Synthesis and Physical Properties Characterization of Artificial Seawater Samples

This dataset contains synthesized artificial seawater samples prepared according to ASTM D1141-98 and spanning a wide salinity range (36,052–80,027 ppm). Each sample reproduces the major seawater ions (Na⁺, Ca²⁺, Mg²⁺, K⁺, Sr²⁺, Cl⁻, Br⁻, F⁻, HCO₃⁻, CO₃²⁻, SO₄²⁻, B(OH)₄⁻) with a constant inter-ion ratio maintained via a TDS scaling factor applied above standard seawater salinity; carbonate and borate species were handled separately because their distribution depends on pH. For every synthesized solution we report measured physical properties: density (36,052-46,000), electrical conductivity (EC), pH, and osmolality (from which osmotic pressure can be derived). The measurements are presented together with the preparation details (stock volumes and scaling factors) so that absolute salinity (SA) is known for each sample and can be directly linked to the measured properties. The dataset supports derivation of empirical correlations between SA (or TDS) and the measured thermophysical properties, and it can be used to assess the accuracy of existing seawater property models when extrapolated to high salinities. In addition, inductively coupled plasma optical emission spectroscopy (ICP-OES) measurements of Na, Mg, Ca, K, Sr, S, and B were performed at selected salinities (36,052–80,027 ppm) to validate the synthesized ionic composition and to provide calibration data for future seawater analyses. Detailed information on sample preparation, dilution protocols, and measurement conditions is provided to ensure reproducibility. The dataset enables direct correlation between absolute salinity and measured physical and chemical properties, supports validation of thermodynamic seawater property models at high salinity, and may be reused for instrument calibration, empirical model development, and desalination process studies. Potential reuse includes calibration of laboratory instruments, validation of thermodynamic or empirical models (e.g., extensions of TEOS-10/Pitzer-based functions), and improved process stream property estimation for desalination research and engineering applications.