Competitive Hydrodeoxygenation and Hydrodenitrogenation Reactions in the Hydrotreatment of Fatty Acid and Amine Mixtures

Abstract

Understanding how hydrotreating oxygen-containing compounds together with nitrogen-containing compounds affects the reactivity and selectivity is relevant for processing renewable feedstocks. In this work, competitive hydrodeoxygenation (HDO) and hydrodenitrogenation (HDN) reactions were studied by co-hydrotreating palmitic acid (C16 acid) and tetradecylamine (C14 amine) over a Pt/ZrO2 catalyst in a batch reactor. HDO proceeded faster than HDN in the studied system, and the deoxygenation reactions were found to have an inhibitory effect on HDN. Co-hydrotreating the C16 acid and the C14 amine expanded the reaction network from the individual HDO and HDN networks and changed the prevailing reaction pathways, initially in favor of oxygen removal. The formation of heavy secondary amides and amines through condensation reactions became increasingly favored as the share of C16 acid in the feed increased. For a given conversion level, the condensation product selectivity was observed to increase as the reaction temperature was decreased, whereas increasing the reaction temperature promoted the formation of the desired paraffins. This work described the ease of HDO compared to HDN, the role of condensation reactions in the co-hydrotreating reaction network, and the inhibitory effect on HDN thereof.

Simulation of conformality of ALD growth inside lateral channels: comparison between a diffusion–reaction model and a ballistic transport–reaction model

“…In this work, the DR model 12 ( DReaM-ALD 31 ) will be referred to as Model A , while the Markov chain based BTR model 10 ( Machball 32 ) will be called Model B . Furthermore, this work will refer to the ALD counter-reactants as Reactant A and Reactant B, with Reactant A being the metal precursor of the process, denoted by subscript ‘A’.…”

“…The parameters describing the inert carrier gas will carry the ‘I’ subscript (in line with ref. 9 and 31), as opposed to ‘B’ used in the original description of the diffusion–reaction model. 12 A brief description of each model will be given next.…”

“…In the original work, 12 the numerical solution was obtained using the 4th order Runge–Kutta method. However, the implementation of Model A used in this work, DReaM-ALD , 31 utilized MATLAB's built-in ODE23 differential equation solver instead. Both solvers have been shown to produce similar saturation profiles.…”

“…A. V. using a code based on the work by Verkama and Puurunen. 31 The saturation profiles obtained from the Yanguas-Gil and Elam 10 ballistic transport–reaction model (Model B) were simulated by J. J. using the implementation by Yanguas-Gil and Elam. 32 The simulation parameters were selected by J.…”

“…Emma Verkama implemented the Ylilammi et al 12 diffusion–reaction model as a MATLAB script. 31 Aleksi Heikkinen initiated the use of the ballistic transport–reaction model by Yanguas-Gil and Elam 10,32 as a summer student in Puurunen's research group. Angel Yanguas-Gil's help in getting the group started with Machball is gratefully acknowledged; likewise is Andreas Werbrouck's peer feedback on the submitted preprint.…”