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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Macroscopic dark matter detection with gravitational wave experiments

We study signatures of macroscopic dark matter (DM) in current and future gravitational wave (GW) experiments. Transiting DM with a mass of ~10 5 –10 15 kg that saturates the local DM density can be potentially detectable by GW detectors, depending on the baseline of the detector and the strength of the force mediating the interaction. In the context of laser interferometers, we derive the gauge invariant observable due to a transiting DM, including the Shapiro effect (gravitational time delay accumulated during the photon propagation), and adequately account for the finite photon travel time within an interferometer arm. In particular, we find that the Shapiro effect can be dominant for short-baseline interferometers such as Holometer and GQuEST. Here, we also find that proposed experiments such as Cosmic Explorer and Einstein Telescope can constrain a fifth force between DM and baryons, at the level of strength ~10 3 times stronger than gravity for, e.g., kg mass DM with a fifth-force range of 10 6 m.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Predicting and Understanding Non-Covalent Interactions Using Novel Forms of Symmetry-Adapted Perturbation Theory

Although sometimes derided as “weak” interactions, non-covalent forces play a critical role in ligand binding and crystal packing and in determining the conformational landscape of flexible molecules. Symmetry-adapted perturbation theory (SAPT) provides a framework for accurate ab initio calculation of intermolecular interactions and furnishes a natural decomposition of the interaction energy into physically meaningful components: semiclassical electrostatics (rigorously obtained from monomer charge densities), Pauli or steric repulsion, induction (including both polarization and charge transfer), and dispersion. This decomposition helps to foster deeper understanding of non-covalent interactions and can be used to construct transferable, physics-based force fields. Separability of the SAPT interaction energy also provides the flexibility to construct composite methods, a feature that we exploit to improve the description of dispersion interactions. Furthermore, these are challenging to describe accurately because they arise from nonlocal electron correlation effects that appear for the first time at second order in perturbation theory but are not quantitatively described at that level.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Strong interplay between superluminosity and radiation friction during direct laser acceleration

Using a test-particle model, we examine direct laser acceleration of electrons within a magnetic filament that has been shown to form inside a laser-irradiated plasma. We focus on ultra-high intensity interactions where the force of radiation friction caused by electron emission of electromagnetic radiation must be taken into account. It is shown that even relatively weak superluminosity of laser wave fronts—the feature that has been previously neglected—qualitatively changes the electron dynamics, leading to a so-called attractor effect. As a result of this effect, electrons with various initial energies reach roughly the same maximum energy and emit roughly the same power in the form of x-rays and gamma-rays. Our analysis implies that the primary cause of the superluminosity is the laser-heated plasma. The discovered strong interplay between superluminosity and radiation friction is of direct relevance to laser-plasma interactions at high-intensity multi-PW laser facilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration

Climate change is reshaping vulnerable ecosystems, leading to uncertain effects on ecosystem dynamics, including evapotranspiration (ET) and ecosystem respiration (R eco ). However, accurate estimation of ET and R eco still remains challenging at sparsely monitored watersheds, where data and field instrumentation are limited. In this study, we developed a hybrid predictive modeling approach (HPM) that integrates eddy covariance measurements, physically based model simulation results, meteorological forcings, and remote-sensing datasets to estimate ET and R eco in high space–time resolution. HPM relies on a deep learning algorithm and long short-term memory (LSTM) and requires only air temperature, precipitation, radiation, normalized difference vegetation index (NDVI), and soil temperature (when available) as input variables. We tested and validated HPM estimation results in different climate regions and developed four use cases to demonstrate the applicability and variability of HPM at various FLUXNET sites and Rocky Mountain SNOTEL sites in Western North America. To test the limitations and performance of the HPM approach in mountainous watersheds, an expanded use case focused on the East River Watershed, Colorado, USA. The results indicate HPM is capable of identifying complicated interactions among meteorological forcings, ET, and R eco variables, as well as providing reliable estimation of ET and R eco across relevant spatiotemporal scales, even in challenging mountainous systems. The study documents that HPM increases our capability to estimate ET and R eco and enhances process understanding at sparsely monitored watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Inferring Nuclear Hamiltonians from 3 rd -Generation Gravitational-Wave Detectors [Slides]

Neutrons stars are some of the densest objects in our universe. Thus, they provide us with a laboratory to study dense nuclear matter and its properties. The neutron star’s stability at such high densities, with an immense gravitational force, is due in large part to nuclear interactions. Specifically, nuclear 3-body forces provide significant repulsive contributions and at high densities. Current and future gravitational-wave detectors can help us to better understand these nuclear interactions. My project aims to predict the constraining power of the next generation of Gravitational Wave detectors: Cosmic Explorer. I have constructed a solver for the Tolman-Oppenheimer-Volkoff equations and studied equations of state with varying strengths of the 3-body forces. Using simulated data from Phillipe Landry at CITA, I can predict to which level of uncertainty Cosmic Explorer will enable us to measure nuclear 3-body force.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Linear thermomagnetic energy harvester for low-grade thermal energy harvesting

Low-grade thermal energy, either from waste heat or from natural resources, constitutes an enormous energy reserve that remains to be fully harvested. Harvesting low-grade heat is challenging because of the low Carnot efficiency. Among various thermal energy harvesting mechanisms available for capturing low-grade heat (temperature less than 100 degrees C), the thermomagnetic effect has been found to be quite promising. In this study, we demonstrate a scalable thermomagnetic energy harvester architecture that exhibits 140% higher power density compared to the previously published spring-mass designs. The alternating force required to oscillate the thermomagnetic mass is generated through the interaction between two magnetic forces in opposite directions. We employed numerical modeling to illustrate the behavior of a thermomagnetic device under different operating conditions and to obtain the optimal hot-side and cold-side temperatures for continuous mode operations. A miniaturized thermomagnetic harvester was fabricated and experiments were conducted to systematically evaluate the performance. The prototype was found to exhibit an oscillation frequency of 0.33 Hz, a work output of 0.6 J/kg/cycle, and a power density of 0.2 W/kg of gadolinium under the temperature difference of 60 K.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A classical model for three-body interactions in aqueous ionic systems

We present a classical induction model to evaluate the three-body ion–water–water (I–W–W) and water–water–water (W–W–W) interactions in aqueous ionic systems. The classical description of the induction energy is based on electrostatic distributed multipoles up to hexadecapole and distributed polarizabilities up to quadrupole–quadrupole on the O and H atoms of water. The monatomic ions were described by a point charge and a dipole–dipole polarizability, while for the polyatomic ions, distributed multipoles up to hexadecapole and distributed polarizabilities up to quadrupole–quadrupole were used. The accuracy of the classical model is benchmarked against an accurate dataset of 936 (I–W–W) and 2184 (W–W–W) three-body terms for 13 different monatomic and polyatomic cation and anion systems. The classical model shows excellent agreement with the reference second order Moller–Plesset and coupled-cluster single double and perturbative triple [CCSD(T)] three-body energies. The Root-Mean-Square-Errors (RMSEs) for monatomic cations, monatomic anions, and polyatomic ions were 0.29, 0.25, and 0.12 kcal/mol, respectively. The corresponding RMSE for 1744 CCSD(T)/aVTZ three-body (W–W–W) energies, used to train MB-pol, was 0.12 kcal/mol. The accuracy of the proposed classical model demonstrates that the three-body term for aqueous ionic systems can be accurately modeled classically. This approach provides a fast, efficient, and as-accurate path toward modeling the three-body term in aqueous ionic systems that is fully transferable across systems with different ions without the need to fit to tens of thousands of ab initio calculations for each ion to extend existing many-body force fields to interactions between water and ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

In-situ magnetic alignment model for additive manufacturing of anisotropic bonded magnets

In this work, we report a mathematical framework which predicts the degree of alignment (DoA) in an in-situ aligned additively manufactured 3D printed bonded magnets. A multiphysics model is developed which couples the harmonious interactions of magnetic particles in a viscous flowing polymer under the presence of an external magnetic field. The hydrodynamic fluid-particle interaction is paired with the magnetophoretic force to predict the particle trajectory and distribution during extrusion through a 3D printer nozzle. Succeeding the force balance, a magnetohydrodynamic torque equilibrium analysis is performed to predict the net-orientation of the magnetic particles as a function of the applied field strength, viscous forces, and particle-to-particle interactions (P2P). Experimental validation of the DoA predictions is performed using 65 vol% Nd-Fe-B+Sm-Fe-N in Nylon12 (DoA exp = 0.620 and DoA theory = 0.686) and 15 vol% Sm-Co in PLA (DoA exp = 0.830 and DoA theory = 0.863). A parametric analysis is performed to analyze the effect of operating and design parameters like alignment field strength, magnetic loading fraction, extrusion load, and particle size. The model predicts a competing behavior between particle-fluid and particle-particle interactions under the presence of an applied field. Lastly, the model provides a framework to efficiently predict the DoA in tandem with a functionalized-magnetic 3D printer and allows the user to adjust the operating parameters according to the desired DoA.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Infrared nanoimaging and nanospectroscopy of electrochemical energy storage materials and interfaces

Electrochemical interfaces are central to the function and performance of energy storage devices. Thus, the development of new methods to characterize these interfaces, in conjunction with electrochemical performance, is essential for bridging the existing knowledge gaps and accelerating the development of energy storage technologies. Of particular need is the ability to characterize surfaces or interfaces in a non-destructive way with adequate resolution to discern individual structural and chemical building blocks. To this end, sub-diffraction-limit low-energy infrared optical probes that exploit near-field interactions within atomic force microscopy platforms, such as pseudoheterodyne nanoimaging, photothermal nanoimaging and nanospectroscopy, and nanoscale Fourier transform infrared spectroscopy, are all powerful emerging techniques. These are capable of non-destructive surface probing and imaging at nanometer resolution. This review outlines recent efforts to characterize ex situ, in situ, and operando electrode materials and electrochemical interfaces in rechargeable batteries with these advanced infrared near-field probes.

25 ENERGY STORAGE↗
DOE OSTI2024

Hydropower expansion in eco-sensitive river basins under global energy-economic change

Vast hydropower resources remain untapped globally, the deployment of which could provide energy-economic benefits but impact riverine ecosystems. Across eco-sensitive river basins, it is unclear how drivers of hydropower expansion, such as rapid economic growth and a low-carbon energy transition, could interact with countervailing forces, such as increasingly cost-competitive variable renewable energy (VRE). Using an integrated energy-water-economy model, we explore the effects of these forces on long-term hydropower expansion in the world’s 20 most eco-sensitive basins, which have high ecological richness and untapped hydropower potential. Here, we find that a low-carbon transition exerts the strongest development pressure, causing deployment exceeding 80% of exploitable potential in more than 72% of eco-sensitive basins by 2050, most of which have limited deployment today. Rapid economic growth induces such extensive deployment in only 44% of eco-sensitive basins. Enhanced integration of VRE reduces deployment, alleviating the impacts of rapid economic growth but not the low-carbon transition.

13 HYDRO ENERGY↗
DOE OSTI2025

Physics-tailored machine learning reveals unexpected physics in dusty plasmas

Dusty plasma is a mixture of ions, electrons, and macroscopic charged particles that is commonly found in space and planetary environments. The particles interact through Coulomb forces mediated by the surrounding plasma, and as a result, the effective forces between particles can be nonconservative and nonreciprocal. Machine learning (ML) models are a promising route to learn these complex forces, yet their structure should match the underlying physical constraints to provide useful insight. Here, we demonstrate and experimentally validate an ML approach that incorporates physical intuition to infer force laws in a laboratory dusty plasma. Trained on 3D particle trajectories, the model accounts for inherent symmetries, nonidentical particles, and learns the effective nonreciprocal forces between particles with exquisite accuracy (R 2 > 0.99). We validate the model by inferring particle masses in two independent yet consistent ways. The model’s accuracy enables precise measurements of particle charge and screening length, identifying large deviations from common theoretical assumptions. Our ability to identify unknown physics from experimental data demonstrates how ML-powered approaches can guide new routes of scientific discovery in many-body systems. Furthermore, we anticipate our ML approach to be a starting point for inferring laws from dynamics in a wide range of many-body systems, from colloids to living organisms.

Science & Technology - Other Topics↗
DOE OSTI2021

Defect Spirograph: Dynamical Behavior of Defects in Spatially Patterned Active Nematics

We report that topological defects in active liquid crystals can be confined by introducing gradients of activity. Here, we examine the dynamical behavior of two defects confined by a sharp gradient of activity that separates an active circular region and a surrounding passive nematic material. Continuum simulations are used to explain how the interplay among energy injection into the system, hydrodynamic interactions, and frictional forces governs the dynamics of topologically required self-propelling + 1/2 defects. Our findings are rationalized in terms of a phase diagram for the dynamical response of defects in terms of activity and frictional damping strength. Different regions of the underlying phase diagram correspond to distinct dynamical modes, namely immobile defects, steady rotation of defects, bouncing defects, bouncing-cruising defects, dancing defects, and multiple defects with irregular dynamics. These dynamic states raise the prospect of generating synchronized defect arrays for microfluidic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Low-Temperature Competing Magnetic Energy Scales in the Topological Ferrimagnet TbMn 6 Sn 6

TbMn 6 Sn 6 is a metallic ferrimagnet displaying signatures of both topological electrons and topological magnons arising from ferromagnetism and spin-orbit coupling within its Mn kagome layers. Inelastic neutron scattering measurements find strong ferromagnetic (FM) interactions within the Mn kagome layer and reveal a magnetic bandwidth of ~230 meV. The low-energy magnetic excitations are characterized by strong FM Mn-Mn and antiferromagnetic (AFM) Mn-Tb interlayer magnetic couplings. We observe weaker, competing long-range FM and AFM Mn-Mn interlayer interactions similar to those driving helical magnetism in the YMn 6 Sn 6 system. Combined with density-functional theory calculations, we find that competing Mn-Mn interlayer magnetic interactions occur in all RMn 6 Sn 6 compounds with R=Y, Gd-Lu, resulting in magnetic instabilities and tunability when Mn-R interactions are weak. In the case of TbMn 6 Sn 6 , strong AFM Mn-Tb coupling ensures a highly stable three-dimensional ferrimagnetic network.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Weak gravity conjecture

The weak gravity conjecture holds that in a theory of quantum gravity any gauge force must mediate interactions stronger than gravity for some particles. This statement has surprisingly deep and extensive connections to many different areas of physics and mathematics. Several variations on the basic conjecture have been proposed, including statements that are much stronger but are nonetheless satisfied by all known consistent quantum gravity theories. These related conjectures and the evidence for their validity in the string theory landscape are reviewed. Also reviewed here are a variety of arguments for these conjectures, which tend to fall into two categories: qualitative arguments that claim the conjecture is plausible based on general principles and quantitative arguments for various special cases or analogs of the conjecture. The implications of these conjectures for particle physics, cosmology, general relativity, and mathematics are also outlined. Finally, important directions for future research are highlighted.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Simulation of Proton Beams in the AGS Booster with Space Charge

As higher intensity accelerators are designed, built and operated, the resonances and instabilities caused by space charge can become dominant effects in limiting the intensity of the beam that can be delivered. Particle loss has many causes but space charge can be a major factor in reducing beam intensity and generating emittance growth, particularly at low energies and in the lower energy stages of accelerators such as the AGS Booster. Successful operation relies on a good understanding of basic particle dynamics and it becomes an important challenge to ascertain how the beam evolves when charged particles experience both external forces through the fields of the magnets combined with internal forces through Coulomb interactions. A possible approach to such a study is to include calculations of space charge in computer simulation codes that track the motions of charged particles in 6D phase space. Unfortunately, repeated space charge calculations in 6D phase space are computationally intensive even with the most modern computing facilities. Study with traditional models of space charge is then either limited to a short real-time scale, or sacrifices accuracy and often omits some of the physics. The study described in this report attempts to explore all aspects of the Booster from injection, through RF capture and acceleration to the extraction energy. The simulations are allied to real machine settings. They do not attempt to model effects that are well known and for which accurate experimental data are available, but they try in many cases to extend beyond the normal Booster parameter range so as to understand the limitations on operations and suggest areas for improvement.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Shift Happens: Building Robust AI Models with Domain Adaptation

Artificial Intelligence (AI) is revolutionizing physics research—from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data—exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This summer school session will introduce students to common challenges in applying AI across domains and present solutions based on domain adaptation—a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery. The concepts discussed are broadly applicable across physics and other scientific disciplines, making this a valuable topic for anyone interested in building robust, transferable AI models for science.

Ciprijanovic, A. [Fermilab] (ORCID:000000031281719↗
DOE OSTI2025

AI in Astrophysics: Tackling Domain Shift, Model Robustness and Uncertainty

Artificial Intelligence (AI) is revolutionizing physics research from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This talk will introduce common challenges in applying AI across domains and present solutions based on domain adaptation a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery.

Ciprijanvoic, Aleksandra [Fermilab] (ORCID:0000000↗
DOE OSTI2022

Nonsteady Load Responses to Daytime Atmospheric Turbulence Eddies on the DOE 1.5 MW Wind Turbine at NREL

Field data collected from the NREL/GE 1.5MW wind turbine (WT) and met tower (MetT) at the NREL Wind Technology Center near Boulder, CO June-October 2018 were analyzed to quantify the impacts of turbulence eddies on the load responses measured from sensors on the main shaft, blade and tower. The passage of individual mountain-generated eddies from the met tower to the WT were critically determined by correlating the optimal time shifts in signal between MetT and nacelle anemometers with mean advection time. Loading responses from mountain eddy passage were compared with atmospheric eddies from the north/south, unimpeded by the mountains, and found to be similar. Whereas time variations in torque were highly correlated with time changes in horizontal eddy velocity, the out-of-plane bending moments on the main shaft (directly forcing the main bearing) were uncorrelated with horizontal eddy velocity. This result is consistent with a previous LES study indicating that the main bearing is forced by asymmetrical interactions between the WT rotor and turbulence eddies, while power fluctuations respond primarily to advective eddy velocity. Surprisingly, the nacelle anemometer produced statistics very similar to the MetT.

ENGINEERING,WIND ENERGY↗