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Noid WG, Szukalo RJ, Kidder KM, Lesniewski MC. Rigorous Progress in Coarse-Graining. Annu Rev Phys Chem 2024; 75:21-45. [PMID: 38941523 DOI: 10.1146/annurev-physchem-062123-010821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
Low-resolution coarse-grained (CG) models provide remarkable computational and conceptual advantages for simulating soft materials. In principle, bottom-up CG models can reproduce all structural and thermodynamic properties of atomically detailed models that can be observed at the resolution of the CG model. This review discusses recent progress in developing theory and computational methods for achieving this promise. We first briefly review variational approaches for parameterizing interaction potentials and their relationship to machine learning methods. We then discuss recent approaches for simultaneously improving both the transferability and thermodynamic properties of bottom-up models by rigorously addressing the density and temperature dependence of these potentials. We also briefly discuss exciting progress in modeling high-resolution observables with low-resolution CG models. More generally, we highlight the essential role of the bottom-up framework not only for fundamentally understanding the limitations of prior CG models but also for developing robust computational methods that resolve these limitations in practice.
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Affiliation(s)
- W G Noid
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania, USA;
| | - Ryan J Szukalo
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania, USA;
- Current affiliation: Department of Chemistry, Princeton University, Princeton, New Jersey, USA
| | - Katherine M Kidder
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania, USA;
| | - Maria C Lesniewski
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania, USA;
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2
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Zhu H, Szymczyk A, Ghoufi A. Multiscale modelling of transport in polymer-based reverse-osmosis/nanofiltration membranes: present and future. DISCOVER NANO 2024; 19:91. [PMID: 38771417 PMCID: PMC11109084 DOI: 10.1186/s11671-024-04020-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 04/22/2024] [Indexed: 05/22/2024]
Abstract
Nanofiltration (NF) and reverse osmosis (RO) processes are physical separation technologies used to remove contaminants from liquid streams by employing dense polymer-based membranes with nanometric voids that confine fluids at the nanoscale. At this level, physical properties such as solvent and solute permeabilities are intricately linked to molecular interactions. Initially, numerous studies focused on developing macroscopic transport models to gain insights into separation properties at the nanometer scale. However, continuum-based models have limitations in nanoconfined situations that can be overcome by force field molecular simulations. Continuum-based models heavily rely on bulk properties, often neglecting critical factors like liquid structuring, pore geometry, and molecular/chemical specifics. Molecular/mesoscale simulations, while encompassing these details, often face limitations in time and spatial scales. Therefore, achieving a comprehensive understanding of transport requires a synergistic integration of both approaches through a multiscale approach that effectively combines and merges both scales. This review aims to provide a comprehensive overview of the state-of-the-art in multiscale modeling of transport through NF/RO membranes, spanning from the nanoscale to continuum media.
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Affiliation(s)
- Haochen Zhu
- State Key Laboratory of Pollution Control and Resources Reuse, Key Laboratory of Yangtze River Water Environment, College of Environmental Science and Engineering, Tongji University, 1239 Siping Rd., Shanghai, 200092, China.
| | - Anthony Szymczyk
- CNRS, ISCR (Institut des Sciences Chimiques de Rennes) - UMR 6226, Univ Rennes, 35000, Rennes, France.
| | - Aziz Ghoufi
- CNRS, ICMPE (Institut de Chimie et des Matériaux Paris-Est) - UMR 7182, Univ Paris-East Creteil, 94320, Thiais, France.
- CNRS, IPR (Institut de Physique de Rennes) - UMR 6251, Univ Rennes, 35000, Rennes, France.
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3
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Izvekov S, Kroonblawd MP, Larentzos JP, Brennan JK, Rice BM. Maximum Entropy Theory of Multiscale Coarse-Graining via Matching Thermodynamic Forces: Application to a Molecular Crystal (TATB). J Phys Chem B 2024. [PMID: 38489758 DOI: 10.1021/acs.jpcb.3c07078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2024]
Abstract
The MSCG/FM (multiscale coarse-graining via force-matching) approach is an efficient supervised machine learning method to develop microscopically informed coarse-grained (CG) models. We present a theory based on the principle of maximum entropy (PME) enveloping the existing MSCG/FM approaches. This theory views the MSCG/FM method as a special case of matching the thermodynamic forces from the extended ensemble described by the set of thermodynamic (relevant) system coordinates. This set may include CG coordinates, the stress tensor, applied external fields, and so forth, and may be characterized by nonequilibrium conditions. Following the presentation of the theory, we discuss the consistent matching of both bonded and nonbonded interactions. The proposed PME formulation is used as a starting point to extend the MSCG/FM method to the constant strain ensemble, which together with the explicit matching of the bonded forces is better suited for coarse-graining anisotropic media at a submolecular resolution. The theory is demonstrated by performing the fine coarse-graining of crystalline 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), a well-known insensitive molecular energetic material, which exhibits highly anisotropic mechanical properties.
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Affiliation(s)
- Sergei Izvekov
- U.S. Army DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, United States
| | - Matthew P Kroonblawd
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - James P Larentzos
- U.S. Army DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, United States
| | - John K Brennan
- U.S. Army DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, United States
| | - Betsy M Rice
- U.S. Army DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, United States
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4
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Alvares CMS, Semino R. Force matching and iterative Boltzmann inversion coarse grained force fields for ZIF-8. J Chem Phys 2024; 160:094115. [PMID: 38445731 DOI: 10.1063/5.0190807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 02/06/2024] [Indexed: 03/07/2024] Open
Abstract
Despite the intense activity at electronic and atomistic resolutions, coarse grained (CG) modeling of metal-organic frameworks remains largely unexplored. One of the main reasons for this is the lack of adequate CG force fields. In this work, we present iterative Boltzmann inversion and force matching (FM) force fields for modeling ZIF-8 at three different coarse grained resolutions. Their ability to reproduce structure, elastic tensor, and thermal expansion is evaluated and compared with that of MARTINI force fields considered in previous work [Alvares et al., J. Chem. Phys. 158, 194107 (2023)]. Moreover, MARTINI and FM are evaluated for their ability to depict the swing effect, a subtle phase transition ZIF-8 undergoes when loaded with guest molecules. Overall, we found that all our force fields reproduce structure reasonably well. Elastic constants and volume expansion results are analyzed, and the technical and conceptual challenges of reproducing them are explained. Force matching exhibits promising results for capturing the swing effect. This is the first time these CG methods, widely applied in polymer and biomolecule communities, are deployed to model porous solids. We highlight the challenges of fitting CG force fields for these materials.
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Affiliation(s)
| | - Rocio Semino
- Sorbonne Université, CNRS, Physico-chimie des Electrolytes et Nanosystèmes Interfaciaux, PHENIX, F-75005 Paris, France
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5
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Jin J, Hwang J, Voth GA. Gaussian representation of coarse-grained interactions of liquids: Theory, parametrization, and transferability. J Chem Phys 2023; 159:184105. [PMID: 37942867 DOI: 10.1063/5.0160567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 10/06/2023] [Indexed: 11/10/2023] Open
Abstract
Coarse-grained (CG) interactions determined via bottom-up methodologies can faithfully reproduce the structural correlations observed in fine-grained (atomistic resolution) systems, yet they can suffer from limited extensibility due to complex many-body correlations. As part of an ongoing effort to understand and improve the applicability of bottom-up CG models, we propose an alternative approach to address both accuracy and transferability. Our main idea draws from classical perturbation theory to partition the hard sphere repulsive term from effective CG interactions. We then introduce Gaussian basis functions corresponding to the system's characteristic length by linking these Gaussian sub-interactions to the local particle densities at each coordination shell. The remaining perturbative long-range interaction can be treated as a collective solvation interaction, which we show exhibits a Gaussian form derived from integral equation theories. By applying this numerical parametrization protocol to CG liquid systems, our microscopic theory elucidates the emergence of Gaussian interactions in common phenomenological CG models. To facilitate transferability for these reduced descriptions, we further infer equations of state to determine the sub-interaction parameter as a function of the system variables. The reduced models exhibit excellent transferability across the thermodynamic state points. Furthermore, we propose a new strategy to design the cross-interactions between distinct CG sites in liquid mixtures. This involves combining each Gaussian in the proper radial domain, yielding accurate CG potentials of mean force and structural correlations for multi-component systems. Overall, our findings establish a solid foundation for constructing transferable bottom-up CG models of liquids with enhanced extensibility.
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Affiliation(s)
- Jaehyeok Jin
- Department of Chemistry, Chicago Center for Theoretical Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, 5735 S. Ellis Ave., Chicago, Illinois 60637, USA
- Department of Chemistry, Columbia University, 3000 Broadway, New York, New York 10027, USA
| | - Jisung Hwang
- Department of Statistics, The University of Chicago, 5747 S. Ellis Ave., Chicago, Illinois 60637, USA
| | - Gregory A Voth
- Department of Chemistry, Chicago Center for Theoretical Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, 5735 S. Ellis Ave., Chicago, Illinois 60637, USA
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6
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Izvekov S, Rice BM. Hierarchical Machine Learning of Low-Resolution Coarse-Grained Free Energy Potentials. J Chem Theory Comput 2023. [PMID: 37256918 DOI: 10.1021/acs.jctc.3c00128] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
A force-matching-based method for supervised machine learning (ML) of coarse-grained (CG) free energy (FE) potentials─known as multiscale coarse-graining via force-matching (MSCG/FM)─is an efficient method to develop microscopically informed CG models that are thermodynamically and statistically equivalent to the reference microscopic models. For low-resolution models, when the coarse-graining is at supramolecular scales, objective-oriented clustering of nonbonded particles is required and the reduced description becomes a function of the clustering algorithm. In the present work, we explore the dependence of the ML of the CG Helmholtz FE potential on the clustering algorithm. We consider coarse-graining based on partitional (k-means, leading to Voronoi diagram) and hierarchical agglomerative (bottom-up) clustering algorithms common in unsupervised ML and develop theory connecting the MSCG/FM learned CG Helmholtz potential and the clustering statistics. By combining the agglomerative clustering and the MSCG/FM learning in a recursive manner, we propose an efficient ML methodology to develop the fine-to-low resolution hierarchies of the CG models. The methodology does not suffer from degrading accuracy or increased computational cost to construct larger hierarchies and as such does not impose an upper size limitation of the CG particles resulting from the extended hierarchies. The utility of the methodology is demonstrated by obtaining the bottom-up agglomerative hierarchy for liquid nitromethane from all-atom molecular dynamics (MD) simulations. For agglomerative hierarchies, we prove the existence of renormalization group transformations that indicate self-similarity and allow for learning the low-resolution MSCG/FM potentials at low computational cost by rescaling and renormalizing the certain finer-resolution members of the hierarchy. The hierarchies of the CG models can be used to carry out simulations under constant-pressure conditions.
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Affiliation(s)
- Sergei Izvekov
- U.S. Army DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, United States
| | - Betsy M Rice
- U.S. Army DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, United States
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7
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Ge P, Zhang L, Lei H. Machine learning assisted coarse-grained molecular dynamics modeling of meso-scale interfacial fluids. J Chem Phys 2023; 158:064104. [PMID: 36792498 DOI: 10.1063/5.0131567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
A hallmark of meso-scale interfacial fluids is the multi-faceted, scale-dependent interfacial energy, which often manifests different characteristics across the molecular and continuum scale. The multi-scale nature imposes a challenge to construct reliable coarse-grained (CG) models, where the CG potential function needs to faithfully encode the many-body interactions arising from the unresolved atomistic interactions and account for the heterogeneous density distributions across the interface. We construct the CG models of both single- and two-component polymeric fluid systems based on the recently developed deep coarse-grained potential [Zhang et al., J. Chem. Phys. 149, 034101 (2018)] scheme, where each polymer molecule is modeled as a CG particle. By only using the training samples of the instantaneous force under the thermal equilibrium state, the constructed CG models can accurately reproduce both the probability density function of the void formation in bulk and the spectrum of the capillary wave across the fluid interface. More importantly, the CG models accurately predict the volume-to-area scaling transition for the apolar solvation energy, illustrating the effectiveness to probe the meso-scale collective behaviors encoded with molecular-level fidelity.
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Affiliation(s)
- Pei Ge
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, Michigan 48824, USA
| | | | - Huan Lei
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, Michigan 48824, USA
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8
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Jin J, Pak AJ, Durumeric AEP, Loose TD, Voth GA. Bottom-up Coarse-Graining: Principles and Perspectives. J Chem Theory Comput 2022; 18:5759-5791. [PMID: 36070494 PMCID: PMC9558379 DOI: 10.1021/acs.jctc.2c00643] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Indexed: 01/14/2023]
Abstract
Large-scale computational molecular models provide scientists a means to investigate the effect of microscopic details on emergent mesoscopic behavior. Elucidating the relationship between variations on the molecular scale and macroscopic observable properties facilitates an understanding of the molecular interactions driving the properties of real world materials and complex systems (e.g., those found in biology, chemistry, and materials science). As a result, discovering an explicit, systematic connection between microscopic nature and emergent mesoscopic behavior is a fundamental goal for this type of investigation. The molecular forces critical to driving the behavior of complex heterogeneous systems are often unclear. More problematically, simulations of representative model systems are often prohibitively expensive from both spatial and temporal perspectives, impeding straightforward investigations over possible hypotheses characterizing molecular behavior. While the reduction in resolution of a study, such as moving from an atomistic simulation to that of the resolution of large coarse-grained (CG) groups of atoms, can partially ameliorate the cost of individual simulations, the relationship between the proposed microscopic details and this intermediate resolution is nontrivial and presents new obstacles to study. Small portions of these complex systems can be realistically simulated. Alone, these smaller simulations likely do not provide insight into collectively emergent behavior. However, by proposing that the driving forces in both smaller and larger systems (containing many related copies of the smaller system) have an explicit connection, systematic bottom-up CG techniques can be used to transfer CG hypotheses discovered using a smaller scale system to a larger system of primary interest. The proposed connection between different CG systems is prescribed by (i) the CG representation (mapping) and (ii) the functional form and parameters used to represent the CG energetics, which approximate potentials of mean force (PMFs). As a result, the design of CG methods that facilitate a variety of physically relevant representations, approximations, and force fields is critical to moving the frontier of systematic CG forward. Crucially, the proposed connection between the system used for parametrization and the system of interest is orthogonal to the optimization used to approximate the potential of mean force present in all systematic CG methods. The empirical efficacy of machine learning techniques on a variety of tasks provides strong motivation to consider these approaches for approximating the PMF and analyzing these approximations.
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Affiliation(s)
- Jaehyeok Jin
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, Institute for Biophysical
Dynamics, and James Franck Institute, The
University of Chicago, Chicago, Illinois 60637, United States
| | - Alexander J. Pak
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, Institute for Biophysical
Dynamics, and James Franck Institute, The
University of Chicago, Chicago, Illinois 60637, United States
| | - Aleksander E. P. Durumeric
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, Institute for Biophysical
Dynamics, and James Franck Institute, The
University of Chicago, Chicago, Illinois 60637, United States
| | - Timothy D. Loose
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, Institute for Biophysical
Dynamics, and James Franck Institute, The
University of Chicago, Chicago, Illinois 60637, United States
| | - Gregory A. Voth
- Department of Chemistry,
Chicago Center for Theoretical Chemistry, Institute for Biophysical
Dynamics, and James Franck Institute, The
University of Chicago, Chicago, Illinois 60637, United States
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9
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Evaluation of net interactions for liquid methane based on coarse-grained simulation. J Mol Liq 2022. [DOI: 10.1016/j.molliq.2022.119205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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10
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Pretti E, Shell MS. A microcanonical approach to temperature-transferable coarse-grained models using the relative entropy. J Chem Phys 2021; 155:094102. [PMID: 34496595 DOI: 10.1063/5.0057104] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Bottom-up coarse-graining methods provide systematic tools for creating simplified models of molecular systems. However, coarse-grained (CG) models produced with such methods frequently fail to accurately reproduce all thermodynamic properties of the reference atomistic systems they seek to model and, moreover, can fail in even more significant ways when used at thermodynamic state points different from the reference conditions. These related problems of representability and transferability limit the usefulness of CG models, especially those of strongly state-dependent systems. In this work, we present a new strategy for creating temperature-transferable CG models using a single reference system and temperature. The approach is based on two complementary concepts. First, we switch to a microcanonical basis for formulating CG models, focusing on effective entropy functions rather than energy functions. This allows CG models to naturally represent information about underlying atomistic energy fluctuations, which would otherwise be lost. Such information not only reproduces energy distributions of the reference model but also successfully predicts the correct temperature dependence of the CG interactions, enabling temperature transferability. Second, we show that relative entropy minimization provides a direct and systematic approach to parameterize such classes of temperature-transferable CG models. We calibrate the approach initially using idealized model systems and then demonstrate its ability to create temperature-transferable CG models for several complex molecular liquids.
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Affiliation(s)
- Evan Pretti
- Department of Chemical Engineering, Engineering II Building, University of California, Santa Barbara, Santa Barbara, California 93106-5080, USA
| | - M Scott Shell
- Department of Chemical Engineering, Engineering II Building, University of California, Santa Barbara, Santa Barbara, California 93106-5080, USA
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11
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Izvekov S, Rice BM. Bottom-up coarse-grain modeling of plasticity and nanoscale shear bands in α-RDX. J Chem Phys 2021; 155:064503. [PMID: 34391357 DOI: 10.1063/5.0057223] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Computationally inexpensive particle-based coarse-grained (CG) models are essential for use in molecular dynamics (MD) simulations of mesoscopically slow cooperative phenomena, such as plastic deformations in solids. Molecular crystals possessing complex symmetry present enormous practical challenges for particle-based coarse-graining at molecularly resolved scales, when each molecule is in a single-site representation, and beyond. Presently, there is no published pairwise non-bonded single-site CG potential that is able to predict the space group and structure of a molecular crystal. In this paper, we present a successful coarse-graining at a molecular level from first principles of an energetic crystal, hexahydro-1,3,5-trinitro-s-triazine (RDX) in the alpha phase, using the force-matching-based multiscale coarse-graining (MSCG/FM) approach. The new MSCG/FM model, which implements an optimal pair decomposition of the crystal Helmholtz free energy potential in molecular center-of-mass coordinates, was obtained by force-matching atomistic MD simulations of liquid, amorphous, and crystalline states and in a wide range of pressures (up to 20 GPa). The MSCG/FM potentials for different pressures underwent top-down optimization to fine-tune the mechanical and thermodynamic properties, followed by consolidation into a transferable density-dependent model referred to as RDX-TC-DD (RDX True-Crystal Density-Dependent). The RDX-TC-DD model predicts accurately the crystal structure of α-RDX at room conditions and reproduces the atomistic reference system under isothermal (300 K) hydrostatic compression up to 20 GPa, in particular, the Pbca symmetry of α-RDX in the elastic regime. The RDX-TC-DD model was then used to simulate the plastic response of uniaxially ([100]) compressed α-RDX resulting in nanoscale shear banding, a key mechanism for plastic deformation and defect-free detonation initiation proposed for many molecular crystalline explosives. Additionally, a comparative analysis of the effect of core-softening of the RDX-TC-DD potential and the degree of molecular rigidity in the all-atom treatment suggests a stress-induced short-range softening of the effective intermolecular interaction as a fundamental cause of plastic instability in α-RDX. The reported RDX-TC-DD model and overall workflow to develop it open up possibilities to perform high quality simulation studies of molecular energetic materials under thermal and mechanical stimuli, including extreme conditions.
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Affiliation(s)
- Sergei Izvekov
- Weapons and Materials Research Directorate, U.S. Army DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, USA
| | - Betsy M Rice
- Weapons and Materials Research Directorate, U.S. Army DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, USA
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12
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Shahidi N, Chazirakis A, Harmandaris V, Doxastakis M. Coarse-graining of polyisoprene melts using inverse Monte Carlo and local density potentials. J Chem Phys 2020; 152:124902. [PMID: 32241142 DOI: 10.1063/1.5143245] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Bottom-up coarse-graining of polymers is commonly performed by matching structural order parameters such as distribution of bond lengths, bending and dihedral angles, and pair distribution functions. In this study, we introduce the distribution of nearest-neighbors as an additional order parameter in the concept of local density potentials. We describe how the inverse-Monte Carlo method provides a framework for forcefield development that is capable of overcoming challenges associated with the parameterization of interaction terms in polymer systems. The technique is applied on polyisoprene melts as a prototype system. We demonstrate that while different forcefields can be developed that perform equally in terms of matching target distributions, the inclusion of nearest-neighbors provides a straightforward route to match both thermodynamic and conformational properties. We find that several temperature state points can also be addressed, provided that the forcefield is refined accordingly. Finally, we examine both the single-particle and the collective dynamics of the coarse-grain models, demonstrating that all forcefields present a similar acceleration relative to the atomistic systems.
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Affiliation(s)
- Nobahar Shahidi
- Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - Antonis Chazirakis
- Department of Mathematics and Applied Mathematics, University of Crete, Heraklion GR-71110, Greece
| | - Vagelis Harmandaris
- Department of Mathematics and Applied Mathematics, University of Crete, Heraklion GR-71110, Greece
| | - Manolis Doxastakis
- Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, Tennessee 37996, USA
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13
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Zhao P, Lee S, Sewell T, Udaykumar HS. Tandem Molecular Dynamics and Continuum Studies of Shock‐Induced Pore Collapse in TATB. PROPELLANTS EXPLOSIVES PYROTECHNICS 2020. [DOI: 10.1002/prep.201900382] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Affiliation(s)
- Puhan Zhao
- Department of Chemistry University of Missouri-Columbia Columbia MO 65211–7600
| | - Sangyup Lee
- Department of Mechanical Engineering University of Iowa Iowa City IA 52242
| | - Tommy Sewell
- Department of Chemistry University of Missouri-Columbia Columbia MO 65211–7600
| | - H. S. Udaykumar
- Department of Mechanical Engineering University of Iowa Iowa City IA 52242
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14
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Rondina GG, Böhm MC, Müller-Plathe F. Predicting the Mobility Increase of Coarse-Grained Polymer Models from Excess Entropy Differences. J Chem Theory Comput 2020; 16:1431-1447. [DOI: 10.1021/acs.jctc.9b01088] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Gustavo G. Rondina
- Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technische Universität Darmstadt, Alarich-Weiss-Straße 8, 64287 Darmstadt, Germany
| | - Michael C. Böhm
- Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technische Universität Darmstadt, Alarich-Weiss-Straße 8, 64287 Darmstadt, Germany
| | - Florian Müller-Plathe
- Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technische Universität Darmstadt, Alarich-Weiss-Straße 8, 64287 Darmstadt, Germany
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15
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Barnes BC, Leiter KW, Larentzos JP, Brennan JK. Forging of Hierarchical Multiscale Capabilities for Simulation of Energetic Materials. PROPELLANTS EXPLOSIVES PYROTECHNICS 2019. [DOI: 10.1002/prep.201900187] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Brian C. Barnes
- Energetic Materials Science Branch, FCDD-RLW-LB U.S. Army Research Laboratory Aberdeen Proving Ground MD 21005-5066
| | - Kenneth W. Leiter
- Simulation Sciences Branch, FCDD-RLC-NB U.S. Army Research Laboratory Aberdeen Proving Ground MD 21005-5066
| | - James P. Larentzos
- Energetic Materials Science Branch, FCDD-RLW-LB U.S. Army Research Laboratory Aberdeen Proving Ground MD 21005-5066
| | - John K. Brennan
- Energetic Materials Science Branch, FCDD-RLW-LB U.S. Army Research Laboratory Aberdeen Proving Ground MD 21005-5066
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16
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Manandhar A, Chakraborty K, Tang PK, Kang M, Zhang P, Cui H, Loverde SM. Rational Coarse-Grained Molecular Dynamics Simulations of Supramolecular Anticancer Nanotubes. J Phys Chem B 2019; 123:10582-10593. [DOI: 10.1021/acs.jpcb.9b07417] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Anjela Manandhar
- Department of Chemistry, College of Staten Island, City University of New York, New York 10314, United States
- Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York 10016, United States
| | - Kaushik Chakraborty
- Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York 10016, United States
| | - Phu K. Tang
- Department of Chemistry, College of Staten Island, City University of New York, New York 10314, United States
- Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York 10016, United States
| | - Myungshim Kang
- Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York 10016, United States
| | - Pengcheng Zhang
- Center of Pharmaceutics, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Honggang Cui
- Department of Chemical and Biomolecular Engineering and Institute for NanoBioTechnology, The Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department of Oncology and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States
| | - Sharon M. Loverde
- Department of Chemistry, College of Staten Island, City University of New York, New York 10314, United States
- Ph.D. Program in Biochemistry, The Graduate Center of the City University of New York, New York 10016, United States
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17
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Lebold KM, Noid WG. Dual-potential approach for coarse-grained implicit solvent models with accurate, internally consistent energetics and predictive transferability. J Chem Phys 2019; 151:164113. [PMID: 31675902 DOI: 10.1063/1.5125246] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
The dual-potential approach promises coarse-grained (CG) models that accurately reproduce both structural and energetic properties, while simultaneously providing predictive estimates for the temperature-dependence of the effective CG potentials. In this work, we examine the dual-potential approach for implicit solvent CG models that reflect large entropic effects from the eliminated solvent. Specifically, we construct implicit solvent models at various resolutions, R, by retaining a fraction 0.10 ≤ R ≤ 0.95 of the molecules from a simple fluid of Lennard-Jones spheres. We consider the dual-potential approach in both the constant volume and constant pressure ensembles across a relatively wide range of temperatures. We approximate the many-body potential of mean force for the remaining solutes with pair and volume potentials, which we determine via multiscale coarse-graining and self-consistent pressure-matching, respectively. Interestingly, with increasing temperature, the pair potentials appear increasingly attractive, while the volume potentials become increasingly repulsive. The dual-potential approach not only reproduces the atomic energetics but also quite accurately predicts this temperature-dependence. We also derive an exact relationship between the thermodynamic specific heat of an atomic model and the energetic fluctuations that are observable at the CG resolution. With this generalized fluctuation relationship, the approximate CG models quite accurately reproduce the thermodynamic specific heat of the underlying atomic model.
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Affiliation(s)
- Kathryn M Lebold
- Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, USA
| | - W G Noid
- Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, USA
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18
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Avalos JB, Lísal M, Larentzos JP, Mackie AD, Brennan JK. Generalised dissipative particle dynamics with energy conservation: density- and temperature-dependent potentials. Phys Chem Chem Phys 2019; 21:24891-24911. [PMID: 31690923 DOI: 10.1039/c9cp04404c] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We present a generalised, energy-conserving dissipative particle dynamics (DPDE) method appropriate for the non-isothermal simulation of particle interaction force fields that are both density- and temperature-dependent. A detailed derivation is formulated in a bottom-up manner by considering the thermodynamics of small systems with the appropriate consideration of the fluctuations. Connected to the local volume is a local density and corresponding local pressure, which is determined from an equation-of-state based force field that depends also on a particle temperature. Compared to the original DPDE method, the formulation of the generalised DPDE method requires a change in the independent variable from the particle internal energy to the particle entropy. As part of the re-formulation, the terms dressed particle entropy and the corresponding dressed particle temperature are introduced, which depict the many-body contributions in the local volume. The generalised DPDE method has similarities to the energy form of the smoothed dissipative particle dynamics method, yet fundamental differences exist, which are described in the manuscript. The basic dynamic equations are presented along with practical considerations for implementing the generalised DPDE method, including a numerical integration scheme based on the Shardlow-like splitting algorithm. Demonstrations and validation tests are performed using analytical equation-of-states for the van der Waals and Lennard-Jones fluids. Particle probability distributions are analysed, where excellent agreement with theoretical estimates is demonstrated. As further validation of the generalised DPDE method, both equilibrium and non-equilibrium simulation scenarios are considered, including adiabatic flash heating response and vapour-liquid phase separation.
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Affiliation(s)
- Josep Bonet Avalos
- Department d'Enginyeria Qumica, ETSEQ, Universitat Rovira i Virgili, Tarragona, Spain
| | - Martin Lísal
- Department of Molecular and Mesoscopic Modelling, Institute of Chemical Process Fundamentals of the CAS, Prague, Czech Republic and Department of Physics, Faculty of Science, J. E. Purkinje University, Úst n. Lab., Czech Republic
| | - James P Larentzos
- Weapons and Materials Research Directorate, U.S. Army Combat Capabilities Development Command Army Research Laboratory, Aberdeen Proving Ground, MD, USA.
| | - Allan D Mackie
- Department d'Enginyeria Qumica, ETSEQ, Universitat Rovira i Virgili, Tarragona, Spain
| | - John K Brennan
- Weapons and Materials Research Directorate, U.S. Army Combat Capabilities Development Command Army Research Laboratory, Aberdeen Proving Ground, MD, USA.
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19
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Lísal M, Larentzos JP, Sellers MS, Schweigert IV, Brennan JK. Dissipative particle dynamics with reactions: Application to RDX decomposition. J Chem Phys 2019; 151:114112. [DOI: 10.1063/1.5117904] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Affiliation(s)
- Martin Lísal
- Department of Molecular and Mesoscopic Modelling, Institute of Chemical Process Fundamentals of the CAS, Prague, Czech Republic
- Department of Physics, Faculty of Science, J. E. Purkinje University, Ústí n. Lab., Czech Republic
| | - James P. Larentzos
- Weapons and Materials Research Directorate, U.S. Army Combat Capabilities Development Command Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005-5066, USA
| | - Michael S. Sellers
- Weapons and Materials Research Directorate, U.S. Army Combat Capabilities Development Command Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005-5066, USA
| | - Igor V. Schweigert
- Code 6189, Theoretical Chemistry Section, U.S. Naval Research Laboratory, Washington, DC 20375, USA
| | - John K. Brennan
- Weapons and Materials Research Directorate, U.S. Army Combat Capabilities Development Command Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005-5066, USA
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20
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Rosenberger D, Sanyal T, Shell MS, van der Vegt NFA. Transferability of Local Density-Assisted Implicit Solvation Models for Homogeneous Fluid Mixtures. J Chem Theory Comput 2019; 15:2881-2895. [PMID: 30995034 DOI: 10.1021/acs.jctc.8b01170] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The application of bottom-up coarse grained (CG) models to study the equilibrium mixing behavior of liquids is rather challenging, since these models can be significantly influenced by the density or the concentration of the state chosen during parametrization. This dependency leads to low transferability in density/concentration space and has been one of the major limitations in bottom-up coarse graining. Recent approaches proposed to tackle this shortcoming range from the addition of thermodynamic constraints, to an extended ensemble parametrization, to the addition of supplementary terms to the system's Hamiltonian. To study fluid phase equilibria with bottom-up CG models, the application of local density (LD) potentials appears to be a promising approach, as shown in previous work by Sanyal and Shell [T. Sanyal, M. S. Shell, J. Phys. Chem. B, 2018, 122, 5678]. Here, we want to further explore this method and test its ability to model a system which contains structural inhomogeneities only on the molecular scale, namely, solutions of methanol and water. We find that a water-water LD potential improves the transferability of an implicit-methanol CG model toward high water concentration. Conversely, a methanol-methanol LD potential does not significantly improve the transferability of an implicit-water CG model toward high methanol concentration. These differences appear due to the presence of cooperative interactions in water at high concentrations that the LD potentials can capture. In addition, we compare two different approaches to derive our CG models, namely, relative entropy optimization and the Inverse Monte Carlo method, and formally demonstrate under which analytical and numerical assumptions these two methods yield equivalent results.
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Affiliation(s)
- David Rosenberger
- Eduard Zintl Institut für Anorganische und Physikalische Chemie , Technische Universität Darmstadt , Darmstadt , Germany
| | - Tanmoy Sanyal
- Department of Chemical Engineering , University of California Santa Barbara , Santa Barbara , California 93106 , United States
| | - M Scott Shell
- Department of Chemical Engineering , University of California Santa Barbara , Santa Barbara , California 93106 , United States
| | - Nico F A van der Vegt
- Eduard Zintl Institut für Anorganische und Physikalische Chemie , Technische Universität Darmstadt , Darmstadt , Germany
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21
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Deichmann G, van der Vegt NFA. Conditional Reversible Work Coarse-Grained Models with Explicit Electrostatics—An Application to Butylmethylimidazolium Ionic Liquids. J Chem Theory Comput 2019; 15:1187-1198. [DOI: 10.1021/acs.jctc.8b00881] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Gregor Deichmann
- Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technische Universität Darmstadt, Alarich-Weiss-Straße 10, 64287 Darmstadt, Germany
| | - Nico F. A. van der Vegt
- Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technische Universität Darmstadt, Alarich-Weiss-Straße 10, 64287 Darmstadt, Germany
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22
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Lebold KM, Noid WG. Systematic study of temperature and density variations in effective potentials for coarse-grained models of molecular liquids. J Chem Phys 2019; 150:014104. [DOI: 10.1063/1.5050509] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Affiliation(s)
- Kathryn M. Lebold
- Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, USA
| | - W. G. Noid
- Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, USA
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23
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Wagner JW, Dannenhoffer-Lafage T, Jin J, Voth GA. Extending the range and physical accuracy of coarse-grained models: Order parameter dependent interactions. J Chem Phys 2018; 147:044113. [PMID: 28764380 DOI: 10.1063/1.4995946] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Order parameters (i.e., collective variables) are often used to describe the behavior of systems as they capture different features of the free energy surface. Yet, most coarse-grained (CG) models only employ two- or three-body non-bonded interactions between the CG particles. In situations where these interactions are insufficient for the CG model to reproduce the structural distributions of the underlying fine-grained (FG) model, additional interactions must be included. In this paper, we introduce an approach to expand the basis sets available in the multiscale coarse-graining (MS-CG) methodology by including order parameters. Then, we investigate the ability of an additive local order parameter (e.g., density) and an additive global order parameter (i.e., distance from a hard wall) to improve the description of CG models in interfacial systems. Specifically, we study methanol liquid-vapor coexistence, acetonitrile liquid-vapor coexistence, and acetonitrile liquid confined by hard-wall plates, all using single site CG models. We find that the use of order parameters dramatically improves the reproduction of structural properties of interfacial CG systems relative to the FG reference as compared with pairwise CG interactions alone.
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Affiliation(s)
- Jacob W Wagner
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA
| | - Thomas Dannenhoffer-Lafage
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA
| | - Jaehyeok Jin
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA
| | - Gregory A Voth
- Department of Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA
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24
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Larentzos JP, Mansell JM, Lísal M, Brennan JK. Coarse-grain modelling using an equation-of-state many-body potential: application to fluid mixtures at high temperature and high pressure. Mol Phys 2018. [DOI: 10.1080/00268976.2018.1459920] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Affiliation(s)
- James P. Larentzos
- U.S. Army Research Laboratory, Weapons and Materials Research Directorate , Aberdeen Proving Ground, MD, USA
| | - J. Matthew Mansell
- Department of Chemical and Biomolecular Engineering, North Carolina State University , Raleigh, NC, USA
| | - Martin Lísal
- Department of Molecular and Mesoscopic Modelling, Institute of Chemical Process Fundamentals of the CAS, v. v. i. , Prague, Czech Republic
- Department of Physics, Faculty of Science, J. E. Purkinje University , Ústí n. Lab., Czech Republic
| | - John K. Brennan
- U.S. Army Research Laboratory, Weapons and Materials Research Directorate , Aberdeen Proving Ground, MD, USA
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25
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Sanyal T, Shell MS. Transferable Coarse-Grained Models of Liquid-Liquid Equilibrium Using Local Density Potentials Optimized with the Relative Entropy. J Phys Chem B 2018; 122:5678-5693. [PMID: 29466859 DOI: 10.1021/acs.jpcb.7b12446] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Bottom-up coarse-grained (CG) models are now regularly pursued to enable large length and time scale molecular simulations of complex, often macromolecular systems. However, predicting fluid phase equilibria using such models remains fundamentally challenging. A major problem stems from the typically low transferability of CG models beyond the densities and/or compositions at which they are parametrized, which is necessary if they are to describe distinct structural and thermodynamic properties unique to each phase. CG model transferability is compounded by the representation of the inherently multibody coarse interactions using pair potentials that neglect higher order effects. Here, we propose to construct transferable single site CG models of liquid mixtures by supplementing traditional CG pair interactions with local density potentials, which constitute a computationally inexpensive mean-field approach to describe many-body effects, in that site energies are modulated by the local solution environment. To illustrate the approach, we use intra- and interspecies local density potentials to develop CG models of benzene-water solutions that show impressive transferability in structural metrics (pair correlation functions, density profiles) throughout composition space, in contrast to pair-only CG representations. While further refinement may be necessary to represent more complex thermodynamic properties, like the liquid-liquid interfacial tension, the generality and improvement offered by the local density approach are highly encouraging for enabling complex phase equilibrium modeling using CG models.
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Affiliation(s)
- Tanmoy Sanyal
- Department of Chemical Engineering , University of California, Santa Barbara , Santa Barbara , California , United States
| | - M Scott Shell
- Department of Chemical Engineering , University of California, Santa Barbara , Santa Barbara , California , United States
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26
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DeLyser MR, Noid WG. Extending pressure-matching to inhomogeneous systems via local-density potentials. J Chem Phys 2017; 147:134111. [DOI: 10.1063/1.4999633] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Michael R. DeLyser
- Department of Chemistry, Penn State University, University
Park, Pennsylvania 16802, USA
| | - William G. Noid
- Department of Chemistry, Penn State University, University
Park, Pennsylvania 16802, USA
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27
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Ramezanghorbani F, Dalgicdir C, Sayar M. A multi-state coarse grained modeling approach for an intrinsically disordered peptide. J Chem Phys 2017; 147:094103. [DOI: 10.1063/1.5001087] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
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28
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Kuo AT, Okazaki S, Shinoda W. Transferable coarse-grained model for perfluorosulfonic acid polymer membranes. J Chem Phys 2017; 147:094904. [DOI: 10.1063/1.4986287] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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29
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Jiang C, Ouyang J, Wang L, Liu Q, Li W. Coarse graining of the fully atomic methane models to monatomic isotropic models using relative entropy minimization. J Mol Liq 2017. [DOI: 10.1016/j.molliq.2017.07.112] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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30
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Montes-Saralegui M, Kahl G, Nikoubashman A. On the applicability of density dependent effective interactions in cluster-forming systems. J Chem Phys 2017; 146:054904. [DOI: 10.1063/1.4975164] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Affiliation(s)
- Marta Montes-Saralegui
- Institute for Theoretical Physics and Center for Computational Material Science (CMS), Technische Universität Wien, Wiedner Hauptstraße 8-10, A-1040 Wien, Austria
| | - Gerhard Kahl
- Institute for Theoretical Physics and Center for Computational Material Science (CMS), Technische Universität Wien, Wiedner Hauptstraße 8-10, A-1040 Wien, Austria
| | - Arash Nikoubashman
- Institute of Physics, Johannes Gutenberg University Mainz, Staudingerweg 7, 55128 Mainz, Germany
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31
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Wagner JW, Dama JF, Durumeric AEP, Voth GA. On the representability problem and the physical meaning of coarse-grained models. J Chem Phys 2017; 145:044108. [PMID: 27475349 DOI: 10.1063/1.4959168] [Citation(s) in RCA: 89] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
In coarse-grained (CG) models where certain fine-grained (FG, i.e., atomistic resolution) observables are not directly represented, one can nonetheless identify indirect the CG observables that capture the FG observable's dependence on CG coordinates. Often, in these cases it appears that a CG observable can be defined by analogy to an all-atom or FG observable, but the similarity is misleading and significantly undermines the interpretation of both bottom-up and top-down CG models. Such problems emerge especially clearly in the framework of the systematic bottom-up CG modeling, where a direct and transparent correspondence between FG and CG variables establishes precise conditions for consistency between CG observables and underlying FG models. Here we present and investigate these representability challenges and illustrate them via the bottom-up conceptual framework for several simple analytically tractable polymer models. The examples provide special focus on the observables of configurational internal energy, entropy, and pressure, which have been at the root of controversy in the CG literature, as well as discuss observables that would seem to be entirely missing in the CG representation but can nonetheless be correlated with CG behavior. Though we investigate these problems in the framework of systematic coarse-graining, the lessons apply to top-down CG modeling also, with crucial implications for simulation at constant pressure and surface tension and for the interpretations of structural and thermodynamic correlations for comparison to experiment.
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Affiliation(s)
- Jacob W Wagner
- Department of Chemistry, James Franck Institute, Institute for Biophysical Dynamics, and Computation Institute, The University of Chicago, Chicago, Illinois 60637, USA
| | - James F Dama
- Department of Chemistry, James Franck Institute, Institute for Biophysical Dynamics, and Computation Institute, The University of Chicago, Chicago, Illinois 60637, USA
| | - Aleksander E P Durumeric
- Department of Chemistry, James Franck Institute, Institute for Biophysical Dynamics, and Computation Institute, The University of Chicago, Chicago, Illinois 60637, USA
| | - Gregory A Voth
- Department of Chemistry, James Franck Institute, Institute for Biophysical Dynamics, and Computation Institute, The University of Chicago, Chicago, Illinois 60637, USA
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32
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Patrone PN, Rosch TW, Phelan FR. Bayesian calibration of coarse-grained forces: Efficiently addressing transferability. J Chem Phys 2017; 144:154101. [PMID: 27389203 DOI: 10.1063/1.4945380] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Generating and calibrating forces that are transferable across a range of state-points remains a challenging task in coarse-grained (CG) molecular dynamics. In this work, we present a coarse-graining workflow, inspired by ideas from uncertainty quantification and numerical analysis, to address this problem. The key idea behind our approach is to introduce a Bayesian correction algorithm that uses functional derivatives of CG simulations to rapidly and inexpensively recalibrate initial estimates f0 of forces anchored by standard methods such as force-matching. Taking density-temperature relationships as a running example, we demonstrate that this algorithm, in concert with various interpolation schemes, can be used to efficiently compute physically reasonable force curves on a fine grid of state-points. Importantly, we show that our workflow is robust to several choices available to the modeler, including the interpolation schemes and tools used to construct f0. In a related vein, we also demonstrate that our approach can speed up coarse-graining by reducing the number of atomistic simulations needed as inputs to standard methods for generating CG forces.
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Affiliation(s)
- Paul N Patrone
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - Thomas W Rosch
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - Frederick R Phelan
- National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
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33
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Gooneie A, Schuschnigg S, Holzer C. A Review of Multiscale Computational Methods in Polymeric Materials. Polymers (Basel) 2017; 9:E16. [PMID: 30970697 PMCID: PMC6432151 DOI: 10.3390/polym9010016] [Citation(s) in RCA: 113] [Impact Index Per Article: 16.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Revised: 12/07/2016] [Accepted: 12/22/2016] [Indexed: 11/17/2022] Open
Abstract
Polymeric materials display distinguished characteristics which stem from the interplay of phenomena at various length and time scales. Further development of polymer systems critically relies on a comprehensive understanding of the fundamentals of their hierarchical structure and behaviors. As such, the inherent multiscale nature of polymer systems is only reflected by a multiscale analysis which accounts for all important mechanisms. Since multiscale modelling is a rapidly growing multidisciplinary field, the emerging possibilities and challenges can be of a truly diverse nature. The present review attempts to provide a rather comprehensive overview of the recent developments in the field of multiscale modelling and simulation of polymeric materials. In order to understand the characteristics of the building blocks of multiscale methods, first a brief review of some significant computational methods at individual length and time scales is provided. These methods cover quantum mechanical scale, atomistic domain (Monte Carlo and molecular dynamics), mesoscopic scale (Brownian dynamics, dissipative particle dynamics, and lattice Boltzmann method), and finally macroscopic realm (finite element and volume methods). Afterwards, different prescriptions to envelope these methods in a multiscale strategy are discussed in details. Sequential, concurrent, and adaptive resolution schemes are presented along with the latest updates and ongoing challenges in research. In sequential methods, various systematic coarse-graining and backmapping approaches are addressed. For the concurrent strategy, we aimed to introduce the fundamentals and significant methods including the handshaking concept, energy-based, and force-based coupling approaches. Although such methods are very popular in metals and carbon nanomaterials, their use in polymeric materials is still limited. We have illustrated their applications in polymer science by several examples hoping for raising attention towards the existing possibilities. The relatively new adaptive resolution schemes are then covered including their advantages and shortcomings. Finally, some novel ideas in order to extend the reaches of atomistic techniques are reviewed. We conclude the review by outlining the existing challenges and possibilities for future research.
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Affiliation(s)
- Ali Gooneie
- Chair of Polymer Processing, Montanuniversitaet Leoben, Otto Gloeckel-Strasse 2, 8700 Leoben, Austria.
| | - Stephan Schuschnigg
- Chair of Polymer Processing, Montanuniversitaet Leoben, Otto Gloeckel-Strasse 2, 8700 Leoben, Austria.
| | - Clemens Holzer
- Chair of Polymer Processing, Montanuniversitaet Leoben, Otto Gloeckel-Strasse 2, 8700 Leoben, Austria.
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34
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Izvekov S. Mori-Zwanzig theory for dissipative forces in coarse-grained dynamics in the Markov limit. Phys Rev E 2017; 95:013303. [PMID: 28208451 DOI: 10.1103/physreve.95.013303] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Indexed: 04/29/2023]
Abstract
We derive alternative Markov approximations for the projected (stochastic) force and memory function in the coarse-grained (CG) generalized Langevin equation, which describes the time evolution of the center-of-mass coordinates of clusters of particles in the microscopic ensemble. This is done with the aid of the Mori-Zwanzig projection operator method based on the recently introduced projection operator [S. Izvekov, J. Chem. Phys. 138, 134106 (2013)10.1063/1.4795091]. The derivation exploits the "generalized additive fluctuating force" representation to which the projected force reduces in the adopted projection operator formalism. For the projected force, we present a first-order time expansion which correctly extends the static fluctuating force ansatz with the terms necessary to maintain the required orthogonality of the projected dynamics in the Markov limit to the space of CG phase variables. The approximant of the memory function correctly accounts for the momentum dependence in the lowest (second) order and indicates that such a dependence may be important in the CG dynamics approaching the Markov limit. In the case of CG dynamics with a weak dependence of the memory effects on the particle momenta, the expression for the memory function presented in this work is applicable to non-Markov systems. The approximations are formulated in a propagator-free form allowing their efficient evaluation from the microscopic data sampled by standard molecular dynamics simulations. A numerical application is presented for a molecular liquid (nitromethane). With our formalism we do not observe the "plateau-value problem" if the friction tensors for dissipative particle dynamics (DPD) are computed using the Green-Kubo relation. Our formalism provides a consistent bottom-up route for hierarchical parametrization of DPD models from atomistic simulations.
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Affiliation(s)
- Sergei Izvekov
- Weapons and Materials Research Directorate, U.S. Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, Maryland 21005, USA
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35
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Dunn NJH, Noid WG. Bottom-up coarse-grained models with predictive accuracy and transferability for both structural and thermodynamic properties of heptane-toluene mixtures. J Chem Phys 2016; 144:204124. [DOI: 10.1063/1.4952422] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Nicholas J. H. Dunn
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - W. G. Noid
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
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36
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Moore JD, Barnes BC, Izvekov S, Lísal M, Sellers MS, Taylor DE, Brennan JK. A coarse-grain force field for RDX: Density dependent and energy conserving. J Chem Phys 2016; 144:104501. [DOI: 10.1063/1.4942520] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Affiliation(s)
- Joshua D. Moore
- Energetic Materials Science Branch, RDRL-WML-B, US Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005-5066, USA
| | - Brian C. Barnes
- Energetic Materials Science Branch, RDRL-WML-B, US Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005-5066, USA
| | - Sergei Izvekov
- Energetic Materials Science Branch, RDRL-WML-B, US Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005-5066, USA
| | - Martin Lísal
- Laboratory of Aerosols Chemistry and Physics, Institute of Chemical Process Fundamentals of the Czech Academy of Sciences, v. v. i., 165 02 Prague 6-Suchdol, Czech Republic
- Department of Physics, Institute of Science, J. E. Purkinje University, 400 96 Ústí n. Lab., Czech Republic
| | - Michael S. Sellers
- Energetic Materials Science Branch, RDRL-WML-B, US Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005-5066, USA
| | - DeCarlos E. Taylor
- Energetic Materials Science Branch, RDRL-WML-B, US Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005-5066, USA
| | - John K. Brennan
- Energetic Materials Science Branch, RDRL-WML-B, US Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005-5066, USA
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37
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Sellers MS, Lísal M, Brennan JK. Free-energy calculations using classical molecular simulation: application to the determination of the melting point and chemical potential of a flexible RDX model. Phys Chem Chem Phys 2016; 18:7841-50. [DOI: 10.1039/c5cp06164d] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Several methods are used in sequence to determine the chemical potential of atomistic RDX in the solid and liquid phases, and its corresponding melting point. Results yield the thermodynamic melting point of 488.75 K at 1.0 atm.
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Affiliation(s)
- Michael S. Sellers
- U.S. Army Research Laboratory
- Weapons and Materials Research Directorate
- RDRL-WML-B
- Aberdeen Proving Ground
- USA 21005
| | - Martin Lísal
- Laboratory of Chemistry and Physics of Aerosols
- Institute of Chemical Process Fundamentals of the ASCR
- 165 02 Prague 6-Suchdol
- Czech Republic
- Department of Physics
| | - John K. Brennan
- U.S. Army Research Laboratory
- Weapons and Materials Research Directorate
- RDRL-WML-B
- Aberdeen Proving Ground
- USA 21005
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38
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Dunn NJH, Noid WG. Bottom-up coarse-grained models that accurately describe the structure, pressure, and compressibility of molecular liquids. J Chem Phys 2015; 143:243148. [DOI: 10.1063/1.4937383] [Citation(s) in RCA: 76] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Affiliation(s)
- Nicholas J. H. Dunn
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - W. G. Noid
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
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39
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Huang W, Riniker S, van Gunsteren WF. Rapid Sampling of Folding Equilibria of β-Peptides in Methanol Using a Supramolecular Solvent Model. J Chem Theory Comput 2015; 10:2213-23. [PMID: 26580745 DOI: 10.1021/ct500048c] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Molecular dynamics simulation of biomolecules in solvent using an atomic model for both the biomolecules and the solvent molecules is still computationally rather demanding considering the time scale of the biomolecular motions. The use of a supramolecular coarse-grained (CG) model can speed up the simulation considerably, but it also reduces the accuracy inevitably. Combining an atomic fine-grained (FG) level of modeling for the biomolecules and a supramolecular CG level for the solvent into a hybrid system, the increased computational efficiency may outweigh the loss of accuracy with respect to the biomolecular properties in the hybrid FG/CG simulation. Here, a previously published CG methanol model is reparametrized, and then a 1:1 mixture of FG and CG methanol is used to calibrate the FG-CG interactions using thermodynamic and dielectric screening data for liquid methanol. The FG-CG interaction parameter set is applied in hybrid FG/CG solute/solvent simulations of the folding equilibria of three β-peptides that adopt different folds. The properties of the peptides are compared with those obtained in FG solvent simulations and with experimental NMR data. The comparison shows that the folding equilibria in the pure CG solvent simulations are different from those in the FG solvent simulations because of the lack of hydrogen-bonding partners in the supramolecular CG solvent. Next, we introduced an FG methanol layer around the peptides in CG solvent to recover the hydrogen-bonding pattern of the FG solvent simulations. The result shows that with the FG methanol layer, the folding equilibria of the three β-peptides are very similar to those in the FG solvent simulations, while the computational efficiency is at least 3 times higher and the cutoff radius for nonbonded interactions could be increased from 1.4 to 2.0 nm.
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Affiliation(s)
- Wei Huang
- Laboratory of Physical Chemistry, Swiss Federal Institute of Technology, ETH , 8093 Zürich, Switzerland
| | - Sereina Riniker
- Laboratory of Physical Chemistry, Swiss Federal Institute of Technology, ETH , 8093 Zürich, Switzerland
| | - Wilfred F van Gunsteren
- Laboratory of Physical Chemistry, Swiss Federal Institute of Technology, ETH , 8093 Zürich, Switzerland
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40
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Wagner JW, Dama JF, Voth GA. Predicting the Sensitivity of Multiscale Coarse-Grained Models to their Underlying Fine-Grained Model Parameters. J Chem Theory Comput 2015; 11:3547-60. [DOI: 10.1021/acs.jctc.5b00180] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Jacob W. Wagner
- Department of Chemistry,
James Franck Institute, Institute for Biophysical Dynamics, and Computation
Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, United States
| | - James F. Dama
- Department of Chemistry,
James Franck Institute, Institute for Biophysical Dynamics, and Computation
Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, United States
| | - Gregory A. Voth
- Department of Chemistry,
James Franck Institute, Institute for Biophysical Dynamics, and Computation
Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, United States
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41
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Haxton TK. High-Resolution Coarse-Grained Modeling Using Oriented Coarse-Grained Sites. J Chem Theory Comput 2015; 11:1244-54. [DOI: 10.1021/ct500881x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Thomas K. Haxton
- Molecular
Foundry, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
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42
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Izvekov S, Rice BM. On the importance of shear dissipative forces in coarse-grained dynamics of molecular liquids. Phys Chem Chem Phys 2015; 17:10795-804. [DOI: 10.1039/c4cp06116k] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
In this work we demonstrate from first principles that the shear frictions describing dissipative forces in the direction normal to the vector connecting the coarse-grained (CG) particles in dissipative particle dynamics (DPD) could be dominant for certain real molecular liquids at high-resolution coarse-graining.
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Affiliation(s)
- Sergei Izvekov
- Weapons and Materials Research Directorate
- U.S. Army Research Laboratory
- Aberdeen Proving Ground
- USA
| | - Betsy M. Rice
- Weapons and Materials Research Directorate
- U.S. Army Research Laboratory
- Aberdeen Proving Ground
- USA
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43
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Haxton TK, Mannige RV, Zuckermann RN, Whitelam S. Modeling Sequence-Specific Polymers Using Anisotropic Coarse-Grained Sites Allows Quantitative Comparison with Experiment. J Chem Theory Comput 2014; 11:303-15. [DOI: 10.1021/ct5010559] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Thomas K. Haxton
- Molecular
Foundry, Lawrence Berkeley
National Laboratory, Berkeley, California 94720, United States
| | - Ranjan V. Mannige
- Molecular
Foundry, Lawrence Berkeley
National Laboratory, Berkeley, California 94720, United States
| | - Ronald N. Zuckermann
- Molecular
Foundry, Lawrence Berkeley
National Laboratory, Berkeley, California 94720, United States
| | - Stephen Whitelam
- Molecular
Foundry, Lawrence Berkeley
National Laboratory, Berkeley, California 94720, United States
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44
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Kar P, Feig M. Recent advances in transferable coarse-grained modeling of proteins. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2014; 96:143-80. [PMID: 25443957 PMCID: PMC5366245 DOI: 10.1016/bs.apcsb.2014.06.005] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Computer simulations are indispensable tools for studying the structure and dynamics of biological macromolecules. Biochemical processes occur on different scales of length and time. Atomistic simulations cannot cover the relevant spatiotemporal scales at which the cellular processes occur. To address this challenge, coarse-grained (CG) modeling of the biological systems is employed. Over the last few years, many CG models for proteins continue to be developed. However, many of them are not transferable with respect to different systems and different environments. In this review, we discuss those CG protein models that are transferable and that retain chemical specificity. We restrict ourselves to CG models of soluble proteins only. We also briefly review recent progress made in the multiscale hybrid all-atom/CG simulations of proteins.
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Affiliation(s)
- Parimal Kar
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, USA
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, USA; Department of Chemistry, Michigan State University, East Lansing, Michigan, USA.
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Abstract
By focusing on essential features, while averaging over less important details, coarse-grained (CG) models provide significant computational and conceptual advantages with respect to more detailed models. Consequently, despite dramatic advances in computational methodologies and resources, CG models enjoy surging popularity and are becoming increasingly equal partners to atomically detailed models. This perspective surveys the rapidly developing landscape of CG models for biomolecular systems. In particular, this review seeks to provide a balanced, coherent, and unified presentation of several distinct approaches for developing CG models, including top-down, network-based, native-centric, knowledge-based, and bottom-up modeling strategies. The review summarizes their basic philosophies, theoretical foundations, typical applications, and recent developments. Additionally, the review identifies fundamental inter-relationships among the diverse approaches and discusses outstanding challenges in the field. When carefully applied and assessed, current CG models provide highly efficient means for investigating the biological consequences of basic physicochemical principles. Moreover, rigorous bottom-up approaches hold great promise for further improving the accuracy and scope of CG models for biomolecular systems.
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Affiliation(s)
- W G Noid
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
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47
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Faure G, Maillet JB, Stoltz G. Local density dependent potential for compressible mesoparticles. J Chem Phys 2014; 140:114105. [DOI: 10.1063/1.4868547] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
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48
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Izvekov S, Rice BM. Multi-scale coarse-graining of non-conservative interactions in molecular liquids. J Chem Phys 2014; 140:104104. [DOI: 10.1063/1.4866142] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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49
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Taylor DE, Rice BM. Quantum-Informed Multiscale M&S for Energetic Materials. ADVANCES IN QUANTUM CHEMISTRY 2014. [DOI: 10.1016/b978-0-12-800345-9.00005-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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50
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Dalgicdir C, Sensoy O, Peter C, Sayar M. A transferable coarse-grained model for diphenylalanine: How to represent an environment driven conformational transition. J Chem Phys 2013; 139:234115. [DOI: 10.1063/1.4848675] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
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