New insight into the composition of the lunar surface from SiO2 map
Year: 2025
Type: article
Abstract: The distribution of FeO and TiO 2 reveals mantle source characteristics and basaltic diversity, whereas SiO 2 distribution is closely related to magma evolution and crustal differentiation. However, global studies on SiO 2 remain limited. To address this gap, we combined the latest lunar sample data, Kaguya Multiband Imager spectra, and Christiansen Feature to develop a One-Dimensional Convolutional Neural Network (1D-CNN) for mapping lunar SiO 2 . The results reveal a clear spatial asymmetry in SiO 2 : high-latitude regions on the nearside show higher SiO 2 , while low-latitude regions exhibit lower values. Mare Tranquillitatis and Oceanus Procellarum have low SiO 2 but distinct TiO 2 variations, indicating different basaltic types and magmatic sources. The highlands are dominated by ferroan anorthosite, whereas the maria mainly consist of mafic to ultramafic rocks. Incorporating Chang’E-6 samples and Christiansen Feature data improved model accuracy. Future work on silicic volcanic rocks will further refine the global SiO 2 map and deepen understanding of lunar crustal evolution.
Authors: Wencong Chen, Denggao Qiu, Jianguo Yan, Sihai Yi
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W4416233408