Elsevier

Journal of Catalysis

Volume 395, March 2021, Pages 143-154
Journal of Catalysis

Increasing electrocatalytic nitrate reduction activity by controlling adsorption through PtRu alloying

https://doi.org/10.1016/j.jcat.2020.12.031Get rights and content

Highlights

  • Pt78Ru22/C is six times more active than Pt/C at 0.1 V vs. RHE.

  • PtxRuy have 93–98% faradaic efficiencies towards NH3 production at 0.1 V vs. RHE.

  • DFT calculations predict maximum activity at 25 at% Ru, consistent with experiments.

  • Maximum activity is due to a change in the rate determining step.

Abstract

Nitrate produced from industrial and agricultural processes has imbalanced the global nitrogen cycle. Electrocatalytic reduction is a sustainable route to remediate nitrate while generating products such as ammonia or N2. Here we report the surface-area normalized activity of platinum-ruthenium (PtxRuy/C) catalysts of different compositions (x = 48–100%) for electrocatalytic nitrate reduction, chosen based on screening using a computational activity volcano plot. The PtxRuy/C alloys are more active than Pt/C, with Pt78Ru22/C six times more active than Pt/C at 0.1 V vs. RHE, and ammonia faradaic efficiencies of 93–98%. Density functional theory calculations predict maximum activity at 25 at% Ru, consistent with experiments. This maximum is due to a transition from nitrate dissociation as the rate determining step to a new rate-determining step at higher Ru content. This study demonstrates how electrocatalyst performance is tunable by changing the adsorption strength of reacting species through alloying.

Introduction

Nitrate is among the world's most widespread water pollutants, and its accumulation leads to adverse health effects and environmental damage through algal blooms and dead zone formation [1], [2]. Multiple approaches have been explored to manage nitrate contamination of water, including physical separation [3], [4], biological denitrification [5], [6], [7], chemical reduction [8], catalytic hydrogenation [9], [10], and electrocatalytic reduction [11], [12]. Each of these approaches has drawbacks for industrial applications. Physical separation can result in fast and large-scale water treatment but produces a concentrated secondary stream that requires further processing. Biological denitrification is currently the most cost-effective method [13], [14]. However, biological approaches are ineffective for treating harsh waste streams (e.g., acidic or containing heavy metals and halides) because these conditions deactivate or kill the bacteria [15], [16]. Chemical reduction and catalytic hydrogenation require continuous external reducing agents, creating hazards in storage, transportation, and utilization, in addition to high cost [17].

A promising, less-explored route to remediate nitrate is electrocatalytic reduction [16], [18]. The electrocatalytic nitrate reduction reaction (NO3RR) uses protons and electrons, which removes the need for an external H2 stream and can be powered via renewable electricity [19]. NO3RR converts aqueous NO3 to NO2 and then to products such as HNO2, NO, NH2OH, NH3, N2O, and N2 (Scheme 1). Preferential selectivity towards N2 or NH3 is often the target in literature [20], [21], [22]. N2 is benign and easily separable, and is the most stable nitrate reduction product with a standard redox potential (E0) of 1.25 V vs. RHE. NH3 is a commodity chemical that would, in principle, reduce the reliance on the Haber-Bosch process for ammonia production if made from NO3RR (E0 = 0.82 V vs. RHE). Producing NH3 from NO3 is kinetically more accessible than breaking the N2 triple bond, and NO3RR may enable decentralized ammonia production using renewable electricity.

Despite ongoing research in electrocatalytic denitrification, there lacks a sufficiently inexpensive, active, selective (i.e., high faradaic efficiency towards N2 or NH3), and stable catalyst that would enable widespread application of this technology in acidic media [23]. Rh is currently the most active and selective pure metal for nitrate reduction towards NH3 in acidic media at low overpotentials [24]. On Rh, nitrate adsorbs strong enough to maintain considerable surface coverages relative to hydrogen. The higher nitrate coverage promotes high rates of nitrate dissociation, which is often the rate-determining step for NO3RR [25]. However, Rh is extremely expensive, costing over $8,200/oz [26]. Besides the catalyst cost, another significant cost in an electrochemical process is electricity, typically accounting for 33% of commodity chemical production [19], [27]. To reduce operating costs in the system, catalysts need to be active at low overpotentials. Finding an inexpensive, stable electrocatalyst with activity and selectivity comparable to those of Rh at low overpotentials is a major challenge for widespread commercial denitrification.

Determining optimal alloy compositions is important because the alloy composition determines the catalyst cost and the catalyst activity and selectivity. We show in Table S1 a summary of different alloys previously investigated for NO3RR [20], [21], [22], [28], [29], [30], [31], [32], [33]. For PtSn alloys, the addition of Sn enhanced the rate-determining step of nitrate reduction to nitrite and altered the selectivity from ammonia toward hydroxylamine [34]. More recently, Cu50Ni50 alloy catalysts were demonstrated to have a six-fold increase in activity compared to pure Cu at 0 V vs. RHE [33]. Alloying Cu with Ni raises the d-band center relative to the Fermi level and increases the adsorption strength of key intermediates such as *NO3, *NO2, and *NH2. However, Ni composition >50% increases the *NH2 → *NH3 reaction free energy, which decreases the overall NH3 production. Consequently, a volcano-like relationship exists between catalyst composition and selectivity towards NH3.

Computational catalysis has emerged as a powerful tool to understand and design electrocatalysts for wastewater treatment [35]. Our recent computational work using density functional theory (DFT) modeling identified the binding energies of atomic O and N as simple thermodynamic descriptors that correlate with the activity and selectivity of metal NO3RR catalysts [25]. These two descriptors were used with mean-field microkinetic modeling to generate theoretical volcano activity plots at different applied potentials. The descriptors reliably predict NO3RR activity trends on metals through adsorbate scaling and Brønsted-Evans-Polanyi relations. Based on these volcano plots, Pt3Ru was predicted to be more active than Pt and among the most active alloys considered. Nevertheless, it is unclear whether the descriptors and microkinetic model for single metals can be applied to bimetallic alloys. This work will focus on experimentally validating such descriptors and the volcano plot for alloys, which would create avenues for rapidly screening NO3RR catalysts.

Here we report the activity and selectivity for NO3RR on well-characterized PtxRuy/C alloys (x = 48–100%) to test our computational hypothesis that platinum-ruthenium alloys are more active than Pt. Our synthesis method results in 3–6 nm PtxRuy alloy nanoparticles on carbon without significant phase or surface segregation. We use hydrogen underpotential deposition (Hupd) and copper underpotential deposition (Cuupd) to measure the electrochemically active surface area (ECSA) and report normalized steady-state current densities for NO3RR. Pt nanoparticles supported on carbon (Pt100/C) have lower activity than all five PtxRuy/C catalysts in the potential range 0.05–0.40 V vs. RHE. The activity increases with the Ru content to a maximum at Pt78Ru22/C, followed by a decrease in activity with higher Ru content. The experimental maximum in activity with Ru at% (atomic %) qualitatively matches predictions from our DFT calculations over the same range of Ru compositions. We attribute the change in activity with Ru content to changing the adsorption strength of nitrate, hydrogen, and intermediates by alloying. Our results support our hypothesis that the activity volcano plot previously developed for pure metals is applicable to bimetallic alloys. This finding suggests that simple thermodynamic descriptors, such as N and O binding energies, can be used to screen alloy catalysts for NO3RR. This work also gives insight into synthesizing more active NO3RR catalysts by tuning the adsorption strength of intermediates through alloying, further aiding the conversion of nitrate to benign or value-added products.

Section snippets

Catalyst preparation

A NaBH4 reduction synthesis was used for catalyst synthesis, as outlined in Fig. S1. A suspension of 25 mg of carbon black (Vulcan XC 72; Fuel Cell Store) was pretreated in H2 at 400 °C for 2 hrs to remove impurities from the surface. After, the support was suspended in 15 mL of Millipore water (18.2 MΩcm, Millipore MilliQ system) and sonicated for 15 min. Measured concentrations of RuCl3 (38% Ru; Alfa Aesar) and H2PtCl6 (38–40% Pt; Sigma Aldrich) in Millipore water were added to the solution

Synthesis and bulk characterization of the supported PtxRuy alloys

We synthesize PtxRuy (x = 48–100%) nanoparticles supported on Vulcan carbon via a modified NaBH4 reduction method using different concentrations of H2PtCl6 and RuCl3 precursors to vary the Pt:Ru ratio (Fig. S1) [53]. ICP-MS measurements determined the bulk weight and atomic loading of Pt and Ru in the alloys. The data in Table 1 shows that a smaller wt% (weight %) of Ru than intended is incorporated into the catalyst. The deviations between the target and actual composition are likely due to the

Conclusions

Using predictions of electrocatalyst activity from a theoretical volcano plot, we synthesize and report a set of PtxRuy/C alloys that are more intrinsically active than pure Pt for the electrocatalytic reduction of nitrate to ammonia in acidic conditions. The binding energy of NO3RR intermediates increases with the inclusion of Ru such that the most active PtxRuy/C alloy binds the intermediates neither too strongly nor too weakly. Our findings suggest that alloy activity for NO3RR can be

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.

Acknowledgments

This work was supported by faculty start-up funds of Goldsmith and Singh from the University of Michigan, Ann Arbor, and by an Mcubed seed grant. N.S acknowledges financial support from NSF grant #DMR-0420785 and #DMR-9871177 and technical support from the Michigan Center for Materials Characterization for XPS and TEM. Z.W. was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program. This research used resources of the

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