Condensed Phase Simulations Research Articles

Balancing Group I Monatomic Ion-Polar Compound Interactions for Condensed Phase Simulation in the Polarizable Drude Force Field.

Molecular dynamics (MD) simulations are a commonly used method for investigating molecular behavior at the atomic level. Achieving reliable MD simulation results necessitates the use of an accurate force field. In the present work, we present a protocol to enhance the quality of group 1 monatomic ions (specifically Li+, Na+, K+, Rb+, and Cs+) with respect to their interactions with common polar model compounds in biomolecules in condensed phases in the context of the Drude polarizable force field. Instead of adjusting preexisting individual parameters for ions, model compounds, and water, we employ atom-pair specific Lennard-Jones (LJ) (known as NBFIX in CHARMM) and through-space Thole dipole screening (NBTHOLE) terms to fine-tune the balance of ion-model compound, ion-water, and model compound-water interactions. This involved establishing a protocol for the optimization of NBFIX and NBTHOLE parameters targeting the difference between molecular mechanical (MM) and quantum mechanical (QM) potential energy scans (PES). It is shown that targeting PES involving complexes that include multiple model compounds and/or ions as trimers and tetramers yields parameters that produce condensed phase properties in agreement with experimental data. Validation of this protocol involved the reproduction of experimental thermodynamic benchmarks, including solvation free energies of ions in methanol and N-methylacetamide, osmotic pressures, ionic conductivities, and diffusion coefficients within the condensed phase. These results show the importance of including more complex ion-model compound complexes beyond dimers in the QM target data to account for many-body effects during parameter fitting. The presented parameters represent a significant refinement of the Drude polarizable force field, which will lead to improved accuracy for modeling ion-biomolecular interactions.

Scaling deep learning for materials discovery

Novel functional materials enable fundamental breakthroughs across technological applications from clean energy to information processing1–11. From microchips to batteries and photovoltaics, discovery of inorganic crystals has been bottlenecked by expensive trial-and-error approaches. Concurrently, deep-learning models for language, vision and biology have showcased emergent predictive capabilities with increasing data and computation12–14. Here we show that graph networks trained at scale can reach unprecedented levels of generalization, improving the efficiency of materials discovery by an order of magnitude. Building on 48,000 stable crystals identified in continuing studies15–17, improved efficiency enables the discovery of 2.2 million structures below the current convex hull, many of which escaped previous human chemical intuition. Our work represents an order-of-magnitude expansion in stable materials known to humanity. Stable discoveries that are on the final convex hull will be made available to screen for technological applications, as we demonstrate for layered materials and solid-electrolyte candidates. Of the stable structures, 736 have already been independently experimentally realized. The scale and diversity of hundreds of millions of first-principles calculations also unlock modelling capabilities for downstream applications, leading in particular to highly accurate and robust learned interatomic potentials that can be used in condensed-phase molecular-dynamics simulations and high-fidelity zero-shot prediction of ionic conductivity.

Does a Machine-Learned Potential Perform Better Than an Optimally Tuned Traditional Force Field? A Case Study on Fluorohydrins

We present a comparative study that evaluates the performance of a machine learning potential (ANI-2x), a conventional force field (GAFF), and an optimally tuned GAFF-like force field in the modeling of a set of 10 γ-fluorohydrins that exhibit a complex interplay between intra- and intermolecular interactions in determining conformer stability. To benchmark the performance of each molecular model, we evaluated their energetic, geometric, and sampling accuracies relative to quantum-mechanical data. This benchmark involved conformational analysis both in the gas phase and chloroform solution. We also assessed the performance of the aforementioned molecular models in estimating nuclear spin-spin coupling constants by comparing their predictions to experimental data available in chloroform. The results and discussion presented in this study demonstrate that ANI-2x tends to predict stronger-than-expected hydrogen bonding and overstabilize global minima and shows problems related to inadequate description of dispersion interactions. Furthermore, while ANI-2x is a viable model for modeling in the gas phase, conventional force fields still play an important role, especially for condensed-phase simulations. Overall, this study highlights the strengths and weaknesses of each model, providing guidelines for the use and future development of force fields and machine learning potentials.

Reduction of CO2 with Hydrated Electrons: Ab Initio Computational Studies for Finite-Size Cluster Models.

In the present work, the mechanisms of the reduction of the CO2 molecule with hydrated electrons to the hydroxyl-formyl (HOCO) radical were studied with ab initio computational methods. Hydrated hydronium radicals, H3O(H2O)n (n = 0,3,6), are considered as finite-size models of the hydrated electron in liquid water. The investigation of cluster models allows the application of high-accuracy electronic-structure methods, which are not computationally feasible in condensed-phase simulations. Reaction paths and potential-energy (PE) profiles of the proton-coupled electron-transfer reaction from hydrated H3O radicals to the CO2 molecule were explored on the ground-state PE surface. The computationally efficient unrestricted second-order Møller-Plesset method is employed, and its accuracy has been carefully benchmarked in comparison with complete-active-space self-consistent-field and multi-reference second-order perturbation calculations. The results provide insights into the interplay of electron transfer from the diffuse Rydberg-type unpaired electron of H3O to the CO2 molecule, the contraction of the electron cloud by the re-hybridization of the carbon atom of CO2, and proton transfer from the nearest water molecule to the CO2- anion, followed by Grotthus-type proton rearrangements to form stable clusters. Starting from local energy minima of hydrogen-bonded CO2-H3O(H2O)n complexes, the reaction to form HOCO-(H2O)n+1 complexes is exothermic by about 1.3 eV (125 kJ/mol). The reaction is barrier controlled with a barrier of the order of a few tenths of an electron volt, depending on size and conformation of the water cluster. This barrier is at least an order of magnitude lower than the barrier of the reaction of CO2 with any closed-shell partner molecule. The HOCO radicals can recombine by H-atom transfer (disproportionation), resulting in formic acid or a dihydroxycarbene product, as well as by the formation of a C-C bond, resulting in oxalic acid. The strong exothermicity of these radical-radical recombination reactions likely results in the fragmentation of the closed-shell products formic acid and oxalic acid, which explains the strong specificity for CO formation observed in recent experiments of Hamers and co-workers.

Multiscale simulations of TDP-43 full-length uncover molecular determinants of its phase separation beyond N/C-terminal oligomerization.

TAR DNA-binding protein 43 (TDP-43) is a multidomain protein involved in the regulation of RNA processing, and its aggregates have been observed in neurodegenerative diseases, including amyotrophic lateral sclerosis and frontotemporal dementia. TDP-43 is composed of a well-folded N-terminal domain (NTD), two RNA recognition motifs (RRM1/2), an intrinsically disordered C-terminal domain (CTD), and short flexible linkers between folded domains. Recently, TDP-43 has been shown to undergo liquid-liquid phase separation (LLPS) to form membraneless compartments referred to as biomolecular condensates. While NTD oligomerization was shown to promote the phase separation of full-length TDP-43 strongly, CTD can also undergo LLPS on its own. However, the complete picture of domain-level intermolecular interactions of full-length TDP-43 within the biological condensates has remained unclear due to the challenges associated with its purification. Here, we utilize a multiscale simulation approach to get molecular-level insights into the role of interdomain interactions in TDP-43 phase separation. Atomistic, single-chain simulations show that interdomain contacts are mediated by electrostatic interactions. Our coarse-grained, condensed phase simulations also reveal that electrostatic interactions involving RRM/NTD-linker modulate the phase separation of TDP-43, in addition to the NTD/CTD-oligomerization. These findings should pave the way for a greater understanding of molecular determinants of TDP-43 phase separation.

Hydrophobic residues in disordered and helical regions mediate the oligomerization and phase separation of TDP-43 C-terminal domain.

TAR DNA binding protein 43 (TDP-43) is a nuclear, multidomain protein implicated in RNA metabolism. The cytoplasmic accumulation of TDP-43 can result in the formation of inclusion bodies which are a hallmark of neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The prion-like, disordered C-terminal domain (CTD) of TDP-43 (spanning residues 267-414) is aggregation-prone and harbors the majority (∼90%) of all ALS-related mutations. Several studies report that CTD can undergo liquid-liquid phase separation (LLPS). The conserved, hydrophobic region (CR, spanning residues 319-341) in CTD populates an α-helical structure which is essential for phase separation. The requirement of CR for phase separation is attributed to its tendency to undergo helix-helix self-association and promote oligomerization. In addition to CR, aromatic residues in the flanking disordered regions (IDR1/2) also play a critical role in CTD self-assembly. However, the relative contributions of critical residue types in CR and flanking regions on the overall phase separation propensity of CTD are unclear. Here, we utilized multiscale simulations coupled with biophysical experiments to determine the role of hydrophobic residues in the CR and IDR1/2 regions on CTD phase separation. Single chain and condensed phase simulations collectively identified the contribution of aromatic residues while also suggesting significant contributions to LLPS by other residue types, which were previously not recognized as essential for phase separation within and outside the CR region. The computational observations were successfully corroborated by in vitro microscopy and saturation concentration measurements. Finally, NMR experiments determined that CTD oligomerization was critically dependent on these residues within CR and IDR1/2 regions. Overall, our work uncovers the collective importance of hydrophobic residues across both helical and disordered regions in modulating the oligomerization and phase separation of CTD.

Greater transferability and accuracy of norm-conserving pseudopotentials using nonlinear core corrections.

We present an investigation into the transferability of pseudopotentials (PPs) with a nonlinear core correction (NLCC) using the Goedecker, Teter, and Hutter (GTH) protocol across a range of pure GGA, meta-GGA and hybrid functionals, and their impact on thermochemical and non-thermochemical properties. The GTH-NLCC PP for the PBE density functional demonstrates remarkable transferability to the PBE0 and ωB97X-V exchange-correlation functionals, and relative to no NLCC, improves agreement significantly for thermochemical benchmarks compared to all-electron calculations. On the other hand, the B97M-rV meta-GGA functional performs poorly with the PBE-derived GTH-NLCC PP, which is mitigated by reoptimizing the NLCC parameters for this specific functional. The findings reveal that atomization energies exhibit the greatest improvements from use of the NLCC, which thus provides an important correction needed for covalent interactions relevant to applications involving chemical reactivity. Finally we test the NLCC-GTH PPs when combined with medium-size TZV2P molecularly optimized (MOLOPT) basis sets which are typically utilized in condensed phase simulations, and show that they lead to consistently good results when compared to all-electron calculations for atomization energies, ionization potentials, barrier heights, and non-covalent interactions, but lead to somewhat larger errors for electron affinities.

A transferable double exponential potential for condensed phase simulations of small molecules.

The Lennard-Jones potential is the most widely-used function for the description of non-bonded interactions in transferable force fields for the condensed phase. This is not because it has an optimal functional form, but rather it is a legacy resulting from when computational expense was a major consideration and this potential was particularly convenient numerically. At present, it persists because the effort that would be required to re-write molecular modelling software and train new force fields has, until now, been prohibitive. Here, we present Smirnoff-plugins as a flexible framework to extend the Open Force Field software stack to allow custom force field functional forms. We deploy Smirnoff-plugins with the automated Open Force Field infrastructure to train a transferable, small molecule force field based on the recently-proposed double exponential functional form, on over 1000 experimental condensed phase properties. Extensive testing of the resulting force field shows improvements in transfer free energies, with acceptable conformational energetics, run times and convergence properties compared to state-of-the-art Lennard-Jones based force fields.

(Invited) Simulating Dynamic Excitons Via Quantum Molecular Dynamics: A Case Study in Lead Halide Perovskites

The ultrafast electronic and structural dynamics invoked by photoexcitation, i.e., “dynamic exciton” phenomena, not only are important in the context of practical applications such as solar cells, but also raise many questions from the viewpoint of fundamental science. Experimental measurement, computational simulations, and theoretical interpretation will be the three pillars for deciphering the dynamic exciton phenomena.From the viewpoint of computational simulations, molecular dynamics (MD) techniques combined with quantum chemical calculations, i.e., quantum molecular dynamics (QMD), has been the popular tool to simulate the dynamic exciton phenomena. The quantum chemical calculations, which are typically conducted on the basis of the density-functional theory (DFT), require the large computational resources and time. These have been the limiting factors for the accessible spatial and time scales by the QMD simulations.To extend the coverage of simulations to more complex, large-scale systems, we have developed efficient excited-state QMD methods that can include nonadiabatic effects. Our method combines the density-functional tight binding (DFTB) method, which is an approximate DFT, and the surface hopping method, which is a theoretical framework to incorporate the nonadiabatic effects into the QMD simulations. The method was further improved to be suitable for condensed-phase simulations explicitly including the environment, i.e., solvent, by using a “divide-and-conquer” style quantum chemical calculation technique. These theoretical framework enables us to simulate the coupled electronic–structural dynamics in excited states of systems consisting of 102–103 atoms[1,2,3].In addition, using the developed method, we conducted the real-time simulations of the ultrafast processes invoked by photoexcitation of lead iodide perovskites, which are known as the key materials for perovskite solar cells. The dissociation of the exciton into the positive and negative charge carriers was observed. Moreover, the hot carrier cooling, where the charge carriers dissipate excess energy via the electron–phonon coupling and relax to the band edges, was also tracked. Finally, the direct evidence of the polaron formation, where the structural deformation is induced by the presence of charge carriers, was observed. These results highlight the importance of the coupling between electronic and structural degrees of freedom.In the talk, recent improvements in the methodology and future perspectives will also be presented[5].

Implementation and Validation of Constrained Density Functional Theory Forces in the CP2K Package.

Constrained density functional theory (CDFT) is a powerful tool for the prediction of electron transfer parameters in condensed phase simulations at a reasonable computational cost. In this work we present an extension to CDFT in the popular mixed Gaussian/plane wave electronic structure package CP2K, implementing the additional force terms arising from a constraint based on Hirshfeld charge partitioning. This improves upon the existing Becke partitioning scheme, which is prone to give unphysical atomic charges. We verify this implementation for a variety of systems: electron transfer in (H2O)2+ in a vacuum, electron tunnelling between oxygen vacancy centers in solid MgO, and electron self-exchange in aqueous Ru2+–Ru3+. We find good agreement with previous plane-wave CDFT results for the same systems, but at a significantly lower computational cost, and we discuss the general reliability of condensed phase CDFT calculations.

Minimal Active Space for Diradicals Using Multistate Density Functional Theory.

This work explores the electronic structure as well as the reactivity of singlet diradicals, making use of multistate density functional theory (MSDFT). In particular, we show that a minimal active space of two electrons in two orbitals is adequate to treat the relative energies of the singlet and triplet adiabatic ground state as well as the first singlet excited state in many cases. This is plausible because dynamic correlation is included in the first place in the optimization of orbitals in each determinant state via block-localized Kohn–Sham density functional theory. In addition, molecular fragment, i.e., block-localized Kohn–Sham orbitals, are optimized separately for each determinant, providing a variational diabatic representation of valence bond-like states, which are subsequently used in nonorthogonal state interactions (NOSIs). The computational procedure and its performance are illustrated on some prototypical diradical species. It is shown that NOSI calculations in MSDFT can be used to model bond dissociation and hydrogen-atom transfer reactions, employing a minimal number of configuration state functions as the basis states. For p- and s-types of diradicals, the closed-shell diradicals are found to be more reactive than the open-shell ones due to a larger diabatic coupling with the final product state. Such a diabatic representation may be useful to define reaction coordinates for electron transfer, proton transfer and coupled electron and proton transfer reactions in condensed-phase simulations.

Enhancing the Accuracy of Ab Initio Molecular Dynamics by Fine Tuning of Effective Two-Body Interactions: Acetonitrile as a Test Case.

Grimme's dispersion-corrected density functional theory (DFT-D) methods have emerged among the most practical approaches to perform accurate quantum mechanical calculations on molecular systems ranging from small clusters to microscopic and mesoscopic samples, i.e., including hundreds or thousands of molecules. Moreover, DFT-D functionals can be easily integrated into popular ab initio molecular dynamics (MD) software packages to carry out first-principles condensed-phase simulations at an affordable computational cost. Here, starting from the well-established D3 version of the dispersion-correction term, we present a simple protocol to improve the accurate description of the intermolecular interactions of molecular clusters of growing size, considering acetonitrile as a test case. Optimization of the interaction energy was performed with reference to diffusion quantum Monte Carlo calculations, successfully reaching the same inherent accuracy of the latter (statistical error of ∼0.1 kcal/mol per molecule). The refined DFT-D3 model was then used to perform ab initio MD simulations of liquid acetonitrile, again showing significant improvements toward available experimental data with respect to the default correction.

Physics-based, neural network force fields for reactive molecular dynamics: Investigation of carbene formation from [EMIM+][OAc-

Reactive molecular dynamics simulations enable a detailed understanding of solvent effects on chemical reaction mechanisms and reaction rates. While classical molecular dynamics using reactive force fields allows significantly longer simulation time scales and larger system sizes compared with ab initio molecular dynamics, constructing reactive force fields is a difficult and complex task. In this work, we describe a general approach following the empirical valence bond framework for constructing ab initio reactive force fields for condensed phase simulations by combining physics-based methods with neural networks (PB/NNs). The physics-based terms ensure the correct asymptotic behavior of electrostatic, polarization, and dispersion interactions and are compatible with existing solvent force fields. NNs are utilized for a versatile description of short-range orbital interactions within the transition state region and accurate rendering of vibrational motion of the reacting complex. We demonstrate our methodology for a simple deprotonation reaction of the 1-ethyl-3-methylimidazolium cation with acetate to form 1-ethyl-3-methylimidazol-2-ylidene and acetic acid. Our PB/NN force field exhibits ∼1 kJ mol-1 mean absolute error accuracy within the transition state region for the gas-phase complex. To characterize the solvent modulation of the reaction profile, we compute potentials of mean force for the gas-phase reaction as well as the reaction within a four-ion cluster and benchmark against ab initio molecular dynamics simulations. We find that the surrounding ionic environment significantly destabilizes the formation of the carbene product, and we show that this effect is accurately captured by the reactive force field. By construction, the PB/NN potential may be directly employed for simulations of other solvents/chemical environments without additional parameterization.

Exploring Free Energy Profiles of Enantioselective Organocatalytic Aldol Reactions under Full Solvent Influence.

We present a computational study on the enantioselectivity of organocatalytic proline-catalyzed aldol reactions between aldehydes in dimethylformamide (DMF). To explore the free energy surface of the reaction, we apply two-dimensional metadynamics on top of ab initio molecular dynamics (AIMD) simulations with explicit solvent description on the DFT level of theory. We avoid unwanted side reactions by utilizing our newly developed hybrid AIMD (HyAIMD) simulation scheme, which adds a simple force field to the AIMD simulation to prevent unwanted bond breaking and formation. Our condensed phase simulation results are able to nicely reproduce the experimental findings, including the main stereoisomer that is formed, and give a correct qualitative prediction of the change in syn:anti product ratio with different substituents. Furthermore, we give a microscopic explanation for the selectivity. We show that both the explicit description of the solvent and the inclusion of entropic effects are vital to a good outcome—metadynamics simulations in vacuum and static nudged elastic band (NEB) calculations yield significantly worse predictions when compared to the experiment. The approach described here can be applied to a plethora of other enantioselective or organocatalytic reactions, enabling us to tune the catalyst or determine the solvent with the highest stereoselectivity.

Polarizable Multipolar Molecular Dynamics Using Distributed Point Charges.

Distributed point charge models (DCM) and their minimal variants (MDCM) have been integrated with tools widely used for condensed-phase simulations, including a virial-based barostat and a slow-growth algorithm for thermodynamic integration. Minimal DCM is further developed in a systematic fashion to reduce fitting errors in the electrostatic interaction energy, and a new fragment-based approach offers considerable speedup of the MDCM fitting process for larger molecules with increased numbers of off-centered charged sites. Finally, polarizable (M)DCM is also introduced in the present work. The developments are used in condensed-phase simulations of popular force fields with commonly applied simulation conditions. (M)DCM equivalents for a range of widely used water force fields and for fluorobenzene (PhF) are developed and applied along with the original models to evaluate the impact of reformulating the electrostatic term. Comparisons of the molecular electrostatic potential (MEP), electrostatic interaction energies, and bulk properties from molecular dynamics simulations for a range of models from simple TIPnP (n = 3-5) to the polarizable, multipolar iAMOEBA models for water and an existing quadrupolar model for PhF confirm that DCMs retain the accuracy of the original models, providing a homogeneous, efficient, and generic point charge alternative to a multipolar electrostatic model for force field development and multilevel simulations.

Benchmarking polarizable and non-polarizable force fields for Ca2+-peptides against a comprehensive QM dataset.

Explicit description of atomic polarizability is critical for the accurate treatment of inter-molecular interactions by force fields (FFs) in molecular dynamics (MD) simulations aiming to investigate complex electrostatic environments such as metal-binding sites of metalloproteins. Several models exist to describe key monovalent and divalent cations interacting with proteins. Many of these models have been developed from ion-amino-acid interactions and/or aqueous-phase data on cation solvation. The transferability of these models to cation-protein interactions remains uncertain. Herein, we assess the accuracy of existing FFs by their abilities to reproduce hierarchies of thousands of Ca2+-dipeptide interaction energies based on density-functional theory calculations. We find that the Drude polarizable FF, prior to any parameterization, better approximates the QM interaction energies than any of the non-polarizable FFs. Nevertheless, it required improvement in order to address polarization catastrophes where, at short Ca2+-carboxylate distances, the Drude particle of oxygen overlaps with the divalent cation. To ameliorate this, we identified those conformational properties that produced the poorest prediction of interaction energies to reduce the parameter space for optimization. We then optimized the selected cation-peptide parameters using Boltzmann-weighted fitting and evaluated the resulting parameters in MD simulations of the N-lobe of calmodulin. We also parameterized and evaluated the CTPOL FF, which incorporates charge-transfer and polarization effects in additive FFs. This work shows how QM-driven parameter development, followed by testing in condensed-phase simulations, may yield FFs that can accurately capture the structure and dynamics of ion-protein interactions.

Highly Accurate Prediction of Core Spectra of Molecules at Density Functional Theory Cost: Attaining Sub-electronvolt Error from a Restricted Open-Shell Kohn-Sham Approach.

We present the use of the recently developed square gradient minimization (SGM) algorithm for excited-state orbital optimization to obtain spin-pure restricted open-shell Kohn-Sham (ROKS) energies for core excited states of molecules. The SGM algorithm is robust against variational collapse and offers a reliable route to converging orbitals for target excited states at only 2-3 times the cost of ground-state orbital optimization (per iteration). ROKS/SGM with the modern SCAN/ωB97X-V functionals is found to predict the K-edge of C, N, O, and F to a root mean squared error of ∼0.3 eV. ROKS/SGM is equally effective at predicting L-edge spectra of third period elements, provided a perturbative spin-orbit correction is employed. This high accuracy can be contrasted with traditional time-dependent density functional theory (TDDFT), which typically has greater than 10 eV error and requires translation of computed spectra to align with experiment. ROKS is computationally affordable (having the same scaling as ground-state DFT and a slightly larger prefactor) and can be applied to geometry optimizations/ab initio molecular dynamics of core excited states, as well as condensed phase simulations. ROKS can also model doubly excited/ionized states with one broken electron pair, which are beyond the ability of linear response based methods.

The Quest for Accurate Liquid Water Properties from First Principles.

Developing accurate ab initio molecular dynamics (AIMD) models that capture both electronic reorganization and nuclear quantum effects associated with hydrogen bonding is key to quantitative understanding of bulk water and its anomalies as well as its role as a universal solvent. For condensed phase simulations, AIMD has typically relied on the generalized gradient approximation (GGA) of density functional theory (DFT) as the underlying model chemistry for the potential energy surface, with nuclear quantum effects (NQEs) sometimes modeled by performing classical molecular dynamics simulations at elevated temperatures. Here we show that the properties of liquid water obtained from the meta-GGA B97M-rV functional, when evaluated using accelerated path integral molecular dynamics simulations, display accuracy comparable to a computationally expensive dispersion-corrected hybrid functional, revPBE0-D3. We show that the meta-GGA DFT functionalreproduces bulk water properties including radial distribution functions, self-diffusion coefficients, and infrared spectra with comparable accuracy of a much more expensive hybrid functional. This work demonstrates that the underlying quality of a good DFT functional requires evaluation with quantum nuclei and that high-temperature simulations are a poor proxy for properly treating NQEs.

Fermi resonance in OH-stretch vibrational spectroscopy of liquid water and the water hexamer.

Vibrational spectroscopy of water contains a wealth of information about the structure and dynamics of this fascinating substance. Theoretical modeling of fundamental vibrational transitions in condensed water has proven difficult, and in many circumstances, one cannot reach even qualitative agreement with experiment. Due to the ability of water to form hydrogen bonds of various strengths, the OH stretching band spans several hundreds of wave numbers in the spectra, overlapping with the first overtone of the HOH bending band and triggering a resonance between these two vibrations. This effect, known as Fermi resonance, has been traditionally ignored in theoretical condensed-phase simulations due to the additional computational burden and its deemed low importance. Depending on a particular molecular environment, the Fermi resonance manifests itself from small spectral features in the spectra of liquid water to pronounced distinct peaks in the spectra of ice and water clusters. The goal of this work is to illustrate the effects of including the Fermi resonance coupling between the bending overtone and stretching fundamental vibrations in the mixed quantum-classical formalism developed by Skinner and co-workers on the IR and Raman spectra of liquid water and the water hexamer. We show that by adding the Fermi resonance coupling, we are able to reproduce the location of the peak and a shoulder on the red side of the IR spectrum as well as the bimodal structure of the polarized Raman spectrum of liquid water at 300 K. Very good agreement between theory and experiment is achieved for the IR spectra of the water hexamer as well. We suggest that the Fermi resonance should not be ignored if intricate features of spectra are of interest. In spite of these promising results obtained in the region of a spectrum where Fermi resonance is important, further development of spectroscopic maps is needed to improve agreement with the experiment outside of the frequency range affected by the Fermi resonance.

Mapping the Drude polarizable force field onto a multipole and induced dipole model.

The induced dipole and the classical Drude oscillator represent two major approaches for the explicit inclusion of electronic polarizability into force field-based molecular modeling and simulations. In this work, we explore the equivalency of these two models by comparing condensed phase properties computed using the Drude force field and a multipole and induced dipole (MPID) model. Presented is an approach to map the electrostatic model optimized in the context of the Drude force field onto the MPID model. Condensed phase simulations on water and 15 small model compounds show that without any reparametrization, the MPID model yields properties similar to the Drude force field with both models yielding satisfactory reproduction of a range of experimental values and quantum mechanical data. Our results illustrate that the Drude oscillator model and the point induced dipole model are different representations of essentially the same physical model. However, results indicate the presence of small differences between the use of atomic multipoles and off-center charge sites. Additionally, results on the use of dispersion particle mesh Ewald further support its utility for treating long-range Lennard Jones dispersion contributions in the context of polarizable force fields. The main motivation in demonstrating the transferability of parameters between the Drude and MPID models is that the more than 15 years of development of the Drude polarizable force field can now be used with MPID formalism without the need for dual-thermostat integrators nor self-consistent iterations. This opens up a wide range of new methodological opportunities for polarizable models.