Paul M. Welch

Thermal fluctuations in shape, thickness, and molecular orientation in lipid bilayers

We present a unified continuum-level model for bilayer energetics that includes the effects of bending, compression, lipid orientation (tilting relative to the monolayer surface normal), and microscopic noise (protrusions). Expressions for thermal fluctuation amplitudes of several physical quantities are derived. These predictions are shown to be in good agreement with molecular simulations.

Dendrimers as synthetic gene vectors: Cell membrane attachment

We present molecular-level simulations of dendrimer/DNA complexes in the presence of a model cell membrane. We determine the required conditions for the complex to arrive intact at the membrane, and the lifetime of the complex as it resides attached to the membrane. Our simulations directly pertain to critical issues arising in emerging gene delivery therapeutic applications, where a molecular carrier is required to deliver DNA segments to the interior of living cells.

Thermal fluctuations in shape, thickness, and molecular orientation in lipid bilayers. II. Finite surface tensions.

We investigate the role of lipid chemical potential on the shape, thickness, and molecular orientation (lipid tilting relative to the monolayer surface normal) of lipid bilayers via a continuum-level model. We predict that decreasing the chemical potential at constant temperature, which is associated with an increase in surface tension via the Gibbs-Duhem relation, leads both to the well known reduction in thermal membrane undulations and also to increasing fluctuation amplitudes for bilayer thickness and molecular orientation. These trends are shown to be in good agreement with molecular simulations, however it is impossible to achieve full quantitative agreement between theory and simulation within the confines of the present model. We suggest that the assumption of lipid volume incompressibility, common to our theoretical treatment and other continuum models in the literature, may be partially responsible for the quantitative discrepancies between theory and simulation.

Examining the role of fluctuations in the early stages of homogenous polymer crystallization with simulation and statistical learning

We propose a relationship between the dynamics in the amorphous and crystalline domains during polymer crystallization: the fluctuations of ordering-rate about a material-specific value in the amorphous phase drive those fluctuations associated with the increase in percent crystallinity. This suggests a differential equation that satisfies the three experimentally observed time regimes for the rate of crystal growth. To test this postulated expression, we applied a suite of statistical learning tools to molecular dynamics simulations to extract the relevant phenomenology. This study shows that the proposed relationship holds in the early time regime. It illustrates the effectiveness of soft computing tools in the analysis of coarse-grained simulations in which patterns exist, but may not easily yield to strict quantitative evaluation. This ability assists us in characterizing the critical early time molecular arrangement during the primary nucleation phase of polymer melt crystallization. In addition to supporting the validity of the proposed kinetics expression, the simulations show that (i) the classical nucleation and growth mechanism is active in the early stages of ordering; (ii) the number of nuclei and their masses grow linearly during this early time regime; and (iii) a fixed inter-nuclei distance is established.

Efficient Full-Field Operational Modal Analysis Using Neuromorphic Event-Based Imaging

As an alternative to traditional sensing methods, video camera measurements offer a non-contact, cost-efficient, and full-field platform for operational modal analysis. However, video cameras record large amounts of redundant background data causing video processing to be computationally inefficient. This work explores the use of a silicon retina imager to perform operational modal analysis. The silicon retina provides an efficient alternative to standard frame-based video cameras. Modeling the biological retina, each silicon retina pixel independently and asynchronously records changes in intensity. By only recording intensity change events, all motion information is captured without recording redundant background information. This asynchronous event-based data representation allows motion to be captured on the microsecond scale, equivalent to traditional cameras operating at thousands of frames per second. With minimal data storage and processing requirements, the silicon retina shows promise for real-time vibration measurement and structural control applications. This study takes the first step toward these applications by adapting existing video frame-based modal analysis techniques to operate on event-based silicon retina measurements. Specifically, blind source separation and video motion processing techniques are used to automatically output vibration parameters from silicon retina data. The developed method is demonstrated on a cantilever beam.

Eigenvector centrality is a metric of elastomer modulus, heterogeneity, and damage

We present an application of eigenvector centrality to encode the connectivity of polymer networks resolved at the micro- and meso-scopic length scales. This method captures the relative importance of different nodes within the network structure and provides a route toward the development of a statistical mechanics model that correlates connectivity with mechanical response. This scheme may be informed by analytical and semi-analytical models for the network structure, or through direct experimental examination. It may be used to predict the reduction in mechanical performance for heterogeneous materials subjected to specific modes of damage. Here, we develop the method and demonstrate that it leads to the prediction of established trends in elastomers. We also apply the model to the case of a self-healing polymer network reported in the literature, extracting insight about the fraction of bonds broken and re-formed during strain and recovery.

Influence of supercoiling on the disruption of dsDNA

We propose that supercoiling energizes double-stranded DNA (dsDNA) so as to facilitate thermal fluctuations to an unzipped state. We support this with a model of two elastic rods coupled via forces that represent base-pair interactions. Supercoiling is shown to lead to a distention of base pairs over a short span of dsDNA. This enhances the thermal probability for their disruption. The localized region of distention is analogous to a soliton. Our theory permits the development of an analogy between the unzipping transition and a second-order phase transition, for which the possibility of a new set of critical exponents is identified.