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At least 271 records · Page 15

Confinement Controls the Bend Instability of Three-Dimensional Active Liquid Crystals

Spontaneous growth of long-wavelength deformations is a defining feature of active liquid crystals. We investigate the effect of confinement on the instability of 3D active liquid crystals in the isotropic phase composed of extensile microtubule bundles and kinesin molecular motors. When shear aligned, such fluids exhibit finite-wavelength self-amplifying bend deformations. By systematically changing the channel size we elucidate how the instability wavelength and its growth rate depend on the channel dimensions. Experimental findings are qualitatively consistent with a minimal hydrodynamic model, where the fastest growing deformation is set by a balance of active driving and elastic relaxation. Furthermore, our results demonstrate that confinement determines the structure and dynamics of active fluids on all experimentally accessible length scales.

59 BASIC BIOLOGICAL SCIENCES↗

Nonlinear Shear Rheology of Entangled Polymer Rings

Steady-state shear viscosity η($\bar{γ}$) of unconcatenated ring polymer melts as a function of the shear rate $\bar{γ}$ is studied by a combination of experiments, simulations, and theory. Experiments using polystyrenes with Z ≈ 5 and Z ≈ 11 entanglements indicate weaker shear thinning for rings compared to linear polymers exhibiting power law scaling of shear viscosity η ~ $\bar{γ}$ –0.56 ± 0.02 , independent of chain length, for Weissenberg numbers up to about 10 2 . Nonequilibrium molecular dynamics simulations using the bead-spring model reveal a similar behavior with η ~ $\bar{γ}$ -0.57 ± 0.08 for 4 ≤ Z ≤ 57. Viscosity decreases with chain length for high $\bar{γ}$. In our experiments, we see the onset of this regime, and in simulations, which we extended to Wi ~ 10 4 , the nonuniversality is fully developed. In addition to a naive scaling theory yielding for the universal regime η ~ $\bar{γ}$ –0.57 , we developed a novel shear slit model explaining many details of observed conformations and dynamics as well as the chain length-dependent behavior of viscosity at large $\bar{γ}$. The signature feature of the model is the presence of two distinct length scales: the size of tension blobs and much larger thickness of a shear slit in which rings are self-consistently confined in the velocity gradient direction and which is dictated by the size of a chain section with relaxation time 1/$\bar{γ}$. These two length scales control the two normal stress differences. In this model, the chain length-dependent onset of nonuniversal behavior is set by tension blobs becoming as small as about one Kuhn segment. This model explains the approximate applicability of the Cox–Merz rule for ring polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experiments in encoding multilevel images as quadtrees

Image storage requirements for several encoding methods are investigated and the use of quadtrees with multigray level or multicolor images are explored. The results of encoding a variety of images having up to 256 gray levels using three schemes (full raster, runlength and quadtree) are presented. Although there is considerable literature on the use of quadtrees to store and manipulate binary images, their application to multilevel images is relatively undeveloped. The potential advantage of quadtree encoding is that an entire area with a uniform gray level may be encoded as a unit. A pointerless quadtree encoding scheme is described. Data are presented on the size of the quadtree required to encode selected images and on the relative storage requirements of the three encoding schemes. A segmentation scheme based on the statistical variation of gray levels within a quadtree quadrant is described. This parametric scheme may be used to control the storage required by an encoded image and to preprocess a scene for feature identification. Several sets of black and white and pseudocolor images obtained by varying the segmentation parameter are shown.

Lansing, Donald L.↗

Virtual Machine Language

Virtual Machine Language (VML) is a mission-independent, reusable software system for programming for spacecraft operations. Features of VML include a rich set of data types, named functions, parameters, IF and WHILE control structures, polymorphism, and on-the-fly creation of spacecraft commands from calculated values. Spacecraft functions can be abstracted into named blocks that reside in files aboard the spacecraft. These named blocks accept parameters and execute in a repeatable fashion. The sizes of uplink products are minimized by the ability to call blocks that implement most of the command steps. This block approach also enables some autonomous operations aboard the spacecraft, such as aerobraking, telemetry conditional monitoring, and anomaly response, without developing autonomous flight software. Operators on the ground write blocks and command sequences in a concise, high-level, human-readable programming language (also called VML ). A compiler translates the human-readable blocks and command sequences into binary files (the operations products). The flight portion of VML interprets the uplinked binary files. The ground subsystem of VML also includes an interactive sequence- execution tool hosted on workstations, which runs sequences at several thousand times real-time speed, affords debugging, and generates reports. This tool enables iterative development of blocks and sequences within times of the order of seconds.

Grasso, Christopher↗

The ZBOT-NC Experiment - Effects of Non-Condensable Gases on Propellant Tank Pressurization and Pressure Control

Introduction Integral to all phases of NASA’s projected planetary expeditions is affordable and reliable cryogenic fluid storage for use in propellant or life support systems. It is greatly advantageous to develop innovative vent-less pressure control designs based on cooling/mixing of the bulk tank fluid to allow storage of the cryogenic fluid with zero or reduced boil-off. The presence of noncondensable gases, can interfere with the condensation at the interface impacting tank pressure control during subcooled jet mixing especially in microgravity. The Zero-Boil-Off Tank (ZBOT) Experiments are a series of small-scale experiments aboard the International Space Station (ISS) that use a transparent volatile simulant fluid in a transparent sealed tank to delineate various fundamental fluid flow, heat and mass transport, and phase change phenomena associated with storage tank pressurization and pressure control in microgravity. The ZBOT-1 experiment was performed on the ISS 2017-2018 timeframe and collected data to validate a state-of-the-art CFD model for tank pressurization and pressure control for a pure system. The ZBOT-NC Experiment is the second experiment in the series to be performed on the International Space Station (ISS) in 2025. Its goal is to investigate the effects of noncondensable gases on interfacial evaporation and condensation during self -pressurization and jet-mixing pressure control in microgravity for a two-component system. Materials & Methods In this work, we will describe the detailed features of the ZBOT-NC experimental hardware and Diagnostics that includes nonintrusive Quantum Dot Thermometry (QDT) for whole field temperature measurement. All microgravity pressurization and pressure control tests will be performed for both the pure and the two-components systems with Xenon and Neon as the two noncondensable gases spanning small and large molecular weights and sizes. The two-phase CFD model that is developed as part of the project will be also presented and discussed. Results Ground-based pressurization and jet mixing experiments and CFD simulation results are compared to each other to validate both the fidelity of the CFD model predictions and the accuracy of the QDT measurement. Model simulations for noncondensable gas effects will also be compared against large Cryogenic LH2-GHe experiments to indicate the noncondensable gas effects on tank pressure control during jet mixing in 1G. Finally, CFD results will be presented to predict the effects of the noncondensable gas during subcooled jet mixing during the ZBOT-NC in advance of the microgravity experiment in 2015.

Evaporation Condensation↗

The Zero-Boil-Off Tank Experiment: the Effects of Non-Condensable Gases on Pressurization and Pressure Control of Propellant Tanks in Microgravity

Introduction Integral to all phases of NASA’s projected planetary expeditions is affordable and reliable cryogenic fluid storage for use in propellant or life support systems. It is greatly advantageous to develop innovative vent-less pressure control designs based on cooling/mixing of the bulk tank fluid to allow storage of the cryogenic fluid with zero or reduced boil-off. The presence of noncondensable gases, can interfere with the condensation at the interface impacting tank pressure control during subcooled jet mixing especially in microgravity. The Zero-Boil-Off Tank (ZBOT) Experiments are a series of small-scale experiments aboard the International Space Station (ISS) that use a transparent volatile simulant fluid in a transparent sealed tank to delineate various fundamental fluid flow, heat and mass transport, and phase change phenomena associated with storage tank pressurization and pressure control in microgravity. The ZBOT-1 experiment was performed on the ISS 2017-2018 timeframe and collected data to validate a state-of-the-art CFD model for tank pressurization and pressure control for a pure system. The ZBOT-NC Experiment is the second experiment in the series to be performed on the International Space Station (ISS) in 2025. Its goal is to investigate the effects of noncondensable gases on interfacial evaporation and condensation during self -pressurization and jet-mixing pressure control in microgravity for a two-component system. Materials & Methods In this work, we will describe the detailed features of the ZBOT-NC experimental hardware and Diagnostics that includes nonintrusive Quantum Dot Thermometry (QDT) for whole field temperature measurement. All microgravity pressurization and pressure control tests will be performed for both the pure and the two-components systems with Xenon and Neon as the two noncondensable gases spanning small and large molecular weights and sizes. The two-phase CFD model that is developed as part of the project will be also presented and discussed. Results Ground-based pressurization and jet mixing experiments and CFD simulation results are compared to each other to validate both the fidelity of the CFD model predictions and the accuracy of the QDT measurement. Model simulations for noncondensable gas effects will also be compared against large Cryogenic LH2-GHe experiments to indicate the noncondensable gas effects on tank pressure control during jet mixing in 1G. Finally, CFD results will be presented to predict the effects of the noncondensable gas during subcooled jet mixing during the ZBOT-NC in advance of the microgravity experiment in 2015.

Evaporation Condensation↗

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), has typically limited machine learning (ML) in space studies and further study of radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNAseq) data from 6 mouse liver GeneLab datasets (GLDS) with a total of 113 spaceflight and ground-control samples to determine top features relevant to spaceflight including the effect of radiation exposure. Data was normalized within each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. The top MRMR features were used to predict spaceflight vs. ground-control samples using a Random Forest (RF) classifier with 5-fold cross validation (CV). The ML-based gene sets were further compared against differential gene expression results from individual GLDS. CV training using the top 100 MRMR genes show averages of 86% accuracy and 0.95 AUC value on the validation set over 5 folds (Figure 1A). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 811 or 68 DEGs overlapping between at least 2 or 3 studies, respectively (Figure 1B). Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism. Set analysis between the MRMR features and the DEGs showed 60 or 8 genes overlapping with at least 1 or 2 studies, respectively. MRMR feature selection and ensemble ML methods (e.g. RF) improve performance relative to a Naïve Bayes classifier when NGS data sets are analyzed. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise ratio. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from RNASeq analysis. Non-intersecting sets introduce opportunity to explore spaceflight relevant genes and implementing ML methods across existing NGS datasets may overcome sample size limitations. ML coupled with existing analytical methods enhances understanding of disease by revealing common underlying pathways across datasets.

Machine Learning↗

Metallurgical Mechanisms Controlling Mechanical Properties of Aluminum Alloy 2219 Produced By Electron Beam Freeform Fabrication

The electron beam freeform fabrication (EBF3) layer-additive manufacturing process has been developed to directly fabricate complex geometry components. EBF3 introduces metal wire into a molten pool created on the surface of a substrate by a focused electron beam. Part geometry is achieved by translating the substrate with respect to the beam to build the part one layer at a time. Tensile properties have been demonstrated for electron beam deposited aluminum and titanium alloys that are comparable to wrought products, although the microstructures of the deposits exhibit features more typical of cast material. Understanding the metallurgical mechanisms controlling mechanical properties is essential to maximizing application of the EBF3 process. In the current study, mechanical properties and resulting microstructures were examined for aluminum alloy 2219 fabricated over a range of EBF3 process variables. Material performance was evaluated based on tensile properties and results were compared with properties of Al 2219 wrought products. Unique microstructures were observed within the deposited layers and at interlayer boundaries, which varied within the deposit height due to microstructural evolution associated with the complex thermal history experienced during subsequent layer deposition. Microstructures exhibited irregularly shaped grains, typically with interior dendritic structures, which were described based on overall grain size, morphology, distribution, and dendrite spacing, and were correlated with deposition parameters. Fracture features were compared with microstructural elements to define fracture paths and aid in definition of basic processing-microstructure-property correlations.

Domack, Marcia S.↗

Support Vector Machines for Classification of Direct Energy Deposition Standoff Distance for Improved Process Control

A critical factor in the implementation of direct energy deposition is the ability to maintain the standoff distance between the nozzle and the build surface, as this influences powder capture efficiency and overall part quality. Due to process-related variations, layer height may vary, causing unintended variation in standoff distance and poor build quality. While prior work has utilized contact probing to qualify standoff distance during processing, in situ methods for qualification of standoff distance are of major interest. The present work seeks to understand efficacy of image-based methods for classifying standoff distance variation in real-time using support vector machines (SVMs). It was hypothesized that the size of the melt pool and the amount of spatter will have significant correlations with deviations in the standoff distance; thus, SVMs were used on a dataset that is comprised of morphological features of melt pool size and image entropy. The SVM model was used to classify melt pool images into categories according to standoff distance variation from nominal. K-folds cross validation was used to find the optimal hyperparameters for the SVM model. To understand the impact of the selected features on the classification performance and inference speed, multiple models were trained with differing numbers of included features. Results for classification score, inference time, and image preprocessing/feature extraction from these data are reported. The present results show that the SVM model was able to predict the standoff distance classification with an accuracy of 97 percent and a speed of 0.122 s per image, making it a viable solution for real-time control of standoff distance.

Klesmith, Zoe↗

Nanoscale reshaping of resonant dielectric microstructures by light-driven explosions

Femtosecond-laser-assisted material restructuring employs extreme optical intensities to localize the ablation regions. To overcome the minimum feature size limit set by the wave nature of photons, there is a need for new approaches to tailored material processing at the nanoscale. Here, we report the formation of deeply-subwavelength features in silicon, enabled by localized laser-induced phase explosions in prefabricated silicon resonators. Using short trains of mid-infrared laser pulses, we demonstrate the controllable formation of high aspect ratio (>10:1) nanotrenches as narrow as ~ $λ / 80$. The trench geometry is shown to be scalable with wavelength, and controlled by multiple parameters of the laser pulse train, such as the intensity and polarization of each laser pulse and their total number. Particle-in-cell simulations reveal localized heating of silicon beyond its boiling point and suggest its subsequent phase explosion on the nanoscale commensurate with the experimental data. The observed femtosecond-laser assisted nanostructuring of engineered microstructures (FLANEM) expands the nanofabrication toolbox and opens exciting opportunities for high-throughput optical methods of nanoscale structuring of solid materials.

42 ENGINEERING↗

Bridging length scales in hard materials with ultra-small angle X-ray scattering – a critical review

Owing to their exceptional properties, hard materials such as advanced ceramics, metals and composites have enormous economic and societal value, with applications across numerous industries. Understanding their microstructural characteristics is crucial for enhancing their performance, materials development and unleashing their potential for future innovative applications. However, their microstructures are unambiguously hierarchical and typically span several length scales, from sub-ångstrom to micrometres, posing demanding challenges for their characterization, especially for in situ characterization which is critical to understanding the kinetic processes controlling microstructure formation. This review provides a comprehensive description of the rapidly developing technique of ultra-small angle X-ray scattering (USAXS), a nondestructive method for probing the nano-to-micrometre scale features of hard materials. USAXS and its complementary techniques, when developed for and applied to hard materials, offer valuable insights into their porosity, grain size, phase composition and inhomogeneities. We discuss the fundamental principles, instrumentation, advantages, challenges and global status of USAXS for hard materials. Using selected examples, we demonstrate the potential of this technique for unveiling the microstructural characteristics of hard materials and its relevance to advanced materials development and manufacturing process optimization. We also provide our perspective on the opportunities and challenges for the continued development of USAXS, including multimodal characterization, coherent scattering, time-resolved studies, machine learning and autonomous experiments. Our goal is to stimulate further implementation and exploration of USAXS techniques and inspire their broader adoption across various domains of hard materials science, thereby driving the field toward discoveries and further developments.

36 MATERIALS SCIENCE↗

Robotics control using isolated word recognition of voice input

A speech input/output system is presented that can be used to communicate with a task oriented system. Human speech commands and synthesized voice output extend conventional information exchange capabilities between man and machine by utilizing audio input and output channels. The speech input facility is comprised of a hardware feature extractor and a microprocessor implemented isolated word or phrase recognition system. The recognizer offers a medium sized (100 commands), syntactically constrained vocabulary, and exhibits close to real time performance. The major portion of the recognition processing required is accomplished through software, minimizing the complexity of the hardware feature extractor.

Weiner, J. M.↗

A solution framework for linear PDE-constrained mixed-integer problems

Abstract We present a general numerical solution method for control problems with state variables defined by a linear PDE over a finite set of binary or continuous control variables. We show empirically that a naive approach that applies a numerical discretization scheme to the PDEs to derive constraints for a mixed-integer linear program (MILP) leads to systems that are too large to be solved with state-of-the-art solvers for MILPs, especially if we desire an accurate approximation of the state variables. Our framework comprises two techniques to mitigate the rise of computation times with increasing discretization level: First, the linear system is solved for a basis of the control space in a preprocessing step. Second, certain constraints are just imposed on demand via the IBM ILOG CPLEX feature of a lazy constraint callback. These techniques are compared with an approach where the relations obtained by the discretization of the continuous constraints are directly included in the MILP. We demonstrate our approach on two examples: modeling of the spread of wildfire and the mitigation of water contamination. In both examples the computational results demonstrate that the solution time is significantly reduced by our methods. In particular, the dependence of the computation time on the size of the spatial discretization of the PDE is significantly reduced.

97 MATHEMATICS AND COMPUTING↗

Understanding the effect of refractory metal chemistry on the stacking fault energy and mechanical property of Cantor-based multi-principal element alloys

Multi-principal-element alloys (MPEAs) based on 3d-transition metals show remarkable mechanical properties. In this study, the stacking fault energy (SFE) in face-centered cubic (fcc) alloys is a critical property that controls underlying deformation mechanisms and mechanical response. Here, we present an exhaustive density-functional theory study on refractory- and copper-reinforced Cantor-based systems to ascertain the effects of refractory metal chemistry on SFE. We find that even a small percent change in refractory metal composition significantly changes SFEs, which correlates favorably with features like electronegativity variance, size effect, and heat of fusion. For fcc MPEAs, we also detail the changes in mechanical properties, such as bulk, Young's, and shear moduli, as well as yield strength. A Labusch-type solute-solution-strengthening model was used to evaluate the temperature-dependent yield strength, which, combined with SFE, provides a design guide for high-performance alloys. We also analyzed the electronic structures of two down-selected alloys to reveal the underlying origin of optimal SFE and strength range in refractory-reinforced fcc MPEAs. These new insights on tuning SFEs and modifying composition-structure-property correlation in refractory- and copper-reinforced MPEAs by chemical disorder, provide a chemical route to tune twinning- and transformation-induced plasticity behavior in fcc MPEAs.

36 MATERIALS SCIENCE↗

Epitaxial Growth of Ga2O3: A Review

Beta-phase gallium oxide (β-Ga2O3) is a cutting-edge ultrawide bandgap (UWBG) semiconductor, featuring a bandgap energy of around 4.8 eV and a highly critical electric field strength of about 8 MV/cm. These properties make it highly suitable for next-generation power electronics and deep ultraviolet optoelectronics. Key advantages of β-Ga2O3 include the availability of large-size single-crystal bulk native substrates produced from melt and the precise control of n-type doping during both bulk growth and thin-film epitaxy. A comprehensive understanding of the fundamental growth processes, control parameters, and underlying mechanisms is essential to enable scalable manufacturing of high-performance epitaxial structures. This review highlights recent advancements in the epitaxial growth of β-Ga2O3 through various techniques, including Molecular Beam Epitaxy (MBE), Metal-Organic Chemical Vapor Deposition (MOCVD), Hydride Vapor Phase Epitaxy (HVPE), Mist Chemical Vapor Deposition (Mist CVD), Pulsed Laser Deposition (PLD), and Low-Pressure Chemical Vapor Deposition (LPCVD). This review concentrates on the progress of Ga2O3 growth in achieving high growth rates, low defect densities, excellent crystalline quality, and high carrier mobilities through different approaches. It aims to advance the development of device-grade epitaxial Ga2O3 thin films and serves as a crucial resource for researchers and engineers focused on UWBG semiconductors and the future of power electronics.

Chemistry↗

Assembly of objects with not fully predefined shapes

An assembly problem in a non-deterministic environment, i.e., where parts to be assembled have unknown shape, size and location, is described. The only knowledge used by the robot to perform the assembly operation is given by a connectivity rule and geometrical constraints concerning parts. Once a set of geometrical features of parts has been extracted by a vision system, applying such a rule allows the dtermination of the composition sequence. A suitable sensory apparatus allows the control the whole operation.

Arlotti, M. A.↗

Cytochemical localization of reserves during seed development in Arabidopsis thaliana under spaceflight conditions

Successful development of seeds under spaceflight conditions has been an elusive goal of numerous long-duration experiments with plants on orbital spacecraft. Because carbohydrate metabolism undergoes changes when plants are grown in microgravity, developing seed storage reserves might be detrimentally affected during spaceflight. Seed development in Arabidopsis thaliana plants that flowered during 11 d in space on shuttle mission STS-68 has been investigated in this study. Plants were grown to the rosette stage (13 d) on a nutrient agar medium on the ground and loaded into the Plant Growth Unit flight hardware 18 h prior to lift-off. Plants were retrieved 3 h after landing and siliques were immediately removed from plants. Young seeds were fixed and processed for microscopic observation. Seeds in both the ground control and flight plants are similar in their morphology and size. The oldest seeds from these plants contain completely developed embryos and seed coats. These embryos developed radicle, hypocotyl, meristematic apical tissue, and differentiated cotyledons. Protoderm, procambium, and primary ground tissue had differentiated. Reserves such as starch and protein were deposited in the embryos during tissue differentiation. The aleurone layer contains a large quantity of storage protein and starch grains. A seed coat developed from integuments of the ovule with gradual change in cell composition and cell material deposition. Carbohydrates were deposited in outer integument cells especially in the outside cell walls. Starch grains decreased in number per cell in the integument during seed coat development. All these characteristics during seed development represent normal features in the ground control plants and show that the spaceflight environment does not prevent normal development of seeds in Arabidopsis.

STS-68 Shuttle Project↗

Development of magnetostrictive active members for control of space structures

The goal of this Phase 2 Small Business Innovative Research (SBIR) project was to determine the technical feasibility of developing magnetostrictive active members for use as truss elements in space structures. Active members control elastic vibrations of truss-based space structures and integrate the functions of truss structure element, actively controlled actuator, and sensor. The active members must control structural motion to the sub-micron level and, for many proposed space applications, work at cryogenic temperatures. Under this program both room temperature and cryogenic temperature magnetostrictive active members were designed, fabricated, and tested. The results of these performance tests indicated that room temperature magnetostrictive actuators feature higher strain, stiffness, and force capability with lower amplifier requirements than similarly sized piezoelectric or electrostrictive active members, at the cost of higher mass. Two different cryogenic temperature magnetostrictive materials were tested at liquid nitrogen temperatures, both with larger strain capability than the room temperature magnetostrictive materials. The cryogenic active member development included the design and fabrication of a cryostat that allows operation of the cryogenic active member in a space structure testbed.

Johnson, Bruce G.↗