Psi4 is a free and open-source ab initio electronic structure program providing Hartree-Fock, density functional theory, many-body perturbation theory, configuration interaction, density cumulant theory, symmetry-adapted perturbation theory, and coupled-cluster theory. Most of the methods are quite efficient thanks to density fitting and multi-core parallelism. The program is a hybrid of C++ and Python, and calculations may be run with very simple text files or using the Python API, facilitating post-processing and complex workflows; method developers also have access to most of Psi4's core functionality via Python. Job specification may be passed using The Molecular Sciences Software Institute (MolSSI) QCSchema data format, facilitating interoperability. A rewrite of our top-level computation driver, and concomitant adoption of the MolSSI QCArchive Infrastructure project, make the latest version of Psi4 well suited to distributed computation of large numbers of independent tasks. The project has fostered the development of independent software components that may be reused in other quantum chemistry programs. File list (2) download file view on ChemRxiv psi4.pdf (4.37 MiB) download file view on ChemRxiv supplementary_material.pdf (297.86 KiB)

Using Brillouin scattering, we measured the single-crystal elastic constants (C ij 's) of a prototypical metal-organic framework (MOF): zeolitic imidazolate framework (ZIF)-8 [Znð2-methylimidazolateÞ 2 ], which adopts a zeolitic sodalite topology and exhibits large porosity. Its C ij 's under ambient conditions are (in GPa) C 11 ¼ 9:522ð7Þ, C 12 ¼ 6:865ð14Þ, and C 44 ¼ 0:967ð4Þ. Tensorial analysis of the C ij 's reveals the complete picture of the anisotropic elasticity in cubic ZIF-8. We show that ZIF-8 has a remarkably low shear modulus G min & 1 GPa, which is the lowest yet reported for a single-crystalline extended solid. Using ab initio calculations, we demonstrate that ZIF-8's C ij 's can be reliably predicted, and its elastic deformation mechanism is linked to the pliant ZnN 4 tetrahedra. Our results shed new light on the role of elastic constants in establishing the structural stability of MOF materials and thus their suitability for practical applications.

ZIF-8, a prototypical zeolitic porous coordination polymer, prepared via the self-assembly of tetrahedral atoms (e.g. Zn and Co) and organic imidazolate linkers, presents large cavities which are interconnected by narrow windows that allow, in principle, molecular sieving. However, ZIF-8 shows flexibility due to the swing of the imidazolate linkers, which results in the adsorption of molecules which are too large to fit through the narrow window. In this work, we assess the impact of this flexibility, previously only observed for nitrogen, and the level of agreement between the experimental and simulated isotherms of different energy-related gases on ZIF-8 (CO(2), CH(4) and alkanes). We combine experimental gas adsorption with GCMC simulations, using generic and adjusted force fields and DFT calculations with the Grimme dispersion correction. By solely adapting the UFF force field to reduce the Lennard-Jones parameter ε, we achieve excellent agreement between the simulated and experimental results not only for ZIF-8 but also for ZIF-20, where the transferability of the adapted force field is successfully tested. Regarding ZIF-8, we show that two different structural configurations are needed to properly describe the adsorption performance of this material, demonstrating that ZIF-8 is undergoing a structural change during gas adsorption. DFT calculations with the Grimme dispersion correction are consistent with the GCMC and experimental observations, illustrating the thermodynamics of the CH(4) adsorption sites and confirming the existence of a new adsorption site with a high binding energy within the 4-ring window of ZIF-8.

The dense, anhydrous zeolitic imidazolate frameworks (ZIFs), Zn(Im)(2) (1) and LiB(Im)(4) (2), adopt the same zni topology and differ only in terms of the inorganic species present in their structures. Their mechanical properties (specifically the Young's and bulk moduli, along with the hardness) have been elucidated by using high pressure, synchrotron X-ray diffraction, density functional calculations and nanoindentation studies. Under hydrostatic pressure, framework 2 undergoes a phase transition at 1.69 GPa, which is somewhat higher than the transition previously reported in 1. The Young's modulus (E) and hardness (H) of 1 (E≈8.5, H≈1 GPa) is substantially higher than that of 2 (E≈3, H≈0.1 GPa), whilst its bulk modulus is relatively lower (≈14 GPa cf. ≈16.6 GPa). The heavier, zinc-containing material was also found to be significantly harder than its light analogue. The differential behaviour of the two materials is discussed in terms of the smaller pore volume of 2 and the greater flexibility of the LiN(4) tetrathedron compared with the ZnN(4) and BN(4) units.

We show that dispersive interactions are important components in modelling zeolitic imidazolate frameworks (ZIF). Our comparative study of Zn-based and LiB-based zeolitic imidazolate frameworks reveals that, unexpectedly, both families exhibit a very similar structure-energy relationship, and exhibit a much larger energy spread than previously proposed. This finding suggests that from thermodynamic considerations, the diversity and synthesizability of LiB-based structures should be very similar to Zn-based ZIFs but very porous Zn-and LiB-ZIFs are predicted to be particularly challenging to synthesize. However, fewer unique LiB-based structure types have been synthesized thus far which suggests kinetic barriers may be more significant for LiB frameworks than Zn-based materials.

<div> <div> <div> <p>Psi4 is a free and open-source ab initio electronic structure program providing Hartree–Fock, density functional theory, many-body perturbation theory, configuration interaction, density cumulant theory, symmetry-adapted perturbation theory, and coupled-cluster theory. Most of the methods are quite efficient thanks to density fitting and multi-core parallelism. The program is a hybrid of C++ and Python, and calculations may be run with very simple text files or using the Python API, facilitating post-processing and complex workflows; method developers also have access to most of Psi4’s core functionality via Python. Job specification may be passed using The Molecular Sciences Software Institute (MolSSI) QCSchema data format, facilitating interoperability. A rewrite of our top-level computation driver, and concomitant adoption of the MolSSI QCArchive Infrastructure project, make the latest version of Psi4 well suited to distributed computation of large numbers of independent tasks. The project has fostered the development of independent software components that may be reused in other quantum chemistry programs. </p> </div> </div> </div>

Fast and accurate molecular force field (FF) parameterization is still an unsolved problem. Accurate FFs are not generally available for all molecules, like novel druglike molecules. While methods based on quantum mechanics (QM) exist to parameterize them with better accuracy, they are computationally expensive and slow, which limits applicability to a small number of molecules. Here, we present an automated FF parameterization method which can utilize either DFT calculations or approximate arXiv:1907.06952v2 [physics.chem-ph] 3 Aug 2019 QM energies produced by different neural network potentials (NNPs), to obtain improved parameters for molecules. We demonstrate that for the case of torchani-ANI-1x NNP, we can parameterize small molecules in a fraction of time compared with an equivalent parameterization using DFT QM calculations while producing more accurate parameters than FF (GAFF2). We expect our method to be of critical importance in computational structure-based drug discovery. The current version is available at PlayMolecule (www.playmolecule.org) and implemented in HTMD, allowing to parameterize molecules with different QM and NNP options.

The free energy calculations of complex chemical and biological systems with molecular dynamics (MD) are inefficient due to multiple local minima separated by high-energy barriers. The minima can be escaped using an enhanced sampling method such as metadynamics, which apply bias (i.e., importance sampling) along a set of collective variables (CV), but the maximum number of CVs (or dimensions) is severely limited. We propose a high-dimensional bias potential method (NN2B) based on two machine learning algorithms: the nearest neighbor density estimator (NNDE) and the artificial neural network (ANN) for the bias potential approximation. The bias potential is constructed iteratively from short biased MD simulations accounting for correlation among CVs. Our method is capable of achieving ergodic sampling and calculating free energy of polypeptides with up to 8-dimensional bias potential.