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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8

Male body size predicts reproductive success but not within-clutch paternity patterns in gopher tortoises ( Gopherus polyphemus )

In many vertebrates, body size is an important driver of variation in male reproductive success. Larger, more fit individuals are more likely to dominate mating opportunities, skewing siring success and resulting in lower effective population sizes and genetic diversity. The mating system of the gopher tortoise (Gopherus polyphemus) has been characterized as both female defense and scramble-competition polygyny. Mating systems are typically not fixed and can be influenced by factors such as population density, demographic structure, and environmental conditions;, however, most populations will have a predominant strategy that results from local conditions. We assessed how male body size influences patterns of paternity and reproductive success in a natural population of gopher tortoises in Florida, USA. Using microsatellites, we assigned parentage of 220 hatchlings from 31 nests collected during two reproductive seasons. Larger males were significantly more likely to sire offspring and sired more offspring than smaller males; however, the likelihood of a clutch being multiply-sired was unrelated to male body size. We also found evidence of mate fidelity across years. Although paternity patterns in this high-density population are more consistent with defense polygyny, female monopoly by males was incomplete, with both large and small males contributing to multiply-sired clutches. Additional behavioral data are needed to clarify the role of female mate selection in paternity outcomes. The context-dependence of mating systems underscores the need to compare parentage patterns across populations and to recognize the potential for more than one strategy to be employed within a single population.

59 BASIC BIOLOGICAL SCIENCES↗

Aerobijels: Ultralight Carbon Monoliths from Cocontinuous Emulsions

In this work, bijels are used to develop a new class of ultralight hierarchically porous aerogels exhibiting multimodal porosity across multiple length scales. Through in situ functionalization of a particle-laden liquid interface wherein binary liquid pairs are kinetically trapped out of equilibrium through interfacial jamming, monolithic and freestanding carbon electrodes are produced with prescribed bulk densities down to ≈2 mg cm -3 . Exemplary electrokinetic experiments indicate that the bicontinuity of the pore structure is essential for enhancing transport to and from the active electrode surfaces, demonstrating that these materials possess a superior ability to accumulate and transport charge when compared to analogous systems with restricted pore connectivity and fluid throughput. This approach offers a new synthetic route to bicontinuous and hierarchical aerogel materials with nested multimodal porosities. Furthermore, the flexibility of this scheme can address critical issues related to transport-limited behaviors that arise in many technological fields, ranging from energy and catalysis research to remediation and sensing applications.

36 MATERIALS SCIENCE↗

Uncertainty quantification in multiscale simulation of woven fiber composites

We report woven fiber composites have been increasingly employed as light-weight materials in aerospace, construction, and transportation industries due to their superior properties. These materials possess a hierarchical structure that necessitates the use of multiscale simulations in their modeling. To account for the inherent uncertainty in materials, such simulations must be integrated with statistical uncertainty quantification (UQ) and propagation (UP) methods. However, limited advancement has been made in this regard due to the significant computational costs and complexities in modeling spatially correlated structural variations coupled at different scales. In this work, a non-intrusive approach is proposed for multiscale UQ and UP to address these limitations. We introduce the top-down sampling method that allows to model non-stationary and continuous (but not differentiable) spatial variations of uncertainty sources by creating nested random fields (RFs) where the hyperparameters of an ensemble of RFs is characterized by yet another RF. We employ multi-response Gaussian RFs in top-down sampling and leverage statistical techniques (such as metamodeling and dimensionality reduction) to address the considerable computational costs of multiscale simulations. We apply our approach to quantify the uncertainty in a cured woven composite due to spatial variations of yarn angle, fiber volume fraction, and fiber misalignment angle. Finally, our results indicate that, even in linear analysis, the effect of uncertainty sources on the material’s response could be significant.

42 ENGINEERING↗

Antiferromagnetic order in CaK ( Fe 1 – x Ni x ) 4 As 4 and its interplay with superconductivity

The magnetic order in CaK(Fe 1–x Ni x ) 4 As 4 (1144) single crystals (x = 0.051 and 0.033) has been studied by neutron diffraction. We observe magnetic Bragg peaks associated with the same propagation vectors as found for the collinear stripe antiferromagnetic (AFM) order in the related BaFe 2 As 2 (122) compound. The AFM state in 1144 preserves tetragonal symmetry and only a commensurate, noncollinear structure with a hedgehog spin-vortex crystal (SVC) arrangement in the Fe plane and simple AFM stacking along the c direction is consistent with our observations. The SVC order is promoted by the reduced symmetry in the FeAs layer in the 1144 structure. The long-range SVC order coexists with superconductivity, however, similar to the doped 122 compounds, the ordered magnetic moment is gradually suppressed with the developing superconducting order parameter. Lastly, this supports the notion that both collinear and noncollinear magnetism and superconductivity are competing for the same electrons coupled by Fermi surface nesting in iron arsenide superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Large-eddy simulation of an atmospheric bore and associated gravity wave effects on wind farm performance in the southern Great Plains

Gravity waves are a common occurrence in the atmosphere, with a variety of generation mechanisms. Their impact on wind farms has only recently gained attention, with most studies focused on wind farm-induced gravity waves. In this study, the interaction between a wind farm and gravity waves generated by an atmospheric bore event is assessed using multiscale large-eddy simulations. The atmospheric bore is created by a thunderstorm downdraft from a nocturnal mesoscale convective system (MCS). The associated gravity waves impact the wind resource and power production at a nearby wind farm during the American Wake Experiment (AWAKEN) in the US southern Great Plains. A two-domain nested setup (Δx=300 and 20 m) is used in the Weather Research and Forecasting (WRF) model, forced with data from the High-Resolution Rapid Refresh model, to capture both the formation of the bore and its interaction with individual wind turbines. The MCS is resolved on the large outer domain, where the structure of the bore and the associated gravity waves are found to be especially sensitive to parameterized microphysics processes. On the finer inner domain, gravity wave interactions with individual wind turbines are resolved; wake dynamics are captured using a generalized actuator disk parameterization in WRF. The gravity waves are found to have a strong effect on the atmosphere above the wind farm; however, the effect of the waves is more nuanced closer to the surface where there is additional turbulence, both ambient and wake-generated. Notably, the gravity waves modulate the mesoscale environment by weakening and dissipating the preexisting low-level jet, which reduces hub-height wind speed and hence the simulated power output, which is confirmed by the observed supervisory control and data acquisition (SCADA) power data. Additionally, the gravity waves induce local wind direction variations correlated with fluctuations in pressure, which lead to fluctuations in the simulated power output as various turbines within the farm are subjected to waking from nearby turbines.

17 WIND ENERGY↗

Going beyond Intercalation Capacity of Aqueous Batteries by Exploiting Conversion Reactions of Mn and Zn electrodes for Energy‐Dense Applications

Abstract The recent trend in zinc (Zn) anode aqueous batteries has been to explore layered structures like manganese dioxides and vanadium oxides as Zn‐ion intercalation hosts. These structures, although novel, face limitations like their layered counterparts in lithium (Li)‐ion batteries, where the capacity is limited to the host's intercalation capacity. In this paper, a new strategy is proposed in enabling new generation of energy dense aqueous‐based batteries, where the conversion reactions of rock salt/spinel manganese oxides and carbon nanotube‐nested nanosized Zn electrodes are exploited to extract significantly higher capacity compared to intercalation systems. Accessing the conversion reactions allows to achieve high capacities of 750 mAh g −1 (≈30 mAh cm −2 ) from manganese oxide (MnO) and 810 mAh g −1 (≈30 mAh cm −2 ) from nanoscale Zn anodes, respectively. The high areal capacities help to attain unprecedented energy densities of 210 Wh per L‐cell and 320 Wh per kg‐total (398 Wh per kg‐active) from aqueous MnO|CNT‐Zn batteries, which allows an assessment of its viable use in a small‐scale automobile.

Yadav, Gautam G.↗

NGEE Arctic Integrated Modeling (IM2): Improved subgrid hillslope hydrologic connectivity

This data product represents the integration of new code capability for arctic tundra hillslope hydrologic processes into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The current ELM represents water movement primarily through vertical processes, such as precipitation, canopy interception, evaporation, infiltration, and soil water movement. Lateral water movement—such as surface runoff, subsurface flow, and river transport—plays a significant role in the hydrological cycle, especially in regions with varied topography. While E3SM includes a runoff routing component representing water transport in the river network, the lateral transport of water at the subgrid scale within the land model has previously not been taken into account. With the recent development of topographic units within the ELM subgrid data structure, there is an opportunity to simulate hillslope hydrologic connectivity by introducing water transport along topographic gradients. We expect that more realistic representation of hillslope hydrologic processes will lead to improved predictions of both soil water content and river network flows. Lateral transport of water at and near the surface is represented as a sub-grid process in this new code development. Water is tracked as it moves from higher to lower elevations within a gridcell. This capability uses the nested hierarchical sub-grid scheme within ELM to connect water fluxes from sub-grid elements with higher elevation to those with lower elevation. This data record consists of a single document (pdf format) that describes the theoretical basis for the hillslope hydrology processes added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗

How well are hazards associated with derechos reproduced in regional climate simulations?

Abstract. A 15-member ensemble of convection-permitting regional simulations of the fast-moving and destructive derecho of 29–30 June 2012 that impacted the northeastern urban corridor of the USA is presented. This event generated 1100 reports of damaging winds, generated significant wind gusts over an extensive area of up to 500 000 km2, caused several fatalities, and resulted in widespread loss of electrical power. Extreme events such as this are increasingly being used within pseudo-global-warming experiments to examine the sensitivity of historical, societally important events to global climate non-stationarity and how they may evolve as a result of changing thermodynamic and dynamic contexts. As such it is important to examine the fidelity with which such events are described in hindcast experiments. The regional simulations presented herein are performed using the Weather Research and Forecasting (WRF) model. The resulting ensemble is used to explore simulation fidelity relative to observations for wind gust magnitudes, spatial scales of convection (as is manifest in high composite reflectivity, cREF), and both rainfall and hail production as a function of model configuration (microphysics parameterization, lateral boundary conditions (LBCs), start date, use of nudging, compiler choice, damping, and number of vertical levels). We also examine the degree to which each ensemble member differs with respect to key mesoscale drivers of convective systems (e.g., convective available potential energy and vertical wind shear) and critical manifestations of deep convection, e.g., vertical velocities, cold-pool generation, and how those properties relate to the correct characterization of the associated atmospheric hazards (wind gusts and hail). Use of a double-moment, seven-class scheme with number concentrations for all species (including hail and graupel) results in the greatest fidelity of model-simulated wind gusts and convective structure to the observations of this event. All ensemble members, however, fail to capture the intensity of the event in terms of the spatial extent of convection and the production of high near-surface wind gusts. We further show very high sensitivity to the LBCs employed and specifically that simulation fidelity is higher for simulations nested within ERA-Interim compared to ERA5. Excess convective available potential energy (CAPE) in all ensemble members after the derecho passage leads to excess production of convective cells, wind gusts, cREF > 40 dBZ, and precipitation during a frontal passage on the subsequent day. This event proved very challenging to forecast in real time and to reproduce in the 15-member hindcast simulation ensemble presented here. Future work could examine if simulations with other initial and lateral boundary conditions can achieve greater fidelity.

Shepherd, Tristan (ORCID:0000000186276419)↗

Nonlinear saturation of ballooning modes in stellarators

Ballooning mode saturation is investigated in realistic stellarator configurations using the flux tube approach of Ham et al (2018 Plasma Phys. Control. Fusion 60 075017), Ham et al (2016 Phys. Rev. Lett. 116 235001). The method is adapted to account for the lack of exact force balance in stellarator equilibrium solvers that assume existence of nested flux surfaces. A variational approach for calculating flux tube energy is developed to overcome this force error problem in stellarator numerical equilibria. Saturated (equilibrium) flux tube states that cross 10%–20% of the plasma minor radius are shown to exist for linearly ballooning unstable profiles. It is shown that several features of the displaced flux tube structure in a full nonlinear MHD simulation of Wendelstein 7X are reproduced by our model. Saturated states are found in a compact stellarator equilibrium close but below the marginal ballooning linear instability, i.e. the unperturbed equilibrium is metastable. This suggests that edge-localized-mode-like explosive MHD behavior may be possible in stellarators.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Macrocycle-Directed Construction of Tetrahedral Anion-pi Receptors for Nesting Anions with Complementary Geometry

The unprecedented tetrahedral anion-? receptors have been successfully constructed by a macrocycle-directed approach. The use of large macrocycle precursors bearing four reaction sites enabled kinetic-favored cross-linking pathway and afforded otherwise-inaccessible tetrahedral cages in considerable yields. Crystal structure suggested that the tetrahedral cages have an enclosed three-dimensional cavity surrounded by four electron-deficient triazine faces in a tetrahedral array. The complementary accommodation of a series of tetrahedral and relevant anions including BF4-, ClO4-, H2PO4-, HSO4-, SO42- and PF6- has been observed by ESI-MS. Two complex crystal structures with ClO4- and PF6- demonstrated the anion was nicely encapsulated within the tetrahedral cavity through up to quadruple cooperative anion-? interactions by an excellent shape and size match. The favored complexation energies were established by DFT calculation and further confirmed by negative ion photoelectron spectroscopy study.

Luo, Jian↗

Do Dominant Ants Affect Secondary Productivity, Behavior and Diversity in a Guild of Woodland Ants?

The degree to which competition by dominant species shapes ecological communities remains a largely unresolved debate. In ants, unimodal dominance–richness relationships are common and suggest that dominant species, when very abundant, competitively exclude non-dominant species. However, few studies have investigated the underlying mechanisms by which dominant ants might affect coexistence and the maintenance of species richness. In this study, we first examined the relationship between the richness of non-dominant ant species and the abundance of a dominant ant species, Formica subsericea, among forest ant assemblages in the eastern US. This relationship was hump-shaped or not significant depending on the inclusion or exclusion of an influential observation. Moreover, we found only limited evidence that F. subsericea negatively affects the productivity or behavior of non-dominant ant species. For example, at the colony-level, the size and productivity of colonies of non-dominant ant species were not different when they were in close proximity to dominant ant nests than when they were away and, in fact, was associated with increased productivity in one species. Additionally, the number of foraging workers of only one non-dominant ant species was lower at food sources near than far from dominant F. subsericea nests, while the number of foragers of other species was not negatively affected. However, foraging activity of the non-dominant ant species was greater at night when F. subsericea was inactive, suggesting a potential mechanism by which some non-dominant species avoid interactions with competitively superior species. Gaining a mechanistic understanding of how patterns of community structure arise requires linking processes from colonies to communities. Our study suggests the negative effects of dominant ant species on non-dominant species may be offset by mechanisms promoting coexistence.

Formicidae↗

Modeling electric vehicle adoption considering a latent travel pattern construct and charging infrastructure

This paper presents a behavioral model of public, revealed preferences (RP) for various types of electric vehicles (EVs) while accounting for a latent (green) travel pattern construct and charging infrastructure characteristics. Specifically, a two-level nested logit (NL) model is estimated to explain households' fuel type choice among five alternatives and three nests: (1) battery electric vehicles (BEVs); (2) hybrid vehicles including hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs); and (3) conventional vehicles including gasoline and diesel vehicles. Further, a latent travel pattern construct which captures a week-long number of trips by non-vehicle travel modes as well as daily vehicle and tollway use is estimated in a structural equation setting and subsequently fed into the NL model. Using a recent RP dataset from the California Household Travel Survey, we identify market segments for alternative fuel types based on households' socio-economic characteristics, built environment factors concerning public plug-in EV (PEV) charging infrastructure characteristics, latent and observable travel behavior factors of a household vehicle's principal driver, and vehicle attributes. The results highlight that the number of public PEV charging stations is only significant for households choosing PHEVs and interestingly insignificant in the BEV utility. Furthermore, the sensitivity analysis of the findings reveals that PHEV users are elastic with respect to household vehicle ownership ratio and the latent green travel pattern construct, while BEV users are inelastic to any explanatory variable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dimensional crossover and symmetry transformation of charge density waves in VSe 2

Collective phenomena in solids can be sensitive to the dimensionality of the system; a case of special interest is VSe 2 , which shows a (√7×√3) charge density wave (CDW) in the single layer with threefold symmetry in the normal phase spontaneously broken, in contrast to the (4×4) in-plane CDW in the bulk. Angle-resolved photoemission spectroscopy (ARPES) from VSe 2 ranging from a single layer to the bulk reveals the evolution of the electronic structure including the Fermi surface contours and the CDW gap. At a thickness of two layers, the ARPES maps are already nearly bulklike, but the transition temperature T C for the (4×4) CDW is much higher than the bulk value of 110 K. These results can be understood as due to dimensional crossover of phonon instability driven by a competition of nesting vectors. Here, in this letter, we provide key insights into the CDW mechanisms and offer a perspective in the search and control of emergent phases in quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Active Learning A Neural Network Model For Gold Clusters & Bulk From Sparse First Principles Training Data

Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs depending on the cluster size; a knowledge of this size-dependent structural motifs and their dynamical evolution has been of longstanding interest. Given the high computational cost of first-principles calculations, molecular modeling and atomistic simulations such as molecular dynamics (MD) has proven to be an important complementary tool to aid this understanding. Classical MD typically employ predefined functional forms which limits their ability to capture such complex size-dependent structural and dynamical transformation. Neural Network (NN) based potentials represent flexible alternatives and in principle, well-trained NN potentials can provide high level of flexibility, transferability and accuracy on-par with the reference model used for training. A major challenge, however, is that NN models are interpolative and requires large quantities (similar to 10 4 or greater) of training data to ensure that the model adequately samples the energy landscape both near and far-from-equilibrium. A highly desirable goal is minimize the number of training data, especially if the underlying reference model is first-principles based and hence expensive. In this work, we introduce an active learning (AL) scheme that trains a NN model on-the-fly with minimal amount of first-principles based training data. Our AL workflow is initiated with a sparse training dataset (similar to 1 to 5 data points) and is updated on-the-fly via a Nested Ensemble Monte Carlo scheme that iteratively queries the energy landscape in regions of failure and updates the training pool to improve the network performance. Using a representative system of gold clusters, we demonstrate that our AL workflow can train a NN with similar to 500 total reference calculations. Using an extensive DFT test set of similar to 1100 configurations, we show that our AL-NN is able to accurately predict both the DFT energies and the forces for clusters of a myriad of different sizes. Our NN predictions are within 30 meV/atom and 40 meV/angstrom of the reference DFT calculations. Moreover, our AL-NN model also adequately captures the various size-dependent structural and dynamical properties of gold clusters in excellent agreement with DFT calculations and available experiments. We finally show that our AL-NN model also captures bulk properties reasonably well, even though they were not included in the training data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Global perspectives of the bulk electronic structure of URu 2 Si 2 from angle-resolved photoemission

Previous high-resolution angle-resolved photoemission (ARPES) studies of URu 2 Si 2 have characterized the temperature-dependent behavior of narrow-band states close to the Fermi level ( E F ) at low photon energies near the zone center, with an emphasis on electronic reconstruction due to Brillouin zone folding. A substantial challenge to a proper description is that these states interact with other hole-band states that are generally absent from bulk-sensitive soft x-ray ARPES measurements. Here we provide a more global k -space context for the presence of such states and their relation to the bulk Fermi surface (FS) topology using synchrotron-based wide-angle and photon energy-dependent ARPES mapping of the electronic structure using photon energies intermediate between the low-energy regime and the high-energy soft x-ray regime. Small-spot spatial dependence, f -resonant photoemission, Si 2 p core-levels, x-ray polarization, surface-dosing modification, and theoretical surface slab calculations are employed to assist identification of bulk versus surface state character of the E F -crossing bands and their relation to specific U- or Si-terminations of the cleaved surface. The bulk FS topology is critically compared to density functional theory (DFT) and to dynamical mean field theory calculations. In addition to clarifying some aspects of the previously measured high symmetry Γ, Z and X points, incommensurate 0.6 a * nested Fermi-edge states located along Z – N – Z are found to be distinctly different from the DFT FS prediction. The temperature evolution of these states above T HO , combined with a more detailed theoretical investigation of this region, suggests a key role of the N -point in the hidden order transition.

36 MATERIALS SCIENCE↗

Simulating Real Atmospheric Boundary Layers at Gray-Zone Resolutions: How Do Currently Available Turbulence Parameterizations Perform?

Recent computational and modeling advances have led a diverse modeling community to experiment with atmospheric boundary layer (ABL) simulations at subkilometer horizontal scales. Accurately parameterizing turbulence at these scales is a complex problem. The modeling solutions proposed to date are still in the development phase and remain largely unvalidated. This work assesses the performance of methods currently available in the Weather Research and Forecasting (WRF) model to represent ABL turbulence at a gray-zone grid spacing of 333 m. We consider three one-dimensional boundary layer parameterizations (MYNN, YSU and Shin-Hong) and coarse large-eddy simulations (LES). The reference dataset consists of five real-case simulations performed with WRF-LES nested down to 25 m. Results reveal that users should refrain from coarse LES and favor the scale-aware, Shin-Hong parameterization over traditional one-dimensional schemes. Overall, the spread in model performance is large for the cellular convection regime corresponding to the majority of our cases, with coarse LES overestimating turbulent energy across scales and YSU underestimating it and failing to reproduce its horizontal structure. Despite yielding the best results, the Shin-Hong scheme overestimates the effect of grid dependence on turbulent transport, highlighting the outstanding need for improved solutions to seamlessly parameterize turbulence across scales.

54 ENVIRONMENTAL SCIENCES↗

The effects of environmental conditions on eggshell thickness of two North American secondary cavity-nesting birds

Egg hatchability in birds is a critical component of individual reproductive success and is associated with eggshell integrity. Contaminants, such as DDT, can influence eggshell thickness and are known to cause population declines. Moisture content and temperature can also impact eggshell thickness, but the influence of environmental conditions on the natural variation in eggshell thickness in wild populations is not well understood. Our goal was to investigate the relationship between environmental conditions and eggshell thickness of Western Bluebird (Sialia mexicana) and Ash-throated Flycatcher (Myiarchus cinerascens) eggs from 1997 to 2013 on the Pajarito Plateau in northern New Mexico. We tested whether nesting elevation, temperature, precipitation, and drought conditions influenced eggshell thickness in these two secondary cavity-nesting species, while also looking at eggshell thickness over time. Over the 16 years, nonviable or abandoned eggs were collected, and the analyzed dataset included 330 bluebird eggs and 113 flycatcher eggs. There was a significant increase in eggshell thickness over time for both species. Flycatcher eggshells were correlated with higher temperatures, whereas bluebird eggshells were influenced by an interaction between temperature and drought severity. In drought conditions, bluebird eggshell thickness was positively correlated with temperature, whereas in wet conditions, eggshell thickness was negatively correlated with temperature. Thicker eggshells in drought conditions may be a way of reducing water loss from eggs, which occurs faster at higher temperatures. In the southwestern United States, frequent and severe drought, higher temperatures, and decreases in precipitation are all expected to continue. In conclusion, the structure of eggs will be important to consider regarding how species may or may not adapt to novel conditions or persist in new environments.

59 BASIC BIOLOGICAL SCIENCES↗

Propane Dehydrogenation on Pt x Zn y Active Sites in Silicalite‐1

Abstract The improvement of Pt‐based catalysts for propane dehydrogenation (PDH) has progressed by recent investigations that have identified Zn as a promising promoter for Pt subnanometer catalysts. It is desirable to gain insights into the structure, stability, and activity of such active sites and the factors that influence them, such as Zn : Pt ratio, Pt coordination and nuclearity. Here, we employ density functional theory and microkinetic simulations to investigate the stability of Pt x Zn y ( x =1–3, y=0–3) active sites grafted on silanols of Silicalite‐1 and the PDH activity of Pt. We find that the coordination of a Pt atom to a nest of grafted Zn(II) atoms increases the stability of the Pt 1 Zn y sites, whose activity is similar for y=0–2 and drops dramatically for y>2. We further demonstrate, via linear scaling relations and microkinetic simulations, that the turnover frequency obeys a volcano law as a function of propylene binding strength. The Pt 2 Zn 1 and Pt 3 Zn 1 sites are stable and exhibit activity similar to Pt 1 Zn 2 , but only Pt 1 Zn 2 manifests reaction kinetics consistent with experimental data, strongly suggesting the active site composition in the synthesized catalyst samples. The methodology presented here suggests a general strategy for deducing active site information such as composition through simple kinetic experiments.

Liu, Yilang↗