Iterative integral equation methods for structural coarse-graining

Bernhardt, Marvin P.; Hanke, Martin; Vegt, Nico F. A. van der

doi:10.1063/5.0038633

Cited by 10 publications

(16 citation statements)

References 46 publications

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“…This opens possibilities to optimize pair potentials not only with respect to structural properties, but also to other properties as well. Building on this idea, Hanke and co-workers have recently developed novel integral equation-based methods that allow one to solve the inverse Henderson problem with additional constraints, , such that the resulting CG model reproduces both the structural correlations and the thermodynamic properties of the microscopic system . When applying such methods, one should keep in mind that the RDFs obtained from FG simulations may suffer from finite-size effects.…”

Section: Scale-bridging Strategiesmentioning

confidence: 99%

“…Building on this idea, Hanke and coworkers have recently developed novel integral equation-based methods that allow one to solve the inverse Henderson problem with additional constraints, 315,316 such that the resulting CG model reproduces both the structural correlations and the thermodynamic properties of the microscopic system. 316 When applying such methods, one should keep in mind that the RDFs obtained from FG simulations may suffer from finite-size effects. Cortes-Huerto and co-workers have recently investigated this in the context of Kirkwood−Buff integrals 317,318 and proposed expressions for finite-size corrections in liquid solutions.…”

Section: IIImentioning

confidence: 99%

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Understanding and Modeling Polymers: The Challenge of Multiple Scales

Schmid

2022

ACS Polym. Au

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Polymer materials are multiscale systems by definition. Already the description of a single macromolecule involves a multitude of scales, and cooperative processes in polymer assemblies are governed by their interplay. Polymers have been among the first materials for which systematic multiscale techniques were developed, yet they continue to present extraordinary challenges for modellers. In this Perspective, we review popular models that are used to describe polymers on different scales and discuss scale-bridging strategies such as static and dynamic coarse-graining methods and multiresolution approaches. We close with a list of hard problems which still need to be solved in order to gain a comprehensive quantitative understanding of polymer systems.

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Section: Scale-bridging Strategiesmentioning

confidence: 99%

Section: IIImentioning

confidence: 99%

Understanding and Modeling Polymers: The Challenge of Multiple Scales

Schmid

2022

ACS Polym. Au

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“…Finally, the methods presented in this Letter may be applied to benchmark force fields for coarse-grained simulations, which has seen a growing interest in structure-inversion techniques. 57,58 ■ THEORY AND COMPUTATIONAL METHODS…”

Section: The Journal Of Physical Chemistry Lettersmentioning

confidence: 99%

“…However, incoherent and inelastic scattering corrections, as well as nonuniqueness of the partial structure factor decomposition, will need to be addressed to extend the presented techniques to complex liquids. Finally, the methods presented in this Letter may be applied to benchmark force fields for coarse-grained simulations, which has seen a growing interest in structure-inversion techniques. , …”

mentioning

confidence: 99%

Transferable Force Fields from Experimental Scattering Data with Machine Learning Assisted Structure Refinement

Shanks

Potoff

Hoepfner

2022

J. Phys. Chem. Lett.

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Deriving transferable pair potentials from experimental neutron and X-ray scattering measurements has been a longstanding challenge in condensed matter physics. State-of-the-art scattering analysis techniques estimate real-space microstructure from reciprocal-space total scattering data by refining pair potentials to obtain agreement between simulated and experimental results. Prior attempts to apply these potentials with molecular simulations have revealed inaccurate predictions of thermodynamic fluid properties. In this Letter, a machine learning assisted structure-inversion method applied to neutron scattering patterns of the noble gases (Ne, Ar, Kr, and Xe) is shown to recover transferable pair potentials that accurately reproduce both microstructure and vapor–liquid equilibria from the triple to critical point. Therefore, it is concluded that a single neutron scattering measurement is sufficient to predict macroscopic thermodynamic properties over a wide range of states and provide novel insight into local atomic forces in dense monatomic systems.

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“…In two previous papers, we have introduced a new type of structural coarse-graining method for solving the inverse problem which is based on integral equation theory. , It uses the hypernetted-chain (HNC) equation for an approximate relation between RDF and the potential. The new iteration methods lead to convergence in a similar number of iterations as IMC while requiring no sampling of cross-correlation matrices.…”

Section: Introductionmentioning

confidence: 99%

Stability, Speed, and Constraints for Structural Coarse-Graining in VOTCA

Bernhardt

Hanke

Vegt

2023

J. Chem. Theory Comput.

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Structural coarse-graining involves the inverse problem of deriving pair potentials that reproduce target radial distribution functions. Despite its clear mathematical formulation, there are open questions about the existing methods concerning speed, stability, and physical representability of the resulting potentials. In this work, we make progress on several aspects of iterative methods used to solve the inverse problem. Based on integral equation theory, we derive fast Gauss−Newton schemes applicable to very general systems, including molecules with bonds and mixtures. Our methods are similar to inverse Monte Carlo in terms of convergence speed and have a similar cost per iteration as iterative Boltzmann inversion. We investigate stability problems in our schemes and in the inverse Monte Carlo method and propose modifications to fix them. Furthermore, we establish how the pair potential can be constrained at each iteration to reproduce the pressure, Kirkwood−Buff integral, or the enthalpy of vaporization. We demonstrate the potential of our approach in deriving coarsegrained force fields for nine different solvents and their mixtures. All methods described are implemented in the free and open VOTCA software framework for systematic coarse-graining.

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Iterative integral equation methods for structural coarse-graining

Cited by 10 publications

References 46 publications

Understanding and Modeling Polymers: The Challenge of Multiple Scales

Understanding and Modeling Polymers: The Challenge of Multiple Scales

Transferable Force Fields from Experimental Scattering Data with Machine Learning Assisted Structure Refinement

Stability, Speed, and Constraints for Structural Coarse-Graining in VOTCA

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