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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 577 records · Page 32

Assessing the Extractability of Rare Earth Elements from Coal Preparation Fines Refuse Using an Organic Acid Lixiviant

We report that this work is a first-order study to assess the suitability of an organic acid lixiviant to extract rare earth elements (REE) from coal preparation fines refuse sourced from a Pennsylvania mine with a total REE of ~ 300 ppm. The extraction of REE using an organic acid, in this case 0.1 M citric acid and 0.5 M trisodium citrate solution, is compared against 0.5 M (NH 4 ) 2 SO 4 , 1 M HCl, 1.2 M H 2 SO 4 , and 0.5 M ethylenediaminetetraacetic acid (EDTA). Ashing the coal waste material prior to leaching tests with the citrate solution nominally improved REE extraction. Buffered citrate solution recovered 7% of the total REE in the as-received Isabella Fines as compared to 11% in ashed samples, whereas (NH 4 ) 2 SO 4 extracted 5–6%, respectively. EDTA recovered up to 33% of the total REE, most likely due to the higher coordination chelate bond. Mineral acids, however, outperformed the organic acids on ashed material (16–52% REE recovery), suggesting that organic acids may not be a suitable competitive option for REE extraction from these types of feedstocks.

01 COAL, LIGNITE, AND PEAT↗

Conceptual core design of the molten metal fueled microreactor with self-regulating capability

The microreactor concept has received significant attention in the United States for its lower capital investment, siting flexibility and high mobility. A microreactor aims to provide reliable electricity in remote communities, mining areas, or isolated islands, which will save the high fuel transportation cost. Thus, minimizing the staff level for operating and maintaining a microreactor is desirable. The objective of the study is to design a self-regulated Molten Metal fueled microReactor core (MMR) and to demonstrate the self-regulating capability of the MMR core. The control of the reactor is solely relying on reactivity feedbacks from fuel temperature perturbation. Molten UMn (liquid form at the temperature over 720°C) was utilized as the fuel material in MMR due to the larger thermal expansion coefficient compared to the conventional solid fuel. The MMR core has a fast neutron spectrum, which corresponds to a small burnup reactivity swing. The core design parameters were selected based on DAKOTA, REBUS, and ANLHTP calculations. The MMR is designed to run for 10 years at a power level of 15 MWth. Furthermore, no refueling is needed during the reactor lifetime. The system dynamic analyses were performed, and it was found that the reactor can be self-regulating within a temperature range of 800 ± 80°C for a loss of heat sink transient.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A chemistry-informed hybrid machine learning approach to predict metal adsorption onto mineral surfaces

Historically, surface complexation model (SCM) constants and distribution coefficients (K d ) have been employed to quantify mineral-based retardation effects controlling the fate of metals in subsurface geologic systems. Our recent SCM development workflow, based on the Lawrence Livermore National Laboratory Surface Complexation/Ion Exchange (L-SCIE) database, illustrated a community FAIR data approach to SCM development by predicting uranium(VI)-quartz adsorption for a large number of literature-mined data. Here, we present an alternative hybrid machine learning (ML) approach that shows promise in achieving equivalent high-quality predictions compared to traditional surface complexation models. At its core, the hybrid random forest (RF) ML approach is motivated by the proliferation of incongruent SCMs in the literature that limit their applicability in reactive transport models. Our hybrid ML approach implements PHREEQC-based aqueous speciation calculations; values from these simulations are automatically used as input features for a random forest (RF) algorithm to quantify adsorption and avoid SCM modeling constraints entirely. Named the LLNL Speciation Updated Random Forest (L-SURF) model, this hybrid approach is shown to have applicability to U(VI) sorption cases driven by both ion-exchange and surface complexation, as is shown for quartz and montmorillonite cases. The approach can be applied to reactive transport modeling and may provide an alternative to the costly development of self-consistent SCM reaction databases.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Empirical validation and comparison of methodologies to simulate micro and macro-encapsulated PCMs in the building envelope

Thermal Energy Storage (TES) has the potential to shift peak electricity demand. Passive TES is usually implemented in building envelope as micro and macro encapsulated phase change materials (PCM) to shift electric energy demand and therefore requires careful heat transfer analysis. Whole building energy modelling with simplified heat transfer analysis has become extremely important for designers, architects, engineers, and researchers to predict energy performance of buildings. It is important to validate PCM modelling algorithms used in building energy programs to quantify their error and prove their capacity to model different PCM encapsulation types. This study uses data from a microencapsulated PCM and two macroencapsulated PCMs (Bio based PCM and hydrate salts) tested in full-scale using the Advanced Multiscale Building Energy Research (AMBER) Lab located at the Colorado School of Mines and is used to validate a numerical algorithm written in MATLAB language. To approximate the heat transfer through a wall assembly with macroencapsulated PCM pouches, several modelling techniques that can reduce 3D heat transfer characteristics to 1D are explored in this research. A parallel path heat transfer modelling approach is found to give the closest agreement with the experimental data for the pouched PCMs in building envelope applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗