Literature DB >> 26653290

Performance of the TPSS Functional on Predicting Core Level Binding Energies of Main Group Elements Containing Molecules: A Good Choice for Molecules Adsorbed on Metal Surfaces.

Noèlia Pueyo Bellafont1, Francesc Viñes1, Francesc Illas1.   

Abstract

Here we explored the performance of Hartree-Fock (HF), Perdew-Burke-Ernzerhof (PBE), and Tao-Perdew-Staroverov-Scuseria (TPSS) functionals in predicting core level 1s binding energies (BEs) and BE shifts (ΔBEs) for a large set of 68 molecules containing a wide variety of functional groups for main group elements B → F and considering up to 185 core levels. A statistical analysis comparing with X-ray photoelectron spectroscopy (XPS) experiments shows that BEs estimations are very accurate, TPSS exhibiting the best performance. Considering ΔBEs, the three methods yield very similar and excellent results, with mean absolute deviations of ∼0.25 eV. When considering relativistic effects, BEs deviations drop approaching experimental values. So, the largest mean percentage deviation is of 0.25% only. Linear trends among experimental and estimated values have been found, gaining offsets with respect to ideality. By adding relativistic effects to offsets, HF and TPSS methods underestimate experimental values by solely 0.11 and 0.05 eV, respectively, well within XPS chemical precision. TPSS is posed as an excellent choice for the characterization, by XPS, of molecules on metal solid substrates, given its suitability in describing metal substrates bonds and atomic and/or molecular orbitals.

Entities:  

Year:  2015        PMID: 26653290     DOI: 10.1021/acs.jctc.5b00998

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  5 in total

1.  Relating X-ray photoelectron spectroscopy data to chemical bonding in MXenes.

Authors:  Néstor García-Romeral; Masoomeh Keyhanian; Ángel Morales-García; Francesc Illas
Journal:  Nanoscale Adv       Date:  2021-03-01

2.  Accurate Computational Prediction of Core-Electron Binding Energies in Carbon-Based Materials: A Machine-Learning Model Combining Density-Functional Theory and GW.

Authors:  Dorothea Golze; Markus Hirvensalo; Patricia Hernández-León; Anja Aarva; Jarkko Etula; Toma Susi; Patrick Rinke; Tomi Laurila; Miguel A Caro
Journal:  Chem Mater       Date:  2022-07-13       Impact factor: 10.508

3.  Real-Space Pseudopotential Method for the Calculation of 1s Core-Level Binding Energies.

Authors:  Qiang Xu; David Prendergast; Jin Qian
Journal:  J Chem Theory Comput       Date:  2022-08-29       Impact factor: 6.578

4.  Accurate Absolute and Relative Core-Level Binding Energies from GW.

Authors:  Dorothea Golze; Levi Keller; Patrick Rinke
Journal:  J Phys Chem Lett       Date:  2020-02-21       Impact factor: 6.475

5.  Computational Study of the Electron Spectra of Vapor-Phase Indole and Four Azaindoles.

Authors:  Delano P Chong
Journal:  Molecules       Date:  2021-03-30       Impact factor: 4.411

  5 in total

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