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At least 631 records · Page 35

SISGR: Chemomechanics of Far-From-Equilibrium Interfaces (COFFEI)

Portable, reliable, and deployable devices for energy storage and conversion require fundamental changes in design of solid-state composites comprising ceramics and metals. These materials comprise the electrodes and electrolytes of next-generation solid-oxide fuel cells and all solid-state batteries, forming solid-state functional composites. The advent of solid-state batteries – which replace liquid electrolytes with solid electrolytes capable of lithium ion transport for reliable energy storage in portable batteries – and the increased demand space for all solid-state fuel cells capable of oxygen reduction at intermediate temperatures remain important challenges for improved material stability and decreased system cost. However, little is understood about three fundamental facets of materials that enable such solid-state energy applications. First, how do such materials deform, fracture, or delaminate under operando conditions? Second, how does such mechanical deformation limit or facilitate electronic and ionic transport within and across such material interfaces? Third, how we can predictably design interface-rich composites to engineer both structural and electrochemical stability? This COFFEI Group comprised expertise from Materials Science & Engineering and Nuclear Science & Engineering to integrate unique in situ experiments, simulations, and fabricated interfaces that address these fundamental questions in solid-state interfaces of nanoscale composites that will guide solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric materials that enable such applications. In particular, we built on COFFEI’s understanding of chemomechanical coupling among defect concentrations, ionic transport, electron transport, and stored elastic energy that is particularly acute in the far-from-equilibrium conditions typical of energy device applications. By tailoring our focus to solid-state interfaces, we addressed these important issues by (a) developing and applying advanced in situ and ex situ characterization tools to characterize model materials and interfaces synthesized with molecular-level control, under both laboratory-controlled and extreme environments representative of energy device operation; and (b) employing computational modeling and simulation frameworks to predict transport mechanisms, reactivity and stability of these model materials and interfaces under significant chemical strains typical of energy device operation. Recent progress provided insights to additional materials systems and electrochemomechanical fatigue and fracture that were not fully envisioned when the program was initiated. Specifically, in the final three years of COFFEI we pursued two integrated thrusts, with complementary focus. Thrust I focused on failure-resistant electrochemomechanical composites, while Thrust II focused on strain-modulated conductivity and reactivity across interfaces. In contrast to our initial COFFEI focus, these thrusts concentrated wholly on solid-state material interfacial interactions and included greater integration of multiscale visualization including in situ electron microscopy of strained structures/interactions and mesoscale simulations. Successful development of functionally superior and long-lived battery and fuel cell systems and stress adaptable oxides requires a deeper, fundamental understanding of the coupling among the historically important subfields of solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric metal oxide electrodes. In this program, the understanding and the application of chemomechanical coupling of defect concentrations, ionic transport, electro-catalytic activity and stored elastic energy, particularly acute in the far-from-equilibrium conditions typical of energy device applications, are being refined and implications for device operation clarified, including for miniaturized solid-state batteries and fuel cells.

36 MATERIALS SCIENCE↗

MINE: a new way to design genetics experiments for discovery

Abstract The Maximally Informative Next Experiment or MINE is a new experimental design approach for experiments, such as those in omics, in which the number of effects or parameters p greatly exceeds the number of samples n (p > n). Classical experimental design presumes n > p for inference about parameters and its application to p > n can lead to over-fitting. To overcome p > n, MINE is an ensemble method, which makes predictions about future experiments from an existing ensemble of models consistent with available data in order to select the most informative next experiment. Its advantages are in exploration of the data for new relationships with n < p and being able to integrate smaller and more tractable experiments to replace adaptively one large classic experiment as discoveries are made. Thus, using MINE is model-guided and adaptive over time in a large omics study. Here, MINE is illustrated in two distinct multiyear experiments, one involving genetic networks in Neurospora crassa and a second one involving a genome-wide association study in Sorghum bicolor as a comparison to classic experimental design in an agricultural setting.

Biochemistry & Molecular Biology↗

Study of coherent J/ ψ production in lead-lead collisions at $\sqrt{{\mathrm{s}}_{\mathrm{NN}}} $ = 5 TeV

Coherent production of J/ψ mesons is studied in ultraperipheral lead-lead collisions at a nucleon-nucleon centre-of-mass energy of 5 TeV, using a data sample collected by the LHCb experiment corresponding to an integrated luminosity of about 10 μb –1 . The J/ψ mesons are reconstructed in the dimuon final state and are required to have transverse momentum below 1 GeV. The cross-section within the rapidity range of 2.0 < y < 4.5 is measured to be 4.45 ± 0.24 ± 0.18 ± 0.58 mb, where the first uncertainty is statistical, the second systematic and the third originates from the luminosity determination. The cross-section is also measured in J/ψ rapidity intervals. The results are compared to predictions from phenomenological models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Observation of a $ {\varLambda}_b^0 $ - $ {\overline{\varLambda}}_b^0 $ production asymmetry in proton-proton collisions at $ \sqrt{s} $ = 7 and 8 TeV

This article presents differential measurements of the asymmetry between $ {\varLambda}_b^0 $ - $ {\overline{\varLambda}}_b^0 $ baryon production rates in proton-proton collisions at centre-of-mass energies of $\sqrt{s}$ = 7 and 8 TeV collected with the LHCb experiment, corresponding to an integrated luminosity of 3 fb -1 . The ${\varLambda}_b^0 $ baryons are reconstructed through the inclusive semileptonic decay ${\varLambda}_b^0 $ → Λ+c μ - $\overline{ν}$ μX. The production asymmetry is measured both in intervals of rapidity in the range 2.15 < y < 4.10 and transverse momentum in 2 < p T < 27 GeV/c. The results are found to be incompatible with symmetric production with a significance of 5.8 standard deviations for both $\sqrt{s}$ = 7 and 8 TeV data, assuming no CP violation in the decay. There is evidence for a trend as a function of rapidity with a significance of 4 standard deviations. Comparisons to predictions from hadronisation models in PYTHIA and heavy-quark recombination are provided. This result constitutes the first observation of a particle-antiparticle asymmetry in b-hadron production at LHC energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurements of W + W - + ≥ 1 jet production cross-sections in pp collisions at $ \sqrt{s} $ = 13 TeV with the ATLAS detector

Fiducial and differential cross-section measurements of W + W - production in association with at least one hadronic jet are presented. These measurements are sensitive to the properties of electroweak-boson self-interactions and provide a test of perturbative quantum chromodynamics and the electroweak theory. The analysis is performed using proton-proton collision data collected at $ \sqrt{s} $ = 13 TeV with the ATLAS experiment, corresponding to an integrated luminosity of 139 fb -1 . Events are selected with exactly one oppositely charged electron-muon pair and at least one hadronic jet with a transverse momentum of p T > 30 GeV and a pseudorapidity of |η| < 4.5. After subtracting the background contributions and correcting for detector effects, the jet-inclusive W + W - + ≥ 1 jet fiducial cross-section and W + W - + jets differential cross-sections with respect to several kinematic variables are measured. These measurements include leptonic quantities, such as the lepton transverse momenta and the transverse mass of the W + W - system, as well as jet-related observables such as the leading jet transverse momentum and the jet multiplicity. Limits on anomalous triple-gauge-boson couplings are obtained in a phase space where interference between the Standard Model amplitude and the anomalous amplitude is enhanced.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sterile neutrinos and the global reactor antineutrino dataset

We present results from global fits to the available reactor antineutrino dataset, as of Fall 2019, to determine the global preference for a fourth, sterile neutrino. We have separately considered experiments that measure the integrated inverse-beta decay (IBD) rate from those that measure the energy spectrum of IBD events at one or more locations. The evidence that we infer from rate measurements varies between ≲ 3σ and negligible depending on the reactor antineutrino flux model employed. Moreover, we find that spectral ratios ostensibly imply ≳ 3σ evidence, consistent with previous work, though these measurements are known to be plagued by issues related to statistical interpretation; these results should therefore be viewed cautiously. The software used is the newly developed GLoBESfit tool set which is based on the publicly available GLoBES framework and will be released as open-source software.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Observation of the ${B}_s^0 $ → D*±D∓ decay

A search for the B 0 → D *± D ∓ decay is performed using proton-proton collision data at centre-of-mass energies of 7, 8 and 13 TeV collected by the LHCb experiment, corresponding to an integrated luminosity of 9 fb -1 . The decay is observed with a high significance and its branching fraction relative to the B 0 → D *± D ∓ decay is measured to be $\frac{\mathrm{\mathcal{B}}\left({B}_s^0\to {D}^{\ast \pm }{D}^{\mp}\right)}{\mathrm{\mathcal{B}}\left({B}^0\to {D}^{\ast \pm }{D}^{\mp}\right)}=0.137\pm 0.017\pm 0.002\pm 0.006$, where the first uncertainty is statistical, the second systematic and the third is due to the uncertainty on the ratio of the $B_{s}^{0}$ and $B^{0}$ hadronisation fractions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Searches for rare ${B}_s^0$ and $B^0$ decays into four muons

Searches for rare ${B}_s^0$ and $B^0$ decays into four muons are performed using proton-proton collision data recorded by the LHCb experiment, corresponding to an integrated luminosity of 9 fb –1 . Direct decays and decays via light scalar and $J/ψ$ resonances are considered. No evidence for the six decays searched for is found and upper limits at the 95% confidence level on their branching fractions ranging between 1.8 x 10 –10 and 2.6 x 10 –9 are set.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Search for dark QCD with emerging jets in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search for “emerging jets” produced in proton-proton collisions at a center-of-mass energy of 13 TeV is performed using data collected by the CMS experiment corresponding to an integrated luminosity of 138 fb$^{−1}$. This search examines a hypothetical dark quantum chromodynamics (QCD) sector that couples to the standard model (SM) through a scalar mediator. The scalar mediator decays into an SM quark and a dark sector quark. As the dark sector quark showers and hadronizes, it produces long-lived dark mesons that subsequently decay into SM particles, resulting in a jet, known as an emerging jet, with multiple displaced vertices. This search looks for pair production of the scalar mediator at the LHC, which yields events with two SM jets and two emerging jets at leading order. The results are interpreted using two dark sector models with different flavor structures, and exclude mediator masses up to 1950 (1950) GeV for an unflavored (flavor-aligned) dark QCD model. The unflavored results surpass a previous search for emerging jets by setting the most stringent mediator mass exclusion limits to date, while the flavor-aligned results provide the first direct mediator mass exclusion limits to date.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for lepton-flavor-violating tau-lepton decays to ℓγ at Belle

Charged lepton flavor violation is forbidden in the Standard Model but possible in several new physics scenarios. In many of these models, the radiative decays τ ± → ℓ ± γ (ℓ = e, μ) are predicted to have a sizeable probability, making them particularly interesting channels to search at various experiments. An updated search via τ ± → ℓ ± γ using full data of the Belle experiment, corresponding to an integrated luminosity of 988 fb –1 , is reported for charged lepton flavor violation. No significant excess over background predictions from the Standard Model is observed, and the upper limits on the branching fractions, B(τ ± → μ ± γ) ≤ 4.2 × 10 –8 and B(τ ± → e ± γ) ≤ 5.6 × 10 –8 , are set at 90% confidence level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Measurement of prompt open-charm production cross sections in proton-proton collisions at $$ \sqrt{s} $$ = 13 TeV

The production cross sections for prompt open-charm mesons in proton-proton collisions at a center-of-mass energy of 13 TeV are reported. The measurement is performed using a data sample collected by the CMS experiment corresponding to an integrated luminosity of 29 nb-1. The differential production cross sections of the D *± , D ± , and D 0 $(\bar{D}^0)$ mesons are presented in ranges of transverse momentum and pseudorapidity 4 < pT < 100 GeV and |η| < 2.1, respectively. The results are compared to several theoretical calculations and to previous measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Accelerating Catalyst Development for Biofuel Production through Multiscale Catalytic Fast Pyrolysis of Biomass over Mo2C

Advanced catalytic materials play an enabling role in producing renewable fuels and chemicals from biomass, thereby helping meet the global climate-change goals set forth by the Intergovernmental Panel on Climate Change. Herein, we present a multiscale approach to accelerate the catalyst-process development cycle for catalytic fast pyrolysis (CFP) of biomass over Mo2C. Mo2C has been shown to possess co-localized acidic and metallic sites and exhibit high activity for deoxygenation of biomass pyrolysis model compounds. However, critical knowledge gaps remain regarding the effectiveness of this catalyst for CFP of whole biomass. We address these knowledge gaps and demonstrate that Mo2C is effective at deoxygenating biomass-pyrolysis products in the presence of H2 but that it undergoes rapid selective and non-selective deactivation. The knowledge gaps addressed from this integrated study, targeting appropriate experiments across scales and feed types, enabled identification of critical modifications for advancing the CFP catalyst-process development cycle.

biofuels↗

Nyström type exponential integrators for strongly magnetized charged particle dynamics

Solving for charged particle motion in electromagnetic fields (i.e. the particle pushing problem) is a computationally intensive component of particle-in-cell (PIC) methods for plasma physics simulations. This task is especially challenging when the plasma is strongly magnetized due numerical stiffness arising from the wide range of time scales between highly oscillatory gyromotion and long term macroscopic behavior. A promising approach to solve these problems is by a class of methods known as exponential integrators that can solve linear problems exactly and are A-stable. This work extends the standard exponential integration framework to derive Nyström-type exponential integrators that integrates the Newtonian equations of motion as a second-order differential equation directly. In particular, we derive second-order and third-order Nyström-type exponential integrators for strongly magnetized particle pushing problems. Numerical experiments show that the Nyström-type exponential integrators exhibit significant improvement in computation speed over the standard exponential integrators.

general physics↗

An experimental study on gas-liquid phase fluid migration in hydrate-bearing sediments during hydrate dissociation

Natural gas hydrate production tests face problems such as severe sand blockage, poor gas-liquid phase separation, and significant land subsidence. This is because of the insufficient understanding of the complex phase transition and gas-liquid multi-phase fluid migration during hydrate dissociation. In hydrate-bearing sediment systems, hydrate phase transition couples with gas-liquid fluid migration. The phase transition causes changes in pore structure, which in turn modifies porous infiltration parameters and fluid flow capacity. Meanwhile, alterations in phase interfaces affect key parameters like surface tension and wettability. Gas-liquid fluid migration influences heat and mass transfer, thus affecting phase equilibrium and dissociation rates. To bridge the gap in describing gas-liquid fluid migration during hydrate dissociation in experiments, this research innovatively integrated an unsteady-state gas displacement by water and a quantitative hydrate dissociation process, independently developed a multi-phase seepage experimental system suitable for hydrate dissociation and determined the relationship between seepage parameters and hydrate saturation under different porosity. The results are as follows: a) Core samples with higher initial porosity show a greater recovery rate of fluid flow capacity. b) The retarding effect of multi-phase fluid has a more significant impact on the migration of the wetting phase fluid (water) than that of the non-wetting phase fluid (methane). c) During hydrate dissociation, the evolution of absolute permeability shows an “S-shaped” pattern, and the evolution of relative permeability shows a “wiring-harness” pattern. In conclusion, the findings can provide a theoretical basis for preventing geological disasters and for geotechnical engineering design during hydrate production.

58 GEOSCIENCES↗

Integrated lipidomic and proteomic profiling reveals metabolic network disruption by SARS-CoV-2 variants

The rapid evolution of SARS-CoV-2 has produced myriad viral strains with increasing transmissibility and capacity for immune evasion. While effective vaccination campaigns have reduced the fatalities associated with SARS-CoV-2, infections continue, and a detailed understanding of how this virus manipulates host biochemical pathways remains elusive. We asked both whether the patterns of host lipid rewiring remained consistent across variants and whether the changes in the abundance of lipid classes are related to changes in the expression of the enzymes involved in their biosynthesis. We compared global nontargeted lipidomics on A549-ACE2 cells infected with the delta variant (B.1.617.2), or the omicron (B.1.1.529) variant to our previous results of global nontargeted lipidomics on A549-ACE2 cells infected with the original WA1 strain and further performed quantitative proteomics to assess changes in the host proteome. We found that metabolic rewiring, both on the lipid and the enzymatic level, is remarkably consistent across all three variants. We further mapped changes in the expression of host metabolic enzymes, linking enzyme expression to alterations in the abundance of specific lipids during infection. This analysis identified key proteins related to virus-mediated changes in lipid abundance, including fatty acid synthase (FASN), lysosomal acid lipase (LIPA), and ORMDL, a regulator of sphingolipid biosynthesis. These integrated lipidomic and proteomic experiments shed light on the importance of the complex network of host metabolism networks that support SARS-CoV-2 infection and suggest that lipid metabolism may be a promising avenue for uncovering conserved therapeutic targets.

SARS-CoV-2↗

Data-Driven Discovery and Experimental Validation of Solvent Polarity Effects on Conjugated Polymer Solution-to-Film Assembly Pathways

Understanding how solvent properties influence the solution-to-film assembly of conjugated polymers remains a critical challenge due to the complex and intertwined nature of polymer–solvent interactions. In this study, we integrate a data-driven framework with experimental validation to identify key parameters influencing the assembly and performance of poly[2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl)thieno[3,2-b]thiophene)] (DPP-DTT) in organic field-effect transistors (OFETs). A machine learning (ML) approach identified the normalized Reichardt polarity parameter (E T N ) as a significant descriptor correlated with DPP-DTT hole mobility (μ). Systematic DPP-DTT devices fabricated using solvents across a wide E T N range revealed that higher E T N solvents yield enhanced μ. To elucidate the structural origins of high μ, we conducted comprehensive analyses using UV–vis–NIR spectroscopy and grazing incidence wide angle X-ray scattering (GIWAXS) measurements. The results revealed that films processed from high E T N solvents exhibit reduced paracrystallinity. By analyzing the solution-state behavior using optical microscopy and solution WAXS, we revealed polymer solubility differences in the various solvents and associated distinct polymer assembly pathways, elucidating why the high E T N solvent produces long-range ordered films. Notably, the high E T N solvent shows a pronounced preference for liquid-crystal (LC)-mediated assembly, providing a mechanistic explanation for the enhanced structural order. Therefore, these results demonstrate that solvent polarity, as evaluated by E T N , serves as an important parameter that plays a significant role in the DPP-DTT assembly pathway and resultant solid-state morphology. This work provides a strategy for integrating data science with experiments to identify critical parameters associated with complex polymer systems and helps guide rational process design for high-performance organic electronics.

36 MATERIALS SCIENCE↗

Statistical Characteristics of Raindrop Size Distributions and Parameters in Central China during the Meiyu Seasons

The rain parameters measured by the laser OTT Parsivel raindrop disdrometer (Parsivel), the two-dimensional video disdrometer (2DVD) and DZZ5 tipping-bucket rain gauge (RG) during the Integrative Monsoon Frontal Rainfall Experiment (IMFRE) in summer 2018 are compared. The total rain amounts observed by Parsivel, 2DVD, and RG during IMFRE are 178.07 mm, 176.76 mm and 182.5 mm, while their total rainy hours are 113, 113 and 90. The mean Dm (mass-weighted mean diameter) and liquid water content values derived from Parsivel and 2DVD are 0.9 mm and 1.02 mm, and 0.247 g m-3 and 0.223 g m-3, respectively, and Parsivel is more sensitive to small raindrops (< 1 mm) than 2DVD. The raindrop spectra measured by Parsivel and 2DVD have excellent agreement for both convective rain (CR) and stratiform rain (SR) within a range of Dm from 1 to 3.5 mm. The rain samples from six Parsivel sites over the middle reaches of the Yangtze River during the 2016–2018 meiyu seasons have been collected and processed. The frequency occurrences for rain rates (RR) < 5 and > 10 mm h-1 are 83.9% and 7.4%, respectively, but they contribute 30.5% and 52.1 % of the total accumulated rainfall. Comparing the results with those over the lower reaches, the RR and total accumulated rainfall over the middle reaches are greater, especially for heavy rainfall. The rain drop size distributions (DSDs) in this study are wider and have higher number concentration than those from the lower reaches.

Raindrop size distribution, Meiyu front, disdromet↗

A ModEx Framework for Watershed Subsurface Investigation With Limited Geophysical Data Using Machine Learning and Hydrologic Modeling

Abstract Subsurface heterogeneity influences watershed hydrology strongly but remains difficult to characterize at catchment scales with sparse and costly field data. Geophysical surveys such as electromagnetic induction (EMI) provide local spatial subsurface images yet scaling them to watershed scales and converting EMI‐derived resistivity into hydraulic properties remains a challenge. We present a Model–Experiment (ModEx) framework that integrates limited EMI data with machine learning (ML) and hydrologic modeling to improve process representation and guide field investigations. Sparse EMI surveys were scaled to the catchment scale using a Random Forest model, and the resulting resistivity fields were combined with nearby borehole constraints to parameterize a hydrologic model. The EMI‐informed hydrological simulations improved predictions of streamflow sustained by subsurface flow and shallow saturation patterns. By combining EMI data and ML with hydrologic modeling, the ModEx framework guides future subsurface surveys, providing a transferable and efficient strategy for data–model integration across diverse watersheds. Plain Language Summary Mapping the underground network of soil and rock that controls water is essential for predicting floods and droughts, but seeing underground is difficult and expensive. We cannot drill everywhere, so scientists use geophysical tools to scan broad areas. There are two key challenges: these geophysical scans are often sparse across the whole watershed, and the geophysical data is hard to translate into water‐related properties. We used artificial intelligence to solve these problems. We taught a computer to find patterns linking the limited geophysical data to the land surface properties. This allowed it to fill in the gaps and create a complete, useful subsurface map for the entire watershed. This new map improves hydrologic simulations, leading to more accurate predictions of water movement in the watershed. It also helps scientists build better models with less data and generates a priority map showing where to measure next, making future investigations more efficient. Key Points Limited EMI scaled with ML improves catchment‐scale subsurface parameterization for hydrologic models The framework integrates hydrologic modeling with limited geophysical data to support subsurface investigation design ModEx framework offers a transferable data–model integration strategy that quantifies and reduces uncertainty guiding watershed studies

Chen, Hang↗