Unexpected Polymorphism and Unique Particle Morphologies from Monodisperse Droplet Evaporation

The particle sizes, morphologies, and structures are presented for succinic acid particles formed from the evaporation of uniform droplets created with a vibrating orifice aerosol generator. Particle sizes are monodisperse, and solvent choice is found to be the dominant factor in determining the final morphology and structure. The external particle morphologies range from round to cap shaped, while the surface roughness ranges from fairly smooth to extremely rough and pitted. Internally, the particles have significant void space and noticeable crystals. X-ray diffraction confirms that the particles are crystalline. Thus, the morphologies of the particles take on a crystal filled structure that is unique in comparison to previous particles formed through droplet evaporation. The structure of the particles contains β succinic acid; however, the particles formed from water also contain α succinic acid. α Succinic acid has not previously been able to be formed from solution at near atmospheric conditions. The unique morphologies and ability to identify unexpected polymorphs provide for a potential tool to not only enhance particle engineering but also to identify metastable polymorphs.

Enhancing Sensitivity In Natural Product Nmr: Exploring Optimal Non-Uniform Sampling

Recent optimizations of NMR spectroscopy have focused their attention on innovations in new hardware, such as novel probes and higher field strengths. Only recently has the potential to enhance the sensitivity of NMR through data acquisition strategies been investigated. This thesis has focused on the practice of enhancing the signal-to-noise ratio (SNR) of NMR using non-uniform sampling (NUS). After first establishing the concept and exact theory of compounding sensitivity enhancements in multiple non-uniformly sampled indirect dimensions, a new result was derived that NUS enhances both SNR and resolution at any given signal evolution time. In contrast, uniform sampling alternately optimizes SNR (t < 1.26T2) or resolution (t~3T2), each at the expense of the other. Experiments were designed and conducted on a plant natural product to explore this behavior of NUS in which the SNR and resolution continue to improve as acquisition time increases. Possible absolute sensitivity improvements of 1.5 and 1.9 are possible in each indirect dimension for matched and 2x biased exponentially decaying sampling densities, respectively, at an acquisition time of ¿T2. Recommendations for breaking into the linear regime of maximum entropy (MaxEnt) are proposed. Furthermore, examination into a novel sinusoidal sampling density resulted in improved line shapes in MaxEnt reconstructions of NUS data and comparable enhancement to a matched exponential sampling density. The Absolute Sample Sensitivity derived and demonstrated here for NUS holds great promise in expanding the adoption of non-uniform sampling.

The Investigation of Uniform, Monodisperse Crystalline Particles via the Evaporation of Small Droplets

Many industrial solids processes require the production of disperse particles. In industries such as food, personal care, and pharmaceuticals, particle formation is widely used to produce solid products or to separate substances in intermediate process steps. The most important characteristics known to impact the effectiveness of a solid product are purity, size, internal structure, and morphology. These characteristics are essential to maintain optimal operation of subsequent process steps and for obtaining the desired high quality product. This thesis aims to aid in the advancement of particle production technology by (1) investigating the use of a vibrating orifice aerosol generator (VOAG) for collecting data to predict particle attributes including morphology, size, and internal structure as a function of processing parameters such as solvent, solution concentration, air flow rate, and initial droplet size, as well as to (2) determine the extent to which uniform droplet evaporation can be a tool to achieve novel particle morphologies, controlled sizes, or internal structures (crystallinity and crystal form). Experimental results for succinic acid, L-serine, and L-glutamic acid suggest that particles of controlled characteristics can indeed be produced by this method. Analysis by scanning electron microscopy (SEM), nanoindentation, and X-ray diffraction (XRD) shows that various sizes, internal structures, and morphologies can be obtained using the VOAG. Furthermore, unique morphologies and unexpected internal structures were able to be achieved for succinic acid, providing an added benefit to particle formation by this method.

Performance Tuning Non-Uniform Sampling for Sensitivity Enhancement of Signal-Limited Biological NMR

Non-uniform sampling (NUS) has been established as a route to obtaining true sensitivity enhancements when recording indirect dimensions of decaying signals in the same total experimental time as traditional uniform incrementation of the indirect evolution period. Theory and experiments have shown that NUS can yield up to two-fold improvements in the intrinsic signal-to-noise ratio (SNR) of each dimension, while even conservative protocols can yield 20-40 % improvements in the intrinsic SNR of NMR data. Applications of biological NMR that can benefit from these improvements are emerging, and in this work we develop some practical aspects of applying NUS nD-NMR to studies that approach the traditional detection limit of nD-NMR spectroscopy. Conditions for obtaining high NUS sensitivity enhancements are considered here in the context of enabling H-1,N-15-HSQC experiments on natural abundance protein samples and H-1,C-13-HMBC experiments on a challenging natural product. Through systematic studies we arrive at more precise guidelines to contrast sensitivity enhancements with reduced line shape constraints, and report an alternative sampling density based on a quarter-wave sinusoidal distribution that returns the highest fidelity we have seen to date in line shapes obtained by maximum entropy processing of non-uniformly sampled data.