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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Persistence of collectivity in the low-lying states of 30,31 Na inside the 𝑁 = 20 island of inversion

Near the 𝛽-stability line, nuclei with magic numbers are expected to exhibit spherical ground states. However, mass measurements of neutron-rich nuclei near the 𝑁 = 20 island of inversion have indicated an excess in the binding energies. These results, together with subsequent spectroscopic studies and theoretical works, point to the structural evolution from normal configurations to intruder-deformed configurations characterized by particle-hole excitations across the shell gap. Despite evidence of intruder-dominant ground states for the 30,31 Na isotopes in the vicinity of 𝑁 = 20, a question remains as to whether the deformation persists into the ground-state bands beyond the first excited states. Here, in this work, we report on a heavy-ion inelastic scattering measurement performed with GRETINA, the TRIPLEX device, and the S800 spectrograph to study the low-lying excitations in neutron-rich 30,31 Na . The observed gamma rays for the (4 + ) → (3 + ), (3 + ) → 2$^+_{g.s.}$, and (4 + ) → 2$^+_{g.s.}$ decays in 30 Na and for the (7/2 + ) → (5/2 + ) and (5/2 + )→3/2$^+_{g.s.}$ decays in 31 Na were used to extract the reduced transition probabilities 𝐵⁡(𝐸⁢2↑). We report the first measurement of the 𝐵⁡(𝐸⁢2↑) between the 3/2$^+_{g.s.}$ and the (7/2 + ) states in 31 Na . The results from this study are compared to shell-model calculations, confirming the persistence of large collectivity in the low-lying excited states consistent with the formation of the well-deformed ground-state bands in 30,31 Na .

collective models↗
DOE OSTI2025

MRCI Task 3: Facilitating Data Collection, Sharing, and Analysis Final Technical Summary Report

The Midwest Regional Carbon Initiative (MRCI) Task 3.0 was defined to facilitate development of carbon capture, utilization, and storage (CCUS) in the region by collection and sharing of existing and new technical data from CCUS projects and research. The task also included support for further analysis and assessment of tools by the project team and by researchers working on programs such as National Risk Assessment Partnership (NRAP), machine learning (ML) techniques, and assessment and improvement of CCUS site assessment, operations, and monitoring aspects. Work under Task 3.0 addressed key issues related to CCUS deployment and provided foundational research and datasets to help establish CCUS projects in the MRCI. Report Authors and Principal Technical Contributors: Joel Sminchak, Laura Keister, Mackenzie Scharenberg, Priya Ravi-Ganesh, Autumn Haagsma, Srikanta Mishra, Jared Hawkins, Jared Schuetter, Amy Lang, Jaelen Lewis, Derrick James, Jorge Barrios, Stuart Skopec, and Sanjay Mawalkar (Battelle). Chris Korose, Carl Carmen, Nate Grigsby, Nathan Webb (Illinois State Geological Survey). Principal Investigators: Dr Neeraj Gupta, Dr. Chris Korose.

MRCI,NRAP,data collection,data compilation,legacy ↗
DOE OSTI2026

Oscillatory and Collective Dynamics of Gold‐Nanoparticle‐Laden Droplets Driven by Photothermal‐Induced Thermocapillarity

Droplets have long intrigued researchers due to their ability to exhibit complex and fascinating behavior when subjected to external stimuli. Here, a coupled oscillatory behavior of gold-nanoparticle-surfactant-laden aqueous droplets is investigated at an oil-oil interface stimulated by light. This study shows that the interaction between light and the droplets gives rise to a range of oscillatory modes, including bouncing and clustering, where droplets exhibit collective movement. From experiment and numerical simulations, this study elucidates the underlying mechanism: upon laser irradiation, gold nanoparticles convert light into heat, generating asymmetric thermal gradients that drive upward thermocapillary flows and a hydrodynamic force from photothermal convection. These forces compete with gravity and buoyancy to induce droplet bouncing, while the resulting asymmetric flow fields bias neighboring droplets toward the illuminated droplet, leading to clustering. These findings not only expand the library of dynamic droplet behavior but also offer insights into the potential applications of light-driven systems in materials science, soft robotics, and microfluidics.

Marangoni effect↗
DOE OSTI2025

Manipulation of Emergent Collective Excitations via Composition Control in Mixed MPX 3 Correlated 2D Antiferromagnets

Transition metal (i.e., Mn, Fe, Cr) and chalcogen (Se) substituents are introduced into single-crystalline NiPS 3 , and the evolution of the two emergent quasi-particle excitations characteristic to the XXZ correlated antiferromagnetism of NiPS 3 (i.e., spin orbit entangled exciton (SOX) and two-magnon scattering (2M )) are investigated as functions of substituent concentration through comprehensive room- and low-temperature photoluminescence (PL) and Raman spectroscopy studies. These findings are further correlated with the magnetic properties of the same set of compounds reported in prior studies. The work revealed that the SOX emission intensities and linewidths are mainly controlled by the magnetic anisotropy and spin orientations, and are strongly suppressed by the introduction of substituents. The suppression depends on the type of substituent, with Fe affecting the SOX emission more than Mn and Cr. The 2 M scattering is linked to short-range correlations and exhibits greater resiliency against metal atom substitution. While the 2M peak at low temperature gets suppressed and red-shifted in frequency with increasing concentrations of all the substituents, Fe induces the weakest suppression compared to all other substituents. Altogether, these findings revealed the introduction of substituents as a powerful route to control the emergent collective excitations in NiPS 3 and mixed-MPX 3 materials.

2D magnet↗
DOE OSTI2025

Biofilm growth in water-cooling towers as collection platforms for airborne radionuclides

Given its history of nuclear material processing, the Savannah River Site (SRS) was used to evaluate whether biofilms growing in water-cooling towers (WCTs) are effective passive collection platforms for environmental radionuclide surveillance. Uranium and plutonium analyses suggest that WCT-sourced biofilms are efficient, indigenous, constantly running samplers that can be used for environmental monitoring, as their isotopic compositions are distinct from atmospheric fallout and representative of SRS historical activities. Further, the ubiquity of WCTs worldwide and demonstrated ability to detect nuclear material processing and constrain specific activities based on biofilm actinide isotopic compositions make WCT biofilms a promising means to improve monitoring.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Empirical evidence that glucan-interacting amino acid side chains within the transmembrane channel collectively facilitate cellulose synthase function

The fundamental mechanism of cellulose synthesis is widely conserved across Kingdoms and depends on cellulose synthases, which are processive, dual-function, family 2 glycosyltransferases (GT-2). These enzymes polymerize glucose on the cytoplasmic side of the plasma membrane and export the glucan chain to the cell surface through an integral transmembrane (TM) channel. Structural studies of active plant cellulose synthases (CESAs) have revealed interactions between the nascent glucan chain and the side chains of polar, charged, and aromatic amino acid residues that line the TM channel. However, the functional consequences of modifying these side chains have not been tested in vivo in CESAs or other processive GT-2s. To test this, we used an established in vivo assay based on genetic complementation of CESA5 in the moss, Physcomitrium patens. For accurate prediction of glucan-interacting amino acid residues, we generated a complete homotrimeric molecular model of PpCESA5 using a combination of homology and de novo modeling. All-atom molecular dynamics-based analyses of contact metrics and interaction energy identified 23 amino acid residues with high propensity to interact with the nascent glucan chain within the TM channel or on the apoplastic surface of PpCESA5. Mutating any one of 18 of these amino acid residues to alanine, thereby removing their side chains, abolished or impaired CESA function, with the strongest effects observed upon the loss of charged amino acid side chains. This provides direct evidence to support the hypothesis that multiple amino acid residues collectively maintain a smooth energy landscape within the TM channel to facilitate glucan translocation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Automated vehicle microscopic energy consumption study (AV-Micro): Data collection and model development

While the Adaptive Cruise Control (ACC) system in automated vehicles (AVs) is expected to impact transportation energy significantly, existing AV energy consumption models only directly adopt those developed with Human-driven Vehicle (HV) data without even slight adaptation or calibration to accommodate unique AV energy consumption features. This study will investigate how accurately HV data-based models can predict the energy consumption of AVs. Empirical trajectory data and corresponding instantaneous energy consumption rates from both AVs and HVs were collected. We adopted two classical HV data-based models to fit these data. The calibration results indicated that these models yield around 20 30% prediction errors for AVs. To further improve the prediction accuracy, this study designed an AV-Micro model by incorporating components of multiple classic energy consumption models that better capture ACC energy consumption features, including piecewise driving behavior. With this, the AV-Micro model achieves lower than 10% prediction errors. The AV-Micro model’s high consistency across different test runs was verified with statistical significance tests, demonstrating its adaptability in different driving profiles. To confirm the discrepancies between the energy consumption features of AVs and HVs, more statistical significance tests were conducted to show that the AV-Micro model cannot be directly applied to HV data. The findings by calibrated AV-Micro models revealed that AVs consume approximately 80.5–146.4 J more energy than HVs for each meter traveled. Furthermore, the frequency analysis of energy consumption indicates that there is still some room for AVs to improve energy efficiency, particularly given their larger amplitude high-frequency fluctuations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Charge collection efficiency of diamond and silicon sensors irradiated with alpha particles

To evaluate the viability of using semiconductors as sensor materials in a detector for the Associated Particle Imaging technique, the radiation hardness of silicon and diamond diodes to alpha particles has been assessed. Here, the detector lifetimes for both silicon and diamond sensors were measured under the prolonged exposure to alpha particles emitted by an 241 Am source. The silicon detector was exposed to alpha radiation for approximately two months, reaching an accumulated fluence of ~ 1.5 x 10 12 α cm –2 . Additionally, by using a high purity single-crystal diamond with coplanar electrodes operating with full charge collection, the diamond detector response was measured over approximately ten months reaching an accumulated fluence of over 6 x 10 12 α cm –2 cm.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Suppressed electric quadrupole collectivity in 49 Ti

Single-step Coulomb excitation of 46,48,49,50 Ti is presented. A complete set of E2 matrix elements for the quintuplet of states in 49 Ti, centred on the core excitation, was measured for the first time. A total of nine E2 matrix elements are reported, four of which were previously unknown. $^{49}_{22}$Ti 27 shows a 20% quenching in electric quadrupole transition strength as compared to its semi-magic $^{50}_{22}$Ti 28 neighbour. This 20% quenching, while empirically unprecedented, can be explained with a remarkably simple two-state mixing model, which is also consistent with other ground-state properties such as the magnetic dipole moment and electric quadrupole moment. A connection to nucleon transfer data and the quenching of single-particle strength is also demonstrated. The simplicity of the 49 Ti- 50 Ti pair (i.e., approximate single-j 0 7/2 valence space and isolation of yrast states from non-yrast states) provides a unique opportunity to disentangle otherwise competing effects in the ground-state properties of atomic nuclei, the emergence of collectivity, and the role of proton-neutron interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Characterizing Defect Dynamics in Silicon Carbide Using Symmetry-Adapted Collective Variables and Machine Learning Interatomic Potentials

Silicon carbide (SiC) divacancies are attractive candidates for spin-defect qubits possessing long coherence times and optical addressability. The high activation barriers associated with SiC defect formation and motion pose challenges for their study by first-principles molecular dynamics. In this work, we develop and deploy machine learning interatomic potentials (MLIPs) to accelerate defect dynamics simulations while retaining ab initio accuracy. We employ an active learning strategy comprising symmetry-adapted collective variable discovery and enhanced sampling to compile configurationally diverse training data, calculation of energies and forces using density functional theory (DFT), and training of an E(3)-equivariant MLIP based on the Allegro model. Here, the trained MLIP reproduces DFT-level accuracy in defect transition activation free energy barriers, enables the efficient and stable simulation of multidefect 216-atom supercells, and permits an analysis of the temperature dependence of defect thermodynamic stability and formation/annihilation kinetics to propose an optimal annealing temperature to maximally stabilize VV divacancies.

Computer simulations↗
DOE OSTI2024

Tunable Collective Excitations in Epitaxial Perovskite Nickelates

The formation of plasmons through the collective excitation of charge density has generated intense discussions, offering insights to fundamental sciences and potential applications. While the underlying physical principles have been well-established, the effects of multibody interactions and orbital hybridization on plasmonic dynamics remain understudied. Here, in this work, we present the observation of conventional metallic and correlated plasmons in epitaxial La 1-x Sr x NiO 3 (LSNO) films with varying Sr doping concentrations (x = 0, 0.125, 0.25), unveiling their intriguing evolution. Unlike samples at other doping concentrations, the x = 0.125 intermediate doping sample does not exhibit the correlated plasmons despite showing high optical conductivity. Through experimental investigation using spectroscopic ellipsometry and X-ray absorption spectroscopy, that is further supported by theoretical calculations, the O2p-Ni3d orbital hybridization for x = 0.125 is found to be significantly enhanced, alongside a considerable weakening of its effective interaction comprising long-range Coulomb and variable interaction, U*. These factors account for the absence of correlated plasmons and the high optical conductivity observed in LSNO(0.125). Our findings highlight the significant impact of orbital hybridization on the electronic structures and the formation of quasiparticles in strongly correlated systems, opening new paths for plasmonic-based engineering research.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Polaritonic Bright and Dark States Collectively Affect the Reactivity of a Hydrolysis Reaction

Vibrational strong coupling (VSC) has emerged as a means for modifying chemical reactivity. Despite the intriguing discoveries and progresses in the field, the precise mechanisms that govern polaritonic chemistry still deserve further interrogation. Herein, we use the hydrolysis of ammonia borane in D 2 O as an exemplary reaction and systematically investigate the influence of VSC on its reactivity. Experimental evidence of the coexistence of a resonant effect and reaction acceleration is observed in this system. In particular, we find that when the O-D stretching mode of D 2 O is strongly coupled to a cavity mode, reaction acceleration is observed. The reaction rate acceleration factor, mu, is consistently observed to be dependent on the coupling conditions between the vibrational and cavity modes, and reaches a minimum at zero mode detuning, suggesting that a resonant effect is likely in play. In addition, we find that mu decreases with an increasing Rabi splitting. Based on these experimental findings, we propose that the overall influence of VSC on this reaction is likely determined collectively by the polaritonic bright and dark states. In conclusion, these findings could help shed new light on the intricate effects of VSC on ground-state reaction landscapes.

Rabi splitting↗
DOE OSTI2024

Collective dynamics and long-range order in thermal neuristor networks

Abstract In the pursuit of scalable and energy-efficient neuromorphic devices, recent research has unveiled a novel category of spiking oscillators, termed “thermal neuristors.” These devices function via thermal interactions among neighboring vanadium dioxide resistive memories, emulating biological neuronal behavior. Here, we show that the collective dynamical behavior of networks of these neurons showcases a rich phase structure, tunable by adjusting the thermal coupling and input voltage. Notably, we identify phases exhibiting long-range order that, however, does not arise from criticality, but rather from the time non-local response of the system. In addition, we show that these thermal neuristor arrays achieve high accuracy in image recognition and time series prediction through reservoir computing, without leveraging long-range order. Our findings highlight a crucial aspect of neuromorphic computing with possible implications on the functioning of the brain: criticality may not be necessary for the efficient performance of neuromorphic systems in certain computational tasks.

Science & Technology - Other Topics↗
DOE OSTI2024

Tuning collective anion motion enables superionic conductivity in solid-state halide electrolytes

Halides of the family Li 3 MX 6 (M = Y, In, Sc and so on, X = halogen) are emerging solid electrolyte materials for all-solid-state Li-ion batteries. They show greater chemical stability and wider electrochemical stability windows than existing sulfide solid electrolytes, but have lower room-temperature ionic conductivities. Here, in this work, we report the discovery that the superionic transition in Li 3 YCl 6 is triggered by the collective motion of anions, as evidenced by synchrotron X-ray and neutron scattering characterizations and ab initio molecular dynamics simulations. Based on this finding, we used a rational design strategy to lower the transition temperature and thus improve the room-temperature ionic conductivity of this family of compounds. We accordingly synthesized Li 3 YCl x Br 6-x and Li 3 GdCl 3 Br 3 and achieved very high room-temperature conductivities of 6.1 and 11 mS cm -1 for Li 3 YCl 4.5 Br 1.5 and Li 3 GdCl 3 Br 3 , respectively. These findings open new routes to the design of room-temperature superionic conductors for high-performance solid batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Strain-affected ferroelastic domain walls in RbMnFe charge-transfer materials undergoing collective Jahn–Teller distortion

Many rubidium manganese hexacyanoferrate materials, with the general formula Rb x Mn[Fe(CN) 6 ] (x+2)/3 ·zH 2 O, exhibit diverse charge-transfer-based functionalities due to the bistability between a high temperature Mn II (S = 5/2)Fe III (S = 1/2) cubic phase and a low-temperature Mn III (S = 2)Fe II (S = 0) tetragonal phase. The collective Jahn–Teller distortion on the Mn sites is responsible for the cubic-to-tetragonal ferroelastic phase transition, which is associated with the appearance of ferroelastic domains. In this study, we use X-ray diffraction to reveal the coexistence of 3 types of ferroelastic tetragonal domains and estimate the spatial extension of the strain around the domain walls, which represents about 30% of the volume of the crystal.

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

A deep learning approach to fast analysis of collective Thomson scattering spectra

Fast analysis of collective Thomson scattering ion acoustic wave features using a deep convolutional neural network model is presented. The network was trained from spectra to predict the plasma parameters, including ion velocities, population fractions, and ion and electron temperatures. A fully kinetic particle-in-cell simulation was used to model a laboratory astrophysics experiment and simulate a diagnostic image of the ion acoustic wave feature. Network predictions were compared with Bayesian inference of the plasma model parameters for both the simulated and experimentally measured images. Both approaches were fairly accurate predicting the simulated image and the network predictions matched a good portion of the Bayesian results for the experimentally measured image. The Bayesian approach is more robust to noise and motivates future work to train deep learning models with realistic noise. The advantage of the deep learning model is making thousands of predictions in a few hundred milliseconds, compared to a few seconds to minutes per prediction for the optimization and Bayesian approaches presented here. The results demonstrate promising capabilities of deep learning models to analyze Thomson data orders of magnitude faster than conventional methods when using the neural network for standalone analysis. If more rigorous analysis is needed, neural network predictions can be used to quickly initialize other optimization methods and increase chances of success. This is especially useful when the dataset becomes very large or highly dimensional and manually refining initial conditions for the entire dataset are no longer tractable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Collective behavior of “flexicles”

In recent years the functionality of synthetic active microparticles has edged even closer to that of their biological counterparts. However, we still lack the understanding needed to recreate at the microscale key features of autonomous behavior exhibited by microorganisms or swarms of macroscopic robots. In this study, we propose a model for a three-dimensional deformable cellular composite particle consisting of self-propelled rod-shaped colloids confined within a flexible vesicle—representing a superstructure we call a “flexicle” that couples particle deformation to the internal dynamics of the internal active components. Using molecular dynamics simulations, we investigate the collective behavior of dense systems composed of many flexicles. We show that individual flexicles exhibit shape changes upon collisions with other flexicles that lead to rearrangements of the internal active rods, which slows flexicle motion. This shape deformability gives rise to a diverse set of motility-induced phase separation phenomena and the spontaneous flow of flexicles reminiscent of the migration of cells in dense tissues. Our findings establish a foundation for designing responsive, cell-like active particles and developing strategies for controlling swarm migration and other autonomous swarm behaviors at cellular and colloidal scales.

Science & Technology - Other Topics↗