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535 records · Page 19

Pinned in Microgravity: How Colloidal Suspensions Inhibit Droplet Motion

Understanding the fundamental behavior of colloidal fluids in microgravity is critical for advancing material science, manufacturing, and biological processes. In this study we investigate the dynamics of a droplet containing colloidal suspension when ejected in short term microgravity. These conditions are generated using a 2.2 second drop tower. A custom droplet generator was designed to produce consistent size-controlled droplets containing passive colloidal particles. The particles are suspended in water and subsequently ejected out of a hydrophobic wedge under microgravity conditions, where the droplet ejection time can be predicted [Torres & Weislogel, 2021]. The ejection times will be compared with de-ionized water ejected from the same system to investigate the effects of change in density and surface tension caused by the colloids. Successful passive colloidal ejection will lay the foundation for active colloid research in the future.

colloids

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

Dense nuclear matter equation of state from heavy-ion collisions

The nuclear equation of state (EOS) is at the center of numerous theoretical and experimental efforts in nuclear physics. With advances in microscopic theories for nuclear interactions, the availability of experiments probing nuclear matter under conditions not reached before, endeavors to develop sophisticated and reliable transport simulations to interpret these experiments, and the advent of multi-messenger astronomy, the next decade will bring new opportunities for determining the nuclear matter EOS, elucidating its dependence on density, temperature, and isospin asymmetry. Among controlled terrestrial experiments, collisions of heavy nuclei at intermediate beam energies (from a few tens of MeV/nucleon to about 25 GeV/nucleon in the fixed-target frame) probe the widest ranges of baryon density and temperature, enabling studies of nuclear matter from a few tenths to about 5 times the nuclear saturation density and for temperatures from a few to well above a hundred MeV, respectively. Collisions of neutron-rich isotopes further bring the opportunity to probe effects due to the isospin asymmetry. However, capitalizing on the enormous scientific effort aimed at uncovering the dense nuclear matter EOS, both at RHIC and at FRIB as well as at other international facilities, depends on the continued development of state-of-the-art hadronic transport simulations. Furthermore, this white paper highlights the essential role that heavy-ion collision experiments and hadronic transport simulations play in understanding strong interactions in dense nuclear matter, with an emphasis on how these efforts can be used together with microscopic approaches and neutron star studies to uncover the nuclear EOS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Impact of Inertia, Friction, and Backlash upon Force Control in Telemanipulation

The mechanical behavior of master controllers of telemanipulators has been a concern of both designers and implementors of telerobotic systems. In general, the literature recommends that telemanipulator systems be constructed that minimize inertia, friction, and backlash in an effort to improve telemanipulative performance. For the most part, these recommendations are founded upon theoretical analysis or simply intuition. Although these recommendations are not challenged on their merit, the material results are measured of building and fielding telemanipulators that possess less than ideal mechanical behaviors. Experiments are described in which forces in a mechanical system with human input are evaluated as a function of mechanical characteristics such as inertia, friction, and backlash. Results indicate that the ability of the human to maintain gripping forces was relatively unaffected by dynamic characteristics in the range studied, suggesting that telemanipulator design in this range should be based on task level force control requirements rather than human factors.

Neil A Duffie

Thermoplastic Matrix Composite Design for Cryotanks Using Multiscale Modeling and Bayesian Optimization

Designing lightweight, robust cryogenic storage tanks is critical for future launch vehicles, in-space propellant storage, and hydrogen powered aircraft. This work presents a multiscale modeling and Bayesian optimization framework for the design of thermoplastic matrix composite cryotanks. Molecular dynamics simulations are first used to determine temperature-dependent constituent properties for candidate thermoplastic matrices, which are homogenized to the lamina scale using NASA’s Multiscale Analysis Tool (NASMAT). These lamina properties, in combination with laminate family generation rules, are evaluated in HyperX structural optimization software to identify stacking sequences that meet all cryogenic load requirements. A Bayesian optimization framework is applied, with HyperX in the loop (via the HyperX API) to efficiently search across material and laminate design variables, yielding an optimized cryotank configuration with significant reductions in design cycle time compared to exhaustive search approaches.

thermoplastics

Multiscale Modeling of Fracture Strength in Fibrous Thermal Protection System Materials

This work presents a multiscale modeling approach to predict the fracture strength of fibrous Thermal Protection System (TPS) materials. The model assumes that system failure is initiated at the joints between individual fibers. We investigated three distinct TPS compositions: amorphous silica, alumina and aluminosilicate fibers. Molecular dynamics (MD) simulations were employed to determine the fracture strength values of these fiber joints for both material systems. These fracture strength values were then integrated into simulations of 3D randomly populated fiber structures, where tensile load transfer occurs through the fiber joints. These microscale properties are upscaled through a renormalization approach [1] to predict macroscale tensile strength of 3D random fiber networks, accounting for joint-dominated failure and effective load-bearing area. The study concludes by demonstrating the resulting strength variation as a function of material composition, fiber density, and morphology. We also show validation of results by comparing them against explicit fiber finite element (FE) modeling [2] where fiber joint fracture is represented by cohesive elements.

Jaehyun Cho

Prediction of prompt NO(x) in hydrocarbon air flames

The gas turbine industry is directing particular attention to very low NOx combustors, whether for aircraft or land based CCGT systems. These low NOx combustors frequently use liquid fuels or natural gas burning under very lean premixed conditions with air or under rich-lean conditions, although only the first case is studied here. In land based systems, diluted steam or nitrogen are sometimes injected into the combustion chambers to reduce flame temperature. The NOx emissions from such systems are the product of three chemical mechanisms which are interrelated: the hydrocarbon prompt NO, the thermal NO (extended Zeldovich mechanism), and the nitrous oxide route to NO. Formation of NO2 from NO also occurs, as well as emission of carbon monoxide and unburnt hydrocarbons. When the fuel-oxidant proportion decreases towards leaner conditions, flame temperatures are lowered, resulting in the total NO being reduced and the thermal-NO contribution greatly diminished to the benefit of the remaining two mechanisms of NO formation. While knowledge of the elementary reactions and their chemical kinetics concerning methane and simple hydrocarbons combustion has existed for a number of years, its use for computer modeling is limited to simple flow dynamics configurations. Nevertheless, understanding of such combusting flows under a wide range of experimental conditions allows for analogies or speculations with more complex actual systems. Such understanding can be achieved by means of one dimensional laminar premixed flame modeling, with a full chemical mechanism which incorporates the three routes of NO formation. Complementary to this understanding is the modeling of the actual combustion system using a full description of the fluid dynamics coupled with a reduced chemical scheme, which is then compared against the first model. The objective of this investigation is to evaluate the relative importance of the three mechanisms of NO formation in lean premixed methane-air combustion with increasing pressure using the one dimensional plug flow package PREMIX, and to test the validity of a three dimensional model with a global chemical mechanism against the one dimensional model in the atmospheric pressure case. Methane is chosen because it is the only mechanism which is reasonably well known and is a good guide to the behavior of other hydrocarbons. The mixture ratio chosen is richer than that in lean gas turbines, but the combustion of this mixture with the low preheat gives realistic gas turbine final flame temperatures. Conditions of NO2 formation are also analyzed in the one dimensional model and results extrapolated to the case of gas turbines.

Valerie Dupont

Deep RL for Fast Long-Horizon Operations Scheduling on NASA's Carruthers Geocorona Observatory Mission

Spacecraft operations scheduling is a highly constrained, long-horizon combinatorial optimization problem that traditionally relies on heuristics, constraint programming, or manual planning. We present a scalable deep reinforcement learning framework developed and deployed for NASA’s Carruthers Geocorona Observatory mission. Our framework introduces a macro-action abstraction known as activity blocks coupled with dynamic action-masking to navigate the intractably large search space and strictly enforce complex power, thermal, and instrument constraints. The resulting architecture generates globally feasible schedules with overwhelming probability, establishes operational trust, and executes a full training cycle in under six hours, circumventing the need for policy robustness by enabling rapid, on-demand retraining. Further, resulting schedules outperform baseline heuristics in scheduled science quality. The deep reinforcement learning framework was deployed as the default operational scheduler for the Carruthers Geocorona Observatory mission from the outset of the mission, demonstrating that deep reinforcement learning can be trusted for real spacecraft operations under complex, evolving constraints.

Geocorona

BLEECAM™ (Benchmarking Life Cycle Environmental, Economic, and Social Metrics for Critical and Advanced Minerals and Materials) [SWR-25-125]

The National Laboratory of the Rockies' (NLR) Benchmarking Life Cycle Environmental, Economic, and Social Metrics for Critical and Advanced Minerals and Materials (BLEECAM™) is an open-source, integrated decision-support tool for evaluating the impacts, risks, and trade-offs across U.S. and global materials supply chains. Funded by the U.S. Department of Energy, BLEECAM supports supply chain and market analysis. The tool integrates multi-objective supply chain optimization, system dynamics, network design, lifecycle assessment, techno-economic modeling, and social impact assessment methods to evaluate how supply chains evolve over time, geography, and deployment scenarios. BLEECAM also supports analysis related to energy infrastructure, data centers and digital infrastructure, advanced manufacturing, and other sectors that depend on critical materials.

Khalifa, SherifA. [National Laboratory of the Rock

A Missed Thrust Framework for Low-Thrust Spiral Trajectories to the NRHO

A framework is developed by which end-to-end optimization of many-revolution low-thrust spiral trajectories can be completed in the presence of missed thrust events. This framework is applied to the Lunar Transit trajectory by which the initial capability of NASA’s Gateway lunar space station will be delivered to a Near Rectilinear Halo Orbit. This low-thrust mission consists of three subphases, each designed according to the specific objectives and dynamical regimes encountered as the mission progresses from a medium Earth insertion orbit to cislunar space. The presented framework accounts for the unique considerations demanded by each mission phase and incorporates appropriate capabilities into a novel mission analysis tool. This methodology enables large scale and reliable analyses of missed thrust events across the end-to-end Lunar Transit to verify the robustness of flight trajectories across the full range of considered launch dates.

missed thrust

Role of ion acoustic instability in magnetic reconnection

We report on a first-principles numerical study of magnetic reconnection in plasmas with different initial ion-to-electron temperature ratios. In cases where this ratio is significantly below unity, we observe intense wave activity in the diffusion region, driven by the ion-acoustic instability. Our analysis shows that the dominant macroscopic effect of this instability is to drive substantial ion heating. In contrast to earlier studies reporting significant anomalous resistivity, we find that anomalous contributions due to the ion-acoustic instability are minimal. These results shed light on the dynamical impact of this instability on reconnection processes, offering new insights into the fundamental physics governing collisionless reconnection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Diffusion Quantum Monte Carlo Calculation of the Austenite and Martensite Phases of NiTi

NiTi is a promising material for smart and active technologies due to its exhibition of the shape memory effect, superelasticity, and biocompatibility. The shape memory effect is tied to the reversible transition between the austenite and martensite phases. A major research direction is to alloy NiTi with Zr, Hf, Pd, Pt, etc., in order to tune the martensitic transition temperature (MTT). Modeling the MTT from first principles is challenging because the lattice dynamics is complicated by anharmonicity and various low-energy structures. Using density functional theory, the energy difference between the austenite and martensite phases of NiTi varies by up to 100 meV/atom depending on the choice of density functional, which is of the same order of the energy difference itself. Consequently, free energy calculations with different functionals can result in estimates of the MTT that vary by several hundred K. Using diffusion quantum Monte Carlo, we calculated the energy difference between the B2 and B19' structures of NiTi to be 70.9 +- 2.5 meV/atom.

Kevin K Ly

Evaluation of Particle Degradation of a Ytterbium Disilicate Gas Turbine Coating in a Combustion Environment

Ytterbium disilicate (Yb2Si2O7) is a state-of-the-art topcoat material used in environmental barrier coatings (EBCs) to protect SiC-SiC composites from water vapor corrosion in gas turbine engines. However, it’s degradation by thermochemical and thermomechanical particle interactions may limit its use in next generation engine systems. Several static furnace tests have been performed on Yb2Si2O7 to elucidate methods of degradation, although dynamic testing in an engine-relevant environment has not been carried out. Ultimately, testing and evaluation of materials that incorporates all environmental damage modes will allow for an accurate assessment of long-term durability and operating lifetime. This work details the investigation of particle-induced erosion and corrosion of Yb2Si2O7 in NASA Glenn’s Erosion Burner Rig Facility. Coating durability was investigated as a function of test temperature, particle size, and deposition rate. Thermal cycling was also incorporated into testing to determine the interplay of heating/cooling cycles with particle degradation. Overall, these analyses will be used to determine coating robustness in an engine relevant environment.

Jamesa L Stokes

Evaluation of Particle Degradation of a Ytterbium Disilicate Gas Turbine Coating in a Combustion Environment

Ytterbium disilicate (Yb2Si2O7) is a state-of-the-art topcoat material used in environmental barrier coatings (EBCs) to protect SiC-SiC composites from water vapor corrosion in gas turbine engines. However, it’s degradation by thermochemical and thermomechanical particle interactions may limit its use in next generation engine systems. Several static furnace tests have been performed on Yb2Si2O7 to elucidate methods of degradation, although dynamic testing in an engine-relevant environment has not been carried out. Ultimately, testing and evaluation of materials that incorporates all environmental damage modes will allow for an accurate assessment of long-term durability and operating lifetime. This work details the investigation of particle-induced erosion and corrosion of Yb2Si2O7 in NASA Glenn’s Erosion Burner Rig Facility. Coating durability was investigated as a function of test temperature, particle size, and deposition rate. Thermal cycling was also incorporated into testing to determine the interplay of heating/cooling cycles with particle degradation. Overall, these analyses will be used to determine coating robustness in an engine relevant environment.

Jamesa L Stokes

Effects of Adverse Weather on Aerodynamics [Les Effets des Conditions Météorologiques Adverses sur I'Aérodynamique]

The 19 technical papers developed for the AGARD Fluid Dynamics Panel (FDP) Specialists' Meeting on "Effects of Adverse Weather on Aerodynamics" held from 28th April—i May 1991 in Toulouse, France are documented in this Conference Proceedings. In addition, introductory material from the Program Chairman and the results of the Round Table Discussion held after the meeting are also included. The FDP organized this meeting to provide a timely review of the progress being made in advancing the state-of-the-art of predicting, simulating, and measuring the effects of icing, anti-icing fluids, and various forms of precipitation on the aerodynamic characteristics of flight vehicles. Topics included results from both theoretical and experimental programs and material related to procedures and regulations for certification and operation. International participation for the meeting included authors from eight nations and representatives from most of the 16 NATO nations.

Precipitation - meteorology

Entanglement properties of SU(2) gauge theory

Understanding how isolated quantum systems thermalize is central to both fundamental physics and the development of quantum technologies. In this Perspective, we present recent and new results on thermalization in nonabelian gauge theory from exact real-time simulations of two-dimensional lattice models. We discuss tests of the eigenstate thermalization hypothesis, entanglement entropy dynamics, the absence of persistent non-thermal states, spectral signatures, and measures of quantum complexity. Our new results include a two-step thermalization process in localized regions and the role of higher gauge field representations. These findings suggest that thermalization in gauge theories may offer a test case for quantum advantage.

information theory and computation

Nuclear quantum effects in molecular liquids across chemical space

Abstract Nuclear quantum effects (NQEs) influence many physical and chemical phenomena, particularly those involving light atoms or occurring at low temperatures. However, their impact has been carefully quantified in few systems-like water-and is rarely considered more broadly. Here we use path-integral molecular dynamics to systematically investigate NQEs on thermophysical properties of 92 organic liquids at ambient conditions. Depending on chemical constitution, we find substantial impact across thermal expansivity, compressibility, dielectric constant, enthalpy of vaporization, and notably molar volume, which shows consistent, positive quantum-classical differences up to 5%; similar, less pronounced trends manifest as isotope effects from deuteration. Using data-driven analysis, we identify three features-molar mass, classical hydrogen density, and classical thermal expansivity-that accurately predict NQEs and facilitate understanding of how characteristics like branching and heteroatom content influence behavior. This work highlights the broad relevance of NQEs in molecular liquids, while also providing a conceptual and practical framework to anticipate their impact.

Science & Technology - Other Topics

Unique Conductivity Behavior in Water-In-Salt Electrolytes Driven by Ion Clusters

Understanding and predicting ion transport in aqueous electrolytes are crucial for advanced energy storage and biophysics, and many emergent technologies yet remain elusive. Herein, we introduce a unified framework to quantitatively describe and predict electrolyte conductivity that shifts from conventional molar concentration-based metrics to a volume fraction-based approach. Through analyzing a variety of electrolyte solutions via this perspective, we observe a universal conductivity peak at a 37% volume fraction. Small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations reveal that nanometer-scale ion clusters drive this general behavior. Moreover, key geometric features of the ion transport pathwayssuch as pore size, tortuosity, and connectivityfollow a consistent dependence with respect to the volume fraction, reinforcing the argument for the universal conductivity trend. This paradigm shift opens new avenues for designing high-performance electrolytes and provides transformative insights for advancing studies in many fields, wherein molecular aggregates dictate transport properties.

Nguyen, Huong T. D.