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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effective point-charge analysis of crystal fields: Application to rare-earth pyrochlores and tripod kagome magnets 𝑅 ⁢3⁢ Mg⁢ 2 ⁢Sb⁢ 3⁢ O⁢ 14

An indispensable step to understand collective magnetic phenomena in rare-earth compounds is the determination of spatially anisotropic single-ion properties resulting from spin-orbit coupling and crystal field (CF). The CF Hamiltonian has a discrete energy spectrum—accessible to spectroscopic probes such as neutron scattering—controlled by a number of independent parameters reflecting the point symmetry of the magnetic sites. Determining these parameters in low-symmetry systems is often challenging. Here, we describe a general method to analyze CF excitation spectra using adjustable effective point-charges. We benchmark our method to existing neutron-scattering measurements on pyrochlore rare-earth oxides and obtain a universal point-charge model that describes a large family of related materials. We adapt this model to the newly discovered tripod kagome magnets (𝑅 3 ⁢Mg 2 ⁢Sb 3 ⁢O 14 , 𝑅 = Tb, Ho, Er, Yb) for which we report broadband inelastic neutron-scattering spectra. Analysis of these data using adjustable point-charges yields the CF wave functions for each compound. From this, we calculate thermomagnetic properties that accurately reflect our measurements on powder samples and predict the effective gyromagnetic tensor for pseudospin degrees of freedom—a crucial step to understand the exotic collective properties of these kagome magnets at low temperature. We present further applications of our method to other tripod kagome materials and triangular rare-earth compounds 𝑅⁢MgGaO 4 (𝑅 =Yb, Tm). Overall, this study establishes a widely applicable methodology to predict CF and single-ion properties of rare-earth compounds based on interpretable and adjustable models of effective point charges.

Crystal-field theory↗
DOE OSTI2016

Positive and negative contribution to birefringence in a family of carbonates: A Born effective charges analysis

It is an important topic to investigate the birefringence and reveal the contribution from ions to birefringence because it plays an important role in nonlinear optical materials. In this paper, the birefringence of carbonates with coplanar CO{sub 3} groups were investigated using the first-principles method. The results show that the lead carbonates exhibit relative large birefringence. After detailed investigate the electronic structures, and Born effective charges, the authors find out that anisotropic electron distribution in the CO{sub 3} groups and Pb atoms give positive contribution, while the negative contribution was found from fluorine atoms, meanwhile the Ca, Mg, and Cd atoms give very small contribution to birefringence. - Graphical abstract: Using the DFT and Born effective charges, the birefringence and the contribution of ions were investigated, the positive and negative contribution was found from Pb and F ions, respectively. - Highlights: • Optical properties and Born effective charges of carbonates are investigated. • Lead carbonates exhibit relative large birefringence. • Coplanar CO{sub 3} groups and Pb atoms give positive contribution. • F atoms give negative contribution. • Ca, Mg, and Cd atoms give very small contribution.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Natural Charge-Transfer Analysis: Eliminating Spurious Charge-Transfer States in Time-Dependent Density Functional Theory via Diabatization, with Application to Projection-Based Embedding

For many types of vertical excitation energies, linear-response time-dependent density functional theory (LR-TDDFT) offers a useful degree of accuracy combined with unrivaled computational efficiency, although charge-transfer excitation energies are often systematically and dramatically underestimated, especially for large systems and those that contain explicit solvent. As a result, low energy electronic spectra of solution-phase chromophores often contain tens to hundreds of spurious charge-transfer states, making LR-TDDFT needlessly expensive in bulk solution. More nefariously, intensity borrowing by the low-energy charge-transfer states can affect intensities of the valence excitations even if those excitation energies are accurate. At higher excitation energies, it is difficult to distinguish spurious CT states from genuine charge-transfer-to-solvent (CTTS) excitations. In this work, we introduce an automated diabatization scheme that enables fast and effective screening of the CTTS acceptor space in bulk solution. Our procedure introduces the concept of “natural charge-transfer orbitals”, which provide a means to isolate characteristic pairs of orbitals that are most likely to participate in a CTTS excitation. The projection of these orbitals onto solvent-centered virtual orbitals provides a criterion for defining the most important solvent molecules in a given excitation. We apply this method to analyze an ab initio molecular dynamics (MD) trajectory of I-(aq) and report the lowest-energy CTTS band in the absorption spectrum. Our results are in excellent agreement with experimental measurements for bulk I-(aq), and only one-third of the water molecules in the I-(H2O)96 simulation cell need to be described with LR-TDDFT in order to obtain excitation energies that are converged to < 0.1 eV. The tools introduced herein will improve the accuracy, efficiency, and usability of LR-TDDFT in solution-phase environments

Carter-Fenk, Kevin D.↗
DOE OSTI2020

A non-perturbative pairwise-additive analysis of charge transfer contributions to intermolecular interaction energies

Energy decomposition analysis (EDA) based on absolutely localized molecular orbitals (ALMOs) decomposes the interaction energy between molecules into physically interpretable components like geometry distortion, frozen interactions, polarization, and charge transfer (CT, also sometimes called charge delocalization) interactions. In this work, a numerically exact scheme to decompose the CT interaction energy into pairwise additive terms is introduced for the ALMO-EDA using density functional theory. Unlike perturbative pairwise charge-decomposition analysis, the new approach does not break down for strongly interacting systems, or show significant exchange–correlation functional dependence in the decomposed energy components. Both the energy lowering and the charge flow associated with CT can be decomposed. Complementary occupied–virtual orbital pairs (COVPs) that capture the dominant donor and acceptor CT orbitals are obtained for the new decomposition. It is applied to systems with different types of interactions including DNA base-pairs, borane-ammonia adducts, and transition metal hexacarbonyls. While consistent with most existing understanding of the nature of CT in these systems, we report the results also reveal some new insights into the origin of trends in donor–acceptor interactions.

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

Data-driven method for electric vehicle charging demand analysis: Case study in Virginia

Electric vehicle (EV) adoption in the U.S. will be accelerated by the historic $7.5 billion public investments in EV charging infrastructure. Careful analysis of EV charging demands plays a vital role in understanding the energy requirements, power grid impact, and smart charging management opportunities of EVs. To this end, this paper develops a data-driven trip-chaining-based modeling framework including five steps: Trip data acquisition and preprocessing, EV adoption modeling, travel itinerary synthesis, EV charging demand simulation and EV load profile generation. The developed analysis framework was demonstrated using real-world data for one region in Virginia, U.S. The results show that the proposed modeling framework can work effectively. For the study region in 2040, the predicted number of plug-in EVs is 470,114, resulting in a weekly charging demand of 38,078,127 kWh (55% home, 9% work, and 36% public) in September and 45,920,358 kWh (61% home, 9% work, and 30% public) in February.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Apodization Specific Fitting for Improved Resolution, Charge Measurement, and Data Analysis Speed in Charge Detection Mass Spectrometry

Short-time Fourier transforms with short segment lengths are typically used to analyze single ion charge detection mass spectrometry (CDMS) data either to overcome effects of frequency shifts that may occur during the trapping period or to more precisely determine the time at which an ion changes mass or charge, or enters an unstable orbit. The short segment lengths can lead to scalloping loss unless a large number of zero-fills are used, making computational time a significant factor in real-time analysis of data. Apodization specific fitting leads to a 9-fold reduction in computation time compared to zero-filling to a similar extent of accuracy. This makes possible real-time data analysis using a standard desktop computer. Rectangular apodization leads to higher resolution than the more commonly used Gaussian or Hann apodization and makes it possible to separate ions with similar frequencies, a significant advantage for experiments in which the masses of many individual ions are measured simultaneously. Equally important is a >20% increase in S/N obtained with rectangular apodization compared to Gaussian or Hann, which directly translates to a corresponding improvement in accuracy of both charge measurements and ion energy measurements that rely on the amplitudes of the fundamental and harmonic frequencies. Finally, combined with computing the fast Fourier transform in a lower-level language, this fitting procedure eliminates computational barriers and should enable real-time processing of CDMS data on a laptop computer.

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

Overview of High-Power Wireless Charging Systems and Analysis of Polyphase Wireless Charging System Phase Winding and Resonant Tuning Network Connection Configurations

In spite of the high energy efficiency and environmental benefits of electric vehicles (EVs), adoption rates are increasing at a relatively slow pace, primarily because of EVs’ limited range and long charging durations. To reduce EV charging times to be comparable to refueling times of conventional vehicles, extreme fast charging systems are required. Such charging systems would reduce drivers’ range anxiety and enable long-distance interstate travel with EVs. Here, this substantial target in charging rates with 15–20 minutes of recharging times, requires research and development from grid to batteries with advanced charging systems. Wireless power transfer systems for EV charging applications are flexible, convenient, and highly efficient, and they allow automated charging. This paper reviews the power electronics and winding and resonant tuning network configurations for polyphase wireless power transfer systems for high-power wireless charging applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

High-pressure reduction of carbon dioxide in reactive liquid mixtures

Density-functional theory based molecular-dynamics simulations were used to investigate high-pressure chemical reactions in liquid mixtures of CO 2 with several elements (Si, Mn, and Fe) at high temperatures of 2000-3000 K. Our ab initio simulations indicate that these reactant elements can reduce CO 2 to C at high pressures (20 GPa) leading to the formation of C-C chains, with Si by far the most effective carbon-reducing agent. A combined chemical analysis using Bader charge analysis and Crystal Orbital Hamilton Population (COHP) on simulation snapshots shows that significant charge transfer from the reducing element to the C atoms creates instability in the C-O covalent bonds. COHP analysis further shows that Mn/Fe-O and Mn/Fe-C bonding interactions are weaker compared to the Si counterparts. These results further our understanding of the redox chemistry of CO 2 at conditions relevant to planetary mantle interiors and demonstrate the effectiveness of high pressure in the reduction of CO 2 directly to solid carbon.

Ab initio molecular dynamics↗
DOE OSTI2026

Continuing Analysis of Charge Current Interactions in ANNIE

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a gadolinium-loaded water Cherenkov detector on the Fermilab Booster Neutrino Beam (BNB).Using νμ in the energy range of 500 to 1000 MeV, ANNIE is designed to measure final-state neutrons.In this poster we will cover the ongoing analysis work exploring Charged-Current neutrino interactions. Charged-Current (CC) νμ interactions in this regime have uncertainties in the relative contributions of quasielastic and res- onance production. Together with intranuclear final-state interactions (FSI) and missing hadronic energy, these interactions drive important biases in neutrino energy reconstruction. ANNIE mit- igates these effects by combining muon kinematics from the downstream Muon Range Detector (MRD) with neutron identification via delayed gamma cascades from thermal captures on gadolin- ium. We characterize CC0π and Δ samples by measuring neutron multiplicity versus event topology and reconstructed kinematics, comparing neutron-tagged data to interaction-model predictions to probe resonance production and pion FSI/absorption

Fleming, Dylon [UC, Davis; Fermilab] (ORCID:000000↗
DOE OSTI2023

Electronic transport in copper–graphene composites

In this work, we investigate electronic transport properties of copper–graphene (Cu–G) composites using a density-functional theory (DFT) framework. Conduction in composites is studied by varying the interfacial distance of copper/graphene/copper (Cu/G/Cu) interface models. Electronic conductivity of the models computed using the Kubo–Greenwood formula shows that the conductivity increases with decreasing Cu–G distance and saturates below a threshold Cu–G distance. The DFT-based Bader charge analysis indicates increasing charge transfer between Cu atoms at the interfacial layers and the graphene with decreasing Cu–G distance. The electronic density of states reveals increasing contributions from both copper and carbon atoms near the Fermi level with decreasing Cu–G interfacial distance. By computing the space-projected conductivity of the Cu/G/Cu models, we show that the graphene forms a bridge to the electronic conduction at small Cu–G distances, thereby enhancing the conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Charge-trap analysis in a SENSEI skipper-CCD: Understanding low-energy backgrounds in rare-event searches

Skipper charge-coupled devices (CCDs) are ultralow-threshold detectors capable of detecting energy deposits in silicon at the electronvolt scale. Skipper CCDs are increasingly used in rare-event searches, including experiments such as SENSEI, DAMIC-M, Oscura, and CONNIE, where one of the major challenges is mitigating low-energy backgrounds. In this work, we present results on trap characterization in a silicon skipper-CCD produced in the same fabrication run as the SENSEI experiment at SNOLAB. Lattice defects contribute to backgrounds in rare-event searches through single-electron charge trapping. To investigate this, we use the charge-pumping technique at different temperatures to identify dipoles produced by traps in the CCD channel. We fully characterize a fraction of these traps and use this information to extrapolate their contribution to the single-electron background in SENSEI. We find that this subpopulation of traps does not contribute significantly, but more work is needed to assess the impact of the traps that cannot be characterized.

Brusco, Agustin↗
DOE OSTI2025

Charge Trap Analysis in a SENSEI Skipper-CCD: Understanding Low-Energy Backgrounds in Rare-Event Searches

Skipper Charge-Coupled Devices (Skipper-CCDs) are ultra-low-threshold detectors capable of detecting energy deposits in silicon at the eV scale. Increasingly used in rare-event searches, one of the major challenges in these experiments is mitigating low-energy backgrounds. In this work, we present results on trap characterization in a silicon Skipper-CCD produced in the same fabrication run as the SENSEI experiment at SNOLAB. Lattice defects contribute to backgrounds in rare-event searches through single-electron charge trapping. To investigate this, we employ the charge-pumping technique at different temperatures to identify dipoles produced by traps in the CCD channel. We fully characterize a fraction of these traps and use this information to extrapolate their contribution to the single-electron background in SENSEI. We find that this subpopulation of traps does not contribute significantly but more work is needed to assess the impact of the traps that can not be characterized.

Brusco, Agustin [Buenos Aires U.]↗
DOE OSTI2022

Effect of applied potential on metal surfaces: Surface energy, Wulff shape and charge distribution

Here we use grand canonical density functional theory to predict the surface energies, Wulff shapes, charge distributions and catalytically active sites of different metal surfaces under electrochemical conditions. We propose a method for computing surface energies from grand canonical density functional theory (GC-DFT) calculations of periodic slab models and use it to compute the surface energies of the facets of Pt, Cu, and Ag crystals to predict their Wulff shapes under electrochemical conditions. GC-DFT predicts that, for the pure metals studied, solvation only slightly affects the Wulff shape while applied potentials considerably affect the surface energies and corresponding Wulff shapes. We used Bader charge analysis of GC-DFT computed electron densities to investigate the effect of applied potential on the distribution of electron density over the atoms of the surfaces of Pt, Cu, Ag, and the 75–25 Ag-Pt and Au-Ni alloys. This analysis shows that, under an applied potential, the electron density is unevenly distributed over the surface atoms and that the charges of atoms more exposed to solvent are more sensitive to bias. Our results show that the most sensitive atom to bias can be used to identify the most favorable adsorption site and thus, the active sites of electrochemical reactions, which is computationally less demanding than calculating the adsorption energies on all possible adsorption sites.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Analysis of Electric Vehicle Charging Behavior Patterns with Function Principal Component Analysis Approach

This manuscript focused on analyzing electric vehicles’ (EV) charging behavior patterns with a functional data analysis (FDA) approach, with the goal of providing theoretical support to the EV infrastructure planning and regulation, as well as the power grid load management. 5-year real-world charging log data from a total of 455 charging stations in Kansas City, Missouri, was used. The focuses were placed on analyzing the daily usage occupancy variability, daily energy consumption variability, and station-level usage variability. Compared with the traditional discrete-based analysis models, the proposed FDA modeling approach had unique advantages in preserving the smooth function behavior of the data, bringing more flexibility in the modeling process with little required assumptions or background knowledge on independent variables, as well as the capability of handling time series data with different lengths or sizes. In addition to the patterns revealed in the EV charging station’s occupancy and energy consumption, the differences between EV driver’s charging time and parking time were analyzed and called for the needs for parking regulation and enforcement. The different usage patterns observed at charging stations located on different land-use types were also analyzed.

Engineering↗
DOE OSTI2024

Machine Learning for Predictive Performance Analysis in Charged Particle Beam Tools

Imaging methods driven by probes, electrons, and ions have played a dominant role in modern science and engineering. Opportunities for machine vision and AI that focus on consumer problems like driving and feature recognition, are now presenting themselves for automating aspects of the scientific processes. This proposal aims to enable and drive discovery in ultra-low energy implantation by taking advantage of faster processing, flexible control and detection methods, and architecture-agnostic workflows that will result in higher efficiency and shorter scientific development cycles. Custom microscope control, collection and analysis hardware will provide a framework for conducting novel in situ experiments revealing unprecedented insight into surface dynamics at the nanoscale. Ion implantation is a key capability for the semiconductor industry. As devices shrink, novel materials enter the manufacturing line, and quantum technologies transition to being more mainstream. Traditional implantation methods fall short in terms of energy, ion species, and positional precision. Here we demonstrate 1 keV focused ion beam Au implantation into Si and validate the results via atom probe tomography. We show the Au implant depth at 1 keV is 0.8 nm and that identical results for low energy ion implants can be achieved by either lowering the column voltage, or decelerating ions using bias – while maintaining a sub-micron beam focus. We compare our experimental results to static calculations using SRIM and dynamic calculations using binary collision approximation codes TRIDYN and IMSIL. A large discrepancy between the static and dynamic simulation is found that is due to lattice enrichment with high stopping power Au and surface sputtering. Additionally, we demonstrate how model details are particularly important to the simulation of these low-energy heavy-ion implantations. Finally, we discuss how our results pave a way to much lower implantation energies, while maintaining high spatial resolution.

47 OTHER INSTRUMENTATION↗