Year: 2019

Tulsi & Kevin Publish in the Journal of Applied Physics

Congratulations to Tulsi & Kevin on their publication, “Ferroelectric Films on Metal Substrates: The Role of Thermal Expansion Mismatch on Dielectric, Piezoelectric, and Pyroelectric properties”, in the Journal of Applied Physics for their findings on the role of metallic substrates on the functional properties of PZT solid solutions.

 

Ferroelectric Films on Metal Substrates: The Role of Thermal Expansion Mismatch on Dielectric, Piezoelectric, and Pyroelectric properties
T. A. Patel, K. Co, R. J. Hebert, and S. P. Alpay, J. Appl. Phys. 126, 134103 (2019)
DOI: DOI: https://doi.org/10.1063/1.5116134

ABSTRACT
We present here a comprehensive analysis of the effect of thermal stresses on the functional properties of ferroelectric oxides on metal substrates. We use a Landau-Devonshire formalism to quantitatively assess the role of in-plane thermal strains that arise from the coefficient of thermal expansion (CTE) mismatch between lead zirconate titanate [PbZrxTi1–xO3, PZT x/(1 – x)] films and Al, Cu, Fe, Ni, and Ti-based substrates. Specifically, we compute Curie transition temperatures, spontaneous polarizations, dielectric permittivities, piezoelectric coefficients, and pyroelectric responses of tetragonal PZT compositions as a function of the growth/processing temperature. To provide a rapid evaluation, we also develop Ashby diagrams of property coefficients as a function of PZT composition, processing temperature, and CTE of the substrate. Our results show that thermal strains in PZT may significantly alter the ferroelectric transition temperature, dielectric, piezoelectric, and pyroelectric properties. For example, for PZT 50/50 films on Ni-based superalloys processed/annealed at 700 °C, we predict monodomain intrinsic dielectric, piezoelectric, and pyroelectric responses to be 234, 152 pC/N, and 0.021 μC cm−2 °C−1, respectively, compared to bulk PZT 50/50 values of 381, 326 pC/N, and 0.045 μC cm−2 °C−1. These are substantial variations which show that thermal strains must be considered in the design and development of built-in functionality obtained through ferroelectric films in structural, aerospace components.

A New Appointment For Our PI !

Congratulations to Dr. Alpay on his new appointment as Associate Dean for Research and Industrial Partnerships.

In addition to his role leading the UConn Tech Park, we are thrilled to share that our PI and Executive Director Dr. Alpay was recently named Associate Dean for Research and Industrial Partnerships at the UConn School of Engineering. This newly created position seeks to enhance and grow partnerships with industries of all sizes in the state and beyond and will complement ongoing efforts at the Tech Park.  The dual role will allow him to effectively lead engineering centers and initiatives in IPB/UConn Tech Park.

What an Exciting Conference at Georgia Tech!!

Dennis & Uche presented their research at the Machine Learning in Science and Engineering Conference at Georgia Tech.

Dennis Trujillo gave a talk:

Applications of Deep Learning to Coherent Diffractive Imaging

Abstract. Convolutional Neural Networks have experienced a surge in interest over recent years as a viable technique in computer vision and other problems involving large datasets. Coherent  diffractive imaging experiments typically generate extremely large datasets which require extensive data storage and extensive computation and manpower to screen through utilizing standard screening (expert analysis by eye) and phase retrieval algorithms. We apply these techniques in the domain of coherent diffractive imaging and phase retrieval for classification of objects of interest (topological phases) and in a regression scheme as an alternative to standard phase reconstruction algorithms.

Uche Anene presented a poster:

Ligand Functionalization for Enhanced Selective Gas Adsorption of Hydrostable STAM-17-OEt MOF

Abstract. Metal-organic framework (MOF), a class of porous crystalline materials, has received extensive attention due to their wide range of applications in areas such as gas storage and separation, catalysis and luminescence. However, its hydrolytic instability has been a major drawback and limit further implementation into new areas. Recently, STAM-17-OEt MOF was reported to overcome these shortcomings.Here we use density functional theory to investigate STAM-17-OEt for its selective sorption for technologically important gases such as CH4, CO, CO2, H2, N2 andH2O by using both molecular cluster and 3D periodic structural models. Further, MOF properties such as their sorption, selectivity, and their stability can be tuned through the functionalization of their organic linkers. In this work, we investigate howlinker functionalization modifies the electronic structure of STAM-17-OEt. Our findings will provide important insight on the unique binding characteristics of the different gas molecules and electronic structural factors associated with the functionalized STAM-17-OEt.

Reference:
1. Mchugh, L. N.; Mcpherson, M. J.; Mccormick, L. J.; Morris, S. A.; Wheatley, P. S.; Teat, S. J.; Mckay, D.; Dawson, D. M.; Sansome, C. E. F.; Ashbrook, S. E.; Stone, C. A.; Smith, M. W.; Morris, R. E. Hydrolytic Stability in Hemilabile Metal–Organic Frameworks. Nature Chemistry. 2018, 10(11), 1096–1102. doi:10.1038/s41557-018-0104-x

 

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

 

Read More

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.