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The paper considers the mechanisms of helium implantation and concentration in minerals of lunar regolith. It is shown that the content of implanted helium is determined by the composition and structure of minerals in lunar regolith and varies in a very wide range up to three orders of magnitude or more. Amorphization of the crystal structure of il...
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月表覆盖着一层结构松散的月壤, 是遥感和卫星观测及探月工程的重要研究对象. 成熟的月壤经历了复杂的撞击、溅射和翻耕过程, 其现今位置相比原岩发生了一定程度的转移. 确定月壤相对原岩的转移距离对相关研究具有重要意义, 这通常基于遥感数据及撞击模型分析展开. 基于玄武质岩浆喷发至月表后的冷却历史模拟, 本文证明月表熔岩流冷却历史主要受岩浆在熔岩流内部所处深度控制, 相似深度岩浆的冷却过程与熔岩流厚度关系较弱. 因此, 矿物扩散所记录的热历史不是熔岩流喷发强度/厚度的准确指标. 将熔岩流冷却历史与撞击溅射过程结合, 我们提出了基于扩散年代学恢复玄武质月壤来源(原地或异地)的新方法.
Lunar soil, or regolith, which blankets the Moon’s surface, contains vital information about the Moon’s formation,
geological history, and surface evolution. Understanding the origin and evolution of this material is essential for
interpreting data collected during past and future lunar missions. One of the key challenges in lunar geology is tracing the
provenance of lunar soil — that is, determining where it originally came from. This is especially critical because lunar soil
is often transported and reworked over time, meaning its current location may not reflect its source. Mature lunar soil
generally undergoes two distinct processes. The first is initial formation, which occurs through high-energy impact events
that physically break down bedrock, generating fragments and ejecting them across the surface. The second is the
gardening process, where micrometeorite bombardment and continual impacts churn and mix the upper regolith layers.
This prolonged mixing leads to a homogenized material in terms of its original depth within the lava flow.
Previous efforts to trace the origin of lunar soil have mainly relied on remote sensing data and theoretical impact ejecta
models, which estimate the contribution of material from known craters or distant sources. Here we propose a novel
method that combines impact modeling with thermal diffusion chronometry to link soil samples to depths within their
source rocks as mare basalts. Using the Maxwell Z-model, which describes the excavation flow field of a crater-forming
impact, we simulate the depth distribution of ejecta from a basaltic lava flow. This model allows us to predict how deep
within a lava flow the material originated, based on the distance it was ejected from the impact site. Additionally, we
simulate the cooling history of lunar lava flows. As a lava flow cools, minerals located at different depths within the flow
experience different thermal histories, which are recorded in their diffusion profiles. These profiles can be measured using
diffusion chronometry, providing a time-temperature record for individual mineral grains.
Our findings show that the depth at which a mineral formed in the original lava flow is the primary control on its thermal
history, rather than the overall thickness of the flow or eruption rate. While this demonstrates that diffusion chronometry
provides a minimum estimate on the flux and/or volume of basaltic lava flow, it also enables us to estimate the original
depth of soil grains with the lava flow.
This integrated approach offers a new method for tracing the provenance of lunar soil using diffusion chronometry. It
enhances our ability to interpret lunar samples in a geological context and provides useful information for future lunar
missions.
This scientific study investigates how artificial intelligence (AI) and satellite remote sensing could work together to transform space resource management. As human activity in space continues to expand, the effective and sustainable utilization of celestial resources is of paramount importance. It begins by highlighting the evolution of space exploration and the growing interest in resource extraction beyond Earth's boundaries. It emphasizes the critical role of resource management for the success of future space missions.
Advances in technology in recent times, including the implementation of in-situ resource utilization (ISRU) and self-governing mining systems, have significantly enhanced the possibility of extracting resources from celestial entities. While the economic feasibility of space mining is compelling, environmental concerns, sustainability, and intricate governance challenges necessitate careful examination.
An approach for comprehending the complex field of space resource management is presented in this research. It delineates a clear roadmap of its content, offering a succinct summary of key objectives and sections, facilitating reader comprehension. The methodology includes a literature review of relevant research materials from Web of Science, Scopus, and Google Scholar sources. It investigates celestial bodies' resource potential, main challenges, and environmental implications.
Preliminary contributions include one analysis of the potential applications of satellite remote sensing and AI technologies in mitigating these challenges, highlighting their pivotal roles in resource identification and management, proposing terrestrial solutions applicable to space resource management. The integration of AI into space resource management is discussed, emphasizing its potential to enhance safety protocols, resource allocation, and overall efficiency. Furthermore, it discusses international agreements and treaties governing space exploration and resource utilization while advocating for cooperation among space-faring nations and stakeholders. It concludes discussing the implications, benefits, challenges, areas requiring further attention, and future directions of integrating these technologies in space resource management.
