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At least 217 records · Page 12

The Landscape of Thermal Transients from Supernovae Interacting with a Circumstellar Medium

The interaction of supernova ejecta with a surrounding circumstellar medium (CSM) generates a strong shock, which can convert ejecta kinetic energy into observable radiation. Given the diversity of potential CSM structures (arising from diverse mass-loss processes such as late-stage stellar outbursts, binary interaction, and winds), the resulting transients can display a wide range of light-curve morphologies. We provide a framework for classifying the transients arising from interaction with a spherical CSM shell. The light curves are decomposed into five consecutive phases, starting from the onset of interaction and extending through shock breakout and subsequent shock cooling. The relative prominence of each phase in the light curve is determined by two dimensionless quantities representing the CSM-to-ejecta mass ratio η, and the breakout parameter ξ. These two parameters define four light-curve morphology classes, where each class is characterized by the location of the shock breakout and the degree of deceleration as the shock sweeps up the CSM. We compile analytic scaling relations connecting the luminosity and duration of each light-curve phase to the physical parameters. We then run a grid of radiation hydrodynamics simulations for a wide range of ejecta and CSM parameters to numerically explore the landscape of interaction light curves, and to calibrate and confirm the analytic scalings. We connect our theoretical framework to several case studies of observed transients, highlighting the relevance in explaining slow-rising and superluminous supernovae, fast blue optical transients, and double-peaked light curves.

79 ASTRONOMY AND ASTROPHYSICS↗

νBDX: a Coherent Elastic Neutrino Nucleus Scattering (CEνNS) experiment at Jefferson Lab

Particle physics is an ever-changing field seeking to explain phenomena that lie at the limits of our current knowledge. Among discovered and hypothesized interactions, Coherent Elastic Neutrino-Nucleus Scattering (CE?NS) stands out as a fascinating and elusive phenomenon, offering a unique window into the nature of neutrinos and their interactions with matter. CE?NS, a process predicted by the Standard Model, represents one of the subtle ways in which neutrinos can interact with atomic nuclei. Unlike other neutrinonucleus interactions, CE?NS occurs coherently, meaning that the entire nucleus collectively responds to the neutrino-mediated weak force, resulting in small energy transfers to the nucleus as a whole. The extremely rare nature of CE?NS events presents a formidable challenge to experimenters seeking to detect and study these interactions. Recent advances in detector technologies and the implementation of large-scale experiments, such as coherent neutrino scattering experiments at research facilities around the world, have opened up new avenues for exploring this elusive phenomenon. These experiments aim not only to observe CE?NS directly but also to extract valuable information on neutrino properties, nuclear structure, and potential deviations from the Standard Model. This thesis aims to study the feasibility of an experiment to study CE?NS at The Thomas Jefferson National Accelerator Facility, Newport News, VA, USA. This would be an experiment that exploits the production of neutrinos by an electron beam dumped on a thick target (the beam dump). The large quantity of neutrinos produced and their energy profile are well suited to the purpose of studying the CE?NS. In my thesis, I will start from previous studies on CE?NS and from theoretical considerations regarding the process, then quantify the expected events for a hypothetical experiment and possible backgrounds through simulations aimed at optimizing the geometry of the future detector. I will also show some tests on selected detector components that will be part of a first prototype.

Grazzi, Stefano↗

The structure of plastocyanin tunes the midpoint potential by restricting axial ligation of the reduced copper ion

Blue copper proteins are models for illustrating how proteins tune metal properties. Nevertheless, the mechanisms by which the protein controls the metal site remain to be fully elucidated. A hindrance is that the closed shell Cu(I) site is inaccessible to most spectroscopic analyses. Carbon deuterium (C-D) bonds used as vibrational probes afford nonperturbative, selective characterization of the key cysteine and methionine copper ligands in both redox states. The structural integrity of Nostoc plastocyanin was perturbed by disrupting potential hydrogen bonds between loops of the cupredoxin fold via mutagenesis (S9A, N33A, N34A), variably raising the midpoint potential. The C-D vibrations show little change to suggest substantial alteration to the Cu(II) coordination in the oxidized state or in the Cu(I) interaction with the cysteine ligand. They rather indicate, along with visible and NMR spectroscopy, that the methionine ligand distinctly interacts more strongly with the Cu(I) ion, in line with the increases in midpoint potential. Here we show that the protein structure determines the redox properties by restricting the interaction between the methionine ligand and Cu(I) in the reduced state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Geometrically frustrated interactions drive structural complexity in amorphous calcium carbonate

Amorphous calcium carbonate is an important precursor for biomineralization in marine organisms. Key outstanding problems include understanding the structure of amorphous calcium carbonate and rationalizing its metastability as an amorphous phase. Here we report high-quality atomistic models of amorphous calcium carbonate generated using state-of-the-art interatomic potentials to help guide fits to X-ray total scattering data. Exploiting a recently developed inversion approach, we extract from these models the effective Ca∙∙∙Ca interaction potential governing the structure. This potential contains minima at two competing distances, corresponding to the two different ways that carbonate ions bridge Ca 2+ -ion pairs. We reveal an unexpected mapping to the Lennard-Jones–Gauss model normally studied in the context of computational soft matter. The empirical model parameters for amorphous calcium carbonate take values known to promote structural complexity. We thus show that both the complex structure and its resilience to crystallization are actually encoded in the geometrically frustrated effective interactions between Ca 2+ ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phonon spectra of a two-dimensional solid dusty plasma modified by two-dimensional periodic substrates

Here, phonon spectra of a two-dimensional (2D) solid dusty plasma modulated by 2D square and triangular periodic substrates are investigated using Langevin dynamical simulations. The commensurability ratio, i.e., the ratio of the number of particles to the number of potential well minima, is set to 1 or 2. The resulting phonon spectra show that propagation of waves is always suppressed due to the confinement of particles by the applied 2D periodic substrates. For a commensurability ratio of 1, the spectra indicate that all particles mainly oscillate at one specific frequency, corresponding to the harmonic oscillation frequency of one single particle inside one potential well. At a commensurability ratio of 2, the substrate allows two particles to sit inside the bottom of each potential well, and the resulting longitudinal and transverse spectra exhibit four branches in total. We find that the two moderate branches come from the harmonic oscillations of one single particle and two combined particles in the potential well. The other two branches correspond to the relative motion of the two-body structure in each potential well in the radial and azimuthal directions. The difference in the spectra between the square and triangular substrates is attributed to the anisotropy of the substrates and the resulting alignment directions of the two-body structure in each potential well.

36 MATERIALS SCIENCE↗

Nucleon-nucleon potentials from Δ-full chiral effective-field-theory and implications

We closely investigate NN potentials based upon the Δ-full version of chiral effective-field-theory. We find that recently constructed NN potentials of this kind, which (when applied together with three-nucleon forces) were presented as predicting accurate binding energies and radii for a range of nuclei from A = 16 to A = 132 and providing accurate equations of state for nuclear matter, yield a χ 2 /datum of 60 for the reproduction of the pp data below 100 MeV laboratory energy. This χ 2 is more than three times what the Hamada-Johnston potential of the year of 1962 achieved already some 60 years ago. We perceive this historical fact as concerning in view of the current emphasis on precision. We are able to trace the very large χ 2 as well as the apparent success of the potentials in nuclear structure to unrealistic predictions for P-wave states, in which the Δ-full next-to-next-to-leading order (NNLO) potentials are off by up to 40 times the NNLO truncation errors. In fact, we show that the worse the description of the P-wave states, the better the predictions in nuclear structure. Thus, these potentials cannot be seen as the solution to the outstanding problems in current microscopic nuclear structure physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cation and anion topotactic transformations in cobaltite thin films leading to Ruddlesden-Popper phases.

Topotactic transformations involve structural changes between related crystal structures due to a loss or gain of material while retaining a crystallographic relationship. The perovskite oxide La0.7Sr0.3CoO3 (LSCO) is an ideal system for investigating phase transformations due to its high oxygen vacancy conductivity, relatively low oxygen vacancy formation energy, and strong coupling of the magnetic and electronic properties to the oxygen stoichiometry. While the transition between cobaltite perovskite and brownmillerite (BM) phases has been widely reported, further reduction beyond the BM phase lacks systematic studies. In this paper, we study the evolution of the physical properties of LSCO thin films upon exposure to highly reducing environments. We observe the rarely reported crystalline Ruddlesden-Popper phase, which involves the loss of both oxygen anions and cobalt cations upon annealing where the cobalt is found as isolated Co ions or Co nanoparticles. First-principles calculations confirm that the concurrent loss of oxygen and cobalt ions is thermodynamically possible through an intermediary BM phase. The strong correlation of the magnetic and electronic properties to the crystal structure highlights the potential of utilizing ion migration as a basis for emerging applications such as neuromorphic computing.

Chiu, I-Ting↗

Leaching Model of Radionuclides in Metal-Organic Framework Particles

Metal-organic frameworks (MOFs) have been used to sequester radionuclides and seal them inside of porous scaffolds using postsynthetic modification procedures. Experiments show that certain Zr-MOF with different capping linkers significantly affects the radionuclide release kinetics. In this work, we developed a leaching model of radionuclides in Zr-MOF particles. The model assumes that uranyl species occupy two energetically favored sites: the metal node and the MOF pores. For a given overall concentration of uranyl species, the partitions of uranyl species at the metal nodes and within the pores are determined by their chemical potentials. The model also considers the effect of particle surface and concentration on chemical potentials and diffusivity. The effects of spatial and structural dependent chemical potentials and diffusivity as well as particle sizes on leaching kinetics are investigated with the model. Predicted and measured uranyl leaching kinetics in Zr-MOF particles under batch experiments are compared. The results demonstrate the model’s capability for exploring the mechanisms of leaching and provide guidance for material design.

Metal-Organic Framework, Diffusion, uranyl, Leachi↗

The significant impact of aerosol vertical structure on lower atmosphere stability and its critical role in aerosol–planetary boundary layer (PBL) interactions

The aerosol–planetary boundary layer (PBL) interaction was proposed as an important mechanism to stabilize the atmosphere and exacerbate surface air pollution. Despite the tremendous progress made in understanding this process, its magnitude and significance still have large uncertainties and vary largely with aerosol distribution and meteorological conditions. In this study, we focus on the role of aerosol vertical distribution in thermodynamic stability and PBL development by jointly using micropulse lidar, sun photometer, and radiosonde measurements taken in Beijing. Despite the complexity of aerosol vertical distributions, cloud-free aerosol structures can be largely classified into three types: well-mixed, decreasing with height, and inverse structures. The aerosol–PBL relationship and diurnal cycles of the PBL height and PM 2.5 associated with these different aerosol vertical structures show distinct characteristics. The vertical distribution of aerosol radiative forcing differs drastically among the three types, with strong heating in the lower, middle, and upper PBL, respectively. Such a discrepancy in the heating rate affects the atmospheric buoyancy and stability differently in the three distinct aerosol structures. Absorbing aerosols have a weaker effect of stabilizing the lower atmosphere under the decreasing structure than under the inverse structure. As a result, the aerosol–PBL interaction can be strengthened by the inverse aerosol structure and can be potentially neutralized by the decreasing structure. Moreover, aerosols can both enhance and suppress PBL stability, leading to both positive and negative feedback loops. This study attempts to improve our understanding of the aerosol–PBL interaction, showing the importance of the observational constraint of aerosol vertical distribution for simulating this interaction and consequent feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Integrating machine learning interatomic potentials with hybrid reverse Monte Carlo structure refinements in RMCProfile

Structure refinement with reverse Monte Carlo (RMC) is a powerful tool for interpreting experimental diffraction data. To ensure that the under-constrained RMC algorithm yields reasonable results, the hybrid RMC approach applies interatomic potentials to obtain solutions that are both physically sensible and in agreement with experiment. To expand the range of materials that can be studied with hybrid RMC, we have implemented a new interatomic potential constraint in RMCProfile that grants flexibility to apply potentials supported by the Large-scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ) molecular dynamics code. This includes machine learning interatomic potentials, which provide a pathway to applying hybrid RMC to materials without currently available interatomic potentials. To this end, we present a methodology to use RMC to train machine learning interatomic potentials for hybrid RMC applications.

Cuillier, Paul↗

Crystal Prediction and Design of Tunable Light Emission in BTB–Based Metal–Organic Frameworks

Metal-organic frameworks (MOFs) have recently been shown to exhibit unique mechanisms of luminescence based on charge transfer between structural units in the framework. These MOFs have the potential to be structural tuned for targeted emission with little or no metal participation. Here a computationally led, material design and synthesis methodology is presented that elucidates the mechanisms of light emission in interpenetrated structures comprised of metal centers (M = In, Ga, InGa, InEu) and BTB (1,3,5-Tris(4-carboxyphenyl)benzene) linkers, forming unique luminescent M-BTB MOF frameworks. Gas phase and periodic electronic structure calculations indicate that the intensity of the emission and the wavelength are overwhelmingly controlled by a combination of the number of interacting stacked linkers and their interatomic spacings, respectively. In the MOF, the ionic radii of the metal centers primarily control the expansion or shrinkage of the linker stacking distances. Experimentally, multiple M-BTB-based MOFs are synthesized and their photoluminescence was tested. Experiments validated the modeling by confirming that shifts in the crystal structure result in variations in light emission. Through this material design method, the mechanisms of tuning luminescence properties in interpenetrated M-BTB MOFs have been identified and applied to the design of MOFs with specific wavelength emission based on their structure.

36 MATERIALS SCIENCE↗

Deep neural operators can predict the real-time response of floating offshore structures under irregular waves

The use of neural operators in a digital twin model of an offshore floating structure holds the potential for a significant shift in the prediction of structural responses and health monitoring, offering valuable real-time control insights. In this work, we investigate the effectiveness of three neural operators, namely the deep operator network (DeepONet), the Fourier neural operator (FNO), and the Wavelet neural operator (WNO), to accurately capture the responses of a floating structure under six different sea state codes (3 − 8) based on the wave characteristics described by the World Meteorological Organization (WMO). To further enhance the accuracy of the vanilla architecture of the neural operators, novel extensions, such as wavelet-DeepONet and self-adaptive WNO, are proposed in this paper. The results demonstrate that these high-precision neural operators can deliver structural responses more efficiently, up to two orders of magnitude faster than a dynamic analysis using conventional numerical solvers. Additionally, compared to gated recurrent units (GRUs), a commonly used recurrent neural network for time-series estimation, neural operators are both more accurate and efficient, especially in situations with limited data availability. Taken together, our study shows that FNO outperforms all other operators for approximating the mapping of one input functional space to the output space as well as for responses that have small bandwidth of the frequency spectrum. Conversely, DeepONet, with historical states, proves most accurate in learning the mapping of multiple input functions to the output space and capturing responses within a broad frequency spectrum.

97 MATHEMATICS AND COMPUTING↗

Evaluation of Composite Structural Materials for Heliostat Cost Reduction

Structures manufactured from steel comprise up to 40% of a CSP heliostat's cost. Composite structures represent a potential opportunity to reduce this cost. A reference heliostat structural model has been created with a reflector area of 25m 2 . The design, constructed of low-carbon steel, pro-vides baseline deflection and stiffness under a 21 m/s operating wind speeds. Wind loads on the tracker structure are determined for both operating and stow conditions. An established roster of suitable metal alternative materials is considered including: glass, basalt, and carbon reinforced polymer (GFRP, BFRP, and CFRP respectively). Three heliostat components are investigated: the pylon, torque tube, and the purlin-strut assembly. Composite material properties are substituted for those of steel, and the beams are re-sized to match the original steel components' deflection under given wind loads. Weight and cost changes resulting from this resizing are evaluated. It is found that GFRP and BFRP represent a 3X–6X cost premium for the same operating deflection character-istics as steel across all three investigated component classes; with weight reduction only achieved for the purlin-strut assembly. While CFRP components can achieve approximately 25–75% weight savings depending on the application, this comes with a 9X–14X cost increase over the steel base-line for tube-type structures and roughly 5X cost increase when replacing c-channel structures. This work does not rule out the possibility of cost savings when the heliostat design and kinematics to take advantage of composites' specific properties.

14 SOLAR ENERGY↗

Excited Rydberg states in MoSe 2 /WSe 2 heterostructures

The functional form of Coulomb interactions in the transition metal dichalcogenides (TDMs) and other van der Waals solids is critical to many of their unique properties, e.g. strongly-correlated electron states, superconductivity and emergent ferromagnetism. This paper presents measurements of key excitonic energy levels in MoSe 2 /WSe 2 heterostructures. These measurements are obtained from resonance Raman experiments on specific Raman peaks only observed at excited states of the excitons. This data is used to validate a model of the Coulomb potential in these structures which predicts the exciton energies to within ~5 meV. This model is used to determine the effect of heterostructure formation on the single-particle band gaps of the layers and will have a wide applicability in designing the next generation of more complex TDM structures.

Materials Science↗

Genomic patterns of structural variation among diverse genotypes of Sorghum bicolor and a potential role for deletions in local adaptation

Genomic structural mutations, especially deletions, are an important source of variation in many species and can play key roles in phenotypic diversification and evolution. Previous work in many plant species has identified multiple instances of structural variations (SVs) occurring in or near genes related to stress response and disease resistance, suggesting a possible role for SVs in local adaptation. Sorghum [Sorghum bicolor (L.) Moench] is one of the most widely grown cereal crops in the world. It has been adapted to an array of different climates as well as bred for multiple purposes, resulting in a striking phenotypic diversity. In this study, we identified genome-wide SVs in the Biomass Association Panel, a collection of 347 diverse sorghum genotypes collected from multiple countries and continents. Using Illumina-based, short-read whole-genome resequencing data from every genotype, we found a total of 24,648 SVs, including 22,359 deletions. The global site frequency spectrum of deletions and other types of SVs fit a model of neutral evolution, suggesting that the majority of these mutations were not under any types of selection. Clustering results based on single nucleotide polymorphisms separated the genotypes into eight clusters which largely corresponded with geographic origins, with many of the large deletions we uncovered being unique to a single cluster. Even though most deletions appeared to be neutral, a handful of cluster-specific deletions were found in genes related to biotic and abiotic stress responses, supporting the possibility that at least some of these deletions contribute to local adaptation in sorghum.

59 BASIC BIOLOGICAL SCIENCES↗

The potential of quantum annealing for rapid solution structure identification

Abstract The recent emergence of novel computational devices, such as quantum computers, coherent Ising machines, and digital annealers presents new opportunities for hardware-accelerated hybrid optimization algorithms. Unfortunately, demonstrations of unquestionable performance gains leveraging novel hardware platforms have faced significant obstacles. One key challenge is understanding the algorithmic properties that distinguish such devices from established optimization approaches. Through the careful design of contrived optimization tasks, this work provides new insights into the computation properties of quantum annealing and suggests that this model has the potential to quickly identify the structure of high-quality solutions. A meticulous comparison to a variety of algorithms spanning both complete and local search suggests that quantum annealing’s performance on the proposed optimization tasks is distinct. This result provides new insights into the time scales and types of optimization problems where quantum annealing has the potential to provide notable performance gains over established optimization algorithms and suggests the development of hybrid algorithms that combine the best features of quantum annealing and state-of-the-art classical approaches.

97 MATHEMATICS AND COMPUTING↗

CASTELO: clustered atom subtypes aided lead optimization—a combined machine learning and molecular modeling method

Background: Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots. Results: The initial data collection is achieved with physics-based molecular dynamics simulation. Contact matrices are calculated as the preliminary features extracted from the simulations. To take advantage of the temporal information from the simulations, we enhanced contact matrices data with temporal dynamism representation, which are then modeled with unsupervised convolutional variational autoencoder (CVAE). Finally, conventional and CVAE-based clustering methods are compared with metrics to rank the submolecular structures and propose potential candidates for lead optimization. Conclusion: With no need for extensive structure-activity data, our method provides new hints for drug modification hotspots which can be used to improve drug potency and reduce the lead optimization time. It can potentially become a valuable tool for medicinal chemists.

59 BASIC BIOLOGICAL SCIENCES↗

Bicontinuous nanoporous design induced homogenization of strain localization in metallic glasses

Bicontinuous nanoporous metallic glasses (MG) synergize the outstanding properties of MGs and open-cell nanoporous materials. The low-density and high-specific-surface-area of bicontinuous nanoporous structures have the potential to enhance the applicability of MGs in catalysis, sensors, and lightweight structural designs. In this work, we report molecular dynamics simulations of tensile loading deformation and failure of bicontinuous nanoporous Cu 64 Zr 36 MG with 55% porosity and 4.4 nm ligament size. Results indicate an anomalous mechanical behavior featuring delocalized plastic deformation preceding ductile failure. The deformation follows two mechanisms: i) Necking of ligaments aligned with the loading direction and ii) progressive alignment of randomly oriented ligaments. Failure occurs at 0.16 strain, following massive rupture of ligaments. This work indicates that a bicontinuous nanoporous design is able to effectively delocalize strain localization in a MG due to a combination of size effect on the ductility of MGs resulting in nano ligaments necking and progressive asynchronous alignment of ligaments.

36 MATERIALS SCIENCE↗