Astrobiology Research Rotations

Sam Gilbert-Janizek Presenting: Predicting Outgassing Rates for L 98-59 b with an Interior Model

AB Rotation with Prof. Laura Schaefer (Stanford University)

JWST is providing our first glimpses of rocky exoplanet atmospheres and ushering in an era of exoplanet characterization. Inner planets orbiting M-dwarf stars with higher equilibrium temperatures are particularly advantageous for observation in thermal emission, which has already been used to rule out thick CO2 atmospheres on TRAPPIST-1 c. To support the interpretation of JWST observations, we require interior models, which self-consistently calculate the planet’s thermal evolution, to evaluate the stability of potential atmospheric states. While numerous planetary interior models assume that exoplanets evolve with Earth-like plate tectonics, it is thought that stagnant-lid planets, like present-day Mars and Venus in our Solar System, occur more commonly. We use a revised thermal evolution model to predict outgassing rates for CO2, CO, H2, and H2O for the M-dwarf planet L 98-59 b, a current JWST Cycle 2 target. We modify the thermal evolution model to enforce a stagnant lid carbon cycle regime in which eruption from the melt layer replaces outgassing at mid ocean ridges, and inter-plate subduction is neglected. Though further model debugging is required, we preliminarily show that, even when varying the mantle redox state and the initial water inventory, eruption cannot outgas volatiles efficiently enough to maintain water on the planet’s surface. Similarly, we predict relatively low CO2 outgassing rates compared to the Earth. If the planet retains its atmospheric CO2, it may sustain planetary surface temperatures of 800-900 K, which are significantly hotter than the planet’s predicted equilibrium temperature (Teq = 558).

Joshua Sacks Presenting: Expanding the Agnostic Biosignature Toolkit: Estimating Molecular Assembly with Gas Chromatography/Mass Spectrometry 

              Life detection on other worlds is a central goal of the field of Astrobiology. The development of agnostic biosignatures, which do not make assumptions about the character of the life present, are considered an important step towards achieving this goal. Molecular assembly theory (MA) is a promising theoretical approach for using mass spectrometry to quantify the complexity of organic molecules which can then be used as an agnostic proxy for biological activity. However, there are many analytical challenges that must be overcome before molecular assembly can be used on future missions. Current MA approaches use liquid-chromatography/mass spectrometry to measure the complexity of biological molecules, but liquid-chromatography has not been developed for spaceflight. Gas chromatography/mass spectrometry (GC-MS) is heritage technique with an extensive history of use in extraterrestrial missions but brings unique challenges such as the need for derivatization. We set out to answer two questions: 1) can GC-MS be used to estimate molecular complexity? and 2) what instrumental or methodological considerations should be considered for future development of mass spectrometry-based agnostic biosignatures. To answer these questions, we developed a mass spectrometry and data processing workflow to analyze compounds individually and in complex mixtures and count the number of fragments (an estimate of molecular complexity) produced through election ionization (MS1) and tandem fragmentation (MS2) approaches. We identified a positive, linear relationship between unique fragment number and MA index that appears to be specific to distinct compound classes. We tested the impact of different quality control thresholds and MS2 collision energies to identify optimal parameters for both the instrument and the data processing code. We then applied the workflow to measure unknown compounds in a living (cyanobacterial extract) and an extraterrestrial non-living (Murchison meteorite extract) sample. These results will inform future instrument development for life detection on other worlds.