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Peer-reviewedCC BY 4.0Npj Computational Materials

High-throughput design of catalytic materials for NOx reduction from aircraft emissions

  • Anshuman Goswami1,2,3
  • Frank Abild-Pedersen1,2
  • John W. Lawson4
  • Joakim Halldin Stenlid3,5
5 affiliations
  1. 1Department of Chemical Engineering, Stanford University, Stanford, CA USA
  2. 2SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park, CA USA
  3. 3KBR, Inc., Intelligent Systems Division, NASA Ames Research Center, Moffett Field, CA USA
  4. 4Intelligent Systems Division, NASA Ames Research Center, Moffett Field, CA USA
  5. 5Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Gothenburg, Sweden
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Abstract

NOx emissions from aircraft exhausts are a major source of air pollutants. Catalytic converters have been proposed as potential technologies to reduce NOx emissions but the high temperatures and rapid exhaust gas flows pose challenges to catalyst design. Ni-based alloys are routinely used for high-temperature applications and exhaust systems; however, standard alloys are insufficient to catalyze NOx reduction effectively. To assess whether alloying Ni with elements active for NOx chemistry can improve performance, we conduct a high-throughput screening study, leveraging Density Functional Theory (DFT) calculations across an expansive materials space. We complement this with microkinetic analyses to identify optimal descriptor spaces for catalyst design. We consider a series of Ni-based equi-compositional ternary alloys that include both temperature-resistant elements (Fe, Co, Cr) and catalytically active metals (Pt, Pd, Rh) for NOx reduction. These alloys are then evaluated according to their catalytic reactivity, high-temperature stability, and coking resistance. Through this in-silico high-throughput screening framework, we identify Ni-Co-Pd, Ni-Co-Pt, Ni-Fe-Pt and Ni-Cr-Pt as promising candidates that satisfy the performance criteria.

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Cite

BibTeXRIS
BibTeX
@article{goswami2026highthroughput,
  title = {{High-throughput design of catalytic materials for NOx reduction from aircraft emissions}},
  author = {Anshuman Goswami and Frank Abild-Pedersen and John W. Lawson and Joakim Halldin Stenlid},
  journal = {Npj Computational Materials},
  year = {2026},
  month = jul,
  doi = {10.1038/s41524-026-02220-9},
  url = {https://doi.org/10.1038/s41524-026-02220-9},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - High-throughput design of catalytic materials for NOx reduction from aircraft emissions
AU  - Anshuman Goswami
AU  - Frank Abild-Pedersen
AU  - John W. Lawson
AU  - Joakim Halldin Stenlid
PY  - 2026
DA  - 2026/07/09
JO  - Npj Computational Materials
DO  - 10.1038/s41524-026-02220-9
UR  - https://doi.org/10.1038/s41524-026-02220-9
AB  - NOx emissions from aircraft exhausts are a major source of air pollutants. Catalytic converters have been proposed as potential technologies to reduce NOx emissions but the high temperatures and rapid exhaust gas flows pose challenges to catalyst design. Ni-based alloys are routinely used for high-temperature applications and exhaust systems; however, standard alloys are insufficient to catalyze NOx reduction effectively. To assess whether alloying Ni with elements active for NOx chemistry can improve performance, we conduct a high-throughput screening study, leveraging Density Functional Theory (DFT) calculations across an expansive materials space. We complement this with microkinetic analyses to identify optimal descriptor spaces for catalyst design. We consider a series of Ni-based equi-compositional ternary alloys that include both temperature-resistant elements (Fe, Co, Cr) and catalytically active metals (Pt, Pd, Rh) for NOx reduction. These alloys are then evaluated according to their catalytic reactivity, high-temperature stability, and coking resistance. Through this in-silico high-throughput screening framework, we identify Ni-Co-Pd, Ni-Co-Pt, Ni-Fe-Pt and Ni-Cr-Pt as promising candidates that satisfy the performance criteria.
SN  - 2057-3960
ER  -