Advances in printed electronics are predicated on the integration of sophisticated printing technologies with functional materials. Although scalable manufacturing methods, such as letterpress and flexographic printing, have significant history in graphic arts printing, functional applications require sophisticated control and understanding of nanoscale transfer of fluid inks. Herein, a versatile platform is introduced to study and engineer printing forms, exploiting a microscale additive manufacturing process to design micro-architected materials with controllable porosity and deformation. Building on this technology, controlled ink transfer for submicron functional films is demonstrated. The design freedom and high-resolution 3D control afforded by this method provide a rich framework for studying mechanics of fluid transfer for advanced manufacturing processes.
Cochrane, Andrew; Tjiptowidjojo, Kristianto; Bonnecaze, Roger T.; Schunk, Randy
The inextensible cylindrical shell theory and lubrication theory combine into a model for the elastohydrodynamics of a rolling-imprint modality of nanoimprint lithography (NIL). Foil-bearing theory describes the formation of the lubrication gap due to relative motion between a tensioned substrate and a rigid, cylindrical surface. Reproduction of the results of foil-bearing theory for both stiff and perfectly flexible substrates validates this coupled model and reveals a highly predictable region of uniformity that provides low shear stress conditions ideal for UV-cure. These results show theoretical limitations that are used to construct an operating window for predicting rolling-mode NIL process feasibility.
Additive Manufacturing (AM) can create novel and complex engineered material structures. Features such as controlled porosity, micro-fibers and/or nano-particles, transitions in materials and integral robust coatings can be important in developing solutions for fusion subcomponents. A realistic understanding of this capability would be particularly valuable in identifying development paths. Major concerns for using AM processes with lasers or electron beams that melt powder to make refractory parts are the power required and residual stresses arising in fabrication. A related issue is the required combination of lasers or e-beams to continue heating of deposited material (to reduce stresses) and to deposit new material at a reasonable built rate while providing adequate surface finish and resolution for meso-scale features. Some Direct Write processes that can make suitable preforms and be cured to an acceptable density may offer another approach for PFCs.
Electrical conductivity is key to the performance of thermal battery cathodes. In this work we present the effects of manufacturing and processing conditions on the electrical conductivity of Li/FeS2 thermal battery cathodes. We use finite element simulations to compute the conductivity of three-dimensional microcomputed tomography cathode microstructures and compare results to experimental impedance spectroscopy measurements. A regression analysis reveals a predictive relationship between composition, processing conditions, and electrical conductivity; a trend which is largely erased after thermally-induced deformation. The trend applies to both experimental and simulation results, although is not as apparent in simulations. This research is a step toward a more fundamental understanding of the effects of processing and composition on thermal battery component microstructure, properties, and performance.
A Galerkin/least-squares stabilization technique is applied to a discrete Elastic Viscous Stress Splitting formulation of for viscoelastic flow. From this, a possible viscoelastic stabilization method is proposed. This method is tested with the flow of an Oldroyd-B fluid past a rigid cylinder, where it is found to produce inaccurate drag coefficients. Furthermore, it fails for relatively low Weissenberg number indicating it is not suited for use as a general algorithm. In addition, a decoupled approach is used as a way separating the constitutive equation from the rest of the system. A Pressure Poisson equation is used when the velocity and pressure are sought to be decoupled, but this fails to produce a solution when inflow/outflow boundaries are considered. However, a coupled pressure-velocity equation with a decoupled constitutive equation is successful for the flow past a rigid cylinder and seems to be suitable as a general-use algorithm.
This report summarizes progress from the Laboratory Directed Research and Development (LDRD) program during fiscal year 2014. In addition to the programmatic and financial overview, the report includes progress reports from 419 individual R&D projects in 16 categories. Information for 176 projects in their final year is presented in a more comprehensive format, while for those 243 in their pre-final years, only an abstract is presented herein.
This document describes the form and use of three supplemental capabilities added to Goma during 1998 -- augmenting conditions, automatic continuation and linear stability analysis. Augmenting conditions allow the addition of constraints and auxiliary conditions which describe the relationship between unknowns, boundary conditions, material properties and post-processing extracted quantities. Automatic continuation refers to a family of algorithms (zeroth and first order here, single and multi-parameter) that allow tracking steady-state solution paths as material parameters or boundary conditions are varied. The stability analysis capability in Goma uses the method of small disturbances and superposition of normal modes to test the stability of a steady- state flow, i.e., it determines if the disturbance grows or decays in time.
Li/FeS2 thermal batteries provide a stable, robust, and reliable power source capable of long-term electrical energy storage without performance degradation. These systems rely on the electrical conductivity of FeS2 cathodes for critical performance parameters such as power and lifetime, and on permeability of the electrolyte through the solid FeS2 particles for ion transfer. The effects of component composition, manufacturing conditions, and the mechanical deformation on conductivity and permeability have not been studied. We present simulation results from a finite element computer model compared with impedance spectroscopy electrical conductivity experiments. Our methods elucidate the combined effects of slumping, particle size distribution, composition, and pellet density on properties related to electrical conduction in Li/FeS2 thermal battery cathodes.
This research project has the objective to extend the range of application, improve the efficiency and conduct simulations with the Fast Lubrication Dynamics (FLD) algorithm for concentrated particle suspensions in a Newtonian fluid solvent. The research involves a combination of mathematical development, new computational algorithms, and application to processing flows of relevance in materials processing. The mathematical developments clarify the underlying theory, facilitate verification against classic monographs in the field and provide the framework for a novel parallel implementation optimized for an OpenMP shared memory environment. The project considered application to consolidation flows of major interest in high throughput materials processing and identified hitherto unforeseen challenges in the use of FLD in these applications. Extensions to the algorithm have been developed to improve its accuracy in these applications.
We present a review and critique of several methods for the simulation of the dynamics of colloidal suspensions at the mesoscale. We focus particularly on simulation techniques for hydrodynamic interactions, including implicit solvents (Fast Lubrication Dynamics, an approximation to Stokesian Dynamics) and explicit/particle-based solvents (Multi-Particle Collision Dynamics and Dissipative Particle Dynamics). Several variants of each method are compared quantitatively for the canonical system of monodisperse hard spheres, with a particular focus on diffusion characteristics, as well as shear rheology and microstructure. In all cases, we attempt to match the relevant properties of a well-characterized solvent, which turns out to be challenging for the explicit solvent models. Reasonable quantitative agreement is observed among all methods, but overall the Fast Lubrication Dynamics technique shows the best accuracy and performance. We also devote significant discussion to the extension of these methods to more complex situations of interest in industrial applications, including models for non-Newtonian solvent rheology, non-spherical particles, drying and curing of solvent and flows in complex geometries. This work identifies research challenges and motivates future efforts to develop techniques for quantitative, predictive simulations of industrially relevant colloidal suspension processes.
Temperature histories on the surface of a body that has been subjected to a rapid, highenergy surface deposition process can be di cult to determine, especially if it is impossible to directly observe the surface or attach a temperature sensor to it. In this report, we explore two methods for estimating the temperature history of the surface through the use of a sensor embedded within the body very near to the surface. First, the maximum sensor temperature is directly correlated with the peak surface temperature. However, it is observed that the sensor data is both delayed in time and greatly attenuated in magnitude, making this approach unfeasible. Secondly, we propose an algorithm that involves tting the solution to a one-dimensional instantaneous energy solution problem to both the sensor data and to the results of a one-dimensional CVFEM code. This algorithm is shown to be able to estimate the surface temperature 20 C.
Ductile metals and other materials typically deform plastically under large applied loads; a behavior most often modeled using plastic deformation constitutive models. However, it is possible to capture some of the key behaviors of plastic deformation using only the framework for nonlinear elastic mechanics. In this paper, we develop a phenomenological, hysteretic, nonlinear elastic constitutive model that captures many of the features expected of a plastic deformation model. This model is based on calculating a secant modulus directly from a materials stress-strain curve. Scalar stress and strain values are obtained in three dimensions by using the von Mises invariants. Hysteresis is incorporated by tracking an additional history variable and assuming an elastic unloading response. This model is demonstrated in both single- and multi-element simulations under varying strain conditions.
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.
This paper presents continuum simulations of viscous polymer flow during nanoimprint lithography (NIL) for embossing tools having irregular spacings and sizes. Simulations varied non-uniform embossing tool geometry to distinguish geometric quantities governing cavity filling order, polymer peak deformation, and global mold filling times. A characteristic NIL velocity predicts cavity filling order. In general, small cavities fill more quickly than large cavities, while cavity spacing modulates polymer deformation mode. Individual cavity size, not total filling volume, dominates replication time, with large differences in individual cavity size resulting in non-uniform, squeeze flow filling. High density features can be modeled as a solid indenter in squeeze flow to accurately predict polymer flow and allow for optimization of wafer-scale replication. The present simulations make it possible to design imprint templates capable of distributing pressure evenly across the mold surface and facilitating symmetric polymer flow over large areas to prevent mold deformation and non-uniform residual layer thickness.
This paper presents continuum simulations of polymer flow during nanoimprint lithography (NIL). The simulations capture the underlying physics of polymer flow from the nanometer to millimeter length scale and examine geometry and thermophysical process quantities affecting cavity filling. Variations in embossing tool geometry and polymer film thickness during viscous flow distinguish different flow driving mechanisms. Three parameters can predict polymer deformation mode: cavity width to polymer thickness ratio, polymer supply ratio, and Capillary number. The ratio of cavity width to initial polymer film thickness determines vertically or laterally dominant deformation. The ratio of indenter width to residual film thickness measures polymer supply beneath the indenter which determines Stokes or squeeze flow. The local geometry ratios can predict a fill time based on laminar flow between plates, Stokes flow, or squeeze flow. Characteristic NIL capillary number based on geometry-dependent fill time distinguishes between capillary or viscous driven flows. The three parameters predict filling modes observed in published studies of NIL deformation over nanometer to millimeter length scales. The work seeks to establish process design rules for NIL and to provide tools for the rational design of NIL master templates, resist polymers, and process parameters.
This SAND report describes progress made during a Sandia National Laboratories sponsored graduate fellowship. The fellowship was funded through an LDRD proposal. The goal of this project is development and characterization of mixing strategies for polymeric microfluidic devices. The mixing strategies under investigation include electroosmotic flow focusing, hydrodynamic focusing, physical constrictions and porous polymer monoliths. For electroosmotic flow focusing, simulations were performed to determine the effect of electroosmotic flow in a microchannel with heterogeneous surface potential. The heterogeneous surface potential caused recirculations to form within the microchannel. These recirculations could then be used to restrict two mixing streams and reduce the characteristic diffusion length. Maximum mixing occurred when the ratio of the mixing region surface potential to the average channel surface potential was made large in magnitude and negative in sign, and when the ratio of the characteristic convection time to the characteristic diffusion time was minimized. Based on these results, experiments were performed to evaluate the manipulation of surface potential using living-radical photopolymerization. The material chosen to manipulate typically exhibits a negative surface potential. Using living-radical surface grafting, a positive surface potential was produced using 2-(Dimethylamino)ethyl methacrylate and a neutral surface was produced using a poly(ethylene glycol) surface graft. Simulations investigating hydrodynamic focusing were also performed. For this technique, mixing is enhanced by using a tertiary fluid stream to constrict the two mixing streams and reduce the characteristic diffusion length. Maximum mixing occurred when the ratio of the tertiary flow stream flow-rate to the mixing streams flow-rate was maximized. Also, like the electroosmotic focusing mixer, mixing was also maximized when the ratio of the characteristic convection time to the characteristic diffusion time was minimized. Physical constrictions were investigated through simulations. The results show that the maximum mixing occurs when the height of the mixing region is minimized. Finally, experiments were performed to determine the effectiveness of using porous polymer monoliths to enhance mixing. The porous polymer monoliths were constructed using a monomer/salt paste. Two salt crystal size ranges were used; 75 to 106 microns and 53 to 180 microns. Mixing in the porous polymer monoliths fabricated with the 75 to 106 micron salt crystal size range was six times higher than a channel without a monolith. Mixing in the monolith fabricated with the 53 to 180 micron salt crystal size range was nine times higher.
This article presents continuum simulations of viscous polymer flow during nanoimprint lithography (NIL) for embossing tools having irregular spacings and sizes. Simulations vary nonuniform embossing tool geometry to distinguish geometric quantities governing cavity filling order, polymer peak deformation, and global mold filling times. A characteristic NIL velocity predicts cavity filling order. In general, small cavities fill more quickly than large cavities, while cavity spacing modulates polymer deformation mode. Individual cavity size, not total filling volume, dominates replication time, with large differences in individual cavity size resulting in nonuniform, squeeze flow filling. High density features can be modeled as a solid indenter in squeeze flow to accurately predict polymer flow and allow for optimization of wafer-scale replication. The present simulations make it possible to design imprint templates capable of distributing pressure evenly across the mold surface and facilitating symmetric polymer flow over large areas to prevent mold deformation and nonuniform residual layer thickness.
This paper presents continuum simulations of polymer flow during nanoimprint lithography (NIL). The simulations capture the underlying physics of polymer flow from the nanometer to millimeter length scale and examine geometry and thermophysical process quantities affecting cavity filling. Variations in embossing tool geometry and polymer film thickness during viscous flow distinguish different flow driving mechanisms. Three parameters can predict polymer deformation mode: cavity width to polymer thickness ratio, polymer supply ratio and capillary number. The ratio of cavity width to initial polymer film thickness determines vertically or laterally dominant deformation. The ratio of indenter width to residual film thickness measures polymer supply beneath the indenter which determines Stokes or squeeze flow. The local geometry ratios can predict a fill time based on laminar flow between plates, Stokes flow, or squeeze flow. A characteristic NIL capillary number based on geometry-dependent fill time distinguishes between capillary- or viscous-driven flows. The three parameters predict filling modes observed in published studies of NIL deformation over nanometer to millimeter length scales. The work seeks to establish process design rules for NIL and to provide tools for the rational design of NIL master templates, resist polymers and process parameters.
This report summarizes research advances pursued with award funding issued by the DOE to Drexel University through the Presidential Early Career Award (PECASE) program. Professor Rich Cairncross was the recipient of this award in 1997. With it he pursued two related research topics under Sandia's guidance that address the outstanding issue of fluid-structural interactions of liquids with deformable solid materials, focusing mainly on the ubiquitous dynamic wetting problem. The project focus in the first four years was aimed at deriving a predictive numerical modeling approach for the motion of the dynamic contact line on a deformable substrate. A formulation of physical model equations was derived in the context of the Galerkin finite element method in an arbitrary Lagrangian/Eulerian (ALE) frame of reference. The formulation was successfully integrated in Sandia's Goma finite element code and tested on several technologically important thin-film coating problems. The model equations, the finite-element implementation, and results from several applications are given in this report. In the last year of the five-year project the same physical concepts were extended towards the problem of capillary imbibition in deformable porous media. A synopsis of this preliminary modeling and experimental effort is also discussed.
Solidification and blood flow seemingly have little in common, but each involves a fluid in contact with a deformable solid. In these systems, the solid-fluid interface moves as the solid advects and deforms, often traversing the entire domain of interest. Currently, these problems cannot be simulated without innumerable expensive remeshing steps, mesh manipulations or decoupling the solid and fluid motion. Despite the wealth of progress recently made in mechanics modeling, this glaring inadequacy persists. We propose a new technique that tracks the interface implicitly and circumvents the need for remeshing and remapping the solution onto the new mesh. The solid-fluid boundary is tracked with a level set algorithm that changes the equation type dynamically depending on the phases present. This novel approach to coupled mechanics problems promises to give accurate stresses, displacements and velocities in both phases, simultaneously.
Encapsulation is a common process used in manufacturing most non-nuclear components including: firing sets, neutron generators, trajectory sensing signal generators (TSSGs), arming, fusing and firing devices (AF and Fs), radars, programmers, connectors, and batteries. Encapsulation is used to contain high voltage, to mitigate stress and vibration and to protect against moisture. The purpose of the ASCI Encapsulation project is to develop a simulation capability that will allow us to aid in the encapsulation design process, especially for neutron generators. The introduction of an encapsulant poses many problems because of the need to balance ease of processing and properties necessary to achieve the design benefits such as tailored encapsulant properties, optimized cure schedule and reduced failure rates. Encapsulants can fail through fracture or delamination as a result of cure shrinkage, thermally induced residual stresses, voids or incomplete component embedding and particle gradients. Manufacturing design requirements include (1) maintaining uniform composition of particles in order to maintain the desired thermal coefficient of expansion (CTE) and density, (2) mitigating void formation during mold fill, (3) mitigating cure and thermally induced stresses during cure and cool down, and (4) eliminating delamination and fracture due to cure shrinkage/thermal strains. The first two require modeling of the fluid phase, and it is proposed to use the finite element code GOMA to accomplish this. The latter two require modeling of the solid state; however, ideally the effects of particle distribution would be included in the calculations, and thus initial conditions would be set from GOMA predictions. These models, once they are verified and validated, will be transitioned into the SIERRA framework and the ARIA code. This will facilitate exchange of data with the solid mechanics calculations in SIERRA/ADAGIO.
Living systems exhibit form and function on multiple length scales and at multiple locations. In order to mimic such natural structures, it is necessary to develop efficient strategies for assembling hierarchical materials. Conventional photolithography, although ubiquitous in the fabrication of microelectronics and microelectromechanical systems, is impractical for defining feature sizes below 0.1 micrometres and poorly suited to pattern chemical functionality. Recently, so-called 'soft' lithographic approaches have been combined with surfactant and particulate templating procedures to create materials with multiple levels of structural order. But the materials thus formed have been limited primarily to oxides with no specific functionality, and the associated processing times have ranged from hours to days. Here, using a self-assembling 'ink', we combine silica-surfactant self-assembly with three rapid printing procedures-pen lithography, ink-jet printing, and dip-coating of patterned self-assembled monolayers-to form functional, hierarchically organized structures in seconds. The rapid-prototyping procedures we describe are simple, employ readily available equipment, and provide a link between computer-aided design and self-assembled nanostructures. We expect that the ability to form arbitrary functional designs on arbitrary surfaces will be of practical importance for directly writing sensor arrays and fluidic or photonic systems.