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At least 1,099 records · Page 61

Dendrites, viscous fingers, and the theory of pattern formation

Recent developments in the theory of pattern formation in dendritic crystal growth and viscous fingering in fluids are reviewed. Consideration is given to the discovery that weak capillary forces act as singular perturbations which lead to selection mechanisms in dendritic crystal growth and fingering patterns. Other topics include the conventional thermodynamic model of the solidification of a pure substance from its melt, fingering instability, pattern selection, the solvability theory, dendritic growth rates, the bubble effect discovered by Couder et al. (1986), the dynamics of pattern-forming systems, and snowflake formation.

Langer, J. S.↗

The 1990 MB: The first Mars Trojan

Asteroid 1990 MB was discovered by D. H. Levy and H. E. Holt during the course of the Mars and Earth Crossing Asteroid and Comet Survey. An orbit based on a 9 day arc and the asteroid's location near Mars' L5 (trailing Lagrangean) longitude led E. Boswell to speculate that it might be in 1:1 resonance with Mars, analogous to the Trojan asteroids of Jupiter. Subsequent observations strengthened the possibility, and later calculations confirmed it. Thus 1990 MB is the first known asteroid in 1:1 resonance with a planet other than Jupiter. The existence of 1990 MB (a small body most likely between 2 and 4 km in diameter) provides remarkable confirmation of computer simulations. These self consistent n-body simulations demonstrated this sort of stability for Trojans of all the terrestrial planets over at least a 2 million year time base. The discovery of 1990 MB suggests that others of similar or smaller diameter may be found. Using hypothetical populations of Mars Trojans, their possible sky plane distributions were modeled as a first step in undertaking a systematic observational search of Mars' L4 and L5 libration regions.

Innanen, Kimmo A.↗

Abundant Cool Magnesium-Rich Pyroxene Crystals in Comet Hale-Bopp

Modeling of the observed dust emission from Comet Hale-Bopp over a large range of heliocentric distances (2.8 AU - 0.93 AU -1.7 AU) led to the discovery of Mg-rich pyroxene crystals in the coma These pyroxene crystals are apparent in the 10 micron spectrum only when the comet is close to perihelion (r(sub h) = 1.2 AU) because they are cooler than the other silicate minerals. The pyroxene crystals are cooler than the other species because of their high Mg-content. They do not absorb as efficiently as the other silicate minerals. Given the same high Mg content of Mg/(Mg + Fe) = 0.9, radiative equilibrium computations show that pyroxene crystals are expected to be 150 K cooler than olivine crystals. The pyroxene crystals are also about 10x more abundant than the other silicate mineral species. Their high Mg content and relatively large abundance are in agreement with the preponderance of pyroxene interplanetary dust particles (IDPs) and the recent reanalysis of the PUMA-I flyby of Comet Halley. Before Hale-Bopp, only olivine crystals were detected spectroscopically in comets, probably because the pyroxene crystals are less optically active, hence significantly cooler and harder to detect in contrast to the warmer silicate species. Determining the relative abundances of silicate minerals depends on their Mg contents. If the pyroxene crystals in Comet Hale-Bopp are solar nebula condensates, then they probably had to form during the early FU Orionis epoch when the inner disk was hot enough and be transported out to the region of formation of icy planetesimals without being reheated. Reheating events appear to reincorporate Fe back into the crystals or form Fe-rich rims, which are not consistent with the high-Mg-content crystals. The condensation of Mg-rich pyroxene crystals is expected from solar nebula thermal equilibrium computations. However, their subsequent transport to the outer solar nebula unaltered has yet to be theoretically demonstrated. The discovery of Mg-rich crystals in Comet Hale-Bopp and in AGB stars opens the possibility that these crystals are relic interstellar grains. One-third of IDPs have been shown to have significant deuterium enrichments, thus indicating that they contain presolar material. By spectroscopic analogy to IDPs the Mg-rich pyroxene crystals in Comet Hale-Bopp may be presolar grains. If so, then the comet contains largely ISM silicates. ISM grains may have been the dominant source of dust in the outer early solar nebula.

Wooden, D. H.↗

Origin and Evolution of the Unusual Object 1996 PW: Asteroids from the Oort Cloud?

The unusual object 1996 PW was discovered on 1996 August 9 by the Near-Earth Asteroid Tracking automated search camera operating from Haleakala in Hawaii. Although asteroidal in appearance, it was soon determined that the object is in a near-parabolic orbit similar to that of a long-period comet. No object that was not an active comet has ever been discovered on such an eccentric orbit. The discovery of 1996 PW prompted us to examine and evaluate its possible origins, including the intriguing possibility that it is an asteroid from the Oort cloud. Current models for the formation of the Oort cloud argue that most of the material there should be from the Uranus-Neptune region and thus cometary, not asteroidal, in composition. We better quantify these models and show that approximately 1% of the Oort Cloud population should be asteroids. We find that 1996 PW has almost certainly been a resident of the Oort cloud. However, we find it equally likely that 1996 PW is an extinct comet or an asteroid. Although not conclusive, our results represent a significant change in our understanding of the Oort cloud, because they suggest that the ejection process sampled material from as close to the Sun as the asteroid belt in the primordial solar nebula and hence much warmer formation temperatures than previously thought. This diverse sample is preserved in the Oort cloud.

Weissman, Paul R.↗

New Development in NASA's Rodent Research Hardware for Conducting Long Duration Biomedical and Basic Research in Space

Animal models, particularly rodents, are the foundation of pre-clinical research to understand human diseases and evaluate new therapeutics, and play a key role in advancing biomedical discoveries both on Earth and in space. The National Research Councils Decadal survey emphasized the importance of expanding NASAs life sciences research to perform long duration, rodent experiments on the International Space Station (ISS). To accomplish this objective, flight hardware, operations, and science capabilities were developed at NASA Ames Research Center (ARC) to enhance science return for both commercial (CASIS) and government-sponsored rodent research. The Rodent Research program at NASA ARC has pioneered a new research capability on the International Space Station and has progressed toward translating research to the ISS utilizing commercial rockets, collaborating with academia and science industry, while training crewmembers to assist in performing research on orbit. Throughout phases of these missions, our practices, hardware and operations have evolved from tested to developed standards, and we are able to modify and customize our procedure and operations for mission specific requirements. The Rodent Research Habitat is capable of providing a living environment for animals on ISS according to standard animal welfare requirements. Using the cameras in the Habitat, the Rodent Research team has the ability to perform daily health checks on animals, and further analyze the collected videos for behavioral studies. A recent development of the Rodent Research hardware is inclusion of enrichment, to provide the animals the ability to rest and huddle. The Enrichment Hut is designed carefully for adult mice (up to 35 week old) within animal welfare, engineering, and operations constraints. The Hut is made out of the same stainless steel mesh as the cage interior, it has an ingress and an egress to allow animals move freely, and a hinge door to allow crewmembers remove the animals easily. The Rodent Research team has also developed Live Animal Return (LAR) capability, which will be implemented during Rodent Research-5 mission for the first time. The animals will be transported from the Habitat to a Transporter, which will return on the Dragon capsule and splashes down in the Pacific Ocean. Once SpaceX retrieves the Dragon, all powered payloads will be transferred to a SeaVan and transferred to the Long Beach pier. The NASA team then receives the transporter and delivers to a PI-designated laboratory within 120 mile radius of Long Beach. This is a significant improvement allowing researchers to examine animals within 72 hrs. of reentry or to conduct recovery experiments. Together, the hardware improvements and experience that the Rodent Research team has gained working with principal investigators and ISS crew to conduct complex experiments on orbit are expanding capabilities for long duration rodent research on the ISS to achieve both basic science and biomedical objectives.

ISS↗

THE DAVINCI+ MISSION TO REVEAL THE MYSTERIES OF VENUS: DEEP ATMOSPHERE VENUS INVESTIGATION OF NOBLE GASES, CHEMISTRY, AND IMAGING PLUS

The Deep Atmosphere Venus Investigation of Noble Gases, Chemistry, and Imaging Plus (DAVINCI+) mission is one of four finalists now in Phase A study as part of the ongoing Discovery Program competition [1-5]. If selected for flight, DAVINCI+ will be the first mission to Venus to incorporate flybys, a descent probe, and an orbital phase into one unified architecture – at the cost of a Discovery mission. The result will be a transformative new understanding of the atmosphere, surface, and evolutionary path of Venus as a once-habitable planet [6] (and model exoplanet) that is now host to a certainly unhabitable surface environment.

S Getty↗

WIS and WIGOS Metadata as the Foundation for a Sustainable Framework for Global Greenhouse Gas Watch Data Exchange

Metadata (data about data) is a critical component of data discovery, description, evaluation, documentation, and preservation. Developing and propagating metadata standards has been a longstanding area of activity in WMO and beyond. The WIS2 and WIGOS metadata models are being actively developed and maintained by dedicated task teams, established under the WMO Expert Team on Metadata. The metadata representations and vocabularies are governed by well-established processes within WMO. These standards are being used in a number of metadata/data exchange activities (e.g., WMO Information System 2.0 (WIS2), WIGOS (WMDR), Climate Data Management Systems (CMDS), etc.). It should also be noted that the application of the WIS2 and WIGOS standards fully support the WMO Unified Data Policy and open data policy as well as greatly enhance the value of observations by fostering data F.A.I.R.ness. Furthermore, the WMO metadata standards can serve as the foundation for a framework that will facilitate metadata mapping between the existing schemas used in well-established data centres, e.g., WMO WDCGG (World Data Centre for Greenhouse Gases) and NOAA ObsPack (Observation Package Data Products) and to automate metadata exchange between data centres as well as with WMO. These activities will play a central role in integrating measurements sponsored by various member countries and organizations to provide a more comprehensive characterization of the temporal and spatial distribution of the greenhouse gases. At the same time, this metadata exchange can lead to member countries and partner organizations improving their current metadata collection process for data discoverability, interoperability, and (re)usability. This presentation will describe metadata activities in the context of WIS2 and WIGOS and how they apply to GGGW data integration via metadata mapping and exchange.

Gao Chen↗

Modeling Space Radiation with Radiomimetic Agent Bleomycin

Space radiation consists of proton and helium from solar particle events (SPE) and high energy heavy ions from galactic cosmic ray (GCR). This mixture of radiation with particles at different energy levels has different effects on biological systems. Currently, majority studies of radiation effects on human were based on single-source radiation due to the limitation of available method to model effects of space radiation on living organisms. While NASA Space Radiation Laboratory is working on advanced switches to make it possible to have a mixed field radiation with particles of different energies, the radiation source will be limited. Development of an easily available experimental model for studying effects of mixed field radiation could greatly speed up our progress in our understanding the molecular mechanisms of damage and responses from exposure to space radiation, and facilitate the discovery of protection and countermeasures against space radiation, which is critical for the mission to Mars. Bleomycin, a radiomimetic agent, has been widely used to study radiation induced DNA damage and cellular responses. Previously, bleomycin was often compared to low low Linear Energy Transfer (LET) gamma radiation without defined characteristics. Our recent work demonstrated that bleomycin could induce complex clustered DNA damage in human fibroblasts that is similar to DNA damage induced by high LET radiation. These type of DNA damage is difficult to repair and can be visualized by gamma-H2Ax staining weeks after the initial insult. The survival ratio between early and late plating of human fibroblasts after bleomycin treatment is between low LET and high LET radiation. Our results suggest that bleomycin induces DNA damage and other cellular stresses resembling those resulted from mixed field radiation with both low and high LET particles. We hypothesize that bleomycin could be used to mimic space radiation in biological systems. Potential advantages and limitations of using bleomycin to treat biological specimen as an easily available model to study effects of space radiation on biological systems and to develop countermeasures for space radiation associated risks will be discussed.

Lu, Tao↗

Interpretable, extensible linear and symbolic regression models for charge density prediction using a hierarchy of many-body correlation descriptors

Here, density functional theory (DFT) is routinely used to make electronic structure predictions for high-throughput screening of materials and molecules for technologically relevant areas, like the identification of better catalysts, electronic materials, and drug discovery. However, the DFT formalism is limited by (a) its poor (quadratic-to-quartic) scaling, and (b) the need to perform repeated eigenvalue computations of the electronic Hamiltonian as part of its self-consistent field (SCF) iteration procedure to obtain the converged ground state electron density, ρ (r). Approaches that directly predict ρ (r) of a structure with high accuracy can accelerate conventional SCF calculations and can also be used in linearly scaling methods such as orbital-free DFT. To this end, we present a procedure to predict the ground state electron density of molecular and periodic three-dimensional systems directly from the atomic structure with a particular emphasis on physical interpretability. In our framework, ρ (r) is modeled using many-body correlation descriptors that accurately capture the effects of local atomic arrangements in the neighborhood of a grid point. Our use of a linear regression scheme to fit to charge density data enables transparent analysis of the relative contributions of various types of local atomic correlations. By systematically including increasingly complex correlations, our model is shown to accurately predict ρ (r) for a variety of chemically and electronically diverse systems — amorphous Ge, Al(001) slab, crystalline Ga 2 O 3 , molecular benzene, and polyethylene. We then demonstrate a symbolic regression-based protocol to construct easily computable, interpretable features from lower-order correlations that significantly improves our electron density predictions with effectively no increase in the computational cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Prediction of histone post-translational modifications using deep learning

Abstract Motivation Histone post-translational modifications (PTMs) are involved in a variety of essential regulatory processes in the cell, including transcription control. Recent studies have shown that histone PTMs can be accurately predicted from the knowledge of transcription factor binding or DNase hypersensitivity data. Similarly, it has been shown that one can predict PTMs from the underlying DNA primary sequence. Results In this study, we introduce a deep learning architecture called DeepPTM for predicting histone PTMs from transcription factor binding data and the primary DNA sequence. Extensive experimental results show that our deep learning model outperforms the prediction accuracy of the model proposed in Benveniste et al. (PNAS 2014) and DeepHistone (BMC Genomics 2019). The competitive advantage of our framework lies in the synergistic use of deep learning combined with an effective pre-processing step. Our classification framework has also enabled the discovery that the knowledge of a small subset of transcription factors (which are histone-PTM and cell-type-specific) can provide almost the same prediction accuracy that can be obtained using all the transcription factors data. Availabilityand implementation https://github.com/dDipankar/DeepPTM. Supplementary information Supplementary data are available at Bioinformatics online.

Baisya, Dipankar Ranjan (ORCID:0000000267847359)↗

Widen the resonance at ultra-high energies: novel probes of neutrino self-interactions in the high-mass regime

Neutrino self-interactions beyond the Standard Model are well motivated by the nonzero masses of neutrinos, which are the only known particles guaranteed to have new physics. Meanwhile, cosmic messengers, especially neutrinos, play a central role in probing new physics, as they provide experimental conditions far beyond the reach of laboratories and serve as the link between laboratory fundamental-physics discoveries and their roles in the Universe, where many new physics motivations originate.In this work, we propose a novel probe of neutrino self-interactions through ultrahigh-energy neutrinos scattering off the cosmic neutrino background when the lightest neutrino species remains relativistic today.This allows us to “Widen the Resonance” of such scattering [1].In addition, we also provide a semi-analytic framework for cosmogenic ultrahigh-energy neutrino production, avoiding computationally intensive simulations and yielding results precise enough for beyond-the-standard-model studies.The widened resonance enables future ultrahigh-energy neutrino telescopes,in particular GRAND, to probe mediator masses from MeV to GeV, reaching couplings down to g ∼ 10$^{-3}$ — up to two orders of magnitude beyond current bounds.Our results enhance the discovery potential of neutrino self-interactions in the high-mass regime, potentially offering crucial insights into the connections between the neutrino sector and dark sector.

Machado, Pedro A.N. [Fermilab] (ORCID:000000029118↗

An Isolated Mass-gap Black Hole or Neutron Star Detected with Astrometric Microlensing

We present the analysis of five black hole candidates identified from gravitational microlensing surveys. Hubble Space Telescope astrometric data and densely sampled light curves from ground-based microlensing surveys are fit with a single-source, single-lens microlensing model in order to measure the mass and luminosity of each lens and determine if it is a black hole. One of the five targets (OGLE-2011-BLG-0462/MOA-2011-BLG-191 or OB110462 for short) shows a significant >1 mas coherent astrometric shift, little to no lens flux, and has an inferred lens mass of 1.6–4.4 M ⨀ . This makes OB110462 the first definitive discovery of a compact object through astrometric microlensing and it is most likely either a neutron star or a low-mass black hole. This compact-object lens is relatively nearby (0.70–1.92 kpc) and has a slow transverse motion of <30 kms -1 . OB110462 shows significant tension between models well fit to photometry versus astrometry, making it currently difficult to distinguish between a neutron star and a black hole. Additional observations and modeling with more complex system geometries, such as binary sources, are needed to resolve the puzzling nature of this object. For the remaining four candidates, the lens masses are <2M ⨀ , and they are unlikely to be black holes; two of the four are likely white dwarfs or neutron stars. We compare the full sample of five candidates to theoretical expectations on the number of black holes in the Milky Way (∼10 8 ) and find reasonable agreement given the small sample size.

Astrophysical black holes↗

Artificial intelligence–powered biofoundries for protein engineering and metabolic engineering

Synthetic biology is rapidly evolving through the integration of artificial intelligence (AI) and automated biofoundries. This convergence accelerates the design–build–test–learn cycle, shifting protein engineering and metabolic engineering from labor-intensive manual experimentation to autonomous experimentation. This review summarizes recent advances in workflow development, AI models, and their integration with biofoundries for automated or autonomous protein engineering and metabolic engineering. Particularly, we highlight the potential of AI-powered biofoundries for accelerated scientific discovery and innovation in synthetic biology.

Chen, Junyu [Univ. of Illinois at Urbana-Champaign↗

Development of multi-scale computational frameworks to solve fusion materials science challenges

Over the past two decades, the US-DOE has funded multiple projects that rely on high-performance computing and exascale computing platforms to accelerate scientific discoveries and address grand scientific challenges, such as harnessing fusion energy. In this article, we review in detail one of these efforts aimed at enhancing our capability to model plasma-facing materials subject to plasma and high-energy ion/neutron irradiation. The plasma surface interactions project has built a multi-scale modeling framework where many of the plasma- and high-energy ion/neutron irradiation-induced effects occurring in tungsten are explored. Here, this knowledge is used to develop atomistically-informed, high-fidelity continuum and meso-scale models that can be validated against experiments. We review the developments within this project, with attention to experimental validation efforts, and specifically highlight activities associated with: helium bubble bursting and equation of state, and hydrogen-helium interactions in tungsten; atomistically-informed model development for beryllium-tungsten material mixing; coupling of scrape-of-layer plasma, sheath and material models; and coupling of stochastic cluster-dynamics and crystal plasticity models to address radiation effects in tungsten under stress. Finally, we present how the project is preparing for future computational architectures, for instance through efforts to adapt atomistic methods to exascale computing.

36 MATERIALS SCIENCE↗

Flow instabilities in helical-coil steam generators for small modular reactors: A review

Here, this study covers the research and discoveries in two-phase flow-boiling instabilities available in the literature—specifically for a helical-coil steam generator (HCSG), including experimental findings, theoretical research, computational models, and system code analyses—supporting research and development of representative small modular reactors (SMRs). Like other new and advanced reactor systems, water-cooled SMRs require experimental data from both integral and separate thermal-hydraulics test facilities for the verification and validation (V&V) of the computational models and computer codes in order to design and obtain regulatory approval. The complex dynamics of two-phase flow-boiling instabilities includes flow regimes physics phenomena, flow-channel geometries, heat-transfer behavior, and interactions among the solid–liquid-gas within the system boundary, all of which are pivotal for understanding the design and operational challenges of SMRs. This study focuses on identifying the relevant knowledge gaps on boiling instabilities—specifically for a HCSG—and provides insights about future research direction optimizing the transport of thermal energy, mass-flow rates, and boundary conditions that ensure the adequate heat-transfer performance, operational stability, and safety associated with SMR systems.

20 FOSSIL-FUELED POWER PLANTS↗

CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer Generation

Molecular conformer generation (MCG) is an important task in cheminformatics and drug discovery. The ability to efficiently generate low-energy 3D structures can avoid expensive quantum mechanical simulations, leading to accelerated virtual screenings and enhanced structural exploration. Several generative models have been developed for MCG, but many struggle to consistently produce high-quality conformers for meaningful downstream applications. To address these issues, we introduce CoarsenConf, which coarse-grains molecular graphs based on torsional angles and integrates them into an SE(3)-equivariant hierarchical variational autoencoder. Through equivariant coarse-graining, we aggregate the fine-grained atomic coordinates of subgraphs connected via rotatable bonds, creating a variable-length coarse-grained latent representation. Our model uses a novel aggregated attention mechanism to restore fine-grained coordinates from the coarse-grained latent representation, enabling efficient generation of accurate conformers. Furthermore, we evaluate the chemical and biochemical quality of our generated conformers on multiple downstream applications, including property prediction and large-scale oracle-based protein docking. Overall, CoarsenConf generates more accurate conformer ensembles compared to prior generative models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning potential assisted exploration of complex defect potential energy surfaces

Abstract Atomic-scale defects generated in materials under both equilibrium and irradiation conditions can significantly impact their physical and mechanical properties. Unraveling the energetically most favorable ground-state configurations of these defects is an important step towards the fundamental understanding of their influence on the performance of materials ranging from photovoltaics to advanced nuclear fuels. Here, using fluorite-structured thorium dioxide (ThO 2 ) as an exemplar, we demonstrate how density functional theory and machine learning interatomic potential can be synergistically combined into a powerful tool that enables exhaustive exploration of the large configuration spaces of small point defect clusters. Our study leads to several unexpected discoveries, including defect polymorphism and ground-state structures that defy our physical intuitions. Possible physical origins of these unexpected findings are elucidated using a local cluster expansion model developed in this work.

36 MATERIALS SCIENCE↗

Nonreciprocal directional dichroism at telecom wavelengths

Magnetoelectrics with ultra-low symmetry and spin-orbit coupling are well known to display a number of remarkable properties including nonreciprocal directional dichroism. As a polar and chiral magnet, Ni 3 TeO 6 is predicted to host this effect in three fundamentally different configurations, although only two have been experimentally verified. Inspired by the opportunity to unravel the structure-property relations of such a unique light-matter interaction, we combined magneto-optical spectroscopy and first-principles calculations to reveal nonreciprocity in the toroidal geometry and compared our findings with the chiral configurations. We find that formation of Ni toroidal moments is responsible for the largest effects near 1.1 eV—a tendency that is captured by our microscopic model and computational implementation. At the same time, we demonstrate deterministic control of nonreciprocal directional dichroism in Ni 3 TeO 6 across the entire telecom wavelength range. This discovery will accelerate the development of photonics applications that take advantage of unusual symmetry characteristics.

36 MATERIALS SCIENCE↗