473195 Reaction Pathways and Microkinetic Modeling of Levulinic Acid Hydrodeoxygenation over Sulfided NiMo/Al2O3
Reaction Pathway and Microkinetic Model for Levulinic Acid Hydrodeoxygenation over Sulfided NiMo/Al2O3
Miha Grilc and Bla Likozar, Laboratory of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Ljubljana, Slovenia
Interest in the bio-chemicals and bio-fuels production from renewable resources has increased in the last decade, mainly as a result of the limited availability of petroleum reserves, uncertain prices of crude oil derivatives and environmental concerns. There is an ongoing challenge to develop economically-efficient and environmentally-friendly technologies to transform lignocellulosic biomass to fuels (BTF) and chemicals.
Levulinic acid is a representative of important biomass-derived building blocks for added-value chemicals production and can be produced from cellulose or hemicellulose. Production from cellulose is conducted by an acidic hydrolysis or solvolysis into 5-hydroxymethylfurfural (HMF), that is further derfomylated to levulinic acid. On the other hand, it can also be produced from hemicellulose, although the pathway is much more challenging and includes its acidic hydrolysis to pentose units, subsequent dehydration to furfural, hydrogenation to furfuryl alcohol and its hydrolysis to levulinic acid. Levulinic acid is therefore the main product of lignocellulosic biomass liquefaction by acidic solvolysis or hydrolysis, with up to 83 mol% yields reported if cellulose is used as a feedstock. Levulinic acid production from biomass shows higher sustainability as well as economic feasibility in comparison to the traditionally used synthesis method involving the petrochemical maleic anhydride conversion. As a member of gamma-keto acids it is recognized as an ideal platform chemical to produce various targeted added-value bio-chemicals or simply a liquid fuel.
A promising method to convert levulinic acid into added-value chemicals is a catalytic hydrodeoxygenation. Hydrodeoxygenation takes place at temperatures above 200 °C in the presence of gaseous hydrogen (or other hydrogen source) and a heterogeneous hydrodeoxygenation catalysts either based on transition metals (Mo, W, Ni, Co) in their sulfide, metal, oxide nitride or carbide form or noble metals (Pt, Ru, Pd) on different supports. Process parameters required for hydrodeoxygenation can also induce competitive (and often undesired) decarbonylation or decarboxylation reactions that can significantly decrease the selectivity of desired catalytic transformation. For that reason the optimization of process parameters and appropriate catalyst design or selection is crucial to maximize the rate of desired transformation and still preserving the permissible selectivity.
Commercially available NiMo/γ-Al2O3 catalyst, developed for hydrodesulphurization (HDS) of crude oil, was used in this work. Prior to testing, the catalyst (received in its oxide form) was sulphided using DMDS under 2.5 MPa hydrogen pressure at temperature of 350 °C for 60 minutes in a stainless steel autoclave. Morphology of the catalyst was characterized by scanning electron microscopy (SEM), specific surface area was determined by BrunauerEmmettTeller method (179 m2 g1), while the concentration of accessible NiMoO4/Al2O3 sites was determined according to the hydrogen consumption during the second TPRTPOTPR step which served as an estimation of active sites (200 ± 40 μmol g1) after the sulfidation. Additional characterization techniques, namely TPR, TPDNH3, DRIFT, XRD and EDX were performed as well for additional insights into the characteristics of the catalyst.
Hydrodeoxygenation was investigated in the same 300 mL autoclave equipped as used for the activation, equipped with a magnetically driven turbine stirrer and electric heating jacket. Hydrodeoxygenation took place at solventless conditions, therefore only solid catalyst, liquid levulinic acid and gaseous hydrogen were in contact in the initial stages of the experiment. Experiment was performed under a constant hydrogen purge (flow rate of 1.0 LN min1) that allowed continuous gas phase analysis, high availability of H2 and constant pressure throughout the experiment.
The influence of temperature (the lowest value 225 °C, the highest value 300 °C), pressure (the lowest value 2.5 MPa, the highest value 7.5 MPa), stirring speed (the lowest value 200 rpm, the highest value 1400 rpm), catalyst particle size (the smallest fraction < 40 μm, the largest fraction: pellet), mass of catalyst (the lowest mass 0 wt%, the highest value 4 wt%) and gas type (hydrogen or nitrogen) was tested in the process-conditions screening tests.
The analysis of gaseous (GC, FTIR) and liquid phase (GCMS/FID) reveals the presence of two deoxygenation mechanisms: hydrodeoxygenation (by a combination of dehydration and hydrogenation in various order) and decarboxylation as shown in Figure 1. Hydrodeoxygenation reaction only took place in the coexistent presence of a catalyst and elevated hydrogen pressure. In case that nitrogen gas was introduced instead of hydrogen, the hydrodeoxygenation reaction was negligible at all temperatures, while the increase of the latter resulted in substantial decarboxylation. However, the experiment in absence of hydrogen showed that catalytic dehydration of levulinic acid to angelica lactone is relatively slow, which reveals that in presence of a catalyst and hydrogen γ-valerolactone is obviously not being formed via angelica lactone route (kc3, kc4), but rather by hydrogenation to unstable hydroxyvaleric acid intermediate and subsequent dehydration (kc1, kc2).
Figure 1: Proposed reaction pathway network for levulinic acid hydrotreatment over NiMo/Al2O3.
Experiment with hydrogen and without a catalyst showed similar results, however; decarboxylation proceeded in two different ways, via direct decarboxylation of levulinic acid to ketone or by decarboxylation with subsequent CC coupling with angelica lactone. It is important to mention that oxobutyl derivate of γ-valerolactone is the main product obtained during the experiment without a catalyst, although its formation rate is low. Figure 2 shows the results for the experiment at 275 °C under 5 MPa of hydrogen pressure and by using sulphided NiMo/Al2O3 in pelletized form. Competition between decarboxylation and catalytic hydrodeoxygenation is clearly seen. Main decarboxylation products in the liquid phase (Butanone and Butanol) were detected, but could not be representatively quantified, due to their high volatility. Hydrodeoxygenation reaction rate is obviously governed by hydrogenation of levulinic acid to hydroxyvaleric acid, followed by rapid dehydration to γ-valerolactone, since the concentration of the intermediate in the liquid phase was below detection limit. Involvement of hydroxylpentanoic acid (although not identified in the liquid phase) in the reaction mechanism can be confirmed with valeric (pentanoic) acid formation. Its low (but constant) reaction rate shows that the dehydration of hydroxypentanoic acid is much faster than hydrodeoxygenation. The main product of catalytic hydrotreatment within the range of tested reaction conditions is therefore γ-valerolactone, since the products of further reactions were only detected in traces (kc5 extremely low).
Kinetic model was developed according to the reaction pathway network. With the regression analysis (by taking all experimental conditions and results into account) the influence of the following phenomena was quantitatively addressed: a) hydrodynamic conditions in the reactor, b) transport phenomena, c) homogeneous (non-catalytic) chemical reaction, d) adsorption rate of components from solidliquid interphase to the active sites on the catalyst surface and desorption in the opposite direction, e) the rate of chemical reactions on the active sites of the catalyst. Modelling results allowed evaluating the contribution of above-mentioned phenomena to overall rate of components transformations in gaseous and liquid phase. With evaluation of parameters obtained by the modelling, the bottlenecks and rate-limiting steps of the process were identified. Detailed information about the modeling methodology and results will be available at the conference.
Acknowledgment: The authors gratefully acknowledge the financial support of the Slovenian Research Agency (ARRS) through the programme P2-0152.