Quasiparticle band structure and excitonic optical response in V 2 O 5 bulk and monolayer
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Garcia, Claudio (ORCID:0009000077503536)↗
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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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Gravothermal collapse and the diversity of galactic rotation curves
The rotation curves of spiral galaxies exhibit a great diversity that challenges our understanding of galaxy formation and the nature of dark matter. Previous studies showed that in self-interacting dark matter (SIDM) models with a cross section per unit mass of σ/m ≈ $\mathscr{O}$(1) cm 2 /g, the predicted dark matter central densities are a good match to the observed densities in galaxies. Here, in this work, we explore a regime with a larger cross section of σ/m ≈ 20−40 cm 2 /g in dwarf galactic halos. We will show that such strong dark matter self-interactions can further amplify the diversity of halo densities inherited from their assembly history. High concentration halos can enter the gravothermal collapse phase within 10 Gyr, resulting in a high density, while low concentration ones remain in the expansion phase and have a low density. We fit the rotation curves of 14 representative low surface brightness galaxies and demonstrate how the large range of observed central densities is naturally accommodated in the strong SIDM regime of σ/m ≈ 20 – 40 cm 2 /g. Galaxies that are outliers in the previous studies, due to their high halo central densities, are no longer outliers in this SIDM regime as their halos would be in the collapse phase. For galaxies with a low density, the SIDM fits are robust to the variation of the cross section. Our findings open up a new window for testing gravothermal collapse, the unique signature of strong dark matter self-interactions, and exploring a broader SIDM model space. As an example, we illustrate how the larger cross sections favored by our fits, together with upper limits from strong lensing observations in clusters, pick out the preferred SIDM model space for a dark matter particle coupled to a light gauge boson in the Born regime.
dark matter↗
In situ coherent x-ray scattering reveals polycrystalline structure and discrete annealing events in strongly coupled nanocrystal superlattices
Solution-phase bottom up self-assembly of nanocrystals into superstructures such as ordered superlattices is an attractive strategy to generate functional materials of increasing complexity, including very recent advances that incorporate strong interparticle electronic coupling. While the self-assembly kinetics in these systems have been elucidated and related to the product characteristics, the weak interparticle bonding interactions suggest the superstructures formed could continue to order within the solution long after the primary nucleation and growth have occurred, even though the mechanism of annealing remains to be elucidated. Here, we use a combination of Bragg coherent diffractive imaging and x-ray photon correlation spectroscopy to create real-space maps of supercrystalline order along with a real-time view of the strain fluctuations in aging strongly coupled nanocrystal superlattices while they remain suspended and immobilized in solution. By combining the results, we deduce that the self-assembled superstructures are polycrystalline, initially comprising multiple nucleation sites, and that shear avalanches at grain boundaries continue to increase crystallinity long after growth has substantially slowed. This multimodal approach should be generalizable to characterize a breadth of materials in their native chemical environments, thus extending the reach of high-resolution coherent x-ray characterization to the benefit of a much wider range of physical systems. Published by the American Physical Society 2024
36 MATERIALS SCIENCE↗
Fully plasma-based electron injector for a linear collider or XFEL
We demonstrate through high-fidelity particle-in-cell (PIC) simulations a simple approach for efficiently generating 20 + GeV electron beams with the necessary charge, energy spread, and emittance for use as an injector in a future linear collider or a next generation XFEL. A high quality injected bunch is generated by self-focusing an unmatched electron driver in a nonlinear plasma wakefield. Over pump depletion distances, the drive beam dynamics and self-loading effects lead to high energy, low-energy spread output beams. For plasma densities of 10 18 cm −3 , PIC simulation results indicate that self-injected beams with 0.52 nC charge can be accelerated to 20 GeV with projected core energy spreads of ≲ 1%, normalized slice emittances of 110nm, peak normalized brightness of ≳ 10 19 A/m 2 /rad 2 , and transfer efficiencies of ≳ 44%.
Particle acceleration in plasmas↗
Tensile and fatigue characterization of multifunctional composites
This research is part of a larger effort to develop advanced self-sensing multifunctional polymer composites that are both lightweight and high-strength, while also enabling structural damage detection, fatigue cycle monitoring, and service life prediction. These multifunctional composites are particularly sought after in the automotive industry for their potential to significantly reduce vehicle weight and simultaneously provide additional functionality like condition monitoring to enhance safety. This study examines the tensile and fatigue properties of a composite material composed of acrylonitrile butadiene styrene (ABS) polymer embedded with piezoelectric barium titanate (BaTiO3) nanoparticles. The integration of BaTiO3 nanoparticles not only supplies the material with self-sensing capabilities but also influences its mechanical properties. While a high content of BaTiO3 nanoparticles is desired to enhance sensing capacity, the brittle nature of such materials causes concerns of decreased strength characteristics. To explore this, various composite samples were fabricated with nanoparticle contents ranging from 0 wt% to 20 wt%. These samples underwent tensile testing to measure their ultimate tensile strengths and Young’s moduli. Following this, fatigue tests were conducted to generate S-N curves, which are essential for understanding the material's durability under cyclic loading. The findings from these tests assess the impact of nanoparticle content on the composite’s tensile strength and fatigue life, providing essential insights that can guide the optimization and design of future self-sensing multifunctional composites. The results suggest that 5 wt% BaTiO3 provides an optimal balance between mechanical properties and nanoparticle concentration, making it a promising composition for semi-structural applications.
Bowland, Christopher [ORNL] (ORCID:000000021229431↗
High-voltage water-scarce hydrogel electrolytes enable mechanically safe stretchable Li-ion batteries
Soft Li-ion batteries, based on conventional organic electrolytes, face performance degradation challenges due to moisture penetration and safety concerns due to possible leakage of toxic fluorine compounds and flammable solvents under mechanical damage. We design a water-scarce hydrogel electrolyte with fluorine-free lithium salt to achieve wide electrochemical stability window (up to 3.11 volts) in ambient air without hermetic packaging while balancing high stretchability (1348%), ion conductivity (41 millisiemens per centimeter), and self-healing capabilities for mechanically and chemically safe stretchable Li-ion batteries. Molecular synergy between hydrophilicity and lithiophilicity of zwitterionic polymer backbone is revealed by molecular dynamics simulations. The battery exhibits capacity retention under harsh mechanical stresses—enduring stretching, twisting, folding, and multiple through-punctures by a needle—while self-healing from repeated through cuts by a razor blade. Stable ambient operation for 1 month over 500 charge-discharge cycles (average coulomb efficiency, 95%) is achieved. A prototype self-healing electronic system with embedded soft batteries demonstrates practical application as a durable embodied energy source.
Science & Technology - Other Topics↗
Nonlinear propagation of chirped laser pulses through a dispersive and turbulent atmosphere
The evolution of ultrashort laser pulses in dispersive, turbulent, nonlinear, and dissipative media is discussed in connection with nonlinear self-focusing collapse and the onset of laser filamentation. In quiescent air, a laser pulse propagating with a peak power greater than a critical power for self-focusing will undergo a catastrophic, transverse collapse until the intensity is large enough for photoionization. At this point, self-focusing is arrested and balanced by plasma refraction, forming a laser filament. By applying an appropriate chirp, the dispersive properties of the medium can be used to enhance this process and control its onset, and to counter dissipative effects such as molecular absorption and atmospheric scattering. This paper presents an analysis of the effect of atmospheric turbulence on the propagation of nonlinear pulses with dispersion compensation (chirp). Furthermore, the analytical results are compared with wave optics simulations and found to be in reasonable agreement as long as the pulse maintains a near-Gaussian spatiotemporal profile.
47 OTHER INSTRUMENTATION↗
Nonlinear regenerative amplification using tunable intracavity cascaded quadratic nonlinearities
Conventional nonlinear regenerative amplification utilizes Kerr (i.e., self-focusing) nonlinearity to broaden the spectrum via self-phase modulation during the direct amplification of ultrashort pulses, which helps overcome spectral gain narrowing for high-energy, ultrashort-pulse generation. We introduce cascaded quadratic nonlinearities from a type-I second-harmonic generation crystal, which can be tuned in both magnitude and sign via the phase-mismatching condition, inside a regenerative amplifier to enable nonlinearity-tunable regenerative amplification. We demonstrate, both experimentally and numerically, a nonlinear Yb:YAG thin-disk regenerative amplifier with either positive or negative net nonlinearity that delivers 1-kHz, >0.4-mJ pulses as short as ∼200 fs and high-quality beams free of self-focusing. The laser’s average power can be scaled to >100 W when seeded and operated at a much higher repetition rate to benefit various applications.
47 OTHER INSTRUMENTATION↗
Comparative study of spectral broadening and few-cycle compression of Yb:KGW laser pulses in gas-filled hollow-core fibers
While industrial-grade Yb-based amplifiers have become very prevalent, their limited gain bandwidth has created a large demand for robust spectral broadening techniques that allow for few-cycle pulse compression. In this work, we perform a comparative study between several atomic and molecular gases as media for spectral broadening in a hollow-core fiber geometry. Exploiting nonlinearities such as self-phase modulation, self-steepening, and stimulated Raman scattering, we explore the extent of spectral broadening and its dependence on gas pressure, the critical power for self-focusing, and the optimal regime for few-cycle pulse compression. Using a 3-mJ, 200-fs input laser pulses, we achieve 17 fs, few-cycle pulses with 80% fiber energy transmission efficiency. The optimal parameters can be scaled for higher or lower input pulse energies with appropriate gas parameters and fiber geometry.
Shalaby, Islam (ORCID:0000000332846636)↗
Plastics recycling via plasma-based depolymerization utilizing aqueous and gaseous discharge exposure
This proposed work aims to understand and quantify the effect of self-organization on polymer depolymerization in liquids. Here, the project will explore the role of the formation of large-scale plasma induced flows that occur under self- organization that leads to the convection of plastic particles (micron sized) to the plasma attachment regions. This convention should lead to enhanced transport and higher depolymerization rates. Also, associated with self-organization is the emission of charged droplets in the region of plasma attachment. A key question is do these droplets contain heavily broken up polymer chains or monomers? Is this emission another approach to collection of depolymerized media? These droplets are also charged and contains particles suggesting a means to control emitted media. Currently, plastics upcycling, the conversion of plastics to higher value products, is energy intensive due to high heat requirements (for example thermolysis). Plasma-based treatment offers a greener approach to the depolymerization of plastics and offers the possibility of upcycling to make higher value products such as higher-grade plastics and fuels.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
The Energetics of He Bubble Nucleation
In this project we considered the initial stages of helium bubble nucleation via the proposed mechanism of self-interstitial atom nucleation. By calculating the energy barrier to self-interstitial atom nucleation in a range of Fe-Ni-Cr alloys we identified the most important energetic contributions to the phenomenon: the Frenkel-pair energy barrier in the absence of helium and the difference of insertion energy for a He cluster into a perfect lattice and vacancy. From this observation, we developed a simple model of helium-assisted self-interstitial atom nucleation.
36 MATERIALS SCIENCE↗
SCRES Energy Quest Workshop (Technical Report)
Energy Quest: Sitka’s Path to 2050 is a game based public engagement tool developed as part of the Sitka Community Renewable Energy Strategy and the U.S. Department of Energy’s Energy Transitions Initiative Partnership Project Cohort 3. Designed for Sitka’s isolated island microgrid, which is powered primarily by hydropower and depends on imported diesel for backup, the game translated complex long term energy planning questions into an interactive format. In facilitated workshops, residents built energy roadmaps to 2050, explored tradeoffs, and expressed priorities around four themes: affordability, reliability, self sufficiency, and innovation. Across sessions, participants showed strong support for increasing local self sufficiency and resilience, even when this required balancing near term affordability with long term investments. They emphasized reducing dependence on imported diesel, making better use of existing hydropower, and considering new renewable generation such as solar, wind, and additional hydropower. Survey and game responses also highlighted interest in using surplus hydropower to support new industries, expanding electrification of heating and transportation, and exploring emerging technologies and green fuels. The report organizes these findings into four scenario themes to guide Sitka’s 2050 energy planning. Affordability focuses on managing rate impacts, efficiency, and conservation. Reliability addresses diversified generation, backup power, and energy security. Self sufficiency emphasizes distributed generation and reduced reliance on imported fuels. Innovation explores new technologies, marine based energy solutions, and low carbon fuels. By grounding future planning in these community derived themes, Energy Quest shows how a game based approach can make technical energy planning more accessible and inclusive for remote communities. For questions about the game board and piece production email Dr. Sarah Troise (sarah.troise@pnnl.gov)
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
A large-scale benchmarking of deterministic and stochastic derivative-free optimization algorithms
This presentation summarizes our work in the PrOMMiS project on benchmarking of data-driven optimization algorithms and their applications in self-driving laboratories. This work supports the broader project goal of accelerating the identification of promising separation methods and operating conditions for critical minerals separation processes. We present a systematic benchmarking study of 42 data-driven optimization algorithms on a broad collection of 502 test problems. The results identify BAM, GLCCLUSTER, and MULTIMIN as the most effective optimization solvers, with BAM showing the highest overall performance and solving more than 80% of the benchmark problems. The study also shows that no single solver consistently outperforms the others across all problem types, indicating that our future laboratory applications may benefit from using a small set of strong solvers rather than relying on a single method. The presentation also illustrates an in-silico chemical reactor case study showing that data-driven optimization methods can guide autonomous experimentation in a self-driving laboratory and identify optimal operating conditions within a small number of experiments. Overall, the results provide a basis for selecting efficient optimization methods and demonstrate the practical use of data-driven optimization in self-driving laboratory workflows.
36 MATERIALS SCIENCE↗
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
Abstract. The radiative–convective equilibrium (RCE) model intercomparison project (RCEMIP) leveraged the simplicity of RCE to focus attention on moist convective processes and their interactions with radiation and circulation across a wide range of model types including cloud-resolving models (CRMs), general circulation models (GCMs), single-column models, global cloud-resolving models, and large-eddy simulations. While several robust results emerged across the spectrum of models that participated in the first phase of RCEMIP (RCEMIP-I), two points that stand out are (1) the strikingly large diversity in simulated climate states and (2) the strong imprint of convective self-aggregation on the climate state. However, the lack of consensus in the structure of self-aggregation and its response to warming is a barrier to understanding. Gaining a deeper understanding of convective aggregation and tropical climate will require reducing the degrees of freedom with which convection can vary. Therefore, we propose phase II of RCEMIP (RCEMIP-II) that utilizes a prescribed sinusoidal sea surface temperature (SST) pattern to provide a constraint on the structure of convection and move one critical step up the model hierarchy. This so-called “mock-Walker” configuration generates features that resemble observed tropical circulations. The specification of the mock-Walker protocol for RCEMIP-II is described, along with example results from one CRM and one GCM. RCEMIP-II will consist of five required simulations: three simulations with the same three mean SSTs as in RCEMIP-I but with an SST gradient and two additional simulations at one of the mean SSTs with different values of the SST gradients. We also test the sensitivity to the imposed SST gradient and the domain size. Under weak SST gradients, unforced self-aggregation emerges across the entire domain, similar to what was found in RCEMIP. As the SST gradient increases, the convective region narrows and is more confined to the warmest SSTs. At warmer mean SSTs and stronger SST gradients, low-frequency variability in the convective aggregation emerges, suggesting that simulations of at least 200 d may be needed to achieve robust equilibrium statistics in this configuration. Simulations with different domain sizes generally have similar mean statistics and convective structures, depending on the value of the SST gradient. The prescribed SST boundary condition is the only difference in the set-up between RCEMIP-II and RCEMIP-I, which enables comparison between the two; however, we also welcome participation in RCEMIP-II from models that did not participate in RCEMIP-I.
Geology↗
Data/code for Mlawer et al. 2024 (A more transparent infrared window)
The infrared window region (780–1,250 cm –1 , 12.8 to 8.0 μm) is of great importance to Earth's climate due to its high transparency and thermal energy. We present here a new investigation of the transparency of this spectral region based on observations by interferometers of downwelling surface radiance at two DOE Atmospheric Radiation Measurement program sites. We focus on the dominant source of absorption in this region, the water vapor continuum, and derive updated values of spectral absorption coefficients for both the self and foreign continua. Our results show that the self continuum is too strong in the previous version of Mlawer-Tobin_Clough-Kneizys-Davies (MT_CKD) water vapor continuum model, a result that is consistent with other recent analyses, while the foreign continuum is too weak in MT_CKD. In general, the weaker self continuum derived in this study results in an overall increase in atmospheric transparency in the window, although in atmospheres with low amounts of water vapor the transparency may slightly decrease due to the increase in foreign continuum absorption. These continuum changes lead to a significant decrease in downwelling longwave flux at the surface for moist atmospheres and a modest increase in outgoing longwave radiation. The increased fraction of surface-leaving radiation that escapes to space leads to a notable increase (~5–10%) in climate feedback, implying that climate simulations that use the new infrared window continuum will show somewhat less warming than before. This study also points out the possibly important role that aerosol absorption may play in the longwave radiative budget.
54 ENVIRONMENTAL SCIENCES↗
Enhancing Unknown Waveform Detection by Learning Intra and Inter-domain Dependencies with Advanced Attention Fusion Mechanisms
Detection of unknown waveforms in mission-critical communications is a crucial area of interest for the Department of Energy (DoE). Traditional methods and recent deep learning-based approaches often assume that the training set includes all possible classes, which is impractical for detecting new waveforms. This limitation gives rise to the problem of open-set recognition (OSR), which involves correctly identifying known classes while detecting and rejecting unknown or unseen classes. To address this limitation, we propose a novel dual-domain complex-valued neural architecture that jointly processes time-domain and frequency-domain signal representations using transformer mechanisms. A transformer model is a deep learning architecture that uses self-attention mechanisms to process and learn relationships in sequential data. Our model employs a cosine similarity loss to extract domain-specific features and incorporates a transformer architecture in the latent space to weigh the importance of different features from the time and frequency domains. The transformer layer includes stacked self-attention and cross-attention modules to learn intra-domain and inter-domain dependencies, creating a more holistic signal representation. An attention-based fusion module intelligently combines the time and frequency-domain features using multi-head attention, enabling the network to learn the optimal feature for each domain in each input signal. Quantitative results demonstrate the impact of these architectural choices on overall performance, showing significant improvement after incorporating self and cross-attention modules and using complex attention fusion over simple weighted fusion. Our ongoing work will focus on addressing the limitations of threshold-based OSR methods by developing a novel generative framework that integrates a conditional diffusion probabilistic model (DPM). DPM is a generative framework that learns to synthesize complex data by reversing a gradual noising process using a neural network trained to denoise step-by-step. Our goal is to leverage the inherent strengths of DPMs for identifying unknown signals more robustly. One primary advantage of using a DPM is its ability to provide a more reliable anomaly score based on the model's reconstruction error, rather than relying solely on classifier confidence. Additionally, the iterative denoising process of DPMs makes this approach naturally resilient to low Signal-to-Noise Ratio (SNR) conditions, where traditional methods often fail. By implementing this generative framework, we aim to enhance the model's capability to accurately detect unknown waveforms and maintain performance in challenging environments.
99 - GENERAL AND MISCELLANEOUS↗
Highly Ordered Eutectic Mesostructures via Template‐Directed Solidification within Thermally Engineered Templates
Template-directed self-assembly of solidifying eutectics results in emergence of unique microstructures due to diffusion constraints and thermal gradients imposed by the template. Here, the importance of selecting the template material based on its conductivity to control heat transfer between the template and the solidifying eutectic, and thus the thermal gradients near the solidification front, is demonstrated. Simulations elucidate the relationship between the thermal properties of the eutectic and template and the resultant microstructure. The overarching finding is that templates with low thermal conductivities are generally advantageous for forming highly organized microstructures. When electrochemically porosified silicon pillars (thermal conductivity < 0.3 Wm −1 K −1 ) are used as the template into which an AgCl-KCl eutectic is solidified, 99% of the unit cells in the solidified structure exhibit the same pattern. In contrast, when higher thermal conductivity crystalline silicon pillars (≈100 Wm −1 K −1 ) are utilized, the expected pattern is only present in 50% of the unit cells. The thermally engineered template results in mesostructures with tunable optical properties and reflectances nearly identical to the simulated reflectances of perfect structures, indicating highly ordered patterns are formed over large areas. This work highlights the importance of controlling heat flows in template-directed self-assembly of eutectics.
36 MATERIALS SCIENCE↗
Rigid Supramolecular Aramid Nanotubes as Catalyst Supports
Solution‐phase heterogeneous catalysts benefit from nanoscale dimensions, which maximize specific surface area and enhance catalytic activity. However, the ease of recovering such nanocatalysts depends on the design of the support materials, which are often particle‐like. Rigid 1D nanomaterials are proposed as supports that can enhance separability while offering high volumetric specific surface area for greater catalyst loading and activity. Here, aramid amphiphiles (AAs) are designed to spontaneously self‐assemble in water into high‐aspect‐ratio supramolecular nanotubes with tunable surface chemistry. These AA nanotubes exhibit high persistence lengths (P = 750 ± 340 µm) and mechanical stiffnesses (3 N/m). Incorporating surface thiol groups enables immobilization of catalytic gold nanoparticles. The resulting AA nanotube‐gold nanoparticle complexes exhibit high catalytic activity, efficient recoverability via simple microfiltration, and sustained reusability over ten reaction cycles. This study demonstrates the utility of molecular self‐assembled 1D nanomaterials as versatile scaffolds for the reuse and recovery of nanoscale catalysts.
1D nanomaterials↗