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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Sagittarius stream in Gaia Early Data Release 3 and the origin of the bifurcations

The Sagittarius dwarf spheroidal (Sgr) is a dissolving galaxy being tidally disrupted by the Milky Way (MW). Its stellar stream still poses serious modelling challenges, which hinders our ability to use it effectively as a prospective probe of the MW gravitational potential at large radii. Our goal is to construct the largest and most stringent sample of stars in the stream with which we can advance our understanding of the Sgr-MW interaction, focusing on the characterization of the bifurcations. We improved on previous methods based on the use of the wavelet transform to systematically search for the kinematic signature of the Sgr stream throughout the whole sky in the Gaia data. We then refined our selection via the use of a clustering algorithm on the statistical properties of the colour-magnitude diagrams. Our final sample contains more than 700 000 candidate stars and is three times larger than previous Gaia samples. With it, we have been able to detect the bifurcation of the stream in both the northern and southern hemispheres, which requires four branches (two bright and two faint) to fully describe the system. We present the detailed proper motion distribution of the trailing arm as a function of the angular coordinate along the stream, showing, for the first time, the presence of a sharp edge (on the side of the small proper motions) beyond which there are no Sgr stars. We also characterize the correlation between kinematics and distance. Finally, the chemical analysis of our sample shows that the faint branch of the bifurcation is more metal poor than the bright. We provide analytical descriptions for the proper motion trends as well as for the sky distribution of the four branches of the stream. Based on our analysis, we interpret the bifurcations as a misaligned overlap of the material stripped at the antepenultimate pericentre (faint branches) with the stars ejected at the penultimate pericentre (bright branch), given that Sgr just went through its perigalacticon. The source of this misalignment is still unknown, but we argue that models with some internal rotation in the progenitor – at least during the time of stripping of the stars that are now in the faint branches – are worth exploring.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Vacuum-ultraviolet absorption cross-sections of functionalized four-carbon species

Absorption cross-sections were measured in the vacuum ultraviolet from 5.17 – 9.92 eV using differential absorption spectroscopy for 33 four-carbon species: n-butane, trans-2-butene, cis-2-butene, butanal, butyric acid, ethyloxirane, trans-2,3-dimethyloxirane, cis-2,3-dimethyloxirane, 2-methyloxetane, 2,2'-bioxirane, vinyl oxirane, 3,4-epoxybutan-2-one, diacetyl, diethyl ether, ethyl vinyl ether, vinyl acetate, acetic anhydride, 1-butanol, 3-buten-1-ol, 1–hydroxy-butan-2-one, 1–hydroxy-butan-3-one, 2,3-epoxybutan-1-ol, 3,4-epoxybutan-1-ol, 2-oxetanemethanol, butanone, methyl vinyl ketone, 4H-1,3-dioxine, allyl formate, 2-oxobutanal, 4-hydroxybutanal, 2-methyloxetan-3-one, cis–but-2-en-1-ol, and trans-2–but-enal. Uncertainties were quantified in all cases by accounting for errors in gas-phase concentration, experimental repeatability, and signal-to-noise ratio as a function of photon energy. With the exception of 2-oxobutanal, which is reported with an uncertainty of 10%, convolving the sources of error using the root-sum-square method led to an upper limit of 5% uncertainty above the detection limit, which is largely attributable to chemical purity. Here, the primary objective of the present work is to provide absolute cross-sections along with quantified uncertainty limits. The majority of the absorption spectra, which reflect electronic transitions such as σ → σ* and n → σ*, are reported for the first time and provide insight into fundamental chemical physics, such as vibrational band structure and Rydberg transitions. The quantitative spectra in the present work facilitates the discovery of chemical intermediates that support improvement in the accuracy of computational models for low-temperature combustion and atmospheric chemistry.

biofuels↗
DOE OSTI2023

A sensitive high repetition rate arrival time monitor for X-ray free electron lasers

X-ray free-electron laser sources enable time-resolved X-ray studies with unmatched temporal resolution. To fully exploit ultrashort X-ray pulses, timing tools are essential. However, new high repetition rate X-ray facilities present challenges for currently used timing tool schemes. Here we address this issue by demonstrating a sensitive timing tool scheme to enhance experimental time resolution in pump-probe experiments at very high pulse repetition rates. Our method employs a self-referenced detection scheme using a time-sheared chirped optical pulse traversing an X-ray stimulated diamond plate. By formulating an effective medium theory, we confirm subtle refractive index changes, induced by sub-milli-Joule intense X-ray pulses, that are measured in our experiment. The system utilizes a Common-Path-Interferometer to detect X-ray-induced phase shifts of the optical probe pulse transmitted through the diamond sample. Owing to the thermal stability of diamond, our approach is well-suited for MHz pulse repetition rates in superconducting linear accelerator-based free-electron lasers.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Geometry-Driven Detection, Tracking and Visual Analysis of Viscous and Gravitational Fingers

Viscous and gravitational flow instabilities cause a displacement front to break up into finger-like fluids. The detection and evolutionary analysis of these fingering instabilities are critical in multiple scientific disciplines such as fluid mechanics and hydrogeology. However, previous detection methods of the viscous and gravitational fingers are based on density thresholding, which provides limited geometric information of the fingers. The geometric structures of fingers and their evolution are important yet little studied in the literature. In this work, we explore the geometric detection and evolution of the fingers in detail to elucidate the dynamics of the instability. Additionally, we propose a ridge voxel detection method to guide the extraction of finger cores from three-dimensional (3D) scalar fields. After skeletonizing finger cores into skeletons, we design a spanning tree based approach to capture how fingers branch spatially from the finger skeletons. Finally, we devise a novel geometric-glyph augmented tracking graph to study how the fingers and their branches grow, merge, and split over time. Feedback from earth scientists demonstrates the usefulness of our approach to performing spatio-temporal geometric analyses of fingers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Structural Changes in Metal Chalcogenide Nanoclusters Associated with Single Heteroatom Incorporation

Atomically precise nanoclusters (NCs) are promising building blocks for designing materials and interfaces with unique properties. By incorporating heteroatoms into the core, the electronic and magnetic properties of NCs can be precisely tuned. To accurately predict these properties, density functional theory (DFT) is often employed, making the rigorous benchmarking of DFT results particularly important. In this study, we present a benchmarking approach based on metal chalcogenide NCs as a model system. We synthesized a series of bimetallic, iron-cobalt chalcogenide NCs [Co 6-x Fe x S 8 (PEt 3 ) 6 ] + (x = 0-6) (PEt = triethyl phosphine) and investigated the effect of heteroatoms in the octahedral metal chalcogenide core on their size and electronic properties. Using ion mobility-mass spectrometry (IM-MS), we observed a gradual increase in the collision cross section (CCS) with an increase in the number of Fe atoms in the core. DFT calculations combined with trajectory method CCS simulations successfully reproduced this trend, revealing that the increase in cluster size is primarily due to changes in metal-ligand bond lengths, while the electronic properties of the core remain largely unchanged. Moreover, this method allowed us to exclude certain multiplicity states of the NCs, as their CCS values were significantly different from those predicted for the lowest-energy structures. Here, this study demonstrates that gas-phase IM-MS is a powerful technique for detecting subtle size differences in atomically precise NCs, which are often challenging to observe using conventional NC characterization methods. Accurate CCS measurements are established as a benchmark for comparison with theoretical calculations. The excellent correspondence between experimental data and theoretical predictions establishes a robust foundation for investigating structural changes of transition metal NCs of interest to a broad range of applications.

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

Demonstration of no catalytical activity of Fe–N–C and Nb–N–C electrocatalysts toward nitrogen reduction using in–line quantification

Ammonia (NH 3 ) production via the electrochemical nitrogen reduction reaction (NRR) is a promising method for sustainable generation of this important chemical. Efforts are ongoing in finding an efficient, stable, and selective catalyst that will enable the reaction. However, progress is hindered in the field due to lack of reproducibility, most likely a consequence of reports of false-positive results due to improper measurement control and methods. In this study, we explore the NRR activity of a promising class of single atom catalysts, transition metal-nitrogen-carbon (M-N-C) electrocatalysts. Using a state-of-the-art in-line ammonia quantification methodology, with detection limit as low as 1 ppb for ammonia, we show that single atom Nb and Fe embedded in a stable carbon and nitrogen framework do not electrochemically reduce N 2 to NH 3 . Critically, this demonstrates that our experimental setup with in-line sequential injection analysis successfully excludes ammonia contamination from the gas supply and atmospheric sources, allowing for thorough and high-throughput examination of potential NRR catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Temperature-dependent changes in gas chromatographic separation metrics for trihexyl(tetradecyl)phosphonium-based ionic liquid stationary phases and comparison to conventional polysiloxane stationary phases

Here, to assess whether the trihexyl(tetradecyl)phosphonium chloride ([P 66614 + ][Cl - ]) ionic liquid (IL), employed as a gas chromatographic stationary phase, exhibits temperature-dependent phase transitions or structural heterogeneity, retention thermodynamics for probe molecules of varied chemical structure were investigated by gas chromatography (GC) over the temperature range of 25 to 64 °C using van’t Hoff analysis. All van’t Hoff plots for n-alkanes (C8–C12) and other probe analytes were linear, indicating the absence of detectable phase-transition behavior. The [P 66614 + ][Cl - ] IL was further compared with the [P 66614 + ] bis[(trifluoromethyl)sulfonyl]imide ([P 66614 + ][NTf 2 - ]) IL and commercial polysiloxane stationary phases in terms of temperature-dependent resolution behavior and chromatographic selectivity over the temperature range of 28–52 °C. The resolution factors of analytes in mixtures obtained using gas chromatography–mass spectrometry (GC–MS) and the summation of resolution values decreased smoothly with temperature on both IL stationary phases and on the dimethylphenylcyano-substituted polymeric stationary phase (OV-1701), whereas the poly(50% diphenyl/50% dimethyl siloxane) stationary phase (SPB-50) exhibited irregularities in its temperature-dependent summation of resolution profile, showing a distinct maximum in the temperature range of 34–40 °C. Selectivity values for the IL stationary phases were largely determined by the anion, with the [P 66614 + ][Cl - ] IL providing enhanced separation between polar and aromatic analytes, while the [P 66614 + ][NTf 2 - ] IL favored dispersive and π-π interactions that resulted in a reversal of elution order for some aliphatic–aromatic and alkyne-containing analyte pairs. Capillary columns prepared using different surface activation methods and coated with identical [P 66614 + ][Cl - ] IL stationary phase showed indistinguishable temperature-dependent trends in summation of resolution value and selectivity. An evaluation of analyte-specific selectivity provides insight into the characteristic separation behavior of the stationary phases and enables identification of analyte classes that are more efficiently separated on the [P 66614 + ]-based IL stationary phases compared to conventional stationary phase materials.

Chromatographic selectivity↗
DOE OSTI2020

Nucleation-controlled growth of superior lead-free perovskite Cs 3 Bi 2 I 9 single-crystals for high-performance X-ray detection

The organic-inorganic hybrid lead halide perovskites have emerged as a series of star materials for solar cells, lasers and detectors. However, the issues raised by the toxic lead element and marginal stability due to the volatile organic components have severely limited their potential applications. In this work, we develop a nucleation-controlled solution method to grow large size high-quality Cs 3 Bi 2 I 9 perovskite single crystals (PSCs). Using the technique, we harvest some centimeter-sized single crystals and achieved high device performance. We find that X-ray detectors based on PSCs exhibit high sensitivity of 1652.3 μC Gy air -1 cm -2 and very low detectable dose rate of 130 nGy air s -1 , both desired in medical diagnostics. In addition, its outstanding thermal stability inspires us to develop a high temperature X-ray detector with stable response at up to 100 °C. Furthermore, PSCs exhibit high X-ray imaging capability thanks to its negligible signal drifting and extremely high stability.

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

Meta-Study of Particulate Detection Losses on Radioactive Air Sample Filters

Several mathematical relationships between air sample filter mass loading and the correlated analytical self-absorption factor were developed using data from other published research in this meta-study. Gross-alpha and -beta applications are addressed for this research. As filter media becomes loaded with particulate matter, there is potential for measurement losses due to self-absorption by mass loading. Components contributing to absorption include particulate dust, radioactive particulates, and filter material. Standards indicate a correction factor should be used when the penetration of radioactive material into the collection media or self-absorption of radiation by the material collected would reduce the detection rate by more than 5%. Previously, losses due to self-absorption have been reported up to 100% over a range up to ~10 mg∙cm -2 mass loading. These absorption losses then can be used to determine a correction factor for sample results. For low mass loadings (e.g., ≤0.1 mg∙cm -2 ) corrections factors in the 0.85 - 1 range have been recommended and used, while at higher mass loadings nearer to 10 mg∙cm -2 correction factors closer to 0 (representing near 100% losses) are used. Based on data from published studies, the different methods for relating percent loss due to self-absorption to mass loading include linear, exponential, quadratic, and trinomial derived functions. Where applicable, both forced zero and non-forced zero results were evaluated. From the derived functions evaluated, the trinomial function provided the best fit. Once the sample filter mass loading is known, the trinomial function can be applied to estimate losses and the corresponding self-absorption factor. When applied to routine operating conditions for radiological facility stacks monitored at the Pacific Northwest National Laboratory for an average sample filter mass loading of 0.09 ± 0.12 (2σ) mg∙cm -2 (excluding negative values and outliers) and a range from 0 - 0.24 mg∙cm -2 , the estimated trinomial function nominal self-absorption losses are less than 5% at 0.09 mg∙cm -2 and less than 10% at 0.24 mg∙cm -2 . The trinomial function is one method that may be used to adjust the activity results of an air sample when the sample-specific mass loading is determined. The application of no correction factor when the ANSI/HPS N13.1-2021 guidance of a 5% threshold for loss is not reached with typical stack sample mass loadings may be reasonable in high-efficiency particulate air filtered systems. For simplicity, it would be conservative in assigning the self-absorption correction factor at the 5% threshold (i.e., 0.95) for general uses but in cases of heavy mass loading to calculate the factor.

air sampling↗
DOE OSTI2021

Gas-phase pyrolysis of trans 3-pentenenitrile: competition between direct and isomerization-mediated dissociation

The flash pyrolysis of trans 3-pentenenitrile (3-PN, CH 3 –$CH=CH$–CH 2 –CN) was studied by combining the results of VUV photoionization mass spectra with broadband microwave spectra recorded as a function of the temperature of the pyrolysis tube. The two separated functional groups (vinyl and nitrile) open up isomerization as an initial step in competition with unimolecular dissociation. Primary products were detected by keeping the 3-PN concentration low and limiting reaction times to the traversal time of the gas in the pyrolysis tube (~100 μs). The reaction is quenched and products are cooled by expansion into vacuum before interrogation over the 8–18 GHz region using chirped-pulse broadband methods. 118 nm VUV photoionization of the same reaction mixture provides a means of detecting all products with ionization potentials below 10.5 eV with minimal fragmentation. These results are combined with a detailed computational investigation of the C 5 H 7 N and related potential energy surfaces, leading to a consistent picture of the unimolecular decomposition of 3-PN. Loss of two H-atoms to form a 79 amu product is proven from its microwave transitions to contain trans-Z-2,4-pentadienenitrile, while no pyridine is observed. Methyl loss, HCN loss, and breaking the central C(2)–C(3) bond all occur following isomerization of the position of the double bond, thereby opening up low-energy pathways to these decomposition channels.

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

Fingerprints of hydrogen bonding in the terahertz dynamics of ethanol and water: An inelastic x-ray scattering study

Here, we used inelastic x-ray scattering methods to measure the terahertz spectrum of density fluctuations of ethanol in both liquid and solid phases. The results of a Bayesian inference-based lineshape analysis with a multiple excitation model and the comparison with a previous similar analysis on water indicate that the different structures induced by hydrogen bonds in ethanol and water have a profound influence on the respective dynamic responses, the latter being characterized by longer living and better resolved high-frequency acoustic excitations. In addition, we compare these findings with those obtained with an alternative approach based on the exponential expansion theory and ensuring sum rules fulfillment, demonstrating that the model’s choice directly impacts the number of spectral modes detected.

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

ClimateNet: an expert-labeled open dataset and deep learning architecture for enabling high-precision analyses of extreme weather

Abstract. Identifying, detecting, and localizing extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Pattern recognition tasks such as classification, object detection, and segmentation (i.e., pixel-level classification) have remained challenging problems in the weather and climate sciences. While there exist many empirical heuristics for detecting extreme events, the disparities between the output of these different methods even for a single event are large and often difficult to reconcile. Given the success of deep learning (DL) in tackling similar problems in computer vision, we advocate a DL-based approach. DL, however, works best in the context of supervised learning – when labeled datasets are readily available. Reliable labeled training data for extreme weather and climate events is scarce. We create “ClimateNet” – an open, community-sourced human-expert-labeled curated dataset that captures tropical cyclones (TCs) and atmospheric rivers (ARs) in high-resolution climate model output from a simulation of a recent historical period. We use the curated ClimateNet dataset to train a state-of-the-art DL model for pixel-level identification – i.e., segmentation – of TCs and ARs. We then apply the trained DL model to historical and climate change scenarios simulated by the Community Atmospheric Model (CAM5.1) and show that the DL model accurately segments the data into TCs, ARs, or “the background” at a pixel level. Further, we show how the segmentation results can be used to conduct spatially and temporally precise analytics by quantifying distributions of extreme precipitation conditioned on event types (TC or AR) at regional scales. The key contribution of this work is that it paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data using a curated expert-labeled dataset – ClimateNet. ClimateNet and the DL-based segmentation method provide several unique capabilities: (i) they can be used to calculate a variety of TC and AR statistics at a fine-grained level; (ii) they can be applied to different climate scenarios and different datasets without tuning as they do not rely on threshold conditions; and (iii) the proposed DL method is suitable for rapidly analyzing large amounts of climate model output. While our study has been conducted for two important extreme weather patterns (TCs and ARs) in simulation datasets, we believe that this methodology can be applied to a much broader class of patterns and applied to observational and reanalysis data products via transfer learning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Enhancing Nanoparticle Detection in Interferometric Scattering (iSCAT) Microscopy Using a Mask R-CNN

Interferometric scattering microscopy (iSCAT) is a label-free optical microscopy technique that enables imaging of individual nano-objects such as nanoparticles, viruses, and proteins. Essential to this technique is the suppression of background scattering and identification of signals from nano-objects. In the presence of substrates with high roughness, scattering heterogeneities in the background, when coupled with tiny stage movements, cause features in the background to be manifested in background-suppressed iSCAT images. Traditional computer vision algorithms detect these background features as particles, limiting the accuracy of object detection in iSCAT experiments. Here, in this paper, we present a pathway to improve particle detection in such situations using supervised machine learning via a mask region-based convolutional neural network (mask R-CNN). Using a model iSCAT experiment of 19.2 nm gold nanoparticles adsorbing to a rough layer-by-layer polyelectrolyte film, we develop a method to generate labeled datasets using experimental background images and simulated particle signals and train the mask R-CNN using limited computational resources via transfer learning. We then compare the performance of the mask R-CNN trained with and without inclusion of experimental backgrounds in the dataset against that of a traditional computer vision object detection algorithm, Haar-like feature detection, by analyzing data from the model experiment. Results demonstrate that including representative backgrounds in training datasets improved the mask R-CNN in differentiating between background and particle signals and elevated performance by markedly reducing false positives. The methodology for creating a labeled dataset with representative experimental backgrounds and simulated signals facilitates the application of machine learning in iSCAT experiments with strong background scattering and thus provides a useful workflow for future researchers to improve their image processing capabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Molecular-Level Design of Heterogeneous Chiral Catalysts

A recent major focus of catalyst research has been on improving the selectivity or atom efficiency of catalytic processes. Perhaps the most subtle and difficult form of selectivity to control is enantioselectivity, a catalyst’s ability to preferentially yield one enantiomer of a chiral product. Since two enantiomers are identical in all respects except for their mirror reflection symmetry, both are formed in non-chiral environments at exactly equal rates; only by introducing some type of chiral modification to the system can the rate of formation of one enantiomer be favored over the other. This has been successfully achieved for homogeneous-phase, organometallic catalysts, but the empirical development of heterogeneous-phase analogs has proven elusive. The design of such heterogeneous-phase catalysts would obviate the need for inefficient purification steps to remove the heavy-metal catalysts. The goal of the proposed research by the Chiral Catalysis Group is to understand the interactions of prochiral reactants on chirally modified surfaces that lead to the preferential formation of one enantiomer over the other. There are two general concepts for designing heterogeneous-phase enantioselective catalysts. The first adopts the strategy used in homogeneous phase, by adding a chiral modifier to the surface. This approach, while conceptually simple has challenges associated with modifying an extended surface. The second concept, which is unique to extended surfaces, is the idea of creating surfaces that are themselves naturally chiral. A fundamental understanding of the interactions that control enantioselectivity will enable the Chiral Catalysis Group to develop the concepts necessary to design novel, heterogenous catalytic materials. Enantioselectivity is also central to catalytic processes that underpin the pharmaceutical and agrochemical industries. With funding from the Department of Energy, the Chiral Catalysis Group has played a leading role in developing a fundamental understanding of chiral catalysis and of the adsorbate structures, interactions and kinetic effects that control heterogenous-phase enantioselectivity. The proposed research program is organized conceptually around three types of enantiospecific interactions: interactions with naturally chiral surfaces; those with modified surfaces categorized as chirally templated surfaces; and one-to-one interactions of prochiral molecules with chiral surface modifiers. Our specific goals are to: (1) determine the structures of chiral surfaces, prochiral reactants, chiral products and chiral modifiers; (2) understand the enantiospecific interactions that occur between prochiral reactants and chiral products with chirally modified surfaces; (3) develop methods for detection of enantiospecific surface phenomena; and (4) elucidate enantioselective reaction pathways and the interactions that control them. The range of expertise within the Chiral Catalysis Group includes molecular-scale theory, surface science experiments, state-of-the-art spectroscopic, kinetic and atomic-scale imaging capabilities carried out in vacuum and under more-realistic liquid- and gas-phase environments complemented by catalytic measurements. By fully integrating such a breadth of approaches and extensive expertise, the Chiral Catalysis Group will, for the first time, be able to understand, rationally design and then control active sites for optimal enantioselectivity. In addition to having a significant impact on the field of chiral catalysis, the proposed research program will further our general understanding of the molecular-scale origins of catalytic selectivity.

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

A numerical approach for detecting switch-like bistability in mass action chemical reaction networks with conservation laws

Theoretical analysis of signaling pathways can provide a substantial amount of insight into their function. One particular area of research considers signaling pathways capable of assuming two or more stable states given the same amount of signaling ligand. This phenomenon of bistability can give rise to switch-like behavior, a mechanism that governs cellular decision making. Investigation of whether or not a signaling pathway can confer bistability and switch-like behavior, without knowledge of specific kinetic rate constant values, is a mathematically challenging problem. Recently a technique based on optimization has been introduced, which is capable of finding example parameter values that confer switch-like behavior for a given pathway. Although this approach has made it possible to analyze moderately sized pathways, it is limited to reaction networks that presume a uniterminal structure. It is this limited structure we address by developing a general technique that applies to any mass action reaction network with conservation laws. In this paper we developed a generalized method for detecting switch-like bistable behavior in any mass action reaction network with conservation laws. The method involves (1) construction of a constrained optimization problem using the determinant of the Jacobian of the underlying rate equations, (2) minimization of the objective function to search for conditions resulting in a zero eigenvalue, (3) computation of a confidence level that describes if the global minimum has been found and (4) evaluation of optimization values, using either numerical continuation or directly simulating the ODE system, to verify that a bistability region exists. The generalized method has been tested on three motifs known to be capable of bistability. We have developed a variation of an optimization-based method for the discovery of bistability, which is not limited to uniterminal chemical reaction networks. Successful completion of the method provides an S-shaped bifurcation diagram, which indicates that the network acts as a bistable switch for the given optimization parameters.

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

Laser-metal interaction dynamics during additive manufacturing resolved by detection of thermally-induced electron emission

In situ monitoring is required to improve the understanding and increase the reliability of additive manufacturing methods such as laser powder bed fusion (LPBF). Current diagnostic methods for LPBF capture optical images, X-ray radiographs, or measure the emission of thermal or acoustic signals from the component. Herein, a methodology based on the thermal emission of electrons - thermionic emission - from the metal surface during LPBF is proposed which can resolve laser-material interaction dynamics. The high sensitivity of thermionic emission to surface temperature and surface morphology is revealed to enable precise determination of the transition between conduction and keyhole mode melting regimes. Increases in thermionic emission are correlated to laser scanning conditions that give rise to pore formation and regions where surface defects are pronounced. The information presented here is a critical step in furthering our understanding and validation of laser-based metal additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Encoding Multilayer Complexity in Anti-Counterfeiting Heterometallic MOF-based Optical Tags

Optical tags provide a way to quickly and unambiguously identify valuable assets. Current tag fluorophore options lack the tunability to allow combined methods of encoding in a single material. Here we report a design strategy to encode multilayer complexity in a family of heterometallic rare-earth metal-organic frameworks based on highly connected nonanuclear clusters. To impart both intricacy and security, a synergistic approach was implemented resulting in both overt (visible) and covert (near infrared, NIR) properties, with concomitant multi-emissive spectra and tunable luminescence lifetimes. Tag authentication is validated with a variety of orthogonal detection methodologies. Importantly, the effect induced by subtle compositional changes on intermetallic energy transfer, and thus on the resulting photophysical properties, is demonstrated. This strategy can be widely implemented to create a large library of highly complex, difficult to counterfeit optical tags.

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

Ordered porous RGO/SnO 2 thin films for ultrasensitive humidity detection

In this work, ordered porous thin films of reduced graphene oxide and tin oxide (rGO/SnO 2 ) were synthesized by a polystyrene sphere monolayer colloidal crystal template method, and their gas-sensing properties were systematically studied. The formed amorphous SnO 2 and partially reduced graphene oxide were analyzed using several complementary material characterization techniques. Further, the results show that the incorporation of rGO significantly improved the humidity sensitivity and the electrical conductivity of the sensor relative to the pristine SnO 2 thin film. Fast response time and excellent selectivity towards humidity were also achieved for the rGO/SnO 2 composite film. The long-term stability of the rGO/SnO 2 sensor was confirmed by comparing its performance to a commercial humidity sensor. The enhanced sensor performance is attributed to the synergistic effects of the incorporation of rGO and the ordered porous structure of the composite film.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗