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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Fate of arsenic during up to 4.5 years of aging of Fe III -As V coprecipitates at acidic pH: Effect of reaction media (Nitrate vs. Sulfate), Fe/As molar ratio, and pH

Iron-arsenate (Fe III -As V ) coprecipitate generated in acid mine drainage and hydrometallurgical practices is one of the potential sources of As contamination in the environment. However, the As behavior as well as the transformation process of the Fe III -As V coprecipitate is still not fully understood under acidic conditions. This work systematically studied the effect of reaction media (sulfate vs. nitrate), Fe/As molar ratios, and acidic pH values on the transformation rates, routes, and products of the Fe III -As V coprecipitates at different temperatures during up to 4.5 years of aging. X-ray diffraction (XRD), transmission electron spectroscopy (TEM), Raman spectroscopy, and extended X-ray absorption fine structure spectroscopy (EXAFS) results showed that the Fe III -As V coprecipitates with Fe/As = 2 transformed to scorodite at pH 4 in both sulfate and nitrate media with poorly crystalline ferric arsenate as precursor. In comparison, for the Fe/As = 4 samples, parascorodite and hematite were formed in sulfate and nitrate media, respectively. We note arsenic was released into the liquid phase during the aging process for the samples with Fe/As = 2 and 4. The aqueous As concentrations ([As] aq ) in sulfate media were larger than those in nitrate media for both the Fe/As = 2 and 4 samples. In addition, the transformation products were goethite and Na-jarosite at Fe/As = 8 and 16, pH 2.5 with the decrease of [As] aq . The results also indicated that 6-line ferrihydrite was a common intermediate for many Fe-As transformation processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Expansion of the global RNA virome reveals diverse clades of bacteriophages

High-throughput RNA sequencing offers broad opportunities to explore the Earth RNA virome. Mining 5,150 diverse metatranscriptomes uncovered >2.5 million RNA virus contigs. Analysis of >330,000 RNA-dependent RNA polymerases (RdRPs) shows that this expansion corresponds to a 5-fold increase of the known RNA virus diversity. Gene content analysis revealed multiple protein domains previously not found in RNA viruses and implicated in virus-host interactions. Extended RdRP phylogeny supports the monophyly of the five established phyla and reveals two putative additional bacteriophage phyla and numerous putative additional classes and orders. The dramatically expanded phylum Lenarviricota, consisting of bacterial and related eukaryotic viruses, now accounts for a third of the RNA virome. Identification of CRISPR spacer matches and bacteriolytic proteins suggests that subsets of picobirnaviruses and partitiviruses, previously associated with eukaryotes, infect prokaryotic hosts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Understanding the microstructural evolution of hypersaline cemented paste backfill with low-field NMR relaxation

Highlights: • Microstructural evolution of CPB, prepared with tap and hypersaline water, is monitored using low-field NMR relaxometry. • T{sub 1} and T{sub 2} NMR relaxation measurements compared with mechanical strength via UCS tests • Hypersaline mixing water results in slower structural evolution and lower mechanical strength. Cemented paste backfill (CPB) comprising mineral tailings, binders and mixing water is an important potential support material in the mining industry. As the mechanical properties of CPB are significantly influenced by its microstructural characteristics the development of measurement tools to better understand its pore structure evolution is important for its increased utilisation. This study reports the application of low-field nuclear magnetic resonance (NMR) relaxation time measurements to characterise the microstructural evolution of CPB materials over 56 days of hydration, contrasting common tap water and hypersaline water (~22 wt% salt) as mixing water. Distinct NMR relaxation time populations were evidenced within each CPB sample, revealing the presence of both capillary (T{sub 1,2} ≈ 10 ms) and gel pore water (T{sub 1,2} ≈ 300–500 μs), with time-dependent relaxation measurements facilitating characterisation of capillary pore structure evolution over the hydration period assessed. Hypersaline samples demonstrated a time-lag in this measured capillary pore evolution, relative to those hydrated with tap water, while pore structure evolution rates were observed to increase with increased CPB binder content. Further, both T{sub 1} and T{sub 2} NMR relaxation times were found to correlate with the uniaxial compressive strength of the CPB materials investigated, facilitating the formulation of a predictive correlation function between NMR relaxation characteristics and mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

CRAGE-CRISPR facilitates rapid activation of secondary metabolite biosynthetic gene clusters in bacteria

With the advent of genome sequencing and mining technologies, secondary metabolite biosynthetic gene clusters (BGCs) within bacterial genomes are becoming easier to predict. For subsequent BGC characterization, clustered regularly interspaced short palindromic repeats (CRISPR) has contributed to knocking out target genes and/or modulating their expression; however, CRISPR is limited to strains for which robust genetic tools are available. Here we present a strategy that combines CRISPR with chassis-independent recombinase-assisted genome engineering (CRAGE), which enables CRISPR systems in diverse bacteria. To demonstrate CRAGE-CRISPR, we select 10 polyketide/non-ribosomal peptide BGCs in Photorhabdus luminescens as models and create their deletion and activation mutants. Subsequent loss- and gain-of-function studies confirm 22 secondary metabolites associated with the BGCs, including a metabolite from a previously uncharacterized BGC. These results demonstrate that the CRAGE-CRISPR system is a simple yet powerful approach to rapidly perturb expression of defined BGCs and to profile genotype-phenotype relationships in bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Te(IV) immobilization by siderite: Reaction kinetics, mechanism, and Te isotopic fractionation

Mining and industrial use over recent decades have released tellurium (Te) into the environment where it potentially contaminates soils, water supplies and food sources. Therefore, it is important to find ways of removing mobile and bioavailable Te from aqueous environments. Here, we report aqueous Te(IV) removal by siderite at varying Te concentrations (2, 6 and 10 mg mL –1 Te(IV)) and pH values (7, 7.9 and 9), together with associated isotope fractionation (ε 130 Te/ 125 Te). Our results show effective immobilization of Te(IV) that follows pseudo-first order rate kinetics. Formation of magnetite indicates reduction of Te(IV) on siderite surfaces and the formation of Te(0). The overall isotope fractionation (ε) is small (–0.23 ± 0.06‰) providing evidence that it is primarily controlled by adsorption of Te(IV) occurring simultaneously with reduction of Te(IV). Therefore, Te(IV) removal by siderite under mildly reducing ferruginous conditions may be identifiable by the characteristically small isotopic fractionation during both natural attenuation and active remediation. To our knowledge, this is the first study reporting reaction mechanisms of Te(IV) immobilization by an environmentally relevant Fe(II) mineral.

58 GEOSCIENCES↗
DOE OSTI2024

Bioelectrochemical reactor to manage anthropogenic sulfate pollution for freshwater ecosystems: Mathematical modeling and experimental validation

Anthropogenic sulfate loading into otherwise low-sulfate freshwater systems can cause significant ecological consequences as a biogeochemical stressor. To address this challenge, in situ bioremediation technologies have been developed to leverage naturally occurring microorganisms that transform sulfate into sulfide rather than implementing resource-intensive physio-chemical processes. However, bioremediation technologies often require the supply of electron donors to facilitate biological sulfate reduction. Bioelectrochemical systems (BES) can be an alternative approach for supplying molecular hydrogen as an electron donor for sulfate-reducing bacteria through water electrolysis. Although the fundamental mechanisms behind BESs have been studied, limited research has evaluated the design and operational parameters of treatment systems when developing BESs on a scale relevant to environmental systems. Further, this study aimed to develop an application-based mathematical model to evaluate the performance of BESs across a range of reactor configurations and operational modes. The model was based on sulfate transformation by hydrogenotrophic sulfate-reducing bacteria coupled with the recovery of solid iron sulfide species formed by the oxidative dissolution of dissolved ferrous iron from a stainless steel anode. Sulfate removal closely corresponded to the rate of electrolytic hydrogen production and hydraulic residence time but was less sensitive to specific microbial rate constants. The mathematical model results were compared to experimental data from a pilot-scale BES tested with nonacidic mine drainage as a case study. The close agreement between the mathematical model and the pilot-scale BES experiment highlights the efficacy of using a mathematical model as a tool to develop a conceptual design of a scaled-up treatment system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A sustainable cobalt separation with validation by techno-economic analysis and life-cycle assessment

Sustainable, cost-effective cobalt/nickel separations chemistry contributes to the realization of economically competitive lithium-ion battery recycling, as well as primary mining of cobalt and nickel. Such improvements can address supply chain challenges for cobalt, a critical element. Herein, we disclose a simple method for separating Co/Ni by second coordination-sphere molecular recognition. Selective cobalt precipitation is achieved using carbonate ions in an ammonia solution due to the outer-sphere, hydrogen bonding interactions between [Co(NH 3 ) 6 ] 3+ and CO 3 2− , evaluated with density functional theory calculations. We demonstrate this method on mixtures of Co/Ni chlorides comprising a 10-fold excess of Ni and provide comparisons with ore-processing systems. High purities (99.4(3)% Co; 98.2(4)% Ni) and recoveries (77(8)% Co; ∼100% Ni) were observed for both Co- and Ni-enriched products using optimized conditions. In conclusion, this method is potentially economically competitive based on initial techno-economic analysis (TEA) and life-cycle assessment (LCA) that also illustrate advantages in terms of sustainability.

cobalt↗
DOE OSTI2020

Phyllosilicate mineral dissolution upon alkaline treatment under aerobic and anaerobic conditions

The dissolution of phyllosilicate minerals exposed to high-pH environments has been studied to determine the influence of alkaline treatments and variable redox conditions on clay dissolution and the potential formation of new phases via incongruent dissolution phenomena. The present study focused on the dissolution of phyllosilicate minerals (illite, muscovite, and montmorillonite) under anaerobic and aerobic conditions using comparative solutions (sodium hydroxide and ammonium hydroxide) at similar ionic strength in the presence and absence of oxygen. Our batch data show that there is a rapid decrease in aluminum dissolution (< 240 hrs) and slow increase in silica over time (up to 1440 hrs). This trend was particularly evident for montmorillonite which shows the greatest dissolution for ammonium hydroxide, likely due to intercalation of the polyatomic cation ammonium into the mineral’s expandable layers. When comparing alkaline treatments, the strong base, sodium hydroxide, dissolved more of the mica minerals, illite and muscovite, likely due to ion-pairing between the silicate tetrahedra [SiO4]n- and Na+ cations in solution. In addition, redox conditions affect the systems similarly with treatment, although the sodium hydroxide treatment results in greater variability in solution redox conditions. For all investigated phyllosilicates, the calculated aqueous aluminum and silicon ratios over time are significantly different from the minerals’ stoichiometric ratios. As a result, we conclude that incongruent dissolution occurred and suggest formation of secondary precipitates. Understanding the potential for clay mineral alterations from interaction with alkaline solutions has implications for in situ remediation, mining operations, and waste interactions with the subsurface. This research shows that incongruent dissolution is likely and will lead to secondary precipitation which may have long term physical and chemical impacts in the subsurface.

mineral dissolution, phyllosilicate, alkaline, amm↗
DOE OSTI2024

Distributed sustainable metals production: opportunities for intensifying separations & alternative feedstocks

Meeting the increased demand for rare earth elements and beyond primary mined ore. Secondary sources like phosphogypsum, coal fly ash, used nuclear fuel, and electronic waste are concentrated sources of critical minerals. One strategy for a resilient supply chain is to decentralize sourcing and hydrometallurgical processing of metals. Rotating packed beds (RPBs) for solid-phase extraction and liquid-liquid extraction are gaining momentum for their ability to increase process throughput by 5-10x the state of the art. In conclusion, this review discusses advances in hydrometallurgical RPB processes and opportunities for implementation in distributed metals production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Characterization of coal extracts and their performances as binder for new carbon-based structural units

Coal production and usage have been declining in the past decade due to the transition to renewable energies, environmental regulations to reduce environmental pollution due to direct coal combustion from coal-fired power stations, and administrative policies. This downturn has created tremendous challenges for the coal industry, and many states rely on revenue from coal mining. Developing new valorization routes with high coal demand is essential and using coal-derived materials to make engineered products does offer an eco-friendly, attractive, and value-added use. This paper presents a brief introduction to the extraction process to derive coal deposits, extracts, and residuals (CDERs) and a comprehensive characterization analysis to determine the suitability of CDERs as binders to produce an innovative construction material named the carbon-based structural unit (CSU). CDERs are used to prepare the CSU with or without using mesophase pitch (MP) as binders and selected CDERs are heat-treated and pressure-heat-treated to improve their binding capabilities. The performances of the CSU specimens are evaluated based on compressive strength, density, and thermal conductivity. The CSU specimens mixed with distilled residue (DR) to pyrolysis char (PC) ratio of 1:2 achieve a compressive strength of 54.85 MPa, which is higher than the compressive strength of 30 MPa of normal concrete. The CSU specimens with deposit (De) and tetralin insoluble (TI) require the addition of MP to obtain compressive strengths greater than 30 MPa. Furthermore, these CSU specimens possess a relatively low density of about 1 g/cm 3 and low thermal conductivity of less than 0.25 W/m.K.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Biotechnological solutions for critical mineral recovery from unconventional feedstocks

Secure and sustainable metal recovery from unconventional feedstocks is needed to meet the mineral demands of energy, defense, and electronic technologies. Here, we highlight the potential to leverage nature’s ability to extract and differentiate metal ions in biotechnologies that could become the next generation of mining and refining. We describe bulk and trace processes and then discuss the advances and opportunities of two key bioprocesses: microbially mediated solubilization of metal ions from solid matrices (termed ‘bioleaching’) and bio-based separation of solubilized ions via selective adsorption to proteins. Both biotechnologies have advantages such as reduced energy input for leaching low-grade feedstocks and reduced organic solvent demand for separating ions with similar physiochemical properties but require more development for industrial scale recovery from unconventional feedstocks. Innovation in biological science and engineering may bring timely solutions to key challenges toward recovering critical minerals from unconventional feedstocks.

organic↗
DOE OSTI2026

Microbial spies and bloggers: programming cells to convert environmental information into discernible signals

Microbes regulate their dynamic behaviors using the chemical and physical characteristics of their environment. The ability of microbes to continuously convert this physicochemical information into biochemical information and to use organic matter in the environment as a power source makes these organisms attractive as chassis for building sensors. However, most biosensors have severe limitations when considering applications in hard-to-image settings like soils, sediments, and wastewater. Emerging technologies at the interface of biomolecular design, microbiome engineering, and synthetic biology offer new tools to program cells and communities as biosensors for these settings. Here, in this review, we describe innovations in biosensor outputs that are enabling new applications in complex environments, including reporters that are read out using electrochemical, gas chromatography, hyperspectral imaging, and next-generation sequencing methods. We also discuss computational advances that are accelerating the diversification of sensing components by mining metagenomics data for new transcriptional regulators and by designing allosteric protein switches that directly regulate reporter outputs using analytes. We highlight emerging opportunities for programming undomesticated microbes in communities to function as distributed sensors in the environment. Finally, we discuss the need for responsible biosensor development and to modernize regulatory frameworks to support evidence-based assessment of environmental biosensors.

analyte↗
DOE OSTI2026

Leveraging large language models to address data scarcity in machine learning for graphene synthesis

Machine learning in experimental materials science faces significant challenges due to the scarcity of data, which are costly and time-consuming to generate, particularly when relying on in-house experiments. Literature data mining offers a potential solution but introduces issues like mixed data quality, inconsistent formats, and non-uniform reporting of synthesis parameters, resulting in partially missing and heterogeneous features across the dataset. Here, we propose data imputation and feature engineering methods that employ pre-trained large language models (LLMs) to enhance machine learning performance on scarce, heterogeneous datasets, demonstrated on graphene CVD synthesis data and the ML-HydPARK hydrogen storage dataset. GPT models perform data imputation via tailored prompting and semantic normalization of inconsistently reported features through embeddings, for example, to harmonize the complex nomenclature of CVD substrates. Beyond yielding more diverse and richer feature representations than traditional methods such as K-nearest neighbors (KNN) and Multivariate Imputation by Chained Equations (MICE), LLM-based data imputation is evaluated against dataset characteristics and prompting strategies. We vary the level of autonomy granted to the LLM, from generic prompting that leverages pre-trained knowledge for autonomous data generation to data-informed prompting that constrains outputs using target-specific information, and demonstrate which level of autonomy yields superior imputation performance across datasets and feature types. The proposed data engineering methods markedly improve downstream performance; for example, in graphene layer number classification using a support vector machine (SVM), binary accuracy increases from 39% to 65% and ternary accuracy from 52% to 72%. Fine-tuning experiments on both datasets show that combining our proposed LLM-based data imputation and feature encoding methods with numerical machine learning predictors outperforms standalone fine-tuned LLM predictors in data-scarce settings. The proposed strategies emphasize data enhancement techniques rather than refining learning architectures or regularizing loss functions, offering a broadly applicable framework for improving machine learning performance on scarce, inhomogeneous datasets.

Chemical vapor deposition↗
DOE OSTI2026

Critical review of lithium recovery from geothermal brines with implications for Smackover Formation, USA

The rapidly growing demand for lithium, a critical element for energy storage and national security technologies, has intensified concerns over the long-term availability and environmental impact of conventional lithium sources, such as hard-rock mining. To meet future demand, it is vital to explore unconventional resources that can provide sustainable domestic supplies. Geothermal brines, produced as a byproduct of geothermal energy generation, offer a promising alternative for lithium recovery by leveraging existing infrastructure and renewable energy production. In particular, the Smackover Formation, an extensive reservoir of high-salinity brines spanning Arkansas, Texas, Louisiana, Mississippi, and Alabama in the U.S. Gulf Coast, holds significant untapped lithium reserves. Co-producing geothermal energy and lithium from these brines aligns with sustainable extraction objectives while addressing resource scarcity. This review synthesizes current knowledge of lithium occurrence in the Smackover Formation and geothermal resources in the region, while also exploring how emerging tools such as machine learning can enhance resource targeting and co-production efficiency. Finally, we discuss key technical challenges and outline future research directions needed to advance lithium extraction from geothermal brines and secure a resilient domestic supply chain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Progress in direct recycling of spent lithium nickel manganese cobalt oxide (NMC) cathodes

With the widespread use of lithium-ion batteries (LIBs) in portable electronics and electric vehicles (EVs), the end-of-life (EOL) LIBs are projected to reach 1336 GWh by 2040 under the sustainable development scenario. Proper recycling is urgently needed to minimize the release of hazardous waste and reduce mining activities by reintroducing critical minerals into the supply chain. Lithium nickel manganese cobalt oxide (LiNi x Mn y Co z O 2 , NMCs) cathodes have become dominant in the LIB market, especially with the increasing production of EVs, which are also the most valuable components in EOL LIBs. Unlike pyrometallurgical and/or hydrometallurgical methods, which convert spent NMCs into metals or metal compounds, direct recycling technologies aim to maximize the value of spent cathodes by restoring their degraded structure and composition. Furthermore, this review summarizes direct recycling methods for NMC cathodes published in the last decade and provides insights into the challenges and future development of direct recycling techniques.

Cathode↗
DOE OSTI2022

Boron isotopes in blue diamond record seawater-derived fluids in the lower mantle

Boron is a quintessential crustal element but its conspicuous presence in diamond – a mantle mineral – raises questions about potential subduction pathways for boron and other volatiles. It has been a long-standing goal to characterize the isotopic composition of boron in blue, boron-bearing (Type IIb) diamonds to reveal its origin. Mineral inclusions indicate that Type IIb diamonds crystallize at transition zone to lower mantle depths, meaning that if the boron is subducted it would trace a pathway of volatile elements into the deep mantle. Here, using off-line laser ablation sampling, we present the first boron isotope compositions, along with trace element contents and carbon isotope compositions, of a suite of blue diamonds mainly sourced from the Cullinan diamond mine in South Africa. The ten analyzed blue diamonds have a wide range in δ 11 B, between -9.2 ± 2‰ and -0.5 ± 2‰, compared to the more restricted range for mid-ocean ridge basalts (-7.1 ± 0.9‰). Carbon isotope values for the blue diamonds range between -20.6 and -1.8‰, with a mode at -17‰, significantly more negative than the main mantle mode at -5‰. Combined, the boron and carbon isotope compositions require fluid input from subducted oceanic lithosphere down into deep mantle source regions of blue diamonds. This finding highlights a deep subduction pathway for volatiles to stoke the source regions of deeply-derived magmas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗
DOE OSTI2022

Technology, technology, technology: An integrated assessment of deep decarbonization pathways for the Canadian oil sands

As a party to the Paris Agreement, Canada has an ambitious climate target of net-zero emissions by 2050. The country also holds the world's third largest oil reserves in the Alberta oil sands. Given increasing emissions from the oil sands sector, achieving Canada's net-zero target requires significant oil sands decarbonization. If, while phasing out fossil fuels, there is still a demand for Canadian oil sands, then the decarbonization of the resource production process becomes crucial. In this study, we use an enhanced version of the Global Change Analysis Model (GCAM) with a detailed unconventional oil sector for Canada, including mining and in situ resources. We ask, what is the future of the oil sands sector in deeply decarbonized global and Canadian economies? We address this question under four mitigation scenarios with varying global net-zero GHG emissions constraints, three additional representative lower carbon extraction technologies available for the oil sands sector, as well as global direct air capture (DAC) deployment. We find that lower carbon technology deployment allows a 20%–44% increase in oil sands production by 2050 for scenarios with net-zero GHG emissions in 2100 or 2075. DAC helps maintain oil sands production in the most ambitious global decarbonization scenario (net-zero GHG by 2050), without which low international oil demand makes Canadian oil sands production uncompetitive. Canadian oil sands production thus depends highly on the availability of lower carbon extraction technologies and international oil demand, which to a certain extent relies on the availability and global deployment of negative emissions technologies.

04 OIL SHALES AND TAR SANDS↗