We have applied DMC to evaluate relative stability of the possible electronic configurations of an isolated FePc under D_4h symmetry, considering some fixed nodes generated from different methods. They predict A_2g ground state consistently, supporting preceding DFT studies, with confidence overcoming the ambiguity about exchange-correlation (XC) functionals. By comparing DMC with several XC, we clarified the importance of the short-range exchange to describe the relative stability. We examined why the predicted A_2g is excluded from possible ground states in the recent ligand field based model. Simplified assumptions made in the superposition model are identified to give unreasonably less energy gain for A_2g when compared with the reality. The state is found to have possible reasons for the stabilization, reducing the occupations from an unstable anti-bonding orbital, avoiding double occupation of a spatially localized orbital, and gaining exchange energy by putting a triplet spin pair in degenerate orbitals.

Although boron nitride (BN) is a well-known compound widely used for engineering and scientific purposes, the phase stability of its polymorphs, one of its most fundamental properties, is still under debate. The ab initio determination of the ground state of the BN polymorphs, such as hexagonal and zinc-blende, is difficult because of the elusive van der Waals interaction, which plays a decisive role in some of the polymorphs, making quantitative prediction highly challenging. Hence, despite multiple theoretical studies, there has been no consensus on the ground state yet, primarily due to contradicting reports. In this study, we apply a state-of-the-art ab initio framework–fixed-node diffusion Monte Carlo (FNDMC), to four well-known BN polymorphs, namely hexagonal, rhombohedral, wurtzite, and zinc-blende BNs. Our FNDMC calculations show that hBN is thermodynamically the most stable among the four polymorphs at 0 K as well as at 300 K. This result agrees with the experimental data of Corrigan et al. and Fukunaga. The conclusions are consistent with those obtained using other high-level methods, such as coupled cluster. We demonstrate that the FNDMC is a powerful method to address polymorphs that exhibit bonds of various forms. It also provides valuable information, like reliable reference energies, when reliable experimental data are missing or difficult to access. Our findings should promote the application of FNDMC for other van der Waals materials.

We investigated the lattice thermal conductivity (LTC) of a subset of polymer crystals from the Polymer Genome Library to explore high LTC polymer systems. We employed a first-principles approach to evaluate the phonon lifetime within third-order perturbation theory combined with density functional theory, and then solved the linearized Boltzmann transport equation with a single-mode relaxation time approximated by the computed lifetime. Typical high LTC polymer systems, namely, polyethylene (PE) crystal and fiber, were benchmarked to validate our approach. In addition to PE, we evaluated the LTC of polyphenylene sulfide (PPS) and polyethylene terephthalate (PET), because, although their experimental LTC values are not obtained from their ``perfect'' crystals, they are mostly available. Our simulations reproduced an experimentally observed LTC ordering (PE >> PPS > PET). Applying our scheme to a number of polymer crystals for the first time, we discovered that the β phase of a poly(vinylidenesurely fluoride) (PVDF-β) crystal at low temperatures has the highest LTC among all the cases considered. We also found the LTC correlating to the curvature of an energy-volume plot. This curvature can be used as one of descriptors of constructing modern machine learning models to further explore high LTC polymer crystals by means of a data-driven approach beyond a human-based one.