Duncan Lyster

ORCID: 0009-0006-3295-7685
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About
Contact & Profiles
Research Areas
  • Planetary Science and Exploration
  • Spacecraft and Cryogenic Technologies
  • Astro and Planetary Science
  • Infection Control and Ventilation
  • Spaceflight effects on biology
  • Space Satellite Systems and Control
  • Climate Change and Health Impacts
  • Space Science and Extraterrestrial Life
  • Spacecraft Design and Technology
  • Thermal Regulation in Medicine

University of Oxford
2024

University of Exeter
2020

Identification of habitable planets beyond our solar system is a key goal current and future space missions. Yet habitability depends not only on the stellar irradiance, but equally constituent parts planetary atmosphere. Here we show, for first time, that radiatively active mineral dust will have significant impact Earth-like exoplanets. On tidally-locked planets, cools day-side warms night-side, significantly widening zone. Independent orbital configuration, suggest airborne can postpone...

10.1038/s41467-020-16543-8 article EN cc-by Nature Communications 2020-06-09

Introduction: Enceladus is a key target for astrobiological study, with its subsurface ocean and cryovolcanism focused at the South Pole’s 'tiger stripe' fractures; understanding temperature variations essential to decipher moon's geological activity potential life. Blending heritage from TechDemoSat-1, Mars Climate Sounder, Lunar Trailblazer, University of Oxford’s Thermal Mapper (ETM) faces new opportunities challenges in observing this active icy moon Saturn. This high...

10.5194/egusphere-egu24-20872 preprint EN 2024-03-11

Abstract:Understanding the thermal properties of comets, asteroids, and icy moons is crucial for advancing our knowledge their composition evolution. An increasing number missions to these bodies, including Rosetta, Osiris-Rex, Europa Clipper, JUICE, necessitate models that accurately consider complex topographies.We have developed a Python model predicts diurnal temperature variations on airless bodies in three dimensions, factoring morphologies. This significantly improves simulation...

10.5194/epsc2024-1121 preprint EN 2024-07-03
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