SCS-MP2 on molecular crystals
Background
Cohesive energies of molecular crystals are a stringent test for electronic-structure methods, because the binding is dominated by weak interactions that cheap methods miss. The cohesive energy per molecule is written as
where is the energy of the crystal unit cell, is the number of molecules in that cell, and is the energy of an isolated molecule. Experimental sublimation enthalpies pin this quantity down tightly, and a method’s errors thus show up directly. The paper behind this repository asks whether periodic spin-component-scaled MP2 can deliver kJ/mol accuracy on the X23 benchmark set of 23 molecular crystals.
Spin-component scaling
MP2 correlation energy separates into contributions from opposite-spin and same-spin electron pairs, and the SCS family of methods rescales the two pieces independently. The scaled correlation energy reads
where and are the opposite-spin and same-spin pair energies and , are empirical coefficients. Plain MP2 corresponds to setting both coefficients to one. The appeal for molecular crystals is that a cheap reweighting of quantities MP2 already computes might repair its known biases for noncovalent binding.
Convergence
Getting a defensible answer required converging every number to both the thermodynamic limit and the complete-basis-set limit, which the study does to about 2 kJ/mol precision. At that level of control, the residual disagreement with experiment belongs to the method rather than to the calculation. The converged results give a mean absolute error of 12.9 kJ/mol against experimental cohesive energies, comparable to dispersion-corrected DFT of the PBE+TS type.
Repository
This repository keeps the pieces a reader would need to redo or reuse that work. The crystal and molecule geometries are provided in both xyz and VASP cell formats, alongside the custom augmented cc-pVXZ basis sets built for the basis-convergence study. Two worksheets carry the numbers behind the paper’s tables, one with the cohesive energies, basis-set extrapolation fits, and BSSE estimation, and one documenting basis-set convergence across basis sizes.
With Hong-Zhou Ye and Tim Berkelbach at Columbia. Everything is Apache-licensed so the results can be reproduced or repurposed.