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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 sources NASA NTRS DOE OSTI

DOE OSTI2026

Chemical-Free Lithium Separation from High-Salinity Brines Using Model-Informed and Machine Learning-Optimized Multi-Column Zwitterionic Chromatography

Direct Lithium Extraction (DLE) technologies often struggle to produce high-purity lithium salts from high-salinity brines, as current approaches require chemical-based elution, regeneration, and precipitation steps, resulting in significant environmental footprints. A novel salt fractionation approach using carboxybetaine resin, known as zwitterionic chromatography (ZIC), has demonstrated that lithium ions can be separated from divalent cations under high-salinity conditions using only water as eluent, with no regeneration required. To enable continuous and scalable deployment of this approach, we developed a chemical-free Multi-column Zwitterionic Chromatography (MZC) process and its theoretical and process models. To predict and optimize this nontraditional separation system, we introduced a novel anti-Langmuir isotherm, and the isotherm parameters were estimated through a machine learning-driven optimization based on artificial neural network ensembles with numerical feasibility assessment. Using machine learning-driven optimization, the MZC process achieved 98.0% lithium recovery, 99.5 % Li/(Li + Mg + Ca) purity, a 31.3% productivity increase, and a 33% reduction in water use compared to batch operation. The proposed MZC process enables lithium separation at $0.6-1.2 kg-1 Li, with costs dominated by resin manufacturing, while offering lower separation costs and carbon footprint compared with conventional carbonation. Overall, these findings position the MZC process as an effective polishing step within scalable and sustainable lithium production pipelines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Systematic Evaluation of Atmospheric Forcing, Surface Datasets, and Mesh Effects on Kilometer-Scale Land Surface and River Modeling

Earth system models are advancing toward kilometer-scale resolution to capture local climate impacts and extremes. High-resolution land and river modeling depends on multiple factors, including mesh, surface datasets, and atmospheric forcing, but their relative effects at kilometer scales remain unquantified. We evaluated five Energy Exascale Earth System Model land and river configurations over the Mid-Atlantic region using two mesh (1/8° structured versus variable-resolution unstructured mesh), two surface datasets (default versus newly developed), and three atmospheric forcings (NLDAS2, MSWX, GSWP). Evaluation against satellite, reanalysis, and in situ benchmarks across water, energy, and carbon cycles quantifies how these factors affect model performance. Forcing selection produces the largest bias reductions (12-99% across variables), followed by surface datasets (7-75%) and mesh (up to 21%). Forcing effects vary by variable, with MSWX reducing biases for snow water equivalent, evapotranspiration, albedo, temperature, and gross primary productivity, GSWP for snow cover and runoff, and NLDAS for soil moisture and streamflow. The use of newly developed surface datasets improves gross primary productivity (58% bias reduction) and evapotranspiration but increase soil moisture and albedo biases due to current modeling limitations. Variable-resolution unstructured mesh improves the simulation of small-basin streamflow through better capturing drainage networks, though mesh minimally affects other land variables. These findings provide important guidance for high-resolution modeling development and actionable science.

Land and River modeling↗

DOE OSTI2018

Cyclic plastic deformation behaviour of a directionally solidified nickel base superalloy at 850 °C: Damage micromechanisms

Highlights: • Isothermal LCF life of CM 247 DS is reduced using R = 0 instead of R = −1. • Reduction in LCF life is significant at lower values of Δε/2. • Reduction in fatigue life is attributed to the development of sustained mean stress. • Sustained mean stress prevents the slip transfer from γ-channels to γ′-precipitates. • Sustained mean stress promotes dislocation network formation and looping. - Abstract: Dislocation based deformation micromechanisms during low cycle fatigue deformation of nickel base superalloy CM 247 DS LC at 850 °C was investigated by conducting fatigue tests employing constant strain amplitudes for strain ratio (R) values of 0, −1 and carrying out extensive SEM and TEM examinations. Cyclic life of the alloy reduces for all fatigue tests conducted employing R = 0 in comparison with R = −1 owing to sustained mean stress developed during fatigue at R = 0. TEM examinations confirmed that sustained mean stress developed during low strain amplitude fatigue test (Δε/2 = 0.5%) using R = 0 condition prevented slip transfer from γ-channels to γ′-precipitates and resulted in the formation of dislocation substructures such as networks, nodes etc. and also promoted dislocation looping around γ′-precipitates. Lower fatigue life at R = 0 is mainly attributed to the development of these types of substructures, which promotes strain localization in both intra as well intergranular regions. Whereas, in specimen fatigue tested (Δε/2 = 0.5%) using R = −1 condition, shearing of γ′-precipitates by APB coupled dislocation and formation of stacking faults were observed. The formation and nature of stacking faults were analysed using weak beam imaging technique. Stacking fault formed during fatigue tests using R = −1 condition matured to micro-twins when Δε/2 value was increased to 0.8%. The mechanism of formation of these microtwins is discussed in detail. SEM based microstructural and fractographic examinations revealed that mean stress induced creep effect resulted in intergranular crack initiation and grain boundary cavitation during fatigue tests under R = 0 condition and therefore verified the facts revealed in TEM studies.

36 MATERIALS SCIENCE↗

DOE OSTI2017

The CMS Data Acquisition - Architectures for the Phase-2 Upgrade

The upgraded High Luminosity LHC, after the third Long Shutdown (LS3), will provide an instantaneous luminosity of 7.5 × 10 34 cm -2 s -1 (levelled), at the price of extreme pileup of up to 200 interactions per crossing. In LS3, the CMS Detector will also undergo a major upgrade to prepare for the phase-2 of the LHC physics program, starting around 2025. The upgraded detector will be read out at an unprecedented data rate of up to 50 Tb/s and an event rate of 750 kHz. Complete events will be analysed by software algorithms running on standard processing nodes, and selected events will be stored permanently at a rate of up to 10 kHz for offline processing and analysis. Here in this paper we discuss the baseline design of the DAQ and HLT systems for the phase-2, taking into account the projected evolution of high speed network fabrics for event building and distribution, and the anticipated performance of general purpose CPU. Implications on hardware and infrastructure requirements for the DAQ “data center” are analysed. Emerging technologies for data reduction are considered. Novel possible approaches to event building and online processing, inspired by trending developments in other areas of computing dealing with large masses of data, are also examined. We conclude by discussing the opportunities offered by reading out and processing parts of the detector, wherever the front-end electronics allows, at the machine clock rate (40 MHz). This idea presents interesting challenges and its physics potential should be studied.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Co-catabolism of arginine and succinate drives symbiotic nitrogen fixation

Biological nitrogen fixation emerging from the symbiosis between bacteria and crop plants holds promise to increase the sustainability of agriculture. One of the biggest hurdles for the engineering of nitrogen-fixing organisms is an incomplete knowledge of metabolic interactions between microbe and plant. In contrast to the previously assumed supply of only succinate, we describe here the CATCH-N cycle as a novel metabolic pathway that co-catabolizes plant provided arginine and succinate to drive the energy-demanding process of symbiotic nitrogen fixation in endosymbiotic rhizobia. Using systems biology, isotope labeling studies and transposon sequencing in conjunction with biochemical characterization, we uncovered highly redundant network components of the CATCH-N cycle including transaminases that interlink the co-catabolism of arginine and succinate. The CATCH-N cycle uses N2 as an additional sink for reductant and therefore delivers up to 25% higher yields of nitrogen than classical arginine catabolism—two alanines and three ammonium ions are secreted for each input of arginine and succinate. We argue that the CATCH-N cycle has evolved as part of a synergistic interaction to sustain bacterial metabolism in the microoxic and highly acid environment of symbiosomes. Thus, the CATCHN cycle entangles the metabolism of both partners to promote symbiosis. Our results provide a theoretical framework and metabolic blueprint for the rational design of plants and plant-associated organisms with new properties to improve nitrogen fixation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Clean Cities 2015 Annual Metrics Report

The U.S. Department of Energy's (DOE's) Clean Cities program advances the nation's economic, environmental, and energy security by supporting local actions to cut petroleum use and greenhouse gas (GHG) emissions in transportation. A national network of nearly 100 Clean Cities coalitions, whose territory covers 80% of the U.S. population, brings together stakeholders in the public and private sectors to deploy alternative and renewable fuels, idle-reduction (IR) measures, fuel economy improvements, and new transportation technologies as they emerge. Each year, DOE asks Clean Cities coordinators to submit annual reports of their activities and accomplishments for the previous calendar year. Progress reports and information are submitted online as a function of the Alternative Fuels Data Center (AFDC) at the National Renewable Energy Laboratory (NREL). Coordinators report a range of information that characterize the membership, funding, projects, and activities of their coalitions. They also document activities in their region related to the development of refueling/charging infrastructure, sales of alternative fuels; deployment of alternative fuel vehicles (AFVs), plug-in electric vehicles (PEVs), hybrid electric vehicles (HEVs), and plug-in hybrid electric vehicles (PHEVs); idle reduction initiatives; fuel economy improvement activities; and programs to reduce vehicle miles traveled (VMT). NREL analyzes the data and translates them into petroleum-use and GHG emission reduction impacts, which are summarized in this report.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2019

Clean Cities Coalitions: 2017 Activity Report

The U.S. Department of Energy's Vehicle Technologies Office (VTO) works with local Clean Cities coalitions across the country as part of its Technology Integration Program. These efforts help businesses and consumers make smarter/more-informed transportation energy choices that can save energy, lower costs, reduce reliance on imported oil, and reduce emissions. This report summarizes the success and impact of coalition activities based on data and information provided in their annual progress reports. A national network of nearly 100 Clean Cities coalitions, whose territory covers 80% of the U.S. population, brings together stakeholders in the public and private sectors to use alternative and renewable fuels, idle-reduction (IR) measures, fuel economy improvements, and new transportation technologies as they emerge. To ensure success, coalitions leverage a robust set of expert resources and tools provided by national laboratories and DOE. From technical assistance and handbooks to websites and targeted analysis, these resources contribute to every facet of coalition success. This strong national framework of resources, which facilitates consistent vision and informed coalitions, is a hallmark of the program.

2017 metrics↗

NASA NTRS1984

Materials properties data base computerization

Material property data plays a key role in the design of jet engine components. Consistency, accuracy and efficient use of material property data is of prime importance to the engineering community. The system conception, development, implementation, and future plans for computer software that captures the Material Properties Handbook into a scientific data base are described. The engineering community is given access to raw data and property curves, display of multiple curves for material evaluation and selection, direct access by design analysis computer programs, display of the material specification, and a historical repository for the material evolution. The impact of this activity includes significant productivity gains and cost reductions; all users have access to the same information nd provides consistent, rapid response to the needs of the engineering community. Future plans include incorporating the materials properties data base into a network environment to access information from other data bases and download information to engineering work stations.

Baur, R. G.↗

NASA NTRS1989

Hierarchical Poly Tree computer architectures defined by computational multidisciplinary mechanics

This paper will develop an alternative computer architecture called the Poly Tree. Based on the requirements of computational mechanics and the concept of hierarchical substructuring, the paper will explore the development of problem-dependent parallel networks of processors which will enable significant, often superlinear, speed enhancements; provide a logical/efficient framework for linear/nonlinear and transient structural mechanics problems; and provide a logical framework from which to apply model reduction procedures. In addition, the paper will explore optimal processor arrangements which define the overall system granularity. Consideration will also be given to system I/O requirements.

Padovan, Joe↗

NASA NTRS1993

Visual information processing II; Proceedings of the Meeting, Orlando, FL, Apr. 14-16, 1993

Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.

Huck, Friedrich O.↗

NASA NTRS1996

Technology Directions for the 21st Century

New technologies will unleash the huge capacity of fiber-optic cable to meet growing demands for bandwidth. Companies will continue to replace private networks with public network bandwidth-on-demand. Although asynchronous transfer mode (ATM) is the transmission technology favored by many, its penetration will be slower than anticipated. Hybrid networks - e.g., a mix of ATM, frame relay, and fast Ethernet - may predominate, both as interim and long-term solutions, based on factors such as availability, interoperability, and cost. Telecommunications equipment and services prices will decrease further due to increased supply and more competition. Explosive Internet growth will continue, requiring additional backbone transmission capacity and enhanced protocols, but it is not clear who will fund the upgrade. Within ten years, space-based constellations of satellites in Low Earth orbit (LEO) will serve mobile users employing small, low-power terminals. 'Little LEO's' will provide packet transmission services and geo-position determination. 'Big LEO's' will function as global cellular telephone networks, with some planning to offer video and interactive multimedia services. Geosynchronous satellites also are proposed for mobile voice grade links and high-bandwidth services. NASA may benefit from resulting cost reductions in components, space hardware, launch services, and telecommunications services.

Crimi, Giles F.↗

NASA NTRS2016

Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

remote sensing↗

DOE OSTI2012

Porphyrin coordination polymer nanospheres and nanorods

A porphyrin coordination polymer nanostructure comprising a network of pyridyl porphyrin molecules and coordinating metal ions coordinatively bound through the pyridyl groups. In some embodiments, the porphyrins are metalloporphyrins. A variety of nanostructures are formed by the network polymer, including nanospheres, polygonal nanostructures, nanorods, and nanofibers, depending on a variety of factors including coordination metal ion, porphyrin type, metal of the metalloporphyrin, and degree of agitation during nanostructure formation. Reduction of coordinating metal ions may be used to form metal nanoparticles on the coordination polymer nanostructure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Porphyrin coordination polymer nanospheres and nanorods

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2018

Modeling the Long-Term Behavior of Cementitious Barriers - 18188

Cementitious materials are commonly included as backfill/barrier materials in geological repositories for radioactive waste. An understanding of the long-term behavior of cement-based barriers is therefore required to provide confidence in their safety functions within an environmental safety case. Geochemical modelling has been undertaken on several different radioactive waste repository concepts (and their natural/industrial analogues), to explore the nature of cement degradation over timescales relevant to postclosure safety (many tens of thousands of years to c. 1 Ma). In radionuclide transport calculations undertaken as part of performance assessments, it is typically considered that the properties of cementitious engineered barrier materials change as they degrade, potentially resulting in an increase in porosity hydraulic conductivity, and effective diffusion coefficients. However, reactive transport modelling (supported by some analogue data) suggests that, in some repository systems, a degree of clogging of the cement pore space could occur and that some advective flow paths (cracks in the barriers, fractures in the host rock) could become (to some extent) infilled by cement and rock alteration products. This could result in a reduction in water flow and contaminant transport in the vicinity of the cement-rock interface, but some uncertainties remain (especially process couplings and the nature of water flow in complex fracture networks that are becoming clogged). In addition, the armoring of fracture surfaces could result in decreased potential for diffusion of solutes into the rock matrix. It is envisaged that ongoing work will continue to improve reactive-transport model capabilities, such that the implications cement degradation has for contaminant transport can be predicted with greater confidence. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

CONCURRENT, CONDENSED STEIN VARIATIONAL GRADIENT DESCENT FOR UNCERTAINTY QUANTIFICATION OF NEURAL NETWORKS

In this work, we propose a Stein variational gradient descent (SVGD) method to concurrently sparsify, train, and provide uncertainty quantification (UQ) of a complexly parameterized model, such as a neural network (NN). It employs a graph reconciliation and condensation process to reduce complexity and increase similarity in the Stein ensemble of parameterizations. Therefore, the proposed concurrent, condensed SVGD (ccSVGD) method can provide UQ on parameters, not just outputs. Furthermore, the parameter reduction speeds up the convergence of the Stein gradient descent as it reduces the combinatorial complexity by aligning and differentiating the sensitivity to parameters. These properties are demonstrated with an illustrative example and an application to a mechanical response representation problem in solid mechanics.

42 ENGINEERING↗

DOE OSTI2024

Machine learning models of intermittent operation of RO wellhead water treatment for salinity reduction and nitrate removal

Machine learning models were developed for intermittent multi-mode operation of a wellhead reverse osmosis water purification and desalination system to predict salt passage, nitrate passage, and permeate flux. The models, based on long short-term memory (LSTM) recurrent neural network (RNN) architecture, included an attention mechanism to increase model performance in proximity of the regulatory limit for nitrate. Training and testing of the models for the Startup, Production, Shutdown and Flushing operational modes were based on operational data (consisting of 22 process variables per data sample) acquired every 2–5 s over a six-month period. The significant sets of model input attributes for the different operational modes were assessed via Spearman ranking correlation, Self-Organizing Map (SOM) analysis and feed forward feature selection (FFFS). Although the variability of nitrate passage, salt passage and permeate flux was significant over the four operational modes, prediction performance for the three outcomes were with R2 and Average Absolute Relative Error (AARE) of 0.78–0.95 and 2.96–6.16 %, respectively. Model updates post membrane elements replacement demonstrated similar levels of prediction accuracy. The study results suggest that there is merit in exploring the utility of multi-mode models for sensor fault detection, data imputation, and for potential use in model-predictive control.

Intermittent RO operation↗

DOE OSTI2015

Delta: Data Reduction for Integrated Application Workflows

Integrated Application Workflows (IAWs) run multiple simulation workflow components concurrently on an HPC resource connecting these components using compute area resources and compensating for any performance or data processing rate mismatches. These IAWs require high frequency and high volume data transfers between compute nodes and staging area nodes during the lifetime of a large parallel computation. The available network band-width between the two areas may not be enough to efficiently support the data movement. As the processing power available to compute resources increases, the requirements for this data transfer will become more difficult to satisfy and perhaps will not be satisfiable at all since network capabilities are not expanding at a comparable rate. Furthermore, energy consumption in HPC environments is expected to grow by an order of magnitude as exascale systems become a reality. The energy cost of moving large amounts of data frequently will contribute to this issue. It is necessary to reduce the volume of data without reducing the quality of data when it is being processed and analyzed. Delta resolves the issue by addressing the lifetime data transfer operations. Delta removes subsequent identical copies of already transmitted data during transfers and restores those copies once the data has reached the destination. Delta is able to identify duplicated information and determine the most space efficient way to represent it. Initial tests show about 50% reduction in data movement while maintaining the same data quality and transmission frequency.

97 MATHEMATICS AND COMPUTING↗