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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Reversible parts-per-trillion-level detection of perfluorooctane sulfonic acid in tap water using field-effect transistor sensors

Widespread, persistent and toxic per- and polyfluoroalkyl substances (PFAS) pose a major threat to water systems and human health. Current detection methods are relatively expensive, slow and complex, underscoring the need for more accessible alternatives to meet increasingly stringent PFAS regulations. Here, in this study, we present an ultrasensitive sensing platform for perfluorooctane sulfonic acid detection in tap water with a reporting limit ( ~ 250 parts per quadrillion) lower than the US Environmental Protection Agency’s regulatory standard (4 parts per trillion), using a remote gate field-effect transistor featuring β-cyclodextrin (β-CD)-modified reduced graphene oxide as the sensing membrane. The sensor exhibits excellent selectivity against common inorganic ions, natural organic matter and select organic pollutants in tap water. The reversible and rapid response ( < 2 min) indicates the potential of remote gate field-effect transistor for continuous in-line monitoring. Mechanistic studies using quartz crystal microbalance and molecular dynamics simulations reveal key roles of analyte adsorption and charge properties in sensing performance and offer insights for designing more selective PFAS capture probes.

Wang, Yuqin [University of Chicago, IL (United Sta↗
DOE OSTI2022

Layer-by-Layer Nanoarchitectonics of Electrochemically Active Thin Films Comprised of Radical-Containing Polymers

Electroactive coatings based on non-conjugated redox-active polymers have increased in popularity with the development of thin film organic batteries. Here, control over coating deposition, redox-activity, and ion transport are key to improving their energy storage performance. In this work, the synthesis, solution state electrochemical characterization, and layer-by-layer (LbL) assembly of a nitroxide-based polycation and polyanion are presented. Solution state electrochemical characterization indicates that the rate of electron transfer for the nitroxide polyanion is much higher as compared to the nitroxide polycation. LbL thin films of the nitroxide polyanion and nitroxide polycation are assembled, demonstrating linear growth and tunable thickness (28 nm/layer pair). This work confirms that the ion transport mechanism of the LbL films during the redox reaction is influenced depending on the charge of the terminating layer, where the nitroxide polyanion can participate in self-doping, which leads to a contribution from cation transport. The nitroxide polyanion-terminated film also exhibits a higher capacity and a slightly reduced charge transfer resistance. However, it was also observed that a more pronounced capacity fade occurred for the polyanion-terminated film than the polycation-terminated film. Taken together, this highlights how oppositely charged radical-containing polyelectrolytes can form electroactive coatings for possible applications in energy storage or sensing.

25 ENERGY STORAGE↗
NASA NTRS2016

A Taxonomy-Based Approach to Shed Light on the Babel of Mathematical Models for Rice Simulation

For most biophysical domains, differences in model structures are seldom quantified. Here, we used a taxonomy-based approach to characterise thirteen rice models. Classification keys and binary attributes for each key were identified, and models were categorised into five clusters using a binary similarity measure and the unweighted pair-group method with arithmetic mean. Principal component analysis was performed on model outputs at four sites. Results indicated that (i) differences in structure often resulted in similar predictions and (ii) similar structures can lead to large differences in model outputs. User subjectivity during calibration may have hidden expected relationships between model structure and behaviour. This explanation, if confirmed, highlights the need for shared protocols to reduce the degrees of freedom during calibration, and to limit, in turn, the risk that user subjectivity influences model performance.

model parameterisation↗
DOE OSTI2022

Experimental and theoretical study of hole scattering in RF sputtered p-type Cu 2 O thin films

One of the key materials of interest for p-type oxide semiconductor thin film electronics is cuprous oxide (Cu 2 O), due to its relatively high hole mobility. Here, in this work, we use experiments, analytical models, and density functional theory calculations to study the scattering mechanisms that determine Hall mobility in two Cu 2 O samples. First, we examine a polycrystalline Cu 2 O thin film deposited by RF magnetron sputtering, and second, a single-crystalline Cu2O bulk substrate. Temperature-dependent Hall measurements indicate that neutral impurity and grain boundary scattering are dominant for the polycrystalline Cu 2 O thin film, while phonon scattering is dominant for single-crystalline Cu 2 O. Our first-principles calculations show that the room-temperature intrinsic hole mobility of Cu 2 O is 106 cm 2 V –1 s –1 , indicating the great promise of the material for p-type electronic devices. This intrinsic mobility is limited by phonon scattering, with the most dominant scattering modes having phonon energies of 88.4 and 17.1 meV. These results indicate that the key pathways to increase the hole mobility in Cu 2 O thin films are by reducing the impurity concentration and by increasing grain size. Our work thus sets the stage for the future development of high performance Cu 2 O-based p-type thin film transistors.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development of Prognostic Models Using Plant Asset Data

The recent growth of machine learning and artificial intelligence technologies provides opportunities for leveraging data-driven algorithms to address the problems of diagnostics and prognostics in the nuclear power industry. The use of machine learning and other statistical methods as prognostic models is of particular interest in the nuclear industry to accurately predict future equipment or plant state given a set of measurements. Such predictive capability will enable predictive assessment of component condition and remaining life and allow for condition-based predictive maintenance. The resulting optimization of maintenance scheduling and reduction in unnecessary maintenance activities will lower overall maintenance costs and improve the economics of nuclear power. This report discusses the various aspects of data processing and model development that are likely to influence the performance of prognostic models. Data from a boiling-water reactor was used to evaluate several prognostic models to identify key considerations for developing such models to predict data-driven plant state and equipment degradation condition. Preliminary results indicate the need for data sets that are relevant to the problem at hand and contain signatures that may be correlated to the prediction problem. Assuming such data exist, development of prognostic models using data-driven methods requires an understanding of the various sources of influence on the prediction accuracy (such as the model architecture, data preprocessing approaches, and potentially external factors influencing the equipment or plant system under assessment). Ongoing research is evaluating these factors in greater detail and examining techniques for calculating prediction uncertainty bounds.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1993

Formal verification of algorithms for critical systems

We describe our experience with formal, machine-checked verification of algorithms for critical applications, concentrating on a Byzantine fault-tolerant algorithm for synchronizing the clocks in the replicated computers of a digital flight control system. First, we explain the problems encountered in unsynchronized systems and the necessity, and criticality, of fault-tolerant synchronization. We give an overview of one such algorithm, and of the arguments for its correctness. Next, we describe a verification of the algorithm that we performed using our EHDM system for formal specification and verification. We indicate the errors we found in the published analysis of the algorithm, and other benefits that we derived from the verification. Based on our experience, we derive some key requirements for a formal specification and verification system adequate to the task of verifying algorithms of the type considered. Finally, we summarize our conclusions regarding the benefits of formal verification in this domain, and the capabilities required of verification systems in order to realize those benefits.

Rushby, John M.↗
NASA NTRS2025

Innovative Drug Selection, Storage, and Shelf-Life Strategies for Exploration Spaceflight

Medications have been a part of space travel dating back to the Apollo missions. A safe and effective medication formulary is essential to maintaining crew health and performance during long-duration spaceflight outside of low Earth orbit (LEO). Distance from Earth creates four key operational changes that increase medical risks, including communication, resupply, crewmember health, and evacuation. The current spaceflight pharmaceutical formulary consists of medications indicated to treat a variety of anticipated medical events and healthcare needs during spaceflight, but depends on a robust consumables resupply chain, which may be strained for a Lunar, and possibly non-existent for a Mars mission. The specific medications selections for the formulary may change to optimally align with the mission, crew compliment, and spacecraft design. Medical support at long-duration exploration missions will differ from LEO missions due to mission duration, lack of consumables resupply, prolonged exposure to space radiation, and the absence of emergency medical return capability. Loss of medication resupply limits or removes the ability to replace medications that have been exhausted or degraded, potentially exacerbating the medical risk posture. To address these anticipated risks, long-duration missions must consider use of novel medical technologies, treatment modalities, and smart medical systems that offer greater crew autonomy, such as physiologically based pharmacokinetic modeling, drug repurposing, on demand drug synthesis, or wearable drug delivery / monitoring devices. Once an ideal formulary for exploration space is determined, it is essential to establish the chemical and physical stability of each medication compound, as well as its safety by identifying its degradation profiles and products. Although few studies have been conducted to provide evidence on the physicochemical stability of pharmaceuticals during space missions, the data suggests that the spaceflight environment may promote degradation in some pharmaceuticals. Formulary drug purity and efficacy should be verified by pharmaceutical stability assessments, and can be realized non-destructively, and accessed in remote environments. Non-destructive pharmaceutical analysis and statistical modelling techniques could optimize exploration spaceflight medical care by enabling early detection of suboptimal therapeutics. Likewise, novel packaging, storage strategies, and dosage form innovations are promising countermeasures to optimize pharmaceutical shelf life, purity, and quality of exploration spaceflight medications. As we prepare for more distant exploration missions, risk management planning for astronaut healthcare should include the assembly of a medication formulary that is comprehensive enough to prevent or treat anticipated medical events, remains safe and chemically stable, and retains sufficient potency to last for the duration of the mission. Following extensive review of the literature, we will present innovative formulary optimization strategies, pharmaceutical stability assessment techniques, and storage and packaging solutions that could enhance drug safety and efficacy for future exploration spaceflight missions.

Vernie R Daniels↗
DOE OSTI2022

Evaluating HPC Kernels for Processing in Memory

Memory subsystems contribute significantly to the performance and energy efficiency of high-performance computing (HPC) applications. Traditional memory technologies with conventional organization (e.g., DRAM) are struggling to keep up with the increasing memory requirements of modern applications. Techniques such as multilayer cache hierarchy and out-of-order execution are still falling short of mitigating the penalty incurred by memory accesses. Processing-in-memory (PIM), which involves moving memory-intensive kernels to memory for execution instead of bringing the data to the processing unit, is emerging as a promising technique. PIM has recently received traction among computer architecture researchers, and the increasing research activity surrounding this technique indicates its potential to alleviate main memory performance bottlenecks. In this paper, we characterize and identify memory-intensive HPC kernels, perform a first-order evaluation of the PIM technique for selected HPC kernels, quantify performance deviation, and analyze the key factors that affect PIM efficiency.

Asifuzzaman, Kazi↗
NASA NTRS1999

Constraining the Global, Cloud-Free Reflected Solar Radiation Flux (RSRF) with Earth Observing System (EOS) Instruments

Variations in the top-of-atmosphere reflected solar radiation flux, and in the factors that determine its value, are among the most important diagnostic indicators of changes in Earth's energy balance. Data from the MISR (Multi-angle Imaging SpectroRadiometer), MODIS (Moderate-resolution Imaging Spectroradiometer), SAGE-3 (Stratospheric Aerosol and Gas Experiment), and CERES (Clouds and Earth's Radiant Energy System), all of which are spacecraft instruments scheduled for launch in 1999, will each constrain pieces of the RSRF budget. Prior to launch, we are performing studies to determine the sensitivity of these instruments to key factors that influence the cloud-free RSRF: aerosol optical depth, aerosol scattering properties, and surface visible bidirectional reflectance distribution function (BRDF). We are also assessing the ability of the aggregate of instruments to constrain the overall RSRF budget under natural conditions over the globe. Consider the MISR retrieval of aerosols: according to simulations over cloud-free, calm ocean, for pure particles with natural ranges of optical depth, particle size, and indices of refraction, MISR can retrieve column aerosol optical depth for all but the darkest particles, to an uncertainty of at most 0.05 or 20%, whichever is larger, even if the particle properties are poorly known. For one common particle type, soot, constraints on the optical depth over dark ocean are very poor. The simulated measurements also allow us to distinguish spherical from non-spherical particles, to separate two to four compositional groups based on indices of refraction, and to identify three to four distinct size groups between 0. 1 and 2.0 microns characteristic radius at most latitudes. Based on these results, we expect to distinguish air masses containing different aerosol types, routinely and globally, with multiangle remote sensing data. Such results far exceed current satellite aerosol retrieval capabilities, which provide only total optical depth for assumed particle properties; the new information will complement in situ data, which give details about aerosol size and composition locally. In addition, our team is using climatologies that reflect the constraints each instrument is expected to provide, along with ERBE (Earth Radiation Budget Experiment) data and a radiative transfer code, to study overall sensitivity to RSRF, helping us prepare for similar studies with new data from the EOS-era instruments.

Kahn, Ralph↗
DOE OSTI2020

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2019 State of Technology and Future Research

NREL’s algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL’s “combined algae processing” (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL R&D projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model and reports on key process sustainability indicators for the biomass production stage including annual biomass yields, facility power demand, and water consumption.

09 BIOMASS FUELS↗
NASA NTRS1993

Imaging spectrometry of the Earth and other solar system bodies

Imaging spectrometry is a relatively new tool for remote sensing of the Earth and other bodies of the solar system. The technique dates back to the late 1970's and early 1980's. It is a natural extension of the earlier multi-spectral imagers developed for remote sensing that acquire images in a few, usually broad spectral bands. Imaging spectrometers combine aspects of classical spectrometers and imaging systems, making it possible to acquire literally hundreds of images of an object, each image in a separate, narrow spectral band. It is thus possible to perform spectroscopy on a pixel-by-pixel basis with the data acquired with an imaging spectrometer. Two imaging spectrometers have flown in space and several others are planned for future Earth and planetary missions. The French-built Phobos Infrared Spectrometer (ISM) was part of the payload of the Soviet Mars mission in 1988, and the JPL-built Near Infrared Mapping Spectrometer (NIMS) is currently en route to Jupiter aboard the Galileo spacecraft. Several airborne imaging spectrometers have been built in the past decade including the JPL-built Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) which is the only such sensor that covers the full solar reflected portion of the spectrum in narrow, contiguous spectral bands. NASA plans two imaging spectrometers for its Earth Observing System, the Moderate and the High Resolution Imaging Spectrometers (MODIS and HIRIS). A brief overview of the applications of imaging spectrometry to Earth science will be presented to illustrate the value of the tool to remote sensing and indicate the types of measurements that are required. The system design for AVIRS and a planetary imaging spectrometer will be presented to illustrate the engineering considerations and challenges that must be met in building such instruments. Several key sensor technology areas will be discussed in which miniaturization and/or enhanced performance through micromachining and nanofabrication may allow smaller, more robust, and more capable imaging spectrometers to be built in the future.

Vane, Gregg↗
NASA NTRS1991

Lessons learned for composite structures

Lessons learned for composite structures are presented in three technology areas: materials, manufacturing, and design. In addition, future challenges for composite structures are presented. Composite materials have long gestation periods from the developmental stage to fully matured production status. Many examples exist of unsuccessful attempts to accelerate this gestation period. Experience has shown that technology transition of a new material system to fully matured production status is time consuming, involves risk, is expensive and should not be undertaken lightly. The future challenges for composite materials require an intensification of the science based approach to material development, extension of the vendor/customer interaction process to include all engineering disciplines of the end user, reduced material costs because they are a significant factor in overall part cost, and improved batch-to-batch pre-preg physical property control. Historical manufacturing lessons learned are presented using current in-service production structure as examples. Most producibility problems for these structures can be traced to their sequential engineering design. This caused an excessive emphasis on design-to-weight and schedule at the expense of design-to-cost. This resulted in expensive performance originated designs, which required costly tooling and led to non-producible parts. Historically these problems have been allowed to persist throughout the production run. The current/future approach for the production of affordable composite structures mandates concurrent engineering design where equal emphasis is placed on product and process design. Design for simplified assembly is also emphasized, since assembly costs account for a major portion of total airframe costs. The future challenge for composite manufacturing is, therefore, to utilize concurrent engineering in conjunction with automated manufacturing techniques to build affordable composite structures. Composite design experience has shown that significant weight savings have been achieved, outstanding fatigue and corrosion resistance have been demonstrated, and in-service performance has been very successful. Currently no structural design show stoppers exist for composite structures. A major lesson learned is that the full scale static test is the key test for composites, since it is the primary structural 'hot spot' indicator. The major durability issue is supportability of thin skinned structure. Impact damage has been identified as the most significant issue for the damage tolerance control of composite structures. However, delaminations induced during assembly operations have demonstrated a significant nuisance value. The future challenges for composite structures are threefold. Firstly, composite airframe weight fraction should increase to 60 percent. At the same time, the cost of composite structures must be reduced by 50 percent to attain the goal of affordability. To support these challenges it is essential to develop lower cost materials and processes.

Whitehead, R. S.↗
NASA NTRS2011

Shuttle Risk Progression: Use of the Shuttle Probabilistic Risk Assessment (PRA) to Show Reliability Growth

It is important to the Space Shuttle Program (SSP), as well as future manned spaceflight programs, to understand the early mission risk and progression of risk as the program gains insights into the integrated vehicle through flight. The risk progression is important to the SSP as part of the documentation of lessons learned. The risk progression is important to future programs to understand reliability growth and the first flight risk. This analysis uses the knowledge gained from 30 years of operational flights and the current Shuttle PRA to calculate the risk of Loss of Crew and Vehicle (LOCV) at significant milestones beginning with the first flight. Key flights were evaluated based upon historical events and significant re-designs. The results indicated that the Shuttle risk tends to follow a step function as opposed to following a traditional reliability growth pattern where risk exponentially improves with each flight. In addition, it shows that risk can increase due to trading safety margin for increased performance or due to external events. Due to the risk drivers not being addressed, the risk did not improve appreciably during the first 25 flights. It was only after significant events occurred such as Challenger and Columbia, where the risk drivers were apparent, that risk was significantly improved. In addition, this paper will show that the SSP has reduced the risk of LOCV by almost an order of magnitude. It is easy to look back afte r 30 years and point to risks that are now obvious, however; the key is to use this knowledge to benefit other programs which are in their infancy stages. One lesson learned from the SSP is understanding risk drivers are essential in order to considerably reduce risk. This will enable the new program to focus time and resources on identifying and reducing the significant risks. A comprehensive PRA, similar to that of the Shuttle PRA, is an effective tool quantifying risk drivers if support from all of the stakeholders is given.

Hamlin, Teri L.↗
DOE OSTI2021

Investigation of the Selectivity of Carrier Transport Layers in Wide-Bandgap Perovskite Solar Cells

Excellent contact passivation and selectivity are prerequisites to realize the full potential of high-material-quality perovskite solar cells, first to maximize the internal voltage (or quasi-Fermi-level separation) iV within the absorber, then to translate this high internal voltage into a high external voltage V. Experimental quantification of contact passivation and selectivity is, thus, key to improving device performance. Here, open-circuit measurements of iV oc and V oc , combined with surface photovoltage measurements, are used to systematically quantify the passivation—using iVoc as a metric—and the selectivity—defined as Soc=V oc /iV oc —of a range of common carrier transport layers to wide-bandgap (1.67 eV) perovskite absorbers. The resulting solar cells suffer from large voltage deficits, particularly when NiO x is used as the hole transport layer, even though it provides better passivation than its polymer-based counterparts (PTAA and PTAA/PFN). This indicates a poor selectivity of NiO x (Soc<0.81 for NiO x -based devices), whereas devices using polymer-based hole transport layers exhibit high selectivity (S oc =0.94–0.95). In agreement with recent reports, this low selectivity is attributed to the formation of an interlayer of non-perovskite material with high resistance to holes at the perovskite/NiO x interface. These measurements also imply that the selectivity of the C60-based electron transport layers is relatively good.

carrier transport layers↗
DOE OSTI2022

Patient-Specific Mathematical Model of the Clear Cell Renal Cell Carcinoma Microenvironment

The interactions between cells and molecules in the tumor microenvironment can give insight into the initiation and progression of tumors and their optimal treatment options. In this paper, we developed an ordinary differential equation (ODE) mathematical model of the interaction network of key players in the clear cell renal cell carcinoma (ccRCC) microenvironment. We then performed a global gradient-based sensitivity analysis to investigate the effects of the most sensitive parameters of the model on the number of cancer cells. The results indicate that parameters related to IL-6 have high a impact on cancer cell growth, such that decreasing the level of IL-6 can remarkably slow the tumor’s growth.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1988

Numerical simulation of the vortical flow over a round-edged double-delta wing

Simulations of three-dimensional vortical flows over a thin double-delta wing with an aspect ratio of 2.05 have been performed. Steady-state solutions to the unsteady incompressible Navier-Stokes equations are obtained using a new implicit upwind-relaxation finite-difference scheme. The method is second-order accurate spatially and naturally dissipative. Numerical results indicate that key features of both vortical interaction and vortex breakdown are successfully simulated. The computed lift coefficients and lateral trajectories of the vortical cores are in good agreement with the experimental data.

Hsu, C.-H.↗
NASA NTRS1991

Advanced CRM training for instructors and evaluators

It is seen that if the maximum operational benefit of crew resource management (CRM) is to be achieved, the evaluator group is the principal key and specialized training that is ongoing is necessary for this group. The training must be customized to fit the needs of a particular organization, and the training must address key topical issues that influence organizational dynamics. Attention is given to the use of video and full length scripted NASA research LOFTS, behavioral markers and debriefing skills, the importance of policy and written CRM standards, and line oriented simulations debriefing performance indicators.

Taggart, William R.↗
DOE OSTI2025

A Simple Data-Centric Methodology for Producible Geothermal Well Determinations: Preprint

The Bureau of Land Management (BLM) has traditionally lacked a standardized methodology for determining if a newly drilled geothermal well is "producible," a designation essential for deciding whether a lease should be "held by production." This is a straightforward problem to solve in oil and gas: Demonstrate that a well is economically viable, meaning it produces sufficient oil or gas to exceed direct operating costs and lease-related expenses, such as rentals or minimum royalties. In geothermal, the problem is more complex: Geothermal wells are tightly coupled with the downstream infrastructure - specifically, the power plant, which is often not designed until well after a lease is deemed as "held by production." Although this designation is critical for advancing geothermal power plant development on BLM-managed lands, current geothermal well assessments often rely on ad hoc approaches that can be complex, operator-biased, and heavy in assumptions related to economic viability. To address this, we have developed two complementary methodologies: a minimum power requirement-based approach and a productivity index (PI)-based approach. These methods leverage key flow test data - pressure, temperature, flow rate, and specific enthalpy - to provide reliable and standardized producible well determinations. The minimum power requirement-based approach evaluates wells against specific power output thresholds informed by reservoir experts and the associated temperature requirements. The PI-based approach assesses well productivity using widely accepted reservoir engineering metrics, proposing a threshold of 2.5 kg/s/bar. Both methods are data-driven and grounded in empirical production data from operational geothermal wells, avoiding uncertain economic assumptions while maintaining decision-making accuracy. Wells falling below key performance thresholds (i.e., PI, specific power) are deemed non-producible. These methodologies aim to streamline BLM's decision-making process, reduce nontechnical barriers to geothermal energy adoption, and enable regulatory expansion into states lacking geothermal expertise. Preliminary results indicate clear trends and thresholds in production data that provide actionable insights for evaluating well producibility. Validation using well completion report (WCR) data is ongoing, with promising results demonstrating the potential for these standardized methodologies to impact geothermal development significantly.

15 GEOTHERMAL ENERGY↗