1
|
Domingues TS, Coifman R, Haji-Akbari A. Estimating Position-Dependent and Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories: Existing Methods and Future Outlook. J Chem Theory Comput 2024; 20:4427-4455. [PMID: 38815171 DOI: 10.1021/acs.jctc.4c00148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Confinement can substantially alter the physicochemical properties of materials by breaking translational isotropy and rendering all physical properties position-dependent. Molecular dynamics (MD) simulations have proven instrumental in characterizing such spatial heterogeneities and probing the impact of confinement on materials' properties. For static properties, this is a straightforward task and can be achieved via simple spatial binning. Such an approach, however, cannot be readily applied to transport coefficients due to lack of natural extensions of autocorrelations used for their calculation in the bulk. The prime example of this challenge is diffusivity, which, in the bulk, can be readily estimated from the particles' mobility statistics, which satisfy the Fokker-Planck equation. Under confinement, however, such statistics will follow the Smoluchowski equation, which lacks a closed-form analytical solution. This brief review explores the rich history of estimating profiles of the diffusivity tensor from MD simulations and discusses various approximate methods and algorithms developed for this purpose. Besides discussing heuristic extensions of bulk methods, we overview more rigorous algorithms, including kernel-based methods, Bayesian approaches, and operator discretization techniques. Additionally, we outline methods based on applying biasing potentials or imposing constraints on tracer particles. Finally, we discuss approaches that estimate diffusivity from mean first passage time or committor probability profiles, a conceptual framework originally developed in the context of collective variable spaces describing rare events in computational chemistry and biology. In summary, this paper offers a concise survey of diverse approaches for estimating diffusivity from MD trajectories, highlighting challenges and opportunities in this area.
Collapse
Affiliation(s)
- Tiago S Domingues
- Department of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut 06520, United States
| | - Ronald Coifman
- Department of Mathematics, Yale University, New Haven, Connecticut 06520, United States
- Department of Computer Science, Yale University, New Haven, Connecticut 06520, United States
| | - Amir Haji-Akbari
- Department of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut 06520, United States
| |
Collapse
|
2
|
Domingues TS, Coifman RR, Haji-Akbari A. Robust Estimation of Position-Dependent Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories. J Phys Chem B 2023; 127:8644-8659. [PMID: 37757480 DOI: 10.1021/acs.jpcb.3c03581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Confinement breaks translational and rotational symmetry in materials and makes all physical properties functions of position. Such spatial variations are key to modulating material properties at the nanoscale, and characterizing them accurately is therefore an intense area of research in the molecular simulations community. This is relatively easy to accomplish for basic mechanical observables. Determining spatial profiles of transport properties, such as diffusivity, is, however, much more challenging, as it requires calculating position-dependent autocorrelations of mechanical observables. In our previous paper (Domingues, T.S.; Coifman, R.; Haji-Akbari, A. J. Phys. Chem. B 2023, 127, 5273 10.1021/acs.jpcb.3c00670), we analytically derive and numerically validate a set of filtered covariance estimators (FCEs) for quantifying spatial variations of the diffusivity tensor from stochastic trajectories. In this work, we adapt these estimators to extract diffusivity profiles from MD trajectories and validate them by applying them to a Lennard-Jones fluid within a slit pore. We find our MD-adapted estimator to exhibit the same qualitative features as its stochastic counterpart, as it accurately estimates the lateral diffusivity across the pore while systematically underestimating the normal diffusivity close to hard boundaries. We introduce a conceptually simple and numerically efficient correction scheme based on simulated annealing and diffusion maps to resolve the latter artifact and obtain normal diffusivity profiles that are consistent with the self-part of the van Hove correlation functions. Our findings demonstrate the potential of this MD-adapted estimator in accurately characterizing spatial variations of diffusivity in confined materials.
Collapse
Affiliation(s)
- Tiago S Domingues
- Department of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut 06520, United States
| | - Ronald R Coifman
- Department of Mathematics, Yale University, New Haven, Connecticut 06520, United States
| | - Amir Haji-Akbari
- Department of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut 06520, United States
| |
Collapse
|
3
|
Liu L, Legg BA, Smith W, Anovitz LM, Zhang X, Harper R, Pearce CI, Rosso KM, Stack AG, Bleuel M, Mildner DFR, Schenter GK, Clark AE, De Yoreo JJ, Chun J, Nakouzi E. Predicting Outcomes of Nanoparticle Attachment by Connecting Atomistic, Interfacial, Particle, and Aggregate Scales. ACS NANO 2023; 17:15556-15567. [PMID: 37556761 DOI: 10.1021/acsnano.3c02145] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
Predicting nanoparticle aggregation and attachment phenomena requires a rigorous understanding of the interplay among crystal structure, particle morphology, surface chemistry, solution conditions, and interparticle forces, yet no comprehensive picture exists. We used an integrated suite of experimental, theoretical, and simulation methods to resolve the effect of solution pH on the aggregation of boehmite nanoplatelets, a case study with important implications for the environmental management of legacy nuclear waste. Real-time observations showed that the particles attach preferentially along the (010) planes at pH 8.5 and the (101) planes at pH 11. To rationalize these results, we established the connection between key physicochemical phenomena across the relevant length scales. Starting from molecular-scale simulations of surface hydroxyl reactivity, we developed an interfacial-scale model of the corresponding electrostatic potentials, with subsequent particle-scale calculations of the resulting driving forces allowing successful prediction of the attachment modes. Finally, we scaled these phenomena to understand the collective structure at the aggregate-scale. Our results indicate that facet-specific differences in surface chemistry produce heterogeneous surface charge distributions that are coupled to particle anisotropy and shape-dependent hydrodynamic forces, to play a key role in controlling aggregation behavior.
Collapse
Affiliation(s)
- Lili Liu
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Benjamin A Legg
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - William Smith
- Department of Chemistry, Washington State University, Pullman, Washington 99164, United States
| | - Lawrence M Anovitz
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Xin Zhang
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Reed Harper
- College of Computing, Engineering & Construction, University of North Florida, 1 UNF Drive, Jacksonville, Florida 32224, United States
| | - Carolyn I Pearce
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
- Department of Crop and Soil Sciences, Washington State University, Pullman, Washington 99164, United States
- University of Manchester, Manchester M13 9PL, United Kingdom
| | - Kevin M Rosso
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Andrew G Stack
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Markus Bleuel
- Center for Neutron Research, National Institute of Standards and Technology, Gaithersburg, Maryland 20889-6102, United States
- Department of Materials Science and Engineering, J. Clark School of Engineering, University of Maryland, College Park, Maryland 20742, United States
| | - David F R Mildner
- Center for Neutron Research, National Institute of Standards and Technology, Gaithersburg, Maryland 20889-6102, United States
| | - Gregory K Schenter
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Aurora E Clark
- Department of Chemistry, University of Utah, 315 1400 East, Salt Lake City, Utah 84112, United States
| | - James J De Yoreo
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
- Department of Materials Science and Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Jaehun Chun
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
- Levich Institute and Department of Chemical Engineering, CUNY City College of New York, New York, New York 10031, United States
| | - Elias Nakouzi
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| |
Collapse
|
4
|
Lesnicki D, Gao CY, Limmer DT, Rotenberg B. On the molecular correlations that result in field-dependent conductivities in electrolyte solutions. J Chem Phys 2021; 155:014507. [PMID: 34241409 DOI: 10.1063/5.0052860] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Employing recent advances in response theory and nonequilibrium ensemble reweighting, we study the dynamic and static correlations that give rise to an electric field-dependent ionic conductivity in electrolyte solutions. We consider solutions modeled with both implicit and explicit solvents, with different dielectric properties, and at multiple concentrations. Implicit solvent models at low concentrations and small dielectric constants exhibit strongly field-dependent conductivities. We compare these results to Onsager-Wilson theory of the Wien effect, which provides a qualitatively consistent prediction at low concentrations and high static dielectric constants but is inconsistent away from these regimes. The origin of the discrepancy is found to be increased ion correlations under these conditions. Explicit solvent effects act to suppress nonlinear responses, yielding a weakly field-dependent conductivity over the range of physically realizable field strengths. By decomposing the relevant time correlation functions, we find that the insensitivity of the conductivity to the field results from the persistent frictional forces on the ions from the solvent. Our findings illustrate the utility of nonequilibrium response theory in rationalizing nonlinear transport behavior.
Collapse
Affiliation(s)
- Dominika Lesnicki
- Sorbonne Université, CNRS, Physico-Chimie des Electrolytes et Nanosystèmes Interfaciaux, Paris, France
| | - Chloe Y Gao
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - David T Limmer
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Benjamin Rotenberg
- Sorbonne Université, CNRS, Physico-Chimie des Electrolytes et Nanosystèmes Interfaciaux, Paris, France
| |
Collapse
|