MP2-F12 Basis Set Convergence for the S66 Noncovalent Interactions Benchmark: Transferability of the Complementary Auxiliary Basis Set (CABS)

Complementary auxiliary basis sets for F12 explicitly correlated calculations appear to be more transferable between orbital basis sets than has been generally assumed. We also find that aVnZ-F12 basis sets, originally developed with anionic systems in mind, appear to be superior for noncovalent interactions as well, and propose a suitable CABS sequence for them.Comment: AIP Conference Proceedings, in press (ICCMSE-2017 proceedings), 4 page

The aug-cc-pVnZ-F12 Basis Set Family: Correlation Consistent Basis Sets for Explicitly Correlated Benchmark Calculations on Anions and Noncovalent Complexes

We have developed a new basis set family, denoted aug-cc-pVnZ-F12 (or aVnZ-F12 for short), for explicitly correlated calculations. The sets included in this family were constructed by supplementing the corresponding cc-pVnZ-F12 sets with additional diffuse functions on the higher angular momenta (i.e., additional d-h functions on non-hydrogen atoms, and p-g on hydrogen), optimized for the MP2-F12 energy of the relevant atomic anions. The new basis sets have been benchmarked against electron affinities of the first- and second-row atoms, the W4-17 dataset of total atomization energies, the S66 dataset of noncovalent interactions, the BEGDB water clusters subset, and the WATER23 subset of the GMTKN24 and GMTKN30 benchmark suites. The aVnZ-F12 basis sets displayed excellent performance, not just for electron affinities but also for noncovalent interaction energies of neutral and anionic species. Appropriate CABS (complementary auxiliary basis sets) were explored for the S66 noncovalent interactions benchmark: between similar-sized basis sets, CABS were found to be more transferable than generally assumed.Comment: J. Chem. Phys., in pres

The cc-pV5Z-F12 basis set: reaching the basis set limit in explicitly correlated calculations

We have developed and benchmarked a new extended basis set for explicitly correlated calculations, namely cc-pV5Z-F12. It is offered in two variants, cc-pV5Z-F12 and cc- pV5Z-F12(rev2), the latter of which has additional basis functions on hydrogen not present in the cc-pVnZ-F12 (n=D,T,Q) sequence.A large uncontracted 'reference' basis set is used for benchmarking. cc-pVnZ-F12 (n=D, T, Q, 5) is shown to be a convergent hierarchy. Especially the cc- pV5Z-F12(rev2) basis set can yield the valence CCSD component of total atomization energies (TAEs), without any extrapolation, to an accuracy normally associated with aug-cc-pV{5,6}Z extrapolations. SCF components are functionally at the basis set limit, while the MP2 limit can be approached to as little as 0.01 kcal/mol without extrapolation. The determination of (T) appears to be the most difficult of the three components and cannot presently be accomplished without extrapolation or scaling. (T) extrapolation from cc-pV{T,Q}Z-F12 basis sets, combined with CCSD-F12b/cc-pV5Z-F12 calculations appears to be an accurate combination for explicitly correlated thermochemistry. For accurate work on noncovalent interactions, basis set superposition error with the cc-pV5Z-F12 basis set is shown to be so small that counterpoise corrections can be neglected for all but the most exacting purposes.Comment: Molecular Physics, in press (Nicholas C. Handy memorial issue). DOI preassigne

The X40x10 Halogen Bonding Benchmark Revisited: Surprising Importance of (n-1)d Subvalence Correlation

We have re-evaluated the X40x10 benchmark for halogen bonding using conventional and explicitly correlated coupled cluster methods. For the aromatic dimers at small separation, improved CCSD(T)–MP2 “high-level corrections” (HLCs) cause substantial reductions in the dissociation energy. For the bromine and iodine species, (n-1)d subvalence correlation increases dissociation energies, and turns out to be more important for noncovalent interactions than is generally realized. As in previous studies, we find that the most efficient way to obtain HLCs is to combine (T) from conventional CCSD(T) calculations with explicitly correlated CCSD-F12–MP2-F12 differences.</jats:p

The X40x10 Halogen Bonding Benchmark Revisited: Surprising Importance of (n-1)d Subvalence Correlation

&lt;p&gt;We have re-evaluated the X40x10 benchmark for halogen bonding using conventional and explicitly correlated coupled cluster methods. For the aromatic dimers at small separation, improved CCSD(T)–MP2 “high-level corrections” (HLCs) cause substantial reductions in the dissociation energy. For the bromine and iodine species, (n-1)d subvalence correlation increases dissociation energies, and turns out to be more important for noncovalent interactions than is generally realized; ; (n-1)sp subvalence correlation is much less important. The (n-1)d subvalence term is dominated by core-valence correlation; with the smaller cc-pVDZ-F12-PP and cc-pVTZ-F12-PP basis sets, basis set convergence for the core-core contribution becomes sufficiently erratic that it may compromise results overall. The two factors conspire to generate discrepancies of up to 0.9 kcal/mol (0.16 kcal/mol RMS) between the original X40x10 data and the present revision.&lt;/p&gt;</jats:p

The X40x10 Halogen Bonding Benchmark Revisited: Surprising Importance of (n-1)d Subvalence Correlation

We have re-evaluated the X40x10 benchmark for halogen bonding using conventional and explicitly correlated coupled cluster methods. For the aromatic dimers at small separation, improved CCSD(T)–MP2 “high-level corrections” (HLCs) cause substantial reductions in the dissociation energy. For the bromine and iodine species, (n-1)d subvalence correlation increases dissociation energies, and turns out to be more important for noncovalent interactions than is generally realized; ; (n-1)sp subvalence correlation is much less important. The (n-1)d subvalence term is dominated by core-valence correlation; with the smaller cc-pVDZ-F12-PP and cc-pVTZ-F12-PP basis sets, basis set convergence for the core-core contribution becomes sufficiently erratic that it may compromise results overall. The two factors conspire to generate discrepancies of up to 0.9 kcal/mol (0.16 kcal/mol RMS) between the original X40x10 data and the present revision.</p

The S66 noncovalent interactions benchmark reconsidered using explicitly correlated methods near the basis set limit

The S66 benchmark for noncovalent interactions has been re-evaluated using explicitly correlated methods with basis sets near the one-particle basis set limit. It is found that post-MP2 “high-level corrections” are treated adequately well using a combination of CCSD(F12*) with (aug-)cc-pVTZ-F12 basis sets on the one hand, and (T) extrapolated from conventional CCSD(T)/heavy-aug-cc-pV{D,T}Z on the other hand. Implications for earlier benchmarks on the larger S66x8 problem set in particular, and for accurate calculations on noncovalent interactions in general, are discussed. At a slight cost in accuracy, (T) can be considerably accelerated by using sano-V{D,T}Z+ basis sets, while half-counterpoise CCSD(F12*)(T)/cc-pVDZ-F12 offers the best compromise between accuracy and computational cost.</p

The S66 noncovalent interactions benchmark reconsidered using explicitly correlated methods near the basis set limit

&lt;p&gt;[Final version of record available at http://dx.doi.org/10.1071/CH17588]&lt;/p&gt;&lt;p&gt;The S66 benchmark for noncovalent interactions has been re-evaluated using explicitly correlated methods with basis sets near the one-particle basis set limit. It is found that post-MP2 “high-level corrections” are treated adequately well using a combination of CCSD(F12*) with (aug-)cc-pVTZ-F12 basis sets on the one hand, and (T) extrapolated from conventional CCSD(T)/heavy-aug-cc-pV{D,T}Z on the other hand. Implications for earlier benchmarks on the larger S66x8 problem set in particular, and for accurate calculations on noncovalent interactions in general, are discussed. At a slight cost in accuracy, (T) can be considerably accelerated by using sano-V{D,T}Z+ basis sets, while half-counterpoise CCSD(F12*)(T)/cc-pVDZ-F12 offers the best compromise between accuracy and computational cost.&lt;br&gt;&lt;/p&gt;</jats:p

Denture base materials surface roughness changes in response to exposure to cigarette smoke in an in vitro experiment

Aim: Denture base materials were subjected to cigarette smoke for the purpose of determining their surface roughness. Materials and Methods: Polymethylmethacrylate and flexible denture base materials were used to manufacture 40 specimens for this study (20 for each). Each sample was randomly assigned to one of four groups: control, flexible, and heat-cured denture base material samples. The heat-cured denture material samples were the only ones that had been exposed to cigarette smoke (subgroup III). There was a control group for each group. For the smoke test groups, distilled water was utilised, whereas cigarette smoking was used for the water test groups. Each participant in the trial was exposed to six cigarettes in a specially created smoking area. Surface roughness differences between pre- and post-smoking samples were analysed using a profilometer. The data was analysed using a paired comparison and an independent comparison. Groupings differed significantly in their initial roughness and final roughness, according to results from a paired t-test. Conclusion: Surface harshness of tobacco-smoke-exposed specimens of both the intensity-restored and the adaptive dental replacement base materials was greater