The main goal of molecular simulation is to accurately predict experimental observables of molecular systems. Another long-standing goal is to devise models for arbitrary neutral organic molecules with little or no reliance on experimental data. While separately these goals have been met to various degrees, for an arbitrary system of molecules they have not been achieved simultaneously. For biophysical ensembles that exist at room temperature and pressure, and where the entropic contributions are on par with interaction strengths, it is the free energies that are both most important and most difficult to predict. We compute the free energies of solvation for a diverse set of neutral organic compounds using a polarizable force field fitted entirely to ab initio calculations. The mean absolute errors (MAE) of hydration, cyclohexane solvation, and corresponding partition coefficients are 0.2 kcal/mol, 0.3 kcal/mol and 0.22 log units, i.e. within chemical accuracy. The model (ARROW FF) is multipolar, polarizable, and its accompanying simulation stack includes nuclear quantum effects (NQE). The simulation tools’ computational efficiency is on a par with current state-of-the-art packages. The construction of a wide-coverage molecular modelling toolset from first principles, together with its excellent predictive ability in the liquid phase is a major advance in biomolecular simulation.

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The cleaning of two-dimensional (2D) materials is an essential step in the fabrication of future devices, leveraging their unique physical, optical, and chemical properties. Part of these emerging 2D materials are transition metal dichalcogenides (TMDs). So far there is limited understanding of the cleaning of “monolayer” TMD materials. In this study, we report on the use of downstream H2 plasma to clean the surface of monolayer WS2 grown by MOCVD. We demonstrate that high-temperature processing is essential, allowing to maximize the removal rate of polymers and to mitigate damage caused to the WS2 in the form of sulfur vacancies. We show that low temperature in situ carbonyl sulfide (OCS) soak is an efficient way to resulfurize the material, besides high-temperature H2S annealing. The cleaning processes and mechanisms elucidated in this work are tested on back-gated field-effect transistors, confirming that transport properties of WS2 devices can be maintained by the combination of H2 plasma cleaning and OCS restoration. The low-damage plasma cleaning based on H2 and OCS is very reproducible, fast (completed in a few minutes) and uses a 300 mm industrial plasma etch system qualified for standard semiconductor pilot production. This process is, therefore, expected to enable the industrial scale-up of 2D-based devices, co-integrated with silicon technology.

Protein–ligand binding free-energy calculations using molecular dynamics (MD) simulations have emerged as a powerful tool for in silico drug design. Here, we present results obtained with the ARROW force field (FF)a multipolar polarizable and physics-based model with all parameters fitted entirely to high-level ab initio quantum mechanical (QM) calculations. ARROW has already proven its ability to determine solvation free energy of arbitrary neutral compounds with unprecedented accuracy. The ARROW FF parameterization is now extended to include coverage of all amino acids including charged groups, allowing molecular simulations of a series of protein–ligand systems and prediction of their relative binding free energies. We ensure adequate sampling by applying a novel technique that is based on coupling the Hamiltonian Replica exchange (HREX) with a conformation reservoir generated via potential softening and nonequilibrium MD. ARROW provides predictions with near chemical accuracy (mean absolute error of ∼0.5 kcal/mol) for two of the three protein systems studied here (MCL1 and Thrombin). The third protein system (CDK2) reveals the difficulty in accurately describing dimer interaction energies involving polar and charged species. Overall, for all of the three protein systems studied here, ARROW FF predicts relative binding free energies of ligands with a similar accuracy level as leading nonpolarizable force fields.