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Articles 1 - 8 of 8
Full-Text Articles in Physics
Development Of Interatomic Potential Of High Entropy Diborides With Artificial Intelligence Approach To Simulate The Thermo-Mechanical Properties, Nur Aziz Octoviawan
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
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 …
Review Of Current Reactive Force Field Potentials For Use In Simulating The Atomic Layer Deposition Of Alumina On Aluminum, Devon T. Romine
Review Of Current Reactive Force Field Potentials For Use In Simulating The Atomic Layer Deposition Of Alumina On Aluminum, Devon T. Romine
MSU Graduate Theses
Alumina has recently garnered quite a bit of attention for use as a tunnel barrier in Josephson tunnel junctions. The quality of the metal oxide layer in the Josephson tunnel junction is a key factor in its effectiveness. To optimize the deposition method of alumina, we need a deep understanding of the large-scale surface interactions that cannot be reached using ab initio molecular dynamics. In this study, I have compared two existing reactive force field (ReaxFF) parameters to determine their abilities to model the atomic layer deposition (ALD) of alumina on an aluminum surface. ReaxFF molecular dynamics was chosen because …
Characterization Of Nanoparticles Using Inductively-Coupled Plasma Mass Spectrometry, Jabez D. Campbell
Characterization Of Nanoparticles Using Inductively-Coupled Plasma Mass Spectrometry, Jabez D. Campbell
MSU Graduate Theses
Nanomaterials are a relatively new class of materials that have many applications which span a wide host of fields from medical products to consumer products. The possible compositions and forms of nanomaterials are just as varied as the applications. Therefore, a versatile characterization method is needed for researchers and regulators alike to ensure nanomaterials are properly used. Single Particle Inductively Coupled Plasma Mass Spectrometry (SP-ICP-MS) is a functional method that could fill the characterization need in the nanomaterial research field. Using data from both SP-ICP-MS tests and data from literature established characterization methods, the viability of making SP-ICP-MS the standard …
Applications Of A Combined Approach Of Kinetic Monte Carlo Simulations And Machine Learning To Model Atomic Layer Deposition (Ald) Of Metal Oxides, Emily Justus
MSU Graduate Theses
Metal-oxides such as ZnO or Al2O3 synthesized through Atomic Layer Deposition (ALD) have been of great research interest as the candidate materials for ultra-thin tunnel barriers. In this study, I have applied a 3D on-lattice Kinetic Monte Carlo (kMC) code developed by Timo Weckman’s group to simulate the growth mechanisms of the tunnel barrier layer and to evaluate the role of various experimentally relevant factors in the ALD processes. I have systematically studied the effect of parameters such as the chamber pressure temperature, pulse, and purge times. The database generated from the kMC simulations was subsequently used …
Modeling Of Argon Bombardment And Densification Of Low Temperature Organic Precursors Using Reactive Md Simulations And Machine Learning, Kwabena Asante-Boahen
Modeling Of Argon Bombardment And Densification Of Low Temperature Organic Precursors Using Reactive Md Simulations And Machine Learning, Kwabena Asante-Boahen
MSU Graduate Theses
In this study, an important aspect of the synthesis process for a-BxC:Hy was systematically modeled by utilizing the Reactive Molecular Dynamics (MD) in modeling the argon bombardment from the orthocarborane molecules as the precursor. The MD simulations are used to assess the dynamics associated with the free radicals that result from the ion bombardment. By applying the Data Mining/Machine Learning analysis into the datasets generated from the large reactive MD simulations, I was able to identify and quality the kinetics of these radicals. Overall, this approach allows for a better understanding of the overall mechanism at the atomistic level of …
Kinetic Monte Carlo Investigations Involving Atomic Layer Deposition Of Metal-Oxide Thinfilms, David Tyler Magness
Kinetic Monte Carlo Investigations Involving Atomic Layer Deposition Of Metal-Oxide Thinfilms, David Tyler Magness
MSU Graduate Theses
Atomic Layer Deposition is a method of manufacturing thin film materials. Metal-oxides such as zinc-oxide and aluminum-oxide are particularly interesting candidates for use in microelectronic devices such as tunnel junction barriers, transistors, Schottky diodes, and more. By adopting a 3D Kinetic Monte Carlo model capable of simulating ZnO deposition, the effect of parameters including deposition temperature, chamber pressure, and composition of the initial substrate at the beginning of deposition can be investigated. This code generates two random numbers: One is used to select a chemical reaction to occur from a list of all possible reactions and the second is used …
Block-Copolymer Assisted Fabrication Of Anisotropic Plasmonic Nanostructures, Calbi J. Gunder
Block-Copolymer Assisted Fabrication Of Anisotropic Plasmonic Nanostructures, Calbi J. Gunder
MSU Graduate Theses
The anisotropic nanostructures of noble metals are of great interest for plasmonic applications due to the possibility of tuning the localized surface plasmon resonance (LSPR) across the UV-VIS-NIR without sacrificing the linewidth as well as to achieve larger local field enhancement. Here, we report a simple and promising fabrication method of anisotropic gold nanostructures film using polystyrene-b-2vinylpyridine (PS-b-P2VP) block copolymers (BCP) as a template. In this approach, PS-b-P2VP spherical micelles were first synthesized as a template followed by selective deposition of Au precursor inside P2VP core of the micelles using ethanol solution of Au salt. Subsequently, heat treatment of the …