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DOE OSTI2022

A Hybrid Quantum–Classical Study of Ion Adsorption at the Copper Electrode

Here, we present a set of computational studies that surveys the molecular structure and thermodynamics of simple ions at the electrode–electrolyte interface. A hybrid quantum–classical approach is used to obtain free energy profiles and solvent structure as a function of the ion’s position relative to the electrochemical liquid/solid interface and system potential. Model systems consist of a copper electrode and single halide or alkali metal ion in contact with an implicit solvent and reveal new insights into the interplay of forces that drive or resist ion absorption at the electrode/ electrolyte interface. We also expand on subtleties of absorption site preference and describe the complex relationship between the energetic barrier to absorption and the ion–electrode binding energy as a function of electrode potential.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Explicit solvent machine-learned coarse-grained model of sodium polystyrene sulfonate to capture polymer structure and dynamics

In this article, strongly charged polyelectrolytes (PEs) demonstrate complex solution behavior as a function of chain length, concentrations, and ionic strength. The viscosity behavior is important to understand and is a core quantity for many applications, but aspects remain a challenge. Molecular dynamics simulations using implicit solvent coarse-grained (CG) models successfully reproduce structure, but are often inappropriate for calculating viscosities. To address the need for CG models which reproduce viscoelastic properties of one of the most studied PEs, sodium polystyrene sulfonate (NaPSS), we report our recent efforts in using Bayesian optimization to develop CG models of NaPSS which capture both polymer structure and dynamics in aqueous solutions with explicit solvent. We demonstrate that our explicit solvent CG NaPSS model with the ML-BOP water model [Chan et al. Nat Commun 10, 379 (2019)] quantitatively reproduces NaPSS chain statistics and solution structure. The new explicit solvent CG model is benchmarked against diffusivities from atomistic simulations and experimental specific viscosities for short chains. We also show that our Bayesian-optimized CG model is transferable to larger chain lengths across a range of concentrations. Overall, this work provides a machine-learned model to probe the structural, dynamic, and rheological properties of polyelectrolytes such as NaPSS and aids in the design of novel, strongly charged polymers with tunable structural and viscoelastic properties

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2014

Solvent friction effects propagate over the entire protein molecule through low-frequency collective modes

Protein solvation dynamics has been investigated using atom-dependent Langevin friction coefficients derived directly from molecular dynamics (MD) simulations. To determine the effect of solvation on the atomic friction coefficients, solution and vacuum MD simulations were performed for lysozyme and staphylococcal nuclease and analyzed by Langevin mode analysis. The coefficients thus derived are roughly correlated with the atomic solvent-accessible surface area (ASA), as expected from the fact that friction occurs as the result of collisions with solvent molecules. However, a considerable number of atoms with higher friction coefficients are found inside the core region. Hence, the influence of solvent friction propagates into the protein core. The internal coefficients have large contributions from the low-frequency modes, yielding a simple picture of the surface-to-core long-range damping via solvation governed by collective low-frequency modes. To make use of these findings in implicit-solvent modeling, we compare the all-atom friction results with those obtained using Langevin dynamics (LD) with two empirical representations: the constant-friction and the ASA-dependent (Pastor Karplus) friction models. The constant-friction model overestimates the core and underestimates the surface damping whereas the ASA-dependent friction model, which damps protein atoms only on the solvent-accessible surface, reproduces well the friction coefficients for both the surface and core regions observed in the explicit-solvent MD simulations. Furthermore, in LD simulation, the solvent friction coefficients should be imposed only on the protein surface.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Atomic Radius and Charge Parameter Uncertainty in Biomolecular Solvation Energy Calculations

Atomic radii and charges are two major parameters used in implicit solvent electrostatics and energy calculations. The optimization problem for charges and radii is under-determined, leading to uncertainty in the values of these parameters and in the results of solvation energy calculations using these parameters. This paper presents a method for quantifying this uncertainty in solvation energies using surrogate models based on generalized polynomial chaos (gPC) expansions. There are relatively few atom types used to specify radii parameters in implicit solvation calculations; therefore, surrogate models for these low-dimensional spaces could be constructed using least-squares fitting. However, there are many more types of atomic charges; therefore, construction of surrogate models for the charge parameter space required compressed sensing combined with an iterative rotation method to enhance problem sparsity. We present results for the uncertainty in small molecule solvation energies based on these approaches. Additionally, we explore the correlation between uncertainties due to radii and charges which motivates the need for future work in uncertainty quantification methods for high-dimensional parameter spaces.

Yang, Xiu↗

DOE OSTI2023

Solvent Phase Optimizations Improve Correlations with Experimental Stability Constants for Aqueous Lanthanide Complexes

Stability constants provide insight into ion complexation in water. While computational studies have been shown to model the energy of the complexation successfully using a thermodynamic cycle approach, it does not extend to calculating the stability constants for 1:1 lanthanide to ligand complexes in solution. Using B3LYP and 6-31+G* Pople basis with small core effective core potential (ECP) on the lanthanum ion, and a solvent model based on the full solute electron density (SMD) solvation model we computed and compared with previously published stability constants of the ligands: acetate, acetohydroximate, acetylacetonate, methanoate, tropolonate, hydroxide, catecholate, malonate, oxalate, phthalate, and sulfate. The best R 2 values for the thermodynamic cycle can only be determined by separating the mono and divalent ions to achieve an R 2 value of 0.86 and 0.74 for mono and divalent ions, respectively. We show that by optimizing the lanthanide-ligand structures in implicit solvent, we achieve an improved correlation between experimental and computed stability constants of R 2 value of 0.89 for the combined mono and divalent ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

An automated framework for NMR chemical shift calculations of small organic molecules

When using nuclear magnetic resonance (NMR) to assist in chemical identification in complex samples, researchers commonly rely on databases for chemical shift spectra. However, authentic standards are typically depended upon to build libraries experimentally. Considering complex biological samples, such as blood and soil, the entirety of NMR spectra required for all possible compounds would be infeasible to ascertain due to limitations of available standards and experimental processing time. As an alternative, we introduce the in silico Chemical Library Engine (ISiCLE) NMR chemical shift module to accurately and automatically calculate NMR chemical shifts of small organic molecules through use of quantum chemical calculations. ISiCLE performs density functional theory (DFT)-based calculations for predicting chemical properties - specifically NMR chemical shifts in this manuscript - via the open source, high-performance omputational chemistry software, NWChem. ISiCLE calculates the NMR chemical shifts of sets of molecules using any available combination of DFT method, solvent, and NMR-active nuclei, using both user-selected reference compounds and/or linear regression methods. Calculated NMR chemical shifts are provided to the user for each molecule, along with comparisons with respect to a number of metrics commonly used in the literature. Here, we demonstrate ISiCLE using a set of 312 molecules, ranging in size up to 90 carbon atoms. For each, calculation of NMR chemical shifts have been performed with 8 different levels of DFT theory, and with solvation effects using the implicit solvent Conductor-like Screening Model (COSMO). The DFT method dependence of the calculated chemical shifts have been systematically investigated through benchmarking and subsequently compared to experimental data available in the literature. Furthermore, ISiCLE has been applied to a set of 80 methylcyclohexane conformers, combined via Boltzmann weighting and compared to experimental values. We demonstrate that our protocol shows promise in the automation of chemical shift calculations and, ultimately, the expansion of chemical shift libraries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Iterative derivation of effective potentials to sample the conformational space of proteins at atomistic scale

The current capacity of computers makes it possible to perform simulations of small systems with portable, explicit-solvent potentials achieving high degree of accuracy. However, simplified models must be employed to exploit the behavior of large systems or to perform systematic scans of smaller systems. While powerful algorithms are available to facilitate the sampling of the conformational space, successful applications of such models are hindered by the availability of simple enough potentials able to satisfactorily reproduce known properties of the system. We develop an interatomic potential to account for a number of properties of proteins in a computationally economic way. The potential is defined within an all-atom, implicit solvent model by contact functions between the different atom types. The associated numerical values can be optimized by an iterative Monte Carlo scheme on any available experimental data, provided that they are expressible as thermal averages of some conformational properties. We test this model on three different proteins, for which we also perform a scan of all possible point mutations with explicit conformational sampling. The resulting models, optimized solely on a subset of native distances, not only reproduce the native conformations within a few Angstroms from the experimental ones, but show the cooperative transition between native and denatured state and correctly predict the measured free-energy changes associated with point mutations. Moreover, differently from other structure-based models, our method leaves a residual degree of frustration, which is known to be present in protein molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Explicit ions/implicit water generalized Born model for nucleic acids

>The ion atmosphere around highly charged nucleic acid molecules plays a significant role in their dynamics, structure, and interactions. Here we utilized the implicit solvent framework to develop a model for the explicit treatment of ions interacting with nucleic acid molecules. The proposed explicit ions/implicit water model is based on a significantly modified generalized Born (GB) model and utilizes a non-standard approach to define the solute/solvent dielectric boundary. Specifically, the model includes modifications to the GB interaction terms for the case of multiple interacting solutes—disconnected dielectric boundary around the solute-ion or ion-ion pairs. A fully analytical description of all energy components for charge-charge interactions is provided. The effectiveness of the approach is demonstrated by calculating the potential of mean force for Na + –Cl – ion pair and by carrying out a set of Monte Carlo (MC) simulations of mono- and trivalent ions interacting with DNA and RNA duplexes. We report the monovalent (Na + ) and trivalent (CoHex 3+ ) counterion distributions predicted by the model are in close quantitative agreement with all-atom explicit water molecular dynamics simulations used as reference. Expressed in the units of energy, the maximum deviations of local ion concentrations from the reference are within k B T . The proposed explicit ions/implicit water GB model is able to resolve subtle features and differences of CoHex distributions around DNA and RNA duplexes. These features include preferential CoHex binding inside the major groove of the RNA duplex, in contrast to CoHex biding at the “external” surface of the sugar-phosphate backbone of the DNA duplex; these differences in the counterion binding patters were earlier shown to be responsible for the observed drastic differences in condensation propensities between short DNA and RNA duplexes. MC simulations of CoHex ions interacting with the homopolymeric poly(dA·dT) DNA duplex with modified (de-methylated) and native thymine bases are used to explore the physics behind CoHex-thymine interactions. The simulations suggest that the ion desolvation penalty due to proximity to the low dielectric volume of the methyl group can contribute significantly to CoHex-thymine interactions. Compared to the steric repulsion between the ion and the methyl group, the desolvation penalty interaction has a longer range and may be important to consider in the context of methylation effects on DNA condensation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

An interoperable implementation of collective‐variable based enhanced sampling methods in extended phase space within the OpenMM package

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. Here, in this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Multiscale simulations reveal TDP-43 molecular-level interactions driving condensation

The RNA-binding protein TDP-43 is associated with mRNA processing and transport from the nucleus to the cytoplasm. TDP-43 localizes in the nucleus as well as accumulating in cytoplasmic condensates such as stress granules. Aggregation and formation of amyloid-like fibrils of cytoplasmic TDP-43 are hallmarks of numerous neurodegenerative diseases, most strikingly present in >90% of amyotrophic lateral sclerosis (ALS) patients. If excessive accumulation of cytoplasmic TDP-43 causes, or is caused by, neurodegeneration is presently not known. In this work, we use molecular dynamics simulations at multiple resolutions to explore TDP-43 self- and cross-interaction dynamics. A full-length molecular model of TDP-43, all 414 amino acids, was constructed from select structures of the protein functional domains (N-terminal domain, and two RNA recognition motifs, RRM1 and RRM2) and modeling of disordered connecting loops and the low complexity glycine-rich C-terminus domain. All-atom CHARMM36m simulations of single TDP-43 proteins served as guides to construct a coarse-grained Martini 3 model of TDP-43. The Martini model and a coarser implicit solvent Cα model, optimized for disordered proteins, were subsequently used to probe TDP-43 interactions; self-interactions from single-chain full-length TDP-43 simulations, cross-interactions from simulations with two proteins and simulations with assemblies of dozens to hundreds of proteins. Our findings illustrate the utility of different modeling scales for accessing TDP-43 molecular-level interactions and suggest that TDP-43 has numerous interaction preferences or patterns, exhibiting an overall strong, but dynamic, association and driving the formation of biomolecular condensates.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Elucidating the Impact of Cis – Trans Organic Structure Directing Agent Isomer Ratios on the Aluminum Distribution Within SSZ-39

Despite their widespread use, the mechanisms governing the synthesis of zeolite catalysts are still poorly understood. A notable example of this problem is the uncertainty surrounding the influence of synthesis conditions on the placement of Al atoms in the zeolite framework which determines the active sites available for catalytic species. In this work, the role of the cis to trans isomer ratio of the OSDA N,N-dimethyl-3-5-dimethylpiperidinium on the energetics of 26 distinct Al pair distributions in SSZ-39 is examined both in the presence and absence of Na using density functional theory calculations. The initial orientation of the OSDA was found to have a significant impact on the final energies present, necessitating the screening of a large number of initial orientations with force field calculations and single point DFT calculations. Ground state energies were found to vary significantly with the ratio of cis to trans OSDAs with a Boltzmann distribution revealing the most likely Al pair distributions shift from sharing the same 8 membered rings to sharing the same double six membered rings to having no shared subunits as one increases the amount of cis OSDA present within the framework. The presence of Na was found to favor Al pair distributions where both Als occupied the same 6-membered ring. When an implicit solvent model was used to evaluate ground state energies the ideal Na sites shifted from 6-membered rings to empty SSZ-39 cages while OSDA positions and orientations remained largely the same. To provide insight on how kinetic factors may influence Al distributions, formation energies we calculated for connected double six membered rings. Further, these formation energies revealed a preference for Al pairs to occupy the same 4-membered ring which indicates kinetic and thermodynamic control may lead to different Al distributions in SSZ-39.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Stability Analysis of Substituted Cobaltocenium [Bis(cyclopentadienyl)cobalt(III)] Employing Chemistry-Informed Neural Networks

Cobaltocenium derivatives are promising components of the anion exchange membranes due to their excellent thermal and alkaline stability under the operating conditions of a fuel cell. Here we present an efficient modeling approach of assessing the chemical stability of substituted cobaltocenium CoCp 2 + based on the computed electronic structure enhanced by machine learning techniques. Within the aqueous environment, the positive charge of the metal cation is balanced by the hydroxide anion through formation of the CoCp 2 + OH¯ complexes, whose dissociation is studied within the implicit solvent employing density functional theory. The data set of about 118 species based on 42 substituent groups characterized by a range of electron- donating (ED) and electron-withdrawing (EW) properties is constructed and analyzed. Given 12 carefully chosen chemistry-informed descriptors of the complexes and relevant fragments, the stability of the complexes is found to strongly correlate with the energies of the highest occupied and lowest unoccupied molecular orbitals, modulated by a switching function of the Hirshfeld charge. The latter is used as a measure of the electron withdrawing-donating character of the substituents. Based on this observation from the conventional regression analysis, two fully connected, feed-forward neural network (FNN) models with different unit structures, called the chemistry-informed (CINN) and the quadratic (QNN) neural networks, are developed. Both models predict the bond dissociation energies of the cobaltocenium complexes with mean relative errors less than 5.40% and average absolute errors less than 0.94 kcal/mol. The results show the potential of QNN to efficiently capture more complex relationships. Here, the concept of incorporating the domain (chemical) knowledge/insight into the neural network structure paves the way to applications of machine learning techniques with small data sets, ultimately leading to better predictive models compared to the conventional regression analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Improved Treatment of 1–4 Interactions in Force Fields for Molecular Dynamics Simulations

Traditional force fields commonly use a combination of bonded torsional terms and empirically scaled nonbonded interactions to capture 1-4 energies and forces of atoms separated by three bonds in a molecule. While this approach can yield accurate torsional energy barriers, it often leads to inaccurate forces and erroneous geometries and creates an interdependence between dihedral terms and nonbonded interactions, complicating parametrization and reducing transferability. Here, in this paper, we demonstrate that 1-4 interactions can be accurately modeled using only bonded coupling terms, eliminating the need for arbitrarily scaled nonbonded interactions altogether. Furthermore, by leveraging the automated parametrization capabilities of the Q-Force toolkit, we efficiently determine the necessary coupling terms without the need for manual adjustment. Our approach is first validated on a range of small molecule systems, encompassing both flexible and rigid structures, and shows a significant improvement in force field accuracy, obtaining subkcal/mol mean absolute error for every molecule tested. We further extend the bonded-only model for 1-4 interactions to Amber ff14sb, CHARMM36, and OPLS-AA force fields to reproduce ab initio gas and implicit solvent ϕ,ψ surfaces of alanine dipeptide.

Abdullah, Aalim S. [University of California, Berk↗

DOE OSTI2016

Implementation of INDO/SCI with COSMO Implicit Solvation and Benchmarking for Solvatochromic Shifts

Accurate and rapid quantum mechanical prediction of solvatochromic shifts, particularly in systems where charge transfer plays a significant role, is important for many aspects of molecular and material design. Although the semiempirical INDO/SCI approach is computationally efficient and performs well for charge-transfer states, the availability of implicit solvent approaches has been limited. As such, we implement the COSMO solvent model with a perturbative state-specific correction to the excited-state energies with the INDO/SCI method. We show that for a series of prototypical π-conjugated molecules, our newly implemented INDO/SCI/COSMO model yields more accurate absorption energies and comparably accurate solvatochromic shifts to those computed using TD-ωB97XD and CIS with COSMO solvation at a substantially lower computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Electronic Origin and Kinetic Feasibility of the Lattice Oxygen Participation During the Oxygen Evolution Reaction on Perovskites

Density functional theory is employed to investigate the electronic origin and feasibility of surface lattice oxygen (O surf ) participation during the oxygen evolution reaction (OER) on perovskites. O surf participation occurs via the nonelectrochemical pathway in which adsorbed atomic oxygen (O*) diffuses from the transition-metal site to the oxygen site, and then O surf shifts out of the surface plane to react with O* to form O surf –O* and a surface oxygen vacancy. The different thermodynamic driving forces of O surf participation on LaMO 3-δ (M = Ni, Co, and Cu) are explained by the changes in the oxidation state of the transition-metal site throughout the reaction. We show that Osurf participation on LaNiO 3 cannot be hindered by Osurf protonation in the OER potential range. By including the coverage effect and utilizing the implicit solvent model, we finally show that lattice oxygen mechanism is more feasible than the conventional mechanism for OER on LaNiO 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Influence of Charge Block Length on Conformation and Solution Behavior of Polyampholytes

In this paper, we investigate the effect of charge block length on polyampholyte chain conformation and phase behavior using small-angle X-ray scattering (SAXS) and implicit-solvent molecular simulations. To this end, we use solid phase peptide synthesis to precision-tailor a series of polyampholytes consisting of l-glutamic acid (E) and l-lysine (K) monomers arranged in alternating blocks from 2 to 16 monomers. We observe that the polyampholytes tend to phase separate as block size increases. With addition of NaCl, phase separated polyampholytes exhibit a salting-in effect dependent on charge block length. Fourier-transform infrared (FTIR) spectroscopy reveals the presence of intramolecular hydrogen bonds that are disrupted upon the addition of NaCl, implicating both electrostatic interactions and hydrogen bonding in the phase behavior. SAXS spectra at no-added salt conditions show minimal dependence of charge block length on the radius of gyration (R g ) for soluble polyampholytes, but local chain stiffening is found to be dependent on charge block length. With increasing NaCl, consistent with electrostatic screening, all polyampholytes expand and behave as neutral or swollen chains in good solvent conditions. Molecular simulations are qualitatively consistent with experiments. Implications for understanding intracellular condensates and material design are noted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Electric Double-Layer Structure in Primitive Model Electrolytes. Comparing Molecular Dynamics with Local-Density Approximations

We evaluate the accuracy of local-density approximations (LDAs) using explicit molecular dynamics simulations of binary electrolytes comprised of equisized ions in an implicit solvent. The Bikerman LDA, which considers ions to occupy a lattice, poorly captures excluded volume interactions between primitive model ions. Instead, LDAs based on the Carnahan–Starling (CS) hard-sphere equation of state capture simulated values of ideal and excess chemical potential profiles extremely well, as is the relationship between surface charge density and electrostatic potential. Excellent agreement between the EDL capacitances predicted by CS-LDAs and computed in molecular simulations is found even in systems where ion correlations drive strong density and free charge oscillations within the EDL, despite the inability of LDAs to capture the oscillations in the detailed EDL profiles.

25 ENERGY STORAGE↗

DOE OSTI2022

Ab initio molecular dynamics free energy study of enhanced copper (II) dimerization on mineral surfaces

Understanding the adsorption of isolated metal cations from water on to mineral surfaces is critical for toxic waste retention and cleanup in the environment. Heterogeneous nucleation of metal oxyhydroxides and other minerals on material surfaces is key to crystal growth and dissolution. The link connecting these two areas, namely cation dimerization and polymerization, is far less understood. In this work we apply ab initio molecular dynamics calculations to examine the coordination structure of hydroxide-bridged Cu(II) dimers, and the free energy changes associated with Cu(II) dimerization on silica surfaces. The dimer dissociation pathway involves sequential breaking of two Cu 2+ -OH – bonds, yielding three local minima in the free energy profiles associated with 0-2 OH – bridges between the metal cations, and requires the design of a (to our knowledge) novel reaction coordinate for the simulations. Cu(II) adsorbed on silica surfaces are found to exhibit stronger tendency towards dimerization than when residing in water. Cluster-plus-implicit-solvent methods yield incorrect trends if OH – hydration is not correctly depicted. The predicted free energy landscapes are consistent with fast equilibrium times (seconds) among adsorbed structures, and favor Cu 2+ dimer formation on silica surfaces over monomer adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗