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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Artificial Intelligence-Enhanced, Multi-Level, Modular System Design

As Moore’s Law and Dennard Scaling come to an end, it is becoming increasingly important to develop non-von Neumann computing architectures that can perform low-power computing in the domains of scientific computing, artificial intelligence, embedded systems, and edge computing. Next-generation computing technologies, such as neuromorphic computing and quantum computing, have the potential to revolutionize computing. However, in order to make progress in these fields, it is necessary to fundamentally change the current computing paradigm by codesigning systems across all system level, from materials to software. Because skilled labor is limited in the field of next-generation computing, we are developing artificial intelligence-enhanced tools to automate the codesign and co-discovery of next-generation computers. Here, we develop a method called Modular and Multi-level MAchine Learning (MAMMAL) which is able to perform analog codesign and co-discovery across multiple system levels, spanning devices to circuits. We prototype MAMMAL by using it to design simple passive analog low-pass filters. We also explore methods to incorporate uncertainty quantification into MAMMAL and to accelerate MAMMAL by using emerging technologies, such as crossbar arrays. Ultimately, we believe that MAMMAL will enable rapid progress in developing next-generation computers by automating the codesign and co-discovery of electronic systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Artificial Intelligence for Data Center Operations (AIOps): Cooperative Research and Development (Final Report)

High performance computing data centers will increasingly need to rely on automation to keep pace with exascale growth in compute capability and to manage and optimize the data center environment and facility resources. Artificial intelligence and machine learning approaches provide the means to improve HPC data center operational efficiency, by learning historical trends and training models to operate on real-time data collected from both IT and facilities sources. NREL has developed methods of real-time collection, aggregation and streaming of these data in the ESIF HPC Data Center and has collected a significant dataset of relevant metrics across computer systems, racks, environmental, building and utility sources for research into various predictive analytics problems. HPE's Advanced Technology Group (ATG) is doing comprehensive research into exascale monitoring and management for High Performance Computing (HPC) systems (hereinafter HPE's Data Monitoring/ Management Technology). NREL and HPE will collaborate to add Artificial Intelligence (AI) to NREL's real-time data collection/ aggregation/ streaming system and HPE's Data Monitoring/ Management System, with the goal of improving the operational efficiency of NREL's Energy Systems Integration Facility (ESIF) HPC Data Center through data analytics on both historical and real-time data from IT systems and facilities operations. This collaboration will consist of efforts in Data Management, Data Analytics, and AI/ML Optimization for both manual and autonomous intervention in data center operations. This will be a multi-year, multi-staged effort with a goal towards building capabilities for an Advanced Smart Facility, and demonstration of these techniques in the NREL ESIF HPC Data Center.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Abbr. Final report: Self-assembled molecular containers as artificial water channels: towards biomimetic desalination membranes

Global water scarcity demands advances in desalination technologies that can deliver more fresh water with less energy. Current reverse osmosis membranes are fundamentally limited by a trade-off between how much water they can pass and how well they block salts. To address this challenge, we developed a bottom-up strategy to design and test artificial water channels that mimic the efficiency of biological proteins but are built from robust synthetic molecules. Over two years, we synthesized and evaluated more than twenty molecular channel candidates, including supramolecular macrocycles and nanographene pores with atomically precise structures. We showed that small chemical modifications allow direct control over pore size and chemistry, which in turn govern water permeability and salt rejection. In collaboration with university partners, we reported the first experimental demonstration of water transport through a nanographene pore, bridging a long-standing gap between simulation and experiment. Several of the artificial channels we developed achieved water–salt selectivity beyond conventional polymer membranes, highlighting their potential for next-generation desalination and precision separations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Searching for Phase Transitions in Artificial Kagome Spin Ice

Artificial Kagome spin ice is a metasurface consisting of small islands of polarizable magnets. These islands can be oriented by an external magnetic field applied in the same plane as the metasurface. By subsequently applying a relatively weaker field in the opposite direction of the initial field, a portion of the magnets in the lattice can be repolarized or “flipped” the other way. These flips cause instabilities in a previously uniformly aligned lattice, causing the system to interact with itself and induce changes in the overall magnetization of the metasurface. This Summer, my goal was to use this phenomenon to discern whether or not these systems could undergo a phase transition caused only by the initial change of the external magnetic field. Based on previous datasets that indicated that such a transition was observable, my task was to find and reproduce this potential phenomena. This process was conducted by repeating measurements on the system by using an external magnet to align the spin ice and then using Magnetic Force Microscopy (MFM) to probe the surface of the material to understand the changes in the magnetization over time. This report will discuss the characteristics of artificial Kagome spin ice, the methodology used to induce phase transitions, and the image processing methods used to understand the results. Although no reproducible evidence of a phase transition was found during the Summer, we were able to successfully reproduce short-term responses in the spin ice, as well as plot a hysteresis curve of the material.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Leveraging Artificial Intelligence to Predict Novel Eutectic Alloys

The goal of this project was to train an artificial neural network (ANN) to predict the fractional composition and melting point of eutectic alloys using fundamental atomic properties as inputs. The fundamental properties considered include atomic number, atomic weight, atomic radius, valence electron concentration, electronegativity, and electron affinity. The project involved several phases, starting with data preparation, where phase diagram data was harvested from the ASM International database. Approximately 1300 binary eutectics were collected and cleaned to ensure relevance and accuracy. A regression model was selected for training, utilizing a rectified linear unit as the activation function. Various model configurations were evaluated for predictive accuracy, with validation techniques employed to ensure robustness. The model demonstrated predictive capabilities above random guessing and was able to achieve up to 11% accuracy under certain conditions. An ablative test identified atomic radius and valence electron concentration as critical inputs for model performance. Incorporating the melting point of atomic constituents improved accuracy significantly, although ultimately the model’s predictive capability still fell short of the 80% target. This report details the methodology, results, and implications of the research, contributing to the understanding of employing artificial intelligence to predict the phase transition behavior of eutectic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Commercial integration of advanced nuclear energy with Artificial Intelligence (AI): Possible implications

The integration of advanced nuclear technologies (both fission and fusion) with artificial intelligence (AI) presents unprecedented national security challenges and opportunities. As fusion energy approaches commercial viability alongside advanced Small Modular Reactors (SMRs), their integration with AI and Artificial General Intelligence (AGI) systems could fundamentally transform the global energy and AI landscapes — two pillars of national security. This document briefly examines how AI could accelerate nuclear energy development and deployment while altering existing power structures, a lot could be done to deepen the discussions. Simultaneously, it observes how nuclear-powered AI may expedite advances toward AGI and beyond. These issues are deeply interconnected and thus need to be examined as a whole and more comprehensively than what’s being summarized here. For instance, AI-powered autonomous operation of nuclear facilities could reduce human error but introduce new cybersecurity vulnerabilities and uncertainties. Further investigation would also address how AI-enhanced nuclear technologies might complicate proliferation concerns through advanced fuel cycle management, nuclear materials production and safeguard. The strategic advantage gained by first entities achieving successful AI-nuclear integration could reshape global and national security framework. Timely analysis of these implications may be crucial for policymakers seeking to harness these technologies' benefits while effectively mitigating their potential risks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Comparison of Artificial Compressibility Methods for Coupled Laminar Fluid Flow and Heat Transfer

Artificial compressibility (AC) methods for incompressible flows perturb the mass continuity equation by the time derivative of the pressure field to achieve direct coupling between pressure and velocity without the need for a projection method. Several variations of the original AC method have been proposed (e.g., the entropically damped artificial compressibility [EDAC] method) that can, in some scenarios, improve on the original model. In this paper, we methodically compare the results of the original AC model and the EDAC model for both steady-state and transient problems with coupling between the momentum and energy equations. We demonstrate that the EDAC model and the AC model yield similar numerical results, and the EDAC model is 10%-20% faster than the AC model for a given problem.

Oz, Furkan [ORNL] (ORCID:0000000265831724)↗
DOE OSTI2021

Al 2 O 3 Thin Films on Magnesium: Assessing the Impact of an Artificial Solid Electrolyte Interphase

Among the many emerging technologies under investigation as alternatives to the successful Lithium-ion battery, the magnesium battery is promising due to the wide availability of magnesium, its high volumetric capacity, and the possibility for safety improvements. One of the largest challenges facing rechargeable magnesium batteries is the formation of a passivation layer at the Mg metal anode interface when reactive species in the electrolyte are reduced at the electrode-electrolyte interface. To control the solid electrolyte interphase in Lithium batteries, protective layers called artificial solid electrolyte interphase (ASEI) layers have been successful in improving Li metal anode performance. The approach of protecting Mg metal anodes from electrolyte degradation has been demonstrated by fewer studies in the literature than Li systems. In this work, we discuss the properties of Al 2 O 3 thin films deposited using atomic layer deposition as an artificial solid electrolyte interphase at the Mg anode. Our results demonstrate that Al 2 O 3 does prevent electrolyte degradation due to the reductive nature of Mg. However, undesirable properties such as defects and layer breakdown lead to Mg growth that causes soft-shorting. The soft-shorting occurs with and without the protection layer, indicating the ALD layer does not prevent it and hinders Al 2 O 3 from being an ideal candidate for a protection layer. Crucial effects of this layer on Mg electrochemistry at the interface were observed, including growth of Mg deposits leading to soft-shorting of the cell whose morphology showed a dependence on the Al 2 O 3 layer. These results may provide guidelines for the future design and development of protective ASEI layers for Mg anodes.

25 ENERGY STORAGE↗
DOE OSTI2023

The Influence of Carbon Fiber Composite Specimen Design Parameters on Artificial Lightning Strike Current Dissipation and Material Thermal Damage

Previous artificial lightning strike direct effect research has examined a broad range of specimen design parameters. No works have studied how such specimen design parameters and electrical boundary conditions impact the dissipation of electric current flow through individual plies. This article assesses the influence of carbon fiber composite specimen design parameters (design parameters = specimen size, shape, and stacking sequence) and electrical boundary conditions on the dissipation of current and the spread of damage resulting from Joule heating. Thermal-electric finite element (FE) modelling is used and laboratory scale (<1 m long) and aircraft scale (>1 m long) models are generated in which laminated ply current dissipation is predicted, considering a fixed artificial lightning current waveform. The simulation results establish a positive correlation between the current exiting the specimen from a given ply and the amount of thermal damage in that ply. The results also establish that the distance to ground, from the strike location to the zero potential boundary conditions (ground), is the controlling factor which dictates the electric current dissipation in each ply. Significantly, this distance to ground is dependent on each of the specimen shape, dimensions, stacking sequence, and location of ground boundary conditions. Therefore, it is not possible to decouple current dissipation and damage from specimen design and boundary condition setup. However, it is possible to define a specimen size for a given specimen shape, stacking sequence, and waveform which limit the influence of specimen dimensions on the resulting current distribution and damage. For a rectangular specimen design which appears in literature multiple times, as 100 × 150 mm and with a stacking sequence of [45/0/-45/90] 4s , a specimen design of greater than 300 × 200 mm is required to limit the influence of specimen dimensions on current distribution and damage.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence

A new global estimate of surface turbulent fluxes, latent heat flux (LE) and sensible heat flux ( H ), and gross primary production (GPP) is developed using a machine learning approach informed by novel remotely sensed solar-induced fluorescence (SIF) and other radiative and meteorological variables. This is the first study to jointly retrieve LE, H , and GPP using SIF observations. The approach uses an artificial neural network (ANN) with a target dataset generated from three independent data sources, weighted based on a triple collocation (TC) algorithm. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides estimates of LE, H , and GPP from 2007 to 2015 at 1° × 1° spatial resolution and at monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are evaluated using eddy covariance tower estimates from the FLUXNET network across various climates and conditions. When compared to eddy covariance estimates, WECANN typically outperforms other products, particularly for sensible and latent heat fluxes. Analyzing WECANN retrievals across three extreme drought and heat wave events demonstrates the capability of the retrievals to capture the extent of these events. Uncertainty estimates of the retrievals are analyzed and the interannual variability in average global and regional fluxes shows the impact of distinct climatic events – such as the 2015 El Niño – on surface turbulent fluxes and GPP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network

Marine dimethyl sulfide (DMS) is important to climate due to the ability of DMS to alter Earth's radiation budget. Knowledge of the global-scale distribution, seasonal variability, and sea-to-air flux of DMS is needed in order to improve understanding of atmospheric sulfur, aerosol/cloud dynamics, and albedo. Here we examine the use of an artificial neural network (ANN) to extrapolate available DMS measurements to the global ocean and produce a global climatology with monthly temporal resolution. A global database of 82 996 ship-based DMS measurements in surface waters was used along with a suite of environmental parameters consisting of latitude–longitude coordinates, time of day, time of year, solar radiation, mixed layer depth, sea surface temperature, salinity, nitrate, phosphate, and silicate. Linear regressions of DMS against the environmental parameters show that on a global-scale mixed layer depth and solar radiation are the strongest predictors of DMS. These parameters capture ~9 % and ~7 % of the raw DMS data variance, respectively. Multilinear regression can capture more of the raw data variance (~39 %) but strongly underestimates DMS in high-concentration regions. In contrast, the artificial neural network captures ~66 % of the raw data variance in our database. Like prior climatologies our results show a strong seasonal cycle in surface ocean DMS with the highest concentrations and sea-to-air fluxes in the high-latitude summertime oceans. We estimate a lower global sea-to-air DMS flux (20.12±0.43 Tg S yr –1 ) than the prior estimate based on a map interpolation method when the same gas transfer velocity parameterization is used. Our sensitivity test results show that DMS concentration does not change unidirectionally with each of the environmental parameters, which emphasizes the interactions among these parameters. The ANN model suggests that the flux of DMS from the ocean to the atmosphere will increase with global warming. Given that larger DMS fluxes induce greater cloud albedo, this corresponds to a negative climate feedback.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1971

Artificial microfossils - Experimental studies of permineralization of blue-green algae in silica.

A technique has been developed to artificially fossilize microscopic algae in crystalline silica under conditions of moderately elevated temperature and pressure. The technique is designed to simulate geochemical processes thought to have resulted in the preservation of organic microfossils in Precambrian bedded cherts. In degree of preservation and mineralogic setting, the artificially permineralized microorganisms are comparable to naturally occurring fossil algae.

Oehler, J. H.↗
NASA NTRS1972

Artificial meteor ablation studies - Iron oxides.

Artificial meteor ablation was performed on natural minerals composed predominantly of magnetite and hematite by using an arc-heated plasma stream of air. Analysis indicates that most of the ablated debris was composed of two or more minerals. Wustite, a metastable mineral, was found to occur as a common product. The 'magnetite' sample, which was 80% magnetite, 14% hematite, 4% apatite, and 2% quartz, yielded ablated products consisting of more than 12 different minerals. Magnetite occurred in 91% of the specimens examined, hematite in 16%, and wustite in 30%. The 'hematite' sample, which was 96% hematite and 3% quartz, yielded ablated products consisting of more than 13 different minerals. Hematite occurred in 47% of the specimens examined, magnetite in 60%, and wustite in 28%. The more volatile elements (Si, P, and Cl) were depleted by about 50%. This study has shown that artificially created ablation products from iron oxides exhibit unique properties that can be used for identification.

Blanchard, M. B.↗
NASA NTRS1973

Study of artificially generated and natural auroras

The feasibility of generating artificial auroras by injecting electrons into the upper atmosphere was investigated by using an electron accelerator aboard an Aerobee 350 rocket. Four of the artificial auroral rays were detected and recorded by two geophysical sites separated enough to enable the spatial coordinates of the rays to be determined by triangulation. It was found that (1) the beam remained well collimated; (2) most of the initial beam energy was deposited in the atmosphere; (3) plasma instabilities did not play a significant role; and (4) the orientations of the rays were determined with sufficient accuracy to improve the knowledge of the earth's magnetic field over the Virginia coast. The publications resulting from this research are listed.

Davis, T. N.↗
NASA NTRS1973

Space vehicle with artificial gravity and earth-like environment

A space vehicle adapted to provide an artificial gravity and earthlike atmospheric environment for occupants is disclosed. The vehicle comprises a cylindrically shaped, hollow pressure-tight body, one end of which is tapered from the largest diameter of the body, the other end is flat and transparent to sunlight. The vehicle is provided with thrust means which rotates the body about its longitudinal axis, generating an artificial gravity effect upon the interior walls of the body due to centrifugal forces. The walls of the tapered end of the body are maintained at a temperature below the dew point of water vapor in the body and lower than the temperature near the transparent end of the body. The controlled environment and sunlight permits an earth like environment to be maintained wherein the CO2/O2 is balanced, and food for the travelers is supplied through a natural system of plant life grown on spacecraft walls where soil is located.

Gray, V. H.↗
NASA NTRS1973

Findings on American astronauts bearing on the issue of artificial gravity for future manned space vehicles

Findings for American astronauts are reviewed that may indicate some alteration in vestibular response related to exposure to zero gravity. Of 25 individuals participating in Apollo missions 7 through 15, nine have experienced symptomatology that could be related to motion sickness. The apparent divergence between these results and those from the Soviet space program, which initially appears great, may reflect the greater emphasis given by Soviet investigators to vestibular aberrations. Presently the incidence of motion sickness, long known as an indicator of vestibular disturbance, seems too low to warrant any positive statement regarding inclusion of an artificial gravity system in future long term space missions. Where motion sickness has occurred, adaptation to weightlessness has always resulted in abatement of symptoms. In the absence of biomedical justification for incorporating artificial gravity systems in long term space flight vehicles, engineering considerations may dictate the manner in which the final ballot is cast.

Berry, C. A.↗
NASA NTRS1973

Artificial meteor ablation studies

Artificial meteor ablation was performed on natural minerals, composed predominately of magnetite and hematite, using an arc heated plasma stream of air. Analysis of the ablated debris indicated most was composed of two or more minerals. The more volatile elements were depleted and the relative abundance of Fe increased as a result of both volatile depletion and a reduction in its oxidation state. Hematite was converted to magnetite in the ablation zone, and quartz and apatite minerals were converted to an Fe-rich glass consisting of varying amounts of Si, P, Cl, and Ca, depending upon the accessory minerals available at the time of melting. Artificially created ablation products from iron oxides exhibited unique properties depending on the composition of the original material and the environmental conditions of formation. In addition to the accepted elemental criteria, these properties were morphologic characteristics, textural parameters, and the existence of metastable minerals.

Blanchard, M. B.↗
NASA NTRS1974

A study of lagoonal and estuarine processes and artificial habitats in the area of the John F. Kennedy Space Center

In order to study the influence of an artificial habitat of discarded automobile tires upon the biomass in and around it, three sites were selected in the Banana River, one of which will serve as a control and the other two as locations for small tire reefs. Measurements and correlation studies of the biomasses and the species indicate that the biodynamics of the sites are appreciably the same in the three cases, that there are probably adequate populations at the lower trophic levels, that there are perhaps reduced numbers of upper level carnivores, and that it is likely that small artificial havens can contribute to an increase in populations of certain species of gamefish.

Poonai, P.↗