Multiscale constitutive modeling of polymer materials

Materials are inherently multi-scale in nature consisting of distinct characteristics at various length scales from atoms to bulk material. There are no widely accepted predictive multi-scale modeling techniques that span from atomic level to bulk relating the effects of the structure at the nanometer (10-9 meter) on macro-scale properties. Traditional engineering deals with treating matter as continuous with no internal structure. In contrast to engineers, physicists have dealt with matter in its discrete structure at small length scales to understand fundamental behavior of materials. Multiscale modeling is of great scientific and technical importance as it can aid in designing novel materials that will enable us to tailor properties specific to an application like multi-functional materials. Polymer nanocomposite materials have the potential to provide significant increases in mechanical properties relative to current polymers used for structural applications. The nanoscale reinforcements have the potential to increase the effective interface between the reinforcement and the matrix by orders of magnitude for a given reinforcement volume fraction as relative to traditional micro- or macro-scale reinforcements. To facilitate the development of polymer nanocomposite materials, constitutive relationships must be established that predict the bulk mechanical properties of the materials as a function of the molecular structure. A computational hierarchical multiscale modeling technique is developed to study the bulk-level constitutive behavior of polymeric materials as a function of its molecular chemistry. Various parameters and modeling techniques from computational chemistry to continuum mechanics are utilized for the current modeling method. The cause and effect relationship of the parameters are studied to establish an efficient modeling framework. The proposed methodology is applied to three different polymers and validated using experimental data available in literature.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

CHARACTERIZATION OF ASPHALT MATERIALS CONTAINING BIO OIL FROM MICHIGAN WOOD

The objective of this research is to develop sustainable wood-blend bioasphalt and characterize the atomic, molecular and bulk-scale behavior necessary to produce advanced asphalt paving mixtures. Bioasphalt was manufactured from Aspen, Basswood, Red Maple, Balsam, Maple, Pine, Beech and Magnolia wood via a 25 KWt fast-pyrolysis plant at 500 °C and refined into two distinct end forms - non-treated (5.54% moisture) and treated bioasphalt (1% moisture). Michigan petroleum-based asphalt, Performance Grade (PG) 58-28 was modified with 2, 5 and 10% of the bioasphalt by weight of base asphalt and characterized with the gas chromatography-mass spectroscopy (GC-MS), Fourier Transform Infra-red (FTIR) spectroscopy and the automated flocculation titrimetry techniques. The GC-MS method was used to characterize the Carbon-Hydrogen-Nitrogen (CHN) elemental ratio whiles the FTIR and the AFT were used to characterize the oxidative aging performance and the solubility parameters, respectively. For rheological characterization, the rotational viscosity, dynamic shear modulus and flexural bending methods are used in evaluating the low, intermediate and high temperature performance of the bio-modified asphalt materials. 54 5E3 (maximum of 3 million expected equivalent standard axle traffic loads) asphalt paving mixes were then prepared and characterized to investigate their laboratory permanent deformation, dynamic mix stiffness, moisture susceptibility, workability and constructability performance. From the research investigations, it was concluded that: 1) levo, 2, 6 dimethoxyphenol, 2 methoxy 4 vinylphenol, 2 methyl 1-2 cyclopentandione and 4-allyl-2, 6 dimetoxyphenol are the dominant chemical functional groups; 2) bioasphalt increases the viscosity and dynamic shear modulus of traditional asphalt binders; 3) Bio-modified petroleum asphalt can provide low-temperature cracking resistance benefits at -18 °C but is susceptible to cracking at -24 °C; 3) Carbonyl and sulphoxide oxidation in petroleum-based asphalt increases with increasing bioasphalt modifiers; 4) bioasphalt causes the asphaltene fractions in petroleum-based asphalt to precipitate out of the solvent maltene fractions; 5) there is no definite improvement or decline in the dynamic mix behavior of bio-modified mixes at low temperatures; 6) bio-modified asphalt mixes exhibit better rutting performance than traditional asphalt mixes; 7) bio-modified asphalt mixes have lower susceptibility to moisture damage; 8) more field compaction energy is needed to compact bio-modified mixes.

Charge induced enhancement of adsorption for hydrogen storage materials

The rising concerns about environmental pollution and global warming have facilitated research interest in hydrogen energy as an alternative energy source. To apply hydrogen for transportations, several issues have to be solved, within which hydrogen storage is the most critical problem. Lots of materials and devices have been developed; however, none is able to meet the DOE storage target. The primary issue for hydrogen physisorption is a weak interaction between hydrogen and the surface of solid materials, resulting negligible adsorption at room temperature. To solve this issue, there is a need to increase the interaction between the hydrogen molecules and adsorbent surface. In this study, intrinsic electric dipole is investigated to enhance the adsorption energy. The results from the computer simulation of single ionic compounds with hydrogen molecules to form hydrogen clusters showed that electrical charge of substances plays an important role in generation of attractive interaction with hydrogen molecules. In order to further examine the effects of static interaction on hydrogen adsorption, activated carbon with a large surface area was impregnated with various ionic salts including LiCl, NaCl, KCl, KBr, and NiCl and their performance for hydrogen storage was evaluated by using a volumetric method. Corresponding computer simulations have been carried out by using DFT (Density Functional Theory) method combined with point charge arrays. Both experimental and computational results prove that the adsorption capacity of hydrogen and its interaction with the solid materials increased with electrical dipole moment. Besides the intrinsic dipole, an externally applied electric field could be another means to enhance hydrogen adsorption. Hydrogen adsorption under an applied electric field was examined by using porous nickel foil as electrodes. Electrical signals showed that adsorption capacity increased with the increasing of gas pressure and external electric voltage. Direct measurement of the amount of hydrogen adsorption was also carried out with porous nickel oxides and magnesium oxides using the piezoelectric material PMN-PT as the charge supplier due to the pressure. The adsorption enhancement from the PMN-PT generated charges is obvious at hydrogen pressure between 0 and 60 bars, where the hydrogen uptake is increased at about 35% for nickel oxide and 25% for magnesium oxide. Computer simulation reveals that under the external electric field, the electron cloud of hydrogen molecules is pulled over to the adsorbent site and can overlap with the adsorbent electrons, which in turn enhances the adsorption energy Experiments were also carried out to examine the effects of hydrogen spillover with charge induced enhancement. The results show that the overall storage capacity in nickel oxide increased remarkably by a factor of 4.

Advanced mechanics of materials with microstructure

The study of advanced materials aimed at improving human life has been performed since time immemorial. Such studies have created everlasting and greatly revered monuments and have helped revolutionize transportation by ushering the age of lighter–than–air flying machines. Hence a study of the mechanical behavior of advanced materials can pave way for their use for mankind’s benefit. In this school of thought, the aim of this dissertation is to broadly perform two investigations. First, an efficient modeling approach is established to predict the elastic response of cellular materials with distributions of cell geometries. Cellular materials find important applications in structural engineering. The approach does not require complex and time-consuming computational techniques usually associated with modeling such materials. Unlike most current analytical techniques, the modeling approach directly accounts for the cellular material microstructure. The approach combines micropolar elasticity theory and elastic mixture theory to predict the elastic response of cellular materials. The modeling approach is applied to the two dimensional balsa wood material. Predicted properties are in good agreement with experimentally determined properties, which emphasizes the model’s potential to predict the elastic response of other cellular solids, such as open cell and closed cell foams. The second topic concerns intraneural ganglion cysts which are a set of medical conditions that result in denervation of the muscles innervated by the cystic nerve leading to pain and loss of function. Current treatment approaches only temporarily alleviate pain and denervation which, however, does not prevent cyst recurrence. Hence, a mechanistic understanding of the pathogenesis of intraneural ganglion cysts can help clinicians understand them better and therefore devise more effective treatment options. In this study, an analysis methodology using finite element analysis is established to investigate the pathogenesis of intraneural ganglion cysts. Using this methodology, the propagation of these cysts is analyzed in their most common site of occurrence in the human body i.e. the common peroneal nerve. Results obtained using finite element analysis show good correlation with clinical imaging patterns thereby validating the promise of the method to study cyst pathogenesis.

Predicting the Mechanical Properties of Carbon-Based Materials Using Molecular Dynamics

The development of innovative carbon-based materials can be greatly facilitated by molecular modeling techniques. Although molecular modeling has been used extensively to predict elastic properties of materials, modeling of more complex phenomenon such as fracture has only recently been possible with the development of new force fields such as ReaxFF, which is used in this work. It is not fully understood what molecular modeling parameters such as thermostat type, thermostat coupling, time step, system size, and strain rate are required for accurate modeling of fracture. Selection of modeling parameters to model fracture can be difficult and non-intuitive compared to modeling elastic properties using traditional force fields, and the errors generated by incorrect parameters may be non-obvious. These molecular modeling parameters are systematically investigated and their effects on the fracture of well-known carbon materials are analyzed. It is determined that for coupling coefficients of 250 fs and greater do not result in substantial differences in the stress-strain response of the materials using any thermostat type. A time step of 0.5 fs of smaller is required for accurate results. Strain rates greater than 2.2 ns-1 are sufficient to obtain repeatable results with slower strain rates for the materials studied. The results of this study indicate that further refinement of the Chenoweth parameter set is required to accurately predict the mechanical response of carbon-based systems. The ReaxFF has been used extensively to model systems in which bond breaking and formation occur. In particular ReaxFF has been used to model reactions of small molecules. Some elastic and fracture properties have been successfully modeled using ReaxFF in materials such as silicon and some metals. However, it is not clear if current parameterizations for ReaxFF are able to accurately reproduce the elastic and fracture properties of carbon materials. The stress-strain response of a new ReaxFF parameterization is compared to the previous parameterization and density functional theory results for well-known carbon materials. The new ReaxFF parameterization makes xv substantial improvements to the predicted mechanical response of carbon materials, and is found to be suitable for modeling the mechanical response of carbon materials. Finally, a new material composed of carbon nanotubes within an amorphous carbon (AC) matrix is modeled using the ReaxFF. Various parameters that may be experimentally controlled are investigated such as nanotube bundling, comparing multi-walled nanotube with single-walled nanotubes, and degree of functionalization of the nanotubes. Elastic and fracture properties are investigated for the composite systems and compared to results of pure-nanotube and pure-AC models. It is found that the arrangement of the nanotubes and degree of crosslinking may substantially affect the properties of the systems, particularly in the transverse directions.