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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Power System Operational Impacts of Electric Vehicle Dynamic Wireless Charging

The electrification of the transportation sector poses an opportunity for reducing greenhouse gas (GHG) emissions from passenger vehicles. Electric vehicle (EV) charging through dynamic wireless power transfer (DWPT), known as roadway electrification, could shift EV demand profiles to better coincide with renewable electricity generation. However, this would be a very large new load and few studies evaluate the regional impacts of DWPT charging in a power transmission system. This paper defines methods that address dataset generation for passenger vehicle trips and models to evaluate regional impacts for this emerging technology. Household vehicle miles traveled (VMT) data form localized EV demand profiles through discrete-event simulation. This data serves as exogenous inputs for a Production Cost Model (PCM) of a synthetic transmission system based on the Electric Reliability Council of Texas's (ERCOT) network. EV charging methods are compared for both a 2018 baseline generation mixture and a high-renewable generation case incorporating 20 GW of installed solar photovoltaic (PV) capacity. The PCM employs unit commitment and economic dispatch (UC&ED) models to compare financial, environmental, and grid reliability impacts from EV charging across passenger EV adoption levels. In-transit charging could reduce grid operational costs by as much as 1.49%, with up to $13.7B saved in annual vehicle operational costs for consumers compared to gas-powered vehicles. Health impacts analysis from power plant and vehicle tailpipe emissions from this study show net health benefits increase by 40% for in-transit charging coupled with high renewable generation. Renewable resources provide an avenue for cost-effective in-transit charging with reduced emissions. The combination of dataset generation and open-source power system modeling establish a foundation for the holistic evaluation of regional DWPT impacts.

dynamic wireless power transfer↗
DOE OSTI2022

Reducing Uncertainty of Fielded Photovoltaic Performance (Final Technical Report)

Improved analysis and reporting of photovoltaic (PV) field performance increases the certainty of owners and financiers that systems will perform as expected. Advanced module technologies (e.g., PERC, HJT, and bifacial) introduce new degradation mechanisms and performance characteristics. The FY19-21 Reducing Uncertainty project leveraged data from the ever-increasing PV fleet to develop models and understanding of the field performance of existing and new technologies. Specifically, we accomplished: report on field performance and degradation rates for high-efficiency silicon (HJT, PERC, IBC) and more conventional technologies; developed automated analysis techniques to quantify system performance (performance ratio, energy yield) and production shortfalls (soiling, degradation, availability); refined the RdTools software toolkit to bring standard, validated analysis techniques to bear on third-party data; analyzed and reported on large datasets including Treasury data and Lawrence Berkeley National Laboratory's Utility-Scale dataset to expand the high-quality degradation-rate histogram published previously; worked with industry partners and the DuraMAT data hub to enable private parties to share and aggregate PV production data anonymously, leveraging cloud-based data analysis infrastructure and publishing on US fleet-scale performance comprising over 7GW of operating systems. (https://www.nrel.gov/pv/fleet-performance-data-initiative.html). Through our industry collaborations we have engaged in NDA-covered data transfer with twelve PV fleet owners as of January 2022, with more agreements in negotiation. Our scalable cloud-based time series database contains over 30 billion rows (20TB) of PV time series data, representing over 1700 commercial and utility-scale systems, and over 7.2 GW of DC capacity (Fig 1). Initial field performance results have been distributed in several public reports. Because our fleet composition and data quality methods are continually improving, annual updates to these results are published to our PV Fleet webpage [ https://www.nrel.gov/pv/fleet-performance-data-initiative.html ] and DuraMAT data hub [DOI: 10.21948/1842958]. Another existing dissemination channel used for observed soiling losses is a map we maintain for soiling losses. Additional products developed include a report detailing fleet-wide performance index, availability, startup loss and snow loss factors, a detailed report on the 1603 grant dataset comprising over 100,000 PV systems with failure and performance details and a utility-scale report coauthored with LBNL on 31 GW of system performance.

14 SOLAR ENERGY↗
DOE OSTI2025

Potential of deep learning methods to enhance satellite-based monitoring of nuclear power plants focusing on remote operation evaluations

The anticipated expansion of the nuclear industry and the deployment of new nuclear reactors (200 + GW of new nuclear capacity by 2050) require the development of monitoring systems that align with safety and security concerns, providing enhanced evaluation capabilities. A remote monitoring system using satellites and deep learning techniques was evaluated for its ability to detect anomalies and capture various features of nuclear reactors independently of the conditions on the ground. Satellite images of current operational and under-construction nuclear power plants were collected from Google Earth Pro as a surrogate database. Subsequently, five datasets were created from the collected images. Transfer learning technique was used for several classification tasks utilizing VGG16, ResNet50V2, Xception, DenseNet121, and MobileNetV2 pre-trained models. In the first task, the capability of the monitoring system to detect abnormal conditions or processes in a nuclear power plant was investigated. In the second task, the ability to capture operational features remotely was examined. As an example, for the purposes of this study, these features included classifying reactors based on type, power range, or onsite condition. Several evaluation metrics were used to compare the performance of the pre-trained models and the overall monitoring system. Here, the evaluation results demonstrated that deep learning techniques and pre-trained models applied to satellite images have the potential to facilitate further and expand capabilities in monitoring systems to assess plant operation details.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Many-body enhancement of high-harmonic generation in monolayer MoS2

Abstract Many-body effects play an important role in enhancing and modifying optical absorption and other excited-state properties of solids in the perturbative regime, but their role in high harmonic generation (HHG) and other nonlinear response beyond the perturbative regime is not well-understood. We develop here an ab initio many-body method to study nonperturbative HHG based on the real-time propagation of the non-equilibrium Green’s function with the GW self energy. We calculate the HHG of monolayer MoS 2 and obtain good agreement with experiment, including the reproduction of characteristic patterns of monotonic and nonmonotonic harmonic yield in the parallel and perpendicular responses, respectively. Here, we show that many-body effects are especially important to accurately reproduce the spectral features in the perpendicular response, which reflect a complex interplay of electron-hole interactions (or exciton effects) in tandem with the many-body renormalization and Berry curvature of the independent quasiparticle bandstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Closed-Loop Pumped Storage Hydropower Resource Assessment for the United States. Final Report on HydroWIRES Project D1: Improving Hydropower and PSH Representations in Capacity Expansion Models

Pumped storage hydropower represents the bulk of the United States' current energy storage capacity: 23 gigawatts (GW) of the 24-GW national total (Denholm et al. 2021). This capacity was largely built between 1960 and 1990. PSH is a mature and proven method of energy storage with competitive round-trip efficiency and long life spans. These qualities make PSH a very attractive potential solution to energy storage needs, particularly for longer-duration storage (8 hours or more); such storage will be crucial to bridge gaps in electricity production as variable wind and solar production continue to comprise an ever-larger portion of the United States' energy portfolio (Cole et al. 2021; Frazier et al. 2021). However, it is unclear how much potential the United States has for the development of new PSH. No new large PSH has been constructed in the United States since the 1990s, and attempts to quantify technical potential capacity from PSH project applications to the Federal Energy Regulatory Commission (FERC) suffer from inconsistent site and cost evaluation methodologies and likely are not representative of all PSH opportunities. This study seeks to better under understand the technical potential for PSH development in the United States by developing a national-scale resource assessment for closed-loop PSH. Individual sites are not modeled in sufficient detail for project-level development, but they do provide valuable insights into potential resource areas across the United States, including the ability to provide estimates for a range of long-term development scenarios.

13 HYDRO ENERGY↗
DOE OSTI2022

Closed Loop Pumped Storage Hydropower Resource Assessment of the United States

The data includes a geospatial and spreadsheet representation of a resource analysis for closed loop pumped storage systems across the Continental United States, Alaska, Hawaii, and Puerto Rico. The data includes energy storage potential, water volume, distance from source to storage, hydraulic head, dollars per kilowatt of storage, and transmission spurline cost for each pumped storage hydropower (PHS) reservoir. Each reservoir represented in this dataset is represented on potential 10 hour storage duration PSH system comprised of two reservoirs. Units of measure are laid out in the dataset. Pumped storage hydropower (PSH) represents the bulk of the United States' current energy storage capacity: 23 gigawatts (GW) of the 24 GW national total (Denholm et al. 2021). This capacity was largely built between 1960 and 1990. PSH is a mature and proven method of energy storage with competitive round-trip efficiency and long life spans. These qualities make PSH a very attractive potential solution to energy storage needs, particularly for longer-duration storage (8 hours or more); such storage will be crucial to bridge gaps in electricity production as variable wind and solar production continue to comprise an ever-larger portion of the United States' energy portfolio. This study seeks to better understand the technical potential for PSH development in the United States by developing a national-scale resource assessment for closed-loop PSH. For more information, please refer to the Closed Loop Pumped Storage Hydropower Resource Assessment for the United States linked in the resources.

Array↗
DOE OSTI2026

Direct inference of nuclear equation-of-state parameters from gravitational-wave observations

The observation of neutron star mergers with gravitational waves (GWs) has provided a new method to constrain the dense-matter equation of state (EOS) and to better understand its nuclear physics. However, inferring nuclear microphysics from GW observations necessitates the sampling of EOS model parameters that serve as input for each EOS used during the GW data analysis. The sampling of the EOS parameters requires solving the Tolman–Oppenheimer–Volkoff (TOV) equations a large number of times—a process that slows down each likelihood evaluation in the analysis on the order of a few seconds. Here, we employ emulators for the TOV equations built using multilayer perceptron neural networks to enable direct inference of nuclear EOS parameters from GW strain data. Our emulators allow us to rapidly solve the TOV equations, taking in EOS parameters and outputting the associated tidal deformability of a neutron star in only a few tens of milliseconds. We implement these emulators in PyCBC to directly infer the EOS parameters using the event GW170817, providing posteriors on these parameters informed solely by GWs. We benchmark these runs against analyses performed using the full TOV solver and find that the emulators achieve speed ups of nearly two orders of magnitude, with negligible differences in the recovered posteriors. Additionally, we constrain the slope and curvature of the symmetry energy at the 90% upper credible interval to be $L$ sym ≲ 106 MeV and $K$ sym ≲ 26 MeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Optoelectronic properties of bent two-dimensional materials from first-principles methods combined with machine learning

A material’s interaction with light is highly relevant in the design of nanoelectronic devices such as photodiodes, solar cells, photocatalytic cells, phototransistors, and photodetectors. The interaction of a material with light can be altered by mechanical deformation. Fine tuning of the optical properties can be achieved by mechanical bending that alters the electronic structure. Optical properties strongly depend on band gaps, therefore any alteration in the band structure results in a changed optical response of the material. The impact of bending was explored in this project. The goal of this project was to assess the impact of mechanical bending of two-dimensional transition metal dichalcogenides on their optoelectronic properties, using first-principles methods. These first-principles approximations are largely built upon many-body theory for the optical properties of magnetic and topological nanoribbons. GW-BSE is standard for optical absorption, but it is less practical for collective excitations as it was shown in model systems. Time-dependent density functional theory, however, has better promises for collective excitations in low-dimensional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Real-space representation of the quasiparticle self-consistent GW self-energy and its application to defect calculations

The quasiparticle self-consistent (QS) GW (G for Green's function, W for screened Coulomb interaction) approach incorporates the corrections of the quasiparticle energies from their Kohn-Sham density functional theory (DFT) eigenvalues by means of an energy-independent and Hermitian self-energy matrix usually given in the basis set of the DFT eigenstates. By expanding these into an atom-centered basis set (specifically here the linearized muffin-tin orbitals) a real space representation of the self-energy corrections becomes possible. In this work, We show that this representation is relatively short-ranged. This offers opportunities to construct the self-energy of a complex system from parts of the system by a cut-and-paste method. Specifically for a point defect, represented in a large supercell, the self-energy can be constructed from those of the host and a smaller defect-containing cell. The self-energy of the periodic host can be constructed simply from a GW calculation for the primitive cell. We show for the case of the As Ga in GaAs that the defect part can already be well represented by a minimal eight-atom cell and allows us to construct the self-energy for a 64-atom cell in good agreement with direct QSGW calculations for the large cell. Using this approach to an even larger 216-atom cell shows the defect band approaches an isolated defect level. The calculations also allow us to identify a second defect band which appears as a resonance near the conduction band minimum. The results on the extracted defect levels agree well with Green's function calculations for an isolated defect and with experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Stochastic GW -GPU: Rapid Quasi-Particle Energies for Molecules beyond 10,000 Atoms

StochasticGW is a code for computing accurate quasi-particle (QP) energies of molecules and material systems in the GW approximation. StochasticGW utilizes the stochastic Resolution of the Identity (sROI) technique to enable a massively parallel implementation with computational costs that scale semilinearly with system size, allowing the method to access systems with tens of thousands of electrons. Here, we introduce a new implementation, StochasticGW-GPU, for which the main bottleneck steps have been ported to GPUs and give substantial performance improvements over previous versions of the code. We showcase the new code by computing band gaps of hydrogenated silicon clusters (Si x H y ) containing up to 10,001 atoms and 35,144 electrons, and we obtain individual QP energies with a statistical precision of better than ±0.03 eV with times-to-solution of less than 1 h.

Thomas, Phillip S. [Lawrence Berkeley National Lab↗
DOE OSTI2024

GPAW: An open Python package for electronic structure calculations

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe–Salpeter Equation, variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn–Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support for graphics processing unit (GPU) acceleration has been achieved with minor modifications to the GPAW code thanks to the CuPy library. We end the review with an outlook, describing some future plans for GPAW.

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

Comprehensive Study of Carrier Recombination in High‐Efficiency CdTe Solar Cells Using Transient Photovoltage

Cadmium telluride (CdTe) solar cells represent a commercially successful photovoltaic technology, with an annual production capacity approaching 20 GW. However, improving the open-circuit voltage (V OC ) remains challenging. This study aims to deepen the understanding of charge carrier recombination in CdTe solar cells and to explore alternative dynamical characterization methods that address the limitations found in conventionally used time-resolved photoluminescence for CdTe solar cells. Transient photovoltage and transient photocurrent techniques are utilized to investigate charge carrier dynamics under conditions resembling real-world solar cell operation. The results reveal that an effective nonradiative recombination lifetime of 580 ns dominates the charge dynamics at VOC values below 850 mV. Above this threshold, radiative recombination becomes significant, with a radiative recombination coefficient of 1.1 × 10 −9 cm 3 s −1 . Additionally, the stationary charge carrier density at 1 sun is determined to be around 1 × 10 14 cm −3 . By accurately determining both radiative and nonradiative recombination, this work provides a comprehensive understanding of carrier dynamics in high-performing CdTe devices and paves the way for improving the V OC and performance of CdTe solar cells.

CdTe solar cells↗
DOE OSTI2022

Bending as a control knob for the electronic and optical properties of phosphorene nanoribbons

We have assessed mechanical bending as a powerful controlling tool for the electronic structure and optical properties of phosphorene nanoribbons. We use state-of-the-art density functional approximations in our work. The overall performance of the recently developed meta-generalized gradient approximation (meta-GGA) mTASK [Phys. Rev. Materials 5, 063803 (2021)] functional establishes the method as a useful alternative to the screened hybrid HSE06 for better band gaps of phosphorene nanoribbons. We present a detailed analysis to interpret the optical absorption of bent phosphorene nanoribbons using the GW-Bethe-Salpeter approximation. Finally, we demonstrate the important role of the unoccupied in-gap state and conclude that this in-gap state in armchair nanoribbons introduced by bending can significantly affect the properties of low-energy excitons and add some useful opportunities for applications in optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A new probe of μ Hz gravitational waves with FRB timing

We propose Fast Radio Burst (FRB) timing, which uses the precision measurements of the arrival time differences of repeated FRB signals along multiple sightlines, as a new probe of gravitational waves (GWs) around nHz to μHz frequencies, with the highest frequency limited by FRB repeating period. The anticipated experiment requires a sightline separation of tens of AU, achieved by sending radio telescopes to space. We find the signal of arrival time difference induced by GWs depends only on the local GWs in the solar system and we can correlate the measurements from different FRB sources or the same source with different repeaters, which leads to a better sensitivity with a larger number of FRB repeaters detected. Here, the projected sensitivity shows this method is a competitive probe in the nHz to μ Hz frequency range. It can fill the 'μHz gap' between pulsar timing arrays and Laser Interferometer Space Antenna (LISA) and is complementary to other proposals of GW detection in this frequency band.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A new probe of μ Hz gravitational waves with FRB timing

We propose Fast Radio Burst (FRB) timing, which uses the precision measurements of the arrival time differences of repeated FRB signals along multiple sightlines, as a new probe of gravitational waves (GWs) around nHz to μ Hz frequencies, with the highest frequency limited by FRB repeating period. The anticipated experiment requires a sightline separation of tens of AU, achieved by sending radio telescopes to space. We find the signal of arrival time difference induced by GWs depends only on the local GWs in the solar system and we can correlate the measurements from different FRB sources or the same source with different repeaters, which leads to a better sensitivity with a larger number of FRB events detected. The projected sensitivity shows this method is a competitive probe in the nHz to μ Hz frequency range. It can fill the ‘ μ Hz gap’ between pulsar timing arrays and Laser Interferometer Space Antenna (LISA) and is complementary to other proposals of GW detection in this frequency band.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Electronic structure and optical properties of halide double perovskites from a Wannier-localized optimally-tuned screened range-separated hybrid functional

Halide double perovskites are a chemically diverse and growing class of compound semiconductors that are promising for optoelectronic applications. However, the prediction of their fundamental gaps and optical properties with density functional theory (DFT) and ab initio many-body perturbation theory has been a significant challenge. Recently, a nonempirical Wannier-localized optimally tuned screened range-separated hybrid (WOT-SRSH) functional has been shown to accurately produce the fundamental band gaps of a wide set of semiconductors and insulators, including lead halide perovskites. Here, in this study, we apply the WOT-SRSH functional to five halide double perovskites and compare the results with those obtained from other known functionals and previous GW calculations. We also use the approach as a starting point for GW calculations and we compute the band structures and optical absorption spectrum for Cs 2 AgBiBr 6 , using both time-dependent DFT and the GW-Bethe-Salpeter equation approach. We show that the WOT-SRSH functional leads to accurate fundamental and optical band gaps, as well as optical absorption spectra, consistent with spectroscopic measurements, thereby establishing WOT-SRSH as a viable method for the accurate prediction of optoelectronic properties of halide double perovskites.

36 MATERIALS SCIENCE↗
DOE OSTI2024

GPU-Accelerated Solution of the Bethe–Salpeter Equation for Large and Heterogeneous Systems

We present a massively parallel GPU-accelerated implementation of the Bethe–Salpeter equation (BSE) for the calculation of the vertical excitation energies (VEEs) and optical absorption spectra of condensed and molecular systems, starting from single-particle eigenvalues and eigenvectors obtained with density functional theory. The algorithms adopted here circumvent the slowly converging sums over empty and occupied states and the inversion of large dielectric matrices through a density matrix perturbation theory approach and a low-rank decomposition of the screened Coulomb interaction, respectively. Further computational savings are achieved by exploiting the nearsightedness of the density matrix of semiconductors and insulators to reduce the number of screened Coulomb integrals. We scale our calculations to thousands of GPUs with a hierarchical loop and data distribution strategy. The efficacy of our method is demonstrated by computing the VEEs of several spin defects in wide-band-gap materials, showing that supercells with up to 1000 atoms are necessary to obtain converged results. We discuss the validity of the common approximation that solves the BSE with truncated sums over empty and occupied states. In conclusion, we then apply our GW-BSE implementation to a diamond lattice with 1727 atoms to study the symmetry breaking of triplet states caused by the interaction of a point defect with an extended line defect.

Absorption spectra↗
DOE OSTI2024

Interplay of coulomb and exciton–phonon coupling controls singlet fission dynamics in two pentacene polymorphs

Pentacene is an important model organic semiconductor in both the singlet exciton fission (SF) and organic electronics communities. We have investigated the effect of changing crystal structure on the SF process, generating multiple triplet excitons from an initial singlet exciton, and subsequent triplet recombination. Unlike for similar organic semiconductors that have strong SF sensitive to polymorphism, we find almost no quantitative difference between the kinetics of triplet pair (TT) formation in the two dominant polymorphs of pentacene. Both pairwise dimer coupling and momentum-space crystal models predict much faster TT formation from the bright singlet excited state of the Bulk vs ThinFilm polymorph, contrasting with the experiment. GW and Bethe–Salpeter equation calculations, including exciton–phonon coupling, reveal that ultrafast phonon-driven transitions in the ThinFilm polymorph compensate the intrinsically slower purely Coulomb-mediated TT formation channel, rationalizing the similarity in observed rates. Taking into account the influence of subtle structural distinctions on both the direct and phonon-mediated SF pathways reveals a predictive capability to these methods, expected to be applicable to a wide variety of molecular crystals.

14 SOLAR ENERGY↗