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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 217 records · Page 12

Sub-Ambient Performance of Potassium Sarcosinate for Direct Air Capture Applications: CO 2 Flux and Viscosity Measurements

Absorption based direct air capture (DAC) technologies have garnered significant interest in recent years due to their scalability, competitive regeneration energy requirements, and low susceptibility to degradation. One of the key advantages of DAC lies in its flexible siting options and the potential to utilize low-value land. However, most of the research in this field has been focused on ambient climate zones (T > 20 °C), overlooking sub-ambient (–30 °C < T < 20 °C) regions, which comprise approximately 70 % of the Earth’s surface. To fully realize the potential of DAC, it is essential to understand how DAC solvents perform in these sub-ambient conditions before any large-scale deployment can be considered. Among DAC solvents of interest, potassium sarcosinate (K-SAR) has emerged as a promising candidate due to its high CO 2 capacity, fast uptake kinetics, compatibility with contactor packing materials, low volatility, good thermal and oxidative stability, and competitive regeneration energy requirements compared to current industry standards. This paper characterizes the CO 2 flux and viscosity of K-SAR at sub-ambient conditions and explores the potential of using ethylene glycol and triethylene glycol as additives to prevent solvent freezing in DAC applications. For 1 M K-SAR, the CO 2 flux ranges between 1.3 × 10 -5 and 8.0 × 10 -5 mol m –2 s –1 across a temperature range of –5 °C to 45 °C. Ethylene glycol is shown to effectively suppress the freezing point of K-SAR below –30 °C with volumetric loadings of the additive as low as 0.1. Here, a reaction model was developed to predict the CO 2 flux for 1 M K-SAR at different temperatures, demonstrating good agreement between experimental and theoretical fluxes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid characterization of MSW and RDF feedstocks for waste-to-energy process using LIBS and ML techniques

The heterogeneity in the composition of municipal solid wastes (MSW) poses significant challenges in the production of biofuel and bioproducts. This research aims to enhance the accuracy and efficiency of waste analysis and characterization by introducing a fast characterization approach for MSW-derived refuse-derived fuels (RDF) by combining Laser-Induced Breakdown Spectroscopy (LIBS) with advanced machine learning (ML) techniques. The approach combines data pre-processing of LIBS spectra of RDF, and the development of ML models trained on domain and theory-based spectral features for predicting process parameters. These models are adept at predicting key process parameters like High Heating Value (HHV), carbon content, and volatile matter. This approach can achieve an average RRMSE of 2.13% and R 2 of 0.98 or higher for all considered parameters on testing data. This work demonstrates significant potential for improving waste sorting, processing efficiency, and environmental compliance over traditional labor- and time-intensive laboratory waste analysis and characterization.

09 BIOMASS FUELS↗

Enhancement of Uranium Ionization Efficiencies Using Zn-MOF-74 Derived Nanoporous Ion Emitters for Thermal Ionization Mass Spectrometry

The recent introduction of nano-porous ion emitters (nano-PIEs) formed from metal organic frameworks (MOFs) has demonstrated the potential to enhance sensitivity for thermal ionization mass spectrometry (TIMS). Nano-PIEs take advantage of the parent MOF’s chemical and structural tunability to form scaffolds for ion emitters. A study by Barpaga et al. 2023 on MOF-74 as the parent material found that with high volatility metals in their framework uranium sample utilization efficiency (SUE) increases by up to nine-fold (e.g., Zn-MOF-74) compared to that of the analyte on a bare filament (~0.05%). Here, in this study, we investigate the performance of Zn-MOF-74 to maximize uranium efficiencies at the trace level (= 10 -12 g) by altering the parent MOF morphology and chemistry (i.e., MOF crystal sizes and thermal degradation) and optimizing its integration with TIMS (i.e., MOF mass on a filament and ramp conditions). We observed improvement in SUE up to 20 times (≤1.0%) that of a bare filament load when nano-PIEs derived from nanocrystals of Zn-MOF-74 were heated under a specific current ramp condition. This demonstrates that rates of nano-PIE structural collapse during TIMS analysis and the subsequently formed nanomaterials (and their features) can be tuned to control analyte ionization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Double-Crucible Vertical Bridgman Technique for Stoichiometry-Controlled Chalcogenide Crystal Growth

Precise stoichiometry control in single-crystal growth is essential for both technological applications and fundamental research. However, conventional growth methods often face challenges such as non-stoichiometry, compositional gradients, and phase impurities, particularly in non-congruent melting systems. Even in congruent melting systems like Bi₂Se₃, deviations from the ideal stoichiometric composition can lead to significant property degradation, such as excessive bulk conductivity, which limits its topological applications. In this study, we introduce the double-crucible vertical Bridgman (DCVB) method, a novel approach that enhances stoichiometry control through the combined use of continuous source material feeding, traveling-solvent growth, and liquid encapsulation, which suppresses volatile element loss under high pressure. Using Bi₂Se₃ as a model system, we demonstrate that crystals grown via DCVB exhibit enhanced stoichiometric control, significantly reducing defect density and achieving much lower carrier concentrations compared to those produced by conventional Bridgman techniques. Moreover, the continuous feeding of source material enables the growth of large crystals. As a result, this approach presents a promising strategy for synthesizing high-quality, large-scale crystals, particularly for metal chalcogenides and pnictides that exhibit challenging non-congruent melting behaviors.

Crystal structure↗

Special Issue: National Laboratories’ Safety Successes, Challenges, Research, and Approaches

In today’s world, volatility, uncertainty, complexity, and ambiguity─collectively referred to as VUCA─is demonstrably greater than before. VUCA is a concept first documented in U.S. Army War College records in the late 1980s to describe challenging and rapidly changing environments. In the VUCA world in which we work, we aim to leverage our colleagues’ knowledge as we push the envelope further. And we must do it now. I urge you to explore these invited articles, as well as those in the larger ACS Chemical Health & Safety collection, and continue innovating.

materials↗

Sequential Infiltration Synthesis of Multinary Metal Oxides: The Role of Precursor Diffusion and Reactivity

Understanding volatile metal–organic precursor transport in polymer matrices during sequential infiltration synthesis (SIS) is critical to the design of hybrid materials of tailored composition and uniform structure. Here, we investigate the diffusion and reaction behavior of diethylzinc (DEZ) in poly(methyl methacrylate) (PMMA) matrices with variable indium and zinc incorporation. Unlike conventional SIS where precursors adduct or react directly with the polymer backbone, DEZ shows minimal interaction with PMMA. However, DEZ may interact strongly with In–OH or Zn–OH moieties that are previously incorporated into a PMMA thick film. Using spectroscopic ellipsometry, X-ray photoelectron spectroscopy depth profiling, and EDX line scans, we quantify Zn incorporation as a function of exposure time, polymer thickness, and previous infiltration steps. The Zn distribution evolves from surface-localized to deep within the ∼1 μm thick film with increasing DEZ exposures up to 30 min. A reaction-diffusion model incorporating a hindering factor to capture diffusivity decay due to product accumulation reproduces the Zn depth profile and yields physically meaningful parameters to guide future growth. Furthermore, this study provides a framework for interpreting metal–organic precursor infiltration behavior and highlights the utility of model-guided SIS process design.

diethylzinc↗

Introduction: Neuromorphic Materials

The explosive growth in data collection and the need to process it efficiently, as well as the desire to automate increasingly complex tasks in transportation, medical care, manufacturing, security and many other fields have motivated a growing interest in neuromorphic computing. Unlike the binary, transistorbased ON/OFF logic gates and separate logic and memory functionalities employed in digital computing, neuromorphic computing is inspired by animal brains that use interconnected synapses and neurons to perform processing, storage and transmission of information at the same location, while only consuming ~20 W or less of power. Motivated by the brain’s efficiency, adaptability, self-learning and resiliency qualities, neuromorphic computing can be broadly defined as an approach to processing and storing information using hardware and algorithms inspired by models of biological neural systems. Present research in neuromorphic computing encompasses approaches that vary significantly in their degree of neuro-inspiration, from systems that only incorporate features such as asynchronous, event-driven operation or use crossbar arrays of non-volatile memory (NVM) elements to accelerate deep neural networks (DNNs), to designs that embrace the extreme parallelism, sparsity, reconfigurability, adaptability, complexity and stochasticity observed in nervous systems. The term ‘neuromorphic’ computing is often credited to Carver Mead, who in the 1980s investigated Si-based analog electronics to replicate functions of the animal retina. Earlier important advances in this field include the work of Frank Rosenblatt, who proposed the concept of the perceptron, Bernard Widrow, who used this concept to build one of the first analog neural networks, the Adaline and many other researchers (see ref. 6 for an historical perspective on neuromorphic computing). With the recent increase in the use of artificial intelligence and large language models, and rising concerns over the associated energy costs, interest in neuromorphic hardware has expanded rapidly. According to some estimates, driven largely by the drastic growth in the training use of artificial intelligence (AI) models using the current computing architectures, the energy cost of computing is projected to reach the energy supply worldwide by 2045. Furthermore, while this is not a realistic outcome, it means that, if more efficient computing technologies are not developed -- soon -- the world will soon become one where demand for energy and market constraints limit the continued increase of societal access to AI and cloud services from data centers. Data centers used for training and use of these models consume hundreds of terawatt hours of electricity, already past 4% of the US electricity demand.

Circuits↗

Low-Temperature Processing of Pyrolysis Bio-Oil for Sustainable Biographite Production

Catalytic graphitization of pyrolysis bio-oil with iron (Fe) can produce an anode material for lithium-ion batteries (LIBs) at a moderate temperature. The key challenge to scaling up the process is foaming, which occurs due to the oxidation of Fe by the organic acids present in bio-oil. This study explored five different pathways to control foaming in bio-oil upon Fe addition, including (i) defoamers use, (ii) use of iron oxide (Fe2O3) as graphitization catalyst, (iii) pH adjustment of bio-oil, (iv) bio-oil coking (300-500 degrees C), and (v) low-temperature pretreatment of bio-oil (150-200 degrees C). The low-temperature pretreatment successfully avoided foaming by removing the volatile acids in bio-oil. The bio-oil was solidified and powdered for even mixing with the Fe catalyst. The biographite catalytically prepared at 1500 degrees C following this pathway demonstrated nearly theoretical specific gravimetric capacity (~370 mAh/g), high initial Coulombic efficiency (90.03%), and minimal capacity fading after 50 cycles in LIB half-cells. The low-temperature pretreatment pathway also addressed the viscosity, swelling, and aging issues associated with bio-oil processing and will make scale-up endeavors more attainable.

09 BIOMASS FUELS↗

Enhancing the Quantification of Critical Elements in WTE and Coal Ash via Alkaline Fusion: Superiority of Lithium Metaborate (LiBO 2 )

Ashes generated from coal combustion, as well as waste incineration, can be a potential source of critical elements necessary for the ongoing transition towards electrification and greener energy technologies. For the quantification of critical elements, traditional methods such as acid digestion are time-intensive and can fail to dissolve critical elements in refractory minerals. One potential solution is to adopt alkaline fusion for faster, total digestion. However, the role of flux choice and the subsequent digestion efficiency (DE) is unknown. Here, we report a systematic investigation on the feasibility of alkaline fusion with Lithium Metaborate (LiBO 2 ) and Lithium Tetraborate (Li 2 B 4 O 7 ) as fluxes for the digestion of two standard reference materials (BCR 176R and SRM 1633c). Our findings suggest that LiBO 2 yields higher DE values than Li 2 B 4 O 7 for several critical REEs and volatiles, such as Pb and Cd. Specifically, for REEs in SRM 1633c, the DE values with LiBO 2 are, on average, ~16 percent higher than those with Li 2 B 4 O 7 . Similarly, for Pb and Cd in BCR 176R, the DE values with LiBO 2 are ~20 percent higher than with Li 2 B 4 O 7 . These results suggest that LiBO 2 is a superior flux for rapid ash digestion.

01 COAL, LIGNITE, AND PEAT↗

Tethered balloon system and High-Resolution Mass Spectrometry Reveal Increased Organonitrates Aloft Compared to the Ground Level

Atmospheric particles play critical roles in climate. However, significant knowledge gaps remain regarding the vertically resolved organic molecular-level composition of atmospheric particles due to aloft sampling challenges. To address this, we use a tethered balloon system at the Southern Great Plains Observatory and high-resolution mass spectrometry to, respectively, collect and characterize organic molecular formulas (MF) in the ground level and aloft (up to 750 m) samples. We show that organic MF uniquely detected aloft were dominated by organonitrates (139 MF; 54% of all uniquely detected aloft MF). Organonitrates that were uniquely detected aloft featured elevated O/C ratios (0.73 ± 0.23) compared to aloft organonitrates that were commonly observed at the ground level (0.63 ± 0.22). Unique aloft organic molecular composition was positively associated with increased cloud coverage, increased aloft relative humidity (~40% increase compared to ground level), and decreased vertical wind variance. Furthermore, 29% of extremely low volatility organic compounds in the aloft sample were truly unique to the aloft sample compared to the ground level, emphasizing potential oligomer formation at higher altitudes. Overall, this study highlights the importance of considering vertically resolved organic molecular composition (particularly for organonitrates) and hypothesizes that aqueous phase transformations and vertical wind variance may be key variables affecting the molecular composition of aloft organic aerosol.

54 ENVIRONMENTAL SCIENCES↗

A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: A Case Study for California and Oklahoma

Undocumented Orphaned Wells (UOWs) are wells without an operator that have limited or no documentation with regulatory authorities. An estimated 310,000 to 800,000 UOWs exist in the United States (US), whose locations are largely unknown. These wells can potentially leak methane and other volatile organic compounds to the atmosphere, and contaminate groundwater. In this study, we developed a novel framework utilizing a state-of-the-art computer vision neural network model to identify the precise locations of potential UOWs. The U-Net model is trained to detect oil and gas well symbols in georeferenced historical topographic maps, and potential UOWs are identified as symbols that are further than 100 m from any documented well. A custom tool was developed to rapidly validate the potential UOW locations. We applied this framework to four counties in California and Oklahoma, leading to the discovery of 1301 potential UOWs across >40,000 km 2 . We confirmed the presence of 29 UOWs from satellite images and 15 UOWs from magnetic surveys in the field with a spatial accuracy on the order of 10 m. This framework can be scaled to identify potential UOWs across the US since the historical maps are available for the entire nation.

54 ENVIRONMENTAL SCIENCES↗

Life-Cycle Emissions and Human Health Implications of Multi-Input, Multi-Output Biorefineries

To meaningfully broaden the supply of fuels for the transportation sector, biofuel production must be scaled up and this requires a wider array of biomass feedstocks, including agricultural residues and organic waste. Rather than pursuing conversion of lignocellulosic biomass to fuels and anaerobic digestion of wastes as separate pathways, there are economic and environmental advantages associated with integrating these processes in a single facility. However, existing research rarely goes beyond carbon footprints in quantifying the effects of such a shift in bioenergy production. In addition to CO2, CH4, and N2O, this study explores the life-cycle air pollution (NH3, volatile organic compounds, NOx, SO2, and PM2.5), marine eutrophication, acidification, and local external cost implications of biorefineries capable of taking in crop residues, food waste, and manure to produce liquid fuel, electricity, and/or other options such as renewable natural gas (RNG), hydrogen, bioplastics, and protein-rich livestock feed. Relative to a single-input, single-output baseline, biorefineries integrated with organic waste codigestion to coproduce electricity or RNG can reduce life-cycle CO2-equivalent emissions by 84-149%, and the monetized external impacts across all scenarios range from $1.07/gallon to -$0.75/gallon ethanol.

Air pollution↗

Physicochemical and Molecular Insights into the Boundary Layer and Free Troposphere Aerosol Interactions over the Southern Great Plains

Ambient aerosols’ vertical profiles are critical for evaluating the role of aerosols in atmospheric chemistry and radiative transfer, but limited data on these profiles hinders our ability to fully assess their impact on the Earth's radiative balance. Here, in this study, we investigated the size-, time-, and altitude resolved composition of individual particles and bulk molecular composition of particle samples collected by an uncrewed aerial system–ArcticShark over the Southern Great Plains. Single particle microanalysis shows that, the free tropospheric (FT) samples are dominated (56-66%) by carbonaceous sulfate particles, while boundary layer (BL) samples are dominated (57-74%) by carbonaceous particles. Back trajectory simulations suggest that FT particles are likely influenced by long-range transport and have undergone aqueous-phase processing. Conversely, in-situ size distribution data shows evidence of particle growth in the upper BL and just below the FT. This observation may indicate vertical transport of particles from an elevated aerosol layer in the FT, possibly linked to a new particle formation event. This observation is further supported by high resolution molecular composition data, which reveals particle volatility increasing with increasing size, which aligns with the growth event. This study aids in fundamental understanding of the compositional and molecular specificity of vertically resolved organic aerosols to provide insights into particle size evolution for future atmospheric models.

ArcticShark↗

Surface Crust Formation Controls Evaporation Kinetics of Secondary Organic Aerosols

Gas-particle partitioning is critical for the evolution of secondary organic aerosols (SOA) in the atmosphere. SOA particles evaporate more slowly than expected at nearly size-independent rates, but the underlying mechanism remains controversial. Here, in this study, we apply kinetic multilayer modeling to simulate evaporation of α-pinene SOA, demonstrating that surface crust formation, emerging from accumulation of low-volatility compounds at the particle surface, leads to slow evaporation and reduced size dependence of the evaporation rate. While evaporation induced by decomposition of oligomers would naturally lead to size-independent evaporation rates, we observe and simulate nearly size-independent slow evaporation of polyethylene glycol mixture particles containing polymeric species that do not decompose, confirming the relevance of composition-dependent diffusivity for size-independent, slow evaporation. Slow evaporation of limonene SOA was also observed in environmental chamber experiments, and model simulations demonstrate strong surface crust formation with bulk diffusivity being depressed by up to 5 orders of magnitude compared to the inner bulk. We present experimental evidence using a surface-based mass spectrometry technique that shows that the particle surface becomes enriched in high molecular weight compounds upon evaporation of monomers. Our findings imply that viscous surface crusts may also limit the growth and chemical transformation of SOA particles, influencing their impacts on air quality and climate.

heterogeneous chemistry↗

Effect of Radical Initiators on Polypropylene Thermal Deconstruction

A new route for polypropylene (PP) deconstruction through radical pathways based on thermodynamic and kinetic considerations has been investigated. Radical polypropylene (PP) deconstruction, activated through small quantities of initiators, can enable the deconstruction of waste POs into unsaturated products. We found that stirring was detrimental to the β-scission extent because it accelerates radical termination reactions through mixing. The best results were achieved by using a semibatch process that included mechanical mixing during the temperature ramp, static heating of the polymer/initiator mixture at the final temperature, and volatile product removal with N 2 . Dicumyl peroxide and alkylated dicumene initiators produced similar liquid and solid products after a 30 min thermal treatment. Terminal alkenes were formed in the liquid products of reactions at 375 and 400 °C, with about 5% of the protons in the liquid product ascribed to terminal alkenes. Yields of liquid products increased with temperature, reaching 60% w/w at 400 °C; at the same time, yields of solid products decreased with temperature to 16% w/w at 400 °C. Although radical initiators decrease PP molecular weight during the temperature ramp, at 400 °C, initiators only marginally increased the liquid product fraction compared to control experiments. Finally, the terminal double bonds in the liquid product mixture (C8–C36) provide multiple pathways for upgrading to surfactants, plasticizers, lube oils, and other valuable products.

liquids↗

Formation of Fully Stoichiometric, Oxidation-State Pure Neptunium and Plutonium Dioxides from Molecular Precursors

Amidate-based ligands (N-(tert-butyl)isobutyramide, ITA) bind κ 2 to form homoleptic, 8-coordinate complexes with tetravalent 237 Np (Np(ITA) 4 , 1-Np) and 242 Pu (Pu(ITA) 4 , 1-Pu). These compounds complete an isostructural series from Th, U–Pu and allow for the direct comparison between many of the early actinides with stable tetravalent oxidation states by nuclear magnetic resonance (NMR) spectroscopy and single crystal X-ray diffraction (SCXRD). The molecular precursors are subjected to controlled thermolysis under mild conditions with the exclusion of exogenous air and moisture, facilitating the removal of the volatile organic ligands and ligand byproducts. The preformed metal–oxygen bond in the precursor, as well as the metal oxidation state, are maintained through the decomposition, forming fully stoichiometric, oxidation-state pure NpO 2 and PuO 2 . Powder X-ray diffraction (PXRD), scanning transmission electron microscopy (STEM), and energy dispersive X-ray spectroscopy (EDS) elemental mapping supported the evaluation of these high-purity materials. This chemistry is applicable to a wide range of metals, including actinides, with accessible tetravalent oxidation states, and provides a consistent route to analytical standards of importance to the field of nuclear nonproliferation, forensics, and fundamental studies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Delta/Lambda Chirality: From Enantiomers to Diastereomers in Heterometallic Complexes with Chelating Ligands

The Δ/Λ chirality observed in octahedral molecules with chelating ligands represents the major group of “chiral-at-metal” complexes. Upon shifting from mononuclear to polynuclear systems with multiple (≥2) chiral centers, not only enantiomers but also diastereomers should be considered. We present the first, to the best of our knowledge, diastereomeric pairs Δ,Δ,Δ/Λ,Λ,Λ (1) and Δ,Δ,Λ/ Λ,Λ,Δ (2) of the pentanuclear assembly [Mn II (ptac) 3 −Na- Co III (acac) 3 −Na-Mn II (ptac) 3 ] (ptac = 1,1,1-trifluoro-5,5-dimethyl- 2,4-hexanedionate; acac = acetylacetonate). Diastereomers 1 and 2 were isolated in pure form and found to exhibit distinctly different structural characteristics. Importantly, for compounds that are applied as single-source precursors for the quaternary oxide cathode material P2−Na 0.67 Mn 0.67 Co 0.33 O 2 , the diastereomers revealed different thermal behaviors in terms of volatility and thermal stability. Unambiguous assignment of the Mn and Co positions in both diastereomers has been confirmed by the synchrotron X-ray resonant diffraction technique. Oxidation states of metal ions have been verified by the synchrotron X-ray fluorescence spectroscopy. The diastereomerization between 1 and 2 is not taking place in the solid state (crystal-to-crystal), as well as in the gas phase. The transformation between two diastereomers was observed in the solutions of noncoordinating solvents and was related to the polarities of the solvents and diastereomeric molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Harnessing the Second-Order Metal−Insulator Transition for Neuromorphic Computing

Vanadium oxides are widely studied phase change materials for brain-inspired computing architectures. Systems like VO 2 and V 2 O 3 exhibit first-order metal−insulator transitions (MITs) with hysteresis and percolative switching, increasing stochasticity and device variability. Here, we focus on the less explored Magnéli phase V 4 O 7 , which undergoes a continuous, non-hysteretic, second-order MIT. This surprisingly enables highly reproducible volatile resistive switching in spiking-neuron-type devices. We synthesize V 4 O 7 films, characterize their structural and transport properties, and demonstrate voltage and current-driven threshold switching with electrothermal feedback. In a Pearson–Anson oscillator, V 4 O 7 devices produce stable, tunable spiking across 20–200 kHz, with consistent operation among multiple devices. We introduce a numerical analog leaky-integrate-and-fire (aLIF) model that captures waveform shapes and their dependence on load resistance, temperature, and voltage. Furthermore, these findings suggest that second-order MIT materials like V 4 O 7 are promising for deterministic, scalable spiking neuron arrays for neuromorphic computing.

V4O7↗