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Learning effective SDEs from Brownian dynamic simulations of colloidal particles

Journal Article · · Molecular Systems Design & Engineering
DOI:https://doi.org/10.1039/d2me00086e· OSTI ID:2424510
We construct a reduced, data-driven, parameter dependent effective stochastic differential equation (eSDE) for electric-field mediated colloidal crystallization using data obtained from Brownian dynamics simulations. We use diffusion maps (a manifold learning algorithm) to identify a set of useful latent observables. In this latent space we identify an eSDE using a deep learning architecture inspired by numerical stochastic integrators and compare it with the traditional Kramers–Moyal expansion estimation. We show that the obtained variables and the learned dynamics accurately encode the physics of the Brownian dynamic simulations. We further illustrate that our reduced model captures the dynamics of corresponding experimental data. Further, our dimension reduction/reduced model identification approach can be easily ported to a broad class of particle systems dynamics experiments/models.
Research Organization:
Johns Hopkins Univ., Baltimore, MD (United States)
Sponsoring Organization:
National Science Foundation (NSF); USDOE
OSTI ID:
2424510
Alternate ID(s):
OSTI ID: 1968541
Journal Information:
Molecular Systems Design & Engineering, Journal Name: Molecular Systems Design & Engineering Journal Issue: 7 Vol. 8; ISSN 2058-9689
Publisher:
Royal Society of ChemistryCopyright Statement
Country of Publication:
United States
Language:
English

References (51)

Multivariate Density Estimation: Theory, Practice, and Visualization book March 2015
Feedback Controlled Colloidal Self-Assembly journal May 2012
Multidimensional Architectures for Functional Optical Devices journal February 2010
Nonlinear principal component analysis using autoassociative neural networks journal February 1991
Model identification of a spatiotemporally varying catalytic reaction journal January 1993
Vector diffusion maps and the connection Laplacian journal March 2012
Particles and suspensions in chemical engineering: Accomplishments and prospects journal December 1995
Identification of distributed parameter systems: A neural net based approach journal March 1998
Diffusion maps, spectral clustering and reaction coordinates of dynamical systems journal July 2006
Diffusion maps journal July 2006
Parsimonious representation of nonlinear dynamical systems through manifold learning: A chemotaxis case study journal May 2018
Noisy dynamic simulations in the presence of symmetry: Data alignment and model reduction journal May 2013
Stochastic physics-informed neural ordinary differential equations journal November 2022
A comparison of open-loop and closed-loop strategies in colloidal self-assembly journal December 2017
A data-driven approach for discovering stochastic dynamical systems with non-Gaussian Lévy noise journal March 2021
Accelerated Simulations of Molecular Systems through Learning of Effective Dynamics journal December 2021
Optimal Feedback Controlled Assembly of Perfect Crystals journal July 2016
kT-Scale Colloidal Interactions in High Frequency Inhomogeneous AC Electric Fields. I. Single Particles journal August 2011
Colloidal crystal grain boundary formation and motion journal August 2014
The construction and application of Markov state models for colloidal self-assembly process control journal January 2017
Anisotropic colloidal interactions & assembly in AC electric fields journal January 2021
Size dependent thermodynamics and kinetics in electric field mediated colloidal crystal assembly journal January 2013
Equation-free Model Reduction in Agent-based Computations: Coarse-grained Bifurcation and Variable-free Rare Event Analysis journal January 2015
Coarse-grained kinetic computations for rare events: Application to micelle formation
  • Kopelevich, Dmitry I.; Panagiotopoulos, Athanassios Z.; Kevrekidis, Ioannis G.
  • The Journal of Chemical Physics, Vol. 122, Issue 4 https://doi.org/10.1063/1.1839174
journal January 2005
Interactions and microstructures in electric field mediated colloidal assembly journal October 2009
A Smoluchowski model of crystallization dynamics of small colloidal clusters journal October 2011
Dynamic colloidal assembly pathways via low dimensional models journal May 2016
Sparse learning of stochastic dynamical equations journal June 2018
Non-equilibrium steady-state colloidal assembly dynamics journal May 2019
Intrinsic map dynamics exploration for uncharted effective free-energy landscapes journal June 2017
Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation journal March 2020
DISCRETE- vs. CONTINUOUS-TIME NONLINEAR SIGNAL PROCESSING OF Cu ELECTRODISSOLUTION DATA journal November 1992
LIII. On lines and planes of closest fit to systems of points in space journal November 1901
Reduction and reconstruction for self-similar dynamical systems journal May 2003
Extracting stochastic governing laws by non-local Kramers–Moyal formulae
  • Lu, Yubin; Li, Yang; Duan, Jinqiao
  • Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 380, Issue 2229 https://doi.org/10.1098/rsta.2021.0195
journal June 2022
Bond-orientational order in liquids and glasses journal July 1983
Analysis of time series from stochastic processes journal September 2000
A solution for the best rotation to relate two sets of vectors journal September 1976
A discussion of the solution for the best rotation to relate two sets of vectors journal September 1978
Diffusion Maps for Signal Processing: A Deeper Look at Manifold-Learning Techniques Based on Kernels and Graphs journal July 2013
Identifying Latent Stochastic Differential Equations journal January 2022
Controlling colloidal crystals via morphing energy landscapes and reinforcement learning journal November 2020
A Global Geometric Framework for Nonlinear Dimensionality Reduction journal December 2000
Nonlinear Dimensionality Reduction by Locally Linear Embedding journal December 2000
Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-informed Deep Generative Models journal January 2022
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation journal June 2003
Formulation and Processing of Colloidal Dispersions journal January 1989
datafold: data-driven models for point clouds and time series on manifolds journal July 2020
Discrete- vs. Continuous-Time Nonlinear Signal Processing: Attractors, Transitions and Parallel Implementation Issues conference June 1993
Reduced Models in Chemical Kinetics via Nonlinear Data-Mining journal January 2014
Simulate Time-integrated Coarse-grained Molecular Dynamics with Geometric Machine Learning preprint January 2022

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