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Generation Of Phase Transitions Boundaries Via Convolutional Neural Networks, Christopher Alexis Ibarra
Generation Of Phase Transitions Boundaries Via Convolutional Neural Networks, Christopher Alexis Ibarra
Open Access Theses & Dissertations
Accurate mapping of phase transitions boundaries is crucial in accurately modeling the equation of state of materials. The phase transitions can be structural (solid-solid) driven by temperature or pressure or a phase change like melting which defines the solid-liquid melt line. There exist many computational methods for evaluating the phase diagram at a particular point in temperature (T) and pressure (P). Most of these methods involve evaluation of a single (P,T) point at a time. The present work partially automates the search for phase boundaries lines utilizing a machine learning method based on convolutional neural networks and an efficient search …
Phonon Thermodynamics Of Bcc Zirconium With Machine Learning, Vanessa Judith Meraz
Phonon Thermodynamics Of Bcc Zirconium With Machine Learning, Vanessa Judith Meraz
Open Access Theses & Dissertations
First principles-based simulations have allowed us to explore emerging phenomena in a variety of systems. Its steadfast practicality has led to an increase in molecular and materials design ranging from drug discovery to planetary formation. However ubiquitous in its field, one of its biggest drawbacks is its computational cost, notably so in molecular dynamics simulations. To counter this setback, there have been many leading efforts in machine learning methods, whether it be in algorithms or network architectures. Our contribution uses an active learning algorithm paired with a tensor field network, e3nn. By steadily feeding new data points to our model, …