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3,213 records · Page 13

Cryogenic Flow Boiling in Microgravity: Effects of Reduced Gravity on Two-Phase Fluid Physics and Heat Transfer

With the growing interest in space exploration, cryogenic technologies involving two-phase flow and heat transfer are in high demand to successfully procure advanced space applications such as fuel depots and nuclear thermal propulsion (NTP) systems for deep space missions. However, the unique and extreme thermal properties of cryogenic fluids introduce distinct flow boiling fluid physics and energy transport phenomena, which differ significantly from those observed with conventional fluids. Understanding the unique two-phase physics in cryogenic flow boiling remains an ongoing challenge. Furthermore, the lack of readily available microgravity cryogenic steady-state heat transfer data hinders the assessment of gravitational effects on cryogenic flow boiling. This study aims to elucidate the gravitational effects on two-phase fluid physics and heat transfer by conducting the first-ever experimental measurement of cryogenic flow boiling performance using a steady-state heated method in a reduced gravity environment. Parabolic flight experiments were performed to acquire both heat transfer measurements and high-speed video of interfacial behaviors, under varying gravity levels (microgravity, hypergravity, Lunar gravity, and Martian gravity). The experiments involved flow boiling of liquid nitrogen (LN 2 ) with a near-saturated inlet along a circular heated tube of dimensions 8.5-mm inner diameter and 680-mm heated length. The operating parameters varied are mass velocity of 398.3 - 1342.8 kg/m2s, inlet quality of -0.08 to -0.01, and inlet pressure of 413.68 - 689.48 kPa. Captured microgravity flow patterns range from bubbly to annular, all having vapor structures that are larger than those under higher gravity levels. Under microgravity, absence of buoyancy yields symmetrical vapor structures without flow stratification, laying a physical foundation for the distinct two-phase heat transfer trends during LN 2 flow boiling in microgravity. Transient data collected during the flight parabolas exhibited decreasing heated wall temperature as the aircraft transitioned from hypergravity to microgravity phases. The temperature variation indicated an enhancement in flow boiling heat transfer with decreasing gravity levels and a reduction with increasing gravity levels. The effect of reduced gravity on cryogenic flow boiling heat transfer coefficient (HTC) is discussed based on steady state heat transfer analysis. Seminal HTC correlations are evaluated against the measured microgravity HTC data, of which one is identified for superior accuracy in predicting microgravity data. Finally, a new HTC correlation is proposed to improve accuracy of microgravity predictions, yet there still exists room for further improvement with future terrestrial flow boiling experiments at different flow orientations relative to Earth gravity.

Microgravity

Sparse non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations

The influence of noise on quantum dynamics is one of the main factors preventing current quantum processors from performing accurate quantum computations. Sufficient noise characterization and modeling can provide key insights into the effect of noise on quantum algorithms and inform the design of targeted error protection protocols. However, constructing effective noise models that are sparse in model parameters, yet predictive can be challenging. In this work, we present an approach for effective noise modeling of multi-qubit operations on transmon-based devices. Through a comprehensive characterization of seven devices offered by the IBM Quantum Platform, we show that the model can capture and predict a wide range of single- and two-qubit behaviors, including non-Markovian effects resulting from spatiotemporally correlated noise sources. The model’s predictive power is further highlighted through multi-qubit dynamical decoupling demonstrations and an implementation of the variational quantum eigensolver. As a training proxy for the hardware, we show that the model can predict expectation values within a relative error of 0.5%; this is a sevenfold improvement over default hardware noise models. Through these demonstrations, we highlight key error sources in superconducting qubits and illustrate the utility of reduced noise models for predicting hardware dynamics.

open quantum systems & decoherence

Physical Parameters of Space Mission Asteroid Targets

Ground-based characterization of asteroids that are planned or potential targets of space missions provides important data on their physical parameters and properties. Knowledge of the properties of mission targets is important especially during mission preparation and planning, as it serves to select best or suitable targets for specific purpose of a given mission, to prepare mission plans, to constrain possible mission scenarios, and to design mission experiments. Such characterization efforts may be particularly critical for flyby missions that take only limited data during the high-speed flybys of their target asteroids, but they also provide very crucial data for targets of rendezvous missions. Moreover, long-term observations taken from Earth also allows the modelling of, or constraining, processes acting on the asteroids over extended time scales. Over the past years and decades we have obtained rich data on physical parameters of 82 asteroids that are planned or potential targets of space missions. Our primary observing technique is time-resolved (lightcurve) photometry, but we use also data obtained with other techniques, such as spectroscopy, thermal or radar observations. 15 of the 82 characterized asteroids are planned or possible targets of several space missions that are in flight or preparation, such as ESA’s Hera, RAMSES and PRIAMOS, NASA’s OSIRIS-APEX, JAXA’s Hayabusa2#, DESTINY+ and Next Generation Sample Return (NGSR), the Emirates Mission to Asteroids (EMA), and Karman+’s High Frontier, but we have also characterized 67 asteroids that are potential targets of space missions for their low delta-V’s and were announced as being “of interest to NASA” in the Small-Bodies-Observations- NASA mailing list or listed on the NHATS page of “Accessible NEAs”. The sample of asteroid targets span 3 orders of magnitude in size, with absolute magnitudes H from 12.57 to 26.8, corresponding to diameters from about 10 m to about 10 km. The sample contains a variety of taxonomic types and physically or dynamically interesting objects. Among them, we have identified 5 binary asteroids and 20 tumblers (i.e., asteroids in excited, non-principal axis rotation states). Rotation periods of the characterized asteroids range from 1.45 min to 280 h, reflecting diversity of their properties and formation/evolution paths. We will present an overview of the data set and highlight several representative cases.

Petr Pravec

Wettability of Two-Dimensional Carbon Allotropes from Molecular Simulations

Force-field Monte Carlo and Molecular Dynamics simulations are used to compare wetting behaviors of model carbon sheets mimicking neat graphene, its saturated derivative, graphane, and related planar allotropes penta-graphene, γ-graphyne, and ψ-graphene in contact with aqueous droplets or an aqueous film confined between parallel carbon sheets. Atomistic and area-integrated surface/water potentials are found to be essentially equivalent in capturing moderate differences between the wetting free energies of tested substrates. Despite notable differences in mechanical and electric properties of distinct allotropes, the predicted allotrope/water contact angles span a narrow window of weakly hydrophilic values. Contact angles in the range of 80 ± 10° indicate modest hydration repulsion incapable of competing with van der Waals attraction between carbon particles. Poor dispersibility in neat water is hence a common feature of studied materials.

Biochemistry & Molecular Biology

Monte Carlo modeling of atomic oxygen attack of polymers with protective coatings on LDEF

Characterization of the behavior of atomic oxygen interaction with materials on the Long Duration Exposure Facility (LDEF) will assist in understanding the mechanisms involved, and will lead to improved reliability in predicting in-space durability of materials based on ground laboratory testing. A computational simulation of atomic oxygen interaction with protected polymers was developed using Monte Carlo techniques. Through the use of assumed mechanistic behavior of atomic oxygen and results of both ground laboratory and LDEF data, a predictive Monte Carlo model was developed which simulates the oxidation processes that occur on polymers with applied protective coatings that have defects. The use of high atomic oxygen fluence-directed ram LDEF results has enabled mechanistic implications to be made by adjusting Monte Carlo modeling assumptions to match observed results based on scanning electron microscopy. Modeling assumptions, implications, and predictions are presented, along with comparison of observed ground laboratory and LDEF results.

Bruce A. Banks

A physically interpretable precursor framework for sub-seasonal prediction of Northern Hemisphere flash flourishing

Flash flourishing describes rapid vegetation increases that can quickly reshape land–atmosphere exchanges and impacts on ecosystem, yet its large-scale precursors, circulation context, and sub-seasonal predictability remain poorly understood. Here, we identified onset-stage circulation regimes across northern extratropical latitudes (NEL; >30°N) using 200 and 1000 hPa geopotential height, and examined their regional expressions over eastern Asia, western North America, and Europe. Flash flourishing onset in East Asian was associated with a baroclinic circulation regime and was preceded by a North Atlantic sea surface temperature (SST) precursor at a four-pentad lead. In contrast, onset in western North American and European preferentially occurred under barotropic regimes, preconditioned by Great Plains soil moisture at three-pentad lead and North Atlantic SST at a four-pentad lead, respectively. Ridge regression forecasts revealed regime-dependent sub-seasonal predictability, with mean out-of-sample R 2 exceeding 0.3 up to lead times of two pentads in East Asia, three pentads in western North America, and four pentads in Europe. Together, these findings established a mechanistic and regionally specific framework for anticipating rapid vegetation greening at sub-seasonal timescales.

Kong, Xiangxu [Nanjing Univ. of Information Scienc

Machine Learning for Multipactor Susceptibility Prediction in Planar RF Gaps

Multipactor discharge is a nonlinear electron avalanche that limits the performance of high-power radio-frequency (RF) and vacuum electronic devices. Predicting multipactor susceptibility traditionally relies on Monte Carlo or particle-in-cell (PIC) simulations, which become computationally expensive for large parametric studies. In this work, we present a supervised machine-learning (ML) framework for prediction of multipactor susceptibility in a two-surface planar geometry. The models are trained using high-fidelity PIC simulation generated susceptibility data and learn the relationship between operational parameters, geometry, and material-dependent secondary electron emission properties. The proposed approach enables rapid reconstruction of susceptibility charts while preserving the physical structure of multipactor growth regions.

43 PARTICLE ACCELERATORS

Thin Film Sensors for Fission Surface Power

Physical sensors fabricated with thin films could result a significant savings in space and weight with improved reliability for monitoring the long-term operation of fission surface power systems. Thin film sensors of 1 µm or less are attractive for FSP applications because they can be incorporated onto component surfaces with minimal machining and the additional weight to a system is minimal compared to thick film-, wire-, or foil-based sensors. The thin, surface fabrication of the sensors is also expected to make them less susceptible to deep dose effects that affect thicker sensors. An overview of thin film sensors using thermocouples and resistive elements designed, fabricated, and demonstrated at GRC for aerospace applications exceeding 900°C is presented.

Physical Sensors

A Study of Space Environment Effect on Highly Thermally Conductive Hybrid Carbon Fiber Polymer Composites

A set of novel highly thermally conductive hybrid carbon fiber (CF) polymer composites has been developed for lightweight thermal radiator applications in space missions. This study investigates the effects of the space environment on these materials following exposure in low-Earth orbit (LEO) during the Materials International Space Station Experiment (MISSE)-17 flight mission, where samples experienced 159 days of combined atomic oxygen (AO), ultraviolet (UV) radiation, high vacuum, space radiation and thermal cycling. Post-flight characterization included weight loss, surface morphology, thermo-optical properties, molecular structures, glass transition temperature, thermal degradation and thermal conductivity analyses. The pyrolytic graphite sheet (PGS) samples exhibited negligible weight loss, stable thermo-optical property, and only minor oxidation signature on the exposed surface. Although AO erosion of the epoxy polymer matrix was evident, carbon nanotube (CNT)-infused PGS/CF epoxy composites retained high thermal emissivity and preserved their high thermal conductivities. These results demonstrate that the novel highly thermally conductive hybrid CF composites possess strong environmental resilience and are promising candidates for lightweight thermal radiators and thermal management components in future space exploration missions.

Space Environment

The SPT-deep Cluster Catalog: Sunyaev–Zel’dovich Selected Clusters from Combined SPT-3G and SPTpol Measurements over 100 Square Degrees

We present a catalog of 500 galaxy cluster candidates in the SPT-Deep field: a 100 deg$^{2}$ field that combines data from the SPT-3G and SPTpol surveys to reach noise levels of 3.0, 2.2, and 9.0 μK-arcmin at 95, 150, and 220 GHz, respectively. Candidates are selected via the thermal Sunyaev–Zel’dovich (SZ) effect with a minimum significance of ξ = 4.0, resulting in a catalog of purity ∼89%. Optical data from the Dark Energy Survey and infrared data from the Spitzer Space Telescope are used to confirm 442 cluster candidates. The clusters span 0.12 < z ≲ 1.8 and 1.0 × 10$^{14}$M$_{⊙}$/h$_{70}$ < M$_{500c}$ < 8.7 × 10$^{14}$M$_{⊙}$/h$_{70}$. The sample’s median redshift is 0.74, and the median mass is 1.7 × 10$^{14}$M$_{⊙}$/h$_{70}$; these are the lowest median mass and highest median redshift of any SZ-selected sample to date. We assess the effect of infrared emission from cluster member galaxies on cluster selection by performing a joint fit to the infrared dust and tSZ signals by combining measurements from SPT and overlapping submillimeter data from Herschel/SPIRE. We find that at high redshift (z > 1), the tSZ signal is reduced by $17.9_{−3.2}^{+3.8}$%$(3.8_{−0.7}^{+0.9}$%$)$ at 150 GHz (95 GHz) due to dust contamination. We repeat our cluster finding method on dust-nulled SPT maps and find the resulting catalog is consistent with the nominal SPT-Deep catalog, suggesting dust contamination does not significantly impact the SPT-Deep selection function; we attribute this lack of bias to the inclusion of the SPT 220 GHz band.

79 ASTRONOMY AND ASTROPHYSICS

Enhanced matter power spectrum from axion kination after Big Bang nucleosynthesis

Despite stringent constraints from Big Bang Nucleosynthesis (BBN) and cosmic microwave background (CMB) observations, it is still possible for well-motivated particle physics models to substantially alter the cosmic expansion history between BBN and recombination. In this work we consider two different axion models that can realize a period of first matter domination, then kination, in this epoch. We perform fits to both primordial element abundances as well as CMB data and determine that up to a decade of late axion domination is allowed by these probes of the early universe. We establish the implications of late axion domination for the matter power spectrum on the scales 1/Mpc ≲ k ≲ 10 3 /Mpc. Our 'log' model predicts a relatively modest bump-like feature together with a small suppression relative to the standard ΛCDM predictions on either side of the enhancement. Our 'two-field' model predicts a larger, plateau-like feature that realizes enhancements to the matter power spectrum of up to two orders of magnitude. These features have interesting implications for structure formation at the forefront of current detection capabilities.

79 ASTRONOMY AND ASTROPHYSICS

Experimental Investigations of Low-Energy (4 to 40 eV) Collisions of O - ( 2 P) Ions and O( 3 P) Atoms With Surfaces

Using a newly-developed, magnetically confined source, low-energy, ground state oxygen negative ions and neutral atoms are generated. The energy range is variable, and atom and neutrals have been generated at energies varying from 2 eV to 40 eV and higher. It was found that the interaction of these low-energy species with a solid magnesium fluoride target leads to optical emissions in the (at least) visible and infrared regions of the spectrum. Researchers describe y details of the photodetachment source, and present spectra of the neutral and ion glows in the wavelength range 250 to 850 nm (for O - ) and 600 to 850 nm (for O), and discuss the variability of the emissions for incident energies between 4 and 40 eV.

A Chutjian

Justification that the Thermo-Fisher Scientific 241 Am Residues Were Generated by Atomic Energy Defense Activities

The Waste Isolation Pilot Plant (WIPP) Land Withdrawal Act (LWA) as amended by the National Defense Authorization Act for Fiscal Year 1997 (1) requires that for Transuranic (TRU) waste to be eligible for disposal at WIPP, it must have been generated by atomic energy defense activities. The definition of “atomic energy defense activity” is defined in the Nuclear Waste Policy Act of 1982 (NWPA) (2).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W

Learning Nonlinear Reduced Models from Data with Operator Inference

This review discusses Operator Inference, a nonintrusive reduced modeling approach that incorporates physical governing equations by defining a structured polynomial form for the reduced model, and then learns the corresponding reduced operators from simulated training data. The polynomial model form of Operator Inference is sufficiently expressive to cover a wide range of nonlinear dynamics found in fluid mechanics and other fields of science and engineering, while still providing efficient reduced model computations. The learning steps of Operator Inference are rooted in classical projection-based model reduction; thus, some of the rich theory of model reduction can be applied to models learned with Operator Inference. This connection to projection-based model reduction theory offers a pathway toward deriving error estimates and gaining insights to improve predictions. Furthermore, through formulations of Operator Inference that preserve Hamiltonian and other structures, important physical properties such as energy conservation can be guaranteed in the predictions of the reduced model beyond the training horizon. This review illustrates key computational steps of Operator Inference through a large-scale combustion example.

Mechanics

Mode Multiplexing for Scalable Cavity-Enhanced Operations in Neutral-Atom Arrays

Neutral-atom arrays provide a versatile platform for quantum information processing. However, in large-scale arrays, efficient photon collection remains a bottleneck for key tasks such as fast, nondestructive qubit readout and remote entanglement distribution. We propose a cavity-based approach that enables fast, parallel operations over many atoms using multiple modes of a single optical cavity. By selectively shifting the relevant atomic transitions, each atom can be coupled to a distinct cavity mode, allowing independent simultaneous processing. We present practical system designs that support cavity-mode multiplexing with up to 50 modes, enabling rapid mid-circuit syndrome extraction and significantly enhancing entanglement distribution rates between remote atom arrays. This approach offers a scalable solution to core challenges in neutral-atom arrays, advancing the development of practical quantum technologies.

Aqua, Ziv [Massachusetts Institute of Technology (

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation