance. TaCER1-6A was highly expressed in flag leaf blades and seedling leaf blades and could respond to abiotic stresses and abscisic acid. TaCER1-6A was located in the endoplasmic reticulum, which is the subcellular compartment responsible for wax biosynthesis. A total of three haplotypes (HapI/II/III) of TaCER1-6A were identified in 43 wheat accessions, and HapI was the dominant haplotype (95%) in these wheat varieties. Additionally, we identified two R2R3-MYB transcription factors TaMYB96-2D and TaMYB96-5D that bound directly to the conserved motif CAACCA in promoters of the cuticular wax biosynthesis genes TaCER1-6A, TaCER1-1A, and fatty acyl-CoA reductase4. Collectively, these results suggest that TaCER1-6A is required for C27, C29, C31, and C33 alkanes biosynthesis and improves drought tolerance in wheat.

Green diesel rich product (C-15) from the hydro-deoxygenation of refined palm oil over activated NH4 +-Indonesian natural zeolite

ABSTRACT Zeolite is a potential material for use as a catalyst in various catalytic reactions. In this research, green diesel-range hydrocarbons were successfully derived from refined palm oil via a hydrotreating process in a batch-stirred autoclave reactor using activated Indonesian natural zeolite (ANZ) as a catalyst. A series of detailed characterizations, including XRD, XRF, SEM, FTIR, N2 sorption isotherm, and NH3-TPD, were utilized to investigate the physicochemical properties of the catalyst. Herein, the ANZ, dominated by the mordenite phase, was prepared through dealumination and NH4 +-exchange, and directly used without calcination that is commonly performed to convert NH4 + into a proton. Moreover, the hydrotreating reaction was carried out at 375°C with a weight ratio of feed to catalyst of 100:1. The catalytic tests showed that C15 alkanes were the most dominant liquid product obtained via the decarbonylation reaction mechanism of refined palm oil. In addition, the highest activity of the ANZ catalyst exhibited up to ~36 wt.% and selectivity up to 70% toward the formation of C15 diesel-range with cetane numbers in the range 71 and 77.

Impact of water deficiency on leaf cuticle lipids and gene expression networks in cotton (Gossypium hirsutum L.)

BackgroundWater deficit (WD) has serious effect on the productivity of crops. Formation of cuticular layer with increased content of wax and cutin on leaf surfaces is closely related to drought tolerance. Identification of drought tolerance associated wax components and cutin monomers and the genes responsible for their biosynthesis is essential for understanding the physiological and genetic mechanisms underlying drought tolerance and improving crop drought resistance.ResultIn this study, we conducted comparative phenotypic and transcriptomic analyses of two Gossypium hirsutum varieties that are tolerant (XL22) or sensitive (XL17) to drought stress. XL17 consumed more water than XL22, particularly under the WD conditions. WD significantly induced accumulation of most major wax components (C29 and C31 alkanes) and cutin monomers (palmitic acid and stearic acid) in leaves of both XL22 and XL17, although accumulation of the major cutin monomers, i.e., polyunsaturated linolenic acid (C18:3n-3) and linoleic acid (C18:2n-6), were significantly repressed by WD in both XL22 and XL17. According to the results of transcriptome analysis, although many genes and their related pathways were commonly induced or repressed by WD in both XL22 and XL17, WD-induced differentially expressed genes specific to XL22 or XL17 were also evident. Among the genes that were commonly induced by WD were the GhCER1 genes involved in biosynthesis of alkanes, consistent with the observation of enhanced accumulation of alkanes in cotton leaves under the WD conditions. Interestingly, under the WD conditions, several GhCYP86 genes, which encode enzymes catalyzing the omega-hydroxylation of fatty acids and were identified to be the hub genes of one of the co-expression gene modules, showed a different expression pattern between XL22 and XL17 that was in agreement with the WD-induced changes of the content of hydroxyacids or fatty alcohols in these two varieties.ConclusionThe results contribute to our comprehending the physiological and genetic mechanisms underlying drought tolerance and provide possible solutions for the difference of drought resistance of different cotton varieties.

Bioethanol Conversion into Propylene over Various Zeolite Catalysts: Reaction Optimization and Catalyst Deactivation.

Catalytic conversions of bioethanol to propylene were investigated over different zeolite catalysts. H-ZSM-5 (SiO2/Al2O3 = 80) was found to be the most effective for propylene production. Furthermore, H-ZSM-5 (SiO2/Al2O3 = 80) was investigated under different variables of catalytic reaction (calcination temperature, feed composition, reaction temperature, and time on stream) for the conversion of ethanol to propylene. The H-ZSM-5(80) catalysts calcined at 600 °C showed the highest propylene yield. The moderate acidic site on ZSM-5 is required for the production of propylene. The activity on ZSM-5 is independent of the ethanol feed composition. H-ZSM-5 catalyst deactivation was observed, owing to dealumination. The highest propylene yield was 23.4% obtained over HZSM-5(80). Propylene, butene, and ≥C5 olefins were formed by parallel reaction from ethylene. Olefins were converted to each paraffin by sequential hydrogenation reaction. HZSM-5(80) catalyst is a promising catalyst not only for ethanol but also for the conversion of bioethanol to light olefins.

Exploring the kinetics and thermochemistry effects on C2-C6 alkene combustion chemistry by ȮH radical; Implications for Combustion Modeling and Simulation

A systematic theoretical study of C2 to C6 alkenes reacting with ȮH radical to explore the kinetics and thermochemistry effects are carried out in this work. The geometries and frequencies of 15 reactants, 15 pre-reaction complexes, 93 transition states, and 93 products are optimized at M06-2X/6-311++G(d,p) level of theory. The hindrance potentials for low-frequency torsional modes are treated at M06-2X/6–31 G level of theory. Single-point energies for all species involved in this work are calculated at spin-unrestricted CCSD(T)/CBS level of theory with basis-set correction from MP2/aug-cc-pVnZ (n = T and Q). High-pressure-limit rate constants for H-atom abstraction reaction channels and pressure-dependent rate constants for addition reaction channels are calculated by solving the Rice-Ramsperger Kassel-Marcus/Master Equation (RRKM/ME) implemented in the Master Equation System Solver (MESS) program, coupled with variational transition-state theory (VTST). Temperature-dependent thermochemical properties for all species and related radicals have been computed using a combination of composite methods to provide adequate accuracy results for modeling application. For straight-chain alkenes, the temperature range, in which the addition channel dominates, shifts to lower temperatures as the alkene gets longer. Hydrogen-atom abstractions from the allylic site of alkenes are the dominant reaction channels at high temperatures. The H-atom abstraction reactions from secondary alkylic and primary alkylic CH sites become more important as substituent groups become larger. High-pressure-limit and pressure-dependent rate constants calculated in this work have been extensively compared with the experimental and theoretical results available in the literature, and they show overall good agreement. The simulation results show that the calculated rate constants in this work have positive influences to the accuracy of simulation results at most reaction conditions. However, at some of the reaction conditions, thermochemical data have much more important influence to the simulation results at low temperature ranges. Rate constants obtained in this work and detailed branching ratio for each reaction can serve as a guidance in alkene combustion model development.

The Role of Vacancies in a Ti2CTx MXene‐Derived Catalyst for Butane Oxidative Dehydrogenation

AbstractMXenes are a new family of 2D carbides or nitrides that have attracted attention due to their layered structure, tunable surface groups and high electrical conductivity. Here, we report for the first time that the Ti2CTx MXene catalyses the selective oxidative dehydrogenation of n‐butane to butenes and 1,3‐butadiene. This catalyst showed higher intrinsic activity compared to a commercial TiC and TiO2 samples in terms of C4 olefin formation rate. We propose that the stabilisation of structural vacancies and the change in composition (from a carbide to a mixed phase oxide) in the MXene causes its higher catalytic activity. These vacancies can lead to a higher concentration of unpaired electrons in the MXene‐derived material, enhancing its nucleophilic properties and favouring the production of olefins.

Control of the proximity of bifunctional zeolite@Al2O3 catalysts for efficient methanol conversion into hydrocarbons

Bifunctional catalysts are widely applied for many important reactions as the synergetic effect of two types of active sites remarkably improves catalysis performance. However, their bifunctionality has not been fully exploited since the proximity of bifunctional catalysts is hard to control. Herein, we demonstrate a bifunctional ZSM-5@Al2O3 catalyst with a core-shell structure and a nano-scale proximity by in-situ growth of γ-Al2O3 nanosheets on the surface of ZSM-5 crystals for methanol conversion. The nano-scale proximity endows the catalyst with higher reaction activity and C2–C3 olefins yield (53 %) in comparison to the catalysts with micro-scale proximity (20 %) and millimeter-scale proximity (27 %), which can be attributed to the fluent transport of the reaction intermediates between two types of active sites. This strategy for constructing bifunctional catalysts with nano-scale proximity is conducive to understanding the relationship between proximity and catalytic performance in methanol conversion.

Polymers from organosilicon derivatives of 5-norbornene-2-methanol for membrane gas separation

In this work, we have proposed a new strategy to the synthesis of norbornene-type monomers with Si–O–C structural motifs via a straightforward and selective dehydrogenative addition reaction between 5-norbornene-2-methanol and trialkylsilanes. As a result, a set of monomers with various trilalkylsiloxy groups (alkyl – CH3, C2H5, and n-C3H7) was synthesized with the yields of 89–90%. These monomers exhibited a high reactivity in both metathesis and vinyl-addition polymerization, affording high-molecular-weight products in yields up to 90%. The metathesis polymers were rubbery with glass transition temperatures from −29 to +23 °C, while related isomeric vinyl-addition polynorbornenes were glassy polymers. Permeability (P) and diffusion (D) coefficients for these polymers were systematically evaluated for permanent gases (He, H2, O2, N2, and CO2) and C1–C4 alkanes. Studying their gas transport properties allowed to establish new structure-property relationships. Particularly, the length of alkyl fragments in trilalkylsiloxy group affected differently gas permeability of metathesis (rubbery) and vinyl-addition (glassy) polymers. Besides, it was shown that the method of linking the Si–O–C-containing group to the main chains of polymers played very important role: Alk3SiO-substituted polynorbornenes are more permeable than isomeric (AlkO)Alk2Si-substituted ones. For the metathesis polynorbornenes, P(CO2) were in the range of 152–226 Barrer, and ideal selectivity (α) of CO2/N2 – 13-16; for the vinyl-addition polynorbornenes, P(CO2) = 230–500 Barrer, and α(CO2/N2) = 14–17. Among studied polymers, promising results for ethane/methane separation was demonstrated by metathesis polynorbornene bearing tri(n-propyl)siloxymethyl substituents: P(C2H6) = 138 Barrer and α(C2H6/CH4) = 2.4. The obtained polymers were also characterized by using TGA, WAXD, and nitrogen adsorption-desorption methods.

Geochemical Characteristics and Gas Source Contributions of Noble Gases of the Sulige Large Tight Gas Field of Upper Paleozoic in Ordos Basin, China

Tight gas is the fastest developing unconventional natural gas resource, becoming the principal part for gas reserves and production growth in China. The Sulige gas field is the largest gas field and also the typical low porosity and low permeability tight sandstone gas field discovered in China, with an annual natural gas output exceeding 300 billion and cumulative output exceeding 290 billion, playing an important role in ensuring national energy provision, helping China’s energy transformation, and promoting green, low-carbon, environmental protection and high-quality development. Based on sample collection and laboratory analysis, natural gas compositions including hydrocarbons, non-hydrocarbons, light hydrocarbons, and noble gases of the Sulige gas field are systematically analyzed, their genetic identifications are identified, and finally gas source originations and contribution proportions are comprehensively discussed from the perspectives of noble gases and hydrocarbon gases. The main achievements are as follows: 1) natural gases in the Sulige gas field are mainly alkane gases, with high methane content, high drying coefficient, low heavy hydrocarbon contents, low non-hydrocarbon gas contents of CO2 and N2, and relatively low noble gas contents. The helium content is relative 2 order of magnitude higher than the atmospheric value, while neon, argon, krypton, and xenon are relatively about 1–2 orders of magnitudes lower than the atmospheric values. 2) The carbon and hydrogen isotopes of alkanes are generally positive sequence distributions with some part inversion. The 3He/4He values are mainly distributed in magnitude of 10−8, the 40Ar/36Ar is ranged from 506 to 1940, the 129Xe is relative loss, and the 132Xe is relative surplus. 3) Natural gases in the Sulige gas field are typical coal-formed gases generated from a humic organic mother material with maturity from high mature to over mature according to C7 and C8 light hydrocarbons and alkane carbon isotopes. Noble gases are typical crustal genesis, mainly originating from the radioactive decay of crustal source materials. 4) The gas source correlations of noble gases and alkane gases and their quantitative evaluations on source contributions show that natural gases in the Sulige gas field are originated from Carboniferous-Permian coal measure source rocks in Ordos Basin, mainly contributed by coals and supplemented by mudstones, accounting for 55–60% and 40–45%, respectively.

Sulfur‐Free Bimetallic Nix‐Fey/γ‐Al2O3 Catalysts for the Hydrodeoxygenation of Methyl Laurate to Biofuel

AbstractThe Ni/γ‐Al2O3, Nix‐Fey/γ‐Al2O3 and Fe/γ‐Al2O3 catalysts are prepared by impregnation method, and the influence of nNi/nFe on the performances of the prepared catalysts for the methyl laurate hydrodeoxidation (HDO) was evaluated. The prepared catalysts and precursors were characterized by BET, H2‐TPR, XRD, and H2‐TPD, which confirmed the existence of NiFe alloy is advantageous to improve the catalytic activity, and the synergistic effect between Ni and Fe was elucidated. The catalytic properties of the studied Nix‐Fey/γ‐Al2O3 catalysts with low Fe content was significantly worse than that of monocomponent Ni/γ‐Al2O3 catalyst, due to the migration and agglomeration of highly dispersed Ni0 species on the corresponding catalyst surface. The introduction of Fe species had significant influence on the HDO performances and product selectivity of the Ni‐based catalyst. The higher Fe content can promote the main reaction path from hydrodecarbonylation/hydrodecarboxylation to hydrodeoxygenation, which results in the high C12 alkane selectivity on the corresponding catalysts and inhibits the cracking reaction. The bimetallic Ni3‐Fe7/γ‐Al2O3 catalyst had the best methyl laurate hydrogenation performances. The conversion of methyl laurate was 93.3 % and the selectivity of alkane compounds could reach 90 % on the Ni3‐Fe7/γ‐Al2O3 catalyst at the reaction temperature of 340 °C.

Research on Efficient Preparation of Ethanol and C4 Olefins Based on Polynomial Regression and Two-Way ANOVA

C4 olefins and ethanol are essential chemical raw materials, and efficiently preparing them is a valuable topic. In this paper, in order to explore the influence of different catalyst combinations and temperatures on ethanol conversion and C4 olefin selectivity, firstly, for each catalyst combination, by observing the scatter diagram of ethanol conversion, C4 olefin selectivity and temperature, a polynomial regression model of no more than three times was established. Then, 42 regression equations corresponding to 21 catalyst groups were obtained. Twenty-one kinds of catalyst combinations were grouped by controlling variables. After grouping, the relationship between a single factor and temperature was discussed. Non-interactive two-way ANOVA judged the significance of a single factor, and the control variables among different groups were compared to determine the strong significant factors of ethanol conversion rate and C4 olefin selectivity. For judging the significance of temperature, the input rate of ethanol is ignored based on grouping, and the same catalyst combination is regarded as a repeated test. By single factor analysis, it is finally found that the temperature has higher significance to ethanol conversion rate and 400℃, while the selectivity to C4 olefins is much lower.

Mathematical optimization model on BP neural network for the preparation of C4 olefins by ethanol coupling

With industrial production, the continuous consumption of resources, people’s use, and consumption of resources make the community concerned about resources. C4 olefins are used as significant raw materials in chemical production, and the use of ethanol coupling to prepare C4 olefins will become an important route in industrial production in the future. The data of ethanol conversion and C4 olefin selectivity can reflect the utilization of resources in the reflective process.With the rapid growth of machine learning and intelligent computing, a large number and different kinds of models have been constructed for the utilization and consumption of resources, which makes it possible to optimize the process of ethanol coupling for the preparation of C4 olefins. The objective of this paper is to construct a mathematical optimization model for the preparation of C4 olefins by ethanol coupling. Firstly, the catalyst combination was split, and secondly, the prediction model for ethanol conversion and C4 selectivity was constructed based on BP neural network. Finally, the feasibility of the model was tested by determining three indicators, Correlation Coefficient (R), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). Meanwhile, the PCA algorithm was applied to rank the degree of influence of catalyst and temperature on the conversion of ethanol and C4 olefin selectivity.

Insights into the confinement effect on isobutane alkylation with C4 olefin catalyzed by zeolite catalyst: A combined theoretical and experimental study

Elucidating the confinement effect harbours tremendous significance for isobutane alkylation with C 4 olefin. Herein, the confinement effect over zeolite catalysts was elucidated by combining DFT calculations, experiments (using the novel Beta zeolite exposing only external surfaces (Beta-E) and conventional Beta-I zeolite with both external and internal surfaces) and multi-techniques ( e . g ., TGA-DTG, HRTEM, SEM and XRD). It is found that the main active sites for C 4 alkylation reaction are located on internal surface rather than external surface. On the external surface, the hydride transfer reaction does not occur because the H-shared intermediate cannot be formed without the confinement effect. Moreover, the external surface has stronger selectivity for C 4 olefin adsorption than isobutane, leading to enhanced oligomerization reactions. Therefore, the suitable micropore with confinement effect is essential for zeolite-catalyzed C 4 alkylation. The atomic-scale insights of this work are of great referential importance to the design of highly effective zeolite catalyst.

Highly selective formation of linear α-olefins over layered and hydrophilic Fe3O4/MAG catalysts in CO hydrogenation

Controlling the product distribution of Fischer–Tropsch synthesis (FTS) reaction has always been a challenge. Fe-based catalysts can produce linear α-olefins with high selectivity in FTS, but it is significantly affected by the secondary reactions of primary olefins. To enhance the olefin selectivity in CO hydrogenation, layered magadiite (MAG) supported Fe3O4 (Fe3O4/MAG) catalysts with hydrophilic property was prepared by solvent (ethanol and water) dispersion methods. The selectivity of C2–C4 olefins can reach 46% (O/P = 6.15) over Fe3O4/MAG (ethanol) catalyst, which is much higher than that of 14% over unsupported Fe3O4 under the same reaction conditions. The particle size of Fe3O4 in Fe3O4/MAG has a great influence on the product distribution. The Fe3O4 with particle size of about 20 nm affords high olefin selectivity to C2–C4 (52%) with super high O/P value of 15 (olefin selectivity of 93.8% in C2–C3 fraction) and low CH4 selectivity of 7%, while the one with particle size about 400 nm affords extremely high linear α-olefin selectivity of 77.9% in C2+ hydrocarbons. In situ DRIFTS and C2H4/H2-TPSR/MS showed that the layered structure and hydrophilic groups can reduce the possibility of secondary hydrogenation reactions. Also, the complex formed by ethanol and surface hydroxyls induces the chain propagation, and promotes more linear α-olefin formation.

GEOCHEMISTRY AND CARBON ISOTOPE CHARACTERISTICS OF ASSOCIATED GASES FROM OILFIELDS IN THE NW GREATER CAUCASUS, RUSSIA

The NW Greater Caucasus and surrounding areas have a long history of petroleum production dating back to the mid-19th century. However the origin of the oil and gas is still a matter of debate. This paper focusses on a study area to the north of the western Greater Caucasus covering the West and East Kuban Basins and neighbouring structural highs where oil and natural gas occur in reservoir units of Neogene, Paleogene, Cretaceous and Jurassic ages. The study is based on the results of organic geochemical and stable carbon isotope analyses of 21 samples of associated gases from 16 oil fields. The gas samples' compositions were investigated together with the δ13C values of C1 to C5 alkanes. Twenty of the gas samples were of thermogenic origin and one was mixed (thermogenic and secondary microbial). δ13C values for CH4 for all the gas samples varied over a wide range from -62.3 to -30.0 ‰, indicating major variations in the thermal maturity of the respective source rocks. In a previous study, three genetic types of oil were identified in the study area and are referred to here as Types 1, 2 and 3. Gaseous hydrocarbons associated with Type 1 oils were generated by source rocks in the Middle Eocene Kuma Formation and the Oligocene (lower) part of the Maikop Group which are inferred to have been deposited in anoxic, deep-marine conditions. C2–C5 alkanes in gases associated with Type 1 oils have the lowest (most negative) δ13C values of the samples studied, and the lowest iso-butane: n-butane and iso-pentane: n-pentane ratios. These gas samples were recovered from wells in oilfields located in the south and SE of the West Kuban Basin, in the Akhtyrskaya fault zone which extends along the northern flank of the Greater Caucasus foldbelt. Higher δ13C values of C2–C5 alkanes were found in gas samples associated with Type 2 oils which were recovered from wells in the central West Kuban Basin. The associated source rocks are interpreted to have been deposited in weakly oxidizing subaqueous conditions and to contain mainly marine organic matter but with an input of higher land plant material. The precise age and stratigraphic identity of the source rocks is unresolved but they may comprise the Upper Oligocene – Lower Miocene (middle and upper) part of the Maikop Group. In gases associated with Type 3 oils, δ13C values of ethane to pentane are similar to those of gases associated with Type 2 oils. These gases were recovered from wells in oilfields located on the Adygeya Swell which divides the southern East and West Kuban Basins and from the Armavir-Nevinnomyssk Swell to the north. The precise source of these gases and oils is not known but the oils are probably older than Late Cretaceous on account of the absence of oleanane.

Construction of an optimal model for the preparation of C4 olefins based on multiple regression

In this paper, based on the data obtained from a series of experiments conducted by a chemical laboratory for different catalysts at different temperatures, the optimization model and regression relationship model are established by using Gibbs free energy law, chemical equation energy analysis, chemical reaction equilibrium, the preparation of C4 alkenes by ethanol coupling was studied. By analyzing the temperature variation law of ethanol conversion and C4 olefin selectivity under different catalyst combinations, a regression relationship model was established, and the functional relationship between the variables was obtained. Then, the effects of different catalyst combinations and temperatures on ethanol conversion and C4 olefin selectivity were discussed. At the same time, in order to establish two optimization models, the first model is the C4 olefin yield model, which takes the minimum C4 olefin yield as the goal, and takes the range of factors such as temperature, and total mass as constraints. The second optimization model is based on the previous one with a constraint that the temperature is below 350°C, and then solved in MATLAB.

Ethane oxidative dehydrogenation by CO2 over stable CsRu/CeO2 catalyst

Oxidative and non-oxidative ethane dehydrogenation were studied and compared over Cs-promoted Ru/CeO2 catalyst. The presence of CO2 improved the ethane conversion to ethylene and led to the formation of C3 and C4 olefins as well. The olefin selectivity and yield in ODH were affected by reaction variables including CO2/C2H6 ratio, temperature, and feed rate. The CsRu/CeO2 remained stable activity for 93 days under reactive conditions wherein intermittent shutdowns and startups were performed. Mechanistically, the interaction between Cs and Ru with ceria in the crystalline structure facilitated reduction and oxidation cycles. It was postulated that Ce3+ had a strong tendency to react with CO2 to form Ce4+, whereas Ce4+ was reduced by hydrogen from ethane dehydrogenation to form Ce3+. The redox cycle can be repeated during the ODH reaction keeping the catalyst active. Furthermore, in the ODH reaction, the CsRu/CeO2 catalyst exhibited resistance to carbon deposition, evidenced by the carbon balance measurement.

Chemical Synthesis Data Modeling Based on Mathematical Optimization

As one of the most important high value-added raw materials in the chemical industry, the synthesis of C4 Olefin by ethanol coupling was of great significance in the field of the chemical industry. Different catalysts and various conditions have different effects on the chemical reaction. This paper is based on the relevant data set. Firstly, Pearson and Spearman correlation coefficient method and corresponding hypothesis test are used to get the influence of different catalysts on the chemical reaction. Ethanol conversion and C4 Olefin selectivity are positively correlated with temperature. Secondly, a multivariate linear regression model with significant core variables is constructed to investigate the effects of catalyst combination and temperature on ethanol conversion and C4 Olefin selectivity. It can be concluded that the ethanol concentration is greatly affected by temperature and CO loading, and there is a positive and negative correlation between ethanol concentration and CO loading. The selectivity of C4 Olefin is affected by temperature and is positively correlated with the charge ratio of CO/SiO2 and HAP. Finally, by using a multiple regression equation and simulated annealing model, it can be obtained that when the loading of CO is 4.75 wt%, the loading ratio of CO/SiO2 and HAP is 1 : 1.4242, the concentration of ethanol is 0.3658 ml/min, and the temperature is 448.21°C, the loading ratio of CO/SiO2 and HAP is 1 : 1.4242, the concentration of ethanol is 0.3658 ml/min, and the temperature is 448.21°C, the yield of C4 Olefin can reach a higher value.

Microwave-responsive SiC foam@zeolite core-shell structured catalyst for catalytic pyrolysis of plastics

Catalytic pyrolysis is a promising chemical recycling technology to supplement mechanical recycling since plastics can be broken down into monomers or converted to the required fuels and chemicals. In this study, a microwave (MW) -responsive SiC foam@zeoltie core-shell structured catalyst was proposed for the catalytic pyrolysis of polyolefins. Under microwave irradiation, the SiC foam core works as both microwave adsorber and catalyst support, thus concentrating the generated heat energy on the ZSM-5 zeolite shell, where the catalytic reaction takes place. SiC foam with an open cellular structure can also improve the global transport of mass and heat during plastics pyrolysis. In this work, the effects of the SiO2/Al2O3 ratio and alkaline treatment of ZSM-5 zeolite coated SiC foam under MW irradiation on the variations in product distribution from low-density polyethylene (LDPE) pyrolysis were investigated at 450 °C. The results indicated that the appropriate acidity and pore structure were crucial to upgrading gas and liquid products. Particularly, the creation of a mesoporous structure in ZSM-5 zeolite via alkaline treatment could improve the diffusion of large molecules and products, thus significantly increasing the selectivity of high-valued light olefins and aromatics while inhibiting the formation of unwanted alkanes, which are expected in the chemical industry. Concretely, the concentration of olefins in gas increased to 51.0 vol% for ZSM-5(50)-0.25AT, and 65.6 vol% for ZSM-5 (50)-0.50AT, compared with 45.2 vol% for the parent ZSM-5(50). The relative concentration of aromatics in liquid decreased from 96.6% for ZSM-5(50) to 75.9% for ZSM-5(50)-0.25AT, and 71.1% for ZSM-5(50)-0.50AT. Given the respective yield of gas and liquid, the total selectivity of C2–C4 olefins and aromatics for mesoporous ZSM-5 zeolites could reach 58.6–64.9% during LDPE pyrolysis, which were higher than that for the parent ZSM-5 zeolite.

Prediction Model and Optimization of Coupling Reaction Yield Based on BP Neural Network

The preparation of C4 olefins from ethanol has become a research hotspot in the field of chemical product production. Based on the test data of given catalyst combination at different temperatures, a neural network prediction model for the effect of different catalyst combination and temperature on C4 olefin yield is proposed in this paper. Firstly, taking the catalyst combination and temperature as independent variables, the C4 olefin yield is analyzed by multiple regression analysis and evaluated by R-square index. Secondly, on the basis of this experiment, the BP neural network model for predicting the yield of coupling reaction is reconstructed, and the adaptive genetic operator is added to the BP neural network to optimize its threshold, weight, and convergence speed, so as to improve the accuracy of yield prediction. Finally, the prediction results of BP and GA-BP models are compared from five aspects: SSE, MAE, MSE, RMSE, and MAPE. The experimental results show that the improved model has good global optimization ability and high yield prediction accuracy in the prediction of coupling reaction yield. Therefore, the multiple control variable model proposed in this paper has a certain positive significance for predicting the effect of catalyst combination on yield in coupling reaction.