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Using a non-empirically tuned range-separated DFT approach, we study both thequasiparticle properties (HOMO-LUMO fundamental gaps) and excitation energiesof DNA and RNA nucleobases (adenine, thymine, cytosine, guanine, and uracil).Our calculations demonstrate that a physically-motivated, first-principlestuned DFT approach accurately reproduces results from both experimentalbenchmarks and more computationally intensive techniques such as many-body GWtheory. Furthermore, in the same set of nucleobases, we show that thenon-empirical range-separated procedure also leads to significantly improvedresults for excitation energies compared to conventional DFT methods. Thepresent results emphasize the importance of a non-empirically tunedrange-separation approach for accurately predicting both fundamental andexcitation gaps in DNA and RNA nucleobases.

Non-Empirically Tuned Range-Separated DFT Accurately Predicts Both Fundamental and Excitation Gaps in DNA and RNA Nucleobases