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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Fusion and fission events regulate endosome maturation and viral escape

Endosomes are intracellular vesicles that mediate the communication of the cell with its extracellular environment. They are an essential part of the cell’s machinery regulating intracellular trafficking via the endocytic pathway. Many viruses, which in order to replicate require a host cell, attach themselves to the cellular membrane; an event which usually initiates uptake of a viral particle through the endocytic pathway. In this way viruses hijack endosomes for their journey towards intracellular sites of replication and avoid degradation without host detection by escaping the endosomal compartment. Recent experimental techniques have defined the role of endosomal maturation in the ability of enveloped viruses to release their genetic material into the cytoplasm. Endosome maturation depends on a family of small hydrolase enzymes (or GTPases) called Rab proteins, arranged on the cytoplasmic surface of its membrane. Here, we model endosomes as intracellular compartments described by two variables (its levels of active Rab5 and Rab7 proteins) and which can undergo coagulation (or fusion) and fragmentation (or fission). The key element in our approach is the “per-cell endosomal distribution” and its dynamical (Boltzmann) equation. The Boltzmann equation allows us to derive the dynamics of the total number of endosomes in a cell, as well as the mean and the standard deviation of its active Rab5 and Rab7 levels. We compare our mathematical results with experiments of Dengue viral escape from endosomes. The relationship between endosomal active Rab levels and pH suggests a mechanism that can account for the observed variability in viral escape times, which in turn regulate the viability of a viral intracellular infection.

59 BASIC BIOLOGICAL SCIENCES↗

Tissue-specific directionality of cellulose synthase complex movement inferred from cellulose microfibril polarity in secondary cell walls of Arabidopsis

In plant cells, cellulose synthase complexes (CSCs) are nanoscale machines that synthesize and extrude crystalline cellulose microfibrils (CMFs) into the apoplast where CMFs are assembled with other matrix polymers into specific structures. We report the tissue-specific directionality of CSC movements of the xylem and interfascicular fiber walls of Arabidopsis stems, inferred from the polarity of CMFs determined using vibrational sum frequency generation spectroscopy. CMFs in xylems are deposited in an unidirectionally biased pattern with their alignment axes tilted about 25° off the stem axis, while interfascicular fibers are bidirectional and highly aligned along the longitudinal axis of the stem. These structures are compatible with the design of fiber-reinforced composites for tubular conduit and support pillar, respectively, suggesting that during cell development, CSC movement is regulated to produce wall structures optimized for cell-specific functions.

59 BASIC BIOLOGICAL SCIENCES↗

Investigation of magnetic noise from conductive shields in the 10–300 kHz frequency range

Here we present experimental and theoretical investigations of magnetic noise originating from radio-frequency (RF) conductive shields of flat geometry in the inductance-dominated impedance regime below 300 kHz. The measurement is based on a Q-factor determination of a coil that provides a sufficient sensitivity, placed at the position where the shield magnetic noise is measured. The theory is based on calculations of magnetic field and inductance of one or a few flat rings that emulate a conductive shield. The theoretical model is found to be in close agreement with experimental data. It can be used to predict the magnetic noise of a conductive shield with different thicknesses, conductivities, and temperatures at different distances for a wide range of frequencies. Although the model can be generalized for a more arbitrary shield geometry, in its presented form, it can be applied to the magnetic noise predictions when the shield surface curvature is not large. One important conclusion is that the RF conductive shield can generate the magnetic noise much lower than femtotesla, and, thus, it can be used in many precision experiments targeting minute high-frequency magnetic signals, such as detection of magnetic resonance imaging and nuclear quadrupole resonance signals and search for axion dark matter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Outsourced hearing in an orb-weaving spider that uses its web as an auditory sensor

Hearing is a fundamental sense of many animals, including all mammals, birds, some reptiles, amphibians, fish, and arthropods. The auditory organs of these animals are extremely diverse in anatomy after hundreds of millions of years of evolution, yet all are made up of cellular tissue and are morphologically part of the bodies of animals. Here, we show that hearing in the orb-weaving spider Larinioides sclopetarius is not constrained by the organism’s body but is extended through outsourcing hearing to its extended phenotype, the proteinaceous, self-manufactured orb web. We find that the wispy, wheel-shaped orb web acts as a hyperacute acoustic antenna to capture the sound-induced air particle movements that approach the maximum physical efficiency better than the acoustic responsivity of all previously known eardrums. By sensing the motion of web threads, the spider remotely detects and localizes the source of an incoming airborne acoustic wave, such as those emitted by approaching prey or predators. By outsourcing its acoustic sensors to its web, the spider is released from body size constraints and permits the araneid spider to increase its sound-sensitive surface area enormously, up to 10,000 times greater than the spider itself. The spider also enables the flexibility to functionally adjust and regularly regenerate its external "eardrum" according to its needs. The outsourcing and supersizing of auditory function in spiders provides unique features for studying extended and regenerative sensing and designing novel acoustic flow detectors for precise fluid dynamic measurement and manipulation.

60 APPLIED LIFE SCIENCES↗

Modeling of noise-assisted quantum transfer between donor and acceptor with finite bandwidths

We present an analytical and numerical study of noise-assisted quantum exciton (electron) transfer (ET) in a dimer consisting of donor and acceptor, modeled by interacting continuous electron bands of finite widths. We start with discrete energy levels for both bands. The interaction with the environment is modeled by a stationary stochastic process (noise) acting on all the donor and acceptor energy levels. Then, by using a continuous limit for the electron spectra, we derive integro-differential equations for the ET dynamics between the two bands. Finally, we derive from these equations rate-type differential equations for the ET dynamics. We formulate the conditions of validity of the rate-type equations. We consider different regions of parameters characterizing the widths of the donor and acceptor bands and the strength of the dimer-noise interaction. For a simplified model with a single energy level donor and a continuous acceptor band, we derive a generalized simple analytic expression and provide numerical simulations for the ET rate. They are consistent with Wigner–Weisskopf, Förster-type, and Marcus-type expressions, in their corresponding regime of parameters. For a weak dimer-noise interaction, our approach leads to the Wigner–Weisskopf ET rate, or to the Förster-type ET rate, depending on other parameters. In the limit of strong dimer-noise interaction, our approach is non-perturbative in the dimer-noise interaction constant, and it recovers the Marcus-type ET rate. Our analytic results are confirmed by numerical simulations. We demonstrate how our theoretical results are modified when both the donor and the acceptor are described by finite bands. We also show that, for a relatively wide acceptor band, the efficiency of the ET from donor to acceptor can be close to 100% for a broad range of noise amplitudes, for both 'downhill' and 'uphill' ET, for sharp and flat redox potentials, and for reasonably short times. We discuss possible applications of our approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Diamond magnetometer enhanced by ferrite flux concentrators

Magnetometers based on nitrogen-vacancy (NV) centers in diamond are promising room-temperature, solid-state sensors. However, their reported sensitivity to magnetic fields at low frequencies (≲1 kHz) is presently ≳10 pTs 1/2 , precluding potential applications in medical imaging, geoscience, and navigation. Here we show that high-permeability magnetic flux concentrators, which collect magnetic flux from a larger area and concentrate it into the diamond sensor, can be used to improve the sensitivity of diamond magnetometers. By inserting an NV-doped diamond membrane between two ferrite cones in a bowtie configuration, we realize a ~ 250-fold increase of the magnetic field amplitude within the diamond. We demonstrate a sensitivity of ~ 0.9pTs 1/2 to magnetic fields in the frequency range between 10 and 1000 Hz. This is accomplished using a dual-resonance modulation technique to suppress the effect of thermal shifts of the NV spin levels. The magnetometer uses 200 mW of laser power and 20 mW of microwave power. This work introduces a new degree of freedom for the design of diamond sensors by using structured magnetic materials to manipulate magnetic fields.

47 OTHER INSTRUMENTATION↗

Thermodynamics of signal transduction systems and fluctuation theorem in a signal cascade

Biochemical chain reactions are signal transduction cascades that can transmit biological information about the intracellular environment. In this study, we modelled a chain reaction as a code string for applying information theory. Herein, we assumed that cell signal transduction selects a strategy to maximize the transduced signal per signal event duration. To investigate the same, we calculated the information transmission capacity of the reaction chain by maximizing the average entropy production rate per reaction time, indicating the idea of the entropy coding method. Moreover, we defined a signal cascade trajectory. Subsequently, we found that the logarithm of the forward and reverse transition ratio per reaction time is equal to the entropy production rate, which derives the form of the fluctuation theorem in signal transduction. Our findings suggest the application of information entropy theory for analysing signal transduction.

59 BASIC BIOLOGICAL SCIENCES↗

Channel capacity: limitation of entropy rate during cell signal transduction

Cellular signal transduction is mediated through chain activation reactions involving signalling molecules. Information thermodynamics may be a promising approach for quantifying signal transduction. A cell signal is transduced through the signal molecule activation as a step of a signal transduction cascade. In each step, two types of entropy can be defined. First, the signal transduction was defined using thermodynamic entropy production during the chemical activation of signal molecules. Second, the chronology was described as a code string, and the logarithm of the number of signal code strings corresponded to the information entropy. Finally, the total entropy during signal transduction was determined by summing the two entropies. When maximising the total entropy, the total entropy rate per signalling molecule concentration was found to be consistent independently of each transduction step (i.e., signal molecule types). Consequently, the speed limit of the entropy rate can be calculated, providing the capacity, which is an essential property of the signal transduction cascade. The theory introduced here is expected to provide a basic framework for understanding new methods of discovering signal cascades and intracellular signal transduction.

59 BASIC BIOLOGICAL SCIENCES↗

Constructing Neural Network Based Models for Simulating Dynamical Systems

Dynamical systems see widespread use in natural sciences like physics, biology, and chemistry, as well as engineering disciplines such as circuit analysis, computational fluid dynamics, and control. For simple systems, the differential equations governing the dynamics can be derived by applying fundamental physical laws. However, for more complex systems, this approach becomes exceedingly difficult. Data-driven modeling is an alternative paradigm that seeks to learn an approximation of the dynamics of a system using observations of the true system. In recent years, there has been an increased interest in applying data-driven modeling techniques to solve a wide range of problems in physics and engineering. Here this article provides a survey of the different ways to construct models of dynamical systems using neural networks. In addition to the basic overview, we review the related literature and outline the most significant challenges from numerical simulations that this modeling paradigm must overcome. Based on the reviewed literature and identified challenges, we provide a discussion on promising research areas.

97 MATHEMATICS AND COMPUTING↗

Randomized probe imaging through deep k-learning

Randomized probe imaging (RPI) is a single-frame diffractive imaging method that uses highly randomized light to reconstruct the spatial features of a scattering object. The reconstruction process, known as phase retrieval, aims to recover a unique solution for the object without measuring the far-field phase information. Typically, reconstruction is done via time-consuming iterative algorithms. In this work, we propose a fast and efficient deep learning based method to reconstruct phase objects from RPI data. The method, which we call deep k-learning, applies the physical propagation operator to generate an approximation of the object as an input to the neural network. This way, the network no longer needs to parametrize the far-field diffraction physics, dramatically improving the results. Deep k-learning is shown to be computationally efficient and robust to Poisson noise. The advantages provided by our method may enable the analysis of far larger datasets in photon starved conditions, with important applications to the study of dynamic phenomena in physical science and biological engineering.

Guo, Zhen (ORCID:0000000213473451)↗

Unexpected symmetry breaking in ferroelectric wurtzite thin films on silicon observed by optical second harmonic generation

Optical second harmonic generation (SHG) exists as a popular tool for probing materials with broken inversion symmetry in the physical and biological sciences. SHG polarimetry can reveal material anisotropy with high sensitivity, including point group and phase transitions. Here, we probe ferroelectric wurtzite films with a nominal 6 mm symmetry under a normal reflection geometry using SHG microscopy and discover an unexpected symmetry breaking. Symmetry considerations would normally forbid the detection of the SHG signal when light propagates along the polar 6-fold rotation axis. Yet a uniquely anisotropic SHG response is observed in this geometry in Al 1-x B x N, Al 1-x Sc x N, Zn 1-x Mg x O, and AlN/Al 1-x Sc x N heterostructures grown on silicon that can be modeled by an average monoclinic symmetry of point group m. A significant enhancement of the SHG signal corresponding to up to a 5.3× increase in the SHG intensity (hence ∼2.3 × in effective SHG tensor coefficient) is observed at antiparallel polar domain walls, suggesting local cooperative alignment of symmetry-breaking structural distortions. Namely, it is found that the monoclinic mirror plane is oriented predominantly perpendicular to the walls. Such increases in domain wall SHG thus reveal that subtle symmetry breaking can be a pathway to large property enhancements.

36 MATERIALS SCIENCE↗

Deep learning enhanced super-resolution x-ray fluorescence microscopy by a dual-branch network

X-ray fluorescence (XRF) microscopy is a powerful technique for quantifying the distribution of elements in complex materials, which makes it a crucial imaging technique across a wide range of disciplines in physical and biological sciences, including chemistry, materials science, microbiology, and geosciences. However, as a scanning microscopy technique, the spatial resolution of XRF imaging is inherently constrained by the x-ray probe profile and scanning step size. Here we propose a dual-branch machine learning (ML) model, which can extract scale-variant features and bypass abundant low-frequency information separately, to enhance the spatial resolution of the XRF images by mitigating the effects of blurring from the probe profile. The model is trained by simulated natural images, and a two-stage training strategy is used to overcome the domain gap between the natural images and experimental data. The tomography reconstruction from enhanced XRF projections shows an improvement in resolution by a scale factor of four and reveals distinct internal features invisible in low-resolution XRF within a battery sample. This study offers a promising approach for obtaining high-resolution XRF imaging from its low-resolution version, paving the way for future investigations in a broader range of disciplines and materials.

36 MATERIALS SCIENCE↗

Quantitative Nonlinear Optical Polarimetry with High Spatial Resolution

Nonlinear optical microscopy such as in the optical second-harmonic generation (SHG) modality has become a popular tool today for probing materials in the physical and biological sciences. While imaging and spectroscopy are widely used in the microscopy mode, nonlinear polarimetry, which can shed light on materials’ symmetry and microstructure, is relatively underdeveloped. This is partly because quantitative analytical modeling of the optical SHG response for anisotropic crystals and films largely assumes low-numerical aperture (NA) focusing of light, where the plane-wave approximation is sufficient. Tight focusing provides unique benefits in revealing out-of-plane polarization responses, which cannot be detected by near-plane-wave illumination at normal incidence. Here, we outline a method for quantitatively analyzing SHG polarimetry measurements obtained under high-NA focusing within a microscope geometry. Experiments and simulations of a variety of standard samples, from single crystals to thin films, are in good agreement, including measured and simulated spatial SHG maps of ferroelectric domains. A solution to the inverse problem is demonstrated, where the spatial distribution of an SHG tensor with unknown tensor coefficient magnitudes is determined by experimentally measured polarimetry. The ability to extract the out-of-plane component of the nonlinear polarization in normal incidence is demonstrated, which can be valuable for high-resolution polarimetry of 2D materials, thin films, heterostructures, and uniaxial crystals with a strong out-of-plane response.

36 MATERIALS SCIENCE↗

Examining the role of glycoside hydrolases in local rheology of Pseudomonas aeruginosa biofilms

Current research strategies in the treatment of biofilm infections have focused on dispersal, in which bacteria are made to vacate the extracellular polymeric substance (EPS) surrounding them and return to a planktonic state where antimicrobial treatments are more effective. Glycoside hydrolases (GHs), which cleave bonds in EPS polysaccharides, have been shown to promote dispersal in Pseudomonas aeruginosa biofilms. The dispersal mechanism is possibly due to GHs’ ability to directly release bacteria from the EPS, disrupt EPS’ ability to regulate the environment, or reduce overall mechanical stability. In this work, passive microrheology is used to examine the relevance of the last mechanism by exploring the effects of three GHs (α-amylase, cellulase, and xylanase) known to disperse P. aeruginosa on local biofilm viscoelasticity. Compared to control studies in wild-type strains, it is found that treatment with all three GHs results in statistically relatively less elastic and stiffer biofilms, indicating that changes to mechanical stability may be a factor in effective dispersal. Both cellulase and xylanase were observed to have the greatest impact in creating a less stiff and elastic biofilm; these GHs have been observed to be effective at dispersal in the published results. Each GH was further tested on biofilms grown with strains that produced EPS missing specific polysaccharide components. Cellulase specifically targeted Psl, which forms the major structural and mechanical backbone of the EPS, explaining its efficacy in dispersal. However, xylanase did not appear to exhibit any affinity to any polysaccharide within the EPS based on the microrheology results. Overall, these results suggest that the local microrheology of the biofilms is impacted by GHs and that may be one of the factors that is causing the ability of these therapeutics to enhance dispersal.

59 BASIC BIOLOGICAL SCIENCES↗

A framework of computer vision-enhanced microfluidic approach for automated assessment of the transient sickling kinetics in sickle red blood cells

The occurrence of vaso-occlusive crisis greatly depends on the competition between the sickling delay time and the transit time of individual sickle cells, i.e., red blood cells from sickle cell disease (SCD) patients, while they are traversing the circulatory system. Many drugs for treating SCD work by inhibiting the polymerization of sickle hemoglobin (HbS), effectively delaying the sickling process in sickle cells (SS RBCs). Most previous studies on screening anti-sickling drugs, such as voxelotor, rely on in vitro testing of sickling characteristics, often conducted under prolonged deoxygenation for up to 1 hour. However, since the microcirculation of RBCs typically takes less than 1 minute, the results of these studies may be less accurate and less relevant for in vitro-in vivo correlation. In our current study, we introduce a computer vision-enhanced microfluidic framework designed to automatically capture the transient sickling kinetics of SS RBCs within a 1-min timeframe. Our study has successfully detected differences in the transient sickling kinetics between vehicle control and voxelotor-treated SS RBCs. This approach has the potential for broader applications in screening anti-sickling therapies.

59 BASIC BIOLOGICAL SCIENCES↗

Ultra-High Resolution Elemental/Isotopic Mass Spectrometry (m/?m> 1,000,000): Coupling of the Liquid Sampling-Atmospheric Pressure Glow Discharge with an Orbitrap Mass Spectrometer for Applications in Biological Chemistry and Environmental Analysis

Many fundamental questions of astrophysics, biochemistry, and geology rely on the ability to accurately and precisely measure the mass and abundance of isotopes. Taken a step further, the capacity to perform such measurements on intact molecules provides insights into processes in diverse biological systems. Described here is the coupling of a combined atomic and molecular (CAM) ionization source, the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma, with a commercially available ThermoScientific Fusion Lumos mass spectrometer. Demonstrated for the first time is the ionization and isotopically-resolved fingerprinting of a long-postulated, but never mass-spectrometrically observed, bi-metallic complex Hg:Se-cysteine. Such a complex has been implicated as having a role in observations of Hg detoxification by selenoproteins/amino acids. Demonstrated as well is the ability to mass spectrometrically-resolve the geochronologically important isobaric 87Sr and 87Rb species (?m ~ 0.3 mDa, mass resolution m/?m ? 1,700,000). The mass difference in this case reflects the beta-decay of the 87Rb to the stable Sr isotope. These two demonstrations highlight what may be a significant change in bioinorganic and atomic mass spectrometry, with impact expected across a broad spectrum of the physical, biological and geological sciences.

Hoegg, Edward D.↗

Accelerator Technologies and Science: Progress and Outlook

For over half a century, high-energy particle accelerators play a key role and shape modern nuclear and particle physics, they are also the instruments at the forefront of research for material science and biology. The physics needs continuously push us to invent novel ways to increase energy and improve the performance of accelerators, reduce their cost and make them more power-efficient. Here we briefly overview the most notable accelerator facilities which recently became operational and are now employed for research in nuclear physics, basic energy sciences, neutrinos, high energy particle frontier. We also present upcoming and planned future facilities and outline their main goals, challenges, and required R&D. Focus will be given to the core accelerator technologies such as magnets, RF acceleration, and targets as we as leading beam physics developments such as beam cooling, colliding beams and plasma acceleration.

Shiltsev, Vladimir D.↗

33 Unresolved Questions in Nanoscience and Nanotechnology

Significant advances in science and engineering often emerge at the intersections of disciplines. Nanoscience and nanotechnology are inherently interdisciplinary, uniting researchers from chemistry, physics, biology, medicine, materials science, and engineering. This convergence has fostered novel ways of thinking and enabled the development of materials, tools, and technologies that have transformed both basic and applied research, as well as how we address critical societal challenges. In this Nano Focus, we pose and explore 33 questions whose answers could profoundly impact fields such as energy, electronics, the environment, optics, and medicine. These questions highlight the need for deeper foundational understanding, improved tools and techniques, and innovative applications─each with significant societal relevance. Together, they represent a global call-to-action for the scientific community.

77 NANOSCIENCE AND NANOTECHNOLOGY↗