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Beyond Static Molecules: Modeling Quantum Fluctuations in Complex Molecular Environments

Periodic Reporting for period 2 - BeStMo (Beyond Static Molecules: Modeling Quantum Fluctuations in Complex Molecular Environments)

Reporting period: 2018-09-01 to 2020-02-29

We propose focused theory developments and applications, which aim to substantially advance our ability to model and understand the behavior of molecules in complex environments. From a large repertoire of possible environments, we have chosen to concentrate on experimentally-relevant situations, including molecular fluctuations in electric and optical fields, disordered molecular crystals, solvated (bio)molecules, and molecular interactions at/through low-dimensional nanostructures. A challenging aspect of modeling such realistic environments is that both molecular electronic and nuclear fluctuations have to be treated efficiently at a robust quantum-mechanical level of theory for systems with 1000s of atoms. In contrast, the current state of the art in the modeling of complex molecular systems typically consists of Newtonian molecular dynamics employing classical force fields. We will develop radically new approaches for electronic and nuclear fluctuations that unify concepts and merge techniques from quantum-mechanical many-body Hamiltonians, statistical mechanics, density-functional theory, and machine learning. Our developments will be benchmarked using experimental measurements with terahertz (THz) spectroscopy, atomic-force and scanning tunneling microscopy (AFM/STM), time-of-flight (TOF) measurements, and molecular interferometry.
Numerous fascinating and useful dynamical phenomena in complex molecular systems stem from an interplay between quantum-mechanical electronic and nuclear fluctuations. Many of the anomalies of water – the most ubiquitous liquid on Earth – are the result of a subtle coupling between its peculiar hydrogen bonded network and quantized nuclear fluctuations. Another particularly striking example is the aspirin molecular crystal, in which the prevalent form I polymorph is stabilized by entropy stemming from an unexpected dynamical coupling between non-covalent van der Waals interactions and quantized lattice vibrations. Additional prominent examples of coaction of electronic and nuclear quantum fluctuations include the peculiar ability of protons to permeate atomically-thin membranes at room temperature, the pervasive observation of delocalized boson peaks in disordered molecular materials, and non-trivial wavelike behavior of large molecules in electric and optical fields. Our ability to atomistically model and understand all of these important phenomena requires substantial breakthroughs.
Our final goal is to bridge the accuracy of quantum mechanics with the efficiency of force fields, enabling large-scale predictive quantum molecular dynamics simulations for complex systems containing 1000s of atoms, and leading to novel conceptual insights into quantum-mechanical fluctuations in large molecular systems. The project goes well beyond the presently possible applications and once successful will pave the road towards having a suite of first-principles-based modeling tools for a wide range of realistic materials, such as biomolecules, nanostructures, disordered solids, and organic/inorganic interfaces.
The BeStMo project had significant advances in all workpackages WP1, WP2, WP3, and WP4.
In WP1, we have developed a coarse-grained multiscale approach to van der Waals interactions in arbitrary external fields including electronic and nuclear fluctuations. Using this model, we have obtained surprising results on modification of van der Waals interactions in systems subjected to external environments. These results have been reported in multidisciplinary journals Science Advances, Physical Review Letters, and Nature Communications (3 publications). In the next period, we will release two open source code package and two comprehensive publications that will allow others to do calculations on complex systems.
In WP2, we have extended the previously published MBD method to treat systems with more than 10,000 atoms. We applied these developments to study the quantum mechanics of fully solvated proteins. The corresponding manuscript has been published in Science Advances. At least three more drafts are being prepared for publication in high-impact journals. At the moment we are also implementing a coarse-grained version of the MBD model that will push its applicability to systems with 100,000 atoms.
In WP3, we have developed a suite of machine learning models for essentially exact molecular dynamics of small molecules. The three ensuing papers have been published in Science Advances (1 paper) and Nature Communications (2 papers). The community has received this work very enthusiastically and I would consider these developments as true breakthroughs. At the moment, we are able to run molecular dynamics simulations with fully quantized electrons and nuclei for molecules with 50-100 atoms for the first time. The remaining challenge is to treat long-range non-covalent interactions with physical approaches such as MBD and derive a coupling potential between machine-learned force field and physics-based Hamiltonians. We already obtained preliminary results indicating that this approach is promising.
In WP4, in collaboration with the group of Michele Ceriotti at EPFL, we have developed a method for carrying out efficient high-order path integral simulations of molecular systems. This work has been published in the Journal of Chemical Theory and Computation and implemented in publically available i-PI code.
Overall, I feel that the original plan of the proposal has been fully accomplished and, indeed, exceeded in WP2 and WP3. During the next period, we will concentrate on the mentioned developments mainly in WP2 and WP3.
The main goal of the BeStMo project is to develop pioneering methods that include both electronic and nuclear quantum-mechanical many-particle fluctuations in the modeling of dynamics of complex molecular systems with 1000s of atoms. This challenging goal will be accomplished by unifying concepts and combining techniques from many-body physics, quantum chemistry, densityfunctional theory, statistical mechanics, and machine learning. My group is uniquely positioned to achieve this ambitious goal, having demonstrated substantial expertise in the development of efficient and accurate methods for long-range electronic correlation, nuclear quantum fluctuations, and atomistic machine learning. Our developments will bridge the efficiency of force fields with the accuracy of quantum mechanics, enabling simulations of large realistic systems with predictive power that is not achievable at this moment.