^1,3Noah Jäggi, ¹Adam K. Woodson, ²Paul S. Szabo, ³Johannes Brötzner, ³Friedrich Aumayr, ¹Catherine A. Dukes
Icarus (in Press) Open Access Link to Article [https://doi.org/10.1016/j.icarus.2026.117231]
¹Laboratory for Astrophysics and Surface Physics, University of Virginia, 395 McCormick Road, Charlottesville, 22904, VA, USA
²Space Sciences Laboratory, University of California, 7 Gauss Way, Berkeley, 94720, CA, USA
³Institute of Applied Physics, TU Wien, Wiedner Hauptstraße 8-10/E134, Vienna, 1040, Austria
Copyright Elsevier

Binary collision approximation (BCA) codes are potentially powerful tools to simulate ion irradiation ejecta properties, such as the composition and the angular and energy distributions of the sputter yield. However, recent advances in the sputtering of minerals have highlighted the low predictive fidelity of BCA codes such as SDTrimSP when compared to experimental measurements. We demonstrate how a sputtering model that underestimates the forward sputtering on a flat surface at large ion incidence angles from surface normal will lead to an erroneous result for rough and porous surfaces, where most ejected particles are directed along the surface normal. We demonstrate how this is the case for an existing model, which reliably predicts sputtering mass yields from a flat enstatite surface but fails to accurately reproduce the angular distribution of sputtered particles. We then compare this to a BCA model incorporating higher surface-binding energies—based on a molecular dynamics description of plagioclase—which underestimates mass yields but significantly reduces back-sputtering and better reproduces laboratory sputter angle distributions measured at large ion incidence angles. We conclude that the BCA model cannot simultaneously reproduce both the sputter yield and the sputter angle distribution arising from He irradiation of mineral targets, either due to the inherent geometric simplicity of the BCA or because the model neglects yield-enhancing processes such as molecule and cluster sputtering. This demonstrates a structural limitation of current BCA-based models when realistic surface morphologies are considered, rather than a problem that can be resolved by parameter tuning alone.

¹Xing Wu, ²Beatrice Baschetti, ^1,3Yang Liu, ²Cristian Carli, ^1,3Xiang Zhou, ¹Yazhou Yang, ¹Yongliao Zou
Icarus (in Press) Link to Article [https://doi.org/10.1016/j.icarus.2026.117235]
¹State Key Laboratory of Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing, 100190, China
²Italian National Institute for Astrophysics (INAF) – Institute for Space Astrophysics and Planetology (IAPS), Via del Fosso del Cavaliere, 100, Rome 00133, Italy
³College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Copyright Elsevier

Quantitative spectral unmixing is essential for identifying and characterizing mineral assemblages on planetary surfaces. The Hapke and Shkuratov models are the most widely used radiative transfer models (RTMs) for interpreting reflectance spectra, yet their quantitative accuracy remains largely untested due to limited laboratory validation. In this study, both models are applied to binary and ternary laboratory powder mixtures composed of phyllosilicates, including nontronite and saponite, sulfates represented by hexahydrite, and basaltic analogs relevant to Martian surface materials. The effects of endmember variability, spectral noise, and spectral sampling interval on unmixing performance are systematically evaluated. The results show both models reproduce measured spectra and compositional trends accurately when correct endmembers are used, achieving abundance retrievals within ~10 wt% for binary mixtures and ~ 15 wt% for ternary mixtures, except in systems with strong reflectance contrasts. The Shkuratov model provides lower errors and greater stability overall, whereas the Hapke model shows slightly better tolerance to compositional mismatch between Al-rich and Al-poor nontronite. Incorporating multiple compositional variants as an endmember bundle effectively mitigates mismatch effects. Estimated grain sizes fall within realistic physical ranges but show large uncertainties for bright or spectrally neutral materials, reflecting reduced model sensitivity to grain size variations. Additionally, we also find the unmixing performance remains robust under spectral noise levels of at least 25 dB and spectral sampling intervals up to 50, consistent with the capabilities of Mars orbital instruments. These results demonstrate that radiative transfer based unmixing, particularly using the Shkuratov model, provides a reliable and physically grounded framework for quantitative mineralogical analysis of Martian hyperspectral data.