Matching Items (4)
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- All Subjects: Planetary Science
- Creators: Li, Mingming
- Creators: Ben Amor, Heni
Description
Hydrogen is the main constituent of stars, and thus dominates the protoplanetary disc from which planets are born. Many planets may at some point in their growth have a high-pressure interface between refractory planetary materials and ahydrogen-dominated atmosphere. However, little experimental data for these materials at the relevant pressure-temperature conditions exists. I have experimentally explored the interactions between planetary materials and hydrogen at high P-T conditions utilizing the pulsed laser-heated diamond-anvil cell. First, I found that ferric/ferrous iron (as Fe2O3 hematite and (Mg,Fe)O ferropericlase) are reduced to metal by hydrogen: Fe2O3 + 4H2 → 2FeO + H2O + 3H2 → 2FeH + 3H2O and (Mg1−xFex) O + 3/2 xH2 → xFeH + (1 − x) MgO + xH2O respectively. This reduction of iron by hydrogen is important because it produces iron metal and water from iron oxide. This can partition H into the core (as FeH) or mantle (as H2O/OH−) of a growing planet.
Next, I expanded my starting materials to silicates. I conducted experiments on San Carlos Olivine at pressures of 5-42 GPa. In the presence hydrogen, I observed the breakdown of molten magnesium silicate and the reduction of both iron and silicon to metal, forming alloys of both Fe-H and Fe-Si: Mg2SiO4 + 2H2 + 3Fe →
2MgO + FeSi + 2FeH + 2H2O.
Similar experiments using natural fayalite (Fe2SiO4) as a starting material at pressures of 5-21 GPa yielded similar results. Hydrogen reduced iron to metal as it did in experiments with iron oxides. Unlike with San Carlos olivine, above 10 GPa silicon remained oxidized, implying the following reaction: Fe2SiO4 + 3H2 → 2FeH+2H2O +SiO2. However, below 7 GPa, silicon reduces and alloys with iron. The formation of Fe-Si alloys from silicates facilitated by hydrogen could have important effects for core composition in growing planets. I also observed at low pressures (<10 GPa), quenched iron melt can trap more hydrogen than previously thought (H/Fe nearly 2 instead of 1). This may have important effects for the chemical sequestration of a hydrogen atmosphere at shallow depths in an early magma ocean.
All of the experimental work presented herein show that the composition, chemical partitioning, and phase stability of the condensed portion of growing planets can be modified via interaction with overlaying or ingassed volatile species.
ContributorsAllen-Sutter, Harrison (Author) / Shim, Sang-Heon Dan (Thesis advisor) / Li, Mingming (Committee member) / Leinenweber, Kurt D (Committee member) / Tyburczy, James A (Committee member) / Gabriel, Travis S.J. (Committee member) / Arizona State University (Publisher)
Created2022
Description
The pace of exoplanet discoveries has rapidly accelerated in the past few decades and the number of planets with measured mass and radius is expected to pick up in the coming years. Many more planets with a size similar to earth are expected to be found. Currently, software for characterizing rocky planet interiors is lacking. There is no doubt that a planet’s interior plays a key role in determining surface conditions including atmosphere composition and land area. Comparing data with diagrams of mass vs. radius for terrestrial planets provides only a first-order estimate of the internal structure and composition of planets [e.g. Seager et al 2007]. This thesis will present a new Python library, ExoPlex, which has routines to create a forward model of rocky exoplanets between 0.1 and 5 Earth masses. The ExoPlex code offers users the ability to model planets of arbitrary composition of Fe-Si-Mg-Al-Ca-O in addition to a water layer. This is achieved by modeling rocky planets after the earth and other known terrestrial planets. The three distinct layers which make up the Earth's internal structure are: core, mantle, and water. Terrestrial planet cores will be dominated by iron however, like earth, there may be some quantity of light element inclusion which can serve to enhance expected core volumes. In ExoPlex, these light element inclusions are S-Si-O and are included as iron-alloys. Mantles will have a more diverse mineralogy than planet cores. Unlike most other rocky planet models, ExoPlex remains unbiased in its treatment of the mantle in terms of composition. Si-Mg-Al-Ca oxide components are combined by predicting the mantle mineralogy using a Gibbs free energy minimization software package called Perple\_X [Connolly 2009]. By allowing an arbitrary composition, ExoPlex can uniquely model planets using their host star’s composition as an indicator of planet composition. This is a proven technique [Dorn et al 2015] which has not yet been widely utilized, possibly due to the lack of availability of easy to use software. I present a model sensitivity analysis to indicate the most important parameters to constrain in future observing missions. ExoPlex is currently available on PyPI so it may be installed using pip or conda on Mac OS or Linux based operating systems. It requires a specific scripting environment which is explained in the documentation currently stored on the ExoPlex GitHub page.
ContributorsLorenzo, Alejandro M., Jr (Author) / Desch, Steven (Thesis advisor) / Shim, Dan S.-H. (Committee member) / Line, Michael (Committee member) / Li, Mingming (Committee member) / Arizona State University (Publisher)
Created2018
Description
Affect is a domain of psychology that includes attitudes, emotions, interests, and values. My own affect influenced the choice of topics for my dissertation. After examining asteroid interiors and the Moon’s thermal evolution, I discuss the role of affect in online science education. I begin with asteroids, which are collections of smaller objects held together by gravity and possibly cohesion. These “rubble-pile” objects may experience the Brazil Nut Effect (BNE). When a collection of particles of similar densities, but of different sizes, is shaken, smaller particles will move parallel to the local gravity vector while larger objects will do the opposite. Thus, when asteroids are shaken by impacts, they may experience the BNE as possibly evidenced by large boulders seen on their surfaces. I found while the BNE is plausible on asteroids, it is confined to only the outer layers. The Moon, which formed with a Lunar Magma Ocean (LMO), is the next topic of this work. The LMO is due to the Moon forming rapidly after a giant impact between the proto-Earth and another planetary body. The first 80% of the LMO solidified rapidly at which point a floatation crust formed and slowed solidification of the remaining LMO. Impact bombardment during this cooling process, while an important component, has not been studied in detail. Impacts considered here are from debris generated during the formation of the Moon. I developed a thermal model that incorporates impacts and find that impacts may have either expedited or delayed LMO solidification. Finally, I return to affect to consider the differences in attitudes towards science between students enrolled in fully-online degree programs and those enrolled in traditional, in-person degree programs. I analyzed pre- and post-course survey data from the online astrobiology course Habitable Worlds. Unlike their traditional program counterparts, students enrolled in online programs started the course with better attitudes towards science and also further changed towards more positive attitudes during the course. Along with important conclusions in three research fields, this work aims to demonstrate the importance of affect in both scientific research and science education.
ContributorsDingatantrige Perera, Jude Viranga (Author) / Asphaug, Erik (Thesis advisor) / Semken, Steven (Thesis advisor) / Anbar, Ariel (Committee member) / Elkins-Tanton, Linda T. (Committee member) / Robinson, Mark (Committee member) / Arizona State University (Publisher)
Created2017
Description
There are more than 20 active missions exploring planets and small bodies beyond Earth in our solar system today. Many more have completed their journeys or will soon begin. Each spacecraft has a suite of instruments and sensors that provide a treasure trove of data that scientists use to advance our understanding of the past, present, and future of the solar system and universe. As more missions come online and the volume of data increases, it becomes more difficult for scientists to analyze these complex data at the desired pace. There is a need for systems that can rapidly and intelligently extract information from planetary instrument datasets and prioritize the most promising, novel, or relevant observations for scientific analysis. Machine learning methods can serve this need in a variety of ways: by uncovering patterns or features of interest in large, complex datasets that are difficult for humans to analyze; by inspiring new hypotheses based on structure and patterns revealed in data; or by automating tedious or time-consuming tasks. In this dissertation, I present machine learning solutions to enhance the tactical planning process for the Mars Science Laboratory Curiosity rover and future tactically-planned missions, as well as the science analysis process for archived and ongoing orbital imaging investigations such as the High Resolution Imaging Science Experiment (HiRISE) at Mars. These include detecting novel geology in multispectral images and active nuclear spectroscopy data, analyzing the intrinsic variability in active nuclear spectroscopy data with respect to elemental geochemistry, automating tedious image review processes, and monitoring changes in surface features such as impact craters in orbital remote sensing images. Collectively, this dissertation shows how machine learning can be a powerful tool for facilitating scientific discovery during active exploration missions and in retrospective analysis of archived data.
ContributorsKerner, Hannah Rae (Author) / Bell, James F. (Thesis advisor) / Ben Amor, Heni (Thesis advisor) / Wagstaff, Kiri L (Committee member) / Hardgrove, Craig J (Committee member) / Shirzaei, Manoochehr (Committee member) / Arizona State University (Publisher)
Created2019