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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Measured and satellite-derived albedo data for estimating bifacial photovoltaic system performance

The albedo of the ground surface is an important factor in the cost-effectiveness of a bifacial photovoltaic (PV) system. To improve the availability of reliable albedo data, datasets of ground albedo and associated meteorological data were developed by using existing measurement network data and data measured by the PV industry. The measured datasets include time-series data as well as summary information of tabular monthly and yearly data and plots of monthly and hourly albedo values. Satellite-derived values of albedo are available from the National Solar Radiation Data Base (NSRDB). The NSRDB albedos were compared to the measured albedos for Surface Radiation budget (SURFRAD) network locations for the period 2001–2017, and the mean bias difference results were from -0.044 to +0.056. Overall, these differences are greater than the albedo measurement uncertainty of ±0.02; consequently, the NSRDB albedos should be used with caution for estimating the performance of bifacial PV systems. Differences between SURFRAD and NSRDB albedos are attributed to the NSRDB method for determining albedo and to the ground surfaces within the NSRDB 4 km spatial resolution pixel consisting of a mixture of surface types rather than just the single surface types viewed by the albedometers at the SURFRAD stations.

14 SOLAR ENERGY↗
DOE OSTI2021

TESS Hunt for Young and Maturing Exoplanets (THYME). IV. Three Small Planets Orbiting a 120 Myr Old Star in the Pisces–Eridanus Stream

Young exoplanets can offer insight into the evolution of planetary atmospheres, compositions, and architectures. We present the discovery of the young planetary system TOI 451 (TIC 257605131, Gaia DR2 4844691297067063424). TOI 451 is a member of the 120 Myr old Pisces–Eridanus stream (Psc–Eri). We confirm membership in the stream with its kinematics, its lithium abundance, and the rotation and UV excesses of both TOI 451 and its wide-binary companion, TOI 451 B (itself likely an M-dwarf binary). We identified three candidate planets transiting in the Transiting Exoplanet Survey Satellite data and followed up the signals with photometry from Spitzer and ground-based telescopes. The system comprises three validated planets at periods of 1.9, 9.2, and 16 days, with radii of 1.9, 3.1, and 4.1 R {sub ⨂}, respectively. The host star is near-solar mass with V = 11.0 and H = 9.3 and displays an infrared excess indicative of a debris disk. The planets offer excellent prospects for transmission spectroscopy with the Hubble Space Telescope and the James Webb Space Telescope, providing the opportunity to study planetary atmospheres that may still be in the process of evolving.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Recent Experiences Calculating g-functions for Use in Simulation of Ground Heat Exchangers

Temperature response functions, known as g-functions, are a computationally efficient method for simulating ground heat exchangers (GHEs), used with ground-source heat pump (GSHP) systems, either as part of a whole-building energy simulation or as part of a dedicated ground heat exchanger design tool. In fact, at present, they are the only feasible way to simulate a ground-source heat pump system in a whole-building energy simulation. This paper summarizes recent developments in the field and recent experience using a new open-source g-function calculation tool known as pygfunction (Cimmino 2018a, 2018b). This experience includes accuracy, computation time, memory requirements and sensitivity to boundary conditions. With larger ground heat exchangers, e.g. in excess of 100 boreholes, the computational time and memory requirements can create challenges.

Spitler, Jeffery↗
DOE OSTI2024

Quantum chaos on edge

Recently, the physics of many-body quantum chaotic systems close to their ground states has come under intensified scrutiny. Such studies are motivated by the emergence of model systems exhibiting chaotic fluctuations throughout the entire spectrum [the Sachdev-Ye-Kitaev (SYK) model being a renowned representative] as well as by the physics of holographic principles, which likewise unfold close to ground states. Interpreting the edge of the spectrum as a quantum critical point, here we combine a wide range of analytical and numerical methods to the identification and comprehensive description of two different universality classes: the near edge physics of “sparse” and the near edge of “dense” chaotic systems. The distinction lies in the ratio between the number of a system's random parameters and its Hilbert space dimension, which is exponentially small or algebraically small in the sparse and dense case, respectively. Notable representatives of the two classes are generic chaotic many-body models (sparse) and invariant random matrix ensembles or chaotic gravitational systems (dense). While the two families share identical spectral correlations at energy scales comparable to the level spacing, the density of states and its fluctuations near the edge are different. Considering the SYK model as a representative of the sparse class, we apply a combination of field theory and exact diagonalization to a detailed discussion of its edge spectrum. Conversely, Jackiw-Teitelboim gravity is our reference model for the dense class, where an analysis of the gravitational path integral and random matrix theory reveal universal differences to the sparse class, whose implications for the construction of holographic principles we discuss. Published by the American Physical Society 2024

Altland, Alexander (ORCID:0000000229914805)↗
DOE OSTI2025

Ground Truth for CSP Mirror Metrology (Full-Length)

The high optical accuracy required for concentrating solar power (CSP) systems in turn requires accurate metrology to assess mirror optical parameters during design, manufacturing, and operation. To meet this need, researchers have developed a variety of CSP optical metrology systems, which include complex calculations and calibration terms. This raises the question: How do we know these methods’ accuracy? One approach is to compare metrology system measurements against a ground truth reference.

14 SOLAR ENERGY↗
DOE OSTI2026

Artificial Intelligence in Nuclear Safeguards; Evaluating Safeguards and Security Risks and Benefits for Advanced and Small Modular Reactor Deployments

Rapidly growing interest in advanced and small modular reactor (A/SMR) technologies presents challenges as well as opportunities for implementing international safeguards and security. A/SMR deployments are expected to be more numerous, more geographically dispersed, and more varied in their designs, placing new demands on the data systems and analytical tools used to support oversight (Alberti et al., 2023; Canadian Nuclear Safety Commission et al., 2024). Because of this variability, the importance and reliance on data systems for A/SMR deployments is expected to be higher than for previous reactor generations. Artificial Intelligence and Machine Learning (AI/ML) offer potential capabilities to address the high variability inherent in A/SMR technology. The beneficiaries of AI-assisted tools include facility operators, government regulators, IAEA inspectors, and A/SMR vendors. This report analyzes how AI/ML-assisted technologies can strengthen the implementation of IAEA safeguards and security measures. It also identifies AI-assisted tools to strengthen operator, facility, and regulator knowledge management practices and examines the potential risks AI/ML-based tools may introduce to IAEA safeguards and security efforts. It concludes with a set of hypothetical, standards-style requirements for AI/ML systems used in safeguards contexts, grounded in an inspector-centric view of system verification. Despite the potential benefits of AI/ML systems, understanding potential intentional and unintentional failure modes is critical for ensuring adequate protection of nuclear materials and facilities. Unique features of A/SMRs including sealed cores, remote and novel paradigms of operation, off-site reactor fabrication, novel fuel forms, and varied refueling requirements, introduce challenges for traditional safeguards technological approaches (Pensado et al., 2024; Federation of American Scientists, 2025). AI/ML systems deployed to address these challenges may introduce new risks requiring systematic evaluation rooted in both AI-specific risk frameworks, such as the NIST AI Risk Management Framework (NIST AI RMF), and established cyber risk management standards such as NIST SP 800-30 (National Institute of Standards and Technology [NIST], 2023; NIST, 2012).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Enhanced Electrocatalytic and Cathode‐Electrolyte Interfacial Properties With a Pr‐Based Simple Perovskite/Ruddlesden‐Popper Nanocomposite Cathode in Protonic Ceramic Fuel Cells

The sluggish kinetics and poor stability of the oxygen reduction reaction (ORR) remain the primary bottleneck for achieving high performance in protonic ceramic fuel cells (PCFCs) at intermediate temperatures (400–650°C). In this work, a Pr-based nanocomposite cathode comprised of simple perovskite phase (PrNi 0.7 Co 0.3 O 3-δ ) and Ruddlesden-Popper phase (Co-doped Pr 4 Ni 3 O 10+δ ) is developed. Although PrNi 0.7 Co 0.3 O 3-δ solely stands as a good cathode with facile proton transfer, combining the superior catalytic activity against oxygen on the Ruddlesden-Popper phase boosts the ORR performance further. The designed nanocomposite cathode outperforms the simple perovskite cathode, attributed to enhanced oxygen absorption and surface diffusion with the Ruddlesden-Popper phase. A precursor-based cathode deposition technique is also developed to achieve cathode grain sizes of ∼100 nm. A single cell with the nanocomposite cathode delivers a peak power density of 1.38 W cm −2 at 650°C, among the highest in reported PCFCs with Pr-based cathodes, with a small degradation rate of 0.145 mV h −1 during 250 h stability test. Further investigation of cathode-electrolyte interface revealed interfacial PrO 2 phase formation, promoted by abundant Pr 6 O 11 in the nanocomposite precursor powder, thereby improving both ohmic resistance and stability. These findings highlight the effectiveness of the nanocomposite cathode and underscore its advantages on interfacial properties.

08 - HYDROGEN↗
DOE OSTI2020

Magnetoresistance effects in a spin-fermion model for multilayers

Here, we consider a spin-fermion model consisting of free electrons coupled to classical spins where the latter are embedded in a quasi-one-dimensional superlattice structure consisting of spin blocks separated by spinless buffers. Using a spiral ansatz for the spins, we study the effect of the electron mediated Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction on the $\textit{T}$ = 0 ground state of the system. We find that the RKKY interaction can lead to ferromagnetic, antiferromagnetic, or intermediate spiral phases for different system parameters. When the width is much larger than the length of the individual blocks, the spiral phases are suppressed, and the ground state oscillates between ferromagnetic and antiferromagnetic orders as the size of the buffer regions is varied. This is accompanied by a corresponding oscillation in the Drude weight reflecting an increased conductivity in the ferromagnetic state compared to the antiferromagnetic one. These results are reminiscent of classic giant magnetoresistance phenomena observed in a similar geometry of thin sandwiched magnetic and nonmagnetic layers. Our analysis provides a robust framework for understanding the role of the RKKY interaction on the ground-state order and corresponding transport properties of such systems, extending beyond the conventional perturbative regime.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Diabatic quantum annealing for the frustrated ring model

Abstract Quantum annealing (QA) is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare ground state and a problem Hamiltonian whose ground state encodes solutions to an optimization problem. The standard implementation relies on the evolution being adiabatic: keeping the system in the instantaneous ground state with high probability and requiring a time scale inversely related to the minimum energy gap between the instantaneous ground and excited states. However, adiabatic evolution can lead to evolution times that scale exponentially with the system size, even for computationally simple problems. Here, we study whether non-adiabatic evolutions with optimized annealing schedules can bypass this exponential slowdown for one such class of problems called the frustrated ring model. For sufficiently optimized annealing schedules and system sizes of up to 39 qubits, we provide numerical evidence that we can avoid the exponential slowdown. Our work highlights the potential of highly-controllable QA to circumvent bottlenecks associated with the standard implementation of QA.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

FY23 Drone RFID (Final Report)

The Drone RFID project successfully completed proof-of-concept testing to demonstrate the potential of a drone-based inventory system for high value remote materials at Los Alamos National Laboratory. Multiple drone platforms were procured, flight authorizations were received, and the vehicles were flown demonstrating what was initially perceived as the most difficult part of the project, successfully flying drones at the lab. Three commercial RFID inventory systems were also purchased, and ground testing performed to determine their suitability. Ultimately, one system was chosen for flight testing and successfully demonstrated the drone's ability to execute inventory with great potential for a relatively low-cost implementation.

42 ENGINEERING↗
DOE OSTI2025

Ground state energy and magnetization curve of a frustrated magnetic system from real-time evolution on a digital quantum processor

Models of interacting many-body quantum systems that may realize new exotic phases of matter, notably quantum spin liquids, are challenging to study using even state-of-the-art classical methods such as tensor network simulations. Quantum computing provides a promising route for overcoming these difficulties to find ground states, dynamics, and more. In this paper, we argue that recently developed hybrid quantum-classical algorithms based on real-time evolution are promising methods for solving a particularly important model in the search for spin liquids, the antiferromagnetic Heisenberg model on the two-dimensional kagome lattice. We show how to construct efficient quantum circuits to implement time evolution for the model and to evaluate key observables on the quantum computer, and we argue that the method has favorable scaling with increasing system size. We then restrict to a 12-spin star plaquette from the kagome lattice and a related 8-spin system, and we give an empirical demonstration on these small systems that the hybrid algorithms can efficiently find the ground state energy and the magnetization curve. For these demonstrations, we use four levels of approximation: exact state vectors, exact state vectors with statistical noise from sampling, noisy classical emulators, and (for the 8-spin system only) real quantum hardware, specifically the Quantinuum H1-1 processor; for the noisy simulations and hardware demonstration, we also employ error mitigation strategies based on the symmetries of the Hamiltonian. Our results strongly suggest that these hybrid algorithms present a promising direction for studying quantum spin liquids and more generally for resolving important unsolved problems in condensed matter theory and beyond.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Ground state wave functions for single-band Hubbard models from the Gutzwiller conjugate gradient minimisation theory

The Gutzwiller conjugate gradient minimisation (GCGM) theory is an ab initio quantum many-body theory for computing the ground-state properties of infinite systems. Previous applications of GCGM provides satisfying accuracy of ground-state energy of Hubbard models. In the current work, we address the problem of whether the obtained wave function is a good approximation for the true ground state by comparing the correlation functions with the benchmark data. Additionally, our results confirms the accuracy of the reproduced ground state of the regular Hubbard model, but with some exception for the frustrated Hubbard model.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Data-driven quantum approximate optimization algorithm for power systems

Abstract Quantum technology provides a ground-breaking methodology to tackle challenging computational issues in power systems. It is especially promising for Distributed Energy Resources (DERs) dominant systems that have been widely developed to promote energy sustainability. In those systems, knowing the maximum sections of power and data delivery is essential for monitoring, operation, and control. However, high computational effort is required. By leveraging quantum resources, Quantum Approximate Optimization Algorithm (QAOA) provides a means to search for these sections efficiently. However, QAOA performance relies heavily on critical parameters, especially for weighted graphs. Here we present a data-driven QAOA, which transfers quasi-optimal parameters between weighted graphs based on the normalized graph density. We verify the strategy with 39,774 expectation value calculations. Without parameter optimization, our data-driven QAOA is comparable with the Goemans-Williamson algorithm. This work advances QAOA and pilots its practical application to power systems in noisy intermediate-scale quantum devices.

Jing, Hang (ORCID:0000000256343489)↗
DOE OSTI2024

Memcomputing the Spectrum of Correlated Quantum Systems

The goals and objectives of the grant DE‐SC0020892 were to apply a new computing paradigm, MemComputing, to efficiently simulate properties of correlated quantum systems. The method has been applied to a wide set of problems ranging from quantum state tomography to finding the ground state of correlated systems. In all cases, substantial advantages compared to state-of-the-art approaches have been obtained. The project has also led to the suggestion of the transformer architecture (used nowadays in large-language models) as an efficient quantum state representation, and a better understanding of the role of memory in the generation of long-range order in neural networks. This grant has supported the work of a PhD student, inspired a new class on unconventional computing taught at the University of California, San Diego and has generated several peer-reviewed papers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Comminty Geothermal: Planning and Design of a Heating and Cooling System in Framingham, Massachusetts

These reports, plans, and drawings review the achievements of Home Energy Efficiency Team (HEET) and its partners to plan and design a network of interconnected ground-source heat pump systems, or geothermal network, in an area encompassing multiple environmental justice (EJ) neighborhoods in the City of Framingham, MA. The materials provided in this dataset include, a) stakeholder and design best practices, b) study on optimal method to interconnect geothermal loops, c) guidelines for monitoring and metering, d) operations and maintenance plans, e) permitting guidelines and f) 10-day driller tutorial curriculum. These materials can guide the efficient and ethical design of future geothermal networks nationwide. The capacity of the system is estimated at 217 tons and is designed to provide 100% of heating and cooling needs for the buildings connected to the loop. In this project, 80 boreholes are used as the main thermal resources, the distribution system (or loop) consists of 0.61 miles of an 8-inch single-pipe at ambient temperature, with the capacity to connect 44 buildings, including 13 apartment buildings from the Framingham Housing Authority, one transitional home, one school building and 29 single family homes. While Framingham already has a geothermal network loop that is currently in the commissioning stage, our proposed project is unique because it is the first utility-led expansion loop (2nd loop) project that will connect to an adjacent existing geothermal loop (1st loop) in a pre-existing neighborhood. Both the 1st and 2nd loops are being installed, owned and operated by Eversource Energy, the utility Deployment Partner.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

A non-orthogonal variational quantum eigensolver

Variational algorithms for strongly correlated chemical and materials systems are one of the most promising applications of near-term quantum computers. We present an extension to the variational quantum eigensolver that approximates the ground state of a system by solving a generalized eigenvalue problem in a subspace spanned by a collection of parametrized quantum states. This allows for the systematic improvement of a logical wavefunction ansatz without a significant increase in circuit complexity. To minimize the circuit complexity of this approach, we propose a strategy for efficiently measuring the Hamiltonian and overlap matrix elements between states parametrized by circuits that commute with the total particle number operator. This strategy doubles the size of the state preparation circuits but not their depth, while adding a small number of additional two-qubit gates relative to standard variational quantum eigensolver. We also propose a classical Monte Carlo scheme to estimate the uncertainty in the ground state energy caused by a finite number of measurements of the matrix elements. We explain how this Monte Carlo procedure can be extended to adaptively schedule the required measurements, reducing the number of circuit executions necessary for a given accuracy. We apply these ideas to two model strongly correlated systems, a square configuration of H4 and the π-system of hexatriene (C6H8).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Lessons Learned from Three Agrivoltaic Installations in New Jersey

Agrivoltaics is a new technology that has the potential to positively impact commercial farming by combining agricultural practices with the generation of solar energy. While some yield reduction is to be expected, resulting from less sunlight reaching the plant canopy and ground occupied by support structures, the generated electricity provides a low-risk supplemental income to farmers. In order to combine farming with electricity generation, agrivoltaic systems use a lower ground coverage ratio compared to normal solar farms and the PV panels are often mounted higher above the ground in order to facilitate the movement of agricultural equipment and to reduce the contrast between shaded and non-shaded areas. With funding provided from the state of New Jersey and the New Jersey Agricultural Experiment Station (NJAES), we designed and installed three unique agrivoltaic research systems at Rutgers/NJAES farms. These projects were recently completed and are generating electricity that is exported to the grid. This paper discusses the lessons we have learned along the way, including all the steps necessary to see an agrivoltaic project through to completion.

Both, A. J. (ORCID:0000000150845296)↗