^1,2Jin Yu Zhang,^1,2Hong Yi Chen,^1,2Yi Man Yin,^1,2Lan Fang Xie,^1,2Xu Kai Gao,²Xi Jun Liu
Meteoritics & Planetary Science (in Press) Link to Article [https://doi.org/10.1111/maps.70164]
¹Institution of Meteorites and Planetary Materials Research, Key Laboratory of Planetary Geological Evolution of GuangxiProvincial Universities, Guilin University of Technology, Guilin, China#
²Guangxi Key Laboratory of Hidden Metallic Ore Deposits Exploration, Guilin University of Technology, Guilin, China
Published by arragement with John Wiley & Sons

The Maoming meteorite, which fell in Guangdong Province, China, on May 28, 2025, represents the second-largest witnessed meteorite recovery event in China since 1949, with a total recovered mass of 423 kg. This study presents an integrated analysis of its petrology, mineral chemistry, and aerodynamic behavior to reconstruct the complete atmospheric entry-to-impact sequence. Fresh samples were examined using optical microscopy, electron probe microanalysis, and density measurements, while the entry trajectory was simulated using a fourth-order Runge–Kutta model constrained by impact crater morphology and atmospheric data. Based on mineralogical homogeneity and shock-weathering features, Maoming is classified as an L5 ordinary chondrite (shock stage S3, weathering grade W1) with a double-layered fusion crust indicating peak temperatures of 1410°C–1615°C. Aerodynamic modeling, based on a constrained initial velocity of ~15 km/s, yields an entry angle of 13.9° and a terminal impact velocity of 267.23 m/s at a trajectory angle of 65°. The simulated penetration depth (2.98 m) closely matches field observations (~3 m), validating the reconstructed dynamics. Despite its friable, fractured structure, the meteoroid survived atmospheric passage without catastrophic disruption, contrasting with typical fragmentation-dominated entries. This case provides critical empirical constraints on the survival of moderately strong, fractured ordinary chondrites under moderate entry conditions. The combined petrological and aerodynamic approach presented here provides a framework for rapid trajectory reconstruction and impact effect quantification. This framework also offers empirical constraints on the trajectory and cratering mechanics of meter-scale, moderately strong meteoroids.

^1,2Louis-Alexandre Lobanov,^1,2Hilary Downes
Meteoritics & Planetary Science (in Press) Open Access Link to Article [https://doi.org/10.1111/maps.70146]
¹Natural History Museum, London, UK
²School of Natural Sciences, Birkbeck University of London, London, UK
Published by arrangement with John Wiley & Sons

Iron meteorites are usually classified manually using bivariate elemental plots. This study extends iron meteorite classification into multi-element space. We present a computational method for the classification of iron meteorites by applying unsupervised machine learning using density-based cluster analysis. It provides formatted iron meteorite data extracted manually from 61 papers, as well as the software created for the application of cluster analysis to iron meteorites. The method can be used to speed up and standardize iron meteorite classification, reduce bias, increase transparency, and check reproducibility of existing classifications. It is fully scalable and can use any number and combination of elements. It allows for the classification of new iron meteorites, checks the validity of existing classifications, and can identify ungrouped iron meteorites that may be related to existing groups. The model has been applied to ungrouped iron meteorites and 29 are suggested for reclassification based on our multi-element results.