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At least 307 records · Page 17

Constraining capture cross sections using proton inelastic scattering as a surrogate reaction

The surrogate reaction method is an alternative to direct measurements of compound nuclear reaction cross sections. We introduce theory tools for extracting capture cross sections from experiments that use proton inelastic scattering as a surrogate reaction mechanism. This makes it possible to constrain compound nucleus decay models which are typically the largest source of uncertainty in capture cross section calculations. This letter describes the theory developments that were used to simultaneously infer 89 Y(p, γ) and 89 Zr(n, γ) cross sections from 90 Zr(p, p′γ) surrogate measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Facet Preferencing by Chemical Substitution Controls Semi-Hydrogenation Selectivity in Ternary Pyrite-Type Intermetallic Compounds

Intermetallic compounds serve as model catalysts for selective hydrogenation reactions, offering precise control over the active site composition(s), geometric and electronic structure. The addition of a third element to form a ternary intermetallic alters the exposed crystal facet(s), demonstrating a strategy to impart improved catalytic behavior in intermetallic catalysts. The site-specific substitution of a small fraction of Pd atoms with Au in pyrite-type PdSb 2 results in the preferential exposure of the (100) facet over the (111) facet. Electron back scattered diffraction and density functional theory calculations confirm the facet change upon the substitution of Pd with Au to form the ternary Pd 1−x Au x Sb 2 (0.075 ≤ x ≤ 0.25). The (100) facet demonstrates higher net alkene selectivity due to significantly weaker alkene binding compared to the (111) facet. Distinct from our prior work on chemical substitution to directly alter the active site composition, this work demonstrates the indirect modification of active sites via preferential facet exposure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods

Artificial intelligence (AI) and machine learning (ML) pose a challenge for achieving science that is both reproducible and replicable. The challenge is compounded in supervised models that depend on manually labeled training data, as they introduce additional decision-making and processes that require thorough documentation and reporting. We address these limitations by providing an approach to hand labeling training data for supervised ML that integrates quantitative content analysis (QCA)—a method from social science research. The QCA approach provides a rigorous and well-documented hand labeling procedure to improve the replicability and reproducibility of supervised ML applications in Earth systems science (ESS), as well as the ability to evaluate them. Specifically, the approach requires (a) the articulation and documentation of the exact decision-making process used for assigning hand labels in a “codebook” and (b) an empirical evaluation of the reliability” of the hand labelers. In this paper, we outline the contributions of QCA to the field, along with an overview of the general approach. We then provide a case study to further demonstrate how this framework has and can be applied when developing supervised ML models for applications in ESS. With this approach, we provide an actionable path forward for addressing ethical considerations and goals outlined by recent AGU work on ML ethics in ESS.

58 GEOSCIENCES↗

Multifunctional textured graphene-based coatings on elastomeric gloves for chemical protection

Nanotechnology offers a variety of new tools for the design of next-generation personal protective equipment (PPE). One example is the use of two-dimensional materials as coatings that enhance the performance and ergonomics of elastomeric gloves designed to protect users from hazardous chemicals. Desirable features in such coatings may include molecular barrier function, liquid droplet repellency, stretchability for compatibility with the elastomer, breathability, and an ultrathin profile that preserves the user's manual dexterity and tactile sensation. The present work explores the potential of engineered graphene-based films with out-of-plane texturing as a novel platform to meet these multifold requirements. Graphene-based films in different formulations were fabricated from water-borne inks by vacuum filtration and solution casting methods on glove-derived nitrile rubber substrates. The various coatings were then subjected to tests of molecular permeation by model volatile organic compounds, droplet contact angle, breathability, and mechanical stability during stretching and solvent immersion. The films dramatically improve the barrier properties of glove-derived nitrile. The out-of-plane graphene texturing imparts stretchability through microscale folding/unfolding, while also enhancing droplet repellency in some cases through a lotus-like roughening effect. The combined results suggest that engineered textured graphene-based films are a promising platform for creating multifunctional coatings for a next generation of chemically protective gloves and other elastomer-based PPE.

36 MATERIALS SCIENCE↗

Four-Dimensional Quasielastic Neutron Scattering (4D-QENS) Analysis of Correlated Ionic Conduction in Sr⁢Cl2

Methods of elucidating the mechanisms of fast-ion conduction in solid-state materials are pivotal for advancements in energy technologies such as batteries, fuel cells, sensors, and supercapacitors. In this study, we examine the ionic conduction pathways in single crystal Sr⁢Cl2, which is a fast-ion conductor above 900 K, using four-dimensional quasielastic neutron scattering (4D-QENS). We explore both coherent and incoherent neutron scattering at temperatures above the transition temperature into the superionic phase to explore the correlated motion of hopping anions. Refinements of the incoherent QENS yield residence times and jump probabilities between lattice sites in good agreement with previous studies, confirming that ionic hopping along nearest-neighbor directions is the most probable conduction pathway. However, the coherent QENS reveals evidence of de Gennes narrowing, indicating the importance of ionic correlations in the conduction mechanism. This highlights the need for improvements both in the theory of ionic transport in fluorite compounds and the modeling of coherent 4D-QENS in single crystals.

Coles, Jared [Materials Science Division, Argonne ↗

Simulating spin dynamics of supersolid states in a quantum Ising magnet

Motivated by a recent experimental study on the quantum Ising magnet K 2 Co(SeO 3 ) 2 that presented spectroscopic evidence of zero-field supersolidity (Chen et al., arXiv:2402.15869), we simulate the excitation spectrum of the corresponding microscopic XXZ model for the compound, using the recently developed excitation ansatz for infinite projected entangled-pair states. Here, we map out the ground state phase diagram and compute the dynamical spin structure factors across a range of magnetic field strengths, focusing especially on the two supersolid phases found near zero and saturation fields. Our simulated excitation spectra for the zero-field supersolid “Y” phase are in excellent agreement with the experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

COVID-19 Infection Prevention through Natural Product Molecules

This project evaluates natural product molecules with the potential to prevent 2019- nCOV infection. The molecules theoretically work by blocking the ACE2 protein active site in human airways. Previous work focused on modeling candidate natural compounds, but this work examined baicalin, hesperetin, glycyrrhizin, and scutellarin in experimental in vitro studies, which included recombinant protein inhibition assays, cell culture virus inhibition assays, and cytotoxicity assays. The project delivered selectivity indices (ratio that measures the window between cytotoxicity and antiviral activity) of the four natural compounds that will help guide the direction of SARS-CoV-2 therapeutic development.

59 BASIC BIOLOGICAL SCIENCES↗

Stratospheric ozone depletion and future levels of atmospheric chlorine and bromine

The rise in atmospheric chlorine levels caused by the emission of chlorofluorocarbons and other halocarbons is thought to be the main cause of the appearance of the Antarctic ozone 'hole' in the late 1970s, and the more modest ozone depletion observed over parts of the Northern Hemisphere. Atmospheric bromine, also associated with halocarbon emissions, is believed to contribute to ozone depletion. Over the next decade, further increases in these compounds are inevitable. Model calculations show that by the end of the next century, atmospheric chlorine and bromine levels may return to those prevalent before the onset of the ozone hole, but only if more stringent regulations are applied to halocarbon production than those currently proposed.

Prather, Michael J.↗

Teleseismic detection of a slow precursor to the great 1989 Macquarie Ridge earthquake

Low-frequency spectra for the 1989 Macquarie Ridge earthquake (magnitude 8.2) show an amplitude increase and a phase-delay decrease below 6 millihertz that require a short-term slow precursor. This earthquake can be modeled as a compound event in which a fast-rupturing, ordinary earthquake was initiated by an episode of slow, smooth deformation that began more than 100 seconds before the main shock. The moment released in the slow precursor was large, about 3 x 10 exp 20 newton-meters, equivalent to an event of magnitude 7.6. The data are consistent with the precursor being generated in a region of the oceanic upper mantle below the main rupture.

Ihmle, Pierre F.↗

Burning and Suppression of Solids–II (BASS-II) Summary Report

The Burning and Suppression of Solids (BASS) experiment hardware is a small flow duct that provides containment for small scale burning of solid samples within the Microgravity Science Glovebox (MSG) aboard the International Space Station (ISS). A video camera with a data overlay and a 35-mm still camera record the combustion events. The controls (ignition, fan speed, etc.) are operated by an astronaut while the principal investigator team monitors the experiment from the ground and communicates directly with the astronaut. For the first time on ISS, BASS–II utilized MSG working volume dilution with gaseous N2. We developed a perfectly stirred reactor model to determine the N2 flow time and flow rate to obtain the desired reduced O2 concentration in the working volume for each test. We calibrated the model with the Compound Specific Analyzer-Combustion Products (CSA-CP) O2 readings offset using the Major Constituents Analyzer reading of the ISS ambient atmosphere data for that day. This worked out extremely well for operations, and added a new vital variable, ambient O2 level, to our test matrices. The main variables tested in BASS–II were ambient O2 concentration, ventilation flow velocity, and fuel type, thickness, and geometry. BASS–II also utilized the onboard CSA-CP for O2 and CO readings, and the Carbon Dioxide Monitor for CO2 readings before and after each test. Readings from these sensors allow us to evaluate the completeness of the combustion. The O2 and CO2 readings before and after each test were analyzed and compared very well to stoichiometric ratios for a one-step gas-phase reaction. The CO versus CO2 followed a linear trend for some datasets, but not for all the different geometries of fuel and flow tested. We calculated the heat release rates during each test from the O2 consumption and burn times, using the constant 13.1 kJ of heat released per gram of O2 consumed. The results showed that most of the tests had heat release rates well below 100 W. Lastly, the global equivalence ratio for the tests is estimated to be fuel rich, 1.3 on average using mass loss and O2 consumption data.

Microgravity↗

Biological evaluation of Keggin‐type polyoxometalates on tyrosinase: Kinetics and molecular modeling

Abstract Abnormal overexpression of tyrosinase activity can lead to the production of hyperpigmentation in human skin and enzymatic browning in fruits and vegetables. Herein, the inhibition and mechanism of the H 3 PMo 12 O 40 and two transition metal‐substituted Keggin‐type polyoxometalates (Na 7 PMo 11 CoO 40 and Na 7 PMo 11 ZnO 40 ) on tyrosinase were studied by kinetics and molecular modeling. Kinetic studies indicated that all compounds had more potent inhibitory activities than standard arbutin, and H 3 PMo 12 O 40 (IC 50 = 0.443 ± 0.006 m m ) is ~15‐fold stronger inhibition than arbutin. Additionally, all compounds inhibited tyrosinase in a reversible competitive manner. Intriguingly, molecular modeling elucidated that three compounds competitively bind to tyrosinase mainly through more interactions with Cu 2+ ions and the amino acid residue capable of forming cation‐π and hydrogen bonding, forming a reversible non‐covalent complex. Molecular simulation study correlated well with the biological activity of three compounds in vitro. This work provided new insights into design and synthesis of polyoxometalates as tyrosinase inhibitors in the field of medicine, cosmetic, and food.

Chi, Guoxiang↗

Scale-invariant machine-learning model accelerates the discovery of quaternary chalcogenides with ultralow lattice thermal conductivity

We design an advanced machine-learning (ML) model based on crystal graph convolutional neural network that is insensitive to volumes (i.e., scale) of the input crystal structures to discover novel quaternary chalcogenides, AMM'Q 3 (A/M/M' = alkali, alkaline earth, post-transition metals, lanthanides, and Q = chalcogens). These compounds are shown to possess ultralow lattice thermal conductivity (κ l ), a desired requirement for thermal-barrier coatings and thermoelectrics. Upon screening the thermodynamic stability of ~1 million compounds using the ML model iteratively and performing density-functional theory (DFT) calculations for a small fraction of compounds, we discover 99 compounds that are validated to be stable in DFT. Taking several DFT-stable compounds, we calculate their κ l using Peierls–Boltzmann transport equation, which reveals ultralow κ l (<2 Wm -1 K -1 at room temperature) due to their soft elasticity and strong phonon anharmonicity. Our work demonstrates the high efficiency of scale-invariant ML model in predicting novel compounds and presents experimental-research opportunities with these new compounds.

36 MATERIALS SCIENCE↗

Refrigerated Wind Tunnel Tests on Surface Coatings for Preventing Ice Formation

This investigation was conducted to determine the effectiveness of various surface coatings as a means for preventing ice formations on aircraft in flight. The substances used as coatings for these tests are divided into two groups: compounds soluble in water, and those which are insoluble in water. It was found that certain soluble compounds were apparently effective in preventing the formation of ice on an airfoil model, while all insoluble compounds which were tested were found to be ineffective.

Knight, Montgomery↗

Wireless sensing and control of temperature using magnetic fields

A method and system for sensing and controlling temperature with magnetic fields are provided. The method comprises placing a compound in thermal communication with a number of temperature or heat sources and placing a number of magnets in thermal communication with the compound. A number of magnetic sensors are placed in electromagnetic communication with the number of magnets. Changes in the magnetic field of the magnets are detected by the sensors and used to determine the temperature of the compound according to a model that maps magnetic field characteristics to temperature. The amount of cure of the compound can then be estimated from the temperature. The temperature or heat sources are controlled in response to the temperature measurement and the estimated amount of cure of the compound.

Chen Mazumdar, Yi↗

Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models

We improved the quality and reduced the time to produce machine learned models for use in small molecule antiviral design. Our globally asynchronous multi-level parallel training approach strong scales to all of Sierra with up to 97.7% efficiency. We trained a novel, character-based Wasserstein autoencoder that produces a higher quality model trained on 1.613 billion compounds in 23 minutes while the previous state of the art takes a day on 1 million compounds. Reducing training time from a day to minutes shifts the model creation bottleneck from computer job turnaround time to human innovation time. Our implementation achieves 318 PFLOPs for 17.1% of half-precision peak. We will incorporate this model into our molecular design loop enabling the generation of more diverse compounds; searching for novel, candidate antiviral drugs improves and reduces the time to synthesize compounds to be tested in the lab.

Jacobs, Sam Ade↗

Tracking dissociation pathways of nitrobenzene via mega-electron-volt ultrafast electron diffraction

As the simplest nitroaromatic compound, nitrobenzene is an interesting model system to explore the rich photochemistry of nitroaromatic compounds. Previous investigations of nitrobenzene's photochemical dynamics have probed structural and electronic properties. These investigations paint, at times, a convoluted and sometimes contradictory description of the photochemical landscape. Here, we investigate the ultrafast dynamics of nitrobenzene triggered by photoexcitation at 267 nm for the first time using a structural probe with femtosecond time resolution. Our probe complements previous measurements of nitrobenzene's electronic structure evolution and aids in determining the photochemical dynamics with less ambiguity. We employ megaelectronvolt ultrafast electron diffraction to follow nitrobenzene's structural evolution within the first 5 ps after photoexcitation. We observe ground state recovery within 160 ± 60 fs through nonadiabatic dynamics. Based on comparisons of the experimental signal with molecular dynamics simulations, we exclude a significant population of the triplet manifold. Furthermore, we do not observe fragmentation of nitrobenzene within the investigated time window, which indicates that previously observed photofragmentation reactions take place in the vibrationally 'hot' ground state on timescales considerably beyond 5 ps.

74 ATOMIC AND MOLECULAR PHYSICS↗