Nonlinear Dynamic Modeling, Simulation And Characterization Of The Mesoscale Neuron-electrode Interface

Extracellular neuroelectronic interfacing has important applications in the fields of neural prosthetics, biological computation and whole-cell biosensing for drug screening and toxin detection. While the field of neuroelectronic interfacing holds great promise, the recording of high-fidelity signals from extracellular devices has long suffered from the problem of low signal-to-noise ratios and changes in signal shapes due to the presence of highly dispersive dielectric medium in the neuron-microelectrode cleft. This has made it difficult to correlate the extracellularly recorded signals with the intracellular signals recorded using conventional patch-clamp electrophysiology. For bringing about an improvement in the signalto-noise ratio of the signals recorded on the extracellular microelectrodes and to explore strategies for engineering the neuron-electrode interface there exists a need to model, simulate and characterize the cell-sensor interface to better understand the mechanism of signal transduction across the interface. Efforts to date for modeling the neuron-electrode interface have primarily focused on the use of point or area contact linear equivalent circuit models for a description of the interface with an assumption of passive linearity for the dynamics of the interfacial medium in the cell-electrode cleft. In this dissertation, results are presented from a nonlinear dynamic characterization of the neuroelectronic junction based on Volterra-Wiener modeling which showed that the process of signal transduction at the interface may have nonlinear contributions from the interfacial medium. An optimization based study of linear equivalent circuit models for representing signals recorded at the neuron-electrode interface subsequently iv proved conclusively that the process of signal transduction across the interface is indeed nonlinear. Following this a theoretical framework for the extraction of the complex nonlinear material parameters of the interfacial medium like the dielectric permittivity, conductivity and diffusivity tensors based on dynamic nonlinear Volterra-Wiener modeling was developed. Within this framework, the use of Gaussian bandlimited white noise for nonlinear impedance spectroscopy was shown to offer considerable advantages over the use of sinusoidal inputs for nonlinear harmonic analysis currently employed in impedance characterization of nonlinear electrochemical systems. Signal transduction at the neuron-microelectrode interface is mediated by the interfacial medium confined to a thin cleft with thickness on the scale of 20-110 nm giving rise to Knudsen numbers (ratio of mean free path to characteristic system length) in the range of 0.015 and 0.003 for ionic electrodiffusion. At these Knudsen numbers, the continuum assumptions made in the use of Poisson-Nernst-Planck system of equations for modeling ionic electrodiffusion are not valid. Therefore, a lattice Boltzmann method (LBM) based multiphysics solver suitable for modeling ionic electrodiffusion at the mesoscale neuron-microelectrode interface was developed. Additionally, a molecular speed dependent relaxation time was proposed for use in the lattice Boltzmann equation. Such a relaxation time holds promise for enhancing the numerical stability of lattice Boltzmann algorithms as it helped recover a physically correct description of microscopic phenomena related to particle collisions governed by their local density on the lattice. Next, using this multiphysics solver simulations were carried out for the charge relaxation dynamics of an electrolytic nanocapacitor with the intention of ultimately employing it for a simulation of the capacitive coupling between the neuron and the v planar microelectrode on a microelectrode array (MEA). Simulations of the charge relaxation dynamics for a step potential applied at t = 0 to the capacitor electrodes were carried out for varying conditions of electric double layer (EDL) overlap, solvent viscosity, electrode spacing and ratio of cation to anion diffusivity. For a large EDL overlap, an anomalous plasma-like collective behavior of oscillating ions at a frequency much lower than the plasma frequency of the electrolyte was observed and as such it appears to be purely an effect of nanoscale confinement. Results from these simulations are then discussed in the context of the dynamics of the interfacial medium in the neuron-microelectrode cleft. In conclusion, a synergistic approach to engineering the neuron-microelectrode interface is outlined through a use of the nonlinear dynamic modeling, simulation and characterization tools developed as part of this dissertation research

Charge relaxation dynamics of an electrolytic nanocapacitor

Understanding ion relaxation dynamics in overlapping electric double layers (EDLs) is critical for the development of efficient nanotechnology based electrochemical energy storage, electrochemomechanical energy conversion and bioelectrochemical sensing devices as well as controlled synthesis of nanostructured materials. Here, a Lattice Boltzmann (LB) method is employed to simulate an electrolytic nanocapacitor subjected to a step potential at t = 0 for various degrees of EDL overlap, solvent viscosities, ratios of cation to anion diffusivity and electrode separations. The use of a novel, continuously varying and Galilean invariant, molecular speed dependent relaxation time (MSDRT) with the LB equation recovers a correct microscopic description of the molecular collision phenomena and enhances the stability of the LB algorithm. Results for large EDL overlaps indicated oscillatory behavior for the ionic current density in contrast to monotonic relaxation to equilibrium for low EDL overlaps. Further, at low solvent viscosities and large EDL overlaps, anomalous plasma-like spatial oscillations of the electric field were observed that appeared to be purely an effect of nanoscale confinement. Employing MSDRT in our simulations enabled a modeling of the fundamental physics of the transient charge relaxation dynamics in electrochemical systems operating away from equilibrium wherein Nernst-Einstein relation is known to be violated.Comment: Accepted for publication in the Journal of Physical Chemistry C on October 30 2014. Supplementary info available free of charge via the Internet at http://pubs.acs.org. Revised version includes more details on the computation of the molecular speed dependent relaxation time (MSDRT) and emphasizes the Galilean invariance of the computed MSDR

Controlled propulsion and separation of helical particles at the nanoscale

Controlling the motion of nano and microscale objects in a fluid environment is a key factor in designing optimized tiny machines that perform mechanical tasks such as transport of drugs or genetic material in cells, fluid mixing to accelerate chemical reactions, and cargo transport in microfluidic chips. Directed motion is made possible by the coupled translational and rotational motion of asymmetric particles. A current challenge in achieving directed and controlled motion at the nanoscale lies in overcoming random Brownian motion due to thermal fluctuations in the fluid. We use a hybrid lattice-Boltzmann Molecular Dynamics method with full hydrodynamic interactions and thermal fluctuations to demonstrate that controlled propulsion of individual nanohelices in an aqueous environment is possible. We optimize the propulsion velocity and the efficiency of externally driven nanohelices. We quantify the importance of the thermal effects on the directed motion by calculating the P\'eclet number for various shapes, number of turns and pitch lengths of the helices. Consistent with the experimental microscale separation of chiral objects, our results indicate that in the presence of thermal fluctuations at P\'eclet numbers $>10$, chiral particles follow the direction of propagation according to its handedness and the direction of the applied torque making separation of chiral particles possible at the nanoscale. Our results provide criteria for the design and control of helical machines at the nanoscale

Plasmonically enhanced reflectance of heat radiation from low-bandgap semiconductor microinclusions

© 2017 The Author(s). Increased reflectance from the inclusion of highly scattering particles at low volume fractions in an insulating dielectric offers a promising way to reduce radiative thermal losses at high temperatures. Here, we investigate plasmonic resonance driven enhanced scattering from microinclusions of low-bandgap semiconductors (InP, Si, Ge, PbS, InAs and Te) in an insulating composite to tailor its infrared reflectance for minimizing thermal losses from radiative transfer. To this end, we compute the spectral properties of the microcomposites using Monte Carlo modeling and compare them with results from Fresnel equations. The role of particle size-dependent Mie scattering and absorption efficiencies, and, scattering anisotropy are studied to identify the optimal microinclusion size and material parameters for maximizing the reflectance of the thermal radiation. For composites with Si and Ge microinclusions we obtain reflectance efficiencies of 57-65% for the incident blackbody radiation from sources at temperatures in the range 400-1600 °C. Furthermore, we observe a broadbanding of the reflectance spectra from the plasmonic resonances due to charge carriers generated from defect states within the semiconductor bandgap. Our results thus open up the possibility of developing efficient high-Temperature thermal insulators through use of the low-bandgap semiconductor microinclusions in insulating dielectrics

Controlled propulsion and separation of helical particles at the nanoscale

Controlling the motion of nano and microscale objects in a fluid environment is a key factor in designing optimized tiny machines that perform mechanical tasks such as transport of drugs or genetic material in cells, fluid mixing to accelerate chemical reactions, and cargo transport in microfluidic chips. Directed motion is made possible by the coupled translational and rotational motion of asymmetric particles. A current challenge in achieving directed and controlled motion at the nanoscale lies in overcoming random Brownian motion due to thermal fluctuations in the fluid. We use a hybrid lattice-Boltzmann molecular dynamics method with full hydrodynamic interactions and thermal fluctuations to demonstrate that controlled propulsion of individual nanohelices in an aqueous environment is possible. We optimize the propulsion velocity and the efficiency of externally driven nanohelices. We quantify the importance of the thermal effects on the directed motion by calculating the Péclet number for various shapes, number of turns and pitch lengths of the helices. Consistent with the experimental microscale separation of chiral objects, our results indicate that in the presence of thermal fluctuations at Péclet numbers >10, chiral particles follow the direction of propagation according to its handedness and the direction of the applied torque making separation of chiral particles possible at the nanoscale. Our results provide criteria for the design and control of helical machines at the nanoscale

Silica-Silicon Composites for Near-Infrared Reflection: A Comprehensive Computational and Experimental Study

Compact layers containing embedded semiconductor particles consolidated using pulsed electric current sintering exhibit intense, broadband near-infrared reflectance. The composites consolidated from nano- or micro-silica powder have a different porous microstructure which causes scattering at the air-matrix interface and larger reflectance primarily in the visible region. The 3 mm thick composite compacts reflect up to 72% of the incident radiation in the near-infrared region with a semiconductor microinclusion volume fraction of 1% which closely matches predictions from multiscale Monte Carlo modeling and Kubelka-Munk theory. Further, the calculated spectra predict an improvement of the reflectance by decreasing the average particle size or broadening the standard deviation. The high reflectance is achieved with minimal dissipative losses and facile manufacturing, and the composites described herein are well-suited to control the radiative transfer of heat in devices at high temperature and under harsh conditions.Comment: 9 pages, 5 figure

Shape and scale dependent diffusivity of colloidal nanoclusters and aggregates

© 2016, EDP Sciences and Springer.The diffusion of colloidal nanoparticles and nanomolecular aggregates, which plays an important role in various biophysical and physicochemical phenomena, is currently under intense study. Here, we examine the shape and size dependent diffusion of colloidal nano- particles, fused nanoclusters and nanoaggregates using a hybrid fluctuating lattice Boltzmann-Molecular Dynamics method. We use physically realistic parameters characteristic of an aqueous solution, with explicitly implemented microscopic no-slip and full-slip boundary conditions. Results from nanocolloids below 10 nm in radii demonstrate how the volume fraction of the hydrodynamic boundary layer influences diffusivities. Full-slip colloids are found to diffuse faster than no-slip particles. We also characterize the shape dependent anisotropy of the diffusion coefficients of nanoclusters through the Green-Kubo relation. Finally, we study the size dependence of the diffusion of nanoaggregates comprising N ≤ 108 monomers and demonstrate that the diffusion coefficient approaches the continuum scaling limit of N−1/3

Charge Relaxation Dynamics Of An Electrolytic Nanocapacitor

Understanding ion relaxation dynamics in overlapping electric double layers (EDLs) is critical for the development of efficient nanotechnology-based electrochemical energy storage, electrochemomechanical energy conversion, and bioelectrochemical sensing devices as well as the controlled synthesis of nanostructured materials. Here, a lattice Boltzmann (LB) method is employed to simulate an electrolytic nanocapacitor subjected to a step potential at t = 0 for various degrees of EDL overlap, solvent viscosities, ratios of cation-to-anion diffusivity, and electrode separations. The use of a novel continuously varying and Galilean-invariant molecular-speed-dependent relaxation time (MSDRT) with the LB equation recovers a correct microscopic description of the molecular-collision phenomena and enhances the stability of the LB algorithm. Results for large EDL overlaps indicated oscillatory behavior for the ionic current density, in contrast to monotonic relaxation to equilibrium for low EDL overlaps. Further, at low solvent viscosities and large EDL overlaps, anomalous plasmalike spatial oscillations of the electric field were observed that appeared to be purely an effect of nanoscale confinement. Employing MSDRT in our simulations enabled modeling of the fundamental physics of the transient charge relaxation dynamics in electrochemical systems operating away from equilibrium wherein Nernst-Einstein relation is known to be violated. (Graph Presented)

Temperature-resilient anapole modes associated with TE polarization in semiconductor nanowires

Funding Information: The authors acknowledge funding and support from the Academy of Finland, COMP Center of Excellence Programs (2015-2017), Grant No. 284621; Quantum Technology Finland Center of Excellence Program, Grant No. 312298; Radiation Detectors for Health, Safety and Security (RADDESS) Consortium Grant of the Academy of Finland; the Aalto University Energy Efficiency Research Program (EXPECTS); the Aalto Science-IT project; the Discovery Grants Program of the Natural Sciences and Engineering Research Council (NSERC) of Canada, and Canada Research Chairs Program. Computational resources were provided by Compute Canada (www.computecanada.ca). Publisher Copyright: © 2022, The Author(s).Polarization-dependent scattering anisotropy of cylindrical nanowires has numerous potential applications in, for example, nanoantennas, photothermal therapy, thermophotovoltaics, catalysis, sensing, optical filters and switches. In all these applications, temperature-dependent material properties play an important role and often adversely impact performance depending on the dominance of either radiative or dissipative damping. Here, we employ numerical modeling based on Mie scattering theory to investigate and compare the temperature and polarization-dependent optical anisotropy of metallic (gold, Au) nanowires with indirect (silicon, Si) and direct (gallium arsenide, GaAs) bandgap semiconducting nanowires. Results indicate that plasmonic scattering resonances in semiconductors, within the absorption band, deteriorate with an increase in temperature whereas those occurring away from the absorption band strengthen as a result of the increase in phononic contribution. Indirect-bandgap thin (20nm) Si nanowires present low absorption efficiencies for both the transverse electric (TE, E⊥) and magnetic (TM, E‖) modes, and high scattering efficiencies for the TM mode at shorter wavelengths making them suitable as highly efficient scatterers. Temperature-resilient higher-order anapole modes with their characteristic high absorption and low scattering efficiencies are also observed in the semiconductor nanowires (r=125-130 nm) for the TE polarization. Herein, the GaAs nanowires present 3-7 times greater absorption efficiencies compared to the Si nanowires making them especially suitable for temperature-resilient applications such as scanning near-field optical microscopy (SNOM), localized heating, non-invasive sensing or detection that require strong localization of energy in the near field.Peer reviewe