skip to main content

Title: Combining dynamic Monte Carlo with machine learning to study nanoparticle translocation
Resistive pulse sensing (RPS) measurements of nanoparticle translocation have the ability to provide information on single-particle level characteristics, such as diameter or mobility, as well as ensemble averages. However, interpreting these measurements is complex and requires an understanding of nanoparticle dynamics in confined spaces as well as the ways in which nanoparticles disrupt ion transport while inside a nanopore. Here, we combine Dynamic Monte Carlo (DMC) simulations with Machine Learning (ML) and Poisson–Nernst–Planck calculations to simultaneously simulate nanoparticle dynamics and ion transport during hundreds of independent particle translocations as a function of nanoparticle size, electrophoretic mobility, and nanopore length. The use of DMC simulations allowed us to explicitly investigate the effects of Brownian motion and nanoparticle/nanopore characteristics on the amplitude and duration of translocation signals. Simulation results were verified with experimental RPS measurements and found to be in quantitative agreement.  more » « less
Award ID(s):
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Soft Matter
Page Range / eLocation ID:
5218 to 5229
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Single nanoparticle analysis can reveal how particle‐to‐particle heterogeneity affects ensemble properties derived from traditional bulk measurements. High‐bandwidth, low noise electrochemical measurements are needed to examine the fast heterogeneous electron‐transfer behavior of single nanoparticles with sufficient fidelity to resolve the behavior of individual nanoparticles. Herein, nanopore electrode arrays (NEAs) are fabricated in which each pore supports two vertically spaced, individually addressable electrodes. The top ring electrode serves as a particle gate to control the transport of silver nanoparticles (AgNPs) within individual attoliter volume NEAs nanopores, as shown by redox collisions of AgNPs collisions at the bottom disk electrode. The AgNP‐nanoporeis system has wide‐ranging technological applications as well as fundamental interest, since the transport of AgNPs within the NEA mimics the transport of ions through cell membranes via voltage‐gated ion channels. A voltage threshold is observed above which AgNPs are able to access the bottom electrode of the NEAs, i.e., a minimum potential at the gate electrode is required to switch between few and many observed collision events on the collector electrode. It is further shown that this threshold voltage is strongly dependent on the applied voltage at both electrodes as well as the size of AgNPs, as shown both experimentally and through finite‐element modeling. Overall, this study provides a precise method of monitoring nanoparticle transport and in situ redox reactions within nanoconfined spaces at the single particle level.

    more » « less
  2. null (Ed.)
    We incorporated polymer-grafted nanoparticles into ionic and zwitterionic liquids to explore the solvation and confinement effects on their heterogeneous dynamics using quasi-elastic neutron scattering (QENS). 1-Hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (HMIM-TFSI) mixed with deuterated poly(methyl methacrylate) (d-PMMA)-grafted nanoparticles is studied to unravel how dynamic coupling between PMMA and HMIM-TFSI influence the fast and slow diffusion characteristics of the HMIM + cations. The zwitterionic liquid, 1-butyl-3-methyl imidazole-2-ylidene borane (BMIM-BH 3 ) is critically selected and mixed with PMMA-grafted nanoparticles for comparison in this work as its ions do not self-dissociate and it does not couple with PMMA through ion-dipole interactions as HMIM-TFSI does. We find that long-range unrestricted diffusion of HMIM + cations is higher in well-dispersed particles than in aggregated particle systems, whereas the localized diffusion of HMIM + is measured to be higher in close-packed particles. Translational diffusion dynamics of BMIM-BH 3 is not influenced by any particle structures suggesting that zwitterions do not interact with PMMA. This difference between two ionic liquid types enables us to decouple polymer effects from the diffusion of ionic liquids, which is integral to understand the ionic transport mechanism in ionic liquids confined in polymer-grafted nanoparticle electrolytes. 
    more » « less
  3. An inexpensive, reliable method for protein sequencing is essential to unraveling the biological mechanisms governing cellular behavior and disease. Current protein sequencing methods suffer from limitations associated with the size of proteins that can be sequenced, the time, and the cost of the sequencing procedures. This study reports the results of all‐atom molecular dynamics simulations that investigated the feasibility of using graphene nanopores for protein sequencing. The study is focused on the biologically significant phenylalanine‐glycine repeat peptides (FG‐nups)—parts of the nuclear pore transport machinery. Surprisingly, FG‐nups are found to behave similarly to single stranded DNA: The peptides adhere to graphene and exhibit stepwise translocation when subject to a transmembrane bias or a hydrostatic pressure gradient. Reducing the peptide's charge density or increasing the peptide's hydrophobicity is found to decrease the translocation speed. Yet, unidirectional and stepwise translocation driven by a transmembrane bias is observed even when the ratio of charged to hydrophobic amino acids is as low as 1:8. The nanopore transport of the peptides is found to produce stepwise modulations of the nanopore ionic current correlated with the type of amino acids present in the nanopore, suggesting that protein sequencing by measuring ionic current blockades may be possible.

    more » « less

    Calcium ions (Ca2+) play key roles in various fundamental biological processes such as cell signaling and brain function. Molecular dynamics (MD) simulations have been used to study such interactions, however, the accuracy of the Ca2+models provided by the standard MD force fields has not been rigorously tested. Here, we assess the performance of the Ca2+models from the most popular classical force fields AMBER and CHARMM by computing the osmotic pressure of model compounds and the free energy of DNA–DNA interactions. In the simulations performed using the two standard models, Ca2+ions are seen to form artificial clusters with chloride, acetate, and phosphate species; the osmotic pressure of CaAc2and CaCl2solutions is a small fraction of the experimental values for both force fields. Using the standard parameterization of Ca2+ions in the simulations of Ca2+‐mediated DNA–DNA interactions leads to qualitatively wrong outcomes: both AMBER and CHARMM simulations suggest strong inter‐DNA attraction whereas, in experiment, DNA molecules repel one another. The artificial attraction of Ca2+to DNA phosphate is strong enough to affect the direction of the electric field‐driven translocation of DNA through a solid‐state nanopore. To address these shortcomings of the standard Ca2+model, we introduce a custom model of a hydrated Ca2+ion and show that using our model brings the results of the above MD simulations in quantitative agreement with experiment. Our improved model of Ca2+can be readily applied to MD simulations of various biomolecular systems, including nucleic acids, proteins and lipid bilayer membranes. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 752–763, 2016.

    more » « less
  5. null (Ed.)
    Particle charging in the afterglows of non-thermal plasmas typically take place in a non-neutral space charge environment. We model the same by incorporating particle-ion collision rate constant models, developed in prior work by analyzing particle-ion trajectories calculated using Langevin Dynamics simulations, into species transport equations for ions, electrons and charged particles in the afterglow. A scaling analysis of particle charging and additional Langevin Dynamics calculations of the particle-ion collision rate constant are presented to extend the range of applicability to ion electrostatic to thermal energy ratios of 300 and diffusive Knudsen number (that scales inversely with gas pressure) up to 2000. The developed collision rate constant models are first validated by comparing predictions of particle charge against measured values in a stationary, non-thermal DC plasma from past PK-4 campaigns published in Phys. Rev. Lett. 93(8): 085001 and Phys. Rev. E 72(1): 016406). The comparisons reveal excellent agreement within ±35% for particles of radius 0.6,1.0,1.3 μm in the gas pressure range of ~20-150 Pa. The experiments to probe particle charge distributions by Sharma et al. (J. Physics D: Appl. Phys. 53(24): 245204) are modeled using the validated particle-ion collision rate constant models and the calculated charge fractions are compared with measurements. The comparisons reveal that the ion/electron concentration and gas temperature in the afterglow critically influence the particle charge and the predictions are generally in qualitative agreement with the measurements. Along with critical assessment of the modeling assumptions, several recommendations are presented for future experimental design to probe charging in afterglows. 
    more » « less