QM-Mechanism-Based Hierarchical High-Throughput in Silico Screening Catalyst Design for Ammonia Synthesis.

Area of Science:

• Catalysis Science
• Materials Science
• Computational Chemistry

Background:

• Catalyst design for complex reactions is challenging and computationally expensive.
• The Haber-Bosch process for ammonia synthesis requires efficient catalysts.

Purpose of the Study:

• To develop and validate a hierarchical high-throughput screening (HHTS) approach for accelerated catalyst design.
• To identify optimal dopants for iron-based catalysts to enhance ammonia synthesis.

Main Methods:

• Quantum mechanics (QM) derived reaction networks were simplified to focus on rate-determining steps.
• A hierarchical screening strategy was employed, prioritizing reactions by free-energy barriers.
• The approach reduced computational effort by 99% for initial screening of dopants.

Main Results:

• Screened 34 candidate dopants for iron-based ammonia synthesis.
• Identified a subset of promising dopants including Rh, Pt, Pd, and Cu.
• Rh-doped iron catalyst predicted to increase ammonia synthesis turnover frequency (TOF) by ~3.3x.

Conclusions:

• The HHTS approach significantly accelerates catalyst design for complex systems.
• Rh doping is predicted to be highly effective for enhancing iron-based ammonia synthesis.
• This validated method offers a computationally efficient pathway for discovering improved catalysts.