Low CO2 hydrogen streams production from formic acid through control of the reaction pH
Graphical abstract
Introduction
One of the major challenges to establish an up-to-date hydrogen economy is the difficulties encountered in its storage and transportation. Recently, as a safer option for chemical storage appears the use of liquid organic hydrogen carriers (LOHCs) [1], [2]. Within this group of compounds, the formic acid (FA) is one of the most promising due to numerous features such as, low toxicity, non-flammability, stability at room temperature, high volumetric H2 capacity (53 L−1) and possibility to be produced through biomass-based processes [1].
Hydrogen generation from formic acid is based on its decomposition and lead either to H2 and CO2 production via dehydrogenation process (Eq. (1)) or to H2O and CO production via dehydration reaction (Eq. (2)) [3].
An optimal process for hydrogen generation must be selective to dehydrogenation and inhibit the dehydration. Using aqueous media at mild temperatures (around 50 °C) or a selective catalyst in gas phase can control the reaction products by suppressing the dehydration reaction [4], [5], [6], [7], [8].
One of the most reported systems for liquid or gas phase formic acid decomposition are the palladium based systems [9], [10], [11], [12], [13], [14]. Nevertheless, this metal suffers deactivation and its activity depends greatly on the nature of the used support [15], [16], [17] on the presence of secondary active metal such as Ag [18], Au [19], [20], Co [21] or Ni [22], and on support functionalization [15], [18], [20], [21], [23]. An important improvement can be also achieved by replacing the formic acid with mixed formic acid/formate salts solutions [2], [15], [24], [25], [26], [27], [28]. Kim et al. [26] observed this positive effect and attributed it to a synergetic common ion effect. This effect consists in formate intermediates stabilization on Pd surface via H-bonding in presence of formic acid. In addition, a conjugated acid-base pair buffer system is formed, where the common ions help the protons refilling via formic acid dissociation thus assuring the pH control via Henderson-Hasselbalch equation (Eq. (3)).HCOO−aq → CO2 + H+aq
There are two different routes for formic acid dehydrogenation, the direct or formate route, where the formic acid dissociates to formate via eq. (3) and then to CO2 via eq. (4) and indirect formic acid dehydrogenation. The latter consists in a first step formic acid dehydration to CO (eq. (2)) and its hydration to CO2 and H2 via water gas shift reaction Eq. (5) [29].CO + H2O ⇄ CO2 + H2
Nevertheless, it could be considered that in aqueous media the dehydration route is completely unfavorable. On the other hand, if we consider the formate route as the preferred one, it must be influenced by the changes in pH and formate concentration [2], [26], [27]. What is more, any control of the pH should be able, in principle, to orient the reaction via one or another pathway. Léval et al. [30] reported that in aqueous solution, formic acid consumption leads to pH increase and drop in activity (following the eq. (2) equilibrium) evited by varying the initial pH to a value where the catalyst remains active. Jeon et al. [8] found that the surface charge of catalyst also has important influence on the reaction pH. They conclude that the presence of different functional groups on the catalyst surface and their behavior in aqueous solution determine the reaction pH and activity in a volcano-type like dependence.
The pH variation could also influence the CO2 solubility independently on formic acid dehydrogenation pathway via bicarbonate/carbonate equilibrium [31]. One could imagine that, an optimal pH exists where the H2/CO2 ratio reach a maximum to produce greener hydrogen from formic acid.
And this is the motivation to study the influence of the reaction pH over hydrogen production via formic acid dehydrogenation evaluating the effect of i) the pH by itself; ii) the nature of the alkaline solutions used to change it and iii) the influence of the formate salt addition to H2 generation. The study also includes the pH effect on the CO2 distribution. As a way to minimize as much as possible, the catalysts surface contribution to the reaction pH, the whole study is carried out over a commercial sample of carbon supported palladium.
Section snippets
Catalysts and chemicals
Commercial palladium on activated carbon catalyst, purchased by Sigma Aldrich (10 wt% Pd/AC), was used in this study. Prior activity measurements, the sample was dried at 100 °C overnight and activated in reducing atmosphere, (N2/H2, 1:1) during 2 h at 300 °C.
For the dehydrogenation experiments, 100 mL of 1 M formic acid aqueous solution (HCOOH, Sigma Aldrich, ACS reagent > 96 %) was used. The reaction pH was set initially at 2.2 (average pH of 1 M formic acid solution) and then changed to 2.8,
Catalyst characterization
The commercial Pd catalyst showed a metal loading slightly inferior to the nominally stated (Table 1) and the X-ray diffractogram of the reduced catalyst (Figure s1) shows the presence of amorphous carbon (2ϴ = 25°, 44° and 80°) and palladium metal (ICDD # 00–004-0784) with broad diffractions at 2θ ≈ 40.1°, 46.7°, 68.1°, 82.1° and 86.6°. The XRD data allows the calculation of Pd average size using Debye-Scherrer equation over the (1 1 1) diffraction as well as the evaluation of Lc parameter and R
Conclusions
Different alkaline solutions were used to adjust the reaction pH (KOH, NaOH, LiOH and NH3) in the reaction of formic acid dehydrogenation over commercial catalyst. An inversely proportional dependence on the hydrated cationic radius over the activity is observed for the series of alkali metals. The higher polarization potential of potassium reflected in higher ionic and smaller hydrated ion radii resulting in stronger Coulomb interactions with the catalyst surface and therefore highest
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
Financial support was obtained from Spanish Ministerio de Ciencia e Innovación (MCIN/AEI /10.13039/501100011033/) and for FEDER Funds, Projects ENE2017-82451-C3-3-R and PID2020-113809RB-C32. Also the financial support from Junta de Andalucía via Consejería de Transformación Económica, Industria, Conocimiento y Universidades and its PAIDI 2020 program (Grant P18-RT-3405) co-financed by FEDER funds from the European Union is welcomed.
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