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At least 1,153 records · Page 64

Ice, glass, and solid phases in artificial spin systems with quenched disorder

We present a numerical study on a disordered artificial spin-ice system, which interpolates between the long-range ordered square ice and the fully degenerate shakti ice. Starting from the square-ice geometry, disorder is implemented by adding vertical/horizontal magnetic islands to the center of some randomly chosen square plaquettes of the array at different densities. When no island is added, we have ordered square ice. When all square plaquettes have been modified, we obtain shakti ice, which is disordered yet in a topological phase corresponding to the Rys F-model. In between, geometrical frustration due to these additional center spins disrupts the long-range Ising order of square ice, giving rise to a spin-glass regime at low temperatures. The artificial spin system proposed in our work provides an experimental platform to study the interplay between quenched disorder and geometrical frustration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Permafrost on Mars: distribution, formation, and geological role

The morphology of channels, valleys, chaotic and fretted terrains and many smaller features on Mars is consistent with the hypothesis that localized deterioration of thick layers of ice-rich permafrost was a dominant geologic process on the Martian surface. Such ground ice deterioration gave rise to large-scale mass movement, including sliding, slumping and sediment gravity flowage, perhaps also catastropic floods. In contrast to Earth, such mass movement processes on Mars lack effective competition from erosion by surface runoff. Therefore, Martian features due to mass movement grew to reach immense size without being greatly modified by secondary erosional processes. The Viking Mission to Mars in 1976 provided adequate measurements of the relevant physical parameters to constrain models for Martian permafrost.

Nummedal, D.↗

Thermal emission from the dust coma of Comet Bowell and a model for the grains

An analysis of the physical characteristics of Comet Bowell is presented based on 10 and 20 microns emissions observed with the NASA 3 m IR telescope during 1981-82. Numerical models are defined for quantifying the number of dust particles at a given radius and at a given angular distance from the nucleus, the contribution of icy grains to the 20 microns flux and the average albedo, and the dust distribution in the coma. Large, dirty ice grains are judged to be responsible for production of OH at a rate of about 10 to the 29th mol/sec during the spring of 1981. The total surface area of the dirty ice grains is projected to be 10 to the 15th sq cm. The coma in 1982 would therefore have consisted of nonvolatile grains, i.e., old dirty ice grains. Further observations of other, similar comets are needed to identify the composition of the emitted grains and the heliocentric distance at which high water production is initiated.

Hanner, M. S.↗

Sensor And Method For Detecting A Superstrate

Method and apparatus are provided for determining a superstrate on or near a sensor, e.g., for detecting the presence of an ice superstrate on an airplane wing or a road. In one preferred embodiment, multiple measurement cells are disposed along a transmission line. While the present invention is operable with different types of transmission lines, construction details for a presently preferred coplanar waveguide and a microstrip waveguide are disclosed. A computer simulation is provided as part of the invention for predicting results of a simulated superstrate detector system. The measurement cells may be physically partitioned, nonphysically partitioned with software or firmware, or include a combination of different types of partitions. In one embodiment, a plurality of transmission lines are utilized wherein each transmission line includes a plurality of measurement cells. The plurality of transmission lines may be multiplexed with the signal from each transmission line being applied to the same phase detector. In one embodiment, an inverse problem method is applied to determine the superstrate dielectric for a transmission line with multiple measurement cells.

Arndt, G. Dickey↗

Effects of Hydrogen Bonding and Molecular Chain Flexibility of Substituted n-Alkyldimethylsilanes On Impact Ice Adhesion Shear Strength

The effects of hydrogen bonding and molecular flexibility upon ice adhesion shear strength were investigated using aluminum substrates coated with substituted n-alkyldimethylalkoxysilanes. The location of the chemical group substitution was on the opposing end of the linear n-alkyl chain with respect to silicon. Three hydrogen-bonding characteristics were evaluated: 1) non-hydrogen bonding, 2) donor/acceptor, and 3) acceptor. Varying the length of the n-alkyl chain provided an assessment of molecular chain flexibility. Coated and uncoated aluminum surfaces were characterized by receding water contact angle and surface roughness. Ice adhesion shear strength was determined in the Adverse Environment Rotor Test Stand facility from -16 to -8°C that simulated aircraft in-flight icing conditions within the FAR Part 25/29 Appendix C icing envelope. Surface roughness of the coatings was similar allowing for comparison of the test results. An adhesion reduction factor, based on the ice adhesion shear strength data with respect to uncoated aluminum obtained at the same temperature, was calculated to compare the data. The results revealed complex interactions with impacting supercooled water droplets that were interdependent upon ice accretion temperature, surface energy characteristics of water and ice, hydrogen bonding characteristic of the substituent, and length of the n-alkyl chain. To aid in explaining the results, 1) changes in the surface energy component (i.e., non-polar and polar) values that water undergoes during its’ phase change from liquid to solid that arise from the freezing of impacting supercooled water droplets on the surface depended upon the temperature during accretion were taken into account and 2) the physical properties (i.e., water solubility and melting point) of small compounds analogous to the substituted n-alkyldimethylalkoxysilanes used in this study were compared.

Smith, Joseph G.↗

Emission characteristics of snow and ice in the microwave range

Some results are presented of a two year investigation on microwave emissions from snow. Included in the investigation were: theoretical studies; laboratory measurements of electrical properties of snow and similar materials; numerical modelling of hypothetical and real snowpacks; analysis of microwave data obtained on everflights; and quantative measurements of natural and artificial snowpacks made in the field. Results indicate that a fairly simple combination of microwave polarizations and frequencies can ultimately be used to monitor the water equivalent and free-water content as well as the distribution of snow. This understanding may also shed light on the physics of microwave emission from other wet, granular, layered media.

Meier, M. F.↗

Evaluation of the CAM6 Climate Model Using Cloud Observations at McMurdo Station, Antarctica

A comparative analysis between observational data from McMurdo Station, Antarctica and the Community Atmosphere Model version 6 (CAM6) simulation is performed focusing on cloud characteristics and their thermodynamic conditions. Ka-band Zenith Radar (KAZR) and High Spectral Resolution Lidar (HSRL) retrievals are used as the basis of cloud fraction and cloud phase identifications. Radiosondes released at 12-hour increments provide atmospheric profiles for evaluating the simulated thermodynamic conditions. Our findings show that the CAM6 simulation consistently overestimates (underestimates) cloud fraction above (below) 3 km in four seasons of a year. Normalized by total in-cloud samples, ice and mixed phase occurrence frequencies are underestimated and liquid phase frequency is overestimated by the model at cloud fractions above 0.6, while at cloud fractions below 0.6 ice phase frequency is overestimated and liquid-containing phase frequency is underestimated by the model. The cloud fraction biases are closely associated with concurrent biases in relative humidity (RH), i.e., high (low) RH biases above (below) 2 km. Frequencies of correctly simulating ice and liquid-containing phase increase when the absolute biases of RH decrease. Cloud fraction biases also show a positive correlation with RH biases. Water vapor mixing ratio biases are the primary contributor to RH biases, and hence, likely a key factor controlling the cloud biases. Finally, this diagnosis of the evident shortfalls of representations of cloud characteristics in CAM6 simulation at McMurdo Station brings new insight in improving the governing model physics therein.

54 ENVIRONMENTAL SCIENCES↗

Kagome qubit ice

Abstract Topological phases of spin liquids with constrained disorder can host a kinetics of fractionalized excitations. However, spin-liquid phases with distinct kinetic regimes have proven difficult to observe experimentally. Here we present a realization of kagome spin ice in the superconducting qubits of a quantum annealer, and use it to demonstrate a field-induced kinetic crossover between spin-liquid phases. Employing fine control over local magnetic fields, we show evidence of both the Ice-I phase and an unconventional field-induced Ice-II phase. In the latter, a charge-ordered yet spin-disordered topological phase, the kinetics proceeds via pair creation and annihilation of strongly correlated, charge conserving, fractionalized excitations. As these kinetic regimes have resisted characterization in other artificial spin ice realizations, our results demonstrate the utility of quantum-driven kinetics in advancing the study of topological phases of spin liquids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Transport and chemistry of isoprene and its oxidation products in deep convective clouds

Deep convective clouds can transport trace gases from the planetary boundary layer into the upper troposphere where subsequent chemistry may impact aerosol particle formation and growth. In this modelling study, we investigate processes that affect isoprene and its oxidation products injected into the upper troposphere by an isolated deep convective cloud in the Amazon. We run a photochemical box model with coupled cloud microphysics along hundreds of individual air parcel trajectories sampled from a cloud-resolving model simulation of a convective event. The box model simulates gas-phase chemical reactions, gas scavenging by liquid and ice hydrometeors, and turbulent dilution inside a deep convective cloud. The results illustrate the potential importance of gas uptake to anvil ice in regulating the intensity of the isoprene oxidation and associated low volatility organic vapour concentrations in the outflow. Isoprene transport and fate also depends on the abundance of lightning-generated nitrogen oxide radicals (NO x = NO + NO 2 ). If gas uptake on ice is efficient and lightning activity is low, around 30% of the boundary layer isoprene will survive to the cloud outflow after approximately one hour of transport, while all the low volatile oxidation products will be scavenged by the cloud hydrometeors. If lightning NO x is abundant and gas uptake by ice is inefficient, then all isoprene will be oxidised during transport or in the immediate outflow region, while several low volatility isoprene oxidation products will have elevated concentrations in the cloud outflow. Reducing uncertainties associated with the uptake of vapours on ice hydrometeors, especially HO 2 and oxygenated organics, is essential to improve predictions of isoprene and its oxidation products in deep convective outflows and their potential contribution to new particle formation and growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energy Frontier Research Centers: Center for the Computational Design of Functional Layered Materials (CCDM) August 1, 2014 - July 31, 2018; Center for Complex Materials from First Principles (CCM) August 1, 2018 - July 31, 2021 (Final Report)

The mission of the DOE Energy Frontier Research Centers CCDM (2014-2018) and CCM (2018-2021) was to theoretically develop, computationally apply, and experimentally validate electronic structure methods for all materials, with a focus on the complex materials, especially layered and two-dimensional materials, strongly-correlated materials, and liquid water. This was achieved by over 200 published journal articles authored by about 17 senior investigators from physics and chemistry and from theory, computation, and experiment, plus their collaborators. In particular, the Centers confirmed the predictive power of the SCAN (strongly constrained and appropriately normed) density functional, which was constructed to satisfy 17 known exact constraints and several appropriate norms. Without being fitted to real bonded systems, and at a modest computational cost, SCAN correctly predicted covalent, ionic, metallic, hydrogen, and van der Waals bonds in many challenging materials. SCAN gave an improved description of defects in semiconductors, surface properties of metals, seven phases of ice, liquid water, liquid and supercooled silicon, subtle structural distortions in ferroelectrics, formation energies and structural predictions for solids, and critical pressures for structural phase transitions. Perhaps most remarkably, SCAN correctly described some strongly-correlated materials that were previously believed to be beyond the reach of density-functional approximations. SCAN is the only density functional that correctly predicts the band gap closing under chemical doping of the cuprate high-temperature superconducting materials. SCAN also predicts a landscape of competing stripe and magnetic phases in the cuprates. For some materials with some codes, SCAN has convergence problems that are greatly reduced by the CCM-developed r 2 SCAN, without loss of accuracy or rigor. SCAN and r 2 SCAN still make some self-interaction error, which is greatly reduced by the CCDM/ CCM-developed local orbital scaling correction (LOSC). These Centers further proved that the fundamental energy gaps of a solid from an orbital energy difference and from total energy differences are the same for a large class of generalized Kohn-Sham (GKS) functionals, including SCAN and standard hybrid functionals, and that symmetry breaking arises when a dynamic density fluctuation drops to zero frequency. The Centers identified new mechanisms for catalysis in layered materials with ions intercalated between the layers, investigated charge density waves both in model systems and in real layered materials, studied changes of band gap with the number of layers, and explored topological ultrathin films, bent nanoribbons, and defects.

08 HYDROGEN↗

High-resolution SOFIA/EXES Spectroscopy of SO2 Gas in the Massive Young Stellar Object MonR2 IRS3: Implications for the Sulfur Budget

Sulfur has been observed to be severely depleted in dense clouds leading to uncertainty in the molecules that contain it and the chemistry behind their evolution. Here, we aim to shed light on the sulfur chemistry in young stellar objects (YSOs) by using high-resolution infrared spectroscopy of absorption by the ν3 rovibrational band of SO2 obtained with the Echelon-Cross-Echelle Spectrograph on the Stratospheric Observatory for Infrared Astronomy. Using local thermodynamic equilibrium models we derive physical parameters for the SO2 gas in the massive YSO MonR2 IRS3. This yields a SO2/H abundance lower limit of 5.6 ± 0.5 × 10(exp -7), or >4% of the cosmic sulfur budget, and an intrinsic line width (Doppler parameter) of b < 3.20 km s(exp -1). The small line widths and high temperature (Tex = 234 ± 15 K) locate the gas in a relatively quiescent region near the YSO, presumably in the hot core where ices have evaporated. This sublimation unlocks a volatile sulfur reservoir (e.g., sulfur allotropes as detected abundantly in comet 67P/Churyumov–Gerasimenko), which is followed by SO2 formation by warm, dense gas-phase chemistry. The narrowness of the lines makes formation of SO2 from sulfur sputtered off grains in shocks less likely toward MonR2 IRS3.

Infrared ISM↗

Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, and Psychosocial Adaptions within a Team

The Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, Communication, and Psychosocial Adaptation within a Team (the Team Risk) is primarily performance-focused, with a secondary emphasis on behavioral health outcomes resulting from team performance and interpersonal interactions. Monitoring tools, measures, and countermeasures are aimed at enhancing team processes and team composition configurations to optimize team performance and functioning. Long-duration exploration missions (LDEMs) will include major challenges that could affect team performance, including social isolation, physical confinement, a small and diverse crew, communication delays between crew and ground, limited or no crew rotation or evacuation options, limited or no resupply, and a high-consequence environment. Each of these conditions will affect the crew’s coordination, cooperation, psychological well-being, and performance. Although the International Space Station (ISS) remains important for studies that require spaceflight testing and validation, the current conditions on the ISS do not adequately mimic the exploration environment that is required for National Aeronautics and Space Administration (NASA) teams research, and thus access to terrestrial or ground-based analogs of LDEM conditions is paramount. The emphasis on analogs for research is reflected in this updated evidence review of the Team Risk, and includes data from studies conducted at isolated, confined, extreme (ICE) environments (e.g., Antarctic stations), and from several mission simulation analogs such as the Human Exploration Research Analog (HERA) (HERA Experiment Information Package, 2014), also known as isolated, confined, controlled (ICC) environments. These studies have characterized many team factors regarding LDEMs, and the Team Risk has now matured from risk characterization to focusing more on countermeasure development. Because spaceflight evidence for team-level research is lacking, no reliable data is available to quantify the impact of team-level variables on individual and team-level outcomes during spaceflight missions. Until recently, no systematic attempt had been undertaken to measure the performance effects of team cohesion, team composition, team training, or team-related psychosocial adaptation during spaceflight. The Team Risk is a relatively young research area for NASA, with substantial growth only since the 2000s, and with limited access to spaceflight performance data. As a result, spaceflight evidence is lacking to identify specifically what team composition, level of training, amount of cohesion, or quality of psychosocial adaptation is necessary to reduce the risk of performance errors in space. However, astronaut journals and interviews and reports from spaceflight subject matter experts (SMEs) provide testimonies that team performance during spaceflight is important for mission success and to maintain crew health. Team spaceflight data is now being collected as part of the Spaceflight Standard Measures task (Clement, 2021)—a set of core measurements related to many human spaceflight risks that are collected from astronauts before, during, and after long-duration missions. The team-related standard measures focus on team cohesion, team performance, group living, team climate, and team processes. Collection of standard measures data is ongoing and published data is not yet available. Finally, although spaceflight evidence is lacking, evidence gleaned from ground studies and spaceflight analog studies will help close the gaps outlined in the Team Risk. Ground-based studies provide quantitative evidence for team functioning in ICE environments. Academic research on teams has produced dozens of meta-analyses that can be used to understand the general relationships among team inputs (e.g., team member characteristics and skills, job context), team processes, and emergent states (e.g., coordination, communication, cooperation, cohesion, trust, shared cognition), and team outcomes (e.g., effectiveness, errors, adaptation). Teams are complex, incorporating individual characteristics of team members, but also existing at a level that is greater than the sum of its parts. Therefore, the Team Risk must be integrated with other individual-focused NASA Human Research Program (HRP) risks, including Behavioral Medicine (BMed), Sleep, and Human-Systems Integration Architecture (HSIA), and emerging research indicates more integration may needed between the Team Risk and the physiologically oriented risks. Much of this integration occurs through the Human Systems Risk Board (HSRB). A lack of team functioning may be a stressor in some circumstances, but the team often acts as a countermeasure. For example, support for team leaders and teammates can facilitate individual functioning and encourage psychological and physically healthy behaviors and attitudes. However, more research is needed regarding teams during LDEMs and the remaining gaps in the research are described in the current report.

Lauren Blackwell Landon↗

Visual feedback and guided balance training in an immersive virtual reality environment for lower extremity rehabilitation

Balance training is essential for physical rehabilitation procedures, as it can improve functional mobility and enhance cognitive coordination. However, conventional balance training methods may have limitations in terms of motivation, real-time objective feedback, and personalization, which a virtual reality (VR) setup may provide a better alternative. In this work, we present an immersive VR training environment for lower extremity balance rehabilitation with real-time guidance and feedback. The VR training environment immerses the user in a 3D ice rink model where a virtual coach (agent) leads them through a series of balance poses, and the user controls a trainee avatar with their own movements. Here we developed two coaching styles: positive-reinforcement and autonomous-supportive, and two viewpoints of the trainee avatar: first-person and third-person. The proposed environment was evaluated in a user study with healthy, non-clinical participants (n = 16, 24.4 ± 5.7 years old, 9 females). Our results show that participants showed stronger performance in the positive-reinforcement style compared to the autonomous-supportive style. Additionally, in the third-person viewpoint, the participants exhibited more stability in the positive-reinforcement style compared to the autonomous-supportive style. For viewpoint, participants exhibited stronger performance in the first-person viewpoint compared to third-person in the autonomous-supportive style, while they were comparable in the positive-reinforcement style. We observed no significant effects on the foot height and number of mistakes. Furthermore, we report the analysis of user performance with balance training poses and subjective measures based on questionnaires to assess the user experience, usability, and task load. The proposed VR balance training could offer an interactive, adaptive, and engaging environment and open new potential research directions for lower extremity rehabilitation.

97 MATHEMATICS AND COMPUTING↗

A Machine Learning Framework for Predicting Microphysical Properties of Ice Crystals From Cloud Particle Imagery

The microphysical properties of ice crystals are important because they significantly alter the radiative properties and spatiotemporal distributions of clouds, which in turn strongly affect Earth's climate. However, it is challenging to measure key properties of ice crystals, such as mass or morphological features. Here, we present a proof-of-concept framework for predicting three-dimensional (3D) microphysical properties of ice crystals from in situ two-dimensional (2D) imagery. First, we computationally generated synthetic ice crystals using 3D modeling software along with geometric parameters estimated from the 2021 Ice Cryo-Encapsulation Balloon (ICEBall) field campaign. Then, we used synthetic crystals to train machine learning (ML) models to predict effective density ($ρ_e$), effective surface area ($A_e$), and number of bullets ($N_b$) from synthetic rosette imagery. On unseen synthetic images, our ML models accurately predicted ice crystal properties. ResNet-18 performed best, achieving $R^2$ values of 0.99 and 0.98 for $ρ_e$ and $A_e$, respectively, and MAE of 0.10 for mathematical equation in single view tasks. Stereo view ResNet-18 further reduced RMSE by 40% for $ρ_e$ and $A_e$ and reduced MAE by 0.08 for $N_b$. This work provides a novel ML-driven framework for estimating ice microphysical properties from in situ imagery, which will allow for downstream constraints on microphysical parameterizations, such as the mass-size relationship.

Ko, J. [Columbia Univ., New York, NY (United State↗

Arctic soil patterns analogous to fluid instabilities

Significance Slow-moving arctic soils form patterns resembling those found in common fluids, such as paint and cake icing drips. Inspired by fluid instabilities, we develop a conceptual model for soil patterns and use mathematical analysis to predict their wavelength. In particular, we propose that soil patterns arise due to competition between gravity and cohesion or the “stickiness” of soil grains. We compare our theoretical predictions with a dataset of soil features from Norway, finding that soil patterns are controlled by fluid-like properties as well as climate. Our work provides a physical explanation for a common pattern on both Earth and Mars, with implications for our understanding of landscapes and complex materials composed of both granular and fluid components.

54 ENVIRONMENTAL SCIENCES↗

Species mix & distribution function dependence of energetic-ion driven magnetospheric instabilities on DIII-D (Final Report)

Energetic ions drive a rich variety of instabilities in the complex multi-species plasma of Earth’s magnetosphere. This experiment exploited the highly flexible, high power particle beam injection capability and sophisticated diagnostic suite of the DIII-D tokamak to advance understanding of two particular instabilities of significant interest to the magnetospheric research community that have closely-related counterparts in beam-heated tokamak plasmas: electromagnetic ion cyclotron waves (EMIC) [1], observed at frequencies somewhat below the ion cyclotron frequencies of bulk ion species, and equatorial noise [2], observed at energetic-ion cyclotron harmonics. In the magnetic fusion energy domain, such waves are called ICE (Ion Cyclotron Emission). Recent substantial advances in diagnostic capability in the ion cyclotron range of frequencies in DIII-D, including measurement of wave polarization, spa)al structure and amplitude created an exciting opportunity to challenge and drive advances in theoretical understanding of these phenomena.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Atmospheric Modeling and Denoising for Millimeter-Wave Line Intensity Mapping

Line-intensity mapping (LIM) offers a promising approach to mapping large-scale cosmic structure, and the greatest obstacle for ground-based observations at millimeter wavelengths is foreground contamination from atmospheric emission. In this work, we present a simulation and denoising framework designed to isolate and subtract atmospheric fluctuations from LIM data, modeled after the instrument parameters of the South Pole Telescope Summertime Line Intensity Mapper (SPT-SLIM). We generate mock observations spanning 125-175 GHz containing cosmic signals, precipitable water vapor screens, ice crystal fluctuations, and photon noise. We then implement a spatial-spectral atmospheric removal pipeline combining per-pixel linear template regression with a two-dimensional Fourier-domain filter. The framework is evaluated under simulated conditions in the South Pole and the Atacama Desert across three key metrics: cosmic signal preservation, foreground subtraction efficiency, and instrument noise injection. Our pipeline achieves atmospheric suppression at large spatial scales, and these results establish a physically grounded foundation for atmosphere removal in ground-based LIM data collection.

Saye, Laney [UC, Berkeley (main)] (ORCID:000900078↗

A New Model for Water Vapor/Ice Abundance in a Protoplanetary Nebula

Water is a unique substance in the protoplanetary nebula since both solid and gaseous phases coexist in large quantities. Quantitative estimates of their relative abundances are important parameters regarding the physical state of the nebula and planet formation processes. This new model is based on computing the chemical evolution of water molecules until its partial pressure is sufficient to pierce the vapor pressure curve for water. The point at which this occurs relative to its steady state values determines final gas/ice ratios. The wide range of temperatures and densities in typical protoplanetary disks result in a range of gadice ratios. It is found that although ice dominates the mid and far nebula, water vapor is predominant in the centerplane region of the near nebula and above the disk photosphere. An interesting near nebula effect is the appearance of a cloud of water ice at the temperature inversion elevation surrounded by vapor above and below. This work is partially supported by the NASA Astrobiology Institute.

Davis, Sanford S.↗