Amorphous molecular materials are ubiquitous, spanning drugs, semiconductors, or solvents. Large predictive capabilities of quantum-chemical simulations of structural and thermodynamic properties and phase transitions for such amorphous materials have remained out of reach for a long time due to the related immense computational costs. This work introduces a novel fragment-based ab initio Monte Carlo (FrAMonC) simulation technique to the amorphous realm of molecular liquids and glasses. It aims at enabling thermodynamic simulations for amorphous molecular materials based on direct ab initio sampling and at minimizing the amount of a priori required empirical inputs for such simulations. Focus on individual cohesive interactions within the bulk, and their sampling from multiple first-principles potentials with a many-body expansion scheme enables the use of very accurate electron-structure methods for the most important cohesive features within the material. Even the coupled-cluster theory, the direct use of which is unprecedented for molecular simulations of thermodynamic properties for liquids, then becomes applicable to the description of bulk amorphous materials. Its incorporation in the proposed Monte Carlo simulations promises very high computational accuracy. Bulk-phase equilibrium properties at finite temperatures and pressures, such as density and vaporization enthalpy, as well as response properties such as thermal expansivity and heat capacity that are particularly challenging to predict accurately, are the observables targeted in this work. Superior computational accuracy of the introduced FrAMonC simulations is demonstrated for most target properties (liquid-phase densities, thermal expansivities, and gas-liquid differences in the heat capacities) when compared with established classical or quantum-chemical models that are commonly used to model such properties of bulk liquids.

Department of Physical Chemistry University of Chemistry and Technology Prague Technická 5 CZ 166 28 Prague 6 Czech Republic

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