Engineering Commons^™

Molecular Dynamics Study Of Characterization In Metal-Free Friction Materials, Yizhan Zhang

Electronic Theses and Dissertations

Metallic friction materials currently used in industry may adversely impact the environment. Substitutions for metals in friction materials, on the other hand, can introduce operational safety issues and other unforeseeable issues such as thermal-mechanical instabilities and insufficient strength. In view of it, this dissertation focuses on developing different kinds of materials from simple structure to complex structure and evaluating the material properties with the assistance of molecular dynamics (MD) tools at the nano scale.

First, the concept of the contacted surfaces in friction at the atomic scale was introduced in order to get accurate understanding of the friction process compared …

Establishing Physical And Chemical Mechanisms Of Polymerization And Pyrolysis Of Phenolic Resins For Carbon-Carbon Composites, Ivan Gallegos, Josh Kemppainen, Jacob R. Gissinger, Malgorzata Kowalik, Adri Van Duin, Kristopher E. Wise, S. Gowtham, Gregory Odegard

Michigan Tech Publications, Part 2

The complex structural and chemical changes that occur during polymerization and pyrolysis critically affect material properties but are difficult to characterize in situ. This work presents a novel, experimentally validated methodology for modeling the complete polymerization and pyrolysis processes for phenolic resin using reactive molecular dynamics. The polymerization simulations produced polymerized structures with mass densities of 1.24 ± 0.01 g/cm3 and Young's moduli of 3.50 ± 0.64 GPa, which are in good agreement with experimental values. The structural properties of the subsequently pyrolyzed structures were also found to be in good agreement with experimental X-ray data for the phenolic-derived carbon …

Molecular Dynamic Studies Of Dye–Dye And Dye–Dna Interactions Governing Excitonic Coupling In Squaraine Aggregates Templated By Dna Holliday Junctions, German Barcenas, Austin Biaggne, Olga A. Mass, William B. Knowlton, Bernard Yurke, Lan Li

Materials Science and Engineering Faculty Publications and Presentations

Dye molecules, arranged in an aggregate, can display excitonic delocalization. The use of DNA scaffolding to control aggregate configurations and delocalization is of research interest. Here, we applied Molecular Dynamics (MD) to gain an insight on how dye–DNA interactions affect excitonic coupling between two squaraine (SQ) dyes covalently attached to a DNA Holliday junction (HJ). We studied two types of dimer configurations, i.e., adjacent and transverse, which differed in points of dye covalent attachments to DNA. Three structurally different SQ dyes with similar hydrophobicity were chosen to investigate the sensitivity of excitonic coupling to dye placement. Each dimer configuration was …

Probing Dna Structural Heterogeneity By Identifying Conformational Subensembles Of A Bicovalently Bound Cyanine Dye, Matthew S. Barclay, Azhad U. Chowdhury, Austin Biaggne, Jonathan S. Huff, Nicholas D. Wright, Paul H. Davis, Lan Li, William B. Knowlton, Bernard Yurke, Ryan D. Pensack, Daniel B. Turner

Materials Science and Engineering Faculty Publications and Presentations

DNA is a re-configurable, biological information-storage unit, and much remains to be learned about its heterogeneous structural dynamics. For example, while it is known that molecular dyes templated onto DNA exhibit increased photostability, the mechanism by which the structural dynamics of DNA affect the dye photophysics remains unknown. Here, we use femtosecond, two-dimensional electronic spectroscopy measurements of a cyanine dye, Cy5, to probe local conformations in samples of single-stranded DNA (ssDNA–Cy5), double-stranded DNA (dsDNA–Cy5), and Holliday junction DNA (HJ–DNA–Cy5). A line shape analysis of the 2D spectra reveals a strong excitation–emission correlation present in only the dsDNA–Cy5 complex, which is …

Study Of Nanocomposite Materials Using Molecular Dynamics, Prashik Sunil Gaikwad

Dissertations, Master's Theses and Master's Reports

There is an increase in demand for new lightweight structural materials in the aerospace industry for more efficient and affordable human space travel. Polymer matrix composites (PMCs) with reinforcement material as carbon nanotubes (CNTs) have shown exceptional increase in the mechanical properties. Flattened carbon nanotubes (flCNTs) are a primary component of many carbon nanotube (CNT) yarn and sheet materials, which are promising reinforcements for the next generation of ultra-strong composites for aerospace applications. These flCNT/polymer materials are subjected to extreme pressure and temperature during curing process. Therefore there is a need to investigate the evolution of properties during the curing …

Development Of Interatomic Potential Of High Entropy Diborides With Artificial Intelligence Approach To Simulate The Thermo-Mechanical Properties, Nur Aziz Octoviawan

MSU Graduate Theses

The interatomic potentials designed for binary/high entropy diborides and ultra-high temperature composites (UHTC) have been developed through the implementation of deep neural network (DNN) algorithms. These algorithms employed two different approaches and corresponding codes; 1) strictly local & invariant scalar-based descriptors as implemented in the DEEPMD code and 2) equivariant tensor-based descriptors as included in the ALLEGRO code. The samples for training and validation sets of the forces, energy, and virial data were obtained from the ab-initio molecular dynamics (AIMD) simulations and Density Functional Theory (DFT) calculations, including the simulation data from the ultra-high temperature region (> 2000K). The study …

Machine Learning Strategies For Potential Development In High-Entropy Driven Nickel-Based Superalloys, Marium Mostafiz Mou

MSU Graduate Theses

In this study, I developed Deep Learning interatomic potentials to model a multi-phase and multi-component system of Ni-based Superalloys. The system has up to three major phase constituents, namely Gamma, Gamma Prime, and Transition-metal rich Carbide. I utilized invariant scalar-based and/or equivariant, tensor-based neural network (NN) approach as implemented in DEEPMD, NEQUIP/ALLEGRO codes, respectively, and Moment Tensor Potential (MTP). For the training and validation sets, I employed the ab-initio molecular dynamics (AIMD) trajectory results and ground state DFT calculations, including the energy, force, and virial database from highly diverse compositions, temperatures, and pressures following a “High Entropy Strategy.” The Deep …