Fission tracks are damage trails from uranium fission in minerals, whose ages and thermal histories are deduced from their number and length. A mineral is etched for observing the tracks with a microscope. We show that the etching and observation conditions affect the track count and explain it in the framework of a recent etch model. We conclude that established solutions do not secure that the ages and thermal histories inferred from track counts and measurements are accurate.

We introduce a new model of how etching reveals damage tracks left by fissioning atoms, which accounts for variable along-track etching rates. This complete characterization explains many observations, including community difficulty in obtaining consistent track length measurements. It also provides a quantitative basis for optimizing etching procedures, discerning more about how radiation damage anneals, and ultimately deriving more reproducible fission-track ages and thermal histories.

Artificial intelligence techniques are capable of automatically detecting fission tracks in minerals. The AI-Track-tive software presented here can be used to automatically determine fission track densities for apatite fission track dating studies. Apatite fission track dating is mainly applied to tectonic research on exhumation rates in orogens. Time-consuming manual track counting can be replaced by deep neural networks capable of automatically finding the large majority of tracks.

We present the results of a series of experiments that constrain the temperature sensitivity of fission tracks in monazite over geological time. It is concluded that over a heating duration of 10 million years, the estimated closure temperature is < 50 °C and perhaps not much above ambient surface temperatures. Monazite fission track thermochronology has the potential to understand the thermal history and constrain the timing of geological processes in the Earth’s upper crust (< 1–2 km).

Nikon–TRACKFlow is a new system with dedicated modules for automated microscope control and imaging for fission track laboratories. It is based on the Nikon Eclipse Ni-E motorised upright microscope and embedded within Nikon NIS-Elements software. The system decouples image acquisition from analysis based on a number of automated user-friendly designs and protocols. Nikon–TRACKFlow aims to grow towards a high-throughput imaging system for Earth Sciences and other material-oriented sciences.