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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 145 records · Page 8

Energy momentum tensor on and off the light cone: exposition with scalar Yukawa theory

Abstract We compute the gravitational form factorsA i ,D i and$$ {\overline{c}}_i $$ c ¯ i of the scalar Yukawa theory using both the light-cone and covariant perturbation theory at the one-loop level. The light-cone formalism provides a potential approach to access these form factors beyond the perturbative regime. However, unlike the covariant formulation, the Poincaré symmetry on the light cone is not manifest. In this work, we use perturbation theory as a benchmark to extract the gravitational form factors from the light-front energy-momentum tensor. By comparing results on and off the light cone, we identifyT ++ ,T +a ,T +− ,T 12 as the “good currents” that are properly renormalized and can be used to extract the gravitational form factors.

Physics↗

Modeling and Simulation of Electrostatics of Ge$_{\text{1-x}}$Sn$_{\text{x}}$ Layers Grown on Ge Substrates

This work introduces a comprehensive simulation tool that provides a robust 1D Schrödinger – Poisson solver for modeling the electrostatics of heterostructures with an arbitrary number of layers, and non-uniform doping profiles along with the treatment of partial ionization of dopants at low temperatures. The effective masses are derived from the first-principles calculations. The solver is used to characterize three Ge 1-x Sn x /Ge heterostructures with non-uniform doping profiles and determine the subband structure at various temperatures. Here, the simulation results of the sheet carrier densities show excellent agreement with the experimentally extracted data, thus demonstrating the capabilities of the solver.

42 ENGINEERING↗

Emergent unitarity, all-loop cuts and integrations from the ABJM amplituhedron

We elaborate on aspects of a new positive geometry proposed recently, which was conjectured to be the four-point amplituhedron for ABJM theory. We study generalized unitarity cuts from the geometry, and in particular we prove that (1) the four-point integrand satisfies perturbative unitarity (or optical theorem) to all loops, which follows directly from the geometry, and (2) vanishing cuts involving odd-point amplitudes follow from the “bipartite” nature of the associated “negative geometries”, which justifies their appearance in ABJM theory. We also take a first step in integrating the forms of these negative geometries and obtain an infrared-finite quantity up to two loops, from which we extract the cusp anomalous dimension at leading order.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ab initio single-neutron spectroscopic overlaps in lithium isotopes

We calculate single-neutron spectroscopic overlaps for lithium isotopes in the framework of the ab initio symmetry-adapted no-core shell model. We report the associated neutron-nucleus asymptotic normalization coefficients (ANCs) and spectroscopic factors (SFs) that are important ingredients in many reaction cross-section calculations. While spectroscopic factors have been traditionally extracted from experimental cross sections, their sensitivity on the type of reactions, the energy, and the underlying models point to the need for determining SFs from first-principle structure considerations. As illustrative examples, we present 6 Li + n, 7 Li ⁢+ n, and 8 Li ⁢+ n, and we show that the results are in a good agreement with those of other ab initio methods, where available, including the quantum Monte Carlo approach. Here, we compare ANCs and SFs to available experimentally deduced values, with a view toward expanding this study to heavier nuclei and to extracting intercluster effective interactions for input into analyses of existing and future experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Ion pair extractant selective for LiCl and LiBr

Improved methods for achieving the selective extraction of lithium salts from lithium sources, including rocky ores, salt-lake brines, and end-of-life lithium-ion batteries, could help address projected increases in the demand for lithium. Here, we report an ion pair receptor (2) capable of extracting LiCl and LiBr into an organic receiving phase both from the solid state and from aqueous solutions. Ion pair receptor 2 consists of a calix[4]pyrrole framework, which acts as an anion binding site, linked to a phenanthroline cation binding motif via ether linkages. Receptor 2 binds MgBr 2 and CaCl 2 with high selectivity over the corresponding lithium salts in a nonpolar aprotic solvent. The preference for Mg 2+ and Ca 2+ salts is reversed in polar protic media, allowing receptor 2 to complex LiCl and LiBr with high selectivity and affinity in organic media containing methanol or water. The effectiveness of receptor 2 as an extractant for LiCl and LiBr under liquid–liquid extraction (LLE) conditions was found to be enhanced by the presence of other potentially competitive salts in the aqueous source phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesizing Lithium Sorbents Using Acid Mine Drainage Solids

In this study, we prepared HMO from coal mine drainage (CMD) solids and examined the practicability of recovering Li from oil and gas produced waters and geothermal brines. We aim to innovate high-value added products from the existing extract REEs and CMs processing chain of legacy byproducts associated with coal production. CMD solids, which are precipitates collected from exhausted limestone gravels of passive CMD treatment beds, are enriched in rare earth elements (REEs) and other critical minerals (CMs), and therefore, considered as a viable alternative source for REEs/CMs to supply the Nation’s demands. A patented extraction process developed by NETL (TREE) has been demonstrated as a cost-effective and efficient approach to recover REEs/CMs from CMD solids. Here, we selected residuals of CMD solids from the TREE process that are enriched in manganese (Mn) (>20% w/w) and successfully prepared LMO using a solid-state method modified from Yoshizuka et al. (2002).

Cheng, Chin-Min↗

High Throughput Laser Processing for Enhanced Battery Performance and Manufacturing

For widespread adoption of electric vehicles, lithium-ion batteries (LiBs) need to achieve energy densities of >275 Wh/kg, cell costs less than $100/kWh, and charge to more than 80% capacity within 15 minutes. Recently, it has been shown that introducing a secondary pore network in thick battery electrodes enables higher extracted capacity without a severe reduction in charge/discharge rate performance. Secondary pore networks consisting of ordered arrays of microstructures reduce tortuosity of Li+-ion transport deep into the thick electrodes, diminishing detrimental concentration gradients within the cell. Ultrafast (femtosecond)-pulsed laser ablation is a promising method to introduce such micro pores or channels in thick battery electrodes as it allows for precise control of pattern geometries, results in minimal damage to the electrode, and can be introduced into existing roll-to-roll electrode manufacturing lines. We have explored laser patterning to create secondary pore networks in a variety of battery electrode materials for both anode and cathode applications and characterized the laser-material interaction parameters. In addition, advanced materials characterization techniques (SEM-EDS, XRD) were used to explore whether ultrafast laser ablation affects the remaining electrode materials' morphology and structure. Furthermore, we have translated lab-scale laser ablation to high-throughput roll-to-roll processing at industrially relevant scales. Finally, we worked with Argonne National Laboratory, developers of the battery cost-analysis package BatPac, to estimate the additional manufacturing costs (CapEx and OpEx) for incorporation of laser-ablation processing to current battery electrode manufacturing. We estimate that ultrafast laser processing will add only -$1kWh, which for considerable improvements in cell performance, creates a compelling case for industry adoption.

battery↗

Investigation of enhanced CO 2 storage in deep saline aquifers by WAG and brine extraction in the Minnelusa sandstone, Wyoming

Geological CO 2 sequestration in deep saline aquifers has been extendedly investigated to reach the goal of carbon neutral as large amount of CO 2 can be reduced in a short time. Here, this study investigates the feasibility of water-alternating-gas (WAG) injection and brine extraction on enhancing CO 2 storage in a target deep saline aquifer, Minnelusa Sandstone in the Powder River Basin (PRB) of Wyoming. An integrated numerical model is developed to account for four scenarios: (1) CO 2 continuous injection (CI) through one injection well, (2) WAG injection through one injection well, (3) CO 2 CI through one injection well and brine extraction through one producer, (4) WAG injection through one injection well and brine extraction through one producer. Simulation results suggest that WAG injection and brine extraction corporately make it possible to enhance CO 2 injectivity while securing CO 2 storage safety. For instance, WAG injection considerably reduces structural trapping contribution while enhances dissolved and residual trapping contributions. As for brine extraction, it can decrease the maximum averaged reservoir pressure by 37% and 22% for CI and WAG injection, respectively. Besides, sensitive analyses of the operational parameters for the fourth scenarios are performed. Results reveal that, when the amount of total CO 2 injection has been predetermined, CO 2 injection time and rate within each period of WAG should be small whereas it is preferable to have large water injection time and rate. This is to secure desirable dissolved and residual trapping contributions (store CO 2 with safety). Sensitive degree results confirm that CO 2 injection rate, water injection time, and CO 2 injection time of WAG injection exhibit significant effects on CO 2 storage whereas the impacts of producer bottom-hole pressure (BHP), water injection rate, and CO 2 -water injection time are relatively weaker. This study not only sheds light on achieving double-win goal: enhance CO 2 injectivity and store CO 2 with safety, but also can be a critical reference for other CO 2 storage in deep saline aquifers.

58 GEOSCIENCES↗

Determining circuit model parameters from operation data for PV system degradation analysis: $\mathrm{PVPRO}$

Physics-based circuit parameters like series and shunt resistance are essential to provide insights into the degradation status of photovoltaic (PV) arrays. However, calculating these parameters typically requires a full current-voltage characteristic (I-V curve), the acquisition of which involves specific measurement devices and costly methods. Thus, I-V curves of the PV system level are often not available. Here this paper proposes a methodology (PVPRO) to estimate these I-V curve parameters using only operation (string-level DC voltage and current) and weather data (irradiance and temperature). PVPRO first performs multi-stage data pre-processing to remove noisy data. Next, the time-series DC data are used to fit an equivalent circuit single-diode model (SDM) to estimate the circuit parameters by minimizing the differences between the measured and estimated values. In this way, the time evolutions of the SDM parameters are obtained. We evaluate PVPRO on synthetic datasets and find an excellent estimation of both SDM and the key I-V parameters (e.g., open-circuit voltage, short-circuit current, maximum power, etc.) with an average relative error of 0.55%. The performance, especially the extracted degradation rate of parameters, is robust to various measurement noises and the presence of faults. In addition, PVPRO is applied to a 271 kW PV field system. The relative error between the real and estimated operation voltage and current is less than 1%, suggesting that degradation trends are well captured. PVPRO represents a promising open-source tool to extract the time-series degradation trends of key PV parameters from routine operation data.

14 SOLAR ENERGY↗

Bayesian Neural Network Variational Autoencoder Inverse Mapper (BNN-VAIM) and its application in Compton Form Factors extraction

Abstract We extend the Variational Autoencoder Inverse Mapper (VAIM) framework for the inverse problem of extracting Compton Form Factors (CFFs) from deeply virtual exclusive reactions, such as the unpolarized Deeply virtual exclusive scattering (DVCS) cross section. VAIM is an end-to-end deep learning framework to address the solution ambiguity issue in ill-posed inverse problems, which comprises of a forward mapper and a backward mapper to simulate the forward and inverse processes, respectively. In particular, we incorporate Bayesian Neural Network (BNN) into the VAIM architecture (BNN-VAIM) for uncertainty quantification. By sampling the weights and biases distributions of the BNN in the backward mapper of the VAIM, BNN-VAIM is able to estimate prediction uncertainty associated with each individual solution obtained for an ill-posed inverse problem. We first demonstrate the uncertainty quantification capability of BNN-VAIM in a toy inverse problem. Then, we apply BNN-VAIM to the inverse problem of extracting 8 CFFs from the unpolarized DVCS cross section.

Instruments & Instrumentation↗