Published November 25, 2025 | Version v1
Dataset Open

Generation of Picosecond Ion Pulses Using Laser-Stimulated Desorption from a Tungsten Nanotip - Dataset

Description

Dataset Description

This data repository provides the underlying data and plotting routines associated with the manuscript titled "Generation of Picosecond Ion Pulses Using Laser-Stimulated Desorption from a Tungsten Nanotip" by Redl et al., published in Physical Review Research (2025). DOI: https://doi.org/10.1103/7wdx-97pf

In the manuscript, we demonstrate a compact experimental method for generating sub-100 ps ion pulses at 4.5–8.5 keV using laser-stimulated desorption from room-temperature tungsten nanotips. Femtosecond UV pulses ionize adsorbed atoms and molecules within the naturally nanoscale field-enhanced region at the tip apex, enabling efficient ion production at moderate fluence. Time-of-flight measurements show stable, well-timed pulses, and we systematically map their dependence on laser settings and gas loading conditions. This simple source design supports time-resolved ion–solid interaction experiments and opens the door to future pump–probe studies.

All data files are released under the Creative Commons Attribution 4.0 International (CC-BY) license, while all code files are distributed under the MIT license.

Dataset Layout

  • Analysis.py - script for parse data files and basic analysis functionality
  • Paper.py - script for pretty plottin
  • plot_laser.py - plotting script for Fig.2
  • plot_pressure.py - plotting script for Fig.3
  • plot_voltage.py - plotting script for Fig.4
  • simulation - folder for simulation output
  • style - folder for plot styles
  • plots - output folder of plotting scripts
  • data - folder with all generated experimental data

Uncommon data Types

  • .cod2 - binned histogram data in ascii-format
  • .lmftxt - individual MCP events in ascii-format
  • .lmf - individual MCP events in byte-format

Script Requirements

Scripts were run using Python 3.13.1 on Windows with following packages installed

  • numpy (2.3.5)
  • matplotlib (3.10.7)
  • scipy (1.16.3)

Files

lsd_data.zip

Files (747.9 MiB)

NameSize
md5:0f6a8c2a3226eaf16e9bbb269789f2db
747.9 MiBPreview Download

Additional details

Related works

Is part of
Journal Article: 10.1103/7wdx-97pf (DOI)

Funding

FWF Austrian Science Fund
10.55776/Y1174