(Ra,Ba)SO4 solid solutions are commonly encountered as problematic scales in subsurface energy-related applications, e.g., geothermal systems, hydraulic fracturing, conventional oil and gas, etc. Despite its relevance, its crystallization kinetics were never determined because of radium (226), high radioactivity (3.7 × 1010 Bq g-1), and utilization in contemporary research, therefore constrained to trace amounts (< 10-8 M) with the composition of BaxRa1-xSO4 commonly restricted to x > 0.99. What if lab-on-a-chip technology could create new opportunities, enabling the study of highly radioactive radium beyond traces to access new information? In this work, we developed a lab-on-a-chip experiment paired with computer vision to evaluate the crystal growth rate of (Ba,Ra)SO4 solid solutions. The computer vision algorithm enhances experimental throughput, yielding robust statistical insights and further advancing the efficiency of such experiments. The 3D analysis results of the precipitated crystals using confocal Raman spectroscopy suggested that {210} faces grew twice as fast as {001} faces, mirroring a common observation reported for pure barite. The crystal growth rate of (Ba0.5Ra0.5)SO4 follows a second-order reaction with a kinetic constant equal to (1.23 ± 0.09) × 10-10 mol m-2 s-1.
Keywords: Computer vision; Crystal growth; Microfluidics; Ra-bearing barite; Solid solutions.
© 2024. The Author(s).