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At least 325 records · Page 18

Atmospheric Variability Drives Anomalies in the Bering Sea Air–Sea Heat Exchange

Abstract High latitudes, including the Bering Sea, are experiencing unprecedented rates of change. Long-term Bering Sea warming trends have been identified, and marine heatwaves (MHWs), event-scale elevated sea surface temperature (SST) extremes, have also increased in frequency and longevity in recent years. Recent work has shown that variability in air–sea coupling plays a dominant role in driving Bering Sea upper-ocean thermal variability and that surface forcing has driven an increase in the occurrence of positive ocean temperature anomalies since 2010. In this work, we characterize the drivers of the anomalous surface air–sea heat fluxes in the Bering Sea over the period 2010–22 using ERA5 fields. We show that the surface turbulent heat flux dominates the net surface heat flux variability from September to April and is primarily a result of near-surface air temperature and specific humidity anomalies. The airmass anomalies that account for the majority of the turbulent heat flux variability are a function of wind direction, with southerly (northerly) wind advecting anomalously warm (cool), moist (dry) air over the Bering Sea, resulting in positive (negative) surface turbulent flux anomalies. During the remaining months of the year, anomalies in the surface radiative fluxes account for the majority of the net surface heat flux variability and are a result of anomalous cloud coverage, anomalous lower-tropospheric virtual temperature, and sea ice coverage variability. Our results indicate that atmospheric variability drives much of the Bering Sea upper-ocean temperature variability through the mediation of the surface heat fluxes during the analysis period. Significance Statement A long-term ocean warming trend and a recent increase in marine heatwaves in the Bering Sea have been identified. Previous work showed that anomalies in the exchange of heat between the ocean and the atmosphere were the primary driver of Bering Sea temperature variability, but the processes responsible for the heat exchange anomalies were unknown. In this work, we show that the atmosphere is the primary driver of anomalies in the Bering Sea air–sea heat exchange and therefore plays an important role in altering the thermal state of the Bering Sea. Our results highlight the importance of understanding more about how the ocean and the atmosphere interact at high latitudes and how this relationship will be affected by future climate change.

Hayden, Emily E. [a College of Earth, Ocean, and A↗

Pb Sorption at the Barite (001)–Water Interface

Sorption of ions at the mineral-water interface is an important factor that determines the fate of toxic metals in the environment. Here, we use barite as a model substrate to understand the interaction of toxic-metal lead (Pb) with ionic crystals. The coverage and location of Pb sorbed to the (001) surface was measured as a function of aqueous Pb concentration ([Pb] aq ) using in situ specular resonant anomalous X-ray reflectivity (RAXR) to determine the sorption capacity and process. In this work, the results show that Pb sorption occurs via incorporation (primarily within the top barite layer similar to 3 angstrom in depth) and adsorption (mostly as an inner-sphere complex at similar to 2 angstrom in height) simultaneously. Both the incorporated and adsorbed Pb coverages increase with increasing [Pb] aq up to [Pb] aq similar to 200 mu M, above which the adsorbed fraction increases more rapidly than the incorporated fraction. This enhanced adsorption has a height distribution that is further extended (>= 15 angstrom from the surface) than that observed in lower [Pb] aq . This change in distribution is interpreted as arising from additional sorption of outer-sphere species or Pb-bearing phases precipitated on the surface. Desorption experiments in Pb-free solutions show that the incorporated fraction is more resistant to removal than the adsorbed fraction, consistent with the speciation-dependent stabilities premised in the classical sorption models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the Effects of the First Atomic Layer on the Dynamic Behavior of Sub-2 nm MgO/Al 2 O 3 Memristors

As electronic devices continue to scale down from the current sub-5 nm range, atomic-scale control of defects becomes increasingly crucial to suppressing their impact on the physical properties of the devices. Memristors present an excellent example as a nonlinear and dynamic device with high speed and endurance required for electronic applications ranging from neuromorphic computing to nonvolatile memories. Herein we investigate the impact of atomic defects in sub-2 nm thick MgO/Al 2 O 3 atomic layer stack (ALS) memristors that use an M1 (switching layer)/M2 (oxygen vacancy reservoir layer) bilayer structure grown using in vacuo atomic layer deposition (iALD). Intriguingly, we revealed a direct correlation of the atomic defects in the M2 layer with the memristor dynamic behavior using a combined analysis of in situ scanning tunneling spectroscopy (iSTS) on the M2 layer and ex situ characterization on the memristors. Specifically, incomplete coverage of the 1st ALD atomic layer of M2 on the electrode yields defects at the M2/electrode interface. Despite the monotonic increase of ALD coverage, by almost three-fold from ~30% to >90%, at completion of the M2 layer of ~ 0.7 nm in thickness, the impact of the defects on the M2/electrode interface has been found detrimental to both memristor switching speed and endurance. Guided by atomistic simulation, we addressed the issue of interface defects via tuning of the Al surface hydroxylation to increase the first atomic layer ALD coverage to ~75%, leading to improved memristor switching speed and endurance by several orders of magnitude. In conclusion, these findings shed light on the correlation between the atomic defects and the dynamic behavior of sub-2 nm memristors and the importance of minimizing the atomic defects in memristors for future electronic applications.

Atomic Layer Deposition↗

Influence of Lake Ice Biases in Reanalysis Data on Downscaled Climate Simulations over the Great Lakes Region

This data package contains observation-based and model-simulated datasets (all provided in NetCDF format) for evaluating how wintertime lake-ice representation affects regional weather and climate over the Laurentian Great Lakes (freshwater lake ecosystem) during the high–ice-cover winter of 2009. The observational component includes: (1) Stage IV gridded precipitation at 4 km, hourly resolution for January–February 2009 over the Great Lakes region (radar–gauge multisensor precipitation analyses); (2) Great Lakes Surface Environmental Analysis (GLSEA) satellite-derived lake-ice coverage at 1.3 km, daily resolution for the 2009 winter months, providing ice coverage over Lakes Superior, Michigan, Huron, Erie, and Ontario; and (3) in situ measurements at the Standard Rock site on Lake Superior from the Great Lakes Evaporation Network (GLEN) at hourly resolution, including near-surface atmospheric variables and sensible and latent heat fluxes (air–lake exchange) at a fixed point location. The modeling component provides corresponding fields from two simulations, both archived at 4 km, hourly resolution: a standalone Weather Research Forecasting model (WRF) run driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5), and a two-way coupled model using WRF and the Finite Volume Community Ocean Model (WRF-FVCOM, a 3-D hydrodynamic lake model). These outputs include variables relevant to air–lake interaction and lake-effect processes (e.g., near-surface temperature, humidity, wind, precipitation, and surface turbulent fluxes), enabling direct comparison with the observational datasets. Users can analyze and visualize these NetCDF files with common tools such as Python (e.g., xarray, netCDF4, numpy, pandas), NCO/CDO, Panoply, or ncview; NetCDF variables can also be converted to other formats (e.g., CSV, GeoTIFF) using these utilities.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗

Trivalent ion overcharging on electrified graphene

We report the structure of the electrical double layer (EDL) formed near graphene in aqueous environments strongly impacts its performance for a plethora of applications, including capacitive deionization. In particular, adsorption and organization of multivalent counterions near the graphene interface can promote nonclassical behaviors of EDL including overcharging followed by co-ion adsorption. In this paper, we characterize the EDL formed near an electrified graphene interface in dilute aqueous YCl 3 solution using in situ high resolution x-ray reflectivity (also known as crystal truncation rod) and resonant anomalous x-ray reflectivity (RAXR). These interface-specific techniques reveal the electron density profiles with molecular-scale resolution. We find that yttrium ions (Y 3+ ) readily adsorb to the negatively charged graphene surface to form an extended ion profile. This ion distribution resembles a classical diffuse layer but with a significantly high ion coverage, i.e., 1 Y 3+ per 11.4 ± 1.6 Å 2 , compared to the value calculated from the capacitance measured by cyclic voltammetry (1 Y 3+ per ~240 Å 2 ). Such overcharging can be explained by co-adsorption of chloride that effectively screens the excess positive charge. The adsorbed Y 3+ profile also shows a molecular-scale gap (≥ 5 Å) from the top graphene surfaces, which is attributed to the presence of intervening water molecules between the adsorbents and adsorbates as well as the lack of inner-sphere surface complexation on chemically inert graphene. We also demonstrate controlled adsorption by varying the applied potential and reveal consistent Y 3+ ion position with respect to the surface and increasing cation coverage with increasing the magnitude of the negative potential. This is the first experimental description of a model graphene-aqueous system with controlled potential and provides important insights into the application of graphene-based systems for enhanced and selective ion separations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

In-situ probing of the Fischer-Tropsch reaction on Co single crystal surfaces up to 1 bar

The surface chemistry of the Fischer-Tropsch catalytic reaction over Co has still several unknows. Here, we report an in-situ X-ray photoelectron spectroscopy study of Co$(0001)$ and Co$(10\bar{1}4)$, and in-situ high energy surface X-ray diffraction of Co$(0001)$ during the Fischer-Tropsch reaction at 0.15 bar - 1 bar and 406 K - 548 K in a H 2 /CO gas mixture. We find that these Co surfaces remain metallic under all conditions and that the coverage of chemisorbed species ranges from 0.4–1.7 monolayers depending on pressure and temperature. The adsorbates include CO on-top, C/-C x H y and various longer hydrocarbon molecules, indicating a rate-limiting direct CO dissociation pathway and that only hydrocarbon species participate in the chain growth. The accumulation of hydrocarbon species points to the termination step being rate-limiting also. Furthermore, we demonstrate that the intermediate surface species are highly dynamic, appearing and disappearing with time delays after rapid changes in the reactants’ composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.

54 ENVIRONMENTAL SCIENCES↗

Simulation of metal nanoparticles growth in methane atmosphere of arc discharge: comparison to experiment

A direct current arc discharge in a methane atmosphere is a scalable and sustainable method to produce metal-carbon core–shell nanoparticles and single-walled carbon nanotubes, where a metal catalyst can be continuously supplied through evaporation of an anode made from the catalyst material. The size of catalyst particles is of critical importance as it can affect the synthesis yield and properties of nanotubes and core–shell nanoparticles. This study presents a numerical model describing the formation and growth of metal particles for the conditions representative of the arc discharge with an evaporating iron anode at near-atmospheric pressure of a methane-rich atmosphere. The model incorporates carbon adsorption to the metal surface and explains the limiting effect of carbon coverage on the size of metal nanoparticles. The predicted particle sizes are compared with experimental observations. The model also predicts higher concentrations of metal particles with the increasing partial pressure of methane.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Understanding Subseasonal Moisture Recycling from Extreme MCSs Using a Land–Atmosphere Coupled Water Tracer Model

Extreme precipitation events often produce severe flooding and pose significant threats to our society. However, their subseasonal impacts on the terrestrial and atmospheric systems are not well understood. Here, we use a new land–atmosphere coupled water tracer tool embedded in the Weather Research and Forecasting (WRF) Model to “tag” precipitation produced by a series of extreme mesoscale convective systems (MCSs) in May 2015 over the southern Great Plains to reveal their contributions to different terrestrial water storages and moisture recycling during May–July. During May, we find that precipitation from earlier MCSs can contribute to 20%–50% of total evapotranspiration (ET) in later May and contribute ∼10% of local precipitation for later MCSs. After May, the water “tagged” to preceding May MCS events has the most active contribution to moisture recycling during the first 5 days in June, but this contribution diminishes quickly afterward. Both periods indicate a quick turnover of tagged precipitation, which may be representative of the southern Great Plains region. The quick turnover is closely associated with the direct evaporation from the soil surface due to the predominant shrubland and grassland coverage over this region. Over some forested areas, however, the tracer-ET flux is dominated by transpiration that stably supplies a small fraction (<1%) of moisture to the atmosphere throughout June and July. In conclusion, the tracer-contributed plume (through evaporation and transpiration) in atmospheric moisture can extend 500–700 km downstream between May and July, highlighting the far-reaching contribution to moisture recycling and precipitation from the tagged MCS events in the southern Great Plains.

Atmosphere-land interaction↗

CO adsorption on MnO(100): Experimental benchmarks compared to DFT

In this study, CO adsorption on the MnO(100) surface was studied using temperature programmed desorption (TPD) and density functional theory (DFT). TPD results show that CO is weakly-bound on MnO(100), with an experimental adsorption energy of -35.6 ± 2.1 kJ/mol at terrace sites in the low coverage limit. PBE simulations suggest that CO adsorption causes an implausible (2 × 2) surface reconstruction. PBE+U simulations show no signs of surface reconstruction, and provide an accurate estimate of the adsorption energy (-36.4 kJ/mol) when combined with the DFT-D3 method with Becke-Jonson damping to correct for van der Waals interactions. This simulation also shows that CO adsorbs C-down onto the Mn 2+ terrace site in a tilted geometry, which is also observed experimentally and computationally on the similarly-structured NiO(100) transition metal oxide surface. TPD results for large doses show a plateauing of the coverage at about 0.4 monolayers of CO at 85 K, with a defect coverage equivalent to 0.08 monolayers. Adsorption associated with defect sites is indicated by a high-temperature desorption tail which is not satisfactorily explained by DFT simulations of simple step or oxygen vacancy defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the interaction between carboxylates and coinage metals from first principles

Carboxylate groups have recently been explored as a new type of ligand to protect superatomic copper and silver nanoclusters, but little is known of the interfacial structure and bonding. Here, we employ density functional theory to investigate the interfaces of a model carboxylate group, CH3COO, on the coinage metal surfaces and clusters. We found that μ2-CH3COO is the most preferred binding mode on the three M(111) surfaces (M = Cu, Ag, and Au), while μ3-CH3COO is also stable on Cu(111) and Ag(111). The saturation coverage was found to be about seven CH3COO groups per nm2 for all surfaces. CH3COO has the strongest binding on Cu and weakest on Au. Moving from the flat surfaces to the icosahedral M13 clusters, we found that the eight-electron superatomic [M13(CH3COO)6]− nanoclusters also prefer the μ2-CH3COO mode on the surface. The icosahedral kernel in [Cu13(CH3COO)6]− and [Ag13(CH3COO)6]− was well maintained after geometry optimization, but a larger deformation was found in [Au13(CH3COO)6]−. Given the broad availability and variety of carboxylic acids including amino acids, our work suggests that carboxylate groups could be the next-generation ligands to further expand the universe of atomically precise metal clusters, especially for Cu and Ag.

Liu, Tongyu↗

Revealing the Predominant Surface Facets of Rough Cu Electrodes under Electrochemical Conditions

Metal electrodes with rough surfaces are frequently found to convert CO or CO 2 to hydrocarbons and oxygenates with high selectivity and at high reaction rates in comparison with their smooth counterparts. The atomic-level morphology of a rough electrode is likely one key factor responsible for its comparatively high catalytic selectivity and activity. However, few methods are capable of probing the atomic-level structure of rough metal electrodes under electrocatalytic conditions. As a result, the nuances in the atomic-level surface morphology that control the catalytic characteristics of these electrodes have remained largely unexplored. Because the C≡O stretching frequency of atop-bound CO (CO atop ) depends on the coordination of the underlying metal atom, the IR spectrum of this reaction intermediate on the copper electrode could, in principle, provide structural information about the catalytic surface during electrolysis. However, other effects, such as dynamic dipole coupling, easily obscure the dependence of the frequency on the surface morphology. Further, in the limit of low CO atop coverage, where coupling effects are small, the C≡O stretching frequencies of CO atop on Cu(111) and Cu(100) facets are virtually identical. Therefore, on the basis of the C≡O stretching frequency, it is not straightforward to distinguish between these two ubiquitous surface facets, which exhibit vastly different CO reduction activities. Herein, we show that key features of the atomic-level surface morphology of rough copper electrodes can be inferred from the potential dependence of the line shape of the C≡O stretching band of CO atop . Specifically, we compared two types of rough copper thin-film electrodes that are routinely employed in the context of surface-enhanced infrared absorption spectroscopy (SEIRAS). We found that copper films that are electrochemically deposited on Si-supported Au films (CuAu–Si) are poor catalysts for the reduction of CO to ethylene in comparison to copper films (Cu–Si) that are electrolessly deposited onto Si crystals. As quantified by differential electrochemical mass spectrometry (DEMS), the onset potential for ethylene is ~200 ± 65 mV more cathodic for CuAu–Si than that for Cu–Si. To reveal the origin of the disparate catalytic properties of Cu–Si and CuAu–Si, we probed the surfaces of the electrodes with cyclic voltammetry (CV) and SEIRAS. The CV characterization suggests that the (111) surface facet predominates on CuAu–Si, whereas the (100) facet is more common on Cu–Si. SEIRAS reveals that the line shape of the C≡O stretching of CO atop is composed of two bands that are attributable to CO atop on terrace and defect sites. The different surface structures manifest themselves in the form of starkly different potential dependences of the line shape of the C≡O stretching mode of CO atop on the two types of electrodes. With a simple Boltzmann model that considers the different adsorption energies of CO atop on terrace and defect sites, and the resulting CO atop populations on terrace and defect sites, we deduced that the observed electrode-specific potential dependence of the line shape is consistent with the presence of different predominant terrace sites on the two types of films. This strategy for assessing the atomic-level morphology is not restricted to SEIRAS but could also be applied to the C≡O stretching bands recorded with surface-enhanced Raman spectroscopy (SERS), which is suitable for probing a wide range of rough copper electrodes. Therefore, with this work, we establish the potential dependence of the C≡O stretching band of CO atop as a probe of the atomic-level surface structure of rough metal electrodes under electrochemical conditions. When it is coupled with complementary techniques, this methodology provides essential structural information for further improvement in the reaction selectivity of rough metal electrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts

Adsorbates often cover the surfaces of catalysts densely as they carry out reactions, dynamically altering their structure and reactivity. Understanding adsorbate-induced phenomena and harnessing them in our broader quest for improved catalysts is a substantial challenge that is only beginning to be addressed. Here, in this work, we chart a path toward a deeper understanding of such phenomena by focusing on emerging in silico modeling methodologies, which will increasingly incorporate machine learning techniques. We first examine how adsorption on catalyst surfaces can lead to local and even global structural changes spanning entire nanoparticles, and how this affects their reactivity. We then evaluate current efforts and the remaining challenges in developing robust and predictive simulations for modeling such behavior. Last, we provide our perspectives in four critical areas—integration of artificial intelligence, building robust catalysis informatics infrastructure, synergism with experimental characterization, and adaptive modeling frameworks—that we believe can help surmount the remaining challenges in rationally designing catalysts in light of these complex phenomena.

catalytic mechanisms↗

Cybersecurity for Distance Relay Protection

This project is a DOE follow-up effort on the CREDC workshop held on September 13, 2018 in Cambridge, MA to discuss cybersecurity of distance relays, which considered the benefits, vulnerabilities and risk mitigations for the use of communication systems in power system protection. The objectives of this project are to define the taxonomy of relay protection and associated communications; define use cases describing approaches to reduce the cyber-attack surface on those protective relays; and evaluate the loss of operational functional capability from changes to communication coverage. Mitigating controls will also be evaluated to understand if there are other approaches to reduce attack surfaces while maintaining communications or partial communications. Distance relays are used to protect transmission lines of approximately 10 to 300 miles in length, by detecting short circuits (i.e., faults) on the lines and then tripping circuit breakers in the substation. Such protection systems are a subset of the power system and they incorporate sensing, logic and communication functions. Protection system exposure to cyberattack could be drastically limited by disconnecting relays from all vulnerable communication systems, but this may adversely impact overall power system performance in the absence of cyberattack. This project began with a use case analysis of protection systems with communications, as summarized in this report. It continued with modeling, testing and evaluation in a miniature power system (MPS), located in the Western Area Power Administration (WAPA) Electric Power Training Center (EPTC). The project also incorporated feedback from two industry meetings held in February and September 2019. The suggested next steps account for and complement the work already underway with DOE/CESER funding: 1. Study the performance of LCD and PC vs. PUTT, which is less reliant on communication system performance and GPS timing references. The PUTT scheme could prove to be more resilient to cyberattack or communications-related disruption. It could also be more tolerant of message re-routing with SDN/SDR communication systems. On the other hand, it will be more vulnerable to false tripping during dynamic events or to loss of the voltage signal. The optimum choice of scheme may depend on the specific power system and risk assessment. This study could provide a new template for evaluation based on business functions. 2. Research and develop new methods to detect and monitor distributed physical attacks, possibly using drones, video sensors, thermal sensors, machine learning and other advanced techniques. This will help mitigate the impact of cyberattack on the protection system, and will also help mitigate the impact of wild fires. 3. Implement a scalable PKI for use in electric utility protection systems. This will encourage widespread adoption of secure authentication methods that are already available, but not widely used at present. This will help secure engineering access to the relays. 4. Investigate the use of SDN in combination with SDR to achieve better cybersecurity and electromagnetic security of the network, incorporating path variability. This would help secure both engineering access and peer-to-peer GOOSE messaging. 5. Perform additional testing, with operator evaluation of “red button” scenarios, PUTT vs. LCD, relay mis-operations, and other cyberattacks in the EPTC. This is an important advantage of testing in the EPTC rather than by computer simulation or even hardware-in-the-loop simulation; the EPTC is already dedicated to managing the situational awareness, operator response times and other human impacts. One of the project objectives was to settle on a common nomenclature for this problem space. We have concluded that the OSI layer model, supplemented by ANSI device numbers and other IEEE standards, is already well-accepted by the industry. The IEEE PSRC knowledge base provides a great deal of public information

24 POWER TRANSMISSION AND DISTRIBUTION↗

Elucidating the water–anatase TiO 2 (101) interface structure using infrared signatures and molecular dynamics

The structure and dynamics of water on solid surfaces critically affect the chemistry of materials in ambient and aqueous environments. Here, we investigate the hydrogen bonding network of water adsorbed on the majority (101) surface of anatase TiO 2 , a widely used photocatalyst, using polarization- and azimuth-resolved infrared spectroscopy combined with neural network potential molecular dynamics simulations. Our results show that one monolayer of water saturates the undercoordinated titanium (Ti 5c ) sites, forming one-dimensional chains of molecule hydrogen bonded to surface undercoordinated bridging oxygen (O 2c ) atoms. As the coverage increases, water adsorption on O 2c sites leads to significant restructuring of the water monolayer and the formation of a two-dimensional hydrogen bond network characterized by tightly bound pairs of water molecules on adjacent Ti 5c and O 2c sites. This structural motif likely persists at ambient conditions, influencing the reactions occurring there. In conclusion, the results reported here provide critical details of the structure of the water–anatase (101) interface that were previously hypothesized but unconfirmed experimentally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A simplified framework for prediction of sensor network coverage in real-time structural health monitoring of plate-like structures

In this article, the coverage area prediction of piezoelectric sensor network for detecting a specific type of under-surface crack in plate-like structures is addressed. In particular, this article proposes a simplified framework to estimate the coverage of any given sensor network arrangement when a critical defect is known. Based on numerical results from finite element methods (FEM), a simplified framework to estimate coverage area of any given network arrangement is developed. Using such a simplified framework, one can avoid time-consuming procedure of evaluating numerous FEM models in estimating sensor network coverage. Back-scatter fields of partial cracks are estimated using a proposed function, whose parameters are estimated from the results of a limited number of FEM simulations. The proposed function efficiently predicts the back-scattered field of any combination of transmitters and receivers for a given crack geometry. Superposition is used to estimate the coverage area of an arbitrary piezoelectric (e.g., PZT) sensor network. It is shown that the coverage area of a sensor network depends on both sensor network geometry and defect properties (e.g., crack inclination) and it is not necessarily a linear function of the number of sensors. Furthermore, it is shown that the network arrangement has an important effect on the geometry of the coverage area. Experimental results of a network of 14 PZTs in two clusters confirm the accuracy of the method.

Engineering↗

Density Functional Theory Investigation of Oxidation Intermediates on Gold and Gold–Silver Surfaces

Gold and gold-silver alloys can be active and selective oxidation catalysts. Previous work has suggested that O 2 dissociation occurs at bimetallic step sites on gold-silver alloys, but the site responsible for the rest of the reaction steps has not been studied. As a first step in gaining insight into this issue, in this work we investigated the adsorption of oxygen and other oxidation intermediates on the (111) and (211) facets of gold-silver alloys using density functional theory. Oxygen and silver coverage effects were analyzed, and different model structures were compared. We also examined the energy barriers for the diffusion of atomic oxygen to gain insight into O migration and spillover. On (111) surfaces, O adsorption is much stronger at low O coverage (less than 0.22 ML), while on (211) surfaces O is strongly bound at both high and low O coverage. O diffusion across the step is faster than diffusion along the step. Ag stabilizes O, both when directly bound to it and when in an adjacent site. Ag also reduces repulsive O-O interactions at low O coverage. Our calculated reaction barriers for O-assisted CH 3 O dehydrogenation suggest that reaction is faster on steps than on terraces. Overall, our findings suggest that spillover of O from Ag-rich steps to Au-rich terraces does not occur, and that oxidation reactions on gold-silver alloys occurs on step sites. More specifically, oxidation likely occurs either on Ag-rich step sites or on Au-rich step sites that are adjacent to Ag-rich step sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗