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Record W4412122221 · doi:10.5194/epsc-dps2025-1193

Solar Wind-Induced Sputtering: Investigating Anisotropy in the Angular Distribution of Ejecta using SDTrimSP

2025· preprint· en· W4412122221 on OpenAlexaff
Ben Clouter-Gergen, Liam Morrissey, Caixia Bu, A. Mutzke, S. Verkercke, D. W. Savin

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Surface Properties and Treatments
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsEjectaSolar windAnisotropySputteringMaterials sciencePhysicsAstrophysicsOpticsNanotechnologyPlasmaThin filmNuclear physics

Abstract

fetched live from OpenAlex

IntroductionSputtering in planetary science occurs as the solar-wind (SW)—a stream of energetic ions emitted from the Sun—impacts an airless body, ejecting atoms from its surface [1,2]. This process alongside micrometeorite impacts, photo-stimulated desorption, and thermal desorption contribute to the formation of planets’ exospheres [3–5]. While various spacecraft can detect exospheric species such as MESSENGER, BepiColombo, LADEE, and CHACE-2, they cannot discern the respective contributions of the mentioned processes and thus a strong theoretical understanding of sputtering is needed to quantify its influence on the exosphere [6–9].The sputtering yield is well-studied. In contrast, the angular distribution of ejecta has been given significantly less attention, its treatment being particularly sparse in cases relevant to planetary science. As such, sputtering models that consider the angular distribution of ejecta often assume isotropy. Here, we present a theoretical study quantifying anisotropy in the angular distribution of ejecta for SW-induced sputtering cases, helping advance the understanding of sputtering’s contribution to exosphere formation. Further, we compare the results to a common experimental case since experiments often employ heavier, higher energy ions to leverage the enhanced mass detection consequent of a greater sputter yield. These experimental results must then be scaled to inform SW-induced sputtering and, as such, unique behaviors occurring for lower mass impactor cases may be overlooked. Finally, following quantification, we consider the relative contributions from four ejecta-types demonstrated in Fig. 1, an approach enabling us to understand the underlying behavior leading to anisotropy differences between the different cases considered. Fig. 1: An incident ion (red) impacts a target, collides with atoms within, and exits as a reflected ion, triggering four ejecta-types in the process (blue), from left to right: ion-in SKAs, ion-in PKAs, ion-out PKAs, and ion-out SKAs.MethodologyTo simulate sputtering, we utilized the software SDTrimSP which follows the binary collision approximation (BCA) model where sputtering occurs through a sequence of independent collisions within a material prior to the ejection of an atom [1,2]. While both electronic and collisional effects occur in the sputtering process, the latter dominate at energies below 100keV amu-1 and thus we consider collisional sputtering exclusively [2].We selected 1 keV ionized Hydrogen (H+) and 4 keV ionized Helium (He++) to emulate the SW, while 20 keV ionized Krypton (Kr+) was employed given its prevalence in experimental studies. For the target surface, silica (SiO2) was selected given its prominence in both the lunar and Mercurian surfaces and recurrent usage in experiments [10–12]. We simulated ion incidence angles between 0° and 85° (measured from the surface normal) while ejecta were interpreted as a function of polar and azimuthal angles, ranging from 0° to 90° and 0° to 180°, respectively. The scenario is illustrated in Fig. 2. Fig. 2: An incident ion impacts a target substrate at an incidence angle, θi, sputtering an atom as a function of polar (θs) and azimuthal (φs) angles within the depicted quarter-sphere.ResultsForward-backward anisotropy exists when a greater percentage of atoms are sputtered at azimuthal angles between 0° and 90° than 90° and 180°. While the azimuthal distribution of ejecta is isotropic at normal incidence, anisotropy emerges as the ion incidence angle is varied. Noticeable differences in anisotropies between ion cases arise as the ion’s incidence angle is made increasingly oblique, forward-backward anisotropy becoming most pronounced in the H+ case while developing more modestly in the He++ and Kr+ cases. Alternatively, to assess anisotropy in the polar distribution of ejecta we consider anisotropy occurring as a greater percentage of atoms are sputtered between 0° and 45° (“low” angles) than 45° and 90° (“high” angles). At normal incidence, low-angle anisotropy is prominent in all cases. With increasing incidence angle, the polar distribution of ejecta becomes more isotropic in the H+ case, slightly more anisotropic in the He++ case, while remaining relatively steady in the Kr+ case.The divergence in the anisotropies witnessed in the H+ case from those occurring in the other two impactor cases considered can be explained by an interplay between the percentage contribution of specific ejecta-types and the extent to which they are forward and low-angle pronounced. On the one hand, the ejecta-types most readily sputtered forward and at high-angles are generally most prominent in the H+ case and on the other, individual ejecta-types in the H+ case typically have higher forward and lower low-angle sputtering percentages than those in the He++ and Kr+ cases.Concluding StatementThe findings demonstrate that sputtering anisotropy varies significantly depending on the ion-target case considered. While anisotropies in the He++ and Kr+ cases are similar, there are clear differences in the case of H+ bombarding SiO2. Experimental cases using increased energies and masses are, therefore, likely underestimating the degree to which forward-backward anisotropy is present in SW-induced sputtering cases, while overestimating the extent of anisotropy in the polar distribution of ejecta. Accounting for these effects is essential when scaling experimental results to inform planetary sputtering.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.071
GPT teacher head0.261
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2025
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