Data-Driven Recommendation of Optimal Tuning Scheme for Range-Separated Hybrid Functionals in Solution-Phase UV/Vis Absorption Energy Prediction

Data-Driven Recommendation of Optimal Tuning Scheme for Range-Separated Hybrid Functionals in Solution-Phase UV/Vis Absorption Energy Prediction

Time-dependent density functional theory (TDDFT) combined with range-separated hybrid (RSH) functionals and a tuned range-separation parameter γ offers a computationally economical approach for high-throughput excited-state property predictions. The γ-tuning procedure in the gas phase is well establ...

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Gorde:
Xehetasun bibliografikoak
Egile nagusia: Fangning Ren (7831376) (author)
Beste egile batzuk: Pinyuan Li (14060412) (author), Xu Chen (432759) (author), Lechen Dong (20634095) (author), Fang Liu (13271) (author)
Argitaratua: 2025
Gaiak:
Biophysics
Neuroscience
Space Science
vis absorption spectra
state property predictions
polarizable continuum model
lesser computational cost
>) asymptotic behavior
computationally economical approach
phase ct excitations
strict vertical γ
partial vertical γ
slightly outperform srsh
mediated tuning procedure
separated hybrid functionals
separated hybrid combined
optimal tuning scheme
separated hybrid
tuning procedure
optimal γ
best scheme
phase γ
tuning methods
phase uv
pcm approach
three γ
smaller γ
default γ
best γ
ωpbeh functional
well established
throughput uv
throughput excited
study created
solvent effect
significantly smaller
results show
r </
findings revealed
driven recommendation
driven perspective
additional benchmarks
accurate prediction
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