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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Toba volcano super eruption destroyed the ozone layer and caused a human population bottleneck

Volcanic eruptions trigger a broad spectrum of climatic responses. For example, the Mount Pinatubo eruption in 1991 forced an El Niño and global cooling, and the Tambora eruption in 1815 caused the "Year Without a Summer." Especially grand eruptions such as Toba around 74,000 years ago can push the Earth's climate into a volcanic winter state, significantly lowering the surface temperature and precipitation globally. Here we present a new, previously overlooked element of the volcanic effects spectrum: the radiative mechanism of stratospheric ozone depletion. We found that the volcanic plume of Toba enhanced the UV optical depth and suppressed the primary formation of stratospheric ozone from O2 photolysis. Sulfate aerosols additionally reflect the photons needed to break the O2 bond (λ < 242 nm), otherwise controlled by ozone absorption and Rayleigh scattering alone during volcanically quiescent conditions. Our NASA GISS ModelE simulations of the Toba eruption reveal up to 50% global ozone loss due to the overall photochemistry perturbations of the sulfate aerosols. We also consider and quantify the radiative effects of SO2, which partially compensated for the ozone loss by inhibiting the photolytic O3 sink. Our analysis shows that the magnitude of the ozone loss and UV-induced health-hazardous effects after the Toba eruption are similar to those in the aftermath of a potential nuclear conflict. These findings suggest a “Toba ozone catastrophe" as a likely contributor to the historic population decline in this period, consistent with a genetic bottleneck in human evolution.

Toba volcano↗
DOE OSTI2024

Twisto-Electrochemical Activity Volcanoes in Trilayer Graphene

In this work, we develop a twist-dependent electrochemical activity map, combining a low-energy continuum electronic structure model with modified Marcus–Hush–Chidsey kinetics in trilayer graphene. We identify a counterintuitive rate enhancement region spanning the magic angle curve and incommensurate twists in the system geometry. We find a broad activity peak with a ruthenium hexamine redox couple in regions corresponding to both magic angles and incommensurate angles, a result qualitatively distinct from the twisted bilayer case. Flat bands and incommensurability offer new avenues for reaction rate enhancements in electrochemical transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

CO oxidation on MgAl 2 O 4 supported Ir n : activation of lattice oxygen in the subnanometer regime and emergence of nuclearity-activity volcano

CO oxidation on Pt group metals is affected by the metal size and reducibility of the oxide support. In this study, we report that Ir supported on MgAl 2 O 4 , traditionally considered non-reducible, exhibits properties similar to reducible oxides when the Ir size is in the subnanometer regime. To show this effect, we synthesized subnanometer Ir clusters and compared their properties to single atoms and nanoparticles (1–1.5 nm). The CO oxidation activity is highest on Ir 0.6–0.8nm while showing distinctly different reaction orders in CO and O 2 (0, +0.4), than single atoms (1, 0) and nanoparticles (–1, +1). Microcalorimetry, in situ X-ray absorption, and infrared spectroscopies show that the CO-saturated Ir 0.6–0.8nm clusters could adsorb and activate O 2 despite binding CO more strongly than nanoparticles. Density functional theory calculations on CO saturated Ir 4 clusters suggest that the increased activity is due to the ability to activate O 2 on oxygen vacancies at the Ir–MgAl 2 O 4 interface. The findings show the important effect of the metal nuclearity on the support and catalyst properties and can guide future design of CO oxidation catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

RAPID STRUCTURE DETECTION IN SUPPORT OF DISASTER RESPONSE : A CASE STUDY OF THE 2018 KILAUEA VOLCANO ERUPTION

Disaster response requires timely damage assessment to prioritize rescue and restoration resources. However, providing critical and actionable knowledge after a natural disaster can be challenging due to the scale and the type of damages. This paper describes how remote sensing and machine learning techniques can be used to support rapid structure detection in the wake of a disaster. We use high resolution satellite imagery to identify structures on Hawaii’s Big Island to support the Federal Emergency Management Agency’s response efforts during the 2018 K¯ilauea lava flow incident. This framework specifically showcases the generalizability of CNN models with no need to collect additional training samples to quickly map structures in pre- and post-event imagery and provide timely information to assist government agencies evaluating the extent and potential loss of disaster. With this case study, we further point out future directions to benefit similar larger scale efforts based on the lessons learned.

Laverdiere, Melanie↗