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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Shaping the Future of Self-Driving Autonomous Laboratories Workshop

The "Shaping the Future of Self-Driving Autonomous Laboratories" workshop, held in Denver on November 7-8, 2024, brought together leading experts from materials science and computing to address the growing need to revolutionize scientific research through AI-driven autonomous laboratories. The workshop identified critical challenges, including the integration of heterogeneous data, development of AI systems that understand fundamental physical principles, and comprehensive safety protocols. Key recommendations emerged around developing universal laboratory equipment interfaces, implementing automated metadata collection systems, and creating hybrid AI approaches that combine data-driven learning with scientific principles. The workshop emphasized maintaining human oversight while leveraging automation, transforming scientific education to prepare the next generation of researchers, and establishing a national consortium leveraging DOE facilities as anchors for broader collaboration with academia and industry. Participants stressed the urgency of addressing the growing disconnect between human decision-making timescales and modern instrumentation capabilities, highlighting the need for strategic automation while preserving essential human insight and oversight in the research process.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Two-micron Detector Development using Sb-based Material Systems

NASA Langley Research Center (LaRC), in partnership with the University of Delaware (UD), developed AlGaAsSb/InGaAsSb custom-designed phototransistors in the 0.6-2.5 micron wavelength range for applications to laser remote sensing. The phototransistor s performance greatly exceeds the previously reported results at this wavelength range in the literature. The performances of the custom-designed phototransistor, such as responsivity, detectivity, and gain, are improved significantly as compared to the previously published detectors as well as commercial detectors. Detection in the 0.6- to 2.5- micron broadband with a single phototransistor will result in reduction or elimination of heavy and complex optical components now required for multiple wavelength detection in atmospheric remote sensors resulting in smaller, lighter, simpler instruments with higher performance. This high performance broadband phototransistor will eliminate the need for high power laser for active remote sensing and also the Si (1.0- micron cutoff) and InGaAs (extended 2.3- micron cutoff) detectors. The developed broadband phototransistor will be applicable for the next generation of space-based Earth observations and other planetary instruments for active and passive remote sensing with substantial reduction in size, complexity, and weight to measure water vapor, methane, and carbon dioxide in planetary atmospheres as well as aerosol, cloud, water vapor, O2, CO, and CO2 for a broad range of applications to Earth and Space Science Missions under Science Mission Directorate (SMD) research programs.

Abedin, M. N.↗
NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗
NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗
NASA NTRS2021

Modernizing Mechatronics Course With Quantum Engineering

Mechatronics is the synergistic application of mechanics, electronics, control engineering, and computer science in the development of electromechanical products and systems, through integrated design. This paper proposes to extend the mechatronics course beyond traditional engineering topics, and to modernize the mechatronics instructions with complementary quantum engineering topics. With the recent rapid advances in quantum technologies such as quantum communications, sensing, computers, and algorithms, it is imperative to train the next generation of engineers and prepare them for their future careers in the ever-changing industry in such areas. Furthermore, due to such progress and advances in the fields associated with quantum mechanics, the integration of quantum technologies with classical mechanical systems will be inevitable both in terms of educational and technological standpoints in future. To address the educational needs of the future engineers in such areas of significant importance, quantum entanglement and quantum cryptography experiments, as two fundamental topics in quantum mechanics, are brought into the mechatronics course in an initiative that is reported in this paper. The integrated quantum and mechatronics topics also provides opportunities for open discussions on exploring the interface of quantum technologies and classical engineering systems, which can potentially push the engineering boundaries beyond classical possibilities by accessing the quantum advantages. An innovative online remote demonstration of such quantum experiments are developed and presented to the students. This course has been offered to undergraduate students once with successful results. The students were able to remotely access the experiments, perform the experiments and collect data. The successful result of such quantum experiments is also reflected in a course survey, presented in this paper, even though the quantum mechanics topics offered in this course are unfamiliar to engineering students and hence more challenging. The paper reports, and aims to promote, the integration of selected quantum technology topics with the mechatronics course for training engineering students in this rapidly growing area.

Ghazinejad, Maziar↗
NASA NTRS2022

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

Kanefsky, Bob↗
NASA NTRSDate not supplied

The State of NOS3

The NASA Operational Simulator for Small Satellites (NOS3) showcases some of the Jon McBride Software Testing and Research (JSTAR) laboratories technologies on an open-source platform. NOS3 is a software digital twin providing a virtualized platform inside which you have your traditional flight software, ground software, environmental simulators, and middleware to keep all pieces in sync. NOS3 leverages the core Flight System (cFS), OpenC3 COSMOS, and NASA GSFC’s 42 software as the baseline to which additional research technologies can be developed. Current technologies to be demonstrated include NOS3 Igniter, constellation support, NASA JPL’s SYNOPSIS integration, and NASA GSFC’s OnAir. NOS3 Igniter is a GUI in which you can configure, build, and run your simulation. This along with improvements to the documentation and training available open source aims to reduce the ramp up time with new users and improve accessibility. As constellations introduce another level of complexity, it is important to ensure the baseline design reference mission covers all the basics required and allows users to experiment, understand, and test at all levels of the system. The Science Yield improvement via Onboard Prioritization and Summary of Information Systems (SYNOPSIS) is an open-source tool developed by NASA JPL to enable data prioritization and planning. GSFC’s Onboard Artificial Intelligence Research (OnAIR) enables custom algorithm development written in python to interface with the flight software allowing scientists to develop what they need for the next generation of missions and easily interface back to the traditional flight software. During the presentation, a review and demonstration of the above technologies is planned along with a roadmap.

NOS3↗
NASA NTRSDate not supplied

Summary of Apollo Next Generation Sample Analysis (ANGSA) and Insights for Artemis Preliminary Examination Activities

Analyses of Apollo samples have provided fundamental insights into the origin and history of the Earth-Moon system and the solar system broadly. With great foresight, a subset of samples from Apollo were left unprocessed so that they could be studied by future generations with their modern technology. To prepare for the return of samples from the Moon by the Artemis Program, NASA initiated the Apollo Next Generation Sample Analysis Program (ANGSA) to analyze a subset of the previously unprocessed Apollo samples. The ANGSA consortium consisted of 9 original teams funded by NASA that combined into a single science team referred to as the ANGSA Science Team. ANGSA was designed to function like the sample analysis phase of a sample return mission with a goal to investigate the lower portion of a double drive tube previously sealed on the lunar surface (73001), the upper portion of that drive tube that had remained unopened (73002), and a variety of Apollo 17 samples that had remained stored at -20 ºC for approximately 50 years.

Francis M. McCubbin↗
DOE OSTI2024

Area-selective deposition of germanium on patterned graphene/monolayer molybdenum disulfide stacks via dipole engineering

Heterogeneous integration of two-dimensional materials and the conventional semiconductor has opened opportunities for next-generation semiconductor devices and their processing. Heterogeneous integration has been studied for economical manufacturing by substrate recycling and novel functionalities by a combination of incommensurate materials. However, utilizing the integration requires controlling locations of the integrated architectures. Here, we show area-selective deposition (ASD) of germanium on the graphene/MoS 2 stack. Ge nucleation precisely occurred on the surfaces of the patterned graphene/MoS 2 stack via dipole engineering. In this study, the growth temperature of ASD of Ge was significantly lower than that based on precursor desorption on SiO 2 . The first-principles calculations revealed that Ge deposited by ASD on the graphene/MoS 2 stack was not affected by charge transfer. This work provides a viable way to utilize atomically thin materials for next-generation semiconductor devices, which can be applicable for “Beyond Moore” and “More Moore” approaches.

2D materials↗
DOE OSTI2025

Acceleration of Thermochemistry Solves in MOOSE and Pronghorn

This work focuses on the development and implementation of strategies to accelerate thermochemical calculations within MOOSE-based multiphysics simulations, particularly for applications in MSRs. We highlight the inherent complexity of nuclear materials, which require a multiscale approach to accurately model their behavior across various physical domains, including mechanical, chemical, and thermal phenomena. Thermochemical equilibrium calculations are crucial for predicting material properties and enhancing the fidelity of these simulations. The integration of Thermochimica, a Gibbs energy minimizer, into MOOSE allows for the direct minimization of Gibbs energy at every point on the mesh. However, the computational cost of such integration is significant. To address this, we explored acceleration strategies such as multi-threading support and the use of a thermodynamic ValueCache to reduce redundant calculations. Additionally, we investigated modifications to Thermochimica to enable phase constraints and improve its coupling with phase-field models, which are essential for simulating microstructural evolution and corrosion in MSR. These efforts aim to optimize the computational efficiency and accuracy of multiphysics simulations, thereby supporting the development of reliable and efficient nuclear materials for next-generation reactor technologies.

36 - MATERIALS SCIENCE↗
NASA NTRS2009

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

Peters-Lidard, Christa D.↗
DOE OSTI2024

Silica–Derived Nanostructured Electrode Materials for ORR, OER, HER, CO 2 RR Electrocatalysis, and Energy Storage Applications: A Review**

Silica-derived nanostructured catalysts (SDNCs) are a class of materials synthesized using nanocasting and templating techniques, which involve the sacrificial removal of a silica template to generate highly porous nanostructured materials. The surface of these nanostructures is functionalized with a variety of electrocatalytically active metal and non-metal atoms. SDNCs have attracted considerable attention due to their unique physicochemical properties, tunable electronic configuration, and microstructure. These properties make them highly efficient catalysts and promising electrode materials for next generation electrocatalysis, energy conversion, and energy storage technologies. The continued development of SDNCs is likely to lead to new and improved electrocatalysts and electrode materials. This review article provides a comprehensive overview of the recent advances in the development of SDNCs for electrocatalysis and energy storage applications. It analyzes 337,061 research articles published in the Web of Science (WoS) database up to December 2022 using the keywords “silica”, “electrocatalysts”, “ORR”, “OER”, “HER”, “HOR”, “CO 2 RR”, “batteries”, and “supercapacitors”. The review discusses the application of SDNCs for oxygen reduction reaction (ORR), oxygen evolution reaction (OER), hydrogen evolution reaction (HER), carbon dioxide reduction reaction (CO 2 RR), supercapacitors, lithium-ion batteries, and thermal energy storage applications. It concludes by discussing the advantages and limitations of SDNCs for energy applications.

25 ENERGY STORAGE↗
NASA NTRS2004

Using Science Driven Technologies for the Defense and Security Applications

For the past three decades, Earth science remote sensing technologies have been providing enormous amounts of useful data and information in broadening our understanding of our home planet as a system. This research, as it has expanded our learning process, has also generated additional questions. This has further resulted in establishing new science requirements, which have culminated in defining and pushing the state-of-the-art technology needs. NASA s Earth science program has deployed 18 highly complex satellites, with a total of 80 sensors, so far and is in a process of defining and launching multiple observing systems in the next decade. Due to the heightened security alert of the nation, researchers and technologists are paying serious attention to the use of these science driven technologies for dual use. In other words, how such sophisticated observing and measuring systems can be used in detecting multiple types of security concerns with a substantial lead time so that the appropriate law enforcement agencies can take adequate steps to defuse any potential risky scenarios. This paper examines numerous NASA technologies such as laser/lidar systems, microwave and millimeter wave technologies, optical observing systems, high performance computational techniques for rapid analyses, and imaging products that can have a tremendous pay off for security applications.

Habib, Shahid↗
NASA NTRS1992

Edison - The next generation infrared space observatory

Edison, a large-aperture, radiatively-cooled telescope, is proposed as the major international mission to follow the current generation of cryogenically-cooled infrared space telescopes. It is being studied at present as a 2.5-3.5 m mixed radiatively- and mechanically-cooled facility optimized to investigate the wavelength range 3-100+ microns. This paper outlines the status of the project, discusses some aspects of a smaller-aperture 'precursor' mission, and describes a portion of the baseline science mission.

Thronson, H. A., Jr.↗
NASA NTRS2016

Architecture and CONOPS of Next-Generation Ground Network for Communications and Tracking of Interplanetary SmallSats

As small spacecraft venture out of Earth orbit, they will encounter challenges not experienced or addressed by the numerous low Earth orbit (LEO) CubeSat and Smallsat missions staged to date. The LEO CubeSats typically use low-cost, proven CubeSat radios, antennas, and university ground stations with small apertures. As more ambitious yet cost-constrained space mission concepts to the Moon and beyond are being developed, CubeSats and smallsats have the potential to provide a more affordable platform for exploring deep space and performing the associated science. Some of the challenges that have, so far, slowed the proliferation of small interplanetary spacecraft are those of communications and navigation.

Cheung, Kar-ming↗
NASA NTRS2006

AIRS Science Accomplishments Version 4.0/Plans for Version 5

This talk is about accomplishments with AIRS data and what we have learned from almost three years of data what part of this is emerging in Version 4.0 what part we would like to see filtering into Version 5.0 and what part constitute limitations in the AIRS requirements, such as spectral and spatial resolution, which have to be deferred to the wish list for the next generation hyperspectral sounder. The AIRS calibration accuracy at the 1OOmK and stability at the 6 mK/year level are amazing. It establishes the unique capability of a cooled grating array spectrometer in Earth orbit for climate research. Data which are sufficiently clear to match the radiometric accuracy of the instrument, have a yield of less than 1%. This is OK for calibration. The 2616/cm window channel combined with the RTG.SST for tropical ocean allow excellent assessment radiometric calibration accuracy and stability. For absolute calibration verification 100mK is the limit due to cloud contamination. The 10 micron window channels can be used for stability assessment, but accuracy is limited at 300mK due to water continuum absorption uncertainties.

lessons learned↗
DOE OSTI2026

Roadmap for transforming heterogeneous catalysis with artificial intelligence

Artificial intelligence (AI) is poised to transform heterogeneous catalysis, opening avenues for catalytic materials discovery. By uncovering intricate patterns in high-dimensional data, AI has been reshaping our pursuit of sustainable catalytic processes across the energy, environmental and chemical sectors. This promise, however, hinges on overcoming fundamental barriers, including limitations in data availability and quality, challenges in the generalizability and interpretability of data-augmented decisions, and the persistent gap between in silico predictions and experiments. Furthermore, we outline a forward-looking roadmap for deeply integrating AI into heterogeneous catalysis with an AI-ready data ecosystem, multimodal foundation models, and ultimately autonomous laboratories to accelerate the development of next-generation catalytic technologies via AI-empowered human–machine collaboration.

Computational methods↗
DOE OSTI2025

Characterization of Lateral Amorphous Selenium Photodetectors for Low-Photon and VUV Detection at Cryogenic Temperatures

The performance of amorphous selenium (a-Se) as a cryogenic photodetector material is evaluated through a series of experiments using laterally structured devices operated in a custom optical test stand. These studies investigate the response of a-Se detectors to low-photon fluxes at high electric fields near avalanche conditions, the linearity of the photoconductive response over a wide dynamic range and the direct detection of narrowband 130 nm vacuum ultraviolet (VUV) illumination. At 87 K, matched-filter analysis shows reliable single-shot detection with efficiencies greater than or equal to 80 percent and area under the curve (AUC) greater than or equal to 0.85 using as few as approximately 6800 incident 401 nm photons, corresponding to approximately 3400 photons within field-active regions after accounting for geometric constraints. Measurements are performed at cryogenic temperatures using calibrated photon fluxes derived from a silicon photomultiplier reference and a characterized optical filter stack. Additional experiments using a tellurium-doped a-Se (a-SeTe) device explore the material's behavior under identical test conditions and demonstrate that avalanche is achievable in a-SeTe at cryogenic temperatures. The results demonstrate reproducible low-noise operation, VUV sensitivity and field-dependent gain behavior in a lateral a-Se architecture, representing the first reported observation of avalanche multiplication in laterally structured a-Se and a-SeTe devices at cryogenic temperatures. These findings support the potential integration of laterally structured a-Se devices into next-generation pixelated liquid-argon time projection chambers (TPCs) requiring scalable, high-field-compatible photon detection systems.

FOS: Physical sciences↗