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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 613 records · Page 34

Evaluation of simulated HPGe detector efficiencies in OpenMC compared to MCNP

In late 2023, the open-source radiation transport code OpenMC introduced a pulse-height tally (PHT) feature, enabling users to track the total energy deposited by individual photons in OpenMC cells. This function represents an important improvement of the OpenMC code because it allows users to simulate the response function of a gamma detector without relying on closed-source alternatives. Despite this, limited work has been published evaluating OpenMC as a radiation transport code for simulating gamma spectroscopy experiments. This study attempts to demonstrate the usefulness of OpenMC in this space by directly comparing its PHT output to MCNP (a trusted industry-standard Monte Carlo code). In the first half of this study, a radiation transport experiment is described in which a detector with a complex internal geometry is exposed to various gamma-emitting isotopes ( 133 Ba, 137 Cs, and 60 Co) over a range of distances. The setup of this experiment was modeled in MCNP with sufficient detail to capture the efficiency characteristics of a high purity germanium (HPGe) detector for the primary gammas of each isotope. After good agreement between the MCNP model and experiment was achieved, an identical model was produced in OpenMC to allow direct comparison between the full energy peak (FEP) values produced in OpenMC and MCNP. The results show strong agreement between OpenMC and MCNP across the full range of tested energies, with each model’s FEP values typically within 2% of each other and most FEP areas within 4% of experimental data. Worse agreement was seen between the Monte Carlo codes and experiment below 300 keV (an expected result). For the 662 keV line of 137 Cs, both codes were found in poor agreement with experiment and each other over the full range of distances tested (possibly indicating an error with the 137 Cs experimental data). Ignoring the anomalous results of the 662 keV line, all other data show good qualitative and quantitative agreement between MCNP and OpenMC. This result demonstrates the accuracy of OpenMC’s PHT feature for spectroscopic applications in which detector efficiency is a primary concern.

07 - ISOTOPES AND RADIATION SOURCES↗

Pulse radiolysis and transient absorption spectra of aqueous solutions of sodium sulfamate

Chemical kinetics for the reactions of sulfamate ions (NH 2 SO 3 − ) with the primary products of water and nitric acid radiolysis were measured in aqueous solutions at ambient temperature. Using time-resolved electron pulse radiolysis techniques with a custom multichannel detection system, we examined the reactivity of NH 2 SO 3 − with the hydroxyl radical ( • OH), hydrogen atom (H • ), and nitrate radical (NO 3 • ). The sulfamate ion was found to react with • OH and H • with second-order rate coefficients of k • OH = (5.60 ± 0.04) × 10 6 M −1 s −1 and k H • = (7.96 ± 0.10) × 10 6 M −1 s −1 , respectively, and with NO 3 • with a rate coefficient of k NO 3 • = (1.67 ± 0.06) × 10 7 M −1 s −1 . The reactions of NH 2 SO 3 − with • OH and H • resulted in the formation of two transient radical species, one with maximum absorbance at 300 nm and a second with maxima at both 300 nm and 600 nm. These spectra are tentatively assigned to • NH 2 SO 3 and • NHSO 3 − , respectively. By measuring the absorbance of these radicals as a function of pH, the radical pK a was determined to be 9.5 ± 0.1. Overall, this work has implications for the longevity and performance of ferrous sulfamate, Fe(NH 2 SO 3 ) 2 , as a plutonium reductant in the reprocessing of used nuclear fuel.

Conrad, Jacy K. [Idaho National Laboratory (INL), ↗

..delta..-Learning of High-Fidelity Electronic Structure Using Graph Neural Networks with Modified Node-Level Features

In this work, we present a ..delta..-learning approach for predicting the eigenvalues calculated with the hybrid functional HSE06 (..epsilon..nkHSE) for a set of metal and nitrogen doped graphene catalysts (MNCs) from Perdew-Burke-Ernzerhof (PBE) inputs. The model presented here incorporates electronic scalar features along with structural information in a graph neural network (GNN). In particular, the PBE eigenvalues for different bands and k-points and orbital-resolved projectors are combined with the applied potential as node-level features along with structural information within the Atomistic Line Graph Neural Network (ALIGNN) architecture. These features enable flexibility for systems with electrified interfaces, such as in electrocatalysts and achieves mean absolute error (MAE) of less than 0.1 eV. The machine learning model reported here achieves a strong generalization to left-out adsorbates (MAE = 0.074 eV) and leave-one-chemical-space-out (MAE = 0.08 eV) and completely left-out metals (MAE = 0.072 eV), confirming the robustness of the machine learning (ML) model in predicting ..epsilon..nkHSE.

36 MATERIALS SCIENCE↗

Self-Sorting vs Coassembly in Peptide Amphiphile Supramolecular Nanostructures

The functionality of supramolecular nanostructures can be expanded if systems containing multiple components are designed to either self-sort or mix into coassemblies. This is critical to gain the ability to craft self-assembling materials that integrate functions, and our understanding of this process is in its early stages. Here, in this work, we have utilized three different peptide amphiphiles with the capacity to form β-sheets within supramolecular nanostructures and found binary systems that self-sort and others that form coassemblies. This was measured using atomic force microscopy to reveal the nanoscale morphology of assemblies and confocal laser scanning microscopy to determine the distribution of fluorescently labeled monomers. We discovered that PA assemblies with opposite supramolecular chirality self-sorted into chemically distinct nanostructures. In contrast, the PA molecules that formed a mixture of right-handed, left-handed, and flat nanostructures on their own were able to coassemble with the other PA molecules. We attribute this phenomenon to the energy barrier associated with changing the handedness of a β-sheet twist in a coassembly of two different PA molecules. This observation could be useful for designing biomolecular nanostructures with dual bioactivity or interpenetrating networks of PA supramolecular assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ab Initio Polariton Spectra of ZnTPP Molecules Collectively Coupled Inside an Optical Cavity

Exciton-polaritons are quasi-particles formed by the quantum mechanical hybridization of electronic and photonic excitations. Despite extensive investigations, a fundamental understanding of molecular polariton spectra and the polariton delocalization from an ab initio theoretical perspective remains elusive. We simulate experimentally measured linear transmission spectroscopy of many Zinc(II) tetraphenylporphyrin (ZnTPP) molecules collectively coupled to a cavity from first principles. Our theoretical approach incorporates many low-lying electronic excitations in ZnTPP molecules, as well as collective light-matter couplings between ZnTPP and the quantized radiation modes, both of which are shown to be the key to accurately recovering the experimental spectra. We further analyzed to what extent the polariton and dark states are delocalized over many molecules, for the first time, using fully ab initio descriptions of the molecules. We finally investigate the line width as a function of detuning, providing new theoretical insights into the experimentally observed motional narrowing behavior. Our work presents first-ofits- kind theoretical studies on molecular polariton spectra, offering a new perspective on molecular polariton formation in realistic ab initio molecular systems whose rich, many-state nature provides spectral features enabled by the high density of electronic states beyond simple quantum optics models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large bandgap observed on the surfaces of EuZn 2 As 2 single crystals

EuM 2 As 2 (M = Zn, Cd, In, Sn etc.) is an excellent material system for studying magnetism-tuned topological properties. However, discrepancies exist between experimental data and theoretical calculations regarding the bulk and surface bandgaps. In this work, cleaved EuZn 2 As 2 crystals are studied using scanning tunneling microscopy/spectroscopy and density functional theory calculations. Triangular-shaped defect-induced modifications in the local density of states help distinguish between Eu-terminated and AsZn-terminated surfaces. While large bandgaps (~1.5 eV at 77 K) are observed on both pristine surfaces, the bandgap size is found to be highly sensitive to local heterogeneity, tending to decrease. By combining experimental observations with theoretical simulations, we conclude that the reduced bandgap in heterogeneous regions arises from Zn vacancies and/or substitution by As atoms, both impacting greater in the Eu surface electronic properties than those in the AsZn surface. This demonstrates the intimate relationship between the electronic structure and magnetism in EuZn 2 As 2 .

interfaces↗

Observing neutron alignment at high angular momenta in heavy deformed actinides

An outstanding puzzle in the structure of very heavy nuclei lies in the rotation response of deformed transuranic isotopes. While the rotation alignment of pairs of 𝑖 13/2 protons is ubiquitous and well understood, observing the analogous alignment of the 𝑗 15/2 neutrons has been elusive. In this work we present a new quantitative analysis approach: from their moments of inertia as a function of frequency, we compare the alignments of rotational bands with both “low” and high-𝑗 intrinsic structures in the 𝑁 = 151 isotones of Pu, Cm, Cf, and No, thereby distinguishing between the alignments of neutron versus proton pairs through “blocking” effects. In this way, the alignment of 𝑗 15/2 neutrons can be clearly identified for the first time. The protons and neutrons begin aligning at a very similar frequency. The contribution of 𝑗 15/2 neutrons to the total alignment is found to grow with increasing 𝑍 compared to 𝑖 13/2 protons. To explain these observations, it is necessary to adopt a self-consistent set of single-particle energies corresponding to the nuclear shape that minimizes the mass. The shape description needs to include high-order deformations up to at least 𝛽 6 .

A ≥ 220↗

Multipole responses in fissioning nuclei and their uncertainties

Electromagnetic multipole responses are key inputs to model the structure, decay, and reactions of atomic nuclei. With the introduction of the finite amplitude method (FAM), large-scale calculations of the nuclear linear response in heavy deformed nuclei have become possible. This work provides a detailed study of multipole responses in actinide nuclei with Skyrme energy density functionals. We quantify both systematic and statistical uncertainties induced by the functional parametrization in FAM calculations. We also extend the FAM formalism to perform blocking calculations with the equal filling approximation for odd-mass and odd-odd nuclei, and analyze the impact of blocking configurations on the response. In conclusion, by examining the entire plutonium isotopic chain from the proton to the neutron drip line, we find a large variability of the response with the neutron number and study how it correlates with the deformation of the nuclear ground state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

b ¯ b ¯ u d and b ¯ b ¯ u s tetraquarks from lattice QCD using symmetric correlation matrices with both local and scattering interpolating operators

We study the b ¯ b ¯ u d tetraquark with quantum numbers I ( J P ) = 0 ( 1 + ) as well as the b ¯ b ¯ u s tetraquark with quantum numbers J P = 1 + using lattice QCD. We improve on existing work by including both local and scattering interpolating operators on both sides of the correlation functions and use symmetric correlation matrices. This allows not only a reliable determination of the energies of QCD-stable tetraquark ground states, but also of low-lying excited states, which are meson-meson scattering states. The latter is particularly important for future finite-volume scattering analyses. Here, we perform chiral and continuum extrapolations of just the ground-state energies, for which finite-volume effects are expected to be small. Our resulting tetraquark binding energies, − 100 ± 10 − 51 + 36 MeV for b ¯ b ¯ u d and − 30 ± 3 − 31 + 11 MeV for b ¯ b ¯ u s , are consistent with other recent lattice-QCD predictions. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Power-Law Entanglement and Hilbert Space Fragmentation in Nonreciprocal Quantum Circuits

Quantum circuits utilizing measurement to evolve a quantum wave function offer a new and rich playground to engineer unconventional entanglement dynamics. Here, in this work, we introduce a hybrid, nonreciprocal setup featuring a quantum circuit, whose updates are conditioned on the state of a classical dynamical agent. In our example the circuit is represented by a Majorana quantum chain controlled by a classical N-state Potts chain undergoing pair flips. The local orientation of the classical spins controls whether randomly drawn local measurements on the quantum chain are allowed or not. This imposes a dynamical kinetic constraint on the entanglement growth, described by the transfer matrix of an N-colored loop model. It yields an equivalent description of the circuit by an SU(N)-symmetric Temperley-Lieb Hamiltonian or by a kinetically constrained surface growth model for an N-component height field. For N = 2, we find a diffusive growth of the half-chain entanglement toward a stationary profile S(L) ~ L 1/2 for L sites. For N ≥ 3, the kinetic constraints impose Hilbert space fragmentation, yielding subdiffusive growth toward S(L) ~ L 0.57 . This showcases how the control by a classical dynamical agent can enrich the entanglement dynamics in quantum circuits, paving a route toward novel entanglement dynamics in nonreciprocal hybrid circuit architectures.

1-dimensional spin chains↗

The impact of kidney function on Alzheimer’s disease blood biomarkers: implications for predicting amyloid-β positivity

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity. We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m 2 , based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models. Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values. We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

60 APPLIED LIFE SCIENCES↗

Los Alamos National Laboratory: SULI Appointment

We use COSMIC, a galaxy population synthesis code, to investigate how metallicity affects the rate of formation of massive stars with a closely orbiting compact object companion, the suggested progenitors of radio loud gamma-ray bursts. We show the evolution time of these systems at different metallicities, and how the formation rates of these systems are anti-correlated with metallicity. In particular, these systems occur about 10 times more frequently in at metallicities between 0.0002 and 0.002, compared to those between 0.002 and 0.02. This work serves as a prerequisite to predicting the global rates of these systems as a function of redshift, ultimately giving crucial insight into our understanding of the progenitors of gamma-ray bursts and their evolution over cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗

Algorithms and file structures to extend and enhance liquid chromatography and ion mobility mass spectrometry workflows (CRADA Final Report)

The purpose of this project was to continue supporting customizations of algorithms and raw data file structures to enhance software workflows for liquid chromatography (LC), mass spectrometry (MS) and ion mobility mass spectrometry (IM-MS)-based protein and metabolite characterization. PNNL worked with Agilent to design, implement, evaluate, and demonstrate new algorithms and integrated them as functionalities into the PNNL-PreProcessor software. The project augmented PNNL’s capabilities to analyze complex proteomics and metabolomics samples. These capabilities are directly beneficial to DOE and PNNL efforts to characterize and analyze these compounds in microbial and plant communities. The project assisted Agilent in further developing improved instrument-software solutions combining liquid chromatography and ion mobility with mass spectrometry for widespread applications in life sciences and other fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemically Enhanced Electrodialysis (CEED) for Recovery of Rare Earth Elements

Rare-earth elements are crucial for numerous technologically relevant industries including energy, electronics, and aerospace; however, both the supply and separation of rare earths are pressing challenges. The long-term goal of the collaborative project is to develop a novel approach to existing extraction behaviors. To achieve this goal, a class of electrodialysis membranes with novel ion-gating functionality will be developed and paired with a conventional electrodialysis strategy. The hypothesis of the work is that incorporating sequestrants of suitable structures at the surface of the electrodialysis membrane will enhance extraction efficiency for ions of interest. Our ability to prepare sequestrants of diverse conformations and to adapt their molecular structure for binding lanthanides renders the proposed technology a versatile method for selective ion separation. Our approach will enable an entirely new technological approach to the separation of valuable rare-earth elements.

36 MATERIALS SCIENCE↗

Liquid Crystal Orientation and Shape Optimization for the Active Response of Liquid Crystal Elastomers

Liquid crystal elastomers (LCEs) are responsive materials that can undergo large reversible deformations upon exposure to external stimuli, such as electrical and thermal fields. Controlling the alignment of their liquid crystals mesogens to achieve desired shape changes unlocks a new design paradigm that is unavailable when using traditional materials. While experimental measurements can provide valuable insights into their behavior, computational analysis is essential to exploit their full potential. Accurate simulation is not, however, the end goal; rather, it is the means to achieve their optimal design. Such design optimization problems are best solved with algorithms that require gradients, i.e., sensitivities, of the cost and constraint functions with respect to the design parameters, to efficiently traverse the design space. In this work, a nonlinear LCE model and adjoint sensitivity analysis are implemented in a scalable and flexible finite element-based open source framework and integrated into a gradient-based design optimization tool. To display the versatility of the computational framework, LCE design problems that optimize both the material, i.e., liquid crystal orientation, and structural shape to reach a target actuated shapes or maximize energy absorption are solved. Multiple parameterizations, customized to address fabrication limitations, are investigated in both 2D and 3D. The case studies are followed by a discussion on the simulation and design optimization hurdles, as well as potential avenues for improving the robustness of similar computational frameworks for applications of interest.

42 ENGINEERING↗

Resolving femtosecond photoinduced energy flow: capture of nonadiabatic reaction pathway topography and wavepacket dynamics from photoexcitation through the conical intersection seam (Final Technical Report)

The dynamics that take place within just tens to hundreds of femtoseconds following the absorption of light by a molecule can play a critical role in how the absorbed energy is directed, allowing it to be used for a specific function or dissipated harmlessly. The form of chemical change that occurs rapidly in these molecules is called a “nonadiabatic electronic transition.” Such transitions are known to mediate energy flow in natural biological systems such as the ultraviolet photoprotection mechanism of DNA and the first step of the human vision response. Understanding how these mechanisms work precisely may help scientists achieve controlled manipulation of solar energy or optical control of a wide range of energy management functions in artificial systems. Experimental methods, however, have not yet allowed a precisely resolved and complete measurement of nonadiabatic electronic transitions. This constitutes a major obstacle to progress in the field. For progress to occur that would inform a wide body of research aiming to efficiently harness the energy of light for practical purposes, it is especially important to benchmark computational models of the molecules undergoing these rapid changes with experimental measurements, in order to learn which models are accurate. With Dept. of Energy funding, we have made strong progress towards establishing a new optical method for experimentally detecting the full nonadiabatic electronic transition. This requires having coordinated pulses of light covering the visible through the mid-infrared range of the electromagnetic spectrum that last only ten femtoseconds. We have developed a new, relatively simple approach for generating such pulses of laser light, and have incorporated them into a time-resolved spectrometer for measuring rapid changes in molecules. These tools can provide the greater precision and new types of data that are needed to benchmark computational models of molecular change and thus to make progress in the field. Our tools were tested on graphene, an excellent solid-state sample for verifying the capabilities and limitations of our instrumentation. The investment made in these tools by the Dept. of Energy Office of Science will allow new fundamental scientific understanding of energy dynamics in molecules in future studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗

Implementation of Genetic Algorithms to Optimize Metal–Organic Frameworks for CO 2 Capture

Metal-organic frameworks (MOFs) are promising materials for CO 2 capture with the potential to use less energy than current industrial CO 2 capture methods. MOFs are highly versatile sorbents, and there is an almost unlimited number of MOFs that could be synthesized. In this work, we used a genetic algorithm (GA) and grand canonical Monte Carlo (GCMC) simulations to efficiently search for high-performing MOFs for CO 2 capture. We analyzed the effects of important GA parameters, including the mutation probability, the number of MOFs per generation and the number of GA generations, on the GA performance. Here, we performed GCMC simulations on-the-fly during the GA procedure to determine the performance of proposed MOFs and optimized their structures using multiple objective functions across different topologies. The GA was able to determine top-performing MOFs balancing CO 2 selectivity versus working capacity and reduced the cost of molecular simulations by a factor of 25 versus brute-force screening of an entire database of structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗