Ames Research Center
  • Mountain View, United States
Recent publications
The Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) is a NASA Earth Ventures Suborbital investigation designed to test the hypothesis that oceanic frontogenesis and the kilometer-scale (“submesoscale”) instabilities that accompany it make important contributions to vertical exchange of climate and biological variables in the upper ocean. These processes have been difficult to resolve in observations, making model validation challenging. A necessary step toward testing the hypothesis was to make accurate measurements of upper-ocean velocity fields over a broad range of scales and to relate them to the observed variability of vertical transport and surface forcing. A further goal was to examine the relationship between surface velocity, temperature and chlorophyll measured by remote sensing, and their depth-dependent distributions, within and beneath the surface boundary layer. To achieve these goals, we used aircraft-based remote sensing, satellite remote sensing, ships, drifter deployments, and a fleet of autonomous vehicles. The observational component of S-MODE consisted of three campaigns, all conducted in the Pacific Ocean approximately 100 km west of San Francisco during 2021-2023 fall and spring. S-MODE was enabled by recent developments in remote sensing technology that allowed operational airborne observation of ocean surface velocity fields and by advances in autonomous instrumentation that allowed coordinated sampling with dozens of uncrewed vehicles at sea. The coordinated use of remote sensing measurements from three aircraft with arrays of remotely operated vehicles and other in situ measurements is a major novelty of S-MODE. All S-MODE data is freely available, and its use is encouraged.
Exoplanet surveys have shown a class of abundant exoplanets smaller than Neptune on close, <100-day orbits1, 2, 3–4. These planets form two populations separated by a natural division at about 1.8 R⊕ termed the radius valley. It is uncertain whether these populations arose from separate dry versus water-rich formation channels, evolved apart because of long-term atmospheric loss or a combination of both5, 6, 7, 8, 9, 10, 11, 12, 13–14. Here we report observations of ongoing hydrogen loss from two sibling planets, TOI-776 b (1.85 ± 0.13 R⊕) and TOI-776 c (2.02 ± 0.14 R⊕), the sizes of which near the radius valley and mature (1–4 Gyr) age make them valuable for investigating the origins of the divided population of which they are a part. During the transits of these planets, absorption appeared against the Lyman-α emission of the host star, compatible with hydrogen escape at rates equivalent to 0.03–0.6% and 0.1–0.9% of the total mass per billion years of each planet, respectively. Observations of the outer planet, TOI-776 c, are incompatible with an outflow of dissociated steam, suggesting both it and its inner sibling formed in a dry environment. These observations support the strong role of hydrogen loss in the evolution of close-orbiting sub-Neptunes5, 6, 7–8,15,16.
Magnetic reconnection is a ubiquitous plasma process that transforms magnetic energy into particle energy during eruptive events throughout the universe. Reconnection not only converts energy during solar flares and geomagnetic substorms that drive space weather near Earth, but it may also play critical roles in the high energy emissions from the magnetospheres of neutron stars and black holes. In this review article, we focus on collisionless plasmas that are most relevant to reconnection in many space and astrophysical plasmas. Guided by first-principles kinetic simulations and spaceborne in-situ observations, we highlight the most recent progress in understanding this fundamental plasma process. We start by discussing the non-ideal electric field in the generalized Ohm’s law that breaks the frozen-in flux condition in ideal magnetohydrodynamics and allows magnetic reconnection to occur. We point out that this same reconnection electric field also plays an important role in sustaining the current and pressure in the current sheet and then discuss the determination of its magnitude (i.e., the reconnection rate), based on force balance and energy conservation. This approach to determining the reconnection rate is applied to kinetic current sheets with a wide variety of magnetic geometries, parameters, and background conditions. We also briefly review the key diagnostics and modeling of energy conversion around the reconnection diffusion region, seeking insights from recently developed theories. Finally, future prospects and open questions are discussed.
Plain Language Summary Measuring the temperature of the Moon revealed the widespread presence of “cold spots,” which are features that have distinctly low temperatures during the night, but camouflage with the background during the day. When the BepiColombo spacecraft arrives at Mercury, we will have the first opportunity to observe cold spots on Mercury, thanks to the first continuous measurements of surface temperature throughout the planet's day/night. Using what we know about lunar cold spots, here we model cold spots on Mercury at different locations. For a given location and cold spot size/age, cold spots on Mercury should be colder than cold spots on the Moon during nighttime due to greater daily temperature changes. Cold spots on Mercury should be coldest just after sunset, but visible throughout the entire night. NASA's crashed MESSENGER spacecraft should have a created a cold spot, but it is probably too small for BepiColombo to detect.
We have carried out first principles calculations of transport properties of the title atom–atom systems using accurate ab initio electronic structure methods and quantum scattering. We go beyond the Born–Oppenheimer approximation and show how one can properly include the spin and orbital angular momentum of atoms in the calculations. We give the explicit transformation between coupled LS atomic states, where L is the total electron angular momentum and S is the total spin angular momentum, and the diatomic Hund’s case (a) basis. We include both Coulomb spin–orbit interaction as well as the effect of the magnetic-moments of the electrons via the Breit interaction. The relations between the long-range forces of different symmetry electronic states are given for S + P and P + P asymptotes.
Large-scale molecular dynamics (MD) simulations enabled by computationally efficient semiempirical potentials are an invaluable tool for materials modeling. In the case of metallic alloys, embedded atom method (EAM) and Finnis–Sinclair (FS) potentials are a reasonable choice based on their good balance of quality and computational cost. However, these semiempirical potentials are not suitable for simulating ionic systems, which prevents their use in studying many technologically relevant metal–oxide systems. The charge transfer ionic potential (CTIP), which can utilize EAM/FS potentials available in the literature together with a variable charge representation of electrostatic interactions, should be a reasonable choice for performing reliable and computationally efficient MD simulations of such systems. However, only a few such potentials are available in the literature, and their computational cost is much higher compared to EAM/FS potentials. In the present work, we have attempted to remedy these deficiencies by combining several modifications to the CTIP model proposed in the literature and efficiently implementing them into the widely used Large-scale Atomic/Molecular Massively Parallel Simulator MD code. Using these modifications, we have developed a new Ni–O CTIP parameterization, which has been tested in several different scenarios of interest. First, the early stages of Ni surface oxidation were simulated, demonstrating the nucleation and growth of a crystalline NiO film across the surface. Second, solidification and vitrification in the Ni–O system were investigated, demonstrating that the new CTIP parameterization provides reasonable agreement with the experimentally determined equilibrium phase diagram. Finally, we studied the interaction of dislocations in a Ni matrix with a NiO inclusion using a simulation cell with an unprecedented number of atoms for a variable charge MD simulation. Thus, the approach utilized in the present study is an efficient method to simulate large scale atomic mechanisms in metal–oxide systems.
A leading approach to algorithm design aims to minimize the number of operations in an algorithm’s compilation. One intuitively expects that reducing the number of operations may decrease the chance of errors. This paradigm is particularly prevalent in quantum computing, where gates are hard to implement and noise rapidly decreases a quantum computer’s potential to outperform classical computers. Here, we find that minimizing the number of operations in a quantum algorithm can be counterproductive, leading to a noise sensitivity that induces errors when running the algorithm in non-ideal conditions. To show this, we develop a framework to characterize the resilience of an algorithm to perturbative noises (including coherent errors, dephasing, and depolarizing noise). Some compilations of an algorithm can be resilient against certain noise sources while being unstable against other noises. We condense these results into a tradeoff relation between an algorithm’s number of operations and its noise resilience. We also show how this framework can be leveraged to identify compilations of an algorithm that are better suited to withstand certain noises.
We investigate Gravity Waves (GWs) in the lower atmosphere of Mars based on pressure timeseries acquired by the InSight lander. We compile a climatology showing that most GW activity detected at the InSight landing site takes place after the sunrise and sunset; they are almost absent during the aphelion season, and more prominent around the equinoxes, with variations during dust events and interannual variations. We find GWs with coherent phases in different sols, and a previously unnoticed coincidence of GW activity with those moments in which the diurnal cycle (of tidal origin) exhibits the fastest increases in absolute pressure. We explore the possibility that some of these GWs might actually be high‐order harmonics of thermal tides transiently interfering constructively to produce relevant meteorological patterns, and discuss other interpretations based on wind patterns. The so‐called Terminator Waves observed on Earth might also explain some of our observations.
Refractory black carbon (rBC) is a primary aerosol species, produced through incomplete combustion, that absorbs sunlight and contributes to positive radiative forcing. The overall climate effect of rBC depends on its spatial distribution and atmospheric lifetime, both of which are impacted by the efficiency with which rBC is transported or removed by convective systems. These processes are poorly constrained by observations. It is especially interesting to investigate rBC transport efficiency through the Asian Summer Monsoon (ASM) since this meteorological pattern delivers vast quantities of boundary layer air from Asia, where rBC emissions are high to the upper troposphere/lower stratosphere (UT/LS) where the lifetime of rBC is expected to be long. Here, we present in situ observations of rBC made during the Asian Summer Monsoon Chemistry and Climate Impact Project of summer, 2022. We use observed relationships between rBC and CO in ASM outflow to show that rBC is removed nearly completely (>98%) from uplifted air and that rBC concentrations in ASM outflow are statistically indistinguishable from the UT/LS background. We compare observed rBC and CO concentrations to those expected based on two chemical transport models and find that the models reproduce CO to within a factor of 2 at all altitudes whereas rBC is overpredicted by a factor of 20–100 at altitudes associated with ASM outflow. We find that the rBC particles in recently convected air have thinner coatings than those found in the UTLS background, suggesting transport of a small number of rBC particles that are negligible for concentration.
Serpentinization, the reaction of water with ultramafic rock, produces reduced, hyperalkaline, and H2-rich fluids that support a variety of hydrogenotrophic microbial metabolisms. Previous work indicates the occurrence of methanogenesis in fluids from the actively serpentinizing Samail Ophiolite in the Sultanate of Oman. While those fluids contain abundant H2 to fuel hydrogenotrophic methanogenesis (CO2 + 4H2 ➔ CH4 + 2H2O), the concentration of CO2 is very low due to the hyperalkalinity (> pH 11) and geochemistry of the fluids. As a result, species such as formate and acetate may be important as alternative methanogenic substrates. In this study we quantified the impact of inorganic carbon, formate and acetate availability for methanogenic metabolisms, across a range of fluid chemistries, in terms of (1) the potential diffusive flux of substrates to the cell, (2) the Affinity (Gibbs energy change) associated with methanogenic metabolism, and (3) the energy “inventory” per kg fluid. In parallel, we assessed the genomic potential for the conduct of those three methanogenic modes across the same set of fluids and consider the results within the quantitative framework of energy availability. We find that formatotrophic methanogenesis affords a higher Affinity (greater energetic yield) than acetoclastic and hydrogenotrophic methanogenesis in pristine serpentinized fluids and, in agreement with previous studies, find genomic evidence for a methanogen of the genus Methanobacterium to carry out formatotrophic and hydrogenotrophic methanogenesis, with the possibility of even using bicarbonate as a supply of CO2. Acetoclastic methanogenesis is also shown to be energetically favorable in these fluids, and we report the first detection of a potential acetoclastic methanogen of the family Methanosarcinaceae, which forms a distinct clade with a genome from the serpentinizing seafloor hydrothermal vent field, Lost City. These results demonstrate the applicability of an energy availability framework for interpreting methanogen ecology in serpentinizing systems.
Shape memory alloys are used in many applications which require them to undergo numerous transformation cycles. Generally, an important property for use in such cyclic applications is a small hysteresis, which is linked to functional fatigue resistance. Leveraging microstructural features which promote martensite nucleation is one strategy to achieve reduced hysteresis. In the austenite phase of NiTi, the Σ9(114)[110] symmetric tilt grain boundary has been recognized as one such feature. We have performed a series of molecular dynamics simulations to characterize this grain boundary and its relationship to the martensitic transformation. Upon thermal equilibration, even above the transformation temperature, the grain boundary spontaneously forms a twinned martensite structure at its core, which serves as a nucleus during the martensitic transformation. When the grain boundaries are near one another, the energetic barrier to the transformation is reduced and a small hysteresis results. In polycrystalline microstructures, the added constraints lead to an expanded transformation window and retained austenite upon cooling. Based on these results, grain boundary engineering could be an effective strategy to produce shape memory alloys with improved performance in cyclic applications.
Evaporation or freezing of water-rich fluids with dilute concentrations of dissolved salts can produce brines, as observed in closed basins on Earth¹ and detected by remote sensing on icy bodies in the outer Solar System2,3. The mineralogical evolution of these brines is well understood in regard to terrestrial environments⁴, but poorly constrained for extraterrestrial systems owing to a lack of direct sampling. Here we report the occurrence of salt minerals in samples of the asteroid (101955) Bennu returned by the OSIRIS-REx mission⁵. These include sodium-bearing phosphates and sodium-rich carbonates, sulfates, chlorides and fluorides formed during evaporation of a late-stage brine that existed early in the history of Bennu’s parent body. Discovery of diverse salts would not be possible without mission sample return and careful curation and storage, because these decompose with prolonged exposure to Earth’s atmosphere. Similar brines probably still occur in the interior of icy bodies Ceres and Enceladus, as indicated by spectra or measurement of sodium carbonate on the surface or in plumes2,3.
Organic matter in meteorites reveals clues about early Solar System chemistry and the origin of molecules important to life, but terrestrial exposure complicates interpretation. Samples returned from the B-type asteroid Bennu by the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer mission enabled us to study pristine carbonaceous astromaterial without uncontrolled exposure to Earth’s biosphere. Here we show that Bennu samples are volatile rich, with more carbon, nitrogen and ammonia than samples from asteroid Ryugu and most meteorites. Nitrogen-15 isotopic enrichments indicate that ammonia and other N-containing soluble molecules formed in a cold molecular cloud or the outer protoplanetary disk. We detected amino acids (including 14 of the 20 used in terrestrial biology), amines, formaldehyde, carboxylic acids, polycyclic aromatic hydrocarbons and N-heterocycles (including all five nucleobases found in DNA and RNA), along with ~10,000 N-bearing chemical species. All chiral non-protein amino acids were racemic or nearly so, implying that terrestrial life’s left-handed chirality may not be due to bias in prebiotic molecules delivered by impacts. The relative abundances of amino acids and other soluble organics suggest formation and alteration by low-temperature reactions, possibly in NH3-rich fluids. Bennu’s parent asteroid developed in or accreted ices from a reservoir in the outer Solar System where ammonia ice was stable.
Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km² (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.
Massive galaxies in cooling-flow clusters display clear evidence of feedback from active galactic nuclei (AGNs). Joint X-ray and radio observations have shown that AGN radio jets push aside the surrounding hot gas and form cavities in the hot intracluster medium (ICM). These systems host complex, kiloparsec-scale, multiphase filamentary structures, from warm and ionized (10,000 K) to cold and molecular (<100 K). These striking clumpy filaments are believed to be a natural outcome of thermally unstable cooling from the hot ICM, probably triggered by feedback processes while contributing to feeding the AGN via chaotic cold accretion (CCA). However, the detailed constraints on the formation mechanism of the filaments are still uncertain, and the connection between the different gas phases has to be fully unveiled. By leveraging a sample of seven X-ray-bright cooling-flow clusters, we have discovered a tight positive correlation between the X-ray surface brightness and the Hα surface brightness of the filaments over two orders of magnitude, as also found in stripped tails. We further show the quantitative consistency of such a relation with CCA predictions by leveraging hydrodynamical simulations. This discovery provides evidence for a shared excitation mechanism between hot and warm filaments, where multiphase condensation, triggered by AGN feedback, drives their tight co-evolution.
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