Login / Signup

Theoretical Study of Dodecafluorophenylene-Based Superalkalides with Significantly High NLO Response.

Areeg SajjadSehrish SarfarazAnnum AhsanImene BayachMalai Haniti S A HamidNadeem S SheikhKhurshid Ayub
Published in: ACS omega (2023)
Scientists are continuously trying to discover new approaches to develop materials with exceptional nonlinear optical responses. Compared with the single-ring Janus face compound (F 6 C 6 H 6 ), the three-ring Janus face compound (C 13 H 10 F 12 ) has a larger surface, where superalkali metals can be doped quite easily. Herein, the nonlinear optical response of Janus molecule dodecafluorophenylene (DDFP)-based superalkalides has been explored. The stability of the newly designed complexes is evident in the negative interaction energy values (ranging from -42.17 to -60.91 kcal/mol). The superalkalide nature of the complexes is corroborated through natural bond orbital (NBO) analysis, which shows negative charges on M 3 . This feature is further confirmed through frontier molecular orbital (FMO) analyses showing the highest occupied molecular orbital (HOMO) density over superalkalis (M 3 ). The analysis also reveals that the H-L gap is reduced from 9.57 eV (for bare DDFP) to 2.11 eV for doped systems by adsorption of dopants on the DDFP surface. Moreover, the NLO response of the studied complexes is evaluated via static hyperpolarizabilities. The maximum value of first hyperpolarizability (β o ) among all of the designed compounds is for K 3 -DDFP-K 3 (7.80 × 10 4 au) at M06-2X/6-31+G(d,p) level of theory. The β o is also rationalized through a two-level model. Furthermore, for β vec , the projection of hyperpolarizability on the dipole moment is calculated. The comparable results of β vec and β o indicate that the charge transfer in the complexes is parallel to the molecular dipole moments. These compounds, besides providing a new entry into excess-electron compounds, will also pave the way for the design and synthesis of further novel NLO materials.
Keyphrases
  • quantum dots
  • high resolution
  • machine learning
  • highly efficient
  • high speed
  • deep learning
  • magnetic resonance imaging
  • sensitive detection
  • gold nanoparticles
  • heavy metals
  • health risk
  • data analysis