This work presents evidence that photo-excitation of guanine radical cations results in high yields of deoxyribose sugar radicals in DNA, guanine deoxyribonucleosides and deoxyribonucleotides. In dsDNA at low temperatures, formation of C1′• is observed from photo-excitation of G•+ in the 310–480 nm range with no C1′• formation observed ≥520 nm. Illumination of guanine radical cations in 2′dG, 3′-dGMP and 5′-dGMP in aqueous LiCl glasses at 143 K is found to result in remarkably high yields (∼85–95%) of sugar radicals, namely C1′•, C3′• and C5′•. The amount of each of the sugar radicals formed varies dramatically with compound structure and temperature of illumination. Radical assignments were confirmed using selective deuteration at C5′ or C3′ in 2′-dG and at C8 in all the guanine nucleosides/tides. Studies of the effect of temperature, pH, and wavelength of excitation provide important information about the mechanism of formation of these sugar radicals. Time-dependent density functional theory calculations verify that specific excited states in G•+ show considerable hole delocalization into the sugar structure, in accord with our proposed mechanism of action, namely deprotonation from the sugar moiety of the excited molecular radical cation.

We report that photo-excitation of one-electron-oxidized adenine [A(-H)•] in dAdo and its 2′-deoxyribonucleotides leads to formation of deoxyribose sugar radicals in remarkably high yields. Illumination of A(-H)• in dAdo, 3′-dAMP and 5′-dAMP in aqueous glasses at 143 K leads to 80-100% conversion to sugar radicals at C5′ and C3′. The position of the phosphate in 5′- and 3′-dAMP is observed to deactivate radical formation at the site of substitution. In addition, the pH has a crucial influence on the site of sugar radical formation; e.g. at pH ∼5, photo-excitation of A(-H)• in dAdo at 143 K produces mainly C5′• whereas only C3′• is observed at high pH ∼12. 13C substitution at C5′ in dAdo yields 13C anisotropic couplings of (28, 28, 84) G whose isotropic component 46.7 G identifies formation of the near planar C5′•. A β-13C 16 G isotropic coupling from C3′• is also found. These results are found to be in accord with theoretically calculated 13C couplings at C5′ [DFT, B3LYP, 6-31(G) level] for C5′• and C3′•. Calculations using time-dependent density functional theory [TD-DFT B3LYP, 6-31G(d)] confirm that transitions in the near UV and visible induce hole transfer from the base radical to the sugar group leading to sugar radical formation.

Absorption UV spectra of gold clusters Au(n) (n = 4, 6, 8, 12, 20) are investigated using the time-dependent density functional theory (TDDFT). The calculations employ several long-range corrected xc functionals: ωB97X, LC-ωPBEh, CAM-B3LYP∗ (where ∗ denotes a variant with corrected asymptote of CAM-B3LYP), and LC-ωPBE. The latter two are subject to first-principle tuning according to a prescription of Stein et al. [Phys. Rev. Lett. 105, 266802 (2010)] by varying the range separation parameter. TDDFT results are validated for Au(4) and Au(8) against the equation-of-motion coupled cluster singles and doubles results and the experiment. Both long-range correction and the inclusion of a fixed portion of the exact exchange in the short-range are essential for the proper description of the optical spectra of gold. The ωB97X functional performs well across all studied cluster sizes. LC-ωPBEh, with parameters recommended by Rohrdanz et al. [J. Chem. Phys. 130, 054112 (2009)], affords the best performance for clusters of n > 4. The optimally tuned CAM-B3LYP∗ features the range separation parameter of 0.33 for Au(4) and 0.25 for all the larger clusters. For LC-ωPBE the tuning procedure resulted in incorrect transition energies and oscillator strengths despite the fact that the optimized functional showed the accurate linear dependence on fractional electron numbers. Au(n) (n = 4, 6, 8) feature optical gaps above of 3 eV and Au(20) of ∼2.9 eV. In Au(12) this gap narrows to ∼2.1 eV. The calculated spectrum for Au(20) involves intensity being concentrated in only a few transitions with the absorption maximum at 3.5 eV. The intense 3.5 eV absorption is present in all cluster sizes of n > 4. The calculated HOMO-LUMO gaps for all cluster sizes are within 0.5 eV of the difference between the vertical ionization potential and electron affinity. The reasons for this and for the failure of conventional xc functionals for optical spectra of gold are discussed.

Donor-acceptor interactions are notoriously difficult and unpredictable for conventional density functional theory (DFT) methodologies. This work presents a reliable computational treatment of gold-ligand interactions of the donor-acceptor type within DFT. These interactions require a proper account of the ionization potential of the electron donor and electron affinity of the electron acceptor. This is accomplished in the Generalized Kohn Sham framework that allows one to relate these properties to the frontier orbitals in DFT via the tuning of range-separated functionals. A donor and an acceptor typically require different tuning schemes. This poses a problem when the binding energies are calculated using the supermolecular method. A two-parameter tuning for the monomer properties ensures that a common functional, optimal for both the donor and the acceptor, is found. A reliable DFT approach for these interactions also takes into account the dispersion contribution. The approach is validated using the water dimer and the (HAuPH3)2 aurophilic complex. Binding energies are computed for Au4 interacting with the following ligands: SCN(-), benzenethiol, benzenethiolate anion, pyridine, and trimethylphosphine. The results agree for the right reasons with coupled-cluster reference values.

This research demonstrates an application of a modified self-organizing feature map (SOFM) algorithm to analyze and discover the quality of chemical absorption spectrum data. By forming an NxN neural array from input features and varying the essential parameters of the algorithm, map recognition quality is increased at the expense of more computation. The features of this SOFM are based on absorption intensity variations with excitation wavelength. SOFMs are used to discern pattern similarities and differences between spectral data. A context tree allows individual features, or key numbers in the data, to be input and classifies the vector to the type of data that is most similar. This research also use the self-organizing map to enhance as well as visualize resultant classification efficiency through the use of watershed transformation.