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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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This poster presents a novel modular, scalability receiver design for various Concentrating Solar Thermal (CST)-Concentrating Solar Power (CSP) applications and scale of economics.
Significance Nanoporous metals are prototypical bicontinuous structures that have a large surface area and many applications. We demonstrate that an in-grain orientation spread develops during coarsening in nanoporous metals, leading to the formation of a nanocrystalline–nanoporous structure. The process of particles detaching and reattaching as the structure coarsens is identified as a mechanism of grain boundary formation. Coarsening the structure results in significant particle detachment with detachment rates that vary drastically with changes in the volume fraction and volume fraction inhomogeneities in the nanostructure. These results demonstrate that particle detachment must be understood to have full control of the nanocrystalline–nanoporous structure and improve material properties.
Experiments at a future $\mathcal{e}$⁺$\mathcal{e}$⁻ collider will be able to search for new particles with masses below the nominal centre-of-mass energy by analyzing collisions with initial-state radiation (radiative return). We show that machine learning methods that use imperfect or missing training labels can achieve sensitivity to generic new particle production in radiative return events. In addition to presenting an application of the classification without labels (CWoLa) search method in $\mathcal{e}$⁺$\mathcal{e}$⁻ collisions, our study combines weak supervision with variable-dimensional information by deploying a deep sets neural network architecture. We have also investigated some of the experimental aspects of anomaly detection in radiative return events and discuss these in the context of future detector design.
Nuclear physics explores the fundamental properties of matter -- how protons and neutrons emerge as quantum systems of elementary particles, how they form the atomic nuclei, and how they give rise to the wide variety of phenomena and applications at biological, technical, and astronomical scales. It is a global scientific effort centered around large-scale experimental user facilities (particle accelerators and detectors), advanced theoretical methods and concepts, and computational techniques and resources. Exchange of knowledge and ideas, scientific collaboration, and workforce development on a global scale are essential for the future of the field. The nuclear physics program envisaged in the 2023 DOE/NSF NSAC Long-Range Plan and pursued at the U.S. National Labs has strong synergies with programs at other facilities worldwide and will realize significant benefits from international collaboration. Nuclear physics is also recognized for promoting international cooperation in the broadest sense through joint construction and operation of experimental equipment, personal contacts between scientists, and education and training. The U.S.-Japan Hadronic Physics Exchange Program (USJPHE) supported collaborative scientific research in hadronic physics and quantum chromodynamics. USJHPE focused on subject areas related to the programs at current and future experimental facilities in the U.S.\ and Japan and supported both experimental and theoretical studies. USJHPE particularly aimed to realize synergies between the hadronic physics programs at Jefferson Lab 12 GeV and J-PARC resulting from the complementarity of electromagnetic and hadronic probes in the multi-GeV energy range. Subject areas of common interest included the quark-gluon structure of hadrons and nuclei, meson and baryon spectroscopy, strangeness and hypernuclear physics, and other related topics. USJHPE also supported research in hadronic physics and nuclear-physics-enabled tests of fundamental symmetries related to the programs at Brookhaven National Lab, Fermilab, KEK, Spring-8, and university-based facilities in the U.S. and Japan. USJHPE especially promoted collaboration between the U.S. and Japanese nuclear physics communities in developing the physics program and instrumentation for the future Electron-Ion Collider. USJHPE was intended to provide travel grants to U.S.-based scientists (primary institutional affiliation with a U.S.\ university, national laboratory, or other research center) to visit Japanese institutions and conduct collaborative research there. The program supported senior researchers, postdoctoral fellows, and students. Continuing the setup of the preceding grant period, J-PARC served as the Japanese “hub” for U.S. physicists for short- and long-term visits, and JLab served as the corresponding U.S. “hub”. The program was officially managed through the U. of Connecticut in Storrs, CT. Support for Japanese physicists visiting the U.S. was provided through funds from Japanese funding agencies. The USJHPE program promoted the scientific exchange and the collaborative spirit in hadronic physics between the two countries.
Controlling the nucleation and growth of nanoparticles in low temperature plasma systems is imperative for controlling nanoparticle size distributions; and for some applications such as deposition and etching in microelectronic processing, preventing particle contamination. In this work, silicon nanoparticle (NP) production from silane is used as a model system to investigate the nucleation process. Although the mechanisms responsible for silicon NP nucleation and growth have been studied, it is unclear how controllable system parameters (e.g., pressure, system geometry, and gas composition) can be used to inhibit or promote NP formation. For example, the transport of reactive silane species is expected to significantly affect the feed fraction of silane required to nucleate silicon NP (the nucleation onset fraction) due to losses at the reactor walls. In this work, NP mass density was determined as a function of system pressure, gas composition, and reactor diameter for a tubular flow-through radiofrequency (RF) plasma using Ar/H2/He/SiH4 gas mixtures. A quartz crystal microbalance (QCM) impactor was developed to measure the total aerosol mass density downstream of the plasma and thereby identify the nucleation onset and its dependence on process parameters. Finally, a reaction mechanism was developed and incorporated into a global plasma chemistry model to better understand the nucleation onset and NP growth.
Numerical simulations have historically played a major role in understanding the hydrodynamics of the tidal disruption process. Given the complexity of the geometry of the system, the challenges posed by the problem have indeed stimulated much work on the numerical side. Smoothed Particles Hydrodynamics methods, for example, have seen their very first applications in the context of tidal disruption and still play a major role to this day. Likewise, initial attempts at simulating the evolution of the disrupted star with the so-called affine method have been historically very useful. Here, we provide an overview of the numerical techniques used in the field and of their limitations, and summarize the work that has been done to simulate numerically the tidal disruption process.
Surface evolution due to exposure to harsh environments is of importance in many scientific and technological applications. In plasma-exposed materials, the surface receives charged particles from the plasma, leading to a series of processes that drive the system far from equilibrium and may lead to the severe deterioration of the surface properties. Although surface morphological changes are driven by atomic collisions taking place over picoseconds and nanometers, these processes result in mass loss and redistribution of matter over much larger length and time scales. This necessitates a multi-scale approach capable of capturing the range of processes linking primary atomic collision events with engineering-level surface geometry changes. In this paper, we develop a computational model to simulate the morphological evolution and effective erosion rate of micro-architected tungsten foams during low-energy plasma ion bombardment. Furthermore, the model acts on several length scales, with the energy and angular dependence of the sputtering yield of flat tungsten surfaces determined using the SRIM code based on the binary collision approximation. This information is introduced into a low-fluence, short-term Monte Carlo raytracing model, and further into a high-fluence, long-term particle transport model. In the latter, material particles representing billions of atoms are described in a digitized 3-D representation of the foam structure from X-ray tomography data, and are sputtered off and redeposited using the atomistic information. We show that the redeposition of sputtered atoms leads to partial self-healing in the bottom layers with a sharp reduction in the sputtering coefficient of low density foams, roughly 25% of the solid W value. This is in qualitative agreement with recent experiments on low porosity W structures. At high fluence, the foam structure degrades considerably as there are fewer ligaments available to recapture sputtered atoms and, consequently, the sputtering rate increases again.
In this paper, a new system, which consists of mature and proven technologies, is suggested for simultaneous objectives in nuclear power plants: CHF enhancement and effective decontamination. It consists of multifunctional magnetic nanoparticles and a collector part. CHF enhancement for severe accident mitigation strategies like IVR-ERVC and core catcher is expected along with an efficient decontamination process of target radioactive nuclides, and through the collector part, where external magnetic fields are applied, working fluid can be effectively purified. The multifunctional magnetic nanoparticle possesses potentials to severe accident scenarios based on its distinct characteristics. Also, a nanofluid system is strongly affected by environments and state of the immersed particles; the CHF enhancement can be stably achieved in real applications with proper consideration and optimization.
The use of metal–organic frameworks (MOFs) in hybrid electrolytes for lithium (Li) metal batteries has grown in prominence in recent years, primarily due to the chemical tunability of the MOF’s pore structures, which can directly influence Li–ion transport properties. The most attractive form factor for a MOF electrolyte is a thin, flexible membrane, which requires the application of pressure to increase the contact between the MOF particles. Herein, a systematic study of the influence of pressure on the properties of MOF-808-based membranes is presented. It is shown that when a dry, roll-pressed membrane is subjected to pressure ≥120 MPa, a total loss of crystallinity and a significant loss of porosity is observed. Alternatively, a slurry-cast membrane, compressed under controlled pressures, can maintain crystallinity and porosity while decreasing the interparticle void space. Interesting, the conductivity of the membranes infiltrated with liquid electrolyte is not greatly affected by the pressure applied, though ultimately it is shown that for cycling with Li metal, compressed membranes with compact particles are preferred. In conclusion, this study highlights the critical importance of controlling the pressure applied to MOF-based membranes during fabrication and during cell assembly and lays out the foundation for further investigation of how to optimize membrane fabrication for hybrid electrolytes that use MOFs as the dominate component.
Ni-rich layered transition metal oxide (NMC, LiNi1-x-yMxCoyO2, 1 – x – y = 0.6) is promising for high-energy-density lithium-ion batteries, but its large-scale application is still hindered by several technical challenges, including secondary particle cracking, interfacial instability, and cell degassing during cycling. Here, we report a facile wet-chemical method to modify both the surface and the bulk of the LiNi0.76Mn0.14Co0.10O2 (NMC76) cathode with Al doping to effectively improve the structural/interfacial stability of the cathode, and hence its long-term cycling capability. With only 1 mol% Al doping, the Al-NMC76 electrode delivers a good capacity retention of 79.2% after 500 cycles at a high voltage limit of 4.5 V, which is far better than those of undoped NMC76 under the similar condition. The enhanced performance can be attributed to the Al doping in the NMC76, which not only strengthens the bulk structural stability through doping into the lattice, but also suppresses acidic attack from the electrolyte through altered surface structure of NMC76.
The utilization of single-crystal (SC) Li[Ni x MnyCo 1-x-y ]O 2 (NMC) cathodes has facilitated unparalleled performance in commercial high-energy lithium-ion batteries (LIBs). In the current study, we evaluate the application of SC cathodes in fast charge (FC)-LIBs where particle cracking is a predominant failure mechanism. Ni-rich SC-NMC samples with various compositions, sizes, and shapes are synthesized and investigated for their influence on FC performance. We reveal the necessity of utilizing smaller SCs (<1 μm) as larger sizes (>2 μm) experience significant particle-level lithium concentration gradients under FC conditions. To improve lithium transport and minimize side reactivities, we strategically expose the (104) crystal facets on the surface. Exceptional performance was observed on an optimized SC-LiNi 0.80 Mn 0.05 Co 0.15 O 2 , delivering a discharge capacity of 165 mAh/g even after 150 cycles at 6C charge. Our study not only demonstrates the promise of SC-NMC but also provides the key insights for the design and optimization of advanced cathodes for FC-LIBs.
The dynamics of complex ordering systems with active rotational degrees of freedom exemplified by protein self-assembly is explored using a machine learning workflow that combines deep learning-based semantic segmentation and rotationally invariant variational autoencoder-based analysis of orientation and shape evolution. The latter allows for disentanglement of the particle orientation from other degrees of freedom and compensates for lateral shifts. The disentangled representations in the latent space encode the rich spectrum of local transitions that can now be visualized and explored via continuous variables. The time dependence of ensemble averages allows insight into the time dynamics of the system and, in particular, illustrates the presence of the potential ordering transition. Finally, analysis of the latent variables along the single-particle trajectory allows tracing these parameters on a single-particle level. The proposed approach is expected to be universally applicable for the description of the imaging data in optical, scanning probe, and electron microscopy seeking to understand the dynamics of complex systems where rotations are a significant part of the process.
Achieving tunable controls on the adsorption and self-assembly of nanoscale building blocks at immiscible fluid interfaces is essential for synthesizing advanced materials, stabilizing emulsions, and the sustainable storage and recovery of fluids. Although extensive efforts have been directed toward resolving the assembly of spherical nanoparticles at water–hydrocarbon interfaces, 2D nanoparticles have received far less attention. In this study, we developed novel controls to direct the adsorption and assembly of 2D laponite nano-discs (diameter = ∼30 nm and thickness = ∼1 nm) at water–heptane interfaces using traces of sodium dodecyl sulfate (SDS) surfactant, demonstrated by advanced in situ small-angle X-ray scattering, atomic force microscopy, spinning drop tensiometer measurements and molecular dynamics simulations. The results show that SDS surfactant displaces the adsorbed laponite nano-discs from the interface toward the aqueous phase. The extent of this displacement increases with SDS concentration such that high SDS concentrations convert laponite-rich interfaces to SDS-rich interfaces free of laponite nano-discs. This transformation is associated with significant alterations in the rheological and nanomechanical properties of the host interface. In this context, reduction in interfacial tension and interfacial stiffness and an increase in the interfacial deformation is observed on increasing the SDS concentration from 0 to 0.1 wt%. The displacement of laponite nano-discs from the interface is driven by strong electrostatic interactions between the hydrophilic SDS group and interfacial water molecules. These studies unlock new insights into the adsorption and assembly of 2D nanoscale particles at water–hydrocarbons interfaces that are relevant for various applications related to energy and environmental science and engineering.
Here, we perform an updated analysis on a long-lived domain wall (DW) network, which may apply to a broad class of axion models. By simulating an axion-like scalar field on a 3D lattice and fitting an analytical model for the DW evolution, we identify the leading energy loss mechanisms of the DWs and compute the spectrum of axions emitted from the network. The contribution from the DWs to axion-like dark matter (DM) density is derived, with viable parameter space given. The application to both QCD axions and general axion-like particles (ALPs) is considered. Due to the new approaches taken, while our results bear consistency with earlier literature, notable discrepancies are also revealed, such as the specifics about DW decay rate which impacts the prediction for DM abundance, which may have a profound impact on axion phenomenology at large.
Large edge-localized modes (ELMs) were mitigated by gravitational injection of lithium granules into the upper X-point region of the experimental advanced superconducting tokamak (EAST) device with tungsten plasma-facing components. The maximum ELM size was reduced by ~70% in high β N H-mode plasmas. Large ELM stabilization was sustained for up to about 40 energy confinement times, with constant core radiated power and no evidence of high-Z or low-Z impurity accumulation. The lithium granules injection reduced the edge plasma pedestal density and temperature and their gradients, due to increased edge radiation and reduced recycling from the plasma-facing components. Ideal stability calculations using the ELITE code indicate that the stabilization of large ELMs correlates with improved stability of intermediate-n peeling-ballooning modes, due to reduced edge current resulting from the profile changes. The pedestal pressure reduction was partially offset by a core density increase, which resulted in a modest ~7% drop in core stored energy and normalized energy confinement time. We surmise that the remnant small ELMs are triggered by the penetration of multiple Li granules just past the separatrix, similar to small ELMs triggered by deuterium pellet Futatani et al (2014 Nucl. Fusion 54 073008). This study extends previous ELM elimination with Li powder injection Maingi et al (2018 Nucl. Fusion 58 024003) in EAST because (1) use of small, dust-like powder and the related potential health hazards were eliminated, and (2) use of macroscopic granules should be more applicable to future devices, due to deeper penetration than dust particles, e.g. inside the separatrix with velocities ~10 m s -1 in EAST.
Flying focus techniques produce laser pulses whose focal points travel at arbitrary, controllable velocities. While this flexibility can enhance a broad range of laser-based applications, existing techniques constrain the motion of the focal point to the propagation direction of the pulse. Here, we introduce a flying focus configuration that decouples the motion of the focus from the propagation direction. Here, a chirped laser pulse focused and diffracted by a diffractive lens and grating creates a focal point that can move both along and transverse to the propagation direction. The focal length of the lens, grating period, and chirp can be tuned to control the direction and velocity of the focus. Simulations demonstrate this control for a holographic configuration suited to high-power pulses, in which two off-axis pump beams with different focal lengths encode the equivalent phase of a chromatic lens and grating in a gas or plasma. For low-power pulses, conventional solid-state or adaptive optics can be used instead. Multi-dimensional control over the focal trajectory enables new configurations for applications, including laser wakefield acceleration of ions, nonlinear Thomson scattering, and surface-plasmon emission of THz radiation.
Experimental particle physics uses machine learning for many tasks, where one application is to classify signal and background events. This classification can be used to bin an analysis region to enhance the expected significance for a mass resonance search. In natural language processing, one of the leading neural network architectures is the transformer. In this work, an event classifier transformer is proposed to bin an analysis region, in which the network is trained with special techniques. The techniques developed here can enhance the significance and reduce the correlation between the network’s output and the reconstructed mass. It is found that this trained network can perform better than boosted decision trees and feed-forward networks. Published by the American Physical Society 2024
Haze, which occurs as a result of the scattering of light in the atmosphere by small particles, diminishes the visibility of scene objects, inflicting important image applications such as object detection. To address the problem, this paper introduces a new physics-based end-to-end deep learning approach to haze mitigation in outdoor scenes, including those in airborne images. The proposed model named DenseCL is designed with dense blocks and adopts a contrastive loss function as an additional regularization. The model also maintains the cycle consistency by remapping the dehazed outputs into a hazy image using the physics-based light scattering function. DenseCL has been trained with publicly available outdoor images and demonstrates outstanding performance on outdoor, indoor, and remotely sensed nonhomogeneous haze satellite images.