Simulating molecular adsorption on surfaces presents considerable challenges, as computational methods typically suffer from either insufficient accuracy or prohibitive computational costs. Now, with ...

Basis set incompleteness error (BSIE) is a common source of error in quantum chemistry calculations, but it has not been comprehensively studied in fixed-node Diffusion Monte Carlo (FN-DMC) calculations. FN-DMC, being a projection method, is often considered minimally affected by basis set biases. Here, we show that this assumption is not always valid. While the relative error introduced by a small basis set in the total FN-DMC energy is minor, it can become significant in binding energy (Eb) evaluations of weakly interacting systems. We systematically investigated BSIEs in FN-DMC-based Eb evaluations using the A24 data set, a well-known benchmark set of 24 noncovalently bound dimers. We found that BSIEs in FN-DMC evaluations of Eb are indeed significant when small localized basis sets, such as cc-pVDZ and cc-pVTZ, are employed. Our study shows that the aug-cc-pVTZ basis set family strikes a good balance between computational cost and BSIEs in the Eb calculations. We also found that augmenting the basis sets with diffuse orbitals, using counterpoise correction, or both, effectively mitigates BSIEs, allowing smaller basis sets such as aug-cc-pVDZ to be used.

Electronic-structure theory is the foundation of the description of materials including multiscale modeling of their properties and functions. Obviously, without sufficient accuracy at the base, relia...

Hybrid density functional approximations (DFAs) offer compelling accuracy for ab initio electronic-structure simulations of molecules, nanosystems, and bulk mat

Fixed-node diffusion quantum Monte Carlo (FN-DMC) is a widely-trusted many-body method for solving the Schrödinger equation, known for its reliable predictions of material and molecular properties. Fu...