Photoinduced relaxation dynamics of nitrogen-capped silicon nanoclusters: a TD-DFT study

ABSTRACT

Herein we have developed and implemented a TD-DFT-based surface-hopping dynamics simulation method with a recently proposed numerical algorithm capable of efficiently computing nonadiabatic couplings, a semiclassical spectrum simulation method, and an excited-state character analysis method based on one-electron transition density matrix. With the use of these developed methods, we have studied the spectroscopic properties, excited-state characters, and photoinduced relaxation dynamics of three silicon nanoclusters capped with different chromophores (Cl@SiQD, Car@SiQD, Azo@SiQD). Spectroscopically, the main absorption peak is visibly red-shifted from Cl@SiQD via Car@SiQD to Azo@SiQD. In contrast to Cl@SiQD and Car@SiQD, there are two peaks observed in Azo@SiQD. Mechanistically, the excited-state relaxation to the lowest S₁ excited singlet state is ultrafast in Cl@SiQD, which is less than 190 fs and without involving excited-state trapping. In comparison, there are clear excited-state trappings in Car@SiQD and Azo@SiQD. In the former, the S₂ state is trapped more than 300 fs; in the latter, the S₃ excited-state trapping is more than 615 fs. These results demonstrate that the interfacial interaction has significant influences on the spectroscopic properties and excited-state relaxation dynamics. The knowledge gained in this work could be helpful for the design of silicon nanoclusters with better photoluminescence performance.

KEYWORDS:

• Nitrogen-capped silicon nanoclusters
• excited-state trapping
• generalised fewest-switches surface hopping
• TD-DFT

Acknowledgments

G.C. is also grateful for financial support from the ‘Fundamental Research Funds for Central Universities’.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 21522302], [grant number 21688102], and [grant number 21421003].