Reaction Mechanisms, Kinetics, and Improved Catalysts for Ammonia Synthesis from Hierarchical High Throughput Catalyst Design

Abstract

The Haber–Bosch (HB) process is the primary chemical synthesis technique for industrial production of ammonia (NH₃) for manufacturing nitrate-based fertilizer and as a potential hydrogen carrier. The HB process alone is responsible for over 2% of all global energy usage to produce more than 160 million tons of NH₃ annually. Iron catalysts are utilized to accelerate the reaction, but high temperatures and pressures of atmospheric nitrogen gas (N₂) and hydrogen gas (H₂) are required. A great deal of research has aimed at increased performance over the last century, but the rate of progress has been slow. This Account focuses on determining the atomic-level reaction mechanism for HB synthesis of NH₃ on the Fe catalysts used in industry and how to use this knowledge to suggest greatly improved catalysts via a novel paradigm of catalyst rational design. We determined the full reaction mechanism on the two most active surfaces for the HB process, Fe(111) and Fe(211)R. We used density functional theory (DFT) to predict the free-energy barriers for all 12 important reactions and the 34 most important 2 × 2 surface configurations. Then we incorporated the mechanism into kinetic Monte Carlo (kMC) simulations run for several hours of real time to predict turnover frequencies (TOFs). The predicted TOFs are within experimental error, indicating that the predicted barriers are within 0.04 eV of experiment. With this level of accuracy, we are poised to use DFT to improve the catalyst. Rather than forming bulk alloys with uniform concentration, we aimed at finding additives that strongly prefer near-surface sites so that minor amounts of the additive might lead to dramatic improvements. However, even for a single additive, the combinations of surface species and reactions multiplies significantly, with ∼48 reaction steps to examine and nearly 100 surface configurations per 2 × 2 site. To make it practical to examine tens of dopant candidates, we developed the hierarchical high-throughput catalysis screening (HHTCS) approach, which we applied to both the Fe(111) and Fe(211) surfaces. For HHTCS, we identified the most important 4 reaction steps out of 12 for the two surfaces to examine >50 dopant cases, where we required performance at each step no worse than for pure Fe. With HHTCS, the computational cost is about 1% of that for doing the full reaction mechanism, allowing us to do ≈50 cases in about 1/2 the time it took to do pure Fe(111). The new leads identified with HHTCS are then validated with full mechanistic studies. For Fe(111), we predict three high-performance dopants that strongly prefer the second layer: Co with a rate 8 times higher, Ni with a rate 16 times higher, and Si with a rate 43 times higher, at 400 °C and 20 atm. We also found four dopants that strongly prefer the top layer and improve performance: Pt or Rh 3 times faster and Pd or Cu 2 times faster. For Fe(211), the best dopant was found to be second-layer Co with a rate 3 times faster than that for the undoped surface. The DFT/kMC data were used to predict reshaping of the catalyst particles under reaction conditions and how to tune dopant content so as to maximize catalytic area and thus activity. Finally, we show how to validate our mechanistic modeling via a comparison between theoretical and experimental operando spectroscopic signatures.

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