Search NASA⌕ Search

SEARCH · Search NASA

Results for “Deep potential”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

Near Earth Object (NEO) Mitigation Options Using Exploration Technologies

This work documents the advancements in MSFC threat modeling and mitigation technology research completed since our last major publication in this field. Most of the work enclosed here are refinements of our work documented in NASA TP-2004-213089. Very long development times from start of funding (10-20 years) can be expected for any mitigation system which suggests that delaying consideration of mitigation technologies could leave the Earth in an unprotected state for a significant period of time. Fortunately there is the potential for strong synergy between architecture requirements for some threat mitigators and crewed deep space exploration. Thus planetary defense has the potential to be integrated into the current U.S. space exploration effort. The number of possible options available for protection against the NEO threat was too numerous for them to all be addressed within the study; instead, a representative selection were modeled and evaluated. A summary of the major lessons learned during this study is presented, as are recommendations for future work.

Arnold William↗

Nuclear Thermal Propulsion Scoping Analysis of Fuel Plate Core Configurations

Nuclear thermal propulsion (NTP) engines use a nuclear reactor to heat up hydrogen to high temperatures. Thrust is generated as the hydrogen is ejected at high velocity through a nozzle. NTP has the potential of reducing travel times for deep space missions, such as to Mars. The United States studied NTP early in the space age and the National Aeronautics and Space Administration (NASA) is currently revisiting the potential of the technology to enable its missions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Origin of water masses in Floridan Aquifer System revealed by 81 Kr

Groundwater in coastal aquifers serves as an essential resource in densely populated areas throughout the world. However, hydrological connection to the ocean leaves it at risk of salinization via changes in climate and hydrological cycles. Therefore, an accurate hydrological characterization of coastal aquifers is of the utmost importance. Although localized salinization of shallow aquifers has commonly been studied, geochemical constraints on the time scale of regional freshwater and seawater in coastal aquifers are limited especially in carbonate aquifers. Such information is not only crucial for water resource management, but also for understanding solute flux over the land-ocean boundary and for interpreting the geochemical signatures that each water mass carries. Toward this goal, we report tracer-based, subsurface residence times of groundwater in the Floridan Aquifer System in southern Florida, which is one of the most productive aquifers on Earth. The first application of Kr 81-an emerging tracer of old groundwater-to this aquifer has identified freshwater recharge during the last glacial period as anticipated from previous studies using other geochemical tools including radiocarbon, stable isotopes and noble gas concentrations. Moreover, freshwater of Holocene age was also detected at 100 km-distance from the recharge area, suggesting the possibility of an active flow system in the upgradient region. A contribution of fossil seawater that predates the last glacial maximum was locally identified, suggesting slow seawater circulation and limited but significant solute flux from the ocean into the aquifer for dolomitization. This also implies that the deep saline coastal groundwater can potentially serve as a paleo-seawater archive.

58 GEOSCIENCES↗

Experimental study of fracture slip due to stress perturbation in fractured geo-resources

Anthropogenic activities such as underground fluid injection/extraction, well stimulation, and dam impoundment will perturb the state-of-stress in the subsurface, which could activate critically stressed pre-existing fractures and faults. Fault and fracture activation can induce seismicity, change flow behavior, and damage asperities on the fracture surface to alter reservoir permeability. Here, in this study, triaxial shear tests were conducted on saw cut and rough fracture Barre granite specimens to better characterize how a decrease in normal stress and increase in shear stress will influence crystalline rock fracture hydromechanical properties. In a triaxial set up, confining pressure (CP) and differential stress (DS) were used to induce normal and shear stress on a 45° oriented fracture. Fracture slip and the corresponding stress relaxation was observed when the confining stress decreased. Fracture permeability increased when the fracture slipped. Moreover, new micro-cracks observed by x-ray images indicated the creation of new flow paths for fluid movement. The experimental outcomes of this study indicate that decrease in normal stress due to stress perturbations along the faults/fractures in the extensional stress regime can induce the slip along the fracture. This could have a significant influence on slope stability in quarries, stimulation and injection strategy in deep geo-resources, and potentially minimize the risk of induced seismicity. The observed stress dependency of hydraulic aperture in rough fracture during pre- and post-slip stages could provide key inputs for field-scale simulation of geo-resources.

58 GEOSCIENCES↗

Decarbonization of the Chemical Industry Through Electrification: Barriers and Opportunities

The chemical industry is a major source of economic productivity and employment globally and among the top 3 industrial sources of greenhouse gas (GHG) emissions, along with steel and cement. As global demand for chemical products continues to grow, there is an urgency to develop and deploy sustainable chemical production pathways and to reconsider continued investment in current emission-intensive production technologies. This perspective describes the challenges and opportunities to decarbonize the chemical industry via electrification powered by low-carbon electricity supply, both in the near term and long term, and it discusses four technological pathways ranging from the more mature direct substitution of heat with electricity and use of hydrogen to technologically less mature, yet potentially more selective, approaches based on electrochemistry and plasma. Finally, we highlight the key elements of integrating an electrified industrial process with the power sector to leverage process flexibility to reduce energy costs of chemical production and provide valuable power grid support services. Unlocking such plant-to-grid coordination and the four electrification pathways has significant potential to facilitate rapid and deep decarbonization of the chemical industry sector.

chemical synthesis↗

Identification of Common Types of Plastics by Vibrational Spectroscopic Techniques

Polyethylene Terephthalate (PET), High-Density Polyethylene (HDPE), Polyvinyl Chloride (PVC), Low-Density Polyethylene (LDPE), Polypropylene (PP), and Polystyrene (PS) account for most plastic use worldwide, with production nearing 380 million tons annually. A considerable portion enters municipal solid waste and landfills, creating long-term environmental concerns. Scaling recycling operations requires automated sorting technologies, with spectroscopy and machine learning offering promising solutions. In this study, a six-class convolutional neural network (CNN) was developed for plastic identification using vibrational spectroscopies. Raman Scattering (RS) spectra collected from recycling samples enabled accurate chemical differentiation while assessing the influence of visible features such as color. A CNN trained on RS data achieved 100% classification accuracy. To strengthen field applicability, Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy was incorporated, achieving 95% accuracy with a similar CNN model. These findings demonstrate the potential of integrating spectroscopy with deep learning for reliable plastic classification, advancing development of scalable, field-ready recycling technologies.

Garcia Tovar, Maria P.↗

Dual‐Transformer Deep Learning Framework for Seasonal Forecasting of Great Lakes Water Levels

Abstract The Great Lakes of North America form one of the largest freshwater systems on Earth, and their lake‐wide average water levels (lake levels) can fluctuate by more than 0.5 m on a seasonal scale. These fluctuations pose substantial challenges for coastal resilience, flood risk management, and navigation planning. Accurate seasonal forecasting of lake levels using traditional mechanistic models is challenging due to the complex physical mechanisms and coupled hydroclimatic processes involved. Recently, deep learning has gained prominence in geoscience applications for its ability to recognize intricate patterns within multiphysical data sets. Here, we introduce a novel Dual‐Transformer deep learning framework, tested on the Great Lakes. This architecture integrates two modified Transformer models: the Prophet, which predicts underlying trends, and the Critic, which refines the Prophet's predictions. The final lake level prediction is derived by weighting the outputs of both models through a multi‐layer perceptron, jointly trained with the Prophet and Critic to enhance overall accuracy. Our results demonstrate that the innovative learning framework achieves the highest prediction accuracy compared to established deep learning models when using identical input features. It attains a root mean square error of 4–7 cm in predicting lake levels up to 6 months in advance across the lakes. Additionally, the Dual‐Transformer model runs six orders of magnitude faster than conventional mechanistic models, producing results in less than one second on a typical personal computer. These findings suggest that our deep learning framework has strong potential to advance lake level prediction and carries important implications for water management and disaster mitigation, thereby enhancing the quality of life in coastal regions.

Chen, Yi [Great Lakes Research Center Michigan Tec↗

What dictates soft clay-like lithium superionic conductor formation from rigid salts mixture

Abstract Soft clay-like Li-superionic conductors, integral to realizing all-solid-state batteries, have been recently synthesized by mixing rigid-salts. Here, through computational and experimental analysis, we clarify how a soft clay-like material can be created from a mixture of rigid-salts. Using molecular dynamics simulations with a deep learning-based interatomic potential energy model, we uncover the microscopic features responsible for soft clay-formation from ionic solid mixtures. We find that salt mixtures capable of forming molecular solid units on anion exchange, along with the slow kinetics of such reactions, are key to soft-clay formation. Molecular solid units serve as sites for shear transformation zones, and their inherent softness enables plasticity at low stress. Extended X-ray absorption fine structure spectroscopy confirms the formation of molecular solid units. A general strategy for creating soft clay-like materials from ionic solid mixtures is formulated.

25 ENERGY STORAGE↗

Structural analysis of mycobacterial homoserine transacetylases central to methionine biosynthesis reveals druggable active site

Mycobacterium tuberculosis is the cause of the world’s most deadly infectious disease. Efforts are underway to target the methionine biosynthesis pathway, as it is not part of the host metabolism. The homoserine transacetylase MetX converts L-homoserine to O-acetyl-L-homoserine at the committed step of this pathway. In order to facilitate structure-based drug design, we determined the high-resolution crystal structures of three MetX proteins, including M. tuberculosis (MtMetX), Mycolicibacterium abscessus (MaMetX), and Mycolicibacterium hassiacum (MhMetX). A comparison of homoserine transacetylases from other bacterial and fungal species reveals a high degree of structural conservation amongst the enzymes. Utilizing homologous structures with bound cofactors, we analyzed the potential ligandability of MetX. The deep active-site tunnel surrounding the catalytic serine yielded many consensus clusters during mapping, suggesting that MtMetX is highly druggable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring orbital angular momentum and spin-orbit correlations for gluons at the Electron-Ion Collider

In our previous work [S. Bhattacharya , ], we introduced a pioneering observable aimed at experimentally detecting the orbital angular momentum (OAM) of gluons. Our focus was on the longitudinal double spin asymmetry observed in exclusive dijet production during electron-proton scattering. We demonstrated the sensitivity of the cos ϕ angular correlation between the scattered electron and proton as a probe for gluon OAM at small x and its intricate interplay with gluon helicity. This current work provides a comprehensive exposition, diving further into the aforementioned calculation with added elaboration and in-depth analysis. We reveal that, in addition to the gluon OAM, one also gains access to the spin-orbit correlation of gluons. We supplement our work with a detailed numerical analysis of our observables for the kinematics of the Electron-Ion Collider. In addition to dijet production, we also consider the recently proposed semi-inclusive diffractive deep inelastic scattering process, which potentially offers experimental advantages over dijet measurements. Finally, we investigate quark-channel contributions to these processes and find an unexpected breakdown of collinear factorization. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Arrested Phase Separation in Double-Exchange Models: Large-Scale Simulation Enabled by Machine Learning

In this work, we present large-scale dynamical simulations of electronic phase separation in the single-band double-exchange model based on deep-learning neural-network potentials trained from small-size exact diagonalization solutions. We uncover an intriguing correlation-induced freezing behavior as doped holes are segregated from half filled insulating background during equilibration. While the aggregation of holes is stabilized by the formation of ferromagnetic clusters through Hund’s coupling between charge carriers and local magnetic moments, this stabilization also creates confining potentials for holes when antiferromagnetic spin-spin correlation is well developed in the background. The dramatically reduced mobility of the self-trapped holes prematurely disrupts further growth of the ferromagnetic clusters, leading to an arrested phase separation. Implications of our findings for phase separation dynamics in materials that exhibit colossal magnetoresistance effect are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Accelerating Lossy and Lossless Compression on Emerging BlueField DPU Architectures

Data compression has become a crucial technique in addressing performance bottlenecks caused by increasing data volumes in High-Performance Computing (HPC), Big Data, and Deep Learning (DL). Despite its potential to boost system performance, recent studies have identified significant challenges with existing compression methods, mainly due to their high computational demands amidst continuously growing data sizes. Concurrently, the advent of Data Processing Units (DPUs), equipped with programmable System-on-Chip (SoC) and specialized compression accelerators, offers a promising opportunity to alter the landscape of data compression. This paper explores the complexities and potential of leveraging NVIDIA BlueField DPUs to accelerate lossy and lossless compression. Towards this, we introduce PEDAL, an innovative library that leverages the hardware capabilities of DPUs to unify and optimize data compression designs. Moreover, we seamlessly co-design PEDAL with the popular MPICH MPI library, demonstrating up to 101x speedup in compression time and 88x decrease in communication latency. Drawing on these achievements, we share our experience with various research communities about accelerating data compression on DPUs in communication-oriented HPC scenarios.

Li, Yuke↗

Surface and bulk characterization of reservoir and cap-rocks: Past, present, and future

Geologic formations provide potentially some of the largest volume capacities for CO 2 storage or sequestration. Potential storage sites can be deep saline aquifers, depleted oil reservoirs, and coal seams, surrounded by sealing layers to prevent CO 2 from leaking. It is therefore critical to understand mechanisms contributing to CO 2 trapping and CO 2 leaks. Both phenomena are governed by reactions at the interfaces of the reservoir and cap-rocks and are controlled by the complex chemistry and pore structures of rocks. Mechanisms at the macroscale are affected by the processes occurring at the nanoscale. This review highlights the necessity of multitechnique, multiscale characterization of rocks and points to the importance of surface analysis and surface science studies. Two shale rocks (seals) from Niobrara and Agardhfjellet formations with complex surface chemistry are used as examples throughout the paper. Typically, evaluation of rocks with x-ray diffraction, thermogravimetric analysis, Rock-Eval pyrolysis, gas adsorption, and electron microscopy combined with energy dispersive x-ray spectroscopy is conducted to provide valuable information about the bulk mineralogy, elemental composition, pore volume, and adsorbed species on the sample surface. These studies are necessary prior to designing surface sensitive experiments with x-ray photoelectron spectroscopy (XPS), guiding both sample preparation and sample analysis. XPS has been widely used to study the surface composition of rocks during the investigations of their fine-scale wettability, and the main findings are highlighted here. This paper also reviews the existing literature on ambient-pressure XPS, which provides new opportunities to study in situ chemical alteration due to interactions with CO 2 and offers recommendations for adapting this technique to study rock-fluid interactions, allowing for the identification of fundamental interactions during CO 2 sequestration and guide selection of formation sites for improved storage.

54 ENVIRONMENTAL SCIENCES↗

The synthesis of novel lanthanum hydroxyborate at extreme conditions

The novel structure of lanthanum hydroxyborate La 2 B 2 O 5 (OH) 2 was synthesized by the reaction of partially hydrolyzed lanthanum and boron oxide in a diamond anvil cell under high-pressure/high-temperature (HPHT) conditions of 30 GPa and ~2,400 K. The single-crystal X-ray structure determination of the lanthanum hydroxyborate revealed: P$\overline{3}$c1 , a = 6.555(2) Å, c = 17.485(8) Å, Z = 6, R 1 = 0.056. The three-dimensional structure consists of discrete planar BO 3 groups and three crystallographically different La ions: one is surrounded by 9, one by 10, and one by 12 oxygen anions. The band gap was estimated using ab initio calculations to be 4.64 eV at ambient pressure and 5.26 eV at 30 GPa. The current work describes the novel HPHT lanthanum hydroxyborate with potential application as a deep-ultraviolet birefringent material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pioneer 10 and 11 mission support

Possible improvements in the Deep Space Network and their potential effect on the telecommunications limit of Pioneer 10 and on Pioneer 11 Saturn encounter are discussed.

Miller, R. B.↗

Constructions for finite-state codes

A class of codes called finite-state (FS) codes is defined and investigated. These codes, which generalize both block and convolutional codes, are defined by their encoders, which are finite-state machines with parallel inputs and outputs. A family of upper bounds on the free distance of a given FS code is derived from known upper bounds on the minimum distance of block codes. A general construction for FS codes is then given, based on the idea of partitioning a given linear block into cosets of one of its subcodes, and it is shown that in many cases the FS codes constructed in this way have a d sub free which is as large as possible. These codes are found without the need for lengthy computer searches, and have potential applications for future deep-space coding systems. The issue of catastropic error propagation (CEP) for FS codes is also investigated.

Pollara, F.↗