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83 records · Page 5

Excitations across the Equilibrium and Photoinduced “Hidden” States of Magnetoresistive Manganites

“Hidden” phases, generated using ultrafast laser pulses (few hundred femtoseconds), with distinct properties than at the thermodynamic equilibrium, are appealing for technologies, as they can be long-lived, with a lifetime of hours or weeks, and reversible with temperature sweeping or extra pulses. In this regard, La 2/3 ⁢Ca 1/3⁢ MnO 3 (LCMO) stands out due to its tunability through epitaxial strain, which can drive the bulk ferromagnetic metal into an antiferromagnetic insulator (AFI), and its susceptibility to photoinduced transitions. Indeed, AFI LCMO displays a long-lived photoinduced transition into a putative hidden phase whose exact nature and excitations are still largely unknown. Here, we combine ultrafast photoexcitation in the near infrared with in situ transport, x-ray absorption, and resonant inelastic x-ray scattering (RIXS) to investigate the excitations (polarons, phonons, and orbital) of the photoexcited phase of LCMO and contrast them with the thermodynamic phases achieved through strain and temperature. In the thermodynamic regime, we establish the correlation between polarons and transport placing them in the “strong coupling” regime of the Holstein model. Upon photoexcitation of LCMO-AFI, we uncover a long-lived phase characterized by the softening of the polaron excitations, the partial suppression of the Jahn-Teller distortion, and nearly unchanged phonons, showing the emergence of a photoexcited state absent in the equilibrium phase diagram. Finally, by varying temperature, epitaxial strain, and photoexcitation fluence, we construct a polaron phase diagram and identify the key spectroscopic signatures of each phase. Our laser-RIXS approach establishes a versatile platform for exploring photoinduced hidden phases in quantum materials in nonstroboscopic conditions.

36 MATERIALS SCIENCE↗

Investigating the Origin of Chlorohydrocarbons Detected by the Sample Analysis at Mars (SAM) Instrument at Rocknest

The search for organic compounds on Mars, including molecules of either abiotic or biological origin is one of the key goals of the Mars Science Laboratory (MSL) mission. Previously the Viking and Phoenix Lander missions searched for organic compounds, but did not find any definitive evidence of martian organic material in the soils. The Viking pyrolysis gas chromatography mass spectrometry (GCMS) instruments did not detect any organic compounds of martian or exogenous origin above a level of a few parts-per-billion (ppb) in the near surface regolith at either landing site [1]. Viking did detect chloromethane and dichloromethane at pmol levels (up to 40 ppb) after heating the soil samples up to 500 C (Table 1), although it was originally argued that the chlorohydrocarbons were derived from cleaning solvents used on the instrument hardware, and not from the soil samples themselves [1]. More recently, it was suggested that the chlorohydrocarbons detected by Viking may have been formed by oxidation of indigenous organic matter during pyrolysis of the soil in the presence of perchlorates [2]. Although it is unknown if the Viking soils contained perchlorates, Phoenix did reveal relatively high concentrations (~0.6 wt%) of perchlorate salt in the icy regolith [3], therefore, it is possible that the chlorohydrocarbons detected by Viking were produced, at least partially, during the experiments [2,4]. The Sample Analysis at Mars (SAM) instrument suite on MSL analyzed the organic composition of the soil at Rocknest in Gale Crater using a combination of pyrolysis evolved gas analysis (EGA) and GCMS. One empty cup procedural blank followed by multiple EGA-GCMS analyses of the Rocknest soil were carried out. Here we will discuss the results from these SAM measurements at Rocknest and the steps taken to determine the source of the chlorohydrocarbons.

Glavin, D.↗

An Empirical State Error Covariance Matrix Orbit Determination Example

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance is suspect. In its most straight forward form, the technique only requires supplemental calculations to be added to existing batch estimation algorithms. In the current problem being studied a truth model making use of gravity with spherical, J2 and J4 terms plus a standard exponential type atmosphere with simple diurnal and random walk components is used. The ability of the empirical state error covariance matrix to account for errors is investigated under four scenarios during orbit estimation. These scenarios are: exact modeling under known measurement errors, exact modeling under corrupted measurement errors, inexact modeling under known measurement errors, and inexact modeling under corrupted measurement errors. For this problem a simple analog of a distributed space surveillance network is used. The sensors in this network make only range measurements and with simple normally distributed measurement errors. The sensors are assumed to have full horizon to horizon viewing at any azimuth. For definiteness, an orbit at the approximate altitude and inclination of the International Space Station is used for the study. The comparison analyses of the data involve only total vectors. No investigation of specific orbital elements is undertaken. The total vector analyses will look at the chisquare values of the error in the difference between the estimated state and the true modeled state using both the empirical and theoretical error covariance matrices for each of scenario.

Frisbee, Joseph H., Jr.↗

Small Particle Glovebox Experiments - Preliminary Results

A substantial portion of the asteroid samples returned by the HAYABUSA2 and OSIRIS-REx missions will consist of small (submm) components (due to the collection of those particles on the asteroid surface and due to the fragmenting of larger, friable material post-collection). In order to minimize the alteration/oxidation of asteroid regolith, the bulk collections will be stored and curated in nitrogen purged gloveboxes. The processing of small particles in an N2 glovebox will present challenges that are different from those experienced during lunar and meteorite sample processing. Particles in this size range are susceptible to unpredictable electrostatic charging that can result in sample loss during processing operations. Methods for the handling of sub-mm particles have been well developed for environments with ambient atmospheric conditions and relative humidity (RH) ranges between 40-70%. In such conditions, a number of factors can be successfully employed to minimize the effects of triboelectric charging, including the use of Po-210 sources that neutralize excess charge and the utilization of conductive manipulation tools and sample substrates. However, relative humidity levels above 40% also contribute significantly to dissipation of triboelectric effects. We had not previously investigated our charge mitigation methods in a completely dry, nitrogen-purged environment, or whether they would be sufficient in enabling the successful processing of sub-mm samples. Current glovebox configurations in use in our lunar and meteorite curation laboratories are optimized for the processing of macroscopic samples and tools; these glovebox designs are likely unsuitable for the processing of collections for which the bulk collection is comprised of sub-mm components. Small particle sample preparation requires the use of an optical magnification instrument – typically a stereo binocular microscope with at least 20x magnification. Current glovebox designs are not optimized for the utilization or integration of stereo microscopes; while many current cabinets include microscope viewports that enable the use of small, externally mounted stereo microscopes, the focusing methods (usually involving the use of a lab jack) lack the fidelity and precision required for small particle manipulation and imaging. Working distances of higher (>50x magnification) objective lenses may preclude the external use of a stereo microscope through a viewport; in order to successfully manipulate and image very small (< 20m) particles, stereo and digital microscope systems that are integrated within the glovebox should be investigated. Finally, ergonomic considerations for small particle work within a glovebox must be considered to minimize risk of injury to sample processors. In order to investigate some of the unknown parameters relating to small particle processing within an N2 glovebox, we conducted preliminary, qualitative experiments utilizing a small lunar cabinet that was originally used for film development.

C. J. Snead↗

An Empirical State Error Covariance Matrix for Batch State Estimation

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty. Also, in its most straight forward form, the technique only requires supplemental calculations to be added to existing batch algorithms. The generation of this direct, empirical form of the state error covariance matrix is independent of the dimensionality of the observations. Mixed degrees of freedom for an observation set are allowed. As is the case with any simple, empirical sample variance problems, the presented approach offers an opportunity (at least in the case of weighted least squares) to investigate confidence interval estimates for the error covariance matrix elements. The diagonal or variance terms of the error covariance matrix have a particularly simple form to associate with either a multiple degree of freedom chi-square distribution (more approximate) or with a gamma distribution (less approximate). The off diagonal or covariance terms of the matrix are less clear in their statistical behavior. However, the off diagonal covariance matrix elements still lend themselves to standard confidence interval error analysis. The distributional forms associated with the off diagonal terms are more varied and, perhaps, more approximate than those associated with the diagonal terms. Using a simple weighted least squares sample problem, results obtained through use of the proposed technique are presented. The example consists of a simple, two observer, triangulation problem with range only measurements. Variations of this problem reflect an ideal case (perfect knowledge of the range errors) and a mismodeled case (incorrect knowledge of the range errors).

Frisbee, Joseph H., Jr.↗

CRCNS22 Learning Rules in the Hippocampus and their Mapping to Neuromorphic Systems (Final Technical Report)

Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.

59 BASIC BIOLOGICAL SCIENCES↗

Root size and soil physicochemical properties drive microscale spatial patterns of Fe and As retention in the rice rhizosphere

Background and Aims: Radial oxygen loss from rice roots in flooded soils oxidizes and precipitates dissolved Fe(II), Mn(II), and As(III) into mixed Fe(III), Mn(III/IV), and As(V) as root plaque and in the rhizosphere soil. It is unknown how different soils and root sizes impact the spatial extent of Fe and As retention outside the root. Methods: We imaged cross-sections of 90 roots from 6 different soils using synchrotron μXRF imaging followed by k-means clustering and elliptical averaging to distinguish bulk soil, rhizosphere, plaque, and roots based on As and Fe patterns. Results: We found preferential As retention in the plaque and rhizospheres of most roots except small (< 0.45 mm) roots in silty soils with low P or high As. In contrast, clayey soils had similar As-Fe correlations across plaque, rhizosphere, and bulk soil. Large (> 0.45 mm) roots often had no oxidized rhizosphere region. We obtained an extensive dataset of 256 As and 155 Mn synchrotron μXANES measurements, which revealed that rhizosphere and plaque As was mainly inorganic As(V) and As(III), and Mn oxidation state varied between soils but not between belowground locations. Conclusion: Small roots in coarse-textured soils were less likely to have As retention in the plaque or rhizosphere compared to large roots and fine-textured soils. Furthermore, the unique and extensive data in this study provides new insight into soil and root size impacts on As retention in the rhizosphere. It is essential to investigate a representative number of samples to draw conclusions from XRF imaging.

36 MATERIALS SCIENCE↗

Effect of bisphosphonate treatment on the oim mouse middle ear ossicles' structure, composition and hearing

Hearing loss is common in people with osteogenesis imperfecta (OI or brittle bone disease). Bisphosphonates are commonly used to treat long bone fragility in children with OI. However, its impact on the bone quality of the middle ear ossicles and hearing remains unknown. This study determines whether bisphosphonates treatment itself may contribute to hearing loss in OI by evaluating its effects in the oim/oim mouse model of severe OI having normal auditory function. Specifically, this study reports the effects of alendronate (ALN), a nitrogen-containing bisphosphonate, on ossicle morphology, porosity, and elemental composition in 14-week-old oim/oim mice treated weekly, starting at 2 weeks of age. The ossicles were examined using synchrotron microtomography and X-ray fluorescence microscopy (XFM). Hearing was assessed longitudinally until 26 weeks of age by determining auditory brainstem response (ABR) thresholds in another group of mice also treated weekly starting at 2 weeks of age. ALN treatment further reduces in size the already small oim/oim ossicles, specifically in female mice. Porosity, bone composition, and hearing function, however, were generally not affected by the ALN treatment. Furthermore, ALN does not prevent joint fusions, excessive bone formations, or enlarged joint spaces in WT or oim/oim experimental groups. One ALN-treated oim/oim mouse with a bone formation in the interior of the footplate, and one ALN-treated WT mouse with a fixed footplate had frequency-specific hearing loss. Since footplate abnormalities are not observed in PBS-treated mice in this study, it remains unclear whether ALN fails to prevent these changes or contributes to their development. Future studies should investigate the mechanisms of ossicular abnormalities and bisphosphonates modulatory role in the ossicles.

60 APPLIED LIFE SCIENCES↗

Mineralized sclerites in the gorgonian coral Leptogorgia chilensis as a natural jamming system

The soft corals (Cnidaria, Octocorallia), a diverse group of colonial marine invertebrates, can reversibly tune their body stiffness in response to external stimuli. This capability is attributed to their dynamic skeletal systems, which consist of thousands of mineralized skeletal elements, called sclerites, embedded within a gel-like matrix that swells/deswells and unjams/jams the sclerites, thus modulating skeletal stiffness. While sclerite morphology is widely used for species identification, its role in the mechanical performance of a soft coral’s skeletal system is largely unknown. Here, we investigated structure-jamming relationships in sclerite-based skeletal architectures using the red gorgonian octocoral Leptogorgia chilensis as a model system. The sclerites of L. chilensis exhibit a shaft-like geometry with two axial branches and two sets of triradiate side branches, which are aligned with the crystallographic symmetry of the constituent magnesium-containing calcite. By combining multiscale three-dimensional (3D) structural characterization, parametric geometrical modeling, 3D printing, mechanical testing, and discrete element simulations, we demonstrate how sclerite geometry achieves a balanced jamming performance in terms of stiffness, weight, strength, and fracture resistance in comparison to alternative geometries parametrically modified from the native sclerites (e.g., changes in the length and number of side branches). Here, we also found that these performance metrics are achieved through the effective interlocking among side and axial branches, which is further enhanced by the fractal-like microscopic spikes on the branch tips. The findings in this natural jamming system offer insights for designing synthetic mechanotunable material architectures for a wide range of applications, from soft robotics to mechanical dampeners.

36 MATERIALS SCIENCE↗

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 2001]. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds [NRC, 2001]." The aerosol effect on clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path [Twomey, 1977] and the "semi-direct" effect on cloud coverage [e.g., Ackerman et al ., 2001]." Enhanced aerosol concentrations can also suppress warm rain processes by producing a narrow droplet spectrum that inhibits collision and coalescence processes [e.g., Squires and Twomey, 1961; Warner and Twomey, 1967; Warner, 1968; Rosenfeld, 19991. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect [Albrecht, 1989], is even more complex, especially for mixed-phase convective clouds. Table 1 summarizes the key observational studies identifying the microphysical properties, cloud characteristics, thermodynamics and dynamics associated with cloud systems from high-aerosol continental environments. For example, atmospheric aerosol concentrations can influence cloud droplet size distributions, warm-rain process, cold-rain process, cloud-top height, the depth of the mixed phase region, and occurrence of lightning. In addition, high aerosol concentrations in urban environments could affect precipitation variability by providing an enhanced source of cloud condensation nuclei (CCN). Hypotheses have been developed to explain the effect of urban regions on convection and precipitation [van den Heever and Cotton, 2007 and Shepherd, 2005]. Please see Tao et al. (2007) for more detailed description on aerosol impact on precipitation. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.

Tao, Wei-Kuo↗

The Galileo Probe: How it Has Changed Our Understanding of Jupiter

The Galileo Mission to Jupiter, which arrived in December of 1995, provided the first study by an orbiter, and the first in-situ sampling via an entry probe, of an outer planet atmosphere. The rationale for an entry probe is that, even from an orbiter, remote sensing of the jovian atmosphere could not adequately retrieve the information desired. This paper provides a current summary of the most significant aspects of the data returned from the Galileo entry probe. As a result of the probe measurements, there has been a reassessment of our understanding of outer planet formation and evolution of the solar system. The primary scientific objective of the Galileo probe was to determine the composition of the jovian atmosphere, which from remote sensing remained either very uncertain, or completely unknown, with respect to several key elements. The probe found that the global He mass fraction is. significantly above the value reported from the Voyager Jupiter flybys but is slightly below the protosolar value, implying that there has been some settling of He to the deep jovian interior. The probe He measurements have also led to a reevaluation of the Voyager He mass fraction for Saturn, which is now determined to be much closer to that of Jupiter. The elements C, N, S, Ar, Kr, Xe were all found to have global abundances approximately 3 times their respective solar abundances. This result has raised a number of fundamental issues with regard to properties of planetesimals and the solar nebula at the time of giant planet formation. Ne, on the other hand, was found to be highly depleted, probably as the result of it being carried along with helium as helium settles towards the deep interior. The global abundance of O was not obtained by the probe because of the influence of local processes at the probe entry site (PES), processes which depleted condensible species, in this case H2O, well below condensation levels. Other condensible species, namely NH3 and H2S, were similarly affected but attained their deep equilibrium mixing ratios before the maximum depth sampled by the probe. Processes that might be capable of producing such effects on the condensibles are still under investigation. Measured isotopic ratios of noble gases and other heavy elements are solar, and (D + (Sup 3)He)/H is the same to within measurement uncertainties as in the local interstellar medium. No thick clouds were detected, and in particular no significant water cloud, but the PES location clearly affected the probe measurements of clouds. In fact, the probe data must be understood in the context of the location of the PES, which was within what is termed a 5 micron hot spot, a local clearing in the clouds that is bright near the 5 microns spectral region. The thermal structure at the PES was determined from approximately 1000 km above the 1 bar pressure level (10(exp -9 bars)) to 132 km 1 bar (22bars). The probe showed the atmosphere to have a generally sub-adiabatic temperature gradient (static stability) of = 0.1 K/km to as deep as the probe made measurements. In the upper atmosphere the probe derived a maximum positive vertical temperature gradient of approximately 5 K/km, and maximum temperature of = 900 K. The energy sources producing the warm upper atmosphere have yet to be completely identified. At first glance, Doppler tracking of the probe indicates that the long observed cloud level zonal winds extend to levels at least as deep as the probe made measurements. Zonal wind increases from = 80 m/s at pressures less than a bar to about 180 m/s near 5 bars, and remains approximately constant with depth thereafter. However, there is a question as to whether the winds measured from probe tracking are representative of the general wind field, or are considerably influenced by localized winds associated with the PES.

Young, Richard E.↗