RT Journal Article
T1 New Tools for Taming Complex Reaction Networks: The Unimolecular Decomposition of Indole Revisited
A1 Garay-Ruiz, Diego
A1 Álvarez-Moreno, Moisés
A1 Bo, Carles
A1 Martínez Núñez, Emilio
K1 Indole
K1 Reaction networks
K1 Automated mechanism discovery
K1 Pyrolysis
K1 Astrochemistry
K1 Data analysis
K1 Visualization
AB The level of detail attained in the computational description of reaction mechanisms can be vastly improved through tools for automated chemical space exploration, particularly for systems of small to medium size. Under this approach, the unimolecular decomposition landscape for indole was explored through the automated reaction mechanism discovery program AutoMeKin. Nevertheless, the sheer complexity of the obtained mechanisms might be a hindrance regarding their chemical interpretation. In this spirit, the new Python library amk-tools has been designed to read and manipulate complex reaction networks, greatly simplifying their overall analysis. The package provides interactive dashboards featuring visualizations of the network, the three-dimensional (3D) molecular structures and vibrational normal modes of all chemical species, and the corresponding energy profiles for selected pathways. The combination of the joined mechanism generation and postprocessing workflow with the rich chemistry of indole decomposition enabled us to find new details of the reaction (obtained at the CCSD(T)/aug-cc-pVTZ//M06-2X/MG3S level of theory) that were not reported before: (i) 16 pathways leading to the formation of HCN and NH3 (via amino radical); (ii) a barrierless reaction between methylene radical and phenyl isocyanide, which might be an operative mechanism under the conditions of the interstellar medium; and (iii) reaction channels leading to both hydrogen cyanide and hydrogen isocyanide, of potential astrochemical interest as the computed HNC/HCN ratios greatly exceed the calculated equilibrium value at very low temperatures. The reported reaction networks can be very valuable to supplement databases of kinetic data, which is of remarkable interest for pyrolysis and astrochemical studies.
PB American Chemical Society
YR 2022
FD 2022-02-04
LK https://hdl.handle.net/10347/43292
UL https://hdl.handle.net/10347/43292
LA eng
NO ACS Phys. Chem Au 2022, 2, 3, 225–236
NO This work was partially supported by: the Spanish Ministerio de Ciencia e Innovación through Projects PID2019-107307RB-I00 and PID2020-112806RB-I00 and through the Severo Ochoa Excellence Accreditation 2020–2023 (CEX2019-000925-S, MCI/AEI), the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria (Axuda para Consolidación e Estructuración de Unidades de Investigación Competitivas do Sistema Universitario de Galicia, Xunta de Galicia ED431C 2021/40), the ICIQ Foundation, and the CERCA Program of the Generalitat de Catalunya. D.G.-R. thanks AGAUR, the Secretaria d’Universitats i Recerca of the Generalitat de Catalunya, and the European Social Fund for a FI predoctoral grant. The authors acknowledge CESGA for providing access to their computing facilities.
DS Minerva
RD 24 abr 2026