
NSF Org: |
DMR Division Of Materials Research |
Recipient: |
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Initial Amendment Date: | September 3, 2013 |
Latest Amendment Date: | February 28, 2018 |
Award Number: | 1334867 |
Award Instrument: | Standard Grant |
Program Manager: |
John Schlueter
jschluet@nsf.gov (703)292-7766 DMR Division Of Materials Research MPS Directorate for Mathematical and Physical Sciences |
Start Date: | September 1, 2013 |
End Date: | February 28, 2019 (Estimated) |
Total Intended Award Amount: | $975,000.00 |
Total Awarded Amount to Date: | $987,000.00 |
Funds Obligated to Date: |
FY 2018 = $12,000.00 |
History of Investigator: |
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Recipient Sponsored Research Office: |
W5510 FRANKS MELVILLE MEMORIAL LIBRARY STONY BROOK NY US 11794-0001 (631)632-9949 |
Sponsor Congressional District: |
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Primary Place of Performance: |
Dept of Physics and Astronomy Stony Brook NY US 11794-3800 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): |
DMR SHORT TERM SUPPORT, DMREF |
Primary Program Source: |
01001819DB NSF RESEARCH & RELATED ACTIVIT |
Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.049 |
ABSTRACT
NON-TECHNICAL: In this DMREF project, the rich physics of three large families of artificially structured oxide materials are being studied using a synergistic combination of theoretical and experimental methods. These artificially structured materials, obtained by stacking atomically-thin layers of two or more different compounds, offer enormous flexibility in the choice of constituents, layer thickness, stacking sequence and choice of substrate, which can strongly influence their structure and properties. The approach being developed and applied in this project, integrating computational data-driven search and modeling methods with sophisticated first-principles analysis and state-of-the-art experimental synthesis and characterization of selected materials, allows the design and discovery of novel materials with specified functional properties enhanced and/or distinct from those possible in naturally occurring compounds, thus having the potential to enable transformative technologies.
TECHNICAL: In this DMREF project, the rich physics of metallic-dielectric perovskite oxide superlattices are being explored through an integrated theoretical-experimental investigation. The principal objective is to map the structure and properties of three selected broad families of superlattices (superlattices of SrMO3 where M=V, Cr, Mn, Fe, Co, Mo or Ru combined with SrTiO3, PbTiO3 or LaMO3) spanning an enormous configuration space. Specifically, the researchers are building on recent advances in high-throughput first-principles infrastructure to develop and demonstrate a guided-sampling high-throughput first-principles approach that uses physically-motivated models to interpret and interpolate first-principles results. Furthermore, their approach compares approximate quantities (that are computed in high-throughput calculations) to those obtained through both high-accuracy computational methods and state-of-the-art experimental synthesis and characterization. This approach is enabling them to identify individual systems with desired functionalities, particularly those related to metal-insulator transitions. In insulating materials the properties of interest are those related to polarization, including piezoresponse and dielectric constant and the size and position of band gaps and band edges. For metallic materials, the thermoelectric properties of these layered systems are especially promising. Intensive theoretical and experimental investigation is validating the theoretically generated structure-property maps, revealing any novel physical phenomena, and pointing the way to potential technological applications. Beyond the systems being studied in this project, the guided-sampling high-throughput approach being developed for this investigation can be applied to other materials design challenges as well. The tight integration of theory and experiment in this project provides a unique opportunity for participants, including graduate, undergraduate and high school students, to develop a broad skill set while participating in cutting edge materials development.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The goal of the Materials Genome Initiative is to accelerate the development of new materials through integration of computational tools and data with experimental realization by synthesis and characterization. The very first step in the materials development pipeline is the identification of promising new candidate materials with enhanced or novel functionalities. This project furthers this goal by drawing on recent dramatic progress in synthesizing structures, called superlattices, with two complex oxide compounds combined into patterns at the atomic scale, giving vast new families of artificial materials in which desired functionalities can be engineered. With computer simulations, we can predict the precise atomic arrangements and properties for each choice of compounds and patterns. From analysis of the simulation results for a large set of superlattices, stored and organized in an online database, we have constructed a model that allows a useful estimate of the relevant properties just from quantities computed for the individual constituent compounds. This estimation capability greatly increases the speed with which the large number of candidate superlattices can be searched. The auxiliary database of simulation results for the necessary information about individual constituent compounds includes information about competing phases distinct from those observed under normal conditions, but which could be accessed by changing external parameters such as temperature, pressure and the size and shape of the sample; our computer simulations are uniquely suited to the generation of this data. These materials design tools and data allow us efficiently to identify the most promising superlattices for a particular application for realization and characterization in the laboratory. Selected candidates have been synthesized and characterized by members of the team using the information from the computer simulations. Examples include the observation of enhanced piezoelectricity in ferroelectric PbTiO3/BaTiO3 superlattices, and the control of intrinsic bias in metallic-dielectric PbTiO3/SrTiO3 and PbTiO3/SrRuO3 superlattices, and synthesis of SrTiO3/SrCrO3 as a candidate metal-insulator switch system.
Last Modified: 04/22/2020
Modified by: Matthew Dawber
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