Eikey, Emily A.
(2024)
Understanding and Leveraging Atom Arrangement in Materials: Synthetic Control and Computational Theory Development.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
The composition of a material dictates its function across length scales, and the diversity of composition provides scientists with many opportunities to tailor material properties for desired applications, ranging from catalysis to medicine. To fully leverage composition, robust methods to study, tune, and predict material compositions and properties are needed. These goals can be realized if approached from both synthetic and theoretical perspectives. Theory can predict properties based on composition, and synthesis allows these compositions to be accessed in the real-world. However, both areas require more work to efficiently accelerate materials discovery and implementation. Specifically, the majority of synthetic methods rely on multiple synthetic and purification steps, inhibiting their scale up and downstream translation into usable products. Theoretical models have been developed to facilitate materials discovery and study, but still these models rely on numerous expensive calculations, hindering the ability to explore the vast space of composition.
Accordingly, this dissertation aims to address these challenges by exploring synthetic control of composition and developing theoretical models to facilitate the exploration of composition space. Room-temperature, aqueous-based synthetic methods were developed to control the composition of metal chalcogenide nanoparticles. Reaction parameters that control composition, specifically atom arrangement, were identified and leveraged to use a simple, direct synthetic method to access two different types of nanoparticle atom arrangements. This work makes a critical step towards streamlining synthetic methods for accessing multiple material compositions. To address current theoretical limitations, the accuracy of quantum alchemy using a Taylor series expansion was studied for atomic and diatomic systems. While large errors were initially observed, these errors were found to significantly cancel when properties were predicted in the framework of a thermodynamic cycle. Three main sources of error were identified, and these results suggest that some sources of error may be independent of system type. This work provides fundamental insight into how and when quantum alchemy using a Taylor series expansion works and also provides a foundation for developing error correction schemes to further improve its accuracy.
Taken together, the work in this dissertation makes significant advances in both synthetic control and computational theory development needed for making and predicting the properties of materials with various compositions. This work emphasizes the importance of both synthesis and theory and how research in both areas can aid in pushing materials science forward.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
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| ETD Committee: |
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| Date: |
21 February 2024 |
| Date Type: |
Publication |
| Defense Date: |
22 November 2021 |
| Approval Date: |
21 February 2024 |
| Submission Date: |
9 December 2021 |
| Access Restriction: |
2 year -- Restrict access to University of Pittsburgh for a period of 2 years. |
| Number of Pages: |
178 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Dietrich School of Arts and Sciences > Chemistry |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
nanomaterial, nanoparticle, synthesis, composition, metal chalcogenide, computation, theory, computational theory, quantum mechanics, quantum alchemy |
| Date Deposited: |
21 Feb 2024 18:00 |
| Last Modified: |
21 Feb 2024 18:00 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/42020 |
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