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Enregistrement W4412122532 · doi:10.5194/epsc-dps2025-1213

Atomic-scale simulations of solar wind sputtering of airless bodies by solar wind ions

2025· preprint· en· W4412122532 sur OpenAlexaff
Anastasis Georgiou, Benjamin Alan Clouter-Gergen, K. Nordlund, Flyura Djurabekova, Eduardo M. Bringa, Liam S. Morrissey

Notice bibliographique

Revuenon disponible
Typepreprint
Langueen
DomainePhysics and Astronomy
ThématiqueAstro and Planetary Science
Établissements canadiensMemorial University of Newfoundland
Organismes subventionnairesnon disponible
Mots-clésSolar windIonSputteringScale (ratio)Environmental sciencePhysicsMeteorologyAstrobiologyAstronomyAtmospheric sciencesAerospace engineeringMaterials sciencePlasmaNanotechnologyEngineeringThin film

Résumé

récupéré en direct d'OpenAlex

IntroductionSputtering of surfaces by ion irradiation is an important process in planetary science, influencing the exospheric composition and surface evolution of airless bodies such as the Moon, Mercury, icy bodies, and asteroids. Such bodies without a significant atmosphere or intrinsic magnetic field are directly impacted by solar wind (SW) ions originating from the Sun’s corona and consisting of approximately 95% protons (H+), 4% alpha particles (He++) and 1% minor ions. These impacts can cause atoms from the surface of the airless body to be ejected into its exosphere, influencing its formation and composition. For example, sodium (Na) abundance in Mercury’s exosphere has been correlated to SW activity and magnetic field dynamics [1].Binary collision approximation (BCA) models have been used to model sputtering of regolith grains like those found on the surface of the Moon and Mercury [2–4]. While BCA models can be used to understand the implantation and ejecta characteristics, they require key user-specified inputs such as surface binding energy (SBE) which can be derived through molecular dynamics (MD) simulations [5]. In addition, BCA models can only simulate single atom ejections without taking into account molecules that can be ejected while also being unable to simulate the complex bond breakage and formation occurring during energetic impacts.Despite being more computationally expensive, MD simulations can provide an alternative method of simulating the entire sputtering process of surfaces by SW ions. While MD sputtering simulations of planetary surface silicates are not well studied, previous research has used MD to study the ejection of atoms and molecules from icy surfaces [6] by energetic ion impacts. In addition, Huang et al. used MD simulations with a reactive force field (ReaxFF), which allows for bond breakage and formation, to study the implantation of SW hydrogen on the Moon.MethodologyIn this study, we use MD with a ReaxFF potential to simulate the sputtering process of energetic SW ions impacting an amorphous albite substrate. We impact the albite surface with 1 keV hydrogen and 4 keV helium (similar to SW conditions) at an angle normal to the substrate surface. The simulation includes both cumulative and non-cumulative bombardment. During cumulative impacts, the surface is continuously bombarded by ions over time, whereas in non-cumulative impacts, the surface resets to its initial state before being bombarded again with a hydrogen ion. After each impact for both cases, we sample the system for any ejected atoms or molecules and record their energy, velocity and ejection angle. We then compare our MD simulations to similar BCA models and available experimental data.ResultsInitial results show the ability of MD simulations to better understand SW sputtering on mineral substrates, potentially removing the need for complex calculations of SBEs and the errors introduced by BCA modelling. These preliminary results show a complex distribution of the sputtering yield, dominated by O atoms. From these initial 50 H and He impacts, no molecules were ejected from the substrate. In addition, we observe an initial sputtering yield of 0.14 for H ions and 0.32 for He ions, a behaviour that is expected due to the higher energy of the He ions. In both incident ion cases, more than 50% of the sputtering yield is O atoms. This agrees well with MD simulations of O SBEs that suggest that O can be weakly bound to the surface. Building on these results, we will use cluster computing resources to significantly increase statistics by simulating thousands of impacts (both static and dynamic) and better capture the sputtering yield, sputter energy, angle and ion backscatter. This will allow us to evaluate preferential sputtering and how the energy distribution (and thus the SBE) can potentially vary as weathering via SW progresses. We will then compare these findings to predictions from BCA modelling, highlighting the significance of molecular interactions and surface change in the sputtering process. Furthermore, we anticipate that the data will reveal insights into the role of surface roughness and defect structures on the ejection dynamics of atoms from the amorphous albite surface. In addition, unlike BCA models MD can identify any molecules that may sputter from the silicate surface. Finally, further simulations will aim to study the sputtering process of adsorbed sodium on amorphous albite as BCA models can only model adsorbed species as changes in the concentration and not as chemically adsorbed species.References[1] R.M. Killen, M. Sarantos, A.E. Potter, P. Reiff, Icarus 171 (2004) 1–19.[2] N. Jäggi, A. Mutzke, H. Biber, J. Brötzner, P.S. Szabo, F. Aumayr, P. Wurz, A. Galli, Planet Sci J 4 (2023) 86.[3] P.S. Szabo, R. Chiba, H. Biber, R. Stadlmayr, B.M. Berger, D. Mayer, A. Mutzke, M. Doppler, M. Sauer, J. Appenroth, J. Fleig, A. Foelske-Schmitz, H. Hutter, K. Mezger, H. Lammer, A. Galli, P. Wurz, F. Aumayr, Icarus 314 (2018) 98–105.[4] L.S. Morrissey, M.J. Schaible, O.J. Tucker, P.S. Szabo, G. Bacon, R.M. Killen, D.W. Savin, Planet Sci J 4 (2023) 67.[5] L.S. Morrissey, O.J. Tucker, R.M. Killen, S. Nakhla, D.W. Savin, Astrophys J Lett 925 (2022) L6.[6] C. Anders, H.M. Urbassek, 482 (2019) 2374–2388.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,018
Score d'incertitude au seuil0,037

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0060,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,010
Tête enseignante GPT0,238
Écart entre enseignants0,228 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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