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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 sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Exploring the NΛ–NΣ coupled system with high precision correlation techniques at the LHC

The interaction of Λ and Σ hyperons (Y) with nucleons (N) is strongly influenced by the coupled-channel dynamics. Due to the small mass difference of the NΛ and NΣ systems, the sizable coupling strength of the NΣ↔NΛ processes constitutes a crucial element in the determination of the NΛ interaction. In this letter we present the most precise measurements on the interaction of pΛ pairs, from zero relative momentum up to the opening of the NΣ channel. The correlation function in the relative momentum space for pΛ ⊕$\bar{p}$$\bar{Λ}$ pairs measured in high-multiplicity triggered pp collisions at $\sqrt{s}$=13 TeV at the LHC is reported. The opening of the inelastic NΣ channels is visible in the extracted correlation function as a cusp-like structure occurring at relative momentum k*=289 MeV/c. This represents the first direct experimental observation of the NΣ↔NΛ coupled channel in the pΛ system. The correlation function is compared with recent chiral effective field theory calculations, based on different strengths of the NΣ↔NΛ transition potential. A weaker coupling, as possibly supported by the present measurement, would require a more repulsive three-body NNΛ interaction for a proper description of the Λ in-medium properties, which has implications on the nuclear equation of state and for the presence of hyperons inside neutron stars.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Characterization of hot-pressed von Alpen type NASICON ceramic electrolytes

The Na-ion conducting solid electrolyte NASICON is a promising solid state electrolyte (SSE) for use in Na based electrochemical systems. The effects of particle morphology and synthesis of von Alpen type NASICON via hot-pressing were investigated. Spray dried particles were shown to improve mechanical and electrochemical properties. X-ray diffraction, scanning electron microscopy, impulse excitation measurements, Vickers hardness, and impedance spectroscopy were used to correlate relationships between phase purity, microstructure, mechanical properties, and electrochemical properties. Scanning electron microscopy showed the presence of a glass phase as between 19.08% and 28.23% area percentage and a ZrO 2 phase between 0.46% and 3.51% area percentage in the hot-pressed samples. Impulse excitation showed elastic modulus varying from 83.65 to 97.65 GPa. The first values of Poisson's ratio and shear modulus of NASICON are reported as between 0.23 and 0.26 and 33.87 to 38.79 GPa, respectively. Vickers hardness and fracture toughness measurements showed Vickers hardness ranging from 4.30 to 4.68 GPa and fracture toughness ranging from 1.05 to 1.09 MPa m ½ . Impedance spectroscopy showed grain conductivities ranging from 1.023 to 1.287 mS/cm, with grain boundary resistance percentages between 73.22 and 47.5%. Total conductivities ranged from 0.292 to 0.596 mS/cm, with 0.596 mS/cm being achieved at room temperature for the spray dried powders with lower grain boundary resistance percentages.

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

A Trapping-Micro-LC-FAIMS/dCV-MS Strategy for Ultrasensitive and Robust Targeted Quantification of Protein Drugs and Biomarkers

The sensitivity of LC-MS in quantifying target proteins in plasma/tissues is significantly hindered by co-eluted matrix interferences. While antibody-based immuno-enrichment effectively reduces interferences, developing and optimizing antibodies are often time-consuming and costly. Here, in this study, by leveraging the orthogonal separation capability of Field Asymmetric Ion Mobility Spectrometry (FAIMS), we developed a FAIMS/differential-compensation-voltage (FAIMS/dCV) method for antibody-free, robust, and ultra-sensitive quantification of target proteins directly from plasma/tissue digests. By comparing the intensity-CV profiles of the target vs. co-eluted endogenous interferences, the FAIMS/dCV approach identifies the optimal CV for quantification of each target protein, thus maximizing the signal-to-noise ratio (S/N). Compared to quantification without FAIMS, this technique dramatically reduces endogenous interferences, showing a median improvement of the S/N by 14.8-fold for the quantification of 17 representative protein drugs and biomarkers in plasma or tissues and a 5.2-fold median increase in S/N over conventional FAIMS approach, which uses the peak CV of each target. We also discovered that the established CV parameters remain consistent over months and are matrix-independent, affirming the robustness of the developed FAIMS/dCV method and the transferability of the method across matrices. The developed method was successfully demonstrated in three applications: the quantification of monoclonal antibodies with sub-ng/mL LOQ in plasma, an investigation of the time courses of evolocumab and its target PCSK9 in a preclinical setting, and a clinical investigation of low abundance obesity-related biomarkers. This innovative and easy-to-use method has extensive potential in clinical and pharmaceutical research, particularly where sensitive and high-throughput quantification of protein drugs and biomarkers is required.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

New Insights into the Bulk and Surface Defect Structures of Ceria Nanocrystals from Neutron Scattering Study

Neutron diffraction and pair distribution function studies coupled with Raman spectroscopy have successfully unraveled the detailed oxygen defect structures of ceria nanocubes and nanorods. Two types of defect sites are revealed for the ceria nanocrystals: surface and bulk defects. It is proposed that the surface oxygen defects in both types of CeO 2 nanocrystals are predominantly the partially reduced Ce 3 O 5+x , with the bulk defect structures dominated by interstitial Frenkel-type oxygen vacancies. Ceria nanorods possess much higher concentration of surface oxygen defects relative to the nanocubes, albeit with only slightly higher concentration of bulk Frenkel-type oxygen vacancies. Upon annealing the nanorod sample at 600 °C under vacuum (~10 –4 to 10 –5 mbar), a partially reduced ceria phase with long-range oxygen vacancy ordering (Ce 3 O 5+x ) has been observed experimentally for the first time. This intriguing observation that surface defect phases can take on ordered defect sublattices under certain conditions is of great value in understanding the temperature-dependent catalytic performance of ceria nanocrystals. Furthermore, a drastic decrease of the surface vacancies in the ceria nanocrystals is observed upon exposure to SO 2 , especially for the nanorods, a likely origin for the sulfur poisoning effect on ceria-based materials. This study suggests that tailoring surface morphology is a promising strategy to control defect properties of ceria nanomaterials. It also provides fundamental insights to stabilize surface oxygen defects in CeO 2 nanocrystals to achieve high redox performance under corrosive environments such as under SO 2 /SO x exposure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning

Metal halide perovskite (MHP) derivatives, a promising class of optoelectronic materials, have been synthesized with a range of dimensionalities that govern their optoelectronic properties and determine their applications. We demonstrate a data-driven approach combining active learning and high-throughput experimentation to discover, control, and understand the formation of phases with different dimensionalities in the morpholinium (morph) lead iodide system. Using a robot-assisted workflow, we synthesized and characterized two novel MHP derivatives that have distinct optical properties: a one-dimensional (1D) morphPbI 3 phase ([C 4 H 10 NO][PbI 3 ]) and a two-dimensional (2D) (morph) 2 PbI 4 phase ([C 4 H 10 NO] 2 [PbI 4 ]). To efficiently acquire the data needed to construct a machine learning (ML) model of the reaction conditions where the 1D and 2D phases are formed, data acquisition was guided by a diverse-mini-batch-sampling active learning algorithm, using prediction confidence as a stopping criterion. Querying the ML model uncovered the reaction parameters that have the most significant effects on dimensionality control. Based on these insights, we discuss possible reaction schemes that may selectively promote the formation of morph-Pb-I phases with different dimensionalities. The data-driven approach presented here, including the use of additives to manipulate dimensionality, will be valuable for controlling the crystallization of a range of materials over large reaction-composition spaces.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Magnetosynthesis Effect on the Structure and Ground State of Cu 2+ -Based Antiferromagnets

Synthetic variables can have an outsized influence on the crystal structure and magnetic properties of a material, particularly those of quantum materials. In this work, we investigate the impact of synthesis under a magnetic field (magnetosynthesis) on the crystal structure and magnetic properties of several Cu 2+ (S = 1/2)-based materials with antiferromagnetic interactions and varying levels of magnetic frustration, from simple antiferromagnets to a quantum spin liquid. Here, we develop methods to apply small (0.09–0.37 T) magnetic fields during low-temperature hydrothermal, evaporative, and rehydration syntheses of the simple antiferromagnet CuCl 2 ·2H 2 O, the canted antiferromagnet (Cu,Zn) 3 Cl 4 (OH) 2 ·2H 2 O, the frustrated and canted antiferromagnet atacamite Cu 2 (OH) 3 Cl, and the highly frustrated quantum spin liquid herbertsmithite Cu 3 Zn(OH) 6 Cl 2 . We report the first single-crystal X-ray structural determination of the Cu 3 Cl 4 (OH) 2 ·2H 2 O structure type and probe the stability of this phase both experimentally and computationally. Atacamite Cu 2 (OH) 3 Cl synthesized under a 0.19 T field experiences a 0.15 K (∼3%) decrease in its Néel transition temperature. This result suggests that magnetosynthesis with small applied fields may have a very subtle influence upon the magnetic properties of moderately magnetically frustrated 3 d materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of Porous Crystalline Materials for Selective Binding of O 2 from Air

Porous materials that take advantage of different chemisorptive behaviors of O 2 and N 2 could be an effective alternative to approaches based on physisorption for this important separation. Recently, the tetra-nuclear cobalt complex [(Co(III) 2 (bpbp)O 2 ) 2 bdc](PF 6 ) 4 (CSD code: GAMVIB; bpbp – = 2,6-bis(N,N-bis(2-pyridylmethyl)aminomethyl)-4-tert-butylphenolato; bdc 2– = 1,4-benzenedicarboxylato) was shown to have potential for O 2 /N 2 separations based on this concept. This observation raises the question of what other known materials have similar properties. Here, we combine structure screening with a high-throughput periodic density functional theory (DFT) workflow to investigate O 2 and N 2 adsorption in materials from validated crystal structure databases (e.g., CoRE-MOF database and CSD database). These calculations identify multiple materials that have similar di-Co clusters to GAMVIB that are predicted to selectively bind O 2 over N 2 , and suggest design rules that can be used to tune the O 2 and N 2 affinities in materials of this kind.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine Learning Automated Analysis of Enormous Synchrotron X-ray Diffraction Datasets

X-ray diffraction (XRD) data analysis can be a time-consuming and laborious task. Deep neural network (DNN) based models trained with synthetic XRD patterns have been proven to be a highly efficient, accurate, and automated method for analyzing common XRD data collected from solid samples in ambient environments. However, it remains unclear whether synthetic XRD-based models can be effective in solving micro(μ)-XRD mapping data for in situ experiments involving liquid phases, which always have lower quality and significant artifacts. In this study, we collected μ-XRD mapping data from a LaCl 3 -calcite hydrothermal fluid system and trained two categories of models to analyze the experimental XRD patterns. Here, the models trained solely with synthetic XRD patterns showed low accuracy (as low as 64%) when solving experimental μ-XRD mapping data. However, the accuracy of the DNN models significantly improved (90% or above) when we trained them with a data set containing both synthetic and a small number of labeled experimental μ-XRD patterns. This study highlights the importance of labeled experimental patterns in training DNN models to solve μ-XRD mapping data from in situ experiments involving liquid phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Effect of Surface Texture on Pinhole Formation in SiO x -Based Passivated Contacts for High-Performance Silicon Solar Cells

High-efficiency silicon solar cells rely on some form of passivating contact structure to reduce recombination losses at the crystalline silicon surface and losses at the metal/Si contact interface. One such structure is polycrystalline silicon (poly-Si) on oxide, where heavily doped poly-Si is deposited on a SiO x layer grown directly on the crystalline silicon (c-Si) wafer. Depending on the thickness of the SiO x layer, the charge carriers can cross this layer by tunneling (<2 nm SiO x thickness) or by direct conduction through disruptions in the SiOx, often referred to as pinholes, in thicker SiO x layers (>2 nm). In this work, we study structures with tunneling- or pinhole-like SiO x contacts grown on pyramidally textured c-Si wafers and expose variations in the SiOx layer properties related to surface morphology using electron-beam-induced current (EBIC) imaging. Using EBIC, we identify and mark regions with potential pinholes in the SiO x layer. We further perform high-resolution transmission electron microscopy on the same areas, thus allowing us to directly correlate locally enhanced carrier collection with variations in the structure of the SiO x layer. Our results show that the pinholes in the SiO x layer preferentially form in different locations based on the annealing conditions used to form the device. With greater understanding of these processes and by controlling the surface texture geometry, there is potential to control the size and spatial distribution of oxide disruptions in silicon solar cells with poly-Si on oxide-type contacts; usually, this is a random phenomenon on polished or planar surfaces. Such control will enable us to consistently produce high-efficiency devices with low recombination currents and low junction resistances using this contact structure.

14 SOLAR ENERGY↗
DOE OSTI2025

Elucidating the Competitive Hydrodeoxygenation of Lignin-Derived Oxygenates over Bulk MoO 3 Catalyst through Kinetic Analysis

Ambient pressure hydrodeoxygenation (HDO) of lignin-derived oxygenates over molybdenum oxide-based catalysts is an effective strategy to produce chemicals that can be directly integrated into our existing petrochemical infrastructure. Complexities pertaining to the simultaneous kinetic and mechanistic analysis of HDO have limited research endeavors to single-compound systems. Although valuable insight into the catalytic reaction has been gained through this approach, it provides limited understanding of the competitive adsorption behavior manifest in a realistic multioxygenate reaction environment. To address this shortcoming, simultaneous gas-phase acetone and anisole HDO was performed at 330 °C and ≤1 bar H 2 partial pressure over bulk MoO 3 . Propene, propane, and benzene were the HDO products formed, showing a similar product distribution to the single-compound system. Selectivity to propene and propane was ∼14 times higher than benzene, even at three times higher anisole partial pressure compared to acetone. A negative anisole HDO (−0.97 ± 0.22) rate order with varying acetone partial pressure suggested a strong inhibition effect on anisole HDO by acetone. Conversely, with increasing anisole partial pressure, a rate order of −0.07 ± 0.12 was observed for acetone HDO, implying a weak impact of anisole cofeed on acetone HDO. A kinetic-driven approach was taken to estimate the relative adsorption constants of the oxygenates. Acetone exhibited a 6.4 times higher adsorption propensity on the HDO active site than anisole. Relative adsorption constants for phenolics increased with increasing basicity of the oxygenate but decreased for aliphatic molecules, suggesting a volcano-shaped relationship. The results suggest the possibility of an optimal electron density around the molecule’s oxygen atom to maximize the molecule’s adsorption strength.

acid sites↗
DOE OSTI2024

Optimizing Nonaqueous Sodium–Polysulfide Redox-Flow Batteries: The Role of Solvation Effects with Glyme Solvents

Nonaqueous redox-flow batteries (NARFBs) that use economical alkali metals and the corresponding metal polysulfides are highly attractive for grid-scale energy storage. Although sodium–sulfur systems have been recognized as promising candidates and have been the focus of many studies due to their high earth abundance and energy density, an understanding of the role of the solvation chemistry of commonly used glyme solvents is missing. Herein, we report a systematic investigation into the solvation effects of glyme-based Na-S electrolytes through comprehensive physiochemical experiments and Density Functional Theory (DFT) simulations. Our findings revealed, on one hand, that an optimal coordination strength between glymes and Na + could maintain a relatively smooth Na + diffusion. On the other hand, glyme solvents with extended chain lengths shift the reduction potential of S 8 2– negatively to elevate the formation barrier of undesirable short-chain polysulfides (S n 2– , n ≤ 4) that have high membrane permeability. This solvation phenomenon not only mitigates capacity fading but also extends the operational longevity of the Na-S NARFBs. In conclusion, the results underscore the critical roles of balanced solvent–cation interactions and controlled redox potentials in improving the stability and efficiency of Na-S NARFB systems, marking a significant advancement in the development of sustainable energy storage solutions.

25 ENERGY STORAGE↗
DOE OSTI2024

Integrated CO 2 Capture and Conversion by a Robust Cu(I)-Based Metal–Organic Framework

Metal-organic frameworks (MOFs) have shown promise in both capturing CO 2 under flue gas conditions and converting it into valuable chemicals. However, the development of a single MOF capable of capturing and selectively converting CO 2 has remained elusive due to lack of harmonious combination of selectivity, water stability, and reactivity. For example, Cu(I)-based MOFs are particularly effective for CO 2 conversion, but they do not typically exhibit selective CO 2 adsorption and often suffer from instability in the presence of air and moisture. Developing a Cu(I) MOF that is stable under flue gas conditions while also capturing CO 2 from this mixture would likely afford a material capable of selectively capturing and converting CO 2 in an integrated pathway, which would represent a significant advancement in this field. In this study, we introduce NU-2100, an ultramicroporous Cu(I) MOF, which exhibits both selectivity for CO 2 adsorption and great stability even in the presence of moisture and air. Comprehensive evaluations involving exposure to air, oxygen, water, and varying temperatures reveal that NU-2100 demonstrates superior stability compared to other known Cu(I) MOFs. Utilizing adsorption isotherms and thermogravimetric analysis coupled with gas chromatography-mass spectrometry (TGA-GCMS), we establish the high selectivity of NU-2100 for CO 2 over common flue gas components, including water, nitrogen, and oxygen. Additionally, under mild reaction conditions (50 °C and H 2 :CO 2 = 3:1), NU-2100 exhibits CO 2 capture and catalytic conversion to formic acid with 100% selectivity. Furthermore, this study marks an important step towards the design of next-generation MOFs capable of integrated carbon capture and utilization (iCCU) under industrial conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Efficient and assured reinforcement learning-based building HVAC control with heterogeneous expert-guided training

Abstract Building heating, ventilation, and air conditioning (HVAC) systems account for nearly half of building energy consumption and $$20\%$$ of total energy consumption in the US. Their operation is also crucial for ensuring the physical and mental health of building occupants. Compared with traditional model-based HVAC control methods, the recent model-free deep reinforcement learning (DRL) based methods have shown good performance while do not require the development of detailed and costly physical models. However, these model-free DRL approaches often suffer from long training time to reach a good performance, which is a major obstacle for their practical deployment. In this work, we present a systematic approach to accelerate online reinforcement learning for HVAC control by taking full advantage of the knowledge from domain experts in various forms . Specifically, the algorithm stages include learning expert functions from existing abstract physical models and from historical data via offline reinforcement learning, integrating the expert functions with rule-based guidelines, conducting training guided by the integrated expert function and performing policy initialization from distilled expert function. Moreover, to ensure that the learned DRL-based HVAC controller can effectively keep room temperature within the comfortable range for occupants, we design a runtime shielding framework to reduce the temperature violation rate and incorporate the learned controller into it. Experimental results demonstrate up to 8.8 X speedup in DRL training from our approach over previous methods, with low temperature violation rate.

Xu, Shichao↗
DOE OSTI2023

Steam caps in geothermal reservoirs can be monitored using seismic noise interferometry

Harvesting geothermal energy often leads to a pressure drop in reservoirs, decreasing their profitability and promoting the formation of steam caps. While steam caps are valuable energy resources, they also alter the reservoir thermodynamics. Accurately measuring the steam fraction in reservoirs is essential for both operational and economic perspectives. However, steam content estimations are very limited both in space and time since current methods rely on direct measurements within production wells. Besides, these estimations normally present large uncertainties. Here, we present a pioneering method for indirectly sampling the steam content in the subsurface using the ever-present seismic background noise. We observe a consistent annual velocity drop in the Hengill geothermal field (Iceland) and establish a correlation between the velocity drop and steam buildup using in-situ borehole data. This application opens new avenues to track the evolution of any gas reservoir in the crust with a surface-based and cost-effective method.

58 GEOSCIENCES↗
DOE OSTI2026

Solid-state thermometry via ionic–electronic coupling in two-dimensional heterostructures

The coupling of ionic and electronic transport in solid-state systems offers new opportunities for realizing compact, energy-efficient sensing technologies, yet practical implementations remain limited. In this article, we introduce a two-dimensional iontronic platform based on field-effect transistors that integrate monolayer MoS 2 channels with van der Waals bimetallic thiophosphates ( AB P 2 X 6 , A = Li, Cu, Ag and so on; B = In, Sc and so on; and X = S and Se) as ionic gate dielectrics to realize on-chip thermometry. Specifically, we exploit thermally activated ion migration within the gate dielectric leading to conductance modulation in the MoS 2 channel for temperature sensing. We achieve ~1–2 °C resolution, fast electronic readout and subpicojoule energy consumption in an ultracompact footprint (~1 µm 2 ). Beyond thermometry, these results establish bimetallic thiophosphates as a versatile platform for solid-state iontronics and broaden the functional design space of van der Waals heterostructures for sensing, actuation and adaptive electronics.

42 ENGINEERING↗