What is Bingo-Antidote?

Bingo-Antidote is a petrological software developed by Pierre Lanari and Erik Duesterhoeft offering an alternative modelling strategy based on iterative thermodynamic models, integrated with quantitative compositional mapping.

This technique provides a powerful alternative to traditional modelling tools and permits use of local bulk compositions for testing the assumption of local equilibrium in rocks that were not fully re-equilibrated during their metamorphic history. We argue that this is the case for most natural samples, even at high-temperature conditions, and that this natural complexity must be taken into consideration when applying equilibrium models.

Bingo-Antidote is implemented in XMapTools using the add-on XThermoTools

What paper should I read to learn more about this technique?

There is one technical paper Duesterhoeft & Lanari (2020) and two older publications so far reporting results obtained with Bingo-Antidote: Lanari & Engi (2017) and Lanari & Duesterhoeft (2019). Note that the paper of Lanari & Duesterhoeft (2019) includes a general review on thermodynamic modelling and also provides an example showing an application of Bingo-Antidote.

  • Duesterhoeft, E., & Lanari, P. (2020). Iterative thermodynamic modelling – Part 1: A theoretical scoring technique and a computer program (BINGO-ANTIDOTE). Journal of Metamorphic Geology DOI:10.1111/jmg.12538. Free access
  • Lanari, P. & Duesterhoeft, E. (2019). Modelling metamorphic rocks using equilibrium thermodynamics and internally consistent databases: past achievements, problems and perspectives.Journal of Petrology, 60, 19-56. Free access
  • Lanari, P., & Engi, M. (2017). Local bulk composition effects on metamorphic mineral assemblages, Reviews in Mineralogy and Geochemistry, 83, 55-102pdf

In which cases should I consider using Bingo-Antidote?

As soon as spatial heterogeneities can control local mineral assemblages and that the bulk rock composition is not relevant for modelling. We also recommend using Bingo-Antidote in samples in which minerals exhibit moderate to strong compositional zoning.

In a more general way, Bingo-Antidote offers several options to optimise the forward part of the model based on the mineralogical record preserved in your rock. It reduces the number of hypotheses required when for instance constructing a pseudosection.

This strategy is also a good alternative to inverse models (average PT or Tweeq) as discussed in Lanari & Duesterhoeft (2019).