Figure 1.
Schematic of laboratory scale pyrolysis reactor used in this study.
Citation: Chisato Kinoshita, Koji Aoyama, Toshio Nakaki. microRNA as a new agent for regulating neuronal glutathione synthesis and metabolism[J]. AIMS Molecular Science, 2015, 2(2): 124-143. doi: 10.3934/molsci.2015.2.124
| [1] | Lihao Chen, Kunio Yoshikawa . Bio-oil upgrading by cracking in two-stage heated reactors. AIMS Energy, 2018, 6(1): 203-215. doi: 10.3934/energy.2018.1.203 |
| [2] | Shouyun Cheng, Lin Wei, Xianhui Zhao, Yinbin Huang, Douglas Raynie, Changling Qiu, John Kiratu, Yong Yu . Directly catalytic upgrading bio-oil vapor produced by prairie cordgrass pyrolysis over Ni/HZSM-5 using a two stage reactor. AIMS Energy, 2015, 3(2): 227-240. doi: 10.3934/energy.2015.2.227 |
| [3] | Vincent E. Efeovbokhan, Augustine O. Ayeni, Osuvwe P. Eduvie, James A. Omoleye, Oladotun P. Bolade, Ajibola T. Ogunbiyi, Victoria N. Anyakora . Classification and characterization of bio-oil obtained from catalytic and non-catalytic pyrolysis of desludging sewage sample. AIMS Energy, 2020, 8(6): 1088-1107. doi: 10.3934/energy.2020.6.1088 |
| [4] | Hasanudin Hasanudin, Wan Ryan Asri, Utari Permatahati, Widia Purwaningrum, Fitri Hadiah, Roni Maryana, Muhammad Al Muttaqii, Muhammad Hendri . Conversion of crude palm oil to biofuels via catalytic hydrocracking over NiN-supported natural bentonite. AIMS Energy, 2023, 11(2): 197-212. doi: 10.3934/energy.2023011 |
| [5] | Lihao Chen, Hu Wu, Kunio Yoshikawa . Research on upgrading of pyrolysis oil from Japanese cedar by blending with biodiesel. AIMS Energy, 2015, 3(4): 869-883. doi: 10.3934/energy.2015.4.869 |
| [6] | Lifita N. Tande, Valerie Dupont . Autothermal reforming of palm empty fruit bunch bio-oil: thermodynamic modelling. AIMS Energy, 2016, 4(1): 68-92. doi: 10.3934/energy.2016.1.68 |
| [7] | Sunbong Lee, Shaku Tei, Kunio Yoshikawa . Properties of chicken manure pyrolysis bio-oil blended with diesel and its combustion characteristics in RCEM, Rapid Compression and Expansion Machine. AIMS Energy, 2014, 2(3): 210-218. doi: 10.3934/energy.2014.3.210 |
| [8] | Xianhui Zhao, Lin Wei, James Julson . First stage of bio-jet fuel production: non-food sunflower oil extraction using cold press method. AIMS Energy, 2014, 2(2): 193-209. doi: 10.3934/energy.2014.2.193 |
| [9] | Deinma T. Dick, Oluranti Agboola, Augustine O. Ayeni . Pyrolysis of waste tyre for high-quality fuel products: A review. AIMS Energy, 2020, 8(5): 869-895. doi: 10.3934/energy.2020.5.869 |
| [10] | Gustavo Aguilar, Pranjali D. Muley, Charles Henkel, Dorin Boldor . Effects of biomass particle size on yield and composition of pyrolysis bio-oil derived from Chinese tallow tree (Triadica Sebifera L.) and energy cane (Saccharum complex) in an inductively heated reactor. AIMS Energy, 2015, 3(4): 838-850. doi: 10.3934/energy.2015.4.838 |
In search of renewable energy sources, the production of liquid hydrocarbons from biomass or bio-hydrocarbons has been considered as one of the priorities by many workers around the globe. Biohydrocarbons are composed of hydrocarbons with different numbers of carbon, and from fuel point of view they can be distinguished into biogasoline, which is a mixture of hydrocarbons with carbon chain of C5-C12, kerosene fuel or bioavture, which is a mixture of hydrocarbons with carbon chain of C13-C17, and biodiesel, which is a mixture of C18-C28 [1,2]. The opportunity to produce bio-hydrocarbons is supported by the development of pyrolysis technology, in which biomass is subjected to thermal treatment in the absence or limited oxygen to produce products in the forms of gas, liquid, and solid [3]. The liquid product is generally known as pyrolysis oil or bio-crude oil (BCO) which is a complex mixture consisting of a large number of compounds including hydrocarbons together with oxygenated organic compounds, such as acids, aldehydes, ketones, ester, and phenols [4,5,6,7].
The presence of non-hydrocarbon components is the main limitation that prevents direct use of BCO as a fuel for ignition machines. To eliminate the oxygenated components of the BCO, two upgrading treatments have been developed, known as hydro treatment upgrading and catalytic upgrading. In the hydro treatment method, hydrogen is reacted with BCO to reduce its oxygen content by the formation of water, thus increasing the hydrocarbon content of the upgraded fuel [6,8]. The main drawback of the hydro treatment method is the need to use large volumes of hydrogen and relatively high pressure. Due to this limitation, catalytic upgrading is more desirable since in this method no need to use hydrogen, and can be carried out at atmospheric pressure. produces hydrocarbon rich upgraded fuel.
The major catalysts used for BCO upgrading reported in literatures are zeolites since this type of material has been acknowledged to have a good ability to promote deoxygenation during pyrolysis through three mechanisms, i.e., by decarbonylation, decarboxylation, and dehydrogenation [8]. The most widely used zeolites reported in previous work are HZSM-5 and zeolite-Y [3,9,10,11]. Other catalysts that have been reported for the same purpose are activated natural zeolites with different Si/Al ratios [12], β-zeolites [13], and NiN-supported natural bentonite [14].
In this study, the BCO obtained by pyrolysis of palm oil without the use of a catalyst was subjected to catalytic upgrading using protonated zeolite-Y (H-Y) as catalyst. The H-Y zeolite was selected since this zeolite is cheaper than HZSM-5 and can be synthesized with a much simpler procedure than that required for the preparation of HZSM-5. Preparation of H-Y was conducted in two stages, starting with the synthesis of zeolite-Y (Na-Y) from rice husk silica and food grade aluminium foil using the hydrothermal method, followed by protonation of the Na-Y through ion exchange using aluminium nitrate solution with different concentrations to produce zeolite H-Y with different protonation levels. The use of ammonium nitrate solution with different concentrations was intended to obtain the H-Y zeolites with different protonation levels. Successful formation of Na-Y and H-Y zeolites was confirmed by characterization using XRD and SEM techniques, while the protonation was evaluated by analysis using XRF technique. The Na-Y and H-Y zeolites were then utilized for catalytic upgrading of BCO produced by pyrolysis of palm oil without the use of a catalyst. The chemical compositions of both BCO and upgraded fuels were then analyzed using GC-MS.
Sodium hydroxide and nitric acid (reagent grade) were purchased from Aldrich. Rice husk (RH) and food grade aluminum foil were obtained from local sources in the City of Bandar Lampung. Crystallization process of zeolite was conducted using a polytetrafluoroethylene (PTFE) lined stainless steel autoclave, and calcination of zeolite was performed using a Nabertherm electrical furnace (Lilienthal, Germany). XRD characterization was performed using a PANalytical type Empyrean diffractometer and SEM characterization using a scanning electron microscope model Zeiss EVO MA 10. XRF analysis was conducted on the PANalytical Epsilon 3 instrument. Pyrolysis experiment was carried out using a laboratory scale pyrolysis unit, and bio-oil resulted was analyzed using the GCMS-QP2010 SE SHIMADZU instrument. The MS Library systems NIST62.LIB and WILEY229.LIB were applied to identify the components of the BCO and upgraded oils. To determine the relative percentage of each component of the samples identified, the peak area of the component was divided by the total area of all identified components.
The RHS was obtained utilizing the sol-gel process as reported in a previous study [4]. Typically, a mixture of 50 g dried husk with 500 mL of 1.5% NaOH was boiled for 30 min, and then left at room temperature for 24 h. The mixture was filtered and the filtrate, which contains silica (silica sol), was collected and then neutralized (pH of 6.8–7.0) with HNO3 solution (10%) to transform silica from sol to gel, followed by aging of the gel for 24 hours. The excess of acid was removed by repeated rinsing of the gel with distilled water, and then the gel was oven dried at 110 ℃ for eight hours. To obtain a sample with a relatively homogeneous size, the silica was ground into powder and sieved with a 250 mesh sieve.
Zeolite-Y was synthesized from RHS, sodium hydroxide, and aluminum foil with the composition to satisfy the formula of Na2O.Al2O3.4.8SiO2.xH2O. In contrast to the other three components, in this molecular formula, the amount of H2O is uncertain depending on the further treatment applied to the sample, for example, calcination. For this reason, the amount of H2O in the molecular formula of the zeolite is expressed as x. Typical procedure for zeolite preparation consists of dissolving 8.0 g NaOH in 250 mL of distilled water, and 175 mL of the solution was used to dissolve 28.8 g of RHS and the rest (75 mL) to dissolve 5.4 g aluminum foil. The two solutions were then thoroughly mixed using a laboratory blender. The mixture was transferred into a Teflon lined stainless autoclave and allowed to stand at room temperature for 24 hours to age. After aging treatment was completed, the sample was subjected to crystallization by placing the autoclave in an oven at 100 ℃ for 48 hours. After the completion of crystallization process, the autoclave was allowed to cool to ambient temperature, and then the sample inside the autoclave was filtered. The solid was collected and rinsed with distilled water to remove the excess of alkali, and then oven dried at 80 ℃ for twenty four hours. The dry sample was ground into 250 mesh powder and finally calcined at 550 ℃ for six hours.
Conversion of zeolite-Y into zeolite H-Y was conducted by ion exchange adopting the method described in previous work by others [15]. Zeolite-Y was mixed with ammonium nitrate solution with the ratio of 1 g zeolite/10 mL ammonium nitrate solution of different concentrations of 2.0; 2.5; 3.0; and 3.5 M. The mixture was sealed and placed on a hotplate stirrer for 6 hours at 80 ℃. After the completion of the experiment, the mixture was filtered and the solid was oven dried at 80 ℃ for 8 hours, and finally calcined at 550 ℃ for 6 hours to obtain protonated zeolite-Y (H-Y zeolite).
The XRD pattern for phase identification was produced by PANalytical type Empyrean diffractometer, using CuKα (λ = 1.54 Å) radiation with the energy of 40 kV and current of 100 mA. The pattern was recorded over the 2θ range of 5–90°, with a scanning rate was 0.06°s−1. The phase identification was done by comparing the pattern with that of the standard listed in the International Zeolite Association (IZA) files. The surface morphology of the sample was examined using SEM technique. The instrument was operated at 30 KV, with an electron acceleration voltage of 20 kV, and the sample was scanned at different magnifications to produce micrographs that display a better image of the surface.
Pyrolysis experiment was performed in a laboratory scale pyrolysis reactor with a schematic arrangement as shown in Figure 1. The first experiment was carried out to produce bio crude oil (BCO) by pyrolysis of palm oil without the use of catalyst. The typical experiment was conducted by transferring 350 mL of palm oil into the inside chamber of the reactor and then the reactor was heated. The cracking products were passed into the condenser and the condensed liquid was collected. The liquid produced was collected for 60 minutes and then transferred into a separatory funnel to allow separation between water phase and organic phase (BCO), which was then used in catalytic upgrading experiment. For the catalytic upgrading experiment, an aliquot of 100 mL of BCO was mixed with 5 g of the catalyst, and then the mixture was transferred into the reactor. The mixture was then pyrolyzed and liquid product (upgraded oil) was collected for 30 minutes. The BCO and upgraded fuel were analyzed by GC-MS and the chemical components of the samples were tentatively identified with the aid of MS Library systems NIST62.LIB and WILEY229.LIB. For component identification, the GC-MS analysis was conducted to evaluate the effect of protonation of the zeolite on the chemical composition of the upgraded fuel.
To see if the zeolite-Y was successfully prepared using the method applied, the sample produced was analyzed using XRD and SEM. Characterization of the sample using XRD produced the diffraction pattern as shown in Figure 2. As can be seen in Figure 2, the XRD pattern (diffractogram) of the synthesized sample is characterized by the presence of sharp peaks, which confirm the existence of the sample as crystalline material, although the existence of an amorphous state should also be acknowledged. In addition, it can be seen that the XRD pattern of the sample is identical to the pattern of the standard zeolite-Y, more specifically faujasite type. Concerning this result of XRD characterization, it is concluded that preparation of zeolite-Y was accomplished as expected.
For further confirmation, the positions (2θ) of some characteristic diffraction peaks of the sample were compared with those of the standard zeolite-Y available in the International Zeolite Association (IZA) Data Base as shown in Table 1. As can be seen in the data, no significant difference in the position (2θ) of the seven peaks is listed in Table 1, although the difference in the relative intensity should be noted, which is most likely due to different crystallinity between the sample synthesized and the standard zeolite. Without ignoring the differences found, based on XRD characteristics presented in Figure 2 and Table 1, it can be concluded that the zeolite-Y has been successfully prepared.
| Standard zeolite-Y | Synthesized zeolite-Y | ||
| 2θ (°) | Relative intensity (%) | 2θ (°) | Relative intensity (%) |
| 6.183 | 100 | 6.209 | 100 |
| 10.104 | 9.09 | 10.097 | 34.47 |
| 11.854 | 7.34 | 11.819 | 14.92 |
| 15.600 | 10.46 | 15.557 | 23.64 |
| 18.621 | 4.10 | 18.548 | 6.13 |
| 20.288 | 3.96 | 20.191 | 12.60 |
| 37.575 | 0.14 | 20.191 | 7.13 |
DownLoad:
CSV
Another unique feature of zeolites is the shape of the particle, in which each zeolite has its particle shape. For this reason, characterization using SEM is an important part of zeolite investigation. In this respect, the zeolite-Y synthesized was also characterized using SEM, and the micrographs of the sample with different magnifications are shown in Figure 3.
As can be seen in Figure 3, the existence of crystallite particles is displayed by the micrographs even at low magnification (1000 x). By increasing the magnification to 5000 x, the presence of particles with octahedral structure, which is the characteristic shape of zeolite-Y, can be observed more evidently. This shape of particles observed in this study is in agreement with the shape of zeolite-Y reported in other studies [16,17].
To investigate the extent of zeolite-Y protonation accomplished, the samples produced from ion exchange experiments with NH4NO3 solution of different concentrations were analyzed using XRF to determine the Na contents before and after ion exchange treatments. The results obtained are shown in Table 2.
| [NH4NO3], M | Na content (%) | Na reduction (%) |
| - | 1.15 | 0 |
| 2.0 | 0.83 | 27.82 |
| 2.5 | 0.72 | 37.95 |
| 3.0 | 0.58 | 49.65 |
| 3.5 | 0.12 | 89.95 |
DownLoad:
CSV
As displayed by the experimental data in Table 2, the ion exchange treatment resulted in reduction of Na contents of the zeolite, confirming that some of the Na+ ions in the zeolite-Y have been replaced by H+ ions. The data also indicate that the reduction of Na+ content increased with increased concentration of NH4NO3 solution, with the highest reduction of 89.948% was achieved with the use of 3.5 M NH4NO3 solution.
To study the effect of protonation treatments applied, the protonated samples produced using NH4NO3 solution with different concentrations were analyzed using SEM, and the diffractograms obtained are compiled in Figure 4. For simplicity, the protonated samples are specified as H-Y1, H-Y2, H-Y3, and H-Y4, which refer to the NH4NO3 concentration of, 2.0, 2.5, 3.0, and 3.5 M, respectively. As the case with the micrograph of the unprotonated zeolite-Y presented in Figure 4, the micrographs of the protonated samples shown in Figure 4 are characterized by the existence of crystalline particles with octahedral shape, implying the samples retain their particle shape although some of the Na+ ions have been replaced by H+ ions. However, protonation also led to the formation of spherical clusters, and with increased concentrations of NH4NO3 led to formation of more clusters as seen in the micrograph of the H-Y4 sample. In this respect, the micrographs also suggest that protonation most likely led to a decrease in the crystallinity of the samples.
In this study, the BCO was produced by pyrolysis of palm oil without the use of catalyst and the BCO was analyzed using GC-MS. The chromatogram of the sample is shown in Figure 5.
It is typical of BCO to be produced by pyrolysis of biomass reported in the literature [3,4]. The GC chromatogram in Figure 5 indicates that the BCO consists of a large number of compounds. The components of the BCO were then identified with the aid of the MS Library system NIST12.LIB and WILEY229.LIB. These databases also provide a similarity index (SI), which indicates the agreement between the MS data for compounds found in the sample with those of the standard compounds provided in the database. The identified components of the BCO sample with the aid of the above MS Library systems are listed in Table 3. In this respect, it should be acknowledged that some of the components were not identified, mostly because of their very small quantities, below the limit of detection of the instrument used. With respect to the distribution of products, the possibility of some error in the relative percentage of the compounds should be acknowledged. This limitation should be taken into account since in the GC-MS analysis the relative percentage of the compound detected is calculated based on the peak area of the compound and does not take into account the difference in peak is of different compounds although they have the same quantity.
| Peak No. | Retention time (Min) | SI (%) | Compound name | Molecular formula | Category | Relative percentage (%) |
| 1 | 2.475 | 94 | 1-Hexene | C6H12 | Hydrocarbon | 2.39 |
| 2 | 3.694 | 97 | 1-Heptene | C7H14 | Hydrocarbon | 2.17 |
| 3 | 3.861 | 96 | Heptane | C7H16 | Hydrocarbon | 3.01 |
| 4 | 6.605 | 96 | 1-Octene | C8H16 | Hydrocarbon | 2.89 |
| 5 | 6.941 | 95 | Octane | C8H18 | Hydrocarbon | 4.69 |
| 6 | 9.279 | 96 | Ethylbenzene | C8H10 | Hydrocarbon | 0.90 |
| 7 | 9.645 | 94 | Benzene | C8H10 | Hydrocarbon | 0.91 |
| 8 | 10.598 | 96 | 1-Nonene | C9H18 | Hydrocarbon | 3.03 |
| 9 | 10.967 | 96 | Nonane | C9H20 | Hydrocarbon | 5.11 |
| 10 | 14.552 | 98 | 1-Decene | C10H20 | Hydrocarbon | 2.75 |
| 11 | 14.890 | 96 | Decane | C10H22 | Hydrocarbon | 3.26 |
| 12 | 18.202 | 96 | 1-Undecene | C11H22 | Hydrocarbon | 3.04 |
| 13 | 18.505 | 96 | Undecane | C11H24 | Hydrocarbon | 2.62 |
| 14 | 18.660 | 95 | 2-Undecene | C11H22 | Hydrocarbon | 1.21 |
| 15 | 21.351 | 85 | Undecanoic Acid | C11H22O2 | Acid | 0.92 |
| 16 | 21.551 | 95 | 1-Dodecene | C12H24 | Hydrocarbon | 2.25 |
| 17 | 21.828 | 97 | Dodecane | C12H26 | Hydrocarbon | 3.11 |
| 18 | 24.292 | 86 | Dodecanoic Acid | C12H24O2 | Acid | 1.15 |
| 19 | 24.666 | 96 | 1-Tridecene | C13H26 | Hydrocarbon | 3.41 |
| 20 | 24.921 | 97 | Tridecane | C13H28 | Hydrocarbon | 4.43 |
| 21 | 27.331 | 91 | Tetradecanoic Acid | C14H28O2 | Acid | 7.35 |
| 22 | 27.573 | 98 | 1-Tetradecene | C14H28 | Hydrocarbon | 3.94 |
| 23 | 27.803 | 97 | Tetradecane | C14H30 | Hydrocarbon | 4.17 |
| 24 | 30.293 | 97 | 1-Pentadecene | C15H30 | Hydrocarbon | 2.25 |
| 25 | 30.553 | 97 | Pentadecane | C15H32 | Hydrocarbon | 12.25 |
| 26 | 32.856 | 98 | 1-Hexadecene | C16H32 | Hydrocarbon | 0.80 |
| 27 | 33.043 | 96 | Hexadecane | C16H34 | Hydrocarbon | 1.21 |
| 28 | 34.935 | 93 | 1-Heptadecene | C17H34 | Hydrocarbon | 1.31 |
| 29 | 35.075 | 97 | 8-Heptadecene | C17H34 | Hydrocarbon | 1.33 |
| 30 | 35.475 | 96 | Heptadecane | C17H36 | Hydrocarbon | 1.79 |
| 31 | 39.979 | 94 | 2-Heptadecanone | C17H34O | Ketone | 0.84 |
| 32 | 41.405 | 92 | Octadecanoic Acid | C18H36O2 | Acid | 8.19 |
| 33 | 44.788 | 93 | Oleic Acid | C18H34O2 | Acid | 1.32 |
DownLoad:
CSV
With respect to the categorization method found in the literature, the identified components of the BCO produced from the experiment without the use of catalyst (Figure 5) were classified into three more common categories of chemical compounds. The three categories are hydrocarbon, acid, and ketone, as indicated in Table 3. Categorizing the components of BCO is also useful to estimate the relative composition of the BCO as a base to compare the composition of BCO samples obtained from different experiments. To determine the relative percentage of each component of the BCO, the following Eq (1) was used:
| $ \%i = \frac{{A}_{i}}{{A}_{t}}x100 $ | (1) |
i = component i
Ai = peak area of component i
At = total peak of all identified components
To calculate the relative composition of the BCO in terms of general categories, the relative percentages of all components in the category were then added. Using this calculation approach, the results for the BCO obtained by pyrolysis of palm oil without catalyst (Figure 5) are presented in Table 3. As can be seen in Table 3, the main component of the BCO is a hydrocarbon category that contributes 80.23% to the composition, followed by 18.93% acid and 0.84% ketone. It is also observed that the hydrocarbon fraction of the BCO consists of linear alkanes and their corresponding alkenes, as indicated by the presence of two peaks at each carbon number. This pattern is in agreement with that of BCO derived from cork granules reported by others [18].
The upgraded oils obtained from catalytic upgrading experiments using Na-Y and H-Y zeolites as catalysts were analyzed using GC-MS and the GC chromatograms obtained are shown in Figure 6. As displayed in Figure 6, the appearance of chromatograms of the upgraded oils using H-Y catalysts is very similar, suggesting that the oils are composed of mostly the same compounds. A different pattern was observed for the upgraded oil using the Na-Y catalyst, in which more compounds were observed and distributed at a longer retention time range, suggesting the presence of compounds with higher molecular weight in the sample.
Due to the complexity of its chemical composition, it is very difficult to describe the characteristics of BCO based on a single component. For practical reasons, the components of BCO were commonly assigned to more general categories of organic compounds. As an example, Yoo et al. [19] divided the components of liquid fuel obtained by pyrolysis of wild reed were grouped into oxygenate, phenolic, aliphatic hydrocarbon, monocyclic aromatic, polycyclic aromatic, and nitrogen-containing species. In another study, the components of BC produced by pyrolysis of grass biomass (Napier grass) the components of liquid fuel obtained by pyrolysis of Napier were divided into hydrocarbon, aromatic, phenol, alcohol, and other oxygenates [20].
The upgraded oils obtained from catalytic upgrading experiments using Na-Y and H-Y zeolites as catalysts were analyzed using GC-MS and the GC chromatograms obtained are shown in Figure 6. As displayed in Figure 6, the appearance of chromatograms of the upgraded oils using H-Y catalysts is very similar, suggesting that the oils are composed of mostly the same compounds. Different pattern was observed for the upgraded oil using Na-Y catalyst, in which more compounds were observed and distributed at a longer retention time range, suggesting the presence of compounds with higher molecular weight in the sample
The components of the samples produced from upgrading experiments (upgraded oils) were identified and their relative percentages were calculated in the same way as applied to the BCO produced without catalyst, and the results are summarized in Table 4.
| Chemical component | Catalyst | ||||
| Na-Y | H-Y1 | H-Y2 | H-Y3 | H-Y4 | |
| Cyclohexene | 0.60 | 0.48 | 0.47 | 0.52 | 0.44 |
| 1-Octene | 3.30 | 3.18 | 2.39 | 2.63 | 2.34 |
| Octane | 4.38 | 3.50 | 3.44 | 3.56 | 3.21 |
| 2-Octene | 0.46 | nd | 0.36 | nd | nd |
| Ethylbenzene | 0.90 | 0.78 | 0.93 | nd | 0.80 |
| 1, 3-dimethylbenzene | nd | 0.66 | nd | nd | nd |
| 1-Nonene | 3.57 | 2.77 | 2.66 | nd | 0.66 |
| Nonane | 6.86 | 5.11 | 5.10 | 5.56 | 2.48 |
| 4-Nonene | nd | nd | nd | nd | 4.77 |
| 1-Decene | 3.32 | 2.56 | 2.44 | nd | 2.31 |
| Decane | 4.44 | 3.46 | 3.36 | nd | 3.26 |
| Cyclopropane, octyl- | nd | 3.14 | 3.00 | 3.51 | nd |
| 4-Undecene | nd | 0.81 | 0.96 | nd | 2.90 |
| Undecane | nd | 3.82 | 3.63 | nd | nd |
| 5-Undecene | nd | 1.77 | 1.69 | nd | 3.54 |
| Isopentylbenzene | nd | nd | 0.68 | nd | nd |
| 1-Dodecene | 4.02 | 3.25 | 3.14 | 2.01 | 1.30 |
| Dodecane | 6.16 | 5.02 | 5.04 | 4.29 | 1.73 |
| 2-Dodecene | nd | nd | nd | 2.15 | 1.70 |
| 6-Dodecene | nd | nd | nd | nd | 4.89 |
| Cyclodecane | 6.66 | nd | nd | nd | nd |
| Cyclododecane | 2.56 | 2.74 | 5.46 | nd | nd |
| 1-Tridecene | nd | 2.81 | 8.27 | nd | nd |
| Tridecane | 9.57 | 8.54 | nd | 5.62 | 5.82 |
| 1-Tetradecene | nd | nd | 3.85 | nd | 4.59 |
| 3-Tetradecene | nd | nd | 2.14 | 3.23 | nd |
| 5-Tetradecene | nd | nd | 8.62 | 9.09 | 9.55 |
| 6-Tetradecene | nd | nd | nd | 1.35 | 1.89 |
| Tetradecane | nd | 8.24 | nd | 3.98 | 7.64 |
| Cyclotetradecane | nd | 6.25 | 0.69 | 2.92 | nd |
| 1-Pentadecene | 3.70 | nd | 1.72 | 1.20 | 0.87 |
| Pentadecane | 22.23 | nd | nd | nd | 22.1 |
| Cyclohexylhexane | 0.82 | nd | nd | nd | nd |
| 1-Hexadecene | nd | nd | 6.92 | nd | 1.12 |
| 3-Hexadecene | nd | nd | nd | 0.68 | 2.65 |
| Hexadecane | 2.25 | 2.16 | 3.40 | 9.25 | nd |
| 3-Hexadecene | nd | nd | nd | nd | 0.28 |
| Heptadec-8-ene | 1.10 | nd | nd | 2.06 | 1.64 |
| Heptadecane | 2.49 | 21.70 | 8.29 | 23.5 | 1.59 |
| Heptadec-1-ene | nd | nd | nd | 0.89 | nd |
| 9-Octadecene | 1.06 | 1.80 | 0.96 | 2.67 | nd |
| 5-Octadecene | nd | 0.99 | 2.21 | 1.12 | nd |
| Dodecane, 2-cyclohexyl | nd | nd | 0.77 | nd | nd |
| 3-Octadecene | nd | 1.22 | nd | nd | nd |
| Octadecane | nd | 2.63 | nd | nd | 3.10 |
| 1-Nonadecene | nd | nd | 2.30 | 1.33 | nd |
| 3-Eicosene | nd | nd | 1.16 | nd | nd |
| 9-Eicosene | nd | nd | 1.26 | 1.46 | nd |
| Eicosane | nd | nd | 2.69 | 3.141 | nd |
| Heptyl methyl ketone | nd | nd | nd | 1.51 | nd |
| 2-Heptadecanone | 0.60 | nd | nd | 0.77 | 0.83 |
| 9-Heptadecanone | nd | 0.61 | nd | nd | nd |
| Hydroxymethyl ethyl ester | 0.88 | nd | nd | nd | nd |
| Nonadecane, 1, 2-epoxi | 0.61 | nd | nd | nd | nd |
DownLoad:
CSV
As displayed by the experimental results in Table 4, the samples are characterized by the existence of some common compounds, while some others are found only in certain samples indicating that some compositional differences between the samples should also be acknowledged. These compositional similarities and differences between the samples are related to the complexity of the reactions during the catalytic upgrading process applied. To make the comparison between the samples easier, the components of the samples were grouped into more general categories as indicated in Table 5.
| Catalyst | Relative composition (%) | ||||
| Hydrocarbon | Acid | Ketone | Ester | Ether | |
| - | 80.23 | 18.93 | 0.84 | - | - |
| Na-Y | 90.46 | - | 0.60 | 8.33 | 0.61 |
| H-Y1 | 99.39 | - | 0.61 | - | - |
| H-Y2 | 100.00 | - | - | - | - |
| H-Y3 | 97.72 | - | 2.28 | - | - |
| H-Y4 | 99.17 | - | 0.83 | - | - |
DownLoad:
CSV
The results in Table 5 displays several interesting features of the relative compositions of the samples. First is the presence of hydrocarbon as the component with the highest relative percentage in all samples, including the BCO, which was produced without the use of a catalyst. With respect to hydrocarbon content, it was also observed that the percentage of this category is significantly lower than those found for the upgraded fuels. In addition to significant increases in hydrocarbon contents as a result of upgrading treatment, another interesting result is that in the upgraded oils, no acid was found, suggesting that the acid was completely deoxygenated during the upgrading process. Comparing the composition of upgraded oils, it can be seen that the hydrocarbon contents of the upgraded oils using H-Y catalysts are significantly higher than that of the upgraded oil using Na-Y as a catalyst. This trend implies that the increased acidity of H-Y, as compared to that of Na-Y, strengthens the performance of the catalysts for deoxygenation process. In addition to lower hydrocarbon content, the upgraded oil using Na-Y is characterized by the presence of ketone, ester, and ether, while in the upgraded oils using H-Y catalysts, only ketone was detected in addition to hydrocarbons, with the exception of the upgraded fuel using the H-Y2 catalyst, which is practically pure hydrocarbon. Overall, the results presented in Table 5 demonstrate that protonation extent has a significant effect on the hydrocarbon contents of the upgraded oil, which signify the appreciable performance of the protonated zeolites to enhance deoxygenation process, leading to hydrocarbon enrichment as expected. It is acknowledged that biomass pyrolysis involves complex and random non-stoichiometric reactions. Despite basic reaction features, several catalytic upgrading reactions leading to deoxygenation and hydrocarbon formation have been suggested, including cracking of long chain hydrocarbons, decarbonylation to remove oxygen as carbon monoxide, decarboxylation to remove oxygen as carbon dioxide, and hydrodeoxygenation to remove oxygen as water [21].
To provide more insight on the profile of hydrocarbon content in the BCO and upgraded oils, the hydrocarbons were distributed into biogasoline range (C5-C12), bioavture range (C13-C17), and biodiesel range (C18-C28) as shown in Table 6.
| Catalyst | Hydrocarbon distribution (%) | ||
| C5-C12 | C13-C17 | C18-C28 | |
| - | 43.33 | 36.89 | nd |
| Na-Y | 48.06 | 41.34 | 1.06 |
| H-Y1 | 42.30 | 50.45 | 6.64 |
| H-Y2 | 44.75 | 43.90 | 11.35 |
| H-Y3 | 24.23 | 63.77 | 9.72 |
| H-Y4 | 36.33 | 59.74 | 3.10 |
DownLoad:
CSV
As displayed by the data in Table 6, no biodiesel range hydrocarbon was found in BCO, which is in agreement with the results obtained for this particular sample, in which two C18 compounds detected are acids (Table 3). In all upgraded oils, the three hydrocarbon categories were found; however, no evident trend to draw the relation between the extent of protonation of the zeolite-Y and the distribution of the hydrocarbon in the oils. Regardless of this lack of evident relation, the results obtained displayed that Na-Y has the highest tendency to enhance the formation of biogasoline, while the H-Y3 is the catalyst with the highest tendency to promote the formation of bioavture. In all samples, it can be seen that biodiesel is the category with the lowest percentage.
The appearance of hydrocarbon compounds belonging to the biodiesel category (C18-C28) in the samples resulting from upgrading, while they are not detected in the BCO samples, is most likely due to deoxygenation of the acids contained in the BCO with the use of catalyst. This assumption is based on the characteristic of zeolite which has been acknowledged to have the ability to promote deoxygenation of oxygen-containing components of the BCO during the upgrading process [21].
Catalytic upgrading of BCO using zeolites as catalyst has also been reported in several literatures. As an example, Chen and Yoshikawa [9] conducted bio-oil upgrading using ZSM-5 as catalyst and reported that upgrading treatment resulted in a reduction of oxygen up to 16%. The same catalyst was used in the study by Pattiya et al. [22] to upgrade bio-oil produced from cassava rhizome and reported enhanced production of aromatic hydrocarbon. In another study [23], catalytic upgrading of volatiles obtained by pyrolysis of lignite sample using H-Y zeolite was reported and the results obtained indicate that upgrading process resulted in increased content of naphthalene and methylnaphthalene up to 8.9 and 6.8 times, respectively, compared to the contents in the original sample. With respect to increased hydrocarbon contents of upgraded bio-oil, the results obtained in this present study are in agreement with the findings reported by others, although some differences in the types of hydrocarbons obtained should be acknowledged.
The results of this investigation demonstrated that zeolite-Y was successfully prepared from rice husk and food grade aluminium as raw materials, as confirmed by the results of XRD which show the existence of faujasite phase, and SEM which displays the existence of octahedral structure. The zeolite was then successfully converted into protonated zeolite with varied protonation extents depending on the concentration of the ammonium nitrate solution used, where the highest Na content reduction up to 89.948% was achieved according to XRF results. The results of catalytic upgrading experiments demonstrate that H-Y zeolites functioned to increase the bio-hydrocarbon content from 80.23% in the BCO to practically 100% in the upgraded oil. In addition, no acids were identified in the upgraded fuels, implying that H-Y zeolite is a promising catalyst for BCO upgrading for bio-hydrocarbon enrichment of the oil.
The authors declare that they have not used Artificial Intelligence (AI) tools in the creation of this article.
We thank the Ministry of Research, Technology and Higher Education of the Republic of Indonesia for their financial support through a research grant Fundamental Research, 2022, contract number: 027/E5/PG.02.00/PT/2022.
The authors declare no conflicts of interest in this paper.
Conceptualization, W.S. and K.D.P.; Methodology, W.S. and K.D.P.; Software, K.D.P. and I.I.; Validation, W.S.; K.D.P.; and I.I.; Formal Analysis, K.D.P and I.I.; Investigation, T.D.F. and A.P.I.; Resources, K.D.P. and W.S.; Data Curation, K.D.P. and I.I.; Visualization, T.D.F. and A.P.I.; Project Administration, K.D.P. and I.I.; Writing—Original Draft Preparation, W.S.; K.D.P. and S.H.; Writing—Review & Editing, W.S.; K.D.P. and S.H.; All authors have read and agreed to the published version of the manuscript.
| [1] | Lee RC, Feinbaum RL, Ambros V (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75: 843-854. |
| [2] |
Lagos-Quintana M, Rauhut R, Lendeckel W, et al. (2001) Identification of novel genes coding for small expressed RNAs. Science 294: 853-858. doi: 10.1126/science.1064921
|
| [3] |
Lau NC, Lim LP, Weinstein EG, et al. (2001) An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science 294: 858-862. doi: 10.1126/science.1065062
|
| [4] |
Lee RC, Ambros V (2001) An extensive class of small RNAs in Caenorhabditis elegans. Science 294: 862-864. doi: 10.1126/science.1065329
|
| [5] |
Pasquinelli AE, Reinhart BJ, Slack F, et al. (2000) Conservation of the sequence and temporal expression of let-7 heterochronic regulatory RNA. Nature 408: 86-89. doi: 10.1038/35040556
|
| [6] | Ardekani AM, Naeini MM (2010) The Role of MicroRNAs in Human Diseases. Avicenna J Med Biotechnol 2: 161-179. |
| [7] |
Reuter S, Gupta SC, Chaturvedi MM, et al. (2010) Oxidative stress, inflammation, and cancer: how are they linked? Free Radic Biol Med 49: 1603-1616. doi: 10.1016/j.freeradbiomed.2010.09.006
|
| [8] |
Magenta A, Greco S, Gaetano C, et al. (2013) Oxidative stress and microRNAs in vascular diseases. Int J Mol Sci 14: 17319-17346. doi: 10.3390/ijms140917319
|
| [9] | Rahal A, Kumar A, Singh V, et al. (2014) Oxidative stress, prooxidants, and antioxidants: the interplay. Biomed Res Int 2014: 761264. |
| [10] |
Dringen R (2000) Metabolism and functions of glutathione in brain. Prog Neurobiol 62: 649-671. doi: 10.1016/S0301-0082(99)00060-X
|
| [11] |
Jomova K, Vondrakova D, Lawson M, et al. (2010) Metals, oxidative stress and neurodegenerative disorders. Mol Cell Biochem 345: 91-104. doi: 10.1007/s11010-010-0563-x
|
| [12] |
Meister A (1988) On the discovery of glutathione. Trends Biochem Sci 13: 185-188. doi: 10.1016/0968-0004(88)90148-X
|
| [13] |
Maruyama Y, Yasuda R, Kuroda M, et al. (2012) Kokumi substances, enhancers of basic tastes, induce responses in calcium-sensing receptor expressing taste cells. PLoS One 7: e34489. doi: 10.1371/journal.pone.0034489
|
| [14] |
Ueda Y, Yonemitsu M, Tsubuku T, et al. (1997) Flavor characteristics of glutathione in raw and cooked foodstuffs. Biosci Biotechnol Biochem 61: 1977-1980. doi: 10.1271/bbb.61.1977
|
| [15] |
Aoyama K, Watabe M, Nakaki T (2012) Modulation of neuronal glutathione synthesis by EAAC1 and its interacting protein GTRAP3-18. Amino Acids 42: 163-169. doi: 10.1007/s00726-011-0861-y
|
| [16] | Kinoshita C, Aoyama K, Matsumura N, et al. (2014) Rhythmic oscillations of the microRNA miR-96-5p play a neuroprotective role by indirectly regulating glutathione levels. Nat Commun 5: 3823. |
| [17] |
Ubhi K, Rockenstein E, Kragh C, et al. (2014) Widespread microRNA dysregulation in multiple system atrophy - disease-related alteration in miR-96. Eur J Neurosci 39: 1026-1041. doi: 10.1111/ejn.12444
|
| [18] |
Ha M, Kim VN (2014) Regulation of microRNA biogenesis. Nat Rev Mol Cell Biol 15: 509-524. doi: 10.1038/nrm3838
|
| [19] |
Sevignani C, Calin GA, Siracusa LD, et al. (2006) Mammalian microRNAs: a small world for fine-tuning gene expression. Mamm Genome 17: 189-202. doi: 10.1007/s00335-005-0066-3
|
| [20] | Cipolla GA (2014) A non-canonical landscape of the microRNA system. Front Genet 5: 337. |
| [21] |
Lytle JR, Yario TA, Steitz JA (2007) Target mRNAs are repressed as efficiently by microRNA-binding sites in the 5' UTR as in the 3' UTR. Proc Natl Acad Sci U S A 104: 9667-9672. doi: 10.1073/pnas.0703820104
|
| [22] | Henchcliffe C, Beal MF (2008) Mitochondrial biology and oxidative stress in Parkinson disease pathogenesis. Nat Clin Pract Neurol 4: 600-609. |
| [23] |
Finkel T, Holbrook NJ (2000) Oxidants, oxidative stress and the biology of ageing. Nature 408: 239-247. doi: 10.1038/35041687
|
| [24] |
Ray PD, Huang BW, Tsuji Y (2012) Reactive oxygen species (ROS) homeostasis and redox regulation in cellular signaling. Cell Signal 24: 981-990. doi: 10.1016/j.cellsig.2012.01.008
|
| [25] |
Lee S, Choi E, Cha MJ, et al. (2014) Looking into a Conceptual Framework of ROS-miRNA-Atrial Fibrillation. Int J Mol Sci 15: 21754-21776. doi: 10.3390/ijms151221754
|
| [26] |
Magenta A, Cencioni C, Fasanaro P, et al. (2011) miR-200c is upregulated by oxidative stress and induces endothelial cell apoptosis and senescence via ZEB1 inhibition. Cell Death Differ 18: 1628-1639. doi: 10.1038/cdd.2011.42
|
| [27] |
Brabletz S, Brabletz T (2010) The ZEB/miR-200 feedback loop--a motor of cellular plasticity in development and cancer? EMBO Rep 11: 670-677. doi: 10.1038/embor.2010.117
|
| [28] |
Mateescu B, Batista L, Cardon M, et al. (2011) miR-141 and miR-200a act on ovarian tumorigenesis by controlling oxidative stress response. Nat Med 17: 1627-1635. doi: 10.1038/nm.2512
|
| [29] |
Rosati J, Spallotta F, Nanni S, et al. (2011) Smad-interacting protein-1 and microRNA 200 family define a nitric oxide-dependent molecular circuitry involved in embryonic stem cell mesendoderm differentiation. Arterioscler Thromb Vasc Biol 31: 898-907. doi: 10.1161/ATVBAHA.110.214478
|
| [30] |
Lin Y, Liu X, Cheng Y, et al. (2009) Involvement of MicroRNAs in hydrogen peroxide-mediated gene regulation and cellular injury response in vascular smooth muscle cells. J Biol Chem 284: 7903-7913. doi: 10.1074/jbc.M806920200
|
| [31] |
Lin H, Qian J, Castillo AC, et al. (2011) Effect of miR-23 on oxidant-induced injury in human retinal pigment epithelial cells. Invest Ophthalmol Vis Sci 52: 6308-6314. doi: 10.1167/iovs.10-6632
|
| [32] | Papaioannou MD, Lagarrigue M, Vejnar CE, et al. (2011) Loss of Dicer in Sertoli cells has a major impact on the testicular proteome of mice. Mol Cell Proteomics 10: M900587MCP900200. |
| [33] |
Wang Q, Wang Y, Minto AW, et al. (2008) MicroRNA-377 is up-regulated and can lead to increased fibronectin production in diabetic nephropathy. FASEB J 22: 4126-4135. doi: 10.1096/fj.08-112326
|
| [34] |
Xu Y, Fang F, Zhang J, et al. (2010) miR-17* suppresses tumorigenicity of prostate cancer by inhibiting mitochondrial antioxidant enzymes. PLoS One 5: e14356. doi: 10.1371/journal.pone.0014356
|
| [35] |
Zhang X, Ng WL, Wang P, et al. (2012) MicroRNA-21 modulates the levels of reactive oxygen species by targeting SOD3 and TNFalpha. Cancer Res 72: 4707-4713. doi: 10.1158/0008-5472.CAN-12-0639
|
| [36] |
Fleissner F, Jazbutyte V, Fiedler J, et al. (2010) Short communication: asymmetric dimethylarginine impairs angiogenic progenitor cell function in patients with coronary artery disease through a microRNA-21-dependent mechanism. Circ Res 107: 138-143. doi: 10.1161/CIRCRESAHA.110.216770
|
| [37] |
Zhao H, Tao Z, Wang R, et al. (2014) MicroRNA-23a-3p attenuates oxidative stress injury in a mouse model of focal cerebral ischemia-reperfusion. Brain Res 1592: 65-72. doi: 10.1016/j.brainres.2014.09.055
|
| [38] |
Xia XG, Zhou H, Samper E, et al. (2006) Pol II-expressed shRNA knocks down Sod2 gene expression and causes phenotypes of the gene knockout in mice. PLoS Genet 2: e10. doi: 10.1371/journal.pgen.0020010
|
| [39] |
Bai XY, Ma Y, Ding R, et al. (2011) miR-335 and miR-34a Promote renal senescence by suppressing mitochondrial antioxidative enzymes. J Am Soc Nephrol 22: 1252-1261. doi: 10.1681/ASN.2010040367
|
| [40] | Togliatto G, Trombetta A, Dentelli P, et al. (2014) Unacylated ghrelin (UnAG) induces oxidative stress resistance in a glucose intolerance mouse model and peripheral artery disease by restoring endothelial cell miR-126 expression. Diabetes 64: 1370-82. |
| [41] |
Ji G, Lv K, Chen H, et al. (2013) MiR-146a regulates SOD2 expression in H2O2 stimulated PC12 cells. PLoS One 8: e69351. doi: 10.1371/journal.pone.0069351
|
| [42] |
Meng X, Wu J, Pan C, et al. (2013) Genetic and epigenetic down-regulation of microRNA-212 promotes colorectal tumor metastasis via dysregulation of MnSOD. Gastroenterology 145: 426-436 e421-426. doi: 10.1053/j.gastro.2013.04.004
|
| [43] | Liu X, Yu J, Jiang L, et al. (2009) MicroRNA-222 regulates cell invasion by targeting matrix metalloproteinase 1 (MMP1) and manganese superoxide dismutase 2 (SOD2) in tongue squamous cell carcinoma cell lines. Cancer Genom Proteom 6: 131-139. |
| [44] |
Kriegel AJ, Fang Y, Liu Y, et al. (2010) MicroRNA-target pairs in human renal epithelial cells treated with transforming growth factor beta 1: a novel role of miR-382. Nucleic Acids Res 38: 8338-8347. doi: 10.1093/nar/gkq718
|
| [45] |
Tu H, Sun H, Lin Y, et al. (2014) Oxidative stress upregulates PDCD4 expression in patients with gastric cancer via miR-21. Curr Pharm Des 20: 1917-1923. doi: 10.2174/13816128113199990547
|
| [46] |
Haque R, Chun E, Howell JC, et al. (2012) MicroRNA-30b-mediated regulation of catalase expression in human ARPE-19 cells. PLoS One 7: e42542. doi: 10.1371/journal.pone.0042542
|
| [47] |
Wang Q, Chen W, Bai L, et al. (2014) Receptor-interacting protein 1 increases chemoresistance by maintaining inhibitor of apoptosis protein levels and reducing reactive oxygen species through a microRNA-146a-mediated catalase pathway. J Biol Chem 289: 5654-5663. doi: 10.1074/jbc.M113.526152
|
| [48] |
Xu X, Wells A, Padilla MT, et al. (2014) A signaling pathway consisting of miR-551b, catalase and MUC1 contributes to acquired apoptosis resistance and chemoresistance. Carcinogenesis 35: 2457-2466. doi: 10.1093/carcin/bgu159
|
| [49] | Espinosa-Diez C, Fierro-Fernandez M, Sanchez-Gomez FJ, et al. (2014) Targeting of gamma-glutamyl-cysteine ligase by miR-433 reduces glutathione biosynthesis and promotes TGF-beta-dependent fibrogenesis. Antioxid Redox Signal. |
| [50] |
Dong X, Liu H, Chen F, et al. (2014) MiR-214 promotes the alcohol-induced oxidative stress via down-regulation of glutathione reductase and cytochrome P450 oxidoreductase in liver cells. Alcohol Clin Exp Res 38: 68-77. doi: 10.1111/acer.12209
|
| [51] | Wang L, Huang H, Fan Y, et al. (2014) Effects of downregulation of microRNA-181a on H2O2-induced H9c2 cell apoptosis via the mitochondrial apoptotic pathway. Oxid Med Cell Longev 2014: 960362. |
| [52] |
Maciel-Dominguez A, Swan D, Ford D, et al. (2013) Selenium alters miRNA profile in an intestinal cell line: evidence that miR-185 regulates expression of GPX2 and SEPSH2. Mol Nutr Food Res 57: 2195-2205. doi: 10.1002/mnfr.201300168
|
| [53] |
Jee MK, Jung JS, Choi JI, et al. (2012) MicroRNA 486 is a potentially novel target for the treatment of spinal cord injury. Brain 135: 1237-1252. doi: 10.1093/brain/aws047
|
| [54] | Mutallip M, Nohata N, Hanazawa T, et al. (2011) Glutathione S-transferase P1 (GSTP1) suppresses cell apoptosis and its regulation by miR-133alpha in head and neck squamous cell carcinoma (HNSCC). Int J Mol Med 27: 345-352. |
| [55] |
Moriya Y, Nohata N, Kinoshita T, et al. (2012) Tumor suppressive microRNA-133a regulates novel molecular networks in lung squamous cell carcinoma. J Hum Genet 57: 38-45. doi: 10.1038/jhg.2011.126
|
| [56] |
Uchida Y, Chiyomaru T, Enokida H, et al. (2013) MiR-133a induces apoptosis through direct regulation of GSTP1 in bladder cancer cell lines. Urol Oncol 31: 115-123. doi: 10.1016/j.urolonc.2010.09.017
|
| [57] |
Patron JP, Fendler A, Bild M, et al. (2012) MiR-133b targets antiapoptotic genes and enhances death receptor-induced apoptosis. PLoS One 7: e35345. doi: 10.1371/journal.pone.0035345
|
| [58] |
Zhang X, Zhu J, Xing R, et al. (2012) miR-513a-3p sensitizes human lung adenocarcinoma cells to chemotherapy by targeting GSTP1. Lung Cancer 77: 488-494. doi: 10.1016/j.lungcan.2012.05.107
|
| [59] |
Kraemer A, Barjaktarovic Z, Sarioglu H, et al. (2013) Cell survival following radiation exposure requires miR-525-3p mediated suppression of ARRB1 and TXN1. PLoS One 8: e77484. doi: 10.1371/journal.pone.0077484
|
| [60] |
Lerner AG, Upton JP, Praveen PV, et al. (2012) IRE1alpha induces thioredoxin-interacting protein to activate the NLRP3 inflammasome and promote programmed cell death under irremediable ER stress. Cell Metab 16: 250-264. doi: 10.1016/j.cmet.2012.07.007
|
| [61] |
Knoll S, Furst K, Kowtharapu B, et al. (2014) E2F1 induces miR-224/452 expression to drive EMT through TXNIP downregulation. EMBO Rep 15: 1315-1329. doi: 10.15252/embr.201439392
|
| [62] |
Ragusa M, Statello L, Maugeri M, et al. (2012) Specific alterations of the microRNA transcriptome and global network structure in colorectal cancer after treatment with MAPK/ERK inhibitors. J Mol Med (Berl) 90: 1421-1438. doi: 10.1007/s00109-012-0918-8
|
| [63] |
Yan GR, Xu SH, Tan ZL, et al. (2011) Global identification of miR-373-regulated genes in breast cancer by quantitative proteomics. Proteomics 11: 912-920. doi: 10.1002/pmic.201000539
|
| [64] |
He HC, Zhu JG, Chen XB, et al. (2012) MicroRNA-23b downregulates peroxiredoxin III in human prostate cancer. FEBS Lett 586: 2451-2458. doi: 10.1016/j.febslet.2012.06.003
|
| [65] | Jiang W, Min J, Sui X, et al. (2014) MicroRNA-26a-5p and microRNA-23b-3p up-regulate peroxiredoxin III in acute myeloid leukemia. Leuk Lymphoma: 1-12. |
| [66] |
Lee HK, Finniss S, Cazacu S, et al. (2014) Mesenchymal Stem Cells Deliver Exogenous miRNAs to Neural Cells and Induce Their Differentiation and Glutamate Transporter Expression. Stem Cells Dev 23: 2851-2861. doi: 10.1089/scd.2014.0146
|
| [67] |
Yang ZB, Zhang Z, Li TB, et al. (2014) Up-regulation of brain-enriched miR-107 promotes excitatory neurotoxicity through down-regulation of glutamate transporter-1 expression following ischaemic stroke. Clin Sci (Lond) 127: 679-689. doi: 10.1042/CS20140084
|
| [68] |
Morel L, Regan M, Higashimori H, et al. (2013) Neuronal exosomal miRNA-dependent translational regulation of astroglial glutamate transporter GLT1. J Biol Chem 288: 7105-7116. doi: 10.1074/jbc.M112.410944
|
| [69] |
Moon JM, Xu L, Giffard RG (2013) Inhibition of microRNA-181 reduces forebrain ischemia-induced neuronal loss. J Cereb Blood Flow Metab 33: 1976-1982. doi: 10.1038/jcbfm.2013.157
|
| [70] |
Kaalund SS, Veno MT, Bak M, et al. (2014) Aberrant expression of miR-218 and miR-204 in human mesial temporal lobe epilepsy and hippocampal sclerosis-Convergence on axonal guidance. Epilepsia 55: 2017-2027. doi: 10.1111/epi.12839
|
| [71] |
Fridovich I (1978) The biology of oxygen radicals. Science 201: 875-880. doi: 10.1126/science.210504
|
| [72] |
Lu M, Zhang Q, Deng M, et al. (2008) An analysis of human microRNA and disease associations. PLoS One 3: e3420. doi: 10.1371/journal.pone.0003420
|
| [73] |
Aoyama K, Watabe M, Nakaki T (2008) Regulation of neuronal glutathione synthesis. J Pharmacol Sci 108: 227-238. doi: 10.1254/jphs.08R01CR
|
| [74] | Cooper AJ, Kristal BS (1997) Multiple roles of glutathione in the central nervous system. Biol Chem 378: 793-802. |
| [75] |
Janaky R, Varga V, Hermann A, et al. (2000) Mechanisms of L-cysteine neurotoxicity. Neurochem Res 25: 1397-1405. doi: 10.1023/A:1007616817499
|
| [76] |
Quintana-Cabrera R, Fernandez-Fernandez S, Bobo-Jimenez V, et al. (2012) gamma-Glutamylcysteine detoxifies reactive oxygen species by acting as glutathione peroxidase-1 cofactor. Nat Commun 3: 718. doi: 10.1038/ncomms1722
|
| [77] | Seelig GF, Simondsen RP, Meister A (1984) Reversible dissociation of gamma-glutamylcysteine synthetase into two subunits. J Biol Chem 259: 9345-9347. |
| [78] |
Dalton TP, Chen Y, Schneider SN, et al. (2004) Genetically altered mice to evaluate glutathione homeostasis in health and disease. Free Radic Biol Med 37: 1511-1526. doi: 10.1016/j.freeradbiomed.2004.06.040
|
| [79] | Yang Y, Dieter MZ, Chen Y, et al. (2002) Initial characterization of the glutamate-cysteine ligase modifier subunit Gclm(-/-) knockout mouse. Novel model system for a severely compromised oxidative stress response. J Biol Chem 277: 49446-49452. |
| [80] |
Ristoff E, Larsson A (2007) Inborn errors in the metabolism of glutathione. Orphanet J Rare Dis 2: 1-9. doi: 10.1186/1750-1172-2-1
|
| [81] |
Brigelius-Flohe R, Maiorino M (2013) Glutathione peroxidases. Biochim Biophys Acta 1830: 3289-3303. doi: 10.1016/j.bbagen.2012.11.020
|
| [82] |
Kryukov GV, Castellano S, Novoselov SV, et al. (2003) Characterization of mammalian selenoproteomes. Science 300: 1439-1443. doi: 10.1126/science.1083516
|
| [83] | Arthur JR (2000) The glutathione peroxidases. Cell Mol Life Sci 57: 1825-1835. |
| [84] |
Power JH, Blumbergs PC (2009) Cellular glutathione peroxidase in human brain: cellular distribution, and its potential role in the degradation of Lewy bodies in Parkinson's disease and dementia with Lewy bodies. Acta Neuropathol 117: 63-73. doi: 10.1007/s00401-008-0438-3
|
| [85] |
Muse KE, Oberley TD, Sempf JM, et al. (1994) Immunolocalization of antioxidant enzymes in adult hamster kidney. Histochem J 26: 734-753. doi: 10.1007/BF00158205
|
| [86] | Li S, Yan T, Yang JQ, et al. (2000) The role of cellular glutathione peroxidase redox regulation in the suppression of tumor cell growth by manganese superoxide dismutase. Cancer Res 60: 3927-3939. |
| [87] |
Knopp EA, Arndt TL, Eng KL, et al. (1999) Murine phospholipid hydroperoxide glutathione peroxidase: cDNA sequence, tissue expression, and mapping. Mamm Genome 10: 601-605. doi: 10.1007/s003359901053
|
| [88] | Hall L, Williams K, Perry AC, et al. (1998) The majority of human glutathione peroxidase type 5 (GPX5) transcripts are incorrectly spliced: implications for the role of GPX5 in the male reproductive tract. Biochem J 333: 5-9. |
| [89] |
Nguyen VD, Saaranen MJ, Karala AR, et al. (2011) Two endoplasmic reticulum PDI peroxidases increase the efficiency of the use of peroxide during disulfide bond formation. J Mol Biol 406: 503-515. doi: 10.1016/j.jmb.2010.12.039
|
| [90] |
Lindenau J, Noack H, Asayama K, et al. (1998) Enhanced cellular glutathione peroxidase immunoreactivity in activated astrocytes and in microglia during excitotoxin induced neurodegeneration. Glia 24: 252-256. doi: 10.1002/(SICI)1098-1136(199810)24:2<252::AID-GLIA10>3.0.CO;2-Z
|
| [91] | Satoh J, Yamamoto Y, Asahina N, et al. (2014) RNA-Seq Data Mining: Downregulation of NeuroD6 Serves as a Possible Biomarker for Alzheimer's Disease Brains. Dis Markers 2014: 123165. |
| [92] |
Deponte M (2013) Glutathione catalysis and the reaction mechanisms of glutathione-dependent enzymes. Biochim Biophys Acta 1830: 3217-3266. doi: 10.1016/j.bbagen.2012.09.018
|
| [93] | Johnson JA, el Barbary A, Kornguth SE, et al. (1993) Glutathione S-transferase isoenzymes in ratbrain neurons and glia. J Neurosci 13: 2013-2023. |
| [94] |
Martin HL, Teismann P (2009) Glutathione--a review on its role and significance in Parkinson's disease. FASEB J 23: 3263-3272. doi: 10.1096/fj.08-125443
|
| [95] |
Zeevalk GD, Razmpour R, Bernard LP (2008) Glutathione and Parkinson's disease: is this the elephant in the room? Biomed Pharmacother 62: 236-249. doi: 10.1016/j.biopha.2008.01.017
|
| [96] | Holmgren A (1989) Thioredoxin and glutaredoxin systems. J Biol Chem 264: 13963-13966. |
| [97] | Kenchappa RS, Ravindranath V (2003) Glutaredoxin is essential for maintenance of brain mitochondrial complex I: studies with MPTP. FASEB J 17: 717-719. |
| [98] |
Lovell MA, Xie C, Gabbita SP, et al. (2000) Decreased thioredoxin and increased thioredoxin reductase levels in Alzheimer's disease brain. Free Radic Biol Med 28: 418-427. doi: 10.1016/S0891-5849(99)00258-0
|
| [99] | Yoshihara E, Masaki S, Matsuo Y, et al. (2014) Thioredoxin/Txnip: redoxisome, as a redox switch for the pathogenesis of diseases. Front Immunol 4: 514. |
| [100] | Dringen R, Pfeiffer B, Hamprecht B (1999) Synthesis of the antioxidant glutathione in neurons: supply by astrocytes of CysGly as precursor for neuronal glutathione. J Neurosci 19: 562-569. |
| [101] |
Shanker G, Allen JW, Mutkus LA, et al. (2001) The uptake of cysteine in cultured primary astrocytes and neurons. Brain Res 902: 156-163. doi: 10.1016/S0006-8993(01)02342-3
|
| [102] |
Chen Y, Swanson RA (2003) The glutamate transporters EAAT2 and EAAT3 mediate cysteine uptake in cortical neuron cultures. J Neurochem 84: 1332-1339. doi: 10.1046/j.1471-4159.2003.01630.x
|
| [103] |
Himi T, Ikeda M, Yasuhara T, et al. (2003) Role of neuronal glutamate transporter in the cysteine uptake and intracellular glutathione levels in cultured cortical neurons. J Neural Transm 110: 1337-1348. doi: 10.1007/s00702-003-0049-z
|
| [104] |
Kanai Y, Hediger MA (2003) The glutamate and neutral amino acid transporter family: physiological and pharmacological implications. Eur J Pharmacol 479: 237-247. doi: 10.1016/j.ejphar.2003.08.073
|
| [105] |
Maragakis NJ, Rothstein JD (2004) Glutamate transporters: animal models to neurologic disease. Neurobiol Dis 15: 461-473. doi: 10.1016/j.nbd.2003.12.007
|
| [106] |
Zerangue N, Kavanaugh MP (1996) Interaction of L-cysteine with a human excitatory amino acid transporter. J Physiol 493: 419-423. doi: 10.1113/jphysiol.1996.sp021393
|
| [107] |
Aoyama K, Suh SW, Hamby AM, et al. (2006) Neuronal glutathione deficiency and age-dependent neurodegeneration in the EAAC1 deficient mouse. Nat Neurosci 9: 119-126. doi: 10.1038/nn1609
|
| [108] |
Lin CI, Orlov I, Ruggiero AM, et al. (2001) Modulation of the neuronal glutamate transporter EAAC1 by the interacting protein GTRAP3-18. Nature 410: 84-88. doi: 10.1038/35065084
|
| [109] |
Abdul-Ghani M, Gougeon PY, Prosser DC, et al. (2001) PRA isoforms are targeted to distinct membrane compartments. J Biol Chem 276: 6225-6233. doi: 10.1074/jbc.M009073200
|
| [110] |
Ruggiero AM, Liu Y, Vidensky S, et al. (2008) The endoplasmic reticulum exit of glutamate transporter is regulated by the inducible mammalian Yip6b/GTRAP3-18 protein. J Biol Chem 283: 6175-6183. doi: 10.1074/jbc.M701008200
|
| [111] |
Aoyama K, Wang F, Matsumura N, et al. (2012) Increased neuronal glutathione and neuroprotection in GTRAP3-18-deficient mice. Neurobiol Dis 45: 973-982. doi: 10.1016/j.nbd.2011.12.016
|
| [112] |
Andersen JK (2004) Oxidative stress in neurodegeneration: cause or consequence? Nat Med 10: S18-25. doi: 10.1038/nrn1434
|
| [113] | Selkoe DJ (2001) Alzheimer's disease: genes, proteins, and therapy. Physiol Rev 81: 741-766. |
| [114] | Maciotta S, Meregalli M, Torrente Y (2013) The involvement of microRNAs in neurodegenerative diseases. Front Cell Neurosci 7: 265. |
| [115] | Schipper HM, Maes OC, Chertkow HM, et al. (2007) MicroRNA expression in Alzheimer blood mononuclear cells. Gene Regul Syst Bio 1: 263-274. |
| [116] | Cogswell JP, Ward J, Taylor IA, et al. (2008) Identification of miRNA changes in Alzheimer's disease brain and CSF yields putative biomarkers and insights into disease pathways. J Alzheimers Dis 14: 27-41. |
| [117] |
Tanner CM, Goldman SM (1996) Epidemiology of Parkinson's disease. Neurol Clin 14: 317-335. doi: 10.1016/S0733-8619(05)70259-0
|
| [118] | Fearnley JM, Lees AJ (1991) Ageing and Parkinson's disease: substantia nigra regional selectivity. Brain 114 : 2283-2301. |
| [119] | Baba M, Nakajo S, Tu PH, et al. (1998) Aggregation of alpha-synuclein in Lewy bodies of sporadic Parkinson's disease and dementia with Lewy bodies. Am J Pathol 152: 879-884. |
| [120] |
Kim J, Inoue K, Ishii J, et al. (2007) A MicroRNA feedback circuit in midbrain dopamine neurons. Science 317: 1220-1224. doi: 10.1126/science.1140481
|
| [121] |
Gusella JF, MacDonald ME, Ambrose CM, et al. (1993) Molecular genetics of Huntington's disease. Arch Neurol 50: 1157-1163. doi: 10.1001/archneur.1993.00540110037003
|
| [122] |
Vonsattel JP, DiFiglia M (1998) Huntington disease. J Neuropathol Exp Neurol 57: 369-384. doi: 10.1097/00005072-199805000-00001
|
| [123] |
Novak MJ, Tabrizi SJ (2010) Huntington's disease. BMJ 340: c3109. doi: 10.1136/bmj.c3109
|
| [124] | Browne SE, Ferrante RJ, Beal MF (1999) Oxidative stress in Huntington's disease. Brain Pathol 9: 147-163. |
| [125] |
Petr GT, Bakradze E, Frederick NM, et al. (2013) Glutamate transporter expression and function in a striatal neuronal model of Huntington's disease. Neurochem Int 62: 973-981. doi: 10.1016/j.neuint.2013.02.026
|
| [126] |
Packer AN, Xing Y, Harper SQ, et al. (2008) The bifunctional microRNA miR-9/miR-9* regulates REST and CoREST and is downregulated in Huntington's disease. J Neurosci 28: 14341-14346. doi: 10.1523/JNEUROSCI.2390-08.2008
|
| [127] |
Marti E, Pantano L, Banez-Coronel M, et al. (2010) A myriad of miRNA variants in control and Huntington's disease brain regions detected by massively parallel sequencing. Nucleic Acids Res 38: 7219-7235. doi: 10.1093/nar/gkq575
|
| [128] |
Mason RP, Casu M, Butler N, et al. (2013) Glutathione peroxidase activity is neuroprotective in models of Huntington's disease. Nat Genet 45: 1249-1254. doi: 10.1038/ng.2732
|
| [129] |
Kim C, Lee HC, Sung JJ (2014) Amyotrophic lateral sclerosis - cell based therapy and novel therapeutic development. Exp Neurobiol 23: 207-214. doi: 10.5607/en.2014.23.3.207
|
| [130] |
Sreedharan J, Brown RH, Jr. (2013) Amyotrophic lateral sclerosis: Problems and prospects. Ann Neurol 74: 309-316. doi: 10.1002/ana.24012
|
| [131] |
Synofzik M, Ronchi D, Keskin I, et al. (2012) Mutant superoxide dismutase-1 indistinguishable from wild-type causes ALS. Hum Mol Genet 21: 3568-3574. doi: 10.1093/hmg/dds188
|
| [132] |
Butovsky O, Siddiqui S, Gabriely G, et al. (2012) Modulating inflammatory monocytes with a unique microRNA gene signature ameliorates murine ALS. J Clin Invest 122: 3063-3087. doi: 10.1172/JCI62636
|
| [133] |
Koval ED, Shaner C, Zhang P, et al. (2013) Method for widespread microRNA-155 inhibition prolongs survival in ALS-model mice. Hum Mol Genet 22: 4127-4135. doi: 10.1093/hmg/ddt261
|
| [134] |
Baillet A, Chanteperdrix V, Trocme C, et al. (2010) The role of oxidative stress in amyotrophic lateral sclerosis and Parkinson's disease. Neurochem Res 35: 1530-1537. doi: 10.1007/s11064-010-0212-5
|
| [135] |
Golenia A, Leskiewicz M, Regulska M, et al. (2014) Catalase activity in blood fractions of patients with sporadic ALS. Pharmacol Rep 66: 704-707. doi: 10.1016/j.pharep.2014.02.021
|
| [136] |
Sturm E, Stefanova N (2014) Multiple system atrophy: genetic or epigenetic? Exp Neurobiol 23: 277-291. doi: 10.5607/en.2014.23.4.277
|
| [137] |
Wenning GK, Tison F, Ben Shlomo Y, et al. (1997) Multiple system atrophy: a review of 203 pathologically proven cases. Mov Disord 12: 133-147. doi: 10.1002/mds.870120203
|
| [138] |
Dallmann R, Brown SA, Gachon F (2014) Chronopharmacology: new insights and therapeutic implications. Annu Rev Pharmacol Toxicol 54: 339-361. doi: 10.1146/annurev-pharmtox-011613-135923
|
| [139] |
Bass J (2012) Circadian topology of metabolism. Nature 491: 348-356. doi: 10.1038/nature11704
|
| [140] |
Kondratov RV (2007) A role of the circadian system and circadian proteins in aging. Ageing Res Rev 6: 12-27. doi: 10.1016/j.arr.2007.02.003
|
| [141] |
Kondratov RV, Kondratova AA, Gorbacheva VY, et al. (2006) Early aging and age-related pathologies in mice deficient in BMAL1, the core componentof the circadian clock. Genes Dev 20: 1868-1873. doi: 10.1101/gad.1432206
|
| [142] |
Willison LD, Kudo T, Loh DH, et al. (2013) Circadian dysfunction may be a key component of the non-motor symptoms of Parkinson's disease: insights from a transgenic mouse model. Exp Neurol 243: 57-66. doi: 10.1016/j.expneurol.2013.01.014
|
| [143] |
Beaver LM, Klichko VI, Chow ES, et al. (2012) Circadian regulation of glutathione levels and biosynthesis in Drosophila melanogaster. PLoS One 7: e50454. doi: 10.1371/journal.pone.0050454
|
| [144] |
Xu YQ, Zhang D, Jin T, et al. (2012) Diurnal variation of hepatic antioxidant gene expression in mice. PLoS One 7: e44237. doi: 10.1371/journal.pone.0044237
|
| [145] |
Krishnan N, Davis AJ, Giebultowicz JM (2008) Circadian regulation of response to oxidative stress in Drosophila melanogaster. Biochem Biophys Res Commun 374: 299-303. doi: 10.1016/j.bbrc.2008.07.011
|
| [146] |
Pablos MI, Reiter RJ, Ortiz GG, et al. (1998) Rhythms of glutathione peroxidase and glutathione reductase in brain of chick and their inhibition by light. Neurochem Int 32: 69-75. doi: 10.1016/S0197-0186(97)00043-0
|
| [147] |
Filipski E, King VM, Etienne MC, et al. (2004) Persistent twenty-four hour changes in liver and bone marrow despite suprachiasmatic nuclei ablation in mice. Am J Physiol Regul Integr Comp Physiol 287: R844-851. doi: 10.1152/ajpregu.00085.2004
|
| [148] |
Arjona A, Sarkar DK (2005) Circadian oscillations of clock genes, cytolytic factors, and cytokines in rat NK cells. J Immunol 174: 7618-7624. doi: 10.4049/jimmunol.174.12.7618
|
| [149] |
Kochman LJ, Weber ET, Fornal CA, et al. (2006) Circadian variation in mouse hippocampal cell proliferation. Neurosci Lett 406: 256-259. doi: 10.1016/j.neulet.2006.07.058
|
| [150] |
Ma D, Panda S, Lin JD (2011) Temporal orchestration of circadian autophagy rhythm by C/EBPbeta. EMBO J 30: 4642-4651. doi: 10.1038/emboj.2011.322
|
| [151] | Kondratova AA, Dubrovsky YV, Antoch MP, et al. (2010) Circadian clock proteins control adaptation to novel environment and memory formation. Aging (Albany NY) 2: 285-297. |
Figures(1) / Tables(1)
Chisato Kinoshita, Koji Aoyama, Toshio Nakaki. microRNA as a new agent for regulating neuronal glutathione synthesis and metabolism[J]. AIMS Molecular Science, 2015, 2(2): 124-143. doi: 10.3934/molsci.2015.2.124
| Standard zeolite-Y | Synthesized zeolite-Y | ||
| 2θ (°) | Relative intensity (%) | 2θ (°) | Relative intensity (%) |
| 6.183 | 100 | 6.209 | 100 |
| 10.104 | 9.09 | 10.097 | 34.47 |
| 11.854 | 7.34 | 11.819 | 14.92 |
| 15.600 | 10.46 | 15.557 | 23.64 |
| 18.621 | 4.10 | 18.548 | 6.13 |
| 20.288 | 3.96 | 20.191 | 12.60 |
| 37.575 | 0.14 | 20.191 | 7.13 |
DownLoad:
CSV
| [NH4NO3], M | Na content (%) | Na reduction (%) |
| - | 1.15 | 0 |
| 2.0 | 0.83 | 27.82 |
| 2.5 | 0.72 | 37.95 |
| 3.0 | 0.58 | 49.65 |
| 3.5 | 0.12 | 89.95 |
DownLoad:
CSV
| Peak No. | Retention time (Min) | SI (%) | Compound name | Molecular formula | Category | Relative percentage (%) |
| 1 | 2.475 | 94 | 1-Hexene | C6H12 | Hydrocarbon | 2.39 |
| 2 | 3.694 | 97 | 1-Heptene | C7H14 | Hydrocarbon | 2.17 |
| 3 | 3.861 | 96 | Heptane | C7H16 | Hydrocarbon | 3.01 |
| 4 | 6.605 | 96 | 1-Octene | C8H16 | Hydrocarbon | 2.89 |
| 5 | 6.941 | 95 | Octane | C8H18 | Hydrocarbon | 4.69 |
| 6 | 9.279 | 96 | Ethylbenzene | C8H10 | Hydrocarbon | 0.90 |
| 7 | 9.645 | 94 | Benzene | C8H10 | Hydrocarbon | 0.91 |
| 8 | 10.598 | 96 | 1-Nonene | C9H18 | Hydrocarbon | 3.03 |
| 9 | 10.967 | 96 | Nonane | C9H20 | Hydrocarbon | 5.11 |
| 10 | 14.552 | 98 | 1-Decene | C10H20 | Hydrocarbon | 2.75 |
| 11 | 14.890 | 96 | Decane | C10H22 | Hydrocarbon | 3.26 |
| 12 | 18.202 | 96 | 1-Undecene | C11H22 | Hydrocarbon | 3.04 |
| 13 | 18.505 | 96 | Undecane | C11H24 | Hydrocarbon | 2.62 |
| 14 | 18.660 | 95 | 2-Undecene | C11H22 | Hydrocarbon | 1.21 |
| 15 | 21.351 | 85 | Undecanoic Acid | C11H22O2 | Acid | 0.92 |
| 16 | 21.551 | 95 | 1-Dodecene | C12H24 | Hydrocarbon | 2.25 |
| 17 | 21.828 | 97 | Dodecane | C12H26 | Hydrocarbon | 3.11 |
| 18 | 24.292 | 86 | Dodecanoic Acid | C12H24O2 | Acid | 1.15 |
| 19 | 24.666 | 96 | 1-Tridecene | C13H26 | Hydrocarbon | 3.41 |
| 20 | 24.921 | 97 | Tridecane | C13H28 | Hydrocarbon | 4.43 |
| 21 | 27.331 | 91 | Tetradecanoic Acid | C14H28O2 | Acid | 7.35 |
| 22 | 27.573 | 98 | 1-Tetradecene | C14H28 | Hydrocarbon | 3.94 |
| 23 | 27.803 | 97 | Tetradecane | C14H30 | Hydrocarbon | 4.17 |
| 24 | 30.293 | 97 | 1-Pentadecene | C15H30 | Hydrocarbon | 2.25 |
| 25 | 30.553 | 97 | Pentadecane | C15H32 | Hydrocarbon | 12.25 |
| 26 | 32.856 | 98 | 1-Hexadecene | C16H32 | Hydrocarbon | 0.80 |
| 27 | 33.043 | 96 | Hexadecane | C16H34 | Hydrocarbon | 1.21 |
| 28 | 34.935 | 93 | 1-Heptadecene | C17H34 | Hydrocarbon | 1.31 |
| 29 | 35.075 | 97 | 8-Heptadecene | C17H34 | Hydrocarbon | 1.33 |
| 30 | 35.475 | 96 | Heptadecane | C17H36 | Hydrocarbon | 1.79 |
| 31 | 39.979 | 94 | 2-Heptadecanone | C17H34O | Ketone | 0.84 |
| 32 | 41.405 | 92 | Octadecanoic Acid | C18H36O2 | Acid | 8.19 |
| 33 | 44.788 | 93 | Oleic Acid | C18H34O2 | Acid | 1.32 |
DownLoad:
CSV
| Chemical component | Catalyst | ||||
| Na-Y | H-Y1 | H-Y2 | H-Y3 | H-Y4 | |
| Cyclohexene | 0.60 | 0.48 | 0.47 | 0.52 | 0.44 |
| 1-Octene | 3.30 | 3.18 | 2.39 | 2.63 | 2.34 |
| Octane | 4.38 | 3.50 | 3.44 | 3.56 | 3.21 |
| 2-Octene | 0.46 | nd | 0.36 | nd | nd |
| Ethylbenzene | 0.90 | 0.78 | 0.93 | nd | 0.80 |
| 1, 3-dimethylbenzene | nd | 0.66 | nd | nd | nd |
| 1-Nonene | 3.57 | 2.77 | 2.66 | nd | 0.66 |
| Nonane | 6.86 | 5.11 | 5.10 | 5.56 | 2.48 |
| 4-Nonene | nd | nd | nd | nd | 4.77 |
| 1-Decene | 3.32 | 2.56 | 2.44 | nd | 2.31 |
| Decane | 4.44 | 3.46 | 3.36 | nd | 3.26 |
| Cyclopropane, octyl- | nd | 3.14 | 3.00 | 3.51 | nd |
| 4-Undecene | nd | 0.81 | 0.96 | nd | 2.90 |
| Undecane | nd | 3.82 | 3.63 | nd | nd |
| 5-Undecene | nd | 1.77 | 1.69 | nd | 3.54 |
| Isopentylbenzene | nd | nd | 0.68 | nd | nd |
| 1-Dodecene | 4.02 | 3.25 | 3.14 | 2.01 | 1.30 |
| Dodecane | 6.16 | 5.02 | 5.04 | 4.29 | 1.73 |
| 2-Dodecene | nd | nd | nd | 2.15 | 1.70 |
| 6-Dodecene | nd | nd | nd | nd | 4.89 |
| Cyclodecane | 6.66 | nd | nd | nd | nd |
| Cyclododecane | 2.56 | 2.74 | 5.46 | nd | nd |
| 1-Tridecene | nd | 2.81 | 8.27 | nd | nd |
| Tridecane | 9.57 | 8.54 | nd | 5.62 | 5.82 |
| 1-Tetradecene | nd | nd | 3.85 | nd | 4.59 |
| 3-Tetradecene | nd | nd | 2.14 | 3.23 | nd |
| 5-Tetradecene | nd | nd | 8.62 | 9.09 | 9.55 |
| 6-Tetradecene | nd | nd | nd | 1.35 | 1.89 |
| Tetradecane | nd | 8.24 | nd | 3.98 | 7.64 |
| Cyclotetradecane | nd | 6.25 | 0.69 | 2.92 | nd |
| 1-Pentadecene | 3.70 | nd | 1.72 | 1.20 | 0.87 |
| Pentadecane | 22.23 | nd | nd | nd | 22.1 |
| Cyclohexylhexane | 0.82 | nd | nd | nd | nd |
| 1-Hexadecene | nd | nd | 6.92 | nd | 1.12 |
| 3-Hexadecene | nd | nd | nd | 0.68 | 2.65 |
| Hexadecane | 2.25 | 2.16 | 3.40 | 9.25 | nd |
| 3-Hexadecene | nd | nd | nd | nd | 0.28 |
| Heptadec-8-ene | 1.10 | nd | nd | 2.06 | 1.64 |
| Heptadecane | 2.49 | 21.70 | 8.29 | 23.5 | 1.59 |
| Heptadec-1-ene | nd | nd | nd | 0.89 | nd |
| 9-Octadecene | 1.06 | 1.80 | 0.96 | 2.67 | nd |
| 5-Octadecene | nd | 0.99 | 2.21 | 1.12 | nd |
| Dodecane, 2-cyclohexyl | nd | nd | 0.77 | nd | nd |
| 3-Octadecene | nd | 1.22 | nd | nd | nd |
| Octadecane | nd | 2.63 | nd | nd | 3.10 |
| 1-Nonadecene | nd | nd | 2.30 | 1.33 | nd |
| 3-Eicosene | nd | nd | 1.16 | nd | nd |
| 9-Eicosene | nd | nd | 1.26 | 1.46 | nd |
| Eicosane | nd | nd | 2.69 | 3.141 | nd |
| Heptyl methyl ketone | nd | nd | nd | 1.51 | nd |
| 2-Heptadecanone | 0.60 | nd | nd | 0.77 | 0.83 |
| 9-Heptadecanone | nd | 0.61 | nd | nd | nd |
| Hydroxymethyl ethyl ester | 0.88 | nd | nd | nd | nd |
| Nonadecane, 1, 2-epoxi | 0.61 | nd | nd | nd | nd |
DownLoad:
CSV
| Catalyst | Relative composition (%) | ||||
| Hydrocarbon | Acid | Ketone | Ester | Ether | |
| - | 80.23 | 18.93 | 0.84 | - | - |
| Na-Y | 90.46 | - | 0.60 | 8.33 | 0.61 |
| H-Y1 | 99.39 | - | 0.61 | - | - |
| H-Y2 | 100.00 | - | - | - | - |
| H-Y3 | 97.72 | - | 2.28 | - | - |
| H-Y4 | 99.17 | - | 0.83 | - | - |
DownLoad:
CSV
| Catalyst | Hydrocarbon distribution (%) | ||
| C5-C12 | C13-C17 | C18-C28 | |
| - | 43.33 | 36.89 | nd |
| Na-Y | 48.06 | 41.34 | 1.06 |
| H-Y1 | 42.30 | 50.45 | 6.64 |
| H-Y2 | 44.75 | 43.90 | 11.35 |
| H-Y3 | 24.23 | 63.77 | 9.72 |
| H-Y4 | 36.33 | 59.74 | 3.10 |
DownLoad:
CSV
| Standard zeolite-Y | Synthesized zeolite-Y | ||
| 2θ (°) | Relative intensity (%) | 2θ (°) | Relative intensity (%) |
| 6.183 | 100 | 6.209 | 100 |
| 10.104 | 9.09 | 10.097 | 34.47 |
| 11.854 | 7.34 | 11.819 | 14.92 |
| 15.600 | 10.46 | 15.557 | 23.64 |
| 18.621 | 4.10 | 18.548 | 6.13 |
| 20.288 | 3.96 | 20.191 | 12.60 |
| 37.575 | 0.14 | 20.191 | 7.13 |
| [NH4NO3], M | Na content (%) | Na reduction (%) |
| - | 1.15 | 0 |
| 2.0 | 0.83 | 27.82 |
| 2.5 | 0.72 | 37.95 |
| 3.0 | 0.58 | 49.65 |
| 3.5 | 0.12 | 89.95 |
| Peak No. | Retention time (Min) | SI (%) | Compound name | Molecular formula | Category | Relative percentage (%) |
| 1 | 2.475 | 94 | 1-Hexene | C6H12 | Hydrocarbon | 2.39 |
| 2 | 3.694 | 97 | 1-Heptene | C7H14 | Hydrocarbon | 2.17 |
| 3 | 3.861 | 96 | Heptane | C7H16 | Hydrocarbon | 3.01 |
| 4 | 6.605 | 96 | 1-Octene | C8H16 | Hydrocarbon | 2.89 |
| 5 | 6.941 | 95 | Octane | C8H18 | Hydrocarbon | 4.69 |
| 6 | 9.279 | 96 | Ethylbenzene | C8H10 | Hydrocarbon | 0.90 |
| 7 | 9.645 | 94 | Benzene | C8H10 | Hydrocarbon | 0.91 |
| 8 | 10.598 | 96 | 1-Nonene | C9H18 | Hydrocarbon | 3.03 |
| 9 | 10.967 | 96 | Nonane | C9H20 | Hydrocarbon | 5.11 |
| 10 | 14.552 | 98 | 1-Decene | C10H20 | Hydrocarbon | 2.75 |
| 11 | 14.890 | 96 | Decane | C10H22 | Hydrocarbon | 3.26 |
| 12 | 18.202 | 96 | 1-Undecene | C11H22 | Hydrocarbon | 3.04 |
| 13 | 18.505 | 96 | Undecane | C11H24 | Hydrocarbon | 2.62 |
| 14 | 18.660 | 95 | 2-Undecene | C11H22 | Hydrocarbon | 1.21 |
| 15 | 21.351 | 85 | Undecanoic Acid | C11H22O2 | Acid | 0.92 |
| 16 | 21.551 | 95 | 1-Dodecene | C12H24 | Hydrocarbon | 2.25 |
| 17 | 21.828 | 97 | Dodecane | C12H26 | Hydrocarbon | 3.11 |
| 18 | 24.292 | 86 | Dodecanoic Acid | C12H24O2 | Acid | 1.15 |
| 19 | 24.666 | 96 | 1-Tridecene | C13H26 | Hydrocarbon | 3.41 |
| 20 | 24.921 | 97 | Tridecane | C13H28 | Hydrocarbon | 4.43 |
| 21 | 27.331 | 91 | Tetradecanoic Acid | C14H28O2 | Acid | 7.35 |
| 22 | 27.573 | 98 | 1-Tetradecene | C14H28 | Hydrocarbon | 3.94 |
| 23 | 27.803 | 97 | Tetradecane | C14H30 | Hydrocarbon | 4.17 |
| 24 | 30.293 | 97 | 1-Pentadecene | C15H30 | Hydrocarbon | 2.25 |
| 25 | 30.553 | 97 | Pentadecane | C15H32 | Hydrocarbon | 12.25 |
| 26 | 32.856 | 98 | 1-Hexadecene | C16H32 | Hydrocarbon | 0.80 |
| 27 | 33.043 | 96 | Hexadecane | C16H34 | Hydrocarbon | 1.21 |
| 28 | 34.935 | 93 | 1-Heptadecene | C17H34 | Hydrocarbon | 1.31 |
| 29 | 35.075 | 97 | 8-Heptadecene | C17H34 | Hydrocarbon | 1.33 |
| 30 | 35.475 | 96 | Heptadecane | C17H36 | Hydrocarbon | 1.79 |
| 31 | 39.979 | 94 | 2-Heptadecanone | C17H34O | Ketone | 0.84 |
| 32 | 41.405 | 92 | Octadecanoic Acid | C18H36O2 | Acid | 8.19 |
| 33 | 44.788 | 93 | Oleic Acid | C18H34O2 | Acid | 1.32 |
| Chemical component | Catalyst | ||||
| Na-Y | H-Y1 | H-Y2 | H-Y3 | H-Y4 | |
| Cyclohexene | 0.60 | 0.48 | 0.47 | 0.52 | 0.44 |
| 1-Octene | 3.30 | 3.18 | 2.39 | 2.63 | 2.34 |
| Octane | 4.38 | 3.50 | 3.44 | 3.56 | 3.21 |
| 2-Octene | 0.46 | nd | 0.36 | nd | nd |
| Ethylbenzene | 0.90 | 0.78 | 0.93 | nd | 0.80 |
| 1, 3-dimethylbenzene | nd | 0.66 | nd | nd | nd |
| 1-Nonene | 3.57 | 2.77 | 2.66 | nd | 0.66 |
| Nonane | 6.86 | 5.11 | 5.10 | 5.56 | 2.48 |
| 4-Nonene | nd | nd | nd | nd | 4.77 |
| 1-Decene | 3.32 | 2.56 | 2.44 | nd | 2.31 |
| Decane | 4.44 | 3.46 | 3.36 | nd | 3.26 |
| Cyclopropane, octyl- | nd | 3.14 | 3.00 | 3.51 | nd |
| 4-Undecene | nd | 0.81 | 0.96 | nd | 2.90 |
| Undecane | nd | 3.82 | 3.63 | nd | nd |
| 5-Undecene | nd | 1.77 | 1.69 | nd | 3.54 |
| Isopentylbenzene | nd | nd | 0.68 | nd | nd |
| 1-Dodecene | 4.02 | 3.25 | 3.14 | 2.01 | 1.30 |
| Dodecane | 6.16 | 5.02 | 5.04 | 4.29 | 1.73 |
| 2-Dodecene | nd | nd | nd | 2.15 | 1.70 |
| 6-Dodecene | nd | nd | nd | nd | 4.89 |
| Cyclodecane | 6.66 | nd | nd | nd | nd |
| Cyclododecane | 2.56 | 2.74 | 5.46 | nd | nd |
| 1-Tridecene | nd | 2.81 | 8.27 | nd | nd |
| Tridecane | 9.57 | 8.54 | nd | 5.62 | 5.82 |
| 1-Tetradecene | nd | nd | 3.85 | nd | 4.59 |
| 3-Tetradecene | nd | nd | 2.14 | 3.23 | nd |
| 5-Tetradecene | nd | nd | 8.62 | 9.09 | 9.55 |
| 6-Tetradecene | nd | nd | nd | 1.35 | 1.89 |
| Tetradecane | nd | 8.24 | nd | 3.98 | 7.64 |
| Cyclotetradecane | nd | 6.25 | 0.69 | 2.92 | nd |
| 1-Pentadecene | 3.70 | nd | 1.72 | 1.20 | 0.87 |
| Pentadecane | 22.23 | nd | nd | nd | 22.1 |
| Cyclohexylhexane | 0.82 | nd | nd | nd | nd |
| 1-Hexadecene | nd | nd | 6.92 | nd | 1.12 |
| 3-Hexadecene | nd | nd | nd | 0.68 | 2.65 |
| Hexadecane | 2.25 | 2.16 | 3.40 | 9.25 | nd |
| 3-Hexadecene | nd | nd | nd | nd | 0.28 |
| Heptadec-8-ene | 1.10 | nd | nd | 2.06 | 1.64 |
| Heptadecane | 2.49 | 21.70 | 8.29 | 23.5 | 1.59 |
| Heptadec-1-ene | nd | nd | nd | 0.89 | nd |
| 9-Octadecene | 1.06 | 1.80 | 0.96 | 2.67 | nd |
| 5-Octadecene | nd | 0.99 | 2.21 | 1.12 | nd |
| Dodecane, 2-cyclohexyl | nd | nd | 0.77 | nd | nd |
| 3-Octadecene | nd | 1.22 | nd | nd | nd |
| Octadecane | nd | 2.63 | nd | nd | 3.10 |
| 1-Nonadecene | nd | nd | 2.30 | 1.33 | nd |
| 3-Eicosene | nd | nd | 1.16 | nd | nd |
| 9-Eicosene | nd | nd | 1.26 | 1.46 | nd |
| Eicosane | nd | nd | 2.69 | 3.141 | nd |
| Heptyl methyl ketone | nd | nd | nd | 1.51 | nd |
| 2-Heptadecanone | 0.60 | nd | nd | 0.77 | 0.83 |
| 9-Heptadecanone | nd | 0.61 | nd | nd | nd |
| Hydroxymethyl ethyl ester | 0.88 | nd | nd | nd | nd |
| Nonadecane, 1, 2-epoxi | 0.61 | nd | nd | nd | nd |
| Catalyst | Relative composition (%) | ||||
| Hydrocarbon | Acid | Ketone | Ester | Ether | |
| - | 80.23 | 18.93 | 0.84 | - | - |
| Na-Y | 90.46 | - | 0.60 | 8.33 | 0.61 |
| H-Y1 | 99.39 | - | 0.61 | - | - |
| H-Y2 | 100.00 | - | - | - | - |
| H-Y3 | 97.72 | - | 2.28 | - | - |
| H-Y4 | 99.17 | - | 0.83 | - | - |
| Catalyst | Hydrocarbon distribution (%) | ||
| C5-C12 | C13-C17 | C18-C28 | |
| - | 43.33 | 36.89 | nd |
| Na-Y | 48.06 | 41.34 | 1.06 |
| H-Y1 | 42.30 | 50.45 | 6.64 |
| H-Y2 | 44.75 | 43.90 | 11.35 |
| H-Y3 | 24.23 | 63.77 | 9.72 |
| H-Y4 | 36.33 | 59.74 | 3.10 |
