Catalytic Hydrodeoxygenation of Fatty Acids for Biodiesel Production

This paper is devoted to the production of second generation biodiesel via catalytic hydrodeoxygenation of fatty acids. Pd/C catalysts with different metal loading were used. The palladium catalysts were characterized using low-temperature nitrogen physisorption and X-ray photoelectron spectroscopy. It was revealed that the most active and selective catalyst was 1%-Pd/C which allowed reaching up 97.5% of selectivity (regarding to n-heptadecane) at 100% conversion of substrate. Moreover, the chosen catalyst is more preferable according to lower metal content that leads the decrease of the process cost. The analysis of the catalysts showed that 1%-Pd/C had the highest specific surface area compared with 5%-Pd/C. Copyright © 2016 BCREC GROUP. All rights reservedReceived: 31st July 2015; Revised: 9th December 2015; Accepted: 30th December 2015How to Cite: Stepacheva, A.A., Sapunov, V.N., Sulman, E.M., Nikoshvili, L.Z., Sulman, M.G., Sidorov, A.I., Demidenko, G.N., Matveeva, V.G. (2016). Catalytic Hydrodeoxygenation of Fatty Acids for Biodiesel Production. Bulletin of Chemical Reaction Engineering & Catalysis, 11 (2): 125-132 (doi:10.9767/bcrec.11.2.538.125-132)Permalink/DOI: http://dx.doi.org/10.9767/bcrec.11.2.538.125-132Article Metrics: (click on the button below to see citations in Scopus)

The ability of the Question and Answer (Q&A) Method With the Help of Learnin Videos Against Student Learning Outcomes Amid the Covid-19 Pandemic

In learning physics, it is very necessary to have the ability to understand concepts, especially in the midst of the Covid-19 pandemic. Education must continue to ensure the implementation of the learning process in accordance with their talents and interests and ensure student learning outcomes. The purpose of this research is to contribute to the teacher's contribution in improving the learning outcomes of class VIII Madrasah Tsanawiyah Pondok Pesantren Darul Arifin Jambi using the question and answer method assisted by video learning to improve student learning outcomes. This research is Classroom Action Research (CAR) using 2 cycles. Each cycle has 4 stages, namely planning, implementation, observation and reflection. The subjects in this study were all students of class VIII Madrasah Tsanawiyah Pondok Pesantren Darul Arifin Jambi City. The technique of collecting data is through observation and learning outcomes tests, with a minimum success indicator of 75% of students succeeding in the learning outcomes test. In the learning outcomes test, the average score of students is still low, namely 34.97 with a percentage of completeness of 5.88%, in the first cycle it increases to 63, with a completeness percentage of 52.94%, in the second cycle the average value becomes 76.47 with a completeness percentage of 82.35

Affine group actions on Euclidean space.

Upto affine conjugacy, we describe properly discontinuous rank two affine groups of Euclidean space (primarily dimensions two and three) in terms of "coordinates" of generators. In dimension two, a chosen generator is put into a normal form. The commuting condition simplifies a second generator, which can be identified with a point of the plane. Thus, R2 can be viewed as a parameter space of groups (since the first normalized generator is common to each group). A homomorphism Res:R2->R (the residue) singles out properly discontinuous groups G isomorphic to Z+Z. Affine conjugacy of two groups is characterized by their residues and an element of GL (2, Z). As a consequence, we show (i) There are uncountably many conjugacy classes of properly discontinuous rank two groups, and (ii) Each point of Ker(Res) is the limit point of every conjugacy class. An analog of the residue is used to determine three dimensional properly discontinuous rank two groups, although this description does not cover all normalized forms

Exome sequencing identified rare variants in genes HSPG2 and ATP2B4 in a family segregating developmental dysplasia of the hip

Variant filtration process illustrating the exome filtering scheme in two affected individuals. Panel 1: Genes containing rare variants (1% in 1000G/ExAC/in-house database; absent from dbSNP) and in accordance with an autosomal dominant inheritance with incomplete penetrance (shared between affected samples III:5 and IV:2). ACOT8, ADCK1, AGMO, ANGPT4, ANKS3, ATP2B4, BARHL1, C12orf44, C18orf56, CACTIN, CCM2L, CEACAM4, CRISPLD2, CTAGE7P, CTSA, CTSE, DAGLB, DAZAP2, DCTN4, DENND1B, EDEM1, EMG1, FAM154A, FAM19A2, GSK3A, HIPK1, HMCN2, HNRNPUL1, HSPG2, INCENP, INTS1, IRG1, KCNIP4, KHSRP, LEPREL2, LPPR3, MAN1C1, MICALCL, MREG, MUC5B, NAV1, NEURL2, NPR2, NUCKS1, PCSK5, PDS5A, PLCG2, POMT1, PPL, PRDM7, PRKAB1, SEZ6L, SLC6A12, SLC7A5, SLIT2, ZCCHC8, ZNF335, ZNF648, ZNF780A. (JPG 128 kb

Palladium nanoparticles by electrospinning from poly(acrylonitrile-co-acrylic acid)-PdCl2 solutions. Relations between preparation conditions, particle size, and catalytic activity

Catalytic palladium (Pd) nanoparticles on electrospun copolymers of acrylonitrile and acrylic acid (PAN-AA) mats were produced via reduction of PdCl2 with hydrazine. Fiber mats were electrospun from homogeneous solutions of PAN-AA and PdCl2 in dimethylformamide (DMF). Pd cations were reduced to Pd metals when fiber mats were treated in an aqueous hydrazine solution at room temperature. Pd atoms nucleate and form small crystallites whose sizes were estimated from the peak broadening of X-ray diffraction peaks. Two to four crystallites adhere together and form agglomerates. Agglomerate sizes and fiber diameters were determined by scanning and transmission electron microscopy. Spherical Pd nanoparticles were dispersed homogeneously on the electrospun nanofibers. The effects of copolymer composition and amount of PdCl2 on particle size were investigated. Pd particle size mainly depends on the amount of acrylic acid functional groups and PdCl2 concentration in the spinning solution. Increasing acrylic acid concentration on polymer chains leads to larger Pd nanoparticles. In addition, Pd particle size becomes larger with increasing PdCl2 concentration in the spinning solution. Hence, it is possible to tune the number density and the size of metal nanoparticles. The catalytic activity of the Pd nanoparticles in electrospun mats was determined by selective hydrogenation of dehydrolinalool (3,7-dimethyloct-6- ene-1-yne-3-ol, DHL) in toluene at 90 °C. Electrospun fibers with Pd particles have 4.5 times higher catalytic activity than the current Pd/Al2O3 catalyst

Stydy of the cobalt containing catalyst synthesized in the medium of supercritical carbon dioxide

The article shows the possibility of using of supercritical carbon dioxide for the synthesis of catalytically active systems. A cobalt-containing catalyst supported on silica was synthesized by supercritical deposition. Physicochemical study of the obtained sample showed that, during the synthesis in the medium of supercritical carbon dioxide, the structure of the support does not change; the particles of the active phase are distributed evenly on the support surface with a thin layer

Sequence analysis of the VSX1 and SOD1 genes in families with Keratoconus and a review of the literature

AbstractObjectiveKeratoconus (KC) is a non-inflammatory disorder of the cornea in which the cornea becomes thin and conical, inducing myopia and irregular astigmatism and resulting in mild to marked impairment of vision. The present study was designed to screen two candidate KC genes to identify pathogenic sequence variants responsible for KC in Saudi families.MethodsPeripheral blood samples from members of five Saudi families with KC from the Northern region were collected. Genomic DNA was isolated, and bidirectional sequencing was performed of all coding exons of VSX1 and SOD1 genes using Sanger sequencing.ResultsAll five of the KC families showed a pattern of autosomal recessive inheritance. Phenotyping of these families was performed by a senior ophthalmologist. Sequence analysis of the VSX1 and SOD1 genes failed to reveal any pathogenic sequence variant that could account for KC in the affected individuals.ConclusionOur failure to detect sequence variants in two of the known KC associated genes triggers an interest in other known KC candidate genes, including miR-184, DOCK9, IL1RN and SLC4A11. Future genotyping with dense SNP arrays followed by exome sequencing in these families will be a useful approach to identify the gene(s) underlying KC in this Saudi cohort, which may be different from those reported elsewhere

The full catalytic processing of biomass components

In this work, experimental studies aimed at the study of the hydrogenolysis of components of plant biomass with the production of valuable chemical substances have been conducted. Research aimed at the finding of the effective catalytic system allows obtaining a high degree of conversion of the substrate with high selectivity in the processing of all components of the biomass. On the basis of experimental data, it can be concluded that 3% Ru/MN270 catalyst is active in the hydrogenolysis of lignin, cellulose and hemicellulose, and it can be used in a complex processing of biomass. The catalytic system is also stable — the five-time use in the reaction of hydrogenolysis did not lead to the change of activity

Metal oxide–zeolite composites in transformation of methanol to hydrocarbons : do iron oxide and nickel oxide matter?

The methanol-to-hydrocarbon (MTH) reaction has received considerable attention as utilizing renewable sources of both value-added chemicals and fuels becomes a number one priority for society. Here, for the first time we report the development of hierarchical zeolites (ZSM-5) containing both iron oxide and nickel oxide nanoparticles. By modifying the iron oxide (magnetite, Fe3O4) amounts, we are able to control the catalyst activity and the product distribution in the MTH process. At the medium Fe3O4 loading, the major fraction is composed of C9–C11 hydrocarbons (gasoline fraction). At the higher Fe3O4 loading, C1–C4 hydrocarbons prevail in the reaction mixture, while at the lowest magnetite loading the major component is the C5–C8 hydrocarbons. Addition of Ni species to Fe3O4–ZSM-5 leads to the formation of mixed Ni oxides (NiO/Ni2O3) positioned either on top of or next to Fe3O4 nanoparticles. This modification allowed us to significantly improve the catalyst stability due to diminishing coke formation and disordering of the coke formed. The incorporation of Ni oxide species also leads to a higher catalyst activity (up to 9.3 g(methanol)/(g(ZSM-5) × h)) and an improved selectivity (11.3% of the C5–C8 hydrocarbons and 23.6% of the C9–C11 hydrocarbons), making these zeolites highly promising for industrial applications

Divergent controls of soil organic carbon between observations and process-based models

The storage and cycling of soil organic carbon (SOC) are governed by multiple co-varying factors, including climate, plant productivity, edaphic properties, and disturbance history. Yet, it remains unclear which of these factors are the dominant predictors of observed SOC stocks, globally and within biomes, and how the role of these predictors varies between observations and process-based models. Here we use global observations and an ensemble of soil biogeochemical models to quantify the emergent importance of key state factors – namely, mean annual temperature, net primary productivity, and soil mineralogy – in explaining biome- to global-scale variation in SOC stocks. We use a machine-learning approach to disentangle the role of covariates and elucidate individual relationships with SOC, without imposing expected relationships a priori. While we observe qualitatively similar relationships between SOC and covariates in observations and models, the magnitude and degree of non-linearity vary substantially among the models and observations. Models appear to overemphasize the importance of temperature and primary productivity (especially in forests and herbaceous biomes, respectively), while observations suggest a greater relative importance of soil minerals. This mismatch is also evident globally. However, we observe agreement between observations and model outputs in select individual biomes – namely, temperate deciduous forests and grasslands, which both show stronger relationships of SOC stocks with temperature and productivity, respectively. This approach highlights biomes with the largest uncertainty and mismatch with observations for targeted model improvements. Understanding the role of dominant SOC controls, and the discrepancies between models and observations, globally and across biomes, is essential for improving and validating process representations in soil and ecosystem models for projections under novel future conditions