Abstract

Inclusion of lattice-fields in density functional theory (DFT) methods has enabled the accurate calculation of solid-state nuclear magnetic resonance (SSNMR) chemical shift tensors. Calculated 13C and 15N tensors (i.e. 3 principle values per nucleus) can be used to monitor crystal structure refinements and to select the correct structure from a large population of computationally generated candidates. In this dissertation, chapter 2 describes a methodology to improve established crystal structures from three different diffraction techniques involving geometric refinement monitored using SSNMR tensor values. The calculated 13C tensors for three relatively simple organic compounds (i.e. acetaminophen, naphthalene, and adenosine) are shown to markedly improve upon DFT refinement. The so-called GGA-PBE functional provided the best agreement with experimental data. The use of the three principle values of the tensor is required for such results as the average (i.e. the isotropic) is less accurate. Chapter 3 applies this method to differentiate between hundreds of computationally predicted crystal structures. Typically, lattice energy of each candidate is used to select the correct structure, a process which is seldom successful. Herein, it is demonstrated that when 13C tensors from DFT refined structures are used for structural ranking by comparison to experimental data, only the correct structure agrees with experimental data in all cases. Chapter 4 illustrates the use of 15N tensors to monitor DFT refinement as an alternative to the 13C approach of Chapter 2. 15N tensors have been very difficult to obtain previously, thus a novel experimental method is developed here which improves signal-to-noise by as much as 300% and allows routine measurement. This improvement also improves the accuracy of the tensor values. Overall, the 15N tensors are found to be at least 5 times more sensitive to DFT refinements than 13C values.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu

Graduation Date

2017

Semester

Fall

Advisor

Harper, James

Degree

Doctor of Philosophy (Ph.D.)

College

College of Sciences

Department

Chemistry

Degree Program

Chemistry

Format

application/pdf

Identifier

CFE0006888

URL

http://purl.fcla.edu/fcla/etd/CFE0006888

Language

English

Release Date

December 2017

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Download

Included in

Chemistry Commons

Share

COinS