Deuterons might be trapped in a bubble embryo which occur s due to statistical fluctuation in heavy water. The size of the bubble embryo is expected to be an order of a small molecule. The ground state energy level which the deuteron may occupy in the bubble is calculated by solving the Schroedinger equation, and by considering the interaction between the trapped deuteron by a spherical bubble and the surrounding polarized liquid medium (heavy water). From the dependence of the energy eigenvalue of the ground state on the bubble radius, the pressure exerted on the bubble wall is obtained. It is found that the pressure is negatively very large if the bubble radius is about the molecular size (3 to 7 Å). From extrapolating this result to larger sizes, we expect that a bubble would quickly collapse if enough energy is supplied and never grows to a stable bubble when the deuteron is trapped in the ground state.

Assemblies of granular particles suspended in a fluid-like state by interstitial liquid or upward gas flow, here referred to as granular suspensions, are critical to numerous industrial applications and natural processes. However, their inherent complexity and opacity pose significant challenges for direct measurement and analysis. Traditional invasive techniques often disrupt the flow dynamics, while optical methods are limited to transparent systems. To overcome these limitations, this study leverages advanced magnetic resonance imaging (MRI) techniques and computational models to analyze multiphase flow dynamics in opaque systems with high spatial and temporal resolution.This work is divided into three primary investigations. First, MRI simulations are developed as a tool for comparison with experimental MRI measurements. These simulations replicate the physical principles of MRI and allow for the evaluation of imaging artifacts, measurement accuracy, and data interpretation in multiphase flow scenarios. By establishing a robust simulation framework, this work bridges the gap between theoretical and experimental studies, providing a basis for refining MRI measurements and improving comparison between simulations and measurements in complex flow systems. Next, we employ MRI to investigate the dynamics of bubble rise in dense (liquid-solid) suspensions. High-resolution two-dimensional and three-dimensional imaging allows for detailed observation of bubble rise, coalescence, and deformation, as well as rise velocities under varying particle volume fractions. This study provides valuable insights into the interplay between bubble behavior and suspension properties, with implications for optimizing processes in chemical reactors, wastewater treatment, and other industries where bubble dynamics are crucial. The final investigation focuses on particle velocity distributions in granular flows within two distinct fluidized bed systems: a gas-solid bed and a liquid-solid bed, both designed for compatibility with a vertical nuclear magnetic resonance (NMR) spectrometer. The overarching goal is to analyze how velocity distributions in granular gases deviate from the Gaussian patterns observed in molecular systems, examining the effects of inter-particle collisions, drag forces, and energy dissipation. Using computational fluid dynamics – discrete element method (CFD-DEM) simulations alongside MRI measurements, this study bridges molecular theory with granular flow behavior, providing critical insights into the physics of confined granular systems fluidized by upward fluid flow. The concluding chapter summarizes the highlights of this study, explores potential future directions, and discusses the broader applicability of these findings. The insights gained here are relevant to a wide range of industrial systems, including fluidized bed reactors and sediment transport, as well as natural processes such as granular avalanches and particulate mixing. By combining the non-invasive imaging capabilities of MRI with advanced computational modeling, this work offers a powerful framework for understanding and optimizing multiphase flow systems across diverse contexts.