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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Control of the Structural Charge Distribution and Hydration State upon Intercalation of CO 2 into Expansive Clay Interlayers

Numerous experimental investigations indicated that expansive clays such as montmorillonite can intercalate CO 2 preferentially into their interlayers and therefore potentially act as a material for CO 2 separation, capture, and storage. However, an understanding of the energy–structure relationship during the intercalation of CO 2 into clay interlayers remains elusive. Here, in this study, we use metadynamics molecular dynamics simulations to elucidate the energy landscape associated with CO 2 intercalation. Our free energy calculations indicate that CO 2 favorably partitions into nanoconfined water in clay interlayers from a gas phase, leading to an increase in the CO 2 /H 2 O ratio in clay interlayers as compared to that in bulk water. CO 2 molecules prefer to be located at the centers of charge-neutral hydrophobic siloxane rings, whereas interlayer spaces close to structural charges tend to avoid CO 2 intercalation. The structural charge distribution significantly affects the amount of CO 2 intercalated in the interlayers. These results provide a mechanistic understanding of CO 2 intercalation in clays for CO 2 separation, capture, and storage.

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

Identification of Brillouin Zones by In-Plane Lasing from Light-Cone Surface Lattice Resonances

Periodic optical structures can control the flow of light, which has facilitated applications in optical fibers, laser cavities, and biochemical sensors. The first Brillouin zone (BZ) in reciprocal space can describe all the electromagnetic fields localized inside a photonic lattice. However, photonic lattices also exhibit radiative losses from light scattering, but the radiated fields are not captured by the first BZ. In a two-dimensional lattice, the in-plane wavevectors of photonic modes are limited by the so-called light cone, which depicts free-photon dispersion relations in the surrounding medium. Here we show that projection of the light cone on extended BZs provides a geometric method to observe radiated electromagnetic fields of photonic lattice modes. We developed a coupled dipole radiation theory to reveal how lattice geometry and dipole orientation affect the angular distributions of the radiated fields. Using dye molecules as local dipole emitters to excite and probe the optical modes, we experimentally identified high-order BZ edges through directional, in-plane lasing emission.

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

Ensemble learning-iterative training machine learning for uncertainty quantification and automated experiment in atom-resolved microscopy

Deep learning has emerged as a technique of choice for rapid feature extraction across imaging disciplines, allowing rapid conversion of the data streams to spatial or spatiotemporal arrays of features of interest. However, applications of deep learning in experimental domains are often limited by the out-of-distribution drift between the experiments, where the network trained for one set of imaging conditions becomes sub-optimal for different ones. This limitation is particularly stringent in the quest to have an automated experiment setting, where retraining or transfer learning becomes impractical due to the need for human intervention and associated latencies. Here we explore the reproducibility of deep learning for feature extraction in atom-resolved electron microscopy and introduce workflows based on ensemble learning and iterative training to greatly improve feature detection. This approach allows incorporating uncertainty quantification into the deep learning analysis and also enables rapid automated experimental workflows where retraining of the network to compensate for out-of-distribution drift due to subtle change in imaging conditions is substituted for human operator or programmatic selection of networks from the ensemble. This methodology can be further applied to machine learning workflows in other imaging areas including optical and chemical imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Simulating sticky particles: A Monte Carlo method to sample a stratification

Many problems in materials science and biology involve particles interacting with strong, short-ranged bonds that can break and form on experimental timescales. Treating such bonds as constraints can significantly speed up sampling their equilibrium distribution, and there are several methods to sample probability distributions subject to fixed constraints. We introduce a Monte Carlo method to handle the case when constraints can break and form. More generally, the method samples a probability distribution on a stratification: a collection of manifolds of different dimensions, where the lower-dimensional manifolds lie on the boundaries of the higher-dimensional manifolds. We show several applications of the method in polymer physics, self-assembly of colloids, and volume calculation in high dimensions.

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

Imaging dynamic exciton interactions and coupling in transition metal dichalcogenides

Transition metal dichalcogenides (TMDs) are regarded as a possible material platform for quantum information science and related device applications. In TMD monolayers, the dephasing time and inhomogeneity are crucial parameters for any quantum information application. In TMD heterostructures, coupling strength and interlayer exciton lifetimes are also parameters of interest. However, many demonstrations in TMDs can only be realized at specific spots on the sample, presenting a challenge to the scalability of these applications. Here, using multi-dimensional coherent imaging spectroscopy, we shed light on the underlying physics—including dephasing, inhomogeneity, and strain—for a MoSe 2 monolayer and identify both promising and unfavorable areas for quantum information applications. We, furthermore, apply the same technique to a MoSe 2 /WSe 2 heterostructure. Despite the notable presence of strain and dielectric environment changes, coherent and incoherent coupling and interlayer exciton lifetimes are mostly robust across the sample. This uniformity is despite a significantly inhomogeneous interlayer exciton photoluminescence distribution that suggests a bad sample for device applications. This robustness strengthens the case for TMDs as a next-generation material platform in quantum information science and beyond.

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

A Performance Model of In-Situ Techniques

The computational capacity of High-Performance Computing (HPC) systems increases continuously with the rapid development of central processing units (CPUs) and graphic processing units (GPUs), while the in-/output (IO) subsystem develops relatively slowly and storage capacity is also limited. Data-intensive applications, which are designed to leverage the high computational capacity of HPC resources, typically generate a considerable amount of data for post-processing visualizations and data analytics. The limited IO speed and storage space could lead to constraints in the actual performance of these applications and, therefore, scientific discovery. In-situ techniques, where data is visualized/analysed while still in memory rather than through disk, can contribute to alleviating these problems as they can reduce or even fully avoid data writing/reading through the IO subsystem to/from storage. However, the overall efficiency of insitu techniques crucially depends on the characteristics of both the in-situ tasks and the applications, and the resource distribution among them. Therefore, choosing the right in-situ approach (synchronous, asynchronous, or hybrid) and resource allocation is essential to minimize overhead and maximize the benefits of concurrent execution. In this paper, we present a performance model of in-situ techniques to find the most beneficial in-situ approach and the preferred resource configuration. We verify the high accuracy of our approach with over 6800 measurements and provide use cases with different applications.

Ju, Yi [Max Planck Computing and Data Facility, Ga↗
DOE OSTI2024

Computing the Instantaneous Collision Probability between Satellites using Characteristic Function Inversion

The probability that two satellites overlap in space at a specified instant of time is called their instantaneous collision probability. Assuming Gaussian uncertainties and spherical satellites, this probability is the integral of a Gaussian distribution over a sphere. This paper shows how to compute the probability using an established numerical procedure called characteristic function inversion. The collision probability in the short-term encounter scenario is also evaluated with this approach, where the instant at which the probability is computed is the time of closest approach between the objects. Python and R code is provided to evaluate the probability in practice. Overall, the approach has been established for over fifty years, is implemented in existing software, does not rely on analytical approximations, and can be used to evaluate two and three dimensional collision probabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Enhanced Carbon Capture Behavior of Carbon Fibers via Ionic Liquid Modification

Carbon-based materials are widely deployed in carbon capture but are only limited to physisorption procedures. Further extending functionalized carbon materials to CO 2 chemisorption under low CO 2 concentration is highly desirable yet challenging. In this study, a carbon fiber composed of solely ultra-micropores (~0.45 nm) was deployed as the precursor to avoid the pore blocking effect, which was modified by superbase-derived ionic liquids (ILs) containing strong interaction sites with CO 2 . By forming a thin coating layer on the surface, the as-afforded surface-functionalized fiber materials demonstrated enhanced CO 2 uptake capacity and improved CO 2 sorption kinetics, as evaluated by both the volumetric method and thermogravimetric analysis, as well as the calculated energy distribution curves. The achievements made in this work provide guidance on the functionalization of carbon-based materials towards enhanced CO 2 chemisorption by forming a thin layer of selected IL coating.

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

Sectoral and growth rate control on elemental uptake by individual calcite crystals

Heterogeneous distribution of trace elements (impurities) within individual calcite crystals is a phenomenon commonly observed in natural and laboratory systems. Changes in thermodynamic intensive parameters (mostly chemical potential and temperature) cannot always explain the inhomogeneous impurity patterns in calcite crystals and it has been suggested that growth rate and crystallographic orientation may exert strong effects on elemental incorporation into calcite. In addition, there are a number of experimental studies on micro-scale element (E) distribution between non-equivalent pairs of calcite vicinal faces (known as sectoral zoning); however, the variability of partition coefficients (e.g., K E = (E/Ca) calcite /(E/Ca) fluid ) within individual crystals remains undetermined. In this study, we have extended the work on elemental distribution between crystal sectors to evaluation of partition coefficients of trace and minor elements (Li, B, Mg, and Sr) in calcite crystal faces (10–14) and (01-12), whose growth rates were assessed. Growth entrapment model (GEM) and lattice strain theory were applied to explain K E heterogeneity by varying near-surface diffusivity of Mg and Sr and by varying surface enrichment factor for Li, B, Mg, and Sr. Decoupling of sectoral and growth rate effects reveals that sectoral zoning plays a key role in elemental distribution. More specifically, K Li and K B vary by more than one order of magnitude and K Mg varies by a factor of two within individual crystal faces. Strontium sectoral distribution is different from those of Li, B, and Mg and K Sr varies by up to a factor of two. Finally, these behaviors likely reflect different mechanisms of incorporation of Li, B, Mg, and Sr into calcite.

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

Efficient Fourier transforms for transverse momentum dependent distributions

Hadron production at low transverse momenta in semi-inclusive deep inelastic scattering can be described by transverse momentum dependent (TMD) factorization. This formalism has also been widely used to study the Drell-Yan process and back-to-back hadron pair production in $e^+e^-$ collisions. These processes are the main ones for extractions of TMD parton distribution functions and TMD fragmentation functions, which encode important information about nucleon structure and hadronization. One of the most widely used TMD factorization formalism in phenomenology formulates TMD observables in coordinate $b_\perp$-space, the conjugate space of the transverse momentum. The Fourier transform from $b_\perp$-space back into transverse momentum space is sufficiently complicated due to oscillatory integrands that it requires a careful and computationally intensive numerical treatment in order to avoid potentially large numerical errors. Within the TMD formalism, the azimuthal angular dependence is analytically integrated and the two-dimensional $b_\perp$ integration reduces to a one-dimensional integration over the magnitude $b_\perp$. In this paper we develop a fast numerical Hankel transform algorithm for such a $b_\perp$-integration that improves the numerical accuracy of TMD calculations in all standard processes. Libraries for this algorithm are implemented in Python 2.7 and 3, C++, as well as FORTRAN77. All packages are made available open source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Evaluating Retention Index Score Assumptions to Refine GC–MS Metabolite Identification

As metabolomics grows into a high-throughput and high demand research field, current metrics for the identification of small molecules in gas chromatography–mass spectrometry (GC–MS) still require manual verification. Though steps have been taken to improve scoring metrics by combining spectral similarity (SS) and retention index (RI), the problem persists. A large body of literature has analyzed and refined SS scores, but few studies have explicitly studied improvements to RI scores. Here, in this study, we examined whether uninvestigated assumptions of the RI score are valid and propose ways to improve them. Query RIs were matched to library RI with a generous window of ±35 to avoid unintentional removal of valid compound identifications. Each match was manually verified as a true positive (TP), true negative, or unknown. Metabolites with at least 30 TP identifications were included in downstream analyses, resulting in a total of 87 metabolites from samples of varying complexity and type (e.g., amino acid mixtures, human urine, fungal species, and so on.). Our results showed that the RI score assumptions of normality, consistent variance across metabolites, and a mean error centered at 0 are often violated. We demonstrated through a cross-validation analysis that modifying these underlying assumptions according to empirical metabolite-specific distributions improved the TP and negative rankings. Further, we statistically determined the minimum number of samples required to estimate distributional parameters for scoring metrics. Overall, this work proposes a robust statistical pipeline to reduce the time bottleneck of metabolite identification by improving RI scores and thus minimize the effort to complete manual verification.

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

Broad Distribution of Local Polar States Generates Large Electrothermal Properties in Pb-Free Relaxor Ferroelectrics

Electrothermal energy conversion provides attractive solutions for global energy management, such as energy harvesting from waste heat using pyroelectric energy conversion (PEC) and efficient cooling of portable electronics or data servers using the electrocaloric effect. Relaxor ferroelectrics are attractive for electrothermal energy conversion because of their large pyroelectric coefficients over a wide temperature range. Although Pb-based relaxors are well-known, toxicity concerns have mandated the intense search for Pb-free alternatives. Here, we engineered (Ba,Ca)TiO 3 -based relaxors based on a multisite doping strategy, which show promising electrothermal performance, viz. a maximum PEC efficiency of 14% and electrocaloric refrigeration capacity of 115 J/kg. Using local-scale structural analysis, we provide an atomistic model for large electrothermal properties in the newly designed Pb-free ferroelectrics, whereby a temperature-independent continuous distribution of cation displacement directions creates easy pathways for microscopic polarization reorientation. This research provides key structural insight for future atomic-scale engineering of environmentally sustainable ferroelectrics in energy applications.

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

Permutationally Invariant Polynomial Expansions with Unrestricted Complexity

A general strategy is presented for constructing and validating permutationally invariant polynomial (PIP) expansions for chemical systems of any stoichiometry. Demonstrations are made for three categories of gas-phase dynamics and kinetics: collisional energy-transfer trajectories for predicting pressure-dependent kinetics, three-body collisions for describing transient van der Waals adducts relevant to atmospheric chemistry, and nonthermal reactivity via quasiclassical trajectories. In total, 30 systems are considered with up to 15 atoms and 39 degrees of freedom. Permutational invariance is enforced in PIP expansions with as many as 13 million terms and 13 permutationally distinct atom types by taking advantage of petascale computational resources. The quality of the PIP expansions is demonstrated through the systematic convergence of in-sample and out-of-sample errors with respect to both the number of training data and the order of the expansion, and these errors are shown to predict errors in the dynamics for both reactive and nonreactive applications. Here, the parallelized code distributed as part of this work enables the automation of PIP generation for complex systems with multiple channels and flexible user-defined symmetry constraints and for automatically removing unphysical unconnected terms from the basis set expansions, all of which are required for simulating complex reactive systems.

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

Depth Thermography: Noninvasive 3D Temperature Profiling Using Infrared Thermal Emission

Here, we introduce a technique based on infrared thermal emission, termed depth thermography, that can remotely measure the temperature distribution beneath the surface of certain objects. Depth thermography utilizes the thermal-emission spectrum in the semitransparent spectral region of the target object to extract its temperature as a function of depth, in contrast with conventional thermography, which uses the spectrally integrated thermally emitted power to measure the surface temperature. Coupled with two-dimensional imaging, for example using an infrared hyperspectral camera or scanning a single-pixel spectrometer, this technique can yield volumetric temperature distributions. Furthermore, we carried out a proof-of-concept experiment on an asymmetrically heated fused-silica window, extracting the temperature distribution throughout the sample. Depth thermography may enable noncontact volumetric temperature measurements of microscopic objects such as multilayer electronic devices or macroscopic volumes of liquids and gases, as well as simultaneous all-optical measurements of optical and thermal properties of materials.

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

Identification and quantification of lignin monomers and oligomers from reductive catalytic fractionation of pine wood with GC × GC – FID/MS

Thorough lignin characterization is vital to understand the physicochemical properties of lignin and to evaluate lignocellulose biorefinery processes. In this study, an in-depth characterization of lignin oil, obtained from reductive catalytic fractionation (RCF) of pine wood, was performed with quantitative GC × GC – FID analysis and qualitative GC × GC – MS. By utilizing high-temperature resistant column sets in the GC × GC system and by applying a derivatization step, unambiguous detection of lignin monomers, dimers, and trimers is enabled. In addition to confirm the identity of eleven monomers, corresponding to 34 wt% of the RCF lignin oil, thirty-six dimers (16 wt%) and twenty-one trimers (7 wt%) were comprehensively identified by analysis of their mass spectra and quantified by a FID, encompassing the identity of an additional 23 wt% of the RCF lignin oil. The proposed structures reveal the interlinkages present in the dimeric and trimeric oligomers, containing β-5, β-1, β–β, 5–5, and a minor fraction of β-O-4 and 4-O-5 bonds. Furthermore, aliphatic end-units in the dimeric and trimeric molecules were identified, consisting of various substituents at the C4 position, that have been previously observed in the RCF-derived lignin monomers. To reduce complexity for analysis, the RCF oil was separated into six fractions, prior to analysis. The structural motifs (inter-unit linkages and end-units) that are found in the different fractions vary significantly, such that the lignin fractions extracted in more polar solvents contained higher molecular weight fragments and more hydroxyl containing structural motifs. Additionally, the identified structures of individual dimer and trimer molecules by GC × GC align well with and further complement the recent findings from 1 H– 13 C HSQC NMR spectroscopy, demonstrating complementarity between both 2D techniques to obtain a holistic view on both the molecular structures and the distribution of bonds and end-units in RCF oil. The combination of these two techniques provides a powerful tool for future RCF and other lignin depolymerization research.

09 BIOMASS FUELS↗
DOE OSTI2021

Probing phonon softening in ferroelectrics by scanning probe microwave spectroscopy

Microwave measurements have recently been successfully applied to measure ferroelectric materials on the nanoscale, including detection of polarization switching and ferroelectric domain walls. In this study we discuss the question of whether scanning probe microscopy operating at microwave frequency can identify the changes associated with the soft phonon dynamics in a ferroic. The analytical expressions for the electric potential, complex impedance, and dielectric losses are derived and analyzed, since these physical quantities are linked to experimentally measurable properties of the ferroic. As a ferroic we consider virtual or proper ferroelectric with an optic phonon mode that softens at a Curie point. We also consider a decay mechanism linked to the conductance of the ferroic, thus manifesting itself as the dielectric loss in the material. Our key finding is that the influence of the soft phonon dispersion on the surface potential distribution, complex impedance, and dielectric losses are evidently strong in the vicinity (~10–30 K) of the Curie temperature. Additionally, we quantified how the spatial distribution and frequency spectra of the complex impedance and the dielectric losses react on the dynamics of the soft phonons near the Curie point. These results set the stage for characterization of polar phase transitions with nanoscale microwave measurements, providing a complementary approach to well established electromechanical measurements for fundamental understanding of ferroelectric properties as well as their applications in telecommunication and computing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Small-Signal Stability of Grid-Forming Converters Under Fault Conditions

Threshold virtual impedance (TVI)-based current limiting for grid-forming converters (GFMs) has gained great interest due to its ability to maintain voltage source behaviour during faults. However, sequence component extraction (SCE) and negative-sequence control (NSC) are often overlooked in small-signal stability assessments during faults. This paper develops small-signal sequence impedance models for GFMs under four well-known SCE methods based on TVI current limiting control during symmetrical fault conditions. Using the developed impedance models, the impacts of SCE and NSC, and the voltage and current control loop bandwidths, on system stability during faults are investigated. Additionally, since negative-sequence TVI (TVI-) is typically added along with its positive-sequence counterpart, which is often inductive, inductive and resistive TVI- are examined. The findings suggest that a higher voltage or current control loop bandwidth has a negative impact on system stability, while SCE and NSC largely reduce the stable range for voltage and current control loop bandwidth during faults, and that the severity of such impacts is determined by the particular SCE method. Furthermore, it is observed that inductive TVI- significantly degrades system stability, while resistive TVI- can enhance stability when suitable SCE methods are appropriately selected and designed. Matlab/Simulink electromagnetic transient simulations validate these analytical results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

X-ray chemical imaging for assessing redox microsites within soils and sediments

Redox reactions underlie several biogeochemical processes and are typically spatiotemporally heterogeneous in soils and sediments. However, redox heterogeneity has yet to be incorporated into mainstream conceptualizations and modeling of soil biogeochemistry. Anoxic microsites, a defining feature of soil redox heterogeneity, are non-majority oxygen depleted zones in otherwise oxic environments. Neglecting to account for anoxic microsites can generate major uncertainties in quantitative assessments of greenhouse gas emissions, C sequestration, as well as nutrient and contaminant cycling at the ecosystem to global scales. However, only a few studies have observed/characterized anoxic microsites in undisturbed soils, primarily, because soil is opaque and microsites require µm-cm scale resolution over cm-m scales. Consequently, our current understanding of microsite characteristics does not support model parameterization. To resolve this knowledge gap, we demonstrate through this proof-of-concept study that X-ray fluorescence (XRF) 2D mapping can reliably detect, quantify, and provide basic redox characterization of anoxic microsites using solid phase “forensic” evidence. First, we tested and developed a systematic data processing approach to eliminate false positive redox microsites, i.e., artefacts, detected from synchrotron-based multiple-energy XRF 2D mapping of Fe (as a proxy of redox-sensitive elements) in Fe-“rich” sediment cores with artificially injected microsites. Then, spatial distribution of Fe II and Fe III species from full, natural soil core slices (over cm-m lengths/widths) were mapped at 1–100 µm resolution. These investigations revealed direct evidence of anoxic microsites in predominantly oxic soils such as from an oak savanna and toeslope soil of a mountainous watershed, where anaerobicity would typically not be expected. We also revealed preferential spatial distribution of redox microsites inside aggregates from oak savanna soils. We anticipate that this approach will advance our understanding of soil biogeochemistry and help resolve “anomalous” occurrences of reduced products in nominally oxic soils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗