Assimina A. Pelegri

Nanoindentation Measurements on Low-k Porous Silica Thin Films Spin Coated on Silicon Substrates

MEMS (MicroElectromechanical Systems) are composed of thin films and composite nanomaterials. Although the mechanical properties of their constituent materials play an important role in controlling their quality, reliability, and lifetime, they are often found to be different from their bulk counterparts. In this paper low-k porous silica thin films spin coated on silicon substrates are studied. The roughness of spin-on coated porous silica films is analyzed with in-situ imaging and their mechanical properties are determined using nanoindentation. A Berkovich type nanoindenter, of a 142.3 deg total included angle, is used and continuous measurements of force and displacements are acquired. It is shown, that the measured results of hardness and Youngs modulus of these films depend on penetration depth. Furthermore, the films mechanical properties are influenced by the properties of the substrate, and the reproduction of the force versus displacement curves depends on the quality of the thin film. The hardness of the studied low-k spin coated silica thin film is measured as 0.35∼0.41 GPa and the Youngs modulus is determined as 2.74∼2.94 GPa.

Mechanical Characterization of Thin Film Materials with Nanoindentation Measurements and FE Analysis

The quantitative study of mechanical properties at nanoscale is motivated by the increasing demand for miniaturization of engineering and electronic components, development of nanostructured materials, thin film technology, and surface science. There are only a few existing, or projected, technologies for conducting such measurements at nanoscale structures, and nanoindentation is the leading candidate. Finite elements (FE) provide a numerical method to calculate the indentation problem. In this article, the mechanical properties of a thin film material system, namely thermally oxidized silicon grown on silicon substrate, SiO2/Si, is characterized with nanoindentation measurements and calculated via FE analysis. Infinite elements in FE nanoindentation analysis are employed to allow for actual specimen size simulation and produce accurate results. It is concluded that the nanoindentation measurements coupled with the proposed FE analysis provide precise mechanical characterization of the tested thin films. For the featured thermally oxidized silicon grown on silicon substrate, the hardness and the reduced Young’s modulus are directly determined from Berkovich nanoindentation measurements as H 1/4 9.23 0.30 GPa and E 1/4 63.11 0.26 GPa, respectively. From the FE analysis, the following mechanical parameters are obtained: hardness, 10.63 GPa, Young’s modulus, 65.20 GPa, initial yield stress, 6.50 GPa, and Poisson’s ratio, 0.35. A FE analysis of a cube corner nanoindenter is also conducted and the results are compared to the Berkovich simulations.

A mechanical model to compute elastic modulus of tissues for harmonic motion imaging

Numerous experimental and computational methods have been developed to estimate tissue elasticity. The existing testing techniques are generally classified into in vitro, invasive in vivo and non-invasive in vivo. For each experimental method, a computational scheme is accordingly proposed to calculate mechanical properties of soft biological tissues. Harmonic motion imaging (HMI) is a new technique that performs radio frequency (RF) signal tracking to estimate the localized oscillatory motion resulting from a radiation force produced by focused ultrasound. A mechanical model and computational scheme based on the superposition principle are developed in this paper to estimate the Youngs modulus of a tissue mimicking phantom and bovine liver in vitro tissue from the harmonic displacement measured by HMI. The simulation results are verified by two groups of measurement data, and good agreement is shown in each comparison. Furthermore, an inverse function is observed to correlate the elastic modulus of uniform phantoms with amplitude of displacement measured in HMI. The computational scheme is also implemented to estimate 3D elastic modulus of bovine liver in vitro.

Optimization of Laminates’ Fracture Toughness Using Design of Experiments and Response Surface

Maximization of mode I critical delamination fracture toughness (G IC) in cross ply graphite–epoxy laminates is studied using Design of Experiments and Taguchi arrays. The novel methodology proposed allows continuous and discrete factors to be considered simultaneously. Main and interactive factor effects on G IC are evaluated. Selection of factors is based on design and material criteria; the ones considered are: width, length, thickness, stacking angle and stacking sequence. A Fractional Factorial experiment is used to reduce the number of tests. Double Cantilever Beam specimens are used for all mode I experiments. Statistically significant factors are culled and a response equation (RE), based on the importance of each factor, is established. The RE is then employed to optimize G IC within the given set of restrictions. The effect of interfaces on delamination propagation is also investigated.

Approximate Analysis of the Buckling Behavior of Composites with Delamination

In this paper, we provide an insight into the governing mechanism of the uni-axial compressive bucklingof a delaminated composite. We propose an approximate method to analyze the bucklingbehavior as the first step to further investigate the effect of contact zone at the ends of a delamination. The agreement of the analytical results with experiments in critical values of relative axial displacement verifies our model and approach. The proposed method provides a simple and effective way to calculate the forces, moments and energy required for the processes of local and global buckling. Moreover, the effect of the thickness ratio, T/h, on the total strain energy can be studied in a continuous range of values, while other methods investigate this parametric effect discretely. The effect of delamination length and position in the buckling behavior are also investigated. The analytical results compare favorably with results of similar, but more elaborate, studies.

A Transition Model for Finite Element Simulation of Kinematics of Central Nervous System White Matter

Mechanical damage to axons is a proximal cause of deficits following traumatic brain injury and spinal cord injury. Axons are injured predominantly by tensile strain, and identifying the strain experienced by axons is a critical step toward injury prevention. White matter demonstrates complex nonlinear mechanical behavior at the continuum level that evolves from even more complex, dynamic, and composite behavior between axons and the “glial matrix” at the microlevel. In situ, axons maintain an undulated state that depends on the location of the white matter and the stage of neurodevelopment. When exposed to tissue strain, axons do not demonstrate pure affine or non-affine behavior, but instead transition from non-affine-dominated kinematics at low stretch levels to affine kinematics at high stretch levels. This transitional and predominant kinematic behavior has been linked to the natural coupling of axons to each other via the glial matrix. In this paper, a transitional kinematic model is applied to a micromechanics finite element model to simulate the axonal behavior within a white matter tissue subjected to uniaxial tensile stretch. The effects of the transition parameters and the volume fraction of axons on axonal behavior is evaluated and compared to previous experimental data and numerical simulations.

Dynamic Simulation of Viscoelastic Soft Tissue in Acoustic Radiation Force Creep Imaging

Acoustic radiation force (ARF) creep imaging applies step ARF excitation to induce creep displacement of soft tissue, and the corresponding time-dependent responses are used to estimate soft tissue viscoelasticity or its contrast. Single degree of freedom (SDF) and homogeneous analytical models have been used to characterize soft tissue viscoelasticity in ARF creep imaging. The purpose of this study is to investigate the fundamental limitations of the commonly used SDF and homogeneous assumptions in ARF creep imaging. In this paper, finite element (FE) models are developed to simulate the dynamic behavior of viscoelastic soft tissue subjected to step ARF. Both homogeneous and heterogeneous models are studied with different soft tissue viscoelasticity and ARF configurations. The results indicate that the SDF model can provide good estimations for homogeneous soft tissue with high viscosity, but exhibits poor performance for low viscosity soft tissue. In addition, a smaller focal region of the ARF is desirable to reduce the estimation error with the SDF models. For heterogeneous media, the responses of the focal region are highly affected by the local heterogeneity, which results in deterioration of the effectiveness of the SDF and homogeneous simplifications.

Multiscale modeling of matrix cracking coupled with interfacial debonding in random glass fiber composites based on volume elements

A multiscale numerical approach is established to model damage in random glass fiber composites. A representative volume element of a random glass fiber composite is employed to analyze microscale damage mechanisms, such as matrix cracking and fiber-matrix interfacial debonding, while the associated damage variables are defined and applied in a mesoscale stiffness reduction law. The macroscopic response of the homogenized mesoscale damage model is investigated using finite element analysis and validated through experiments. A case study of a random glass fiber composite plate containing a central hole subjected to tensile loading is performed to illustrate the applicability of the multiscale damage model.

Finite Element Modeling of CNS White Matter Kinematics: Use of a 3D RVE to Determine Material Properties

Axonal injury represents a critical target area for the prevention and treatment of traumatic brain and spinal cord injuries. Finite element (FE) models of the head and/or brain are often used to predict brain injury caused by external mechanical loadings, such as explosive waves and direct impact. The accuracy of these numerical models depends on correctly determining the material properties and on the precise depiction of the tissues’ microstructure (microscopic level). Moreover, since the axonal microstructure for specific regions of the brain white matter is locally oriented, the stress, and strain fields are highly anisotropic and axon orientation dependent. Additionally, mechanical strain has been identified as the proximal cause of axonal injury, which further demonstrates the importance of this multi-scale relationship. In this study, our previously developed FE and kinematic axonal models are coupled and applied to a pseudo 3-dimensional representative volume element of central nervous system white matter to investigate the multi-scale mechanical behavior. An inverse FE procedure was developed to identify material parameters of spinal cord white matter by combining the results of uniaxial testing with FE modeling. A satisfactory balance between simulation and experiment was achieved via optimization by minimizing the squared error between the simulated and experimental force-stretch curve. The combination of experimental testing and FE analysis provides a useful analysis tool for soft biological tissues in general, and specifically enables evaluations of the axonal response to tissue-level loading and subsequent predictions of axonal damage.

Three-Dimensional Numerical Simulation of Random Fiber Composites With High Aspect Ratio and High Volume Fraction

Organic and inorganic fiber reinforced composites with various fiber orientation distributions and fiber geometries are abundantly available in several natural and synthetic structures. Inorganic glass fiber composites have been introduced to numerous applications due to their economical fabrication and tailored structural properties. Numerical characterization of such composite materials is necessitated due to their intrinsic statistical nature, since elaborate experiments are prohibitively costly and time consuming. In this work, representative volume elements of unidirectional random filaments and fibers are numerically developed in PYTHON to enhance accuracy and efficiency of complex geometric representations encountered in random fiber networks. A modified random sequential adsorption algorithm is applied to increase the volume fraction of the representative volume elements, and a spatial segment shortest distance algorithm is introduced to construct a 3D random fiber composite with high fiber aspect ratio (100:1) and high volume fraction (31.8%). For the unidirectional fiber networks, volume fractions as high as 70% are achieved when an assortment of circular fiber diameters are used in the representative volume element.