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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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The transformation of captured CO 2 into value-added chemicals to mitigate increasing CO 2 concentration in the atmosphere has gained significant attention recently.
Colloidal semiconductor nanocrystals (NCs) represent a promising class of nanomaterials for lasing applications. Currently, one of the key challenges facing the development of high-performance NC optical gain media lies in enhancing the lifetime of biexciton populations. This usually requires the employment of charge-delocalizing particle architectures, such as core/shell NCs, nanorods, and nanoplatelets. Here, we report on a two-dimensional nanoshell quantum dot (QD) morphology that enables a strong delocalization of photoinduced charges, leading to enhanced biexciton lifetimes and low lasing thresholds. A unique combination of a large exciton volume and a smoothed potential gradient across interfaces of the reported CdS bulk /CdSe/CdS shell (core/shell/shell) nanoshell QDs results in strong suppression of Auger processes, which was manifested in this work though the observation of stable amplified stimulated emission (ASE) at low pump fluences. An extensive charge delocalization in nanoshell QDs was confirmed by transient absorption measurements, showing that the presence of a bulk-size core in CdS bulk /CdSe/CdS shell QDs reduces exciton–exciton interactions. Altogether, present findings demonstrate unique advantages of the nanoshell QD architecture as a promising optical gain medium in solid-state lighting and lasing applications.
Nanoparticle-based platforms are gaining strong interest in plant biology and bioenergy research to monitor and control biological processes in whole plants. However, in vivo monitoring of biomolecules using nanoparticles inside plant cells remains challenging due to the impenetrability of the plant cell wall to nanoparticles beyond the exclusion limits (5-20 nm). To overcome this physical barrier, we have designed unique bimetallic silver-coated gold nanorods (AuNR@Ag) capable of entering plant cells, while conserving key plasmonic properties in the near-infrared (NIR). To demonstrate cellular internalization and tracking of the nanorods inside plant tissue, we used a comprehensive multimodal imaging approach that included transmission electron microscopy (TEM), confocal fluorescence microscopy, two-photon luminescence (TPL), X-ray fluorescence microscopy (XRF), and photoacoustics imaging (PAI). We successfully acquired SERS signals of nanorods in vivo inside plant cells of tobacco leaves. On the same leaf samples, we applied orthogonal imaging methods, TPL and PAI techniques for in vivo imaging of the nanorods. This study first demonstrates the intracellular internalization of AuNR@Ag inside whole plant systems for in vivo SERS analysis in tobacco cells. This work demonstrates the potential of this nanoplatform as a new nanotool for intracellular in vivo biosensing for plant biology.
Semiconductor quantum shells – an emerging nanomaterial class for optical gain media, photovoltaic, and high-energy radiation detection applications.
Despite the large binding energy of charge transfer (CT) excitons in type-II organic/2D heterostructures, it has been demonstrated that free carriers can be generated from CT excitons with a long lifetime. Using a model fluorinated zine phthalocyanine (F 8 ZnPc)/monolayer-WS 2 interface, we find that CT excitons can dissociate spontaneously into free carriers despite it being an enthalpy-uphill process. Specifically, it is observed that CT excitons can gain an energy of 250 meV in 50 ps and dissociate into free carriers without any applied electric field. This observation is surprising because excited electrons typically lose energy to the environment and relax to lower energy states. Here, we hypothesize that this abnormal enthalpy-uphill CT exciton dissociation process is driven by entropy gain. Kinetically, the entropic driving force can also reduce the rate for the reverse process – the conversion of free electron–hole pairs back to CT excitons. Hence, this mechanism can potentially explain the very long carrier lifetime observed in organic/2D heterostructures.
The rapid growth of automated and autonomous instrumentation brings forth opportunities for the co-orchestration of multimodal tools that are equipped with multiple sequential detection methods or several characterization techniques to explore identical samples. This is exemplified by combinatorial libraries that can be explored in multiple locations via multiple tools simultaneously or downstream characterization in automated synthesis systems. In co-orchestration approaches, information gained in one modality should accelerate the discovery of other modalities. Correspondingly, an orchestrating agent should select the measurement modality based on the anticipated knowledge gain and measurement cost. Herein, we propose and implement a co-orchestration approach for conducting measurements with complex observables, such as spectra or images. The method relies on combining dimensionality reduction by variational autoencoders with representation learning for control over the latent space structure and integration into an iterative workflow via multi-task Gaussian Processes (GPs). This approach further allows for the native incorporation of the system's physics via a probabilistic model as a mean function of the GPs. We illustrate this method for different modes of piezoresponse force microscopy and micro-Raman spectroscopy on a combinatorial Sm-BiFeO3 library. However, the proposed framework is general and can be extended to multiple measurement modalities and arbitrary dimensionality of the measured signals.
Iron-based Prussian blue analogues (PBAs) have gained attention as low-cost, relatively higher-potential cathodes for sodium-ion batteries, due to their open 3D-framework structures. However, understanding the local structural changes is critical to unveiling the intercalation pathways and degradation mechanisms. We employ here operando Raman spectroscopy to probe the changes in the cyanide vibrational modes during cycling and degradation after cycling, which are not adequately resolved by X-ray diffraction due to the low structure factor and limited X-ray sensitivity of the cyanide groups. Vibrational spectroscopy has thus proven essential for deciphering these complex materials. Additionally, we implement pre-sodiation strategies to assess the impact of sodium inventory loss by pairing PBAs with a hard carbon anode in a full-cell configuration. Operando galvanostatic electrochemical impedance spectroscopy (EIS) and ex situ X-ray photoelectron spectroscopy (XPS) further elucidate the interface evolution and the role of water molecules in forming the cathode-electrolyte interphase (CEI) and solid-electrolyte interphase (SEI). The insights gained advance the understanding of PBAs and enhance their practical viability.
Harmonic instability events between modular multilevel converter (MMC) and ac systems have been widely reported in recent years. To damp harmonic resonance, this paper proposes an adaptive narrowband damping control that automatically programs, adds, and adjusts the damping around the oscillation frequency when an oscillation is detected. First, the paper presents a low-pass filter design for MMC control loops that pushes all negative damping of the MMC impedance down to the medium-frequency range (< ~ 1000 Hz). Then, an adaptive damping control that uses online oscillation detection is proposed, which can automatically configure the narrowband damper to provide positive damping to the MMC around the detected oscillation frequency. In contrast to existing narrowband damping methods, the proposed adaptive narrowband damper dynamically adjusts the damping gain and the width of the damping range based on continuous monitoring of system resonance conditions (e.g., adjust damping gain to zero when the system resonance disappears). Electromagnetic transient simulation results validate the efficacy of the proposed method in two typical MMC-based power systems.
Context. The response of imaging atmospheric Cherenkov telescopes to incident γ -ray-initiated showers in the atmosphere changes as the telescopes age due to exposure to light and weather. These aging processes affect the reconstructed energies of the events and γ -ray fluxes. Aims. This work discusses the implementation of signal calibration methods for the Very Energetic Radiation Imaging Telescope Array System (VERITAS) to account for changes in the optical throughput and detector performance over time. Methods. The total throughput of a Cherenkov telescope is the product of camera-dependent factors, such as the photomultiplier tube gains and their quantum efficiencies, and the mirror reflectivity and Winston cone response to incoming radiation. This document summarizes different methods to determine how the camera gains and mirror reflectivity have evolved over time and how we can calibrate this changing throughput in reconstruction pipelines for imaging atmospheric Cherenkov telescopes. The implementation is validated against seven years of observations with the VERITAS telescopes of the Crab Nebula, which is a reference object in very-high-energy astronomy. Results. Regular optical throughput monitoring and the corresponding signal calibrations are found to be critical for the reconstruction of extensive air shower images. The proposed implementation is applied as a correction to the signals of the photomultiplier tubes in the telescope simulation to produce fine-tuned instrument response functions. This method is shown to be effective for calibrating the acquired γ -ray data and for recovering the correct energy of the events and photon fluxes. At the same time, it keeps the computational effort of generating Monte Carlo simulations for instrument response functions affordably low.
We present Planck Low Frequency Instrument (LFI) frequency sky maps derived within the BEYONDPLANCK framework. This framework draws samples from a global posterior distribution that includes instrumental, astrophysical, and cosmological parameters, and the main product is an entire ensemble of frequency sky map samples, each of which corresponds to one possible realization of the various modeled instrumental systematic corrections, including correlated noise, time-variable gain, as well as far sidelobe and bandpass corrections. This ensemble allows for computationally convenient end-to-end propagation of low-level instrumental uncertainties into higher-level science products, including astrophysical component maps, angular power spectra, and cosmological parameters. We show that the two dominant sources of LFI instrumental systematic uncertainties are correlated noise and gain fluctuations, and the products presented here support – for the first time – full Bayesian error propagation for these effects at full angular resolution. We compared our posterior mean maps with traditional frequency maps delivered by the Planck Collaboration, and find generally good agreement. The most important quality improvement is due to significantly lower calibration uncertainties in the new processing, as we find a fractional absolute calibration uncertainty at 70 GHz of Δg 0 /g 0 = 5 x 10 -5 , which is nominally 40 times smaller than that reported by Planck 2018. However, we also note that the original Planck 2018 estimate has a nontrivial statistical interpretation, and this further illustrates the advantage of the new framework in terms of producing self-consistent and well-defined error estimates of all involved quantities without the need of ad hoc uncertainty contributions. We describe how low-resolution data products, including dense pixel-pixel covariance matrices, may be produced from the posterior samples directly, without the need for computationally expensive analytic calculations or simulations. We conclude that posterior-based frequency map sampling provides unique capabilities in terms of low-level systematics modeling and error propagation, and may play an important role for future Cosmic Microwave Background (CMB) B-mode experiments aiming at nanokelvin precision.
We describe the BEYONDPLANCK project in terms of our motivation, methodology, and main products, and provide a guide to a set of companion papers that describe each result in more detail. Building directly on experience from ESA’s Planck mission, we implemented a complete end-to-end Bayesian analysis framework for the Planck Low Frequency Instrument (LFI) observations. The primary product is a full joint posterior distribution P(ω | d), where ω represents the set of all free instrumental (gain, correlated noise, bandpass, etc.), astrophysical (synchrotron, free-free, thermal dust emission, etc.), and cosmological (cosmic microwave background – CMB – map, power spectrum, etc.) parameters. Some notable advantages of this approach compared to a traditional pipeline procedure are seamless end-to-end propagation of uncertainties; accurate modeling of both astrophysical and instrumental effects in the most natural basis for each uncertain quantity; optimized computational costs with little or no need for intermediate human interaction between various analysis steps; and a complete overview of the entire analysis process within one single framework. As a practical demonstration of this framework, we focus in particular on low-ℓ CMB polarization reconstruction with Planck LFI. In this process, we identify several important new effects that have not been accounted for in previous pipelines, including gain over-smoothing and time-variable and non-1/f correlated noise in the 30 and 44 GHz channels. Modeling and mitigating both previously known and newly discovered systematic effects, we find that all results are consistent with the ΛCDM model, and we constrained the reionization optical depth to τ = 0.066 ± 0.013, with a low-resolution CMB-based χ 2 probability to exceed of 32%. This uncertainty is about 30% larger than the official pipelines, arising from taking a more complete instrumental model into account. The marginal CMB solar dipole amplitude is 3362.7 ± 1.4 μK, where the error bar was derived directly from the posterior distribution without the need of any ad hoc instrumental corrections. We are currently not aware of any significant unmodeled systematic effects remaining in the Planck LFI data, and, for the first time, the 44 GHz channel is fully exploited in the current analysis. We argue that this framework can play a central role in the analysis of many current and future high-sensitivity CMB experiments, including LiteBIRD, and it will serve as the computational foundation of the emerging community-wide COSMOGLOBE effort, which aims to combine state-of-the-art radio, microwave, and submillimeter data sets into one global astrophysical model.
One critical step on the path from data taking to physics analysis is calibration. For many experiments this step is both time consuming and computationally expensive. The AI Experimental Calibration and Control project seeks to address these issues, starting first with the GlueX Central Drift Chamber (CDC). We demonstrate the ability of a Gaussian Process to estimate the gain correction factor (GCF) of the GlueX CDC accurately, and also the uncertainty of this estimate. Using the estimated GCF, the developed system infers a new high voltage (HV) setting that stabilizes the GCF in the face of changing environmental conditions. This happens in near real time during data taking and produces data which are already approximately gain-calibrated, eliminating the cost of performing those calibrations which vary ±15% with fixed HV. We also demonstrate an implementation of an uncertainty aware system which exploits a key feature of a Gaussian process.
We describe the Moderator Test Station (MTS), under construction at the Spallation Neutron Source. We will leverage the Beam Test Facility (BTF) at the Spallation Neutron Source to provide a moderator neutronics test stand with which we will verify the anticipated performance gains expected and required from the innovative moderator concepts central to the SNS Second Target Station (STS) and the future of the First Target Station (FTS). These concepts include large-volume para-hydrogen moderators and high-brightness tube moderators. The MTS will add to the existing BTF a proton beam chopper similar to that already used in the SNS at the RFQ exit (the so-called MEBT chopper), various proton beam transport components, a neutron-producing target, a cryogenic moderator test stand, a reflector-shielding assembly, and a performance assessment neutron beamline. The MTS will provide the ability to test a wide variety of moderators in a prototypic configuration, simultaneously measuring the neutronic performance of the moderator concept central to the anticipated STS gains and developing the instrumentation necessary to provide that performance in a production environment. The presentation will describe the MTS, its progress, and the way we optimize the prototypic nature of the moderators we will test.
This work introduces automated machine learning workflows that address critical bottlenecks in surrogate model development for Ion Cyclotron Range of Frequencies (ICRF) heating applications. The automated framework includes data analysis tools that transform raw datasets into actionable insights in seconds, replacing weeks of manual exploratory effort and ensuring consistent, reproducible dataset characterization. By integrating advanced hyperparameter optimization (HPO) methods including Bayesian optimization via BoTorch and Tree-structured Parzen Estimators (TPE), the framework significantly reduces model development time from weeks to hours, decreasing computational cost and required expertise, while enabling high-accuracy surrogate models. Compared to traditional hyperparameter scanning (HPS) techniques such as methodical, randomized, and grid searches, HPO methods achieve superior convergence and predictive performance, even when compared to already well-tuned reference models. On NSTX High Harmonic Fast Wave (HHFW) heating datasets, both Random Forest Regressor (RFR) and neural network surrogates demonstrate improved accuracy, achieving R 2 values beyond 0.97 and 0.98, respectively. The results show that while HPO gains are modest for robust architectures like RFR, they become essential for more sensitive models such as neural networks, highlighting the trade-offs across optimization strategies. Through automated workflows that eliminate manual hyperparameter tuning and require minimal ML expertise, this work enables widespread adoption of high-fidelity surrogate models across the fusion community for real-time plasma control, uncertainty quantification, rapid experimental scenario development, and integrated system optimization.
The helicity injected torus-steady inductive (HIT-SI) experiment uses steady inductive helicity injection to form a spheromak equilibrium and sustain the structure against resistive decay. Helicity injection is performed using two half-tori “injectors” connected to the main plasma volume, whose fields are oscillated in an AC manner. The properties of the sustained spheromak equilibrium have been experimentally observed to vary with the frequency of the injector oscillation, producing higher current gains and more-symmetric and outwardly shifted current centroids with higher frequency. A computational scan of injector frequency using the 3D MHD code PSI-Tet, which models the entire HIT-SI plasma volume including the injectors, has been performed, including a comparison of the results using the full Hall MHD model to those obtained using a simplified “zero-beta” (constant temperature and density) model. The results of both PSI-Tet models are also compared with experimental data and with simulations using the NIMROD code, which does not model the injector regions. The results of the PSI-Tet simulations show that the average temperature and current gain increase with injector frequency, in agreement with experimental trends. The simulations also show qualitative changes in the dynamics of several quantities with increasing injector frequency, such as density oscillations and current evolution. However, the outward shift and symmetrizing of the current centroid, observed experimentally, are not observed in these MHD simulations, indicating that unresolved or excluded dynamics may be important.
We present 2D particle-in-cell simulations of laser-plasma instabilities (LPI) performed using conditions relevant to experiments on the OMEGA and NIF laser facilities. The laser intensity used is 2×10 15 W cm -2 , which allows comparison with previous experiments and simulations investigating shock ignition, though this is a relatively low intensity for the scheme. We find that the large convective gain of the instabilities leads to dynamics that are largely controlled by pump depletion and to scattering or absorption by LPIs predominantly occurring away from the quarter-critical density. The two-plasmon decay (TPD) instability is dominant for OMEGA-type conditions and remains important at the NIF-scale. In both cases, most absorption from TPD occurs near its Landau cutoff density, and we examine its nonlinear dynamics in this region, focusing on the ion-acoustic waves responsible for saturation. For NIF-type conditions, stimulated Raman scattering (SRS) and stimulated Brillouin scattering divert significant fractions of laser energy, and we find that SRS backscatter can occur with high gain at low densities due to kinetic effects. An in-depth analysis of hot-electron production is performed to identify the main sources and their characteristic electron temperature. For both simulations presented, the overall hot-electron temperature lies between 30 and 35 keV. This is relatively low and will likely increase shock pressure; however, the distributions also contain a significant number of high-energy (E k >100 keV) electrons that would likely cause unacceptable preheat. We, therefore, suggest some strategies that may be utilized to minimize this high-energy component. I. INTROD
This paper deals with a significant family of compounds predicted by simplistic electronic structure theory to be metals but are, in fact, insulators. This false metallic state has been traditionally attributed in the literature to reflect the absence of proper treatment of electron-electron correlation (“Mott insulators”) whereas, in fact, even mean-field like density functional theory describes the insulating phase correctly if the restrictions posed on the simplistic theory are avoided. Such unwarranted restrictions included different forms of disallowing symmetry breaking described in this article. As the science and technology of conductors have transitioned from studying simple elemental metals such as Al or Cu to compound conductors such as binary or ternary oxides and pnictides, a special class of degenerate but gapped metals has been noticed. Their presumed electronic configurations show the Fermi level inside the conduction band or valence band, yet there is an “internal band gap” between the principal band edges. The significance of this electronic configuration is that it might be unstable toward the formation of states inside the internal band gap when the formation of such states costs less energy than the energy gained by transferring carriers from the conduction band to these lower energy acceptor states, changing the original (false) metal to an insulator. The analogous process also exists for degenerate but gapped metals with the Fermi level inside the valence band, where the energy gain is defined by transfer of electrons from the donor level to the unoccupied part of the valence band. We focus here on the fact that numerous electronic structure methodologies have overlooked some physical factors that could stabilize the insulating alternative, predicting instead false metals that do not really exist (note that this is in general not a physical phase transition, but a correction of a previous error in theory that led to a false prediction of a metal). Such errors include: (i) ignoring spin symmetry breaking, such as disallowing magnetic spin ordering in CuBi2O4 or disallowing the formation of polymorphous spin networks in paramagnetic LaTiO 3 and YTiO 3 ; (ii) ignoring structural symmetry breaking, e.g., not enabling energy-lowering bond disproportionation (Li-doped TiO 2 , SrBiO 3 , and rare-earth nickelates), or not exploring pseudo-Jahn–Teller-like distortions in LaMnO 3 , or disallowing spontaneous formation of ordered vacancy compounds in Ba 4 As 3 and Ag 3 Al 22 O 34 ; and (iii) ignoring spin–orbit coupling forcing false metallic states in CaIrO 3 and Sr 2 IrO 4 . The distinction between false metals vs real insulators is important because (a) predicting theoretically that a given compound is metal even though it is found to be an insulator often creates the temptation to invoke high order novel physical effects (such as correlation in d-electron Mott insulators) to explain what was in effect caused by a more mundane artifact in a lower-level mean-field band theory, (b) recent prediction of exotic physical effects such as topological semimetals were unfortunately based on the above compounds that were misconstrued by theory to be metal, but are now recognized to be stable insulators not hosting exotic effects, and (c) practical technological applications based on stable degenerate but gapped metals such as transparent conductors or electrides for catalysis must rely on the systematically correct and reliable theoretical classification of metals vs insulators.
Oxygen vacancies are found to play a crucial role in inducing many functional properties at the heterointerfaces in complex oxides. Gaining better control over the properties requires an understanding of the atomic structure of oxygen vacancies at the heterointerfaces. In this paper, we elucidate the effects of the interfacial strain on the oxygen-vacancy ordering in fluorite δ-Bi 2 O 3 and perovskite LaNiO 2.5 using first-principles calculations. By applying biaxial strains, we find that the <110>-<111> oxygen vacancy order in δ-Bi2O3 is broken, resulting in a faster diffusion of oxygen ions. Similarly, the biaxial strain is used to leverage both ordered and disordered arrangements of vacancies in LaNiO 2.5 . Besides the vacancy order, we find that the biaxial strain can also be used to break the cation order in Gd 2 Ti 2 O 7 , where Gd and Ti antisites can be created on the cation sublattice, which leads to enhanced radiation tolerance and higher oxygen diffusivity. Overall, these results indicate that the biaxial strain that is commonly present at heterointerfaces can be used to gain control over both ordered and disordered arrangements of defects, potentially opening new opportunities to functionalize complex oxides.