Calculation of Electron Ionization Mass Spectra with Semiempirical GFNn-xTB Methods

Abstract

In this work, we have tested two different extended tight-binding methods in the framework of the quantum chemistry electron ionization mass spectrometry (QCEIMS) program to calculate electron ionization mass spectra. The QCEIMS approach provides reasonable, first-principles computed spectra, which can be directly compared to experiment. Furthermore, it provides detailed insight into the reaction mechanisms of mass spectrometry experiments. It sheds light upon the complicated fragmentation procedures of bond breakage and structural rearrangements that are difficult to derive otherwise. The required accuracy and computational demands for successful reproduction of a mass spectrum in relation to the underlying quantum chemical method are discussed. To validate the new GFN2-xTB approach, we conduct simulations for 15 organic, transition-metal, and main-group inorganic systems. Major fragmentation patterns are analyzed, and the entire calculated spectra are directly compared to experimental data taken from the literature. We discuss the computational costs and the robustness (outliers) of several calculation protocols presented. Overall, the new, theoretically more sophisticated semiempirical method GFN2-xTB performs well and robustly for a wide range of organic, inorganic, and organometallic systems.

Comparison of computational chemistry methods for the discovery of quinone-based electroactive compounds for energy storage

“…The choice of this solvation method is constrained by the present availability in the ADF program. The gas-phase FF optimized geometries are also used as inputs for DFTB optimizations using the DFTB-D3 54 and GFN1-xTB 55,56 methods. The DFTB-D3 computations are performed with a self-consistent charge cycle using the QuasiNANO-2015 parameter set 33 , while the parameters for GFN1-xTB are taken from the work of Grimme et al 55,56 The aqueous-phase geometry optimizations of molecules are not performed with the DFTB method, since currently there is no available routine for this task in the ADF program.…”

“…The gas-phase FF optimized geometries are also used as inputs for DFTB optimizations using the DFTB-D3 54 and GFN1-xTB 55,56 methods. The DFTB-D3 computations are performed with a self-consistent charge cycle using the QuasiNANO-2015 parameter set 33 , while the parameters for GFN1-xTB are taken from the work of Grimme et al 55,56 The aqueous-phase geometry optimizations of molecules are not performed with the DFTB method, since currently there is no available routine for this task in the ADF program. Finally, FF minimized geometries are used as inputs to perform geometry optimizations in gas-phase DFT calculations using different flavors of exchange-correlation functionals, including the local density approximation (LDA) 57 , generalized gradient approximation (GGA) 58 , hybrid and meta-GGA functionals 58 , all of which vary drastically in their accounting of the exchange-correlation energy.…”

A quantitative evaluation of computational methods to accelerate the study of alloxazine-derived electroactive compounds for energy storage

“…These lowest energy conformers are then used as inputs to perform the gas- and aqueous-phase geometry optimizations using nine different SEQM methods, including AM1 44 , MNDO 45 , MNDOD 46 , PM3 47 , PM6 48 , PM6-D3 49 , PM6-D3H4X 29 , PM7 50 and RM1 51 . The gas-phase FF optimized geometries are also used as inputs for DFTB level optimizations using the DFTB-D3 52 and GFN1-xTB 53 , 54 methods. The DFTB-D3 computations are performed with a self-consistent charge cycle using the QuasiNANO-2015 32 parameter set, while the parameters for GFN1-xTB are taken from the work of Grimme et al 53 , 54 .…”

Approaching black-box calculations of pump-probe fragmentation dynamics of polyatomic molecules

“…This semi-empirical theory has been shown to perform well in the simulation of EIMS spectra. [49] Mass spectra at each pump-probe delay for ethylene and phenanthrene were computed using 500 trajectories, whilst for naphthalene 400 trajectories were used. The integration step for BOMD in all simulations was 0.5 fs, and the free evolution time free after the pumping and probing was 2 ps for ethylene, 6 ps for napthalene, and 2.5 ps for phenanthrene.…”