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At least 55 records · Page 3

Enhancing Thermal Transport in Polymeric Composites Via Engineered Noncovalent Filler–Polymer Interactions

Understanding thermal transport mechanisms in polymeric composites allows us to expand the boundaries of thermal conductivity in them, either increasing it for more efficient heat dissipation or decreasing it for better thermal insulation. But, these mechanisms are not fully understood. Systematic experimental investigations remain limited. Practical strategies to tune the interfacial thermal resistance (ITR) between fillers and polymers and the thermal conductivity of composites remain elusive. Here, we studied the thermal transport in representative polymer composites, using polyethylene (PE) or polyaniline (PANI) as matrices and graphite as fillers. PANI, with aromatic rings in its backbone, interacts with graphite through strong noncovalent π–π stacking interactions, whereas PE lacks such interactions. We can then quantify how π–π stacking interactions between graphite and polymers enhance thermal transport in composites. PE/graphite and PANI/graphite composites with the same 1.5% filler volume fractions show a ∼22.82% and ∼34.85% enhancement in thermal conductivity compared to pure polymers, respectively. Calculated ITRs in PE/graphite and PANI/graphite are ~6 x 10 -8 m 2 KW -1 and ~1 x 10 -8 m 2 KW -1 , respectively, highlighting how π–π stacking interactions reduce ITR. Molecular dynamics (MD) simulations suggest that π–π stacking interactions between PANI chains and graphite surfaces enhance alignment of PANI's aromatic rings with graphite surfaces. This allows more carbon atoms from PANI chains to interact with graphite surfaces at a shorter distance compared to PE chains. Finally, our work indicates that tuning the π–π stacking interactions between polymers and fillers is an effective approach to reduce the ITR and enhance the thermal conductivity of composites.

atoms

Quantitative stable isotope probing (qSIP) and cross-domain networks reveal bacterial-fungal interactions in the hyphosphere

Interactions between fungi and bacteria have the potential to substantially influence soil carbon dynamics in soil, but we have yet to fully identify these interactions and partners in their natural environment. In this study, we stacked two powerful methods, 13 C quantitative stable isotope probing (qSIP) and cross-domain co-occurrence network, to identify interacting fungi and bacteria in a California grassland soil. We used in-field whole plant 13 CO 2 labeling along with sand-filled ingrowth bags (that trap fungi and hyphae-associated bacteria) to amplify the signal of fungal-bacterial interactions, separate from the bulk soil background. We found a total of 54 bacterial ASVs and 9 fungal OTUs that were significantly 13 C-enriched. These were saprotrophic and biotrophic fungi, and motile, sometimes predatory bacteria. Among these, 70% of all 13 C-enriched bacteria identified were motile. Notably, we detected fungal-bacterial network links between a fungal OTU of the genus Alternaria and several bacterial ASVs of the genera Bacteriovorax, Mucilaginibacter, and Flavobacterium, providing empirical evidence of their direct interactions through C exchange. We observed a strong positive co-occurrence pattern between predatory bacteria of the phylum Bdellovibrionota and fungal OTUs, suggesting the transfer of C across the soil food web. To date, our ability to associate microbial co-occurrence network patterns with biological interactions is limited, but the incorporation of qSIP allowed us to more precisely detect interacting partners by narrowing in on the taxa that were actively incorporating plant-fixed, fungal-transported labeled substrates. Together, these approaches can help build a mechanistic understanding of the complex nature of fungal-bacterial interactions in soil.

59 BASIC BIOLOGICAL SCIENCES

Investigating Electro-Nuclear Interactions in a New Dark Matter Search

Electro-nuclear (EN) interactions are interactions in which an incident electron collides with a nucleus, scattering the electron and creating byproduct particles. Such interactions are of interest to neutrino physicists, who use EN interactions to inform model building of neutrino-nucleus interactions. The Light Dark Matter Experiment (LDMX) is a small-scale, fixed-target, electron beam experiment which seeks to probe for dark matter and mediator particle production in the sub-GeV mass region. The 8GeV LDMX electron beam will serve as an opportunity to study electro-nuclear interactions in their final states in the multi-GeV region. LDMX’s missing energy trigger however, will not be sufficient to efficiently capture EN interactions. An additional trigger needs to be created. Using simulated background events, including EN interactions, for the LDMX experiment, a trigger on momentum was developed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Neutrino-Argon Cross Sections in MicroBooNE: Measurements Spanning Multiple Interaction Channels, Final States, and Neutrino Fluxes

Neutrinos are one of the most elusive particles in the Standard Model of particle physics due to their tiny interaction cross section, which makes them challenging to detect and study. There are three known flavors of neutrinos, and any given neutrino probabilistically oscillates between them as a function of the particle's energy and propagation distance. Experimental characterization of these oscillations elucidates fundamental properties of the neutrino and the Standard Model. Meeting the precision goals of ongoing and future oscillation measurements requires detailed modeling of the way neutrinos interact with nuclear matter. Precision modeling of these interactions is a challenging theoretical problem, rich with intricate physics effects to explore, and requires input from equally precise measurements of neutrino-nucleus interaction cross sections spanning a broad range of scattering channels. To fill this need, there is an ongoing multi-experiment effort to measure these cross sections across energies, interaction channels, and nuclear targets. This thesis describes three analyses reporting neutrino-argon cross section measurements with data from the MicroBooNE liquid argon time projection chamber detector. These span multiple interaction channels, final state topologies, and neutrino fluxes. The first analysis is a set of inclusive charged current muon neutrino cross section measurements for final states with and without protons, which provides a unique view of the hadronic final state produced in these interactions. Second is a set of cross section measurements for neutral current neutral pion production, which provides a vital dataset on this under-characterized channel. Third is significant progress on measuring neutrinos produced by kaons decaying at rest, which represents a unique opportunity to measure cross sections with a mono-energetic flux of neutrinos. These measurements are accompanied by a modeling study in the GiBUU theory framework, which probes the sensitivity of the muon neutrino and pion production measurements to the modeling of nucleon-nucleon final state interactions in neutrino-nucleus scattering.

Bogart, Benjamin [Michigan U.]

Effect of tert -Butyl Substitution on the Interactions of Cobalt Phthalocyanine with a Carbon Monoxide-Functionalized Tip

Supported cobalt phthalocyanines (CoPc) are promising catalysts for CO 2 reduction, a critical process for mitigating greenhouse gas emissions. Enhancing the catalytic performance of CoPc involves modifying the interaction between the cobalt center and intermediate species. This study focuses on the effects of tert-butyl substitution on CoPc using (tert-butyl) 4 CoPc, where the substitution can both directly alter the molecule’s intramolecular electronic structure and indirectly alter it by the bulky group weakening the interaction with the support. Toward this end, we investigated the structural and chemical properties of (tert-butyl) 4 CoPc on a Ag(111) surface at the single-molecule level using three-dimensional atomic force microscopy (AFM) with a CO-terminated tip and discussed them in comparison with data for unmodified CoPc and amino-substituted CoPc. Notably, distance-dependent force measurements revealed anomalies in the tert-butyl groups’ force curves, attributed to their rotational flexibility. The tert-butyl (t-butyl) groups were also observed to increase the attraction of the central Co atom to CO, but this effect was attributed largely to enhanced interactions of the back of the tip with the peripheral t-butyl groups. In conclusion, while this longer-range interaction would not be expected to impact the interaction of small molecules with the catalytic center, the results reveal the ability of AFM to characterize longer range environmental interactions that can enhance adsorption and subsequent reactions of larger molecules, as well as the role side chains that offer configurational adaptability may play in these interactions.

77 NANOSCIENCE AND NANOTECHNOLOGY

Accounting for linkages between wildfire-driven shifts in plant-microbial interactions and soil carbon dynamics in Arctic tundra

Increasing wildfire regimes in the rapidly changing Arctic tundra are altering the soil carbon budget through increased permafrost degradation, shrubs expansion, and shifts in microbial activities. Whether future arctic wildfires will result in net C losses or gains in the future will depend on complex biotic and abiotic interactions that regulate belowground C biogeochemical processes, including linkages among biotic communities. One important linkage is plant-microbe interactions. While these interactions are likely shaped or altered by wildfires, they remain little explored in the context of successional trajectories. Yet, incorporating plant-microbe interactions in frameworks for defining and understanding post-fire soil C trajectories is critical to predict belowground C responses to future tundra wildfires. Here, we provide examples of and discuss how fire-mediated changes in plant-soil-microbe (PSM) interactions can impact soil C dynamics in the Arctic tundra. We consider different impacts of wildfires on PSM interactions and their implications to soil C dynamics, as well as the nuances associated with particular wildfire regimes (severity and intensity) and successional timescales. We suggest that accounting for plant-microbial linkages in future wildfire-succession interactions frameworks can inform future experimental designs and reduce uncertainties in our ability to predict the net effect of Arctic wildfires on ecosystem C.

fungi, bacteria

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge

Understanding the interactions and regulatory relationships among biomolecules is essential for deciphering complex biological systems and elucidating the mechanisms behind diverse biological functions. Traditionally, the collection of such molecular interaction data has relied on expert curation, a process that is both time-consuming and labor-intensive. To address these limitations, this study explores the use of large language models (LLMs) to automate the genome-scale extraction of molecular interaction knowledge. Here, we evaluate the performance of various LLMs on key biological tasks, including the identification of protein-protein interactions, detection of genes associated with pathways influenced by low-dose radiation, and inference of gene regulatory relationships. Our findings demonstrate that larger LLMs tend to perform better, particularly in extracting intricate gene and protein interactions. Despite their strengths, these models face challenges in recognizing functionally diverse gene groups and highly correlated regulatory relationships. Through a comprehensive analysis using established molecular interaction and pathway databases, we show that LLMs possess the potential to identify relevant biomolecules and predict their interactions, offering valuable insights and marking a significant step toward AI-driven biological knowledge discovery.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN

Anisotropic light-tailored RKKY interaction in two-dimensional 𝑑-wave altermagnets

Altermagnets are known in spintronics for their intrinsic spin-splitting and unconventional magnetic responses, particularly to magnetic impurities. However, effectively controlling the magnetic exchange interactions in altermagnets is challenging for practical applications. Here, in this work, we propose using circularly polarized light to tune the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction in two-dimensional 𝑑-wave altermagnets. Using the real-space retarded Green's functions approach, our results show that while the Heisenberg and Ising exchanges dominate, a notable Dzyaloshinskii–Moriya (DM) interaction also plays a key role. Furthermore, the inherent strength of altermagnetism imprints chirp-like signatures into the magnetic responses, which can be dynamically tuned via light. We mainly demonstrate that gate-induced Rashba spin-orbit coupling is essential in response to light—light selectively and anisotropically adjusts the DM interaction without affecting the other exchanges. Our findings further indicate that rotating the altermagnet by 45° relative to the light's polarization direction generates a Dirac-like dispersion and different DM interactions. We finally extract critical thresholds where light reverses DM interactions along one axis or balances both in-plane components. The anisotropic light-driven control of RKKY interactions in altermagnets not only highlights their unique properties but also opens new avenues for engineering tailored magnetic characteristics in spintronic applications.

altermagnetism

Selective enhancement of Coulomb interactions in planar Weyl fermions

We report on our study of the electron interaction effects in topological two-dimensional (2D) materials placed in a quantizing magnetic field. Taking our cue from a recent experimental report, we consider a particular case of bismuthene monolayer with a strong spin-orbit interaction which can be a Weyl semimetal when placed on a specially tuned substrate. Interestingly, we observe that in some Landau levels of this material, the interaction effects are enhanced compared to those for a conventional 2D system and graphene monolayer. Such an enhancement of electron-electron interactions in these materials is largely due to an anisotropy present in the materials. Additionally, the interaction effects can be tuned by changing the coupling to the substrate and the strongest inter-electron interactions are observed when the system is a Weyl semimetal. Furthermore, the observed enhancement of the interaction effects can therefore be an important signature of the 2D Weyl fermions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Probing interspecies metabolic interactions within a synthetic binary microbiome using genome-scale modeling

Metabolic interactions within a microbial community play a key role in determining the structure, function, and composition of the community. However, due to the complexity and intractability of natural microbiomes, limited knowledge is available on interspecies interactions within a community. In this work, using a binary synthetic microbiome, a methanotroph-photoautotroph (M-P) coculture, as the model system, we examined different genome-scale metabolic modeling (GEM) approaches to gain a better understanding of the metabolic interactions within the coculture, how they contribute to the enhanced growth observed in the coculture, and how they evolve over time. Using batch growth data of the model M-P coculture, we compared three GEM approaches for microbial communities. Two of the methods are existing approaches: SteadyCom, a steady state GEM, and dynamic flux balance analysis (DFBA) Lab, a dynamic GEM. We also proposed an improved dynamic GEM approach, DynamiCom, for the M-P coculture. SteadyCom can predict the metabolic interactions within the coculture but not their dynamic evolutions; DFBA Lab can predict the dynamics of the coculture but cannot identify interspecies interactions. DynamiCom was able to identify the cross-fed metabolite within the coculture, as well as predict the evolution of the interspecies interactions over time. A new dynamic GEM approach, DynamiCom, was developed for a model M-P coculture. Constrained by the predictions from a validated kinetic model, DynamiCom consistently predicted the top metabolites being exchanged in the M-P coculture, as well as the establishment of the mutualistic N-exchange between the methanotroph and cyanobacteria. The interspecies interactions and their dynamic evolution predicted by DynamiCom are supported by ample evidence in the literature on methanotroph, cyanobacteria, and other cyanobacteria-heterotroph cocultures.

59 BASIC BIOLOGICAL SCIENCES

dynamics of organic-mineral interactions at the metal oxide-solution interface as studied via binding energetics (Final report)

This project focused on addressing longstanding fundamental and experimental uncertainties on how dissolved organic substances (DOS) interact with metal oxide surface under environmentally relevant conditions. By leveraging a custom-built real-time, in-tandem flow adsorption microcalorimetry-UV-Vis/fluorescence spectroscopy platform, we characterized the binding energetics, kinetics and mechanistic pathways driving DOS-metal oxide interactions at temporal resolution on the order of 1-5 seconds. We studied a diverse suite of model organic compounds/substances – including monocarboxylates (e.g. acetate and benzoate), di-carboxylates (oxalate and succinate), amino acids, amino-based nanparticles and natural organic matter – interacting at the mineral-water interface of structurally- and/or chemically distinct metal oxides (including SiO2, boehmite, ferrihydrite, and γ-Al2O3). Our results indicated that DOS-metal oxide interactions are governed by multi-step reaction pathways, often switching between distinct, resolvable enthalpy- and entropy-driven non-electrostatic or electrostatic configurations. To quantify these interactions, we developed and implemented an analytical workflow that integrates peak deconvolution and Monte-Carlo based error propagation to determine site-specific thermodynamic and kinetic parameters for individual binding/debinding events. In addition to resolving apparent first-order rate constants of each event, we were able to quantify associated apparent equilibrium constants as well as free energy, enthalpy and entropy contribution to the activation and subsequent progression of the binding/debinding process across compounds, compound class and metal oxide surfaces. The kinetic-thermodynamic data produced in this study captured how the interplay between oxide surface reactivity and DOS molecular structure jointly drives binding-debinding dynamics. Notably, that at pH below PZC of the oxide surface, neutral species were heavily involved in monocarboxylate binding, while anionic species drove dicarboxylate binding. Also, that among amino acids 1) positional isomers show distinctive binding characteristics to each other while enantiomers show no significant differences in binding characteristics, 2) molecules that bind via outer-sphere complexation show a larger entropic shift between binding and debinding with no impact on oxide surface while 3) inner-sphere interactions increased anion exchange capacity of the oxide surface. The new insights and data from this work has great potential for improving predictive modeling of carbon dynamics and specifically organic-mineral interactions in environmental and industrial systems.

54 ENVIRONMENTAL SCIENCES

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Interactions involved in the adsorption of ethylene glycol and 2-hydroxyethoxide on the Au(111) surface: a Density Functional Theory study

Abstract Context:The monolayers of ethylene glycol and 2-hydroxyethoxide on gold surfaces have been used in hybrid materials as biosensors. In this article, the adsorption of ethylene glycol and 2-hydroxyethoxide on the Au(111) surface was analyzed. For the first system, ethylene glycol on Au(111), there are Au$$\cdot \cdot \cdot $$ · · · O and Au$$\cdot \cdot \cdot $$ · · · H interactions. To the best of our knowledge, the Au$$\cdot \cdot \cdot $$ · · · H interaction has been overlooked until now. However, in this work, there is strong evidence that this interaction is important to stabilize the system. For the second system, the atomic interactions mentioned previously are also predicted, although there is an additional interaction between 2-hydroxyethoxide molecules. Such an interaction induces the link -O-H-O-, with high values of the electron density at the critical points of the corresponding bond path of the O-H interaction. These links suggest the forming of ethylene glycol chains.Methods:The calculations were performed using two exchange-correlation functionals: BEEF-vdW and C09$$_{x}$$ x -vdW; both functionals incorporate dispersion effects within the Kohn-Sham approach in Density Functional Theory as implemented in GPAW code and ASE computational packages. The contacts between the molecules considered in this article and the Au(111) surface were analyzed through the Quantum Theory of Atoms in Molecules implemented in GPUAM code.

Biochemistry & Molecular Biology

Substituent and Heteroatom Effects on π–π Interactions: Evidence That Parallel-Displaced π-Stacking is Not Driven by Quadrupolar Electrostatics

Stacking interactions are a recurring motif in supramolecular chemistry and biochemistry, where a persistent theme is a preference for parallel-displaced aromatic rings rather than face-to-face π-stacking. This is usually explained in terms of quadrupole–quadrupole interactions between the arene moieties but that interpretation is inconsistent with accurate calculations, which reveal that the quadrupolar picture is qualitatively wrong. At typical π-stacking distances, quadrupolar electrostatics may differ in sign from an exact calculation based on charge densities of the interacting arenes. We apply symmetry-adapted perturbation theory to dimers composed of substituted benzene and various aromatic heterocycles, which display a wide range of electrostatic interactions, and we investigate the interplay of Pauli repulsion, dispersion, and electrostatics as it pertains to parallel-displaced π-stacking. Profiles of energy components along cofacial slip-stacking coordinates support a prominent role for the “van der Waals model” (dispersion in competition with Pauli repulsion), even for polar monomers where electrostatic interactions are significant. While electrostatic interactions are necessary to explain the optimal face-to-face π-stacking distance and to account for the relative orientation of one polar arene with respect to another, we find no evidence to support continued invocation of quadrupolar electrostatics as a basis for π-stacking. Our results suggest that a driving force for offset-stacking exists even in the absence of electrostatic interactions. Consequently, tuning electrostatics via functionalization does not guarantee that slip-stacking can be avoided. This has implications for rational design of soft materials and other supramolecular architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Magnon-mediated exciton–exciton interaction in a van der Waals antiferromagnet

Excitons are fundamental excitations that govern the optical properties of semiconductors. Interactions between excitons can lead to various emergent phases of matter and large nonlinear optical responses. In most semiconductors, excitons interact via exchange interactions or phase-space filling. Correlated materials that host excitons coupled to other degrees of freedom could offer pathways for controlling these interactions. Here, in this study, we demonstrate magnon-mediated interactions between excitons in CrSBr, an antiferromagnetic semiconductor. These interactions manifest as the dependence of the exciton energy on the exciton density via a magnonic adjustment of the spin canting angle. Our study demonstrates the emergence of quasiparticle-mediated interactions in correlated quantum materials, leading to large nonlinear optical responses and potential device concepts such as magnon-mediated quantum transducers.

36 MATERIALS SCIENCE

A real-time search for Type Ia Supernovae with late-time interactions with circumstellar material in ZTF data

While it is generally accepted that Type Ia supernovae (SNe Ia) are the terminal explosions of white dwarfs (WDs), the nature of their progenitor systems and the mechanisms that lead up to these explosions remain widely debated. In rare cases, the SN ejecta interact with circumstellar material (CSM) that had previously been ejected from the progenitor system. The longer the delay between the creation of the CSM and the SN explosion, the greater the distance between the SN explosion site and the CSM and the later the onset of the interaction. The unknown distance between the CSM and SN explosion site makes it impossible to predict when the interaction will start. If the time between the SN explosion and the onset of the CSM interaction is of the order of several months to years, the SN has generally faded and it is no longer actively followed up on. This makes it even more difficult to detect the interaction while it is happening. In this work, we report on a real-time monitoring programme running between 13 November 2023 and 9 July 2024. It monitored 6914 SNe Ia for signs of late-time rebrightening using the Zwicky Transient Facility (ZTF). Flagged candidates were rapidly followed up on with photometry and spectroscopy to confirm the late-time excess and its position. We report the discovery of a ∼50 day rebrightening event in SN 2020qxz around 1200 rest-frame days after the peak of its light curve. SN 2020qxz exhibited signs of an early CSM interaction, but had faded from view over two years before its reappearance. Initial follow-up spectroscopy revealed the presence of four emission lines, while later follow-up spectroscopy showed that these had faded shortly after the end of the ZTF-detected rebrightening event. Our best match for these emission lines are H β (blueshifted by ∼5900 km s −1 ) and Ca II λ8542 , N I λ8567 , and K I λλ8763, 8767 (all blueshifted by 5100 km s −1 ; although we note that the line identifications are uncertain). This shows that catching and following up on late-time interactions as they occur can offer new clues on the nature of the progenitor systems that produce these SNe by putting constraints on the possible type of donor star. The only way to do this systematically is to use large sky surveys such as ZTF and the upcoming Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) to monitor a large sample of objects for the rare events that reappear long after the object has faded from view.

circumstellar matter

Non-Gaussianity from explicit U(1)-breaking interactions

We investigate primordial non-Gaussianity (NG) arising from the explicit U(1) symmetry-breaking interactions during inflation involving a nearly massless axial component of a complex scalar field P. We analyze the induced NG parameter f NL under scenarios where the axial field functions as either a curvaton or cold dark matter (CDM). In the curvaton framework, there is a conventional contribution to the local NG of f NL ≃ -O(1). Additional positive local NG can result from either the self-interactions of axial field fluctuations, their interactions with a light radial partner, or kinetic mixing with the inflaton via U(1) symmetry-breaking terms. We identify parameter regions where the interactions lead to cancellations, suppressing the overall local NG to |f loc NL | ≲ O(0.1). In the CDM scenario, these interactions enhance the NG in the isocurvature fluctuations. Moreover, interactions between the axial field and another light scalar, such as a curvaton, can generate O(1) curvature NG signals and significant mixed curvature-isocurvature NGs that are within the reach of future experiments with σ(f loc NL ) ∼ 1. We also explore the role of a heavy radial field in generating oscillating correlation signals, noting that such signals can dominate the shape of the mixed adiabatic-isocurvature bispectrum. In certain cases, an oscillatory isocurvature bispectrum signal may be observable in the future, aiding in distinguishing between certain types of the U(1)-breaking self-interactions of the axial field.

axions

Probing scalar non-standard interaction of supernova neutrinos in next-generation neutrino experiments

A new neutrino-matter interaction can potentially affect neutrino propagation through matter. In this work, we explore the impact of a flavor-conserving scalar-mediated non-standard neutrino interaction in the supernova neutrino flux. We observe that the presence of a scalar interaction involving muon and tau neutrinos (parameterized as η μμ and η ττ , respectively) can invert the neutrino mass eigenstate in which three neutrino flavor states are produced inside the supernova core, resulting in a significant modification of the electron neutrino flux from the supernova reaching the Earth. In the context of the DUNE experiment, we estimate the number of supernova neutrino events in the presence of scalar non-standard neutrino interaction η μμ or η ττ and contrast with the case without scalar-mediated non-standard interactions. Our results indicate that such scalar interactions introduce a new degeneracy in the measurement of neutrino mass ordering from supernova neutrinos. We show how the ν̅e event distribution in Hyper-Kamiokande experiment may help resolve the degeneracy between a model with new scalar interactions for normal ordered neutrino masses and the standard model with inverted mass ordering for a galactic supernova.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS