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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Curiosity Rover's Exploration of Glen Torridon, Gale Crater, Mars: An Overview of the Campaign and Scientific Results

The Mars Science Laboratory rover, Curiosity, explored the clay mineral-bearing Glen Torridon region for 1 Martian year between January 2019 and January 2021, including a short campaign onto the Greenheugh pediment. The Glen Torridon campaign sought to characterize the geology of the area, seek evidence of habitable environments, and document the onset of a potentially global climatic transition during the Hesperian era. Curiosity roved 5 km in total throughout Glen Torridon, from the Vera Rubin ridge to the northern margin of the Greenheugh pediment. Curiosity acquired samples from 11 drill holes during this campaign and conducted the first Martian thermochemolytic-based organics detection experiment with the Sample Analysis at Mars instrument suite. The lowest elevations within Glen Torridon represent a continuation of lacustrine Murray formation deposits, but overlying widespread cross bedded sandstones indicate an interval of more energetic fluvial environments and prompted the definition of a new stratigraphic formation in the Mount Sharp group called the Carolyn Shoemaker formation. Glen Torridon hosts abundant phyllosilicates yet remains compositionally and mineralogically comparable to the rest of the Mount Sharp group. Glen Torridon samples have a great diversity and abundance of sulfur-bearing organic molecules, which are consistent with the presence of ancient refractory organic matter. The Glen Torridon region experienced heterogeneous diagenesis, with the most striking alteration occurring just below the Siccar Point unconformity at the Greenheugh pediment. Results from the pediment campaign show that the capping sandstone formed within the Stimson Hesperian aeolian sand sea that experienced seasonal variations in wind direction.

58 GEOSCIENCES↗
DOE OSTI2021

The price of curiosity: information recovery in de Sitter space

Recent works have revealed that quantum extremal islands can contribute to the fine-grained entropy of black hole radiation reproducing the unitary Page curve. In this paper, we use these results to assess if an observer in de Sitter space can decode information hidden behind their cosmological horizon. By computing the fine-grained entropy of the Gibbons-Hawking radiation in a region where gravity is weak we find that this is possible, but the observer’s curiosity comes at a price. At the same time the island appears, which happens much earlier than the Page time, a singularity forms which the observer will eventually hit. We arrive at this conclusion by studying de Sitter space in Jackiw-Teitelboim gravity. We emphasize the role of the observer collecting radiation, breaking the thermal equilibrium studied so far in the literature. By analytically solving for the backreacted geometry we show how an island appears in this out-of-equilibrium state.

2D gravity↗
DOE OSTI2024

A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments

Optimization of experimental materials synthesis and characterization through active learning methods has been growing over the last decade, with examples ranging from measurements of diffraction on combinatorial alloys at synchrotrons, to searches through chemical space with automated synthesis robots for perovskites. In virtually all cases, the target property of interest for optimization is defined a priori with the ability to shift the trajectory of the optimization based on human-identified findings during the experiment is lacking. Thus, to highlight the best of both human operators and AI-driven experiments, here we present the development of a human–AI collaborated experimental workflow, via a Bayesian optimized active recommender system (BOARS), to shape targets on the fly with human real-time feedback. Here, the human guidance overpowers AI at early iteration when prior knowledge (uncertainty) is minimal (higher), while the AI overpowers the human during later iterations to accelerate the process with the human-assessed goal. We showcase examples of this framework applied to pre-acquired piezoresponse force spectroscopy of a ferroelectric thin film, and in real-time on an atomic force microscope, with human assessment to find symmetric hysteresis loops. It is found that such features appear more affected by subsurface defects than the local domain structure. This work shows the utility of human–AI approaches for curiosity driven exploration of systems across experimental domains.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Curiosity driven exploration to optimize structure–property learning in microscopy

Rapidly determining structure–property correlations in materials is an important challenge in better understanding fundamental mechanisms and greatly assists in materials design. In microscopy, imaging data provides a direct measurement of the local structure, while spectroscopic measurements provide relevant functional property information. Deep kernel active learning approaches have been utilized to rapidly map local structure to functional properties in microscopy experiments, but are computationally expensive for multi-dimensional and correlated output spaces. Here, we present an alternative lightweight curiosity algorithm which actively samples regions with unexplored structure–property relations, utilizing a deep-learning based surrogate model for error prediction. We show that the algorithm outperforms random sampling for predicting properties from structures, and provides a convenient tool for efficient mapping of structure–property relationships in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Exploring Mars with Curiosity and its Laser

The 1-ton Curiosity rover has been exploring Gale crater on Mars since 2012. Its payload includes the ChemCam laser instrument, led by LANL. ChemCam uses the laser-induced breakdown spectroscopy (LIBS) technique to obtain remote elemental compositions of Mars rocks and soils. In this presentation I explain how we operate this instrument on Mars and what we have discovered.

42 ENGINEERING↗
DOE OSTI2021

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Networks (DGAPNs), a curiosity-driven reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. Here, the framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention Network (sGAT) that leverages self-attention over both node and edge attributes as well as encoding spatial structure -- this capability is of considerable interest in areas such as molecular and synthetic biology and drug discovery. An attentional policy network is then introduced to learn decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with enhanced stability. Exploration is efficiently encouraged by incorporating innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while increasing the diversity of proposed molecules and reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Networks (DGAPNs), a curiosity-driven reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention Network (sGAT) that leverages self-attention over both node and edge attributes as well as encoding spatial structure -- this capability is of considerable interest in areas such as molecular and synthetic biology and drug discovery. An attentional policy network is then introduced to learn decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with enhanced stability. Exploration is efficiently encouraged by incorporating innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while increasing the diversity of proposed molecules and reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2021

Early-Career Reflections: Curiosity Saves the Researcher

Defining your own research questions and working with a clear direction in mind is key to a successful career in academia. Evangelia Spyrou explains how following her thirst for knowledge in her specific area of interest prepared her for when research opportunities arose.

electricity↗
DOE OSTI2022

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure --- this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

Collegiate Competitions Spark Curiosity and Careers in Water Power

Hydropower is the oldest renewable energy source, powering U.S. lives and livelihoods for more than a century, and marine energy may be the youngest. But old or young, both forms of water power will play a significant, vital role in helping the United States transition to a carbon-pollution -free energy sector by 2035. And to do that, these growing technologies need a workforce to match.

HYDRO ENERGY↗
DOE OSTI2022

SPATIAL GRAPH ATTENTION AND CURIOSITY-DRIVEN POLICY FOR ANTIVIRAL DRUG DISCOVERY

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure - this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis.

Wu, Y↗
DOE OSTI2024

Collegiate Competitions Spark Curiosity and Careers in Water Power

Hydropower is the oldest renewable energy source, and marine energy may be the youngest. Regardless of whether they are old or young, both forms of water power will play a significant role in helping the United States reach a 100% carbon-free energy sector by 2035. To meet the challenge, we need a strong water power workforce.

collegiate competitions↗
DOE OSTI2026

Amapari Marker Band Metal‐Enrichments: Potential Mechanisms and Implications for Surface and Subsurface Water and Weathering in Gale Crater

NASA's Curiosity rover is exploring a 5 km tall sedimentary mound that is hypothesized to record the transition from a warm and wet (phyllosilicate-rich) to a cold and drier (sulfate-rich) Mars. Evidence of magnesium sulfate-bearing rock has shown that Curiosity has crossed through this phyllosilicate-sulfate transition. Recently, Curiosity arrived at the Amapari Marker Band, a darker, indurated unit that can be traced laterally for tens of kilometers in orbiter images. Here, Curiosity found evidence for a very broad lake, and bedforms interpreted as wave-ripple laminated sedimentary rock that likely was deposited in shallow water in the explored location, before becoming a deeper lake. These rocks are enriched in Fe, Mn, and Zn which has major implications for groundwater paleohydrology in Gale crater. Three formation hypotheses are considered: concretion formation during early diagenetic alteration of shallow lake sediments, laterization or leaching of the sediments, and addition of Fe, Mn, and Zn by a mildly acidic and reducing groundwater interacting with a redox and/or pH front in a stratified lake. The preferred interpretation of the metal enrichments within the Amapari Marker band sedimentary rocks is that they formed in a shallow water environment at a redox and/or pH front within the ripple unit, which drove precipitation and concentration of metals. If the enrichments are due to groundwater alteration, these processes could link subsurface and surface environments. Water and the presence of high amounts of redox sensitive elements and other metals are favorable indicators for habitability.

58 GEOSCIENCES↗
DOE OSTI2018

Using ChemCam LIBS data to constrain grain size in rocks on Mars: Proof of concept and application to rocks at Yellowknife Bay and Pahrump Hills, Gale crater

Grain size in martian sedimentary rocks can be constrained using point-to-point chemical variabilities in Laser Induced Breakdown Spectroscopy (LIBS) data from the ChemCam instrument on the Mars Science Laboratory (MSL) Curiosity rover. The diameter of each point ablated by the ChemCam laser is in the range of medium to coarse sand in size. Thus, rocks with grains significantly smaller than the laser spot size produce bulk rock compositions at each LIBS point and low point-to-point chemical variability among LIBS points. In contrast, analyses of rocks with grains about the size of the spot or larger contain contributions from individual grains at each point and often have high point-to-point chemical variability. Here the Gini index, a statistical parameter, was used to calculate the point-to-point chemical variability in major-element oxide compositions derived from the ChemCam LIBS data. First, the total range of each LIBS major-element oxide composition was normalized from 0 to 1 across all LIBS observations. Then the Gini index was calculated for each oxide in each LIBS observation. Finally, the Gini indices of each oxide were averaged to derive a Gini index mean score, G MEAN , for each LIBS observation. A correlation between G MEAN and grain size was validated using sedimentary rocks of various grain sizes from the Yellowknife Bay formation and the Pahrump Hills member of the Murray formation in Gale crater. Overall, finer-grained rocks had smaller G MEAN than coarser-grained rocks. To calibrate G MEAN to grain size, grain size estimates based on visual assessment of high-resolution images were compared to G MEAN values for the same targets to create a calibrated scale. This calibrated scale was used to infer the grain size of rocks with unknown grain size. Overall, the grain sizes predicted for rocks with unknown grain size overlapped with those of known grain size from the same units and/or bedrock targets. The grain sizes inferred using the G MEAN based on ChemCam LIBS data are complimentary to those determined from images and both techniques can be used to improve interpretations of the depositional environments of rocks analyzed by Curiosity and future Mars missions with LIBS, such as the Mars 2020 rover.

58 GEOSCIENCES↗
DOE OSTI2023

Boron adsorption in clay minerals: Implications for martian groundwater chemistry and boron on Mars

Boron has been detected on Mars in calcium-sulfate veins found within clay mineral rich rocks on Mars by the Mars Science Laboratory (MSL) Curiosity rover using Laser Induced Breakdown Spectroscopy (LIBS) analysis. Borates play a vital role in stabilizing ribose on Earth and has been suggested as a key requirement for life. Borate ions readily adsorb to phyllosilicate clay minerals. The discovery of boron on Mars in proximity to phyllosilicate-bearing bedrock may have strong implications for potential past prebiotic conditions on Mars. In this study we generated a suite of clay minerals with adsorbed borate, including both typical terrestrial clay minerals (montmorillonite) and Mars-analog clay minerals (nontronite, saponite, griffithite), to understand controls on borate adsorption and to analyze with LIBS to compare with MSL data. Clay minerals were subjected to mineralogical and chemical analysis before and after adsorption. Adsorption analysis revealed that the Mars analog clay minerals adsorbed less boron than terrestrial counterparts, but within comparable amounts to those detected on Mars and in meteorites. Post-adsorption analysis by X-ray diffraction (XRD) revealed slight changes in the interlayer spacing of many of the clay minerals. Based on the adsorption analysis of the Mars-analog clay minerals, phyllosilicate-bearing bedrock in Gale crater may contain up to 90-110 ppm B. A series of borate-enriched samples were created for analysis of LIBS spectra from ChemCam on the Curiosity rover and SuperCam on the Perseverance Rover. Finally, the results of this study may provide insight into martian groundwater geochemistry processes and the mobility of a key molecule connected with life.

58 GEOSCIENCES↗