Congratulations Dennis & Uche for Receiving MLSE Travel Awards

Dennis and Uche were both awarded travel grants to attend the Machine Learning in Science and Engineering Conference to be held at Georgia Tech on June 10-12.


The second-annual MLSE conference highlights advances in research that utilize methods of artificial intelligence, the development of new machine learning algorithms designed for science and engineering problems, and the ways these methods lead to innovations across various fields. Researchers from academia, government, and industry will gather to explore the future of research in science and engineering.

On May 10, 2017, an internal symposium known as Machine Learning in Science and Engineering was held at Carnegie Mellon University to identify ways in which these computational tools are advancing diversity in several fields. Based on the strong response at CMU, an open conference was held on June 6–8, 2018 at the CMU campus in Pittsburgh in partnership with Georgia Tech.

This conference surveyed advances in basic research that utilizes methods of artificial intelligence, the development of new machine learning algorithms designed for science and engineering problems, and ways that these methods are leading to innovations across these fields. Researchers from academia, government, and industry participated in a unique and fascinating forum on the future of research and innovation in science and engineering.

http://dsf.ideas.gatech.edu/events/mlse

 

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Erik Defended His Dissertation

Eric and Professor Alpay

Eric's defense


Abstract: Ceramics are very diverse class of materials and their properties can vary greatly from material to material. It is this diversity that make ceramics so useful in advanced technology. The relatively open crystal structure of ceramics makes it possible to impart functionalities via judicious doping. This work focuses on developing a generalized method for introducing magnetism into normally non-magnetic (diamagnetic) ceramics, using the example case of alumina (\ce{Al2O3}).

The results show that adding small concentrations of transition metals to alumina may increase magnetic activity by generating unpaired electrons whose net magnetic moments may couple with external magnetic fields. The dopant species and dopant coordination environment are the most important factors in determining the spin density distribution (localized or delocalized from the dopant atom) and net magnetic moment, which strongly direct the ability of the doped alumina to couple with an external field.

Our findings show conclusively that significant spin delocalization can only occur in \alpha-alumina when there are unpaired electrons in the transition metal \ce{e_{g}} states. Similar coordination environments in different phases produce similar spin densities and magnetic moments, indicating that the results presented in this work may be generalizable to the other five or more metastable phases of alumina not studied here.

The results of our slab studies indicate that if originally introduced into the bulk all of the dopant except for Fe and Co will remain there, or diffuse further into the bulk. This work serves as a template for determining promising dopants that may induce magnetism in other diamagnetic ceramics. Such doping may aid in the creation of an advanced, high strength, chemically resistant, dilute magnetic semiconductor oxides for use in advanced systems for spintronics or magnetic qubit systems, and decrease the difficulty of magnetoforming the gain structure of such diamagnetic ceramics.

Our research group was awarded a $5.4 million R&D contract by the AFRL

Alpay’s research group, in collaboration with Hebert’s research group and other researchers, will work to provide the next generation manufacturing solutions for the aerospace sector. The project, titled “Simulation-Based Uncertainty Quantification of Manufacturing Technologies,” will help the U.S. Air Force develop more efficient manufacturing processes. The goal is to understand each and every step of the manufacturing process to eliminate failures in specialized aerospace parts. Better understanding the manufacturing process will lead to reduced costs, improved component and system quality, and enhanced industrial capability.

https://today.uconn.edu/2019/03/uconn-receives-major-contract-air-force-rd-advanced-manufacturing/