Physics Commons^™

Evolution Of Barred Galaxies In Spinning Dark Matter Halos: High Resolution N-Body Simulations At Dlx, Angela Collier, Isaac Shlosman, Clayton Heller

Commonwealth Computational Summit

Observations show that galaxies are dominated by stellar disks immersed in much more massive, slowly tumbling dark matter (DM) halos. Large fraction of galactic disks, at least 75%, are barred (see Hubble Fork on the right). Stellar bars form either via spontaneous break of axial symmetry or via galaxy interactions.

The formation and evolution of stellar bars is not fully understood. Stellar bar evolution is highly nonlinear and cannot be treated analytically. The main approach to study these disk-halo systems is via numerical simulations, whose goal is to explain why galaxies have such a wide range of morphologies as shown …

Optimization And Control Of Production Of Graphene, Atharva Hans, Nimish M. Awalgaonkar, Majed Alrefae, Ilias Bilionis, Timothy S. Fisher

The Summer Undergraduate Research Fellowship (SURF) Symposium

Graphene is a 2-dimensional element of high practical importance. Despite its exceptional properties, graphene’s real applications in industrial or commercial products have been limited. There are many methods to produce graphene, but none has been successful in commercializing its production. Roll-to-roll plasma chemical vapor deposition (CVD) is used to manufacture graphene at large scale. In this research, we present a Bayesian linear regression model to predict the roll-to-roll plasma system’s electrode voltage and current; given a particular set of inputs. The inputs of the plasma system are power, pressure and concentration of gases; hydrogen, methane, oxygen, nitrogen and argon. This …

Machine Learning In Xenon1t Analysis, Dillon A. Davis, Rafael F. Lang, Darryl P. Masson

The Summer Undergraduate Research Fellowship (SURF) Symposium

In process of analyzing large amounts of quantitative data, it can be quite time consuming and challenging to uncover populations of interest contained amongst the background data. Therefore, the ability to partially automate the process while gaining additional insight into the interdependencies of key parameters via machine learning seems quite appealing. As of now, the primary means of reviewing the data is by manually plotting data in different parameter spaces to recognize key features, which is slow and error prone. In this experiment, many well-known machine learning algorithms were applied to a dataset to attempt to semi-automatically identify known populations, …

Designing Novel Nanostructured Permanent Magnets, Ali Al Kadhim

UNO Student Research and Creative Activity Fair

Rare earth element based alloys have been the source of high performance magnetic alloys, and have played a paramount role in the development of various technologies, including: memory devices (such as credit cards, random-access memory), sensors, and various biomedical applications. However, there is a tremendous need to replace rare earth metals with material with powerful magnetic properties. Our group recently found CrTe-based materials that show very promising magnetic properties in nanostructured form. The magnetic modeling of such material in nanostructured form prior to their fabrication demonstrates their magnetic properties in bulk form. In this project, we investigate the behavior of …