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Most torsional barriers are predicted to high accuracy (about 1kJ/mol) by standard semilocal functionals, but a small subset has been found to have much larger errors. We create a database of almost 300 carbon-carbon torsional barriers, including 12 poorly behaved barriers, all stemming from Y=C-X group, where X is O or S, and Y is a halide. Functionals with enhanced exchange mixing (about 50%) work well for all barriers. We find that poor actors have delocalization errors caused by hyperconjugation. These problematic calculations are density sensitive (i.e., DFT predictions change noticeably with the density), and using HF densities (HF-DFT) fixes these issues. For example, conventional B3LYP performs as accurately as exchange-enhanced functionals if the HF density is used. For long-chain conjugated molecules, HF-DFT can be much better than exchange-enhanced functionals. We suggest that HF-PBE0 has the best overall performance.
We present a simple torsional potential for graphene to accurately describe its out-of-plane deformations. The parameters of the potential are derived through appropriate fitting with suitable DFT calculations regarding the deformation energy of grap
We analyze theoretically the interplay between the torsional and the rotational motion of an aligned biphenyl-like molecule. To do so, we consider a transition between two electronic states with different internal torsional potentials, induced by mea
Projection-based embedding provides a simple, robust, and accurate approach for describing a small part of a chemical system at the level of a correlated wavefunction method while the remainder of the system is described at the level of density funct
Using a set of oscillator strengths and excited-state dipole moments of near full configuration interaction (FCI) quality determined for small compounds, we benchmark the performances of several single-reference wave function methods (CC2, CCSD, CC3,
Bottom-up coarse-grained molecular dynamics models are parameterized using complex effective Hamiltonians. These models are typically optimized to approximate high dimensional data from atomistic simulations. In contrast, human validation of these mo