Large-scale, high-throughput production of nano-structured materials (i.e. nanomanufacturing) is a strategic area in manufacturing, with markets projected to exceed $1T by 2015. Nanomanufacturing is still in its infancy; process/product developments are costly and only touch on potential opportunities enabled by growing nanoscience discoveries. The greatest promise for high-volume manufacturing lies in age-old coating and imprinting operations. For materials with tailored nm-scale structure, imprinting/embossing must be achieved at high speeds (roll-to-roll) and/or over large areas (batch operation) with feature sizes less than 100 nm. Dispersion coatings with nanoparticles can also tailor structure through self- or directed-assembly. Layering films structured with these processes have tremendous potential for efficient manufacturing of microelectronics, photovoltaics and other topical nano-structured devices. This project is designed to perform the requisite R and D to bring Sandia's technology base in computational mechanics to bear on this scale-up problem. Project focus is enforced by addressing a promising imprinting process currently being commercialized.
Multilayer coextrusion has become a popular commercial process for producing complex polymeric products from soda bottles to reflective coatings. A numerical model of a multilayer coextrusion process is developed based on a finite element discretization and two different free-surface methods, an arbitrary-Lagrangian-Eulerian (ALE) moving mesh implementation and an Eulerian level set method, to understand the moving boundary problem associated with the polymer-polymer interface. The goal of this work is to have a numerical capability suitable for optimizing and troubleshooting the coextrusion process, circumventing flow instabilities such as ribbing and barring, and reducing variability in layer thickness. Though these instabilities can be both viscous and elastic in nature, for this work a generalized Newtonian description of the fluid is used. Models of varying degrees of complexity are investigated including stability analysis and direct three-dimensional finite element free surface approaches. The results of this work show how critical modeling can be to reduce build test cycles, improve material choices, and guide mold design.
Nano-imprinting is an increasingly popular method of creating structured, nanometer scale patterns on a variety of surfaces. Applications are numerous, including non-volatile memory devices, printed flexible circuits, light-management films for displays and sundry energy-conversion devices. While there have been many extensive studies of fluid transport through the individual features of a pattern template, computational models of the entire machine-scale process, where features may number in the trillions per square inch, are currently computationally intractable. In this presentation we discuss a multiscale model aimed at addressing machine-scale issues in a nano-imprinting process. Individual pattern features are coarse-grained and represented as a structured porous medium, and the entire process is modeled using lubrication theory in a two-dimensional finite element method simulation. Machine pressures, optimal initial liquid distributions, pattern fill fractions (shown in figure 1), and final coating distributions of a typical process are investigated. This model will be of interest to those wishing to understand and carefully design the mechanics of nano-imprinting processes.
Controlled assembly in soft-particle colloidal suspensions is a technology poised to advance manufacturing methods for nano-scale templating, coating, and bio-conjugate devices. Applications for soft-particle colloids include photovoltaics, nanoelectronics, functionalized thin-film coatings, and a wide range of bio-conjugate devices such as sensors, assays, and bio-fuel cells. This presentation covers the topics of modeling and simulation of soft-particle colloidal systems over dewetting, evaporation, and irradiation gradients, including deposition of particles to surfaces. By tuning particle/solvent and environmental parameters, we transition from the regime of self-assembly to that of controlled assembly, and enable finer resolution of features at both the nano-scale and meso-scale. We report models of interparticle potentials and order parametrization techniques including results from simulations of colloids utilizing soft-particle field potentials. Using LAMMPS (Large-Scale Atomic/Molecular Massively Parallel Simulator), we demonstrate effects of volume fraction, shear and drag profiles, adsorbed and bulk polymer parameters, solvent chi parameter, and deposition profiles. Results are compared to theoretical models and correlation to TEM images from soft-particle irradiation experiments.
Heightened interest in micro-scale and nano-scale patterning by imprinting, embossing, and nano-particulate suspension coating stems from a recent surge in development of higher-throughput manufacturing methods for integrated devices. Energy-applications addressing alternative, renewable energy sources offer many examples of the need for improved manufacturing technology for micro and nano-structured films. In this presentation we address one approach to micro- and nano-pattering coating using film deposition and differential wetting of nanoparticles suspensions. Rather than print nanoparticle or colloidal inks in discontinuous patches, which typically employs ink jet printing technology, patterns can be formed with controlled dewetting of a continuously coated film. Here we report the dynamics of a volatile organic solvent laden with nanoparticles dispensed on the surfaces of water droplets, whose contact angles (surface energy) and perimeters are defined by lithographic patterning of initially (super)hydrophobic surfaces.. The lubrication flow equation together with averaged particle transport equation are employed to predict the film thickness and particle average concentration profiles during subsequent drying of the organic and water solvents. The predictions are validated by contact angle measurements, in situ grazing incidence small angle x-ray scattering experiments, and TEM images of the final nanoparticle assemblies.
When a fluid jet impinges on a solid substrate, a variety of behaviors may occur around the impact region. One example is mounding, where the fluid enters the impact region faster than it can flow away, forming a mound of fluid above the main surface. For some operating conditions, this mound can destabilize and buckle, entraining air in the mound. Other behaviors include submerging flow, where the jet impinges into an otherwise steady pool of liquid, entraining a thin air layer as it enters the pool. This impact region is one of very high shear rates and as such, complex fluids behave very differently than do Newtonian fluids. In this work, we attempt to characterize this range of behavior for Newtonian and non-Newtonian fluids using dimensionless parameters. We model the fluid as a modified Bingham-Carreau-Yasuda fluid, which exhibits the full range of pseudoplastic flow properties throughout the impact region. Additionally, we study viscoelastic effects through the use of the Giesekus model. Both 2-D and 3-D numerical simulations are performed using a variety of finite element method techniques for tracking the jet interface, including Arbitrary Lagrangian Eulerian (ALE), diffuse level sets, and a conformal decomposition finite element method (CDFEM). The presence of shear-thinning characteristics drastically reduces unstable mounding behavior, yet can lead to air entrainment through the submerging flow regime. We construct an operating map to understand for what flow parameters mounding and submerging flows will occur, and how the fluid rheology affects these behaviors. This study has many implications in high-speed industrial bottle filling applications.
In this presentation we examine the accuracy and performance of a suite of discrete-element-modeling approaches to predicting equilibrium and dynamic rheological properties of polystyrene suspensions. What distinguishes each approach presented is the methodology of handling the solvent hydrodynamics. Specifically, we compare stochastic rotation dynamics (SRD), fast lubrication dynamics (FLD) and dissipative particle dynamics (DPD). Method-to-method comparisons are made as well as comparisons with experimental data. Quantities examined are equilibrium structure properties (e.g. pair-distribution function), equilibrium dynamic properties (e.g. short- and long-time diffusivities), and dynamic response (e.g. steady shear viscosity). In all approaches we deploy the DLVO potential for colloid-colloid interactions. Comparisons are made over a range of volume fractions and salt concentrations. Our results reveal the utility of such methods for long-time diffusivity prediction can be dubious in certain ranges of volume fraction, and other discoveries regarding the best formulation to use in predicting rheological response.
The objective of the experimental effort is to provide a model particle system that will enable modeling of the macroscopic rheology from the interfacial and environmental structure of the particles and solvent or melt as functions of applied shear and volume fraction of the solid particles. This chapter describes the choice of the model particle system, methods for synthesis and characterization, and results from characterization of colloidal dispersion, particle film formation, and the shear and oscillatory rheology in the system. Surface characterization of the grafted PDMS interface, dispersion characterization of the colloids, and rheological characterization of the dispersions as a function of volume fraction were conducted.
Nanoparticles are now more than ever being used to tailor materials function and performance in differentiating technologies because of their profound effect on thermo-physical, mechanical and optical properties. The most feasible way to disperse particles in a bulk material or control their packing at a substrate is through fluidization in a carrier, followed by solidification through solvent evaporation/drying/curing/sintering. Unfortunately processing particles as concentrated, fluidized suspensions into useful products remains an art largely because the effect of particle shape and volume fraction on fluidic properties and suspension stability remains unexplored in a regime where particle-particle interaction mechanics is prevalent. To achieve a stronger scientific understanding of the factors that control nanoparticle dispersion and rheology we have developed a multiscale modeling approach to bridge scales between atomistic and molecular-level forces active in dense nanoparticle suspensions. At the largest length scale, two 'coarse-grained' numerical techniques have been developed and implemented to provide for high-fidelity numerical simulations of the rheological response and dispersion characteristics typical in a processing flow. The first is a coupled Navier-Stokes/discrete element method in which the background solvent is treated by finite element methods. The second is a particle based method known as stochastic rotational dynamics. These two methods provide a new capability representing a 'bridge' between the molecular scale and the engineering scale, allowing the study of fluid-nanoparticle systems over a wide range of length and timescales as well as particle concentrations. To validate these new methodologies, multi-million atoms simulations explicitly including the solvent have been carried out. These simulations have been vital in establishing the necessary 'subgrid' models for accurate prediction at a larger scale and refining the two coarse-grained methodologies.