Dynamic Nuclear Polarization Enhanced Multiple-Quantum Spin Counting of Molecular Assemblies in Vitrified Solutions.
Mesopotamia S NowotarskiLokeswara Rao PotnuruJoshua S StraubRaj K ChaklashiyaToshihiko ShimasakiBholanath PahariHunter CoffaroSheetal JainSong-I HanPublished in: The journal of physical chemistry letters (2024)
Crystallization pathways are essential to various industrial, geological, and biological processes. In nonclassical nucleation theory, prenucleation clusters (PNCs) form, aggregate, and crystallize to produce higher order assemblies. Microscopy and X-ray techniques have limited utility for PNC analysis due to the small size (0.5-3 nm) and time stability constraints. We present a new approach for analyzing PNC formation based on 31 P nuclear magnetic resonance (NMR) spin counting of vitrified molecular assemblies. The use of glassing agents ensures that vitrification generates amorphous aqueous samples and offers conditions for performing dynamic nuclear polarization (DNP)-amplified NMR spectroscopy. We demonstrate that molecular adenosine triphosphate along with crystalline, amorphous, and clustered calcium phosphate materials formed via a nonclassical growth pathway can be differentiated from one another by the number of dipolar coupled 31 P spins. We also present an innovative approach for examining spin counting data, demonstrating that a knowledge-based fitting of integer multiples of cosine wave functions, instead of the traditional Fourier transform, provides a more physically meaningful retrieval of the existing frequencies. This is the first report of multiquantum spin counting of assemblies formed in solution as captured under vitrified DNP conditions, which can be useful for future analysis of PNCs and other aqueous molecular clusters.
Keyphrases
- room temperature
- single molecule
- magnetic resonance
- ionic liquid
- high resolution
- density functional theory
- molecular dynamics
- transition metal
- electronic health record
- high throughput
- photodynamic therapy
- computed tomography
- machine learning
- big data
- optical coherence tomography
- heavy metals
- risk assessment
- mass spectrometry
- current status
- data analysis
- quantum dots
- wastewater treatment