Armstrong Mikayla D, Vickers Riley, Coronell Orlando
Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Data Brief. 2022 Aug 12;44:108538. doi: 10.1016/j.dib.2022.108538. eCollection 2022 Oct.
The data shared in this work represent aspects of the performance of reverse osmosis membranes during filtration. We present pressure, permeate flux, and solute rejection data gathered during cross-flow filtration experiments, which were used to (i) model water and solute permeation through the membranes and (ii) calculate concentration polarization moduli and a suite of transport properties, including water permeance, solute permeance, and water-solute selectivity. Membrane transport properties were calculated with the different approaches commonly used to simplify transport property calculations. Typical calculations of these transport properties often use simplifying assumptions (e.g., negligible concentration polarization and solute rejection close to 100%). However, the extent of the errors associated with using simplifying assumptions in this context were not previously known or quantified. This publication and corresponding dataset pertain to figures presented in the accompanying work (Armstrong et al., 2022) [1].
本研究中共享的数据代表了反渗透膜在过滤过程中的性能方面。我们展示了在错流过滤实验中收集的压力、渗透通量和溶质截留数据，这些数据用于（i）模拟水和溶质透过膜的过程，以及（ii）计算浓差极化模量和一系列传输特性，包括水渗透系数、溶质渗透系数和水 - 溶质选择性。膜传输特性是用通常用于简化传输特性计算的不同方法计算得出的。这些传输特性的典型计算通常使用简化假设（例如，浓差极化可忽略不计且溶质截留率接近100%）。然而，此前并不清楚或未量化在此背景下使用简化假设所产生的误差程度。本出版物及相应数据集与随附论文（阿姆斯特朗等人，2022年）[1]中呈现的图表相关。
