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. 2024 Oct 24;128(42):9184-9194.
doi: 10.1021/acs.jpca.4c04630. Epub 2024 Oct 14.

Decomposition and Growth Pathways for Ammonium Nitrate Clusters and Nanoparticles

Affiliations

Decomposition and Growth Pathways for Ammonium Nitrate Clusters and Nanoparticles

Ubaidullah S Hassan et al. J Phys Chem A. .

Abstract

Understanding the formation and decomposition mechanisms of aerosolized ammonium nitrate species will lead to improvements in modeling the thermodynamics and kinetics of aerosol haze formation. Studying the sputtered mass spectra of cation and anion ammonium nitrate clusters can provide insights as to which growth and evaporation pathways are favored in the earliest stages of nucleation and thereby guide the development and use of accurate models for intermolecular forces for these systems. Simulated annealing Monte Carlo optimization followed by density functional theory optimizations can be used reliably to predict minimum-energy structures and interaction energies for the cation and anion clusters observed in mass spectra as well as for neutral nanoparticles. A combination of translational and rotational mag-walking and sawtooth simulated annealing methods was used to find optimum structures of the various heterogeneous clusters identifiable in the mass spectra. Following these optimizations with ωB97X-D3 density functional theory calculations made it possible to rationalize the pattern of peaks in the mass spectra through computation of the binding energies of clusters involved in various growth and dissociation pathways. Testing these calculations against CCSD(T) and MP2 predictions of the structures and binding energies for small clusters demonstrates the accuracy of the chosen model chemistry. For the first time, the peaks corresponding with all detectable species in both the positive and negative ion mass spectra of ammonium nitrate are identified with their corresponding structures. Thermodynamic control of particle growth and decomposition of ions due to loss of ammonia or nitric acid molecules is indicated. Structures and interaction energies for larger (NH4NO3)n nanoparticles are also presented, including the prediction of new particle morphologies with trigonal pyramidal character.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
(NH3HNO3)and (NH4HNO3)2 structures at the ωB97X-D3/def2-SVPD level of theory.
Figure 2
Figure 2
[(NH4)2NO3]+ (upper) and formula image (lower) structures optimized at the ωB97X-D3/def2-SVPD level of theory and those reported by Dunlap and Doyle using the BP functional (right). Adapted from 23. Copyright 1996 American Chemical Society.
Figure 3
Figure 3
Positive-ion sputtered mass spectrum of ammonium nitrate clusters. Predicted ωB97X-D3 structures of parent and daughter ions corresponding to the numbered peaks have been added to the original spectrum. Adapted from 23. Copyright 1996 American Chemical Society.
Figure 4
Figure 4
ωB97X-D3 electronic binding energies for different fragmentation channels of formula image.
Figure 5
Figure 5
ωB97X-D3 and OPLS/TR differential interaction energies for the formula imageparents.
Figure 6
Figure 6
Negative-ion sputtered mass spectrum of ammonium nitrate clusters. Predicted structures of parent ions corresponding to the numbered peaks have been added to the original spectrum. Adapted from 23. Copyright 1996 American Chemical Society.
Figure 7
Figure 7
ωB97X-D3 electronic binding energies for different fragmentation channels of formula image cations.
Figure 8
Figure 8
ωB97X-D3 electronic binding energies for fragmentation of formula image anions by successive ammonia loss, according to reactions (R9,R10).
Figure 9
Figure 9
ωB97X-D3 (DFT) and OPLS/TR differential interaction energies for the formula imageparents.
Figure 10
Figure 10
Predicted structures of selected (NH4NO3)n nanoparticles from OPLS/TR calculations followed by ωB97X-D3/def2-SVPD geometry optimization.
Figure 11
Figure 11
ωB97X-D3 differential interaction energies for (NH4NO3)n from OPLS-AA (black) and ωB97X-D3/def2-TZPD calculations (blue). Also shown: ωB97X-D3 calculations using a 6-311+G(2df,2p)[6-311G(d)] “Pople” basis; see text (orange). The optimized n = 4, 6, 9, 16, 21, 27, and 37 structures are shown.

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