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At least 703 records · Page 39

Molecular dynamics study of carbon dioxide and nitrogen selectivity through poly[bis((methoxyethoxy)ethoxy)phosphazene] (MEEP) membrane

Here, a molecular dynamics simulation model was developed to comprehensively understand carbon dioxide over nitrogen (CO 2 /N 2 ) selectivity through polyphosphazene-based membrane comprising of poly[bis((methoxyethoxy)ethoxy)phosphazene] (MEEP) selective layer at the molecular level. The effects of temperature, pressure, and initial feed gas composition on the CO 2 transport on a polymer membrane were studied. The computed free energy and density profile of the permeating gas mixture exhibited that CO 2 molecules express higher interactions with the membrane than N 2 molecules, resulting in higher CO 2 /N 2 selectivity. Statistical analysis of gas molecules (CO 2 , water (H 2 O), and N 2 ) transportation suggested that hydro- and CO 2 -philic functional groups in the membrane significantly impact CO 2 permeability and CO 2 /N 2 selectivity. This study suggested that Lewis acid–base and hydrogen bonding combinations contribute to CO 2 permeation and CO 2 /N 2 selectivity. An equal CO 2 /N 2 selectivity was observed with and without water vapor in the feed gas suggesting that water does not hinder CO 2 transport through the membrane.

36 MATERIALS SCIENCE↗

Three-Dimensional Imaging and Quantification of Gas Storativity in Nanoporous Media via X-rays Computed Tomography

This study provides the engineering science underpinnings for improved characterization and quantification of the interplay of gases with kerogen and minerals in shale. Natural nanoporous media such as shale (i.e., mudstone) often present with low permeability and dual porosity, making them difficult to characterize given the complex structural and chemical features across multiple scales. These structures give nanoporous solids a large surface area for gas to sorb. In oil and gas applications, full understanding of these media and their sorption characteristics are critical for evaluating gas reserves, flow, and storage for enhanced recovery and CO 2 sequestration potential. Other applications include CO 2 capture from industrial plants, hydrogen storage on sorbent surfaces, and heterogeneous catalysis in ammonia synthesis. Therefore, high-resolution experimental procedures are demanded to better understand the gas–solid behavior. In this study, CT imaging was applied on the sub-millimeter scale to shale samples (Eagle Ford and Wolfcamp) to improve quantitative agreement between CT-derived and pulse decay (mass balance) derived results. Improved CT imaging formulations are presented that better match mass balance results, highlighting the significance of gas sorption in complex nanoporous media. The proposed CT routine implemented on the Eagle Ford sample demonstrated a 17% error reduction (22% to 5%) when compared to the conventional CT procedure. These observations are consistent in the Wolfcamp sample, emphasizing the reliability of this technique for broader implementation of digital adsorption studies in nanoporous geomaterials.

42 ENGINEERING↗

A review of neutronics and thermal hydraulics–based screening methods applied to accelerated nuclear fuel qualification

This paper reviews the state-of-the-art engineering approach for using thermal hydraulic (TH) and neutronics modeling and simulation (M&S) tools to perform rapid screening studies of novel nuclear fuel concepts within the context of accelerated fuel qualification. Global research efforts have introduced nuclear fuel and material concepts that mark a significant departure from traditional reactor materials. The number of new technologies being considered for development for light water reactors and advanced reactor types has created the need for an accelerated fuel qualification procedure. A key component of this procedure is the rapid identification of the most promising fuel concepts using computational screening studies. Advanced TH and neutronic M&S tools should be leveraged to efficiently determine whether the reactor performance and safety characteristics of a given concept warrant additional studies or whether the concept requires modification or elimination. This paper reviews best practices for performing these TH and neutronics screening studies at various stages during a fuel concept's progression through the qualification procedure. The motivation behind standardizing this approach is to minimize time and resources spent on qualification activities for fuel concepts that could be quickly refined or eliminated from consideration based on their reactor physics and TH characteristics. Adoption of this screening procedure—which focuses primarily on nuclear fuels but may be applicable to other reactor materials—will also help accelerate new material qualification by generating boundary conditions crucial to fuel performance evaluations and highlighting needed areas of separate effects experimentation. This article reviews the motivation behind the introduction of novel nuclear fuel concepts, provides incentive for utilizing TH- and neutronics-based screening studies, describes the screening approach and methodology, and includes discussion on how to interpret screening results to provide recommendations for the continued development of a given concept.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SPARC-X: Quantum simulations at extreme scale - reactive dynamics from first principles

We have developed the massively parallel electronic structure code SPARC-X: a computational framework for performing Kohn-Sham Density Functional Theory (DFT) calculations that can scale linearly with the number of atoms in the system, while being able to leverage petascale and emerging exascale parallel computers to study chemical phenomena at unprecedented length and time scales. SPARC-X exploits a recent breakthrough in electronic structure methodologies: systematically improvable, strictly local, orthonormal, discontinuous real-space bases that efficiently and systematically capture the local chemistry of the system. With further adaptation using new machine-learning techniques and the use of the massively parallel Spectral Quadrature (SQ) electronic structure method, the algorithmic complexity and prefactor associated with DFT calculations involving semilocal as well as hybrid functionals are dramatically reduced. Using petascale computational resources, SPARC-X enables quantum mechanical simulations at length and time scales previously accessible only by empirical approaches, e.g., 1,000,000 atoms for a few picoseconds using semilocal functionals or 1,000 atoms for a few picoseconds using hybrid functionals. Using exascale resources, the sizes and times targeted are two orders of magnitude larger. Such a capability has applications in a wide variety of chemical sciences, including reactive interfaces where large length- and/or long time-scales are needed and traditional force fields fail. This is particularly important in dynamic catalysis, where bond breaking and formation must be understood in detail. We developed, tested, and employed the SPARC-X framework to understand the photocatalytic properties of TiO 2 nanoparticles, revealing finite size effects that cannot be captured with standard model systems or functionals. This integrated development and application strategy ensures that SPARC-X remains a robust, efficient, and scalable software package for quantum simulations on current petascale and emerging exascale computing resources.

97 MATHEMATICS AND COMPUTING↗

Efficient Bayesian inference with latent Hamiltonian neural networks in No-U-Turn Sampling

When sampling for Bayesian inference, one popular approach in the computational field is to use Hamiltonian Monte Carlo (HMC) and specifically the No-U-Turn Sampler (NUTS), which automatically decides the end time of the Hamiltonian trajectory. However, HMC and NUTS can require numerous numerical gradients of the target density and can prove slow in practice when relying on computationally expensive forward models. We propose Latent Hamiltonian neural networks (L-HNNs) with HMC and NUTS for solving Bayesian inference problems. Once trained, L-HNNs do not require numerical gradients of the target density during sampling, and hence numerous evaluations of the forward computational model. Moreover, L-HNNs satisfy important properties such as perfect time reversibility and Hamiltonian conservation, making them well-suited for use within HMC and NUTS because stationarity can be shown. We also propose the integration of L-HNNs in an online error monitoring scheme, in which numerical gradients of the target density are used for a few samples whenever the L-HNNs prediction errors are large. This online error monitor scheme prevents sample degeneracy in regions of low probability density and ensures robust uncertainty quantification. We demonstrate L-HNNs in NUTS with online error monitoring on several analytical examples involving complex, heavy-tailed, and high-local-curvature probability densities. We then demonstrate the applicability of L-HNNs in NUTS to two computational case studies, namely the Allen-Cahn stochastic partial differential equation and an elliptic partial differential equation with 25 and 50 inference parameters, respectively. Overall, the L-HNNs in NUTS with online error monitoring satisfactorily inferred these probability densities. In conclusion, compared to traditional NUTS, L-HNNs in NUTS with online error monitoring required 1–2 orders of magnitude fewer numerical gradients of the target density and improved the effective sample size (ESS) per gradient (which is a measure of both the sampling quality and the computational expense) by an order of magnitude.

97 MATHEMATICS AND COMPUTING↗

Phase distribution in Fischer-Tropsch mimicked slurry bubble column via computed tomography

This study aims to investigate the phases distribution and hydrodynamics in an air-Therminol LT-glass beads slurry bubble column reactor in bubbly and churn-turbulent flow regimes by implementing a gamma-ray computed tomography. It is found that gas holdup increases with increasing superficial gas velocity and operating pressure while increasing solids loading has an opposite effect on gas holdup measurements. It is noticed that the pressure effect is more significant at high solids loading and the solids loading is relatively more substantial at lower pressure. Solids loading has the most significant a stronger effect on the solids holdup profile than on the gas holdup profile. Current results were compared with the Sedimentation-Dispersion Model (SDM) predictions. Overall, the findings of this study advance the knowledge of the true behavior of phases distribution in FT mimicked slurry bubble columns which are pertinent in designing such reactors.

42 ENGINEERING↗

Mechanistic Pathways for N 2 O Elimination from trans -R 3 Sn-O-N=N-O-SnR 3 and for Reversible Binding of CO 2 to R 3 Sn-O-SnR 3 (R = Ph, Cy)

The rate and mechanism of the elimination of N 2 O from trans-R 3 Sn-O-N=N-O-SnR 3 (R = Ph ( 1 Ph ) and R = Cy ( 1 Cy )) to form R 3 Sn-O-SnR 3 (R = Ph ( 2 Ph ) and R = Cy ( 2 Cy )) have been studied using both NMR and IR techniques to monitor the reactions in the temperature range of 39–79 °C in C 6 D 6 . Activation parameters for this reaction are ΔH ‡ = 15.8 ± 2.0 kcal·mol –1 and ΔS ‡ = –28.5 ± 5 cal·mol –1 ·K –1 for 1 Ph and ΔH ‡ = 22.7 ± 2.5 kcal·mol –1 and ΔS ‡ = –12.4 ± 6 cal·mol –1 ·K –1 for 1 Cy . Addition of O 2 , CO 2 , N 2 O, or PPh 3 to sealed tube NMR experiments did not alter in a detectable way the rate or product distribution of the reactions. Computational DFT studies of elimination of hyponitrite from trans-Me 3 Sn-O-N=N-O-SnMe 3 ( 1 Me ) yield a mechanism involving initial migration of the R 3 Sn group from O to N passing through a marginally stable intermediate product and subsequent N 2 O elimination. Reactions of 1 Ph with protic acids HX are rapid and lead to formation of R 3 SnX and trans-H 2 N 2 O 2 . Reaction of 1 Ph with the metal radical •Cr(CO) 3 C 5 Me 5 at low concentrations results in rapid evolution of N 2 O. At higher •Cr(CO) 3 C 5 Me 5 concentrations, evolution of CO 2 rather than N 2 O is observed. Addition of 1 atm or less CO 2 to benzene or toluene solutions of 2 Ph and 2 Cy resulted in very rapid reaction to form the corresponding carbonates R 3 Sn-O-C(=O)-O-SnR 3 (R = Ph ( 3 Ph ) and R = Cy ( 3 Cy )) at room temperature. Evacuation results in fast loss of bound CO 2 and regeneration of 2 Ph and 2 Cy . Variable temperature data for formation of 3 Cy yield ΔH o = –8.7 ± 0.6 kcal·mol –1 , ΔS o = –17.1 ± 2.0 cal·mol –1 ·K –1 , and ΔG o 298K = –3.6 ± 1.2 kcal·mol –1 . Furthermore, DFT studies were performed and provide additional insight into the energetics and mechanisms for the reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bed form-induced hyporheic exchange and geochemical hotspots

Small-scale bed form topographies control hyporheic exchange and biogeochemical processes within aquatic sediments, which ultimately affect water quality and nutrient cycling at the watershed scale. The impact of three-dimensional and small-scale bed form topographies on hyporheic exchange and solute mixing is investigated in the present work. The effect of bed form morphologies on the development of zones of enhanced reaction rates (i.e., hotspots) is also studied. A computational fluid dynamics model to simulate river flow over bed forms is combined with a subsurface flow and multicomponent reactive solute transport model. A wide variety of bed form topographies are generated using geometric models by varying parameters controlling curvature as well as bed form wavelength and amplitude. The results in this research suggest that out-of-phase bed forms generate more complex hyporheic flow patterns which reduce the efficiency of solute transformations. Higher phase shifts in bed form shapes result in overall higher average velocity, larger zones of enhanced pressure and reaction rates, and higher amounts of solute exchange. Moreover, the bed form shapes control the reaction process for a wide range of sediment conductivities. Here this study advances the understanding of the effects of complex and small scale morphological features on hyporheic exchange processes including the rate and spatio-temporal distribution of reaction hotspots.

54 ENVIRONMENTAL SCIENCES↗

Development and Integration of Predictive Models for Manufacturing and Structural Performance of Carbon Fiber Composites in Automotive Applications (Final Report)

The goal of this project is to develop integrated, state-of-the-art, computational modeling tools based on an integrated computational materials engineering (ICME) methodology that are critically needed to enable structural carbon fiber (CF) applications in automobiles. These tools are designed to predict the manufacturing and structural performance of CF composites, including stochastic effects. During the first phase of the project, the manufacturing and structural performance tools, including a stochastic driver, were developed, calibrated, and validated against coupon and component level test results. For this project, from the manufacturing side, the development efforts were focused on high-pressure resin transfer molding (HP-RTM), a potentially game-changing manufacturing technology that is capable of reaching the 3-5-minute cycle time that is necessary for volume manufacturing of composites. On the structural performance side, the crashworthiness of CF structures was studied. Accordingly, computational tools were developed and validated. The resulting differences between the numerical predictions and the experimental results in the first phase of the project were required to be less than 15%. During the second phase of the project, the manufacturing and performance tools were integrated by mapping the manufacturing outcomes (e.g., fiber angles, residual stresses, degree of cure, and defects) into the structural models. Also, using the tools developed in this project, an automotive assembly currently manufactured in steel (2016 GM Malibu) was redesigned to be manufactured using advanced CF composites with the objective of comparing the performance of the CF assembly with the developed ICME model predictions. The weight, performance and cost of the CF assembly were compared with the baseline steel assembly as well. The CF underbody design was shown to be 30% lighter than the corresponding steel design. The CF underbody assembly withstood the side pole impact with less than half the intrusion for the steel assembly. Excellent correlations within 10% for both peak impact load and intrusion were observed between the numerical predictions and experimental results. Based on the cost models developed in the project, the cost increase per Kg saved was determined to be $22. The project team has prepared a total of 28 publications in various journals and conferences and broadly communicated the project results for the benefit of the composite industry. The project team has also prepared a total of 10 patent applications that were submitted to the US Patent and Trademark office.

36 MATERIALS SCIENCE↗

NETL Plastic Pipes Project (Final Report)

Plastic or composite pipelines have been the bane of the utility locating industry because they are neither conductive nor magnetic which are the properties traditionally used to locate buried utilities. Ground penetrating radar (GPR) is an effective geophysical tool for locating plastic/composite pipelines where resistive cover allows for adequate penetration of radar energy. However, GPR has limited applicability in areas where the soil cover is conductive due to significant clay and/or salt content. This study examines complementary near-surface geophysical methods that are potentially useful for locating buried plastic/composite pipelines, either singly or in combination. Specifically, this modeling study used computational numerical methods to forward model the response of GPR, resistivity, seismic, gravity gradiometry, and photoacoustic/thermoacoustic imaging methods to plastic/composite pipelines for various scenarios including: (1) pipe diameters ranging between 2 in. to 12 in.; (2) burial depths ranging between 3 ft. to 4 ft.; (3) various degrees in contrast in physical properties (i.e., electrical permittivity, elasticity, resistivity, density); and (4) various experimental acquisition choices (e.g., GPR radar and seismic source frequencies, electrode spacing). Numerical modeling performed herein reconfirmed that GPR is the preferred method for detecting/locating plastic pipelines. A caveat for GPR detection is that the material covering the plastic pipe (trench fill material and adjacent soil) must be sufficiently resistive to allow the two-way propagation to the required depth of investigation and back to the surface. GPR was the only method modeled in this study that can be used to directly detect plastic pipelines of 2-in.-diameter and larger when buried 3-ft-deep. GPR data processing and imaging also can determine pipe depth, pipe diameter, trench dimensions, and moisture conditions. Seismic modeling results suggest that direct detection of a 12-in.-diameter plastic pipe at 3-ft.-depth may be possible under favorable conditions; however, the associated signature would be weak (e.g., surface- to S-wave, backscattered surface-waves, and/or forward scattered surface-waves to S-wave). Direct pipe detection under field conditions with noise and strong lateral geologic heterogeneity is doubtful. Numerical modeling also suggests that plastic pipelines can be indirectly located by detecting the trench in which they are buried. GPR, direct current (DC) resistivity, and seismic methods have the potential to locate the pipeline trench if there is sufficient contrast between the trench-wall and trench-fill materials for the physical property being measured by each method (i.e., electrical permittivity for GPR; resistivity for DC resistivity; or density, compressional velocity, or shear velocity for seismic). Modeling also indicated that currently available (commercial) gravity gradiometers would be unable to directly detect/locate plastic pipelines ≤ 8-in.-diameter when buried 3-ft.-deep given the typical instrument noise floor for field surveying as well as the expected density variations due to geologic heterogeneity. The numerical modeling performed in this project did not identify a universal geophysical technology that can locate buried plastic pipelines in all parts of the United States (although GPR is suggested for all areas with resistive cover). However, the project results suggest that a towed land streamer simultaneously acquiring multiple geophysical data types including multi-offset GPR, multi-channel DC resistivity, seismic geophone- and/or distributed acoustic sensing (DAS), and potentially photoacoustic/thermoacoustic data would be an appropriate platform for locating buried plastic pipeline. Moreover, the complementary multiphysics data acquired by a towed land streamer would permit the use of joint and/or cooperative inversion frameworks for a more rigorous and consistent data interpretation.

42 ENGINEERING↗

Mechanism of Catechol Oxidation by the Coupled Bicupric Active Site of Tyrosinase: Completion of the Oxygenase/Oxidase Reaction Cycle

Tyrosinase contains a coupled binuclear copper (CBC) active site, which in its bicuprous form (deoxy-Ty) binds O 2 to form a side-on peroxide [Cu(II) 2 O 2 ] 2+ intermediate (oxy-Ty) that performs the regioselective monooxygenation of monophenols to catechols and their subsequent 2e − oxidation to quinones. Previously, we used spectroscopic, kinetic, and computational methods to elucidate the mechanism of the initial steps in the monooxygenation reaction. Herein, we investigated the final step in catecholate formation and provide experimental and computational results elucidating the catechol oxidation reaction, formally a proton-coupled 2e − process. We employed single-turnover stoppedflow absorption to observe the elusive catecholate-Cu(II) 2 OH intermediate via the anaerobic reaction of resting Cu(II) 2 OH Ty (met-Ty) with the catecholate substrate. This intermediate was cryo-trapped and characterized by electron paramagnetic resonance and X-ray absorption spectroscopies. These experimental results were correlated to quantum mechanics/molecular mechanics (QM/MM) and QM calculations to describe the complete catalytic cycle of tyrosinase, revealing that the 2e − oxidation of catechol to quinone involves two steps: (i) coupled 1H + /1e − transfer from the bound monoanionic catecholate to the bridged hydroxide of the met-Ty active site, followed by (ii) the second 1e − transfer. The latter is calculated to be the rate-limiting step in catechol oxidation, confirmed by experimental solvent kinetic isotope effect studies. Our computational data suggest that quinone release from the protein provides the necessary driving force for this reaction. These results establish a detailed description of this oxidase cycle of the tyrosinase mechanism and more broadly provide molecular-level insights into the diverse reactivity of CBC sites in biology.

QM/MM modeling↗

Measurements of β -delayed proton emitters in the region of 100 Sn

An experiment on neutron-deficient nuclei in the region of doubly magic 100 Sn was carried out at the Radioactive Ion Beam Factory (RIBF) at the RIKEN Nishina Center in Japan. 𝑁 ≈ 𝑍 ≈ 50 nuclei were produced following fragmentation of an intense primary 124 Xe beam and implanted in the Advanced Implantation Detector Array silicon setup for the first study of proton-rich nuclei with this system at RIKEN. Measurements of the 𝛽-delayed proton emitter decay half-lives, branching ratios and proton energy spectra of nuclei in the region of 100 Sn were performed, with improved precision in many cases. New results for the energy spectrum of 101 Sn are presented, where a 2.03(5)-MeV peak was observed. In conclusion, these results are compared to shell-model calculations, using the recent precise measurement of the 101 In proton separation energy are presented.

Appleton, C. J. [Univ. of Edinburgh, Scotland (Uni↗

A hybrid machine-learning approach for analysis of methane hydrate formation dynamics in porous media with synchrotron CT imaging

Fast multi-phase processes in methane hydrate bearing samples pose a challenge for quantitative micro-computed tomography study and experiment steering due to complex tomographic data analysis involving time-consuming segmentation procedures. This is because of the sample's multi-scale structure, which changes over time, low contrast between solid and fluid materials, and the large amount of data acquired during dynamic processes. Here, a hybrid approach is proposed for the automatic segmentation of tomographic data from time-resolved imaging of methane gas-hydrate formation in sandy granular media, which includes a deep-learning 3D U-Net model. To prepare a training dataset for the 3D U-Net, a technique to automate data labeling based on sample-specific information about the mineral matrix immobility and occasional fluid movement in pores is proposed. Automatic segmentation allowed for studying properties of the hydrate growth in pores, as well as dynamic processes such as incremental flow and redistribution of pore brine. Results of the quantitative analysis showed that for typical gas-hydrate stability parameters (100 bar methane pressure, 7°C temperature) the rate of formation is slow (less than 1% per hour), after which the surface area of contact between brine and gas increases, resulting in faster formation (2.5% per hour). Hydrate growth reaches the saturation point after 11 h of the experiment. Finally, the efficacy of the proposed segmentation scheme in on-the-fly automatic data analysis and experiment steering with zooming to regions of interest is demonstrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Preliminary analysis of TREAT free-field experiments using openmc

This work analyses activation calculations for dosimetry materials during a steady-state irradiation in the Transient Reactor Test (TREAT) reactor core. Hence, we developed a workflow based on the Monte Carlo code OpenMC alongside a custom depletion solver. The irradiation-induced activity as a function of time is computed, and several sensitivity studies are performed to evaluate uncertainty. This study has shown activity computations are sensitive to flux amplitude, irradiation time, atoms quantity and microscopic cross sections. Stochastic uncertainties have been propagated to evaluate the activity uncertainty for each dosimetry material. Most uncertainties are below our target of 3%, which demonstrates OpenMC as a powerful predictive and analysis tool. The precise results obtained through this newly developed computation scheme will be used in future experiments to characterize quantities of interest when operating the TREAT reactor in new configurations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Improving Gas Reactor Design with Complex Non-Standard Reaction Mechanisms in a Reactive Flow Model

Fluorinated gases are critical to a number of high-technology industries including semiconductor manufacturing and related processes such as flat panel display, LED, and photovoltaic manufacturing. These fluorinated gases have very high global warming potentials (GWPs) and, unfortunately are chemically very stable, in some cases lasting for thousands of years in the atmosphere. For environmental reasons, it is imperative that the release of these gases be minimized, but existing methods to destroy them requires a significant amount of energy. The goal of this project was to develop a more energy efficient method of destroying these high GWP gases using computational fluid dynamics, but the computational requirements are significant. In this project, we bring together resources available at the national labs, including high-performance computing hardware and modern computational methods, in order to explore an industrially important problem with key environmental and economic impact. In this project, we examined the state-of-the-art models for the physical processes involved, and made subtle changes to arrive at alternative formulations considerably better suited for computation and study. We examined several representative scenarios and developed a set of analyses techniques and tools that could be used to explore the systems in much greater detail. This exploratory project has demonstrated to ALZETA that HPC can indeed provide a unique view into their complex engineering problem - one that is simply inaccessible by any other means. The tools allow us to explore the details of the chemical process, and allow one to construct "what-if" scenarios to address shortcomings of the physical device in its current operating modes. However, as with many sources of completely new information, many new questions are illuminated with this capability. It will take considerable time, effort and experience before we learn to probe the solutions, pose operating scenarios and confirm modifications to the device that lead to real engineering advances.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advancing material modeling in hydrocodes using a concurrent finite-element and molecular dynamics multiscale framework

We present a multiscale simulation framework that couples the finite-element method with molecular dynamics. Bypassing traditional equations of state (EOS) by using in-line atomistic simulations, the method offers the advantage of incorporating detailed microscale physics not easily represented with coarse-grained models. Coupling consistency with the continuum code is ensured through the use of lifting and restriction operators, in line with heterogeneous multiscale methods. The concurrent continuum-atomistic framework is validated through comparison with experimental results and conventional EOS models, and demonstrated in a shock-driven hydrodynamic flow simulation under extreme conditions. We further evaluate the framework's usability by comparing it to state-of-the-art EOS models of deuterium. A computational performance study reveals that the atomistic EOS evaluation is a feasible alternative to conventional approaches, and demonstrates a weak scaling of 99% efficiency. These results highlight the framework's potential for large-scale multiscale modeling across a broad range of materials and conditions.

Computer science↗

ODIN: Probing the LAE Ly α Luminosity Function across Cosmic Time and Different Environments

The ubiquity and relative ease of discovery make 2 ≲ z ≲ 5 Lyα emitting galaxies (LAEs) ideal tracers for large-scale structure of the distant Universe. In addition, because Lyα is a resonance line, but frequently observed at large equivalent width, it is potentially a probe of galaxy evolution. The LAE Lyα luminosity function (LF) is an essential measurement for making progress on both of these topics. Although several studies have computed the LAE LF, very few have delved into how the function varies with environment. The large area and depth of the One-hundred-deg 2 DECam Imaging in Narrowbands (ODIN) survey makes such measurements possible at the cosmic noon redshifts of z ∼ 2.4, 3.1, and 4.5. In this initial work, we present algorithms needed to rigorously compute the LAE LF, and test them on the ∼16,000 ODIN LAEs found in the extended COSMOS field. Using these limited samples, we find weak evidence that protocluster environments suppress the numbers of faint LAEs compared to the field. We also find that the LF decreases in number density and evolves towards a steeper faint-end slope over cosmic time from z ∼ 4.5 to z ∼ 2.4.

Lyman-alpha galaxies↗

Mechanistic Studies of an Iron-Catalyzed Intermolecular C–H Amination Reaction under Catalytic Conditions and Having a Large KIE

The conversion of C–H bonds into amines by nitrene insertion is an attractive transformation since it is both atom- and step-economical, and provides a direct route to functionalizing hydrocarbons. Using an iron catalyst [{( tBu pyrr) 2 pyr}Fe(OEt 2 )] (1-OEt 2 ) (( tBu pyrr) 2 pyr 2– = 3,5- t Bu 2 -bis(pyrrolyl)pyridine), we recently demonstrated the catalytic conversion of weak C–H bonds into secondary amines using aryl azides as the nitrene source [Zars, E.; Angew. Chem., Int. Ed. 2023, 62, e202311749]. Here, we describe detailed mechanistic studies of this intermolecular C–H amination reaction under catalytic conditions. We find by Variable Time Normalization Analysis (VTNA) that the conversion of xanthene (2-H 2 ) and 2,4,6-trimethyl-phenyl azide ( Me 3) catalyzed by 1-OEt 2 is an overall 3/2 order process, being 1 st order in 2-H 2 and half order in Me 3. A kinetic isotope effect study (KIE) using 2-d 2 results in a significant decrease in the rate (KIE = 61(15)), which clearly implicates the C–H insertion step as rate-determining. Furthermore, treatment of 1-OEt 2 with one equivalent of N 3 -2,6- i Pr 2 –C 6 H 3 yields the mixed-valence C–N coupled product [( tBu pyrr) 2 pyrFe-N═C(2,6 i Pr 2 –Ph)═N-(2,6 i Pr 2 –Ph))Fe tBu pyrrpyr(2-H-pyrr)] (5 iPr ). Quantum chemical calculations confirm the electronic structure of the mixed-valence dimer in 5 iPr and rationalize the Hammett correlation by a delicate balance in the dinuclearization of the catalytically active monomers. Calculations further indicate significant tunneling for the pivotal H atom abstraction by the iron-imidyl complex. Combining all these results allows us to propose a mechanism consisting of imido formation in equilibrium with a radical-coupled diiron system, followed by stepwise C–H insertion via a linear H atom abstraction transition state and subsequent radical rebound.

azides↗