Recent  

The concept of open data has become the modern science meme. Funding bodies and publishers support open data. However, the open data mandate frequently encounters technical obstacles, such as a lack of a suitable data format for data sharing and long-term data preservation. Such issues are often community-specific and demand community-tailored solutions. We propose a new human-readable data format for data exchange and long-term preservation of luminescence data called XLUM.

We propose using the Wasserstein-2 distance (W₂) as an alternative to the widely used Kolmogorov–Smirnov (KS) statistic for analysing distributional data in geochronology. W₂ measures the horizontal distance between observations, while KS measures vertical differences in cumulative distributions. Using case studies, we find that W₂ is preferable in scenarios where the absolute age differences in observations provide important geological information. W₂ has been added to the R package IsoplotR.

We present our model ChronoLorica. We coupled the original Lorica model, which simulates soil and landscape evolution, with a geochronological module that traces cosmogenic nuclide inventories and particle ages through simulations. These properties are often measured in the field to determine rates of landscape change. The coupling enables calibration of the model and the study of how soil, landscapes and geochronometers change under complex boundary conditions such as intensive land management.

Accurately dating ocean cores is challenging because the radiocarbon age of water masses varies substantially. We identify ash fragments from eruptions more than 4000 km from their source and use these time markers to develop a new age–depth model for an ocean core in Placentia Bay, North Atlantic. Our results show that the radiocarbon age of waters masses in the bay varied considerably during the last 10 000 years and highlight the potential of using ultra-distal ash deposits in this region.

(U–Th) / He dating relies on proper characterization of apatite crystal dimensions so that eU concentrations and dates can be calculated accurately and precisely, but there is systematic error and uncertainty in geometric measurements. By comparing 2D microscopy to true 3D measurements, we present a simple solution to correcting the error and quantifying the geometric uncertainty in eU and dates. Including this geometric correction and uncertainty matters for data evaluation and interpretation.

When using the uranium–lead (U–Pb) radiometric dating method on very young materials (e.g. Quaternary age zircon and carbonate minerals), it is important to accurately account for the production and decay of intermediate daughter isotopes in the uranium-series decay chain. DQPB is open-source software that allows users to easily perform such calculations for a variety of sample types and produce publication-ready graphical outputs of the resulting age information.

About 2 million years ago, rich gold deposits formed at Martabe, on the island of Sumatra in Indonesia. Fluids may have moved as the result of fault dilation caused by changes in stress orientation during the earthquake cycle, so to work out exactly when and how long between cycles, we dated a potassium-bearing mineral, alunite, using argon geochronology in association with diffusion experiments during temperature-controlled furnace step-heating, showing two episodes 250 thousand years apart.

Acid leaching is commonly used to remove damaged portions of zircon crystals prior to U–Pb dating. However, a basic understanding of the microstructural processes that occur during leaching is lacking. We present the first 3D view of zircon dissolution based on X-ray computed tomography data acquired before and after acid leaching. These data are paired with images of etched grain surfaces and Raman spectral data. We also reveal exciting opportunities for imaging radiation damage zoning in 3D.

We developed code to automatically and semi-automatically measure dimensions of detrital mineral grains in reflected-light images saved at laser ablation–inductively coupled plasma–mass spectrometry facilities that use Chromium targeting software. Our code uses trained deep learning models to segment grain images with greater accuracy than is achievable using other segmentation techniques. We implement our code in Jupyter notebooks which can also be run online via Google Colab.