Construction of a photothermal evaporation-sorption integrated device for lithium extraction from salt lakes and study on its synergistic enhancement mechanism

This dataset is derived from the experimental study on the construction and performance evaluation of the integrated photothermal evaporation-absorption device for lithium extraction from salt lakes. It focuses on the preparation, structural characterization, photothermal response, evaporation behavior, lithium adsorption performance, and analysis of the synergistic enhancement mechanism of the HMO/PU@PPy integrated photothermal evaporation-absorption device. The data generation process mainly includes: Firstly, using three-dimensional porous polyurethane (PU) as the framework, loading the spinel-type manganese-based lithium ion sieve material (HMO), and coating a polypyrrole (PPy) photothermal layer on its surface through an in-situ polymerization method to obtain the integrated device; Then, conducting evaporation-absorption coupling experiments in simulated lithium-containing solutions or salt lake brine systems under dark and light conditions, collecting raw data such as surface temperature of the device, changes in evaporation mass, changes in lithium ion concentration in the solution, adsorption capacity, and cycle stability; Finally, combining kinetic fitting, comparative analysis, and mechanism discussion, the experimental data are sorted, filtered, statistically analyzed, and plotted to form this dataset. Data processing mainly adopts methods such as experimental repeated measurement, blank control, mean statistics, and error analysis, and some results are obtained through formula conversion to derive derived data such as unit mass adsorption capacity, unit area evaporation rate, and removal efficiency. The content of the dataset mainly consists of four parts: device fabrication and characterization data, photothermal evaporation data, lithium adsorption data, and mechanism analysis-related data. Among them, the device performance tests are mainly conducted at the laboratory scale, and the spatial information does not involve geographical grids or the spatial resolution in the sense of remote sensing, but it involves the local interface mass transfer process between the evaporation interface, the device surface and the solution body; the time information is mainly reflected in the light response process, the adsorption equilibrium process and the continuous evaporation stability test process, including minute-level or hour-level dynamic records and daily-level stability records. According to the content of the manuscript, the data should at least include the temperature change of the device evaporation interface under 1 sun illumination conditions, the comparison of adsorption performance under different initial lithium concentrations, and the results of continuous 5-day evaporation stability tests. For time series data, its time resolution is usually the fixed sampling interval set by the experiment; for adsorption equilibrium and cycling test data, each sampling time or each test round is used as the recording unit. Tabular data is usually recorded as a single experiment or a single sampling time point. The row labels of the data table generally represent sample numbers, experimental groups, sampling times, cycle numbers or initial concentration conditions, while the column labels generally represent test indicators and their units, such as temperature (℃), light intensity (sun or kW·m⁻²), evaporation mass loss (g), evaporation rate (kg·m⁻²·h⁻¹), initial lithium concentration and equilibrium lithium concentration (mg·L⁻¹), adsorption capacity (mg·g⁻¹), removal rate (%), etc. If the data set includes material characterization results, it may also include diffraction peak positions, intensities, pore structure parameters, element contents or surface morphology image numbers, etc. Each data file is generally organized according to the logic of "raw data - processed data - corresponding data for charts", where the raw data saves the direct detection results or experimental weighing records exported by the instrument, the processed data saves the results after unit conversion, mean statistics or fitting, and the chart data corresponds to the drawing source data of each figure and table in the main text and supplementary materials of the paper. The testing equipment and tools in this dataset mainly include material preparation devices, constant temperature or conventional experimental reaction devices, solar light simulators or equivalent light source devices, electronic balances, temperature collection devices, lithium ion concentration measurement instruments, and conventional material characterization equipment, etc. Data organization and plotting can usually be accomplished using Excel, Origin, Python or other general data processing software. If some original files are saved in proprietary formats of the instruments, they need to be opened and exported using the corresponding instrument software. The exported general formats usually include.xlsx, .csv, .txt, .jpg/.png or.xlsx corresponding chart files, which are convenient for reproduction and reanalysis. If there are relatively rare original format files included when submitting, it is recommended to also indicate the applicable software name, version and official acquisition method in the file description. Regarding the issue of data missing, this dataset will generally retain all valid experimental results. If there are missing measurements at certain time points, it is usually caused by sampling failure, instrument instantaneous fluctuations, sample operation losses, or the exclusion of abnormal values. The relevant situations should be noted in the corresponding documentation. The errors mainly come from weighing errors, temperature collection errors, light intensity fluctuations, solution sampling and volume determination errors, material preparation batch differences, and systematic errors during the ion concentration detection process. For repeated experimental data, it is recommended to present them in the form of average value ± standard deviation; if a fitting analysis was conducted, the fitting model, parameter meanings, and relevant coefficients should also be explained. Overall, the data can accurately reflect the performance change patterns of the device and its synergistic enhancement effect during the coupling process of photothermal evaporation and adsorption, providing a basis for verifying the conclusions of the paper, reproducing the methods, and conducting subsequent related research.