Constraining the Impact of Post‐Entrapment Crystallization Correction Algorithms on Melt Inclusion Compositions and Petrological Interpretations With MagmaPEC

• Published in: Geochemistry, geophysics, geosystems : G3 Vol. 26; no. 10
• Main Authors: Gerve, T. D., Namur, O., Borst, A.
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 01.10.2025
• Subjects: Algorithms; Crystallization; Diffusion models; Equilibrium; igneous petrology; Lava; Magma; melt inclusions; Olivine; Parameters; post‐entrapment crystallization; Propagation; Python; Storage conditions; Temperature; Volcanism
• ISSN: 1525-2027; 1525-2027
• DOI: 10.1029/2025GC012420

Olivine‐hosted melt inclusions give unique information about primary melt differentiation, magma storage conditions, and their volatile contents, but their compositions are typically affected by post‐entrapment processes. Corrections for post‐entrapment crystallization (PEC) are often done numerically and their results shape interpretations of deep magmatic processes. Importantly, calculated PEC extents (PEC%) depend on how these algorithms internally model key parameters like mineral‐melt partition coefficients, melt Fe3+/Fe2+ ratios, and liquidus temperatures. However, current PEC correction algorithms offer no or limited flexibility in model selection for these parameters. To investigate the impact of PEC correction algorithms and associated uncertainties on corrected melt compositions and petrological interpretations, we developed MagmaPEC. MagmaPEC is a Python‐based software that supports a wide range of models and includes error propagation of analytical and model calibration errors. Results indicate variations of up to 25 PEC%, depending on model choice for the various parameters. Crucially, total propagated errors are generally smaller, highlighting the importance of flexible model selection. Examples of melt inclusions from oceanic intraplate and rift volcanism show variations of up to 6.7 wt.% MgO in corrected melts calculated with different model setups. Associated inclusion entrapment temperature estimates vary by 140°C and applying this temperature range to olivine Fe‐Mg diffusion models produces timescales varying by a factor of seven, while modeled melt viscosities vary by one log unit. Combined, our results highlight the impact PEC corrections have on our understanding of magmatic processes and emphasize the need for flexible correction tools. Plain Language Summary Analyzing droplets of melt captured by olivine crystals at depth in the crust is a key method for studying pre‐eruptive magma compositions and storage conditions. However, melt inclusions often crystallize post‐ entrapment (PEC), altering their original composition. This requires corrections, usually via software, that simulate olivine crystallization. These software internally calculate element valencies, mineral‐melt element distributions, and crystallization temperatures. Importantly, which specific models are used to calculate these parameters impacts correction results. However, current software offer no or limited configuration options. To investigate the impact of PEC corrections on corrected melt compositions and petrological interpretations, we developed MagmaPEC, a Python‐based software that supports a wide range of models and includes error propagation methods. Results indicate variations of up to 25% crystallization and 6.7 wt.% corrected melt MgO content depending on model choice. These variations are important because melt MgO content influences magma storage temperature estimates, which consequently vary by up to 140°C. Applying the temperatures to diffusion‐based magma storage timescale models produces timescales varying by a factor of seven, while melt viscosity estimates vary by one log unit. These results highlight the impact of PEC corrections on our understanding of magmatic processes and the need for flexible correction software. Key Points Numeric PEC correction results are highly dependent on which Fe3+/Fe2+ and mineral‐melt partition coefficient modes are used internally MagmaPEC is Python PEC correction software that supports a wide range of models and includes extensive error propagation PEC corrections potentially have significant impact on melt inclusion‐based petrological interpretations