Data and scripts for "Sub-Kelvin Resolution X-ray Diffraction Thermometry Defies the Existence of Nanoscale Hotspots in Induction Heated Magnetic Nanoparticles"

This dataset contains measurement data and data analysis scripts used in the article: "Sub-Kelvin Resolution X-ray Diffraction Thermometry Defies the Existence of Nanoscale Hotspots in Induction Heated Magnetic Nanoparticles” by Hanson et al., ACS Nano, 2026. The purpose of this work is to determine the temperature inside magnetic nanoparticles and support particles during induction heating. The induction is caused by an AC field, which causes the magnetic nanoparticles to generate heat. The thermal expansion of the magnetic nanoparticles and support causes peak shifts in the X-ray diffraction. From knowing the thermal expansion, the peak shifts can be transformed into temperature changes through Bragg's Law.Measurement data: The measurement data included in this collection consist of synchrotron X-ray diffraction data measured at the MAX IV synchrotron at the DanMAX beamline. The data can be divided into three groups. Sample temperature calibration measurementsThermal expansion coefficient measurementsInduction heating measurements.All X-ray diffraction data are reduced to azimuthally integrated datasets since no asymmetry was observed in the 2D detector image. All data files are in the file format h5. The data is structured chronologically through scan IDs, and an overview of the data files is given in "Scan overview DanMAX X-ray diffraction experiments.pdf".Data analysis scripts: The data analysis scripts included in this collection cover all analyses used to obtain the results in Hanson et al., ACS Nano, 2026. Here is an overview of the scripts. ACS Nano - Temperature Calibration . ipynb: These scripts are used to determine the calibration factor that relates the temperature measured at the heat gun nozzle to the temperature measured with a thermocouple at the sample position. This calibration factor is used to determine the sample temperature in subsequent measurements. ACS Nano - Thermal expansion . ipynb: These scripts are used to determine the thermal expansion of magnetic nanoparticles and support material. The thermal expansion is determined from a pseudo-Voigt fit to the X-ray diffraction peaks and then transforming the peak shifts into changes in the lattice spacing through Bragg's law. Additionally, a factor relating the temperature changes and peak shifts, γ, is determined.ACS Nano – Compare thermal expansions.ipynb: Comparison of thermal expansion coefficients across multiple scans and both beamtimes. ACS Nano – Induction heating - peak fit with displacement correction . ipynb: This script is used to determine the temperature change in magnetic nanoparticles and support as a function of time during induction heating. Firstly, Pseudo Voigt functions are fitted to evaluate the peak position as a function of time. These peak shifts are then translated into temperature changes through the rigid shift correction/sample displacement correction and the thermal expansion, as described in the article. The corrected peak positions and temperature changes are saved in a new data file since the Pseudo Voigt fitting and rigid shift algorithms are time-consuming. Only one data file is treated when running the script by specifying the scan ID of interest.ACS Nano – Induction heating - compare scans . ipynb: This script is used to compare different X-ray diffraction scans measured during induction heating. Measurements with different field amplitudes are compared for example. This script uses the files created with the script “ACS Nano – Induction heating - peak fit with displacement correction . ipynb”.ACS Nano - Heating power and SAR . ipynb: This script is used to calculate the heating power of an individual magnetic nanoparticle and the specific absorption rate (SAR) of the magnetic nanoparticles. The heating power is determined by slope curves and the corrected slope method. Programming language: Python (JupyterLab). Treated measurement data: When running the data analysis scripts, e.g., “ACS Nano - Thermal expansion . ipynb”, the output is saved in new data files. An overview of the scripts and data folders is seen inside the folder “Overview of data analysis scripts” and “Data analysis scripts”. The data format of the treated measurement data is pickle, which allows for saving data in the form of directories. Acknowledgements: The DanMAX package (DanMAX.py) used in the scripts is written and developed by Mads Ry Jørgensen, Frederik Holm Gjørup, and others from the DanMAX team. This Python package is developed for treating data measured at the DanMAX beamline. Scan overview table: The tables in “Scan overview DanMAX X-ray diffraction experiments” provide an overview of all X-ray diffraction scans relevant to the article.