Materials Science and Engineering Commons^™

Prediction Of Metal Sample Failure From Scanning Electron Microscope Images Using Deep Learning Neural Network, Lawrence Madriaga, Ivan Novikov, Morteza Nurcheshmeh

Posters-at-the-Capitol

We present the preliminary results on using a deep learning neural network to predict a metal sample failure based on a set of images obtained with a Scanning Electron Microscope.

Various metal alloy samples were prepared according to ASTM E8/E8M-11 standards for a tensile test. Each sample was prepared for circle grid analysis and then stressed on a tensile machine. Stress and strain values were obtained for each position along the sample by measuring dimensions of each elongated circle. Increasing stress and strain values were found closer to the breakage of the sample with low values found at the holding …

Creating A Computational Tool To Simulate Vibration Control For Piezoelectric Devices, Ahmet Ozkan Ozer, Emma J. Moore

Posters-at-the-Capitol

Piezoelectric materials have the unique ability to convert electrical energy to mechanical vibrations and vice versa. This project takes a stab to develop a reliable computational tool to simulate the vibration control of a novel “partial differential equation” model for a piezoelectric device, which is designed by integrating electric conducting piezoelectric layers constraining a viscoelastic layer to provide an active and lightweight intelligent structure. Controlling unwanted vibrations on piezoelectric devices (or harvesting energy from ambient vibrations) through piezoelectric layers has been the major focus in cutting-edge engineering applications such as ultrasonic welders and inchworms. The corresponding mathematical models for piezoelectric …

Two-Dimensional Layered Materials (Graphene-Mos2) Nanocatalysts For Hydrogen Production, Jacob Dobler, Taylor Robinson, Sanju Gupta 7455940

Posters-at-the-Capitol

Recent development of two-dimensional layered materials including graphene-family and related nanomaterials have arisen as potential game changer for energy, water and sensing applications. While graphene is a form of carbon arranged hexagonally within atomic thin sheet, MoS₂ is becoming a popular, efficient, and cost-effective catalyst for electrochemical energy devices, in contrast to expensive platinum and palladium catalysts. In this work, we electrochemically desulfurize few-layer molybdenum disulfide (MoS₂) and aerogels with reduced graphene oxide (rGO) prepared under hydrothermal conditions ((P< 20 bar, T< 200 ^oC), for improving hydrogen evolution reaction (HER) activity via point defects (S-vacancy). Moreover, the interactions between rGO …