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Title: Azo(xy) vs Aniline Selectivity in Catalytic Nitroarene Reduction by Intermetallics: Experiments and Simulations

Abstract

Intermetallic nanoparticles are promising catalysts in hydrogenation and fuel cell technologies. Much is known about the ability of intermetallic nanoparticles to selectively reduce nitro vs alkene, alcohol, or halide functional groups; less is known about their selectivity toward aniline vs azo or azoxy condensation products that result from the reduction of a nitro group alone. Because azo(xy)arenes bear promise as dyes, chemical stabilizers, and building blocks to functional materials but can be difficult to isolate, developing high surface area nanoparticle catalysts that display azo(xy) selectivity is desirable. To address this question, we studied a family of nanocrystalline group 10 metal (Pd, Pt)- and group 14 metal (Ge, Sn, Pb)-containing intermetallics-Pd2Ge, Pd2Sn, Pd3Sn2, Pd3Pb, and PtSn-in the catalytic reduction of nitroarenes. In contrast to monometallic Au, Pt, and Pd nanoparticles and "random" PdxSn1 – x nanoalloys, which are selective for aniline, nanoparticles of atomically precise intermetallic Pd2Ge, Pd2Sn, Pd3Sn2, and PtSn prefer an indirect condensation pathway and have a high selectivity for the azo(xy) products. The only exception is Pd3Pb, the most active among the intermetallic nanoparticles studied here, which is instead selective for aniline. Employing a novel application of molecular dynamics-based on machine learned potentials within a DeePMD framework-to heterogeneousmore » catalysis, we are able to identify key reaction species on the different types of catalysts employed, furthering our understanding of the unique selectivity of these materials. By demonstrating how intermetallic nanoparticles can be as active yet more selective than other more traditional catalysts, this work provides new physical insights and opens new opportunities in the use of these materials in other important chemical transformations and applications.« less

Authors:
 [1]; ORCiD logo [2];  [1];  [1]; ORCiD logo [3]
  1. Iowa State Univ., Ames, IA (United States)
  2. Ames Lab., Ames, IA (United States)
  3. Ames Lab., and Iowa State Univ., Ames, IA (United States)
Publication Date:
Research Org.:
Ames Lab., Ames, IA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Chemical Sciences, Geosciences & Biosciences Division
OSTI Identifier:
1833541
Report Number(s):
IS-J-10,634
Journal ID: ISSN 1932-7447; 1905066
Grant/Contract Number:  
AC02-07CH11358
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Physical Chemistry. C
Additional Journal Information:
Journal Volume: 125; Journal Issue: 44; Journal ID: ISSN 1932-7447
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Palladium; Metal nanoparticles; Nanoparticles; Intermetallics; Catalysts

Citation Formats

Daniels, Carena L., Liu, Da-Jiang, Adamson, Marquix S., Knobeloch, Megan, and Vela, Javier. Azo(xy) vs Aniline Selectivity in Catalytic Nitroarene Reduction by Intermetallics: Experiments and Simulations. United States: N. p., 2021. Web. doi:10.1021/acs.jpcc.1c08569.
Daniels, Carena L., Liu, Da-Jiang, Adamson, Marquix S., Knobeloch, Megan, & Vela, Javier. Azo(xy) vs Aniline Selectivity in Catalytic Nitroarene Reduction by Intermetallics: Experiments and Simulations. United States. https://doi.org/10.1021/acs.jpcc.1c08569
Daniels, Carena L., Liu, Da-Jiang, Adamson, Marquix S., Knobeloch, Megan, and Vela, Javier. Wed . "Azo(xy) vs Aniline Selectivity in Catalytic Nitroarene Reduction by Intermetallics: Experiments and Simulations". United States. https://doi.org/10.1021/acs.jpcc.1c08569. https://www.osti.gov/servlets/purl/1833541.
@article{osti_1833541,
title = {Azo(xy) vs Aniline Selectivity in Catalytic Nitroarene Reduction by Intermetallics: Experiments and Simulations},
author = {Daniels, Carena L. and Liu, Da-Jiang and Adamson, Marquix S. and Knobeloch, Megan and Vela, Javier},
abstractNote = {Intermetallic nanoparticles are promising catalysts in hydrogenation and fuel cell technologies. Much is known about the ability of intermetallic nanoparticles to selectively reduce nitro vs alkene, alcohol, or halide functional groups; less is known about their selectivity toward aniline vs azo or azoxy condensation products that result from the reduction of a nitro group alone. Because azo(xy)arenes bear promise as dyes, chemical stabilizers, and building blocks to functional materials but can be difficult to isolate, developing high surface area nanoparticle catalysts that display azo(xy) selectivity is desirable. To address this question, we studied a family of nanocrystalline group 10 metal (Pd, Pt)- and group 14 metal (Ge, Sn, Pb)-containing intermetallics-Pd2Ge, Pd2Sn, Pd3Sn2, Pd3Pb, and PtSn-in the catalytic reduction of nitroarenes. In contrast to monometallic Au, Pt, and Pd nanoparticles and "random" PdxSn1 – x nanoalloys, which are selective for aniline, nanoparticles of atomically precise intermetallic Pd2Ge, Pd2Sn, Pd3Sn2, and PtSn prefer an indirect condensation pathway and have a high selectivity for the azo(xy) products. The only exception is Pd3Pb, the most active among the intermetallic nanoparticles studied here, which is instead selective for aniline. Employing a novel application of molecular dynamics-based on machine learned potentials within a DeePMD framework-to heterogeneous catalysis, we are able to identify key reaction species on the different types of catalysts employed, furthering our understanding of the unique selectivity of these materials. By demonstrating how intermetallic nanoparticles can be as active yet more selective than other more traditional catalysts, this work provides new physical insights and opens new opportunities in the use of these materials in other important chemical transformations and applications.},
doi = {10.1021/acs.jpcc.1c08569},
journal = {Journal of Physical Chemistry. C},
number = 44,
volume = 125,
place = {United States},
year = {Wed Oct 27 00:00:00 EDT 2021},
month = {Wed Oct 27 00:00:00 EDT 2021}
}

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