Abstract
(Ra,Ba)SO(4) 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 × 10(10) Bq g(-1)), and utilization in contemporary research, therefore constrained to trace amounts (< 10(-8) M) with the composition of Ba(x)Ra(1-x)SO(4) 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)SO(4) 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 (Ba(0.5)Ra(0.5))SO(4) follows a second-order reaction with a kinetic constant equal to (1.23 ± 0.09) × 10(-10) mol m(-2) s(-1).