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At least 307 records · Page 17

In situ catalyst activation and regeneration enable energy-efficient high-current CO 2 reduction to ethanol-rich C 2+ mixtures

Electrochemical conversion of dissolved CO 2 in bicarbonate electrolytes, i.e., bicarbonate electrolysis, offers distinct advantages over gas diffusion electrode systems by enabling direct utilization of the CO 2 capture electrolyte while bypassing the energy-intensive CO 2 release step. However, bicarbonate electrolysis faces challenges such as CO 2 mass-transfer limitation, local pH-driven CO 2 depletion, and high cathodic potentials. The higher potential often causes catalyst surface reorganization, leading to a gradual loss of active sites and variations in selectivity during CO 2 reduction. Here, we report a directed, in situ activation and regeneration method that allows precatalysts to equilibrate under dynamic (pulsed) electrolysis conditions. We demonstrate in situ activation of a scalable Cu 2 O/Cu mesh that, under short-width (t = 4 s) pulsed electrolysis, provides stable mixed oxidation states of Cu, favoring the formation of an ethanol-rich crude mixture. The pulsed electrolysis waveform, consisting of six distinct segments, is tuned to form Cu + oxides, which are then reduced to generate local alkaline conditions favoring C–C coupling. This synergistic effect results in FEs of 73% for C2+ products and 39% for ethanol at an applied current density of −150 mA cm −2 and a cathodic potential of −1.45 V (vs. RHE). The overall half-cell energy efficiency is ∼30% for C 2+ products. The in situ Raman experiments confirm the role of pCO 2 R in dynamically regenerating Cu+-containing surface species during pulsed operation, thereby steering selectivity towards C 2+ products. A comprehensive multiscale, multiphysics model is developed to investigate the dynamic behavior of copper surface species (Cu, Cu + , and Cu 2+ ) and local microenvironmental conditions during the pCO 2 R. The results reveal that the coexistence of different copper oxidation states, especially the Cu+ intermediate, is critical in steering selectivity towards multicarbon (C 2+ ) products. The dynamic modulation of surface redox states via tailored pulsing strategies favors C–C coupling pathways by inducing localized alkaline conditions and stabilizing reactive intermediates. This work establishes a predictive modeling platform that links pulse waveform design with mechanistic insights into catalyst state evolution and product selectivity. Overall, this study provides valuable insights into the synergistic effect of in situ activation of pre-catalysts and pulsed electrolysis for higher selectivity towards C 2+ products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Light-induced electron dynamics of molecules in cavities: comparison of model Hamiltonians

The rapidly expanding field of polaritonic chemistry requires accurate theoretical simulations to understand new phenomena at the atomic scale. Computing the optoelectronic properties of molecules using established electronic structure methods is a careful balance of accuracy and computational expense, and expanding these methods to quantum electrodynamics to describe coupled cavity-molecule systems is an active topic of development. Key to these methods are the Hamiltonian operators representing the photon cavity modes. The recently introduced quantum electrodynamics time-dependent configuration interaction (QED-TDCI) method allows for the combination of electron dynamics simulations with quantum electrodynamics, enabling the simulation of time-dependent optoelectronic properties of cavity-molecule systems. Using this method, a comparison of two many-state QED Hamiltonians—the Pauli-Fierz and quantum Rabi model Hamiltonians—is presented, with a particular focus on time-dependent properties in applied electric fields.

Peyton, Benjamin G. (ORCID:0000000163190751)↗

A Perspective on the Successes of the NNSS Underground Test Area (UGTA) Activity - 20221

Between 1951 and 1992, 828 underground nuclear tests were performed at the Nevada National Security Site (NNSS). Underground testing was done in five major testing areas, which included (1) Frenchman Flat, (2) Rainier Mesa/Shoshone Mountain, (3) Yucca Flat/Climax Mine (4) Central Pahute Mesa, and (5) Western Pahute Mesa. About one third of the underground tests were detonated near, at or below the water table, and thus radioactive contamination was introduced to the groundwater system. The U.S. Department of Energy's Underground Test Area (UGTA) Activity was established in the late 1990's to address the fate and movement of residual radioactivity in groundwater, and characterize the risk that it may pose to NNSS workers and the offsite public. It has accomplished this goal through a process of iterative groundwater sampling and numerical groundwater flow and transport modeling, and long-term monitoring. The UGTA Activity draws on the expertise of scientists in the fields of geology, hydrology, radiochemistry, and risk assessment from the U.S. DOE staff, the lead contractor (currently Navarro) and many other organizations, in cooperation with the governing regulatory body, the State of Nevada's Division of Environmental Protection (NDEP). Los Alamos National Laboratory (LANL) is one of the participating research organizations involved with the UGTA Activity. Under the direction of DOE and the lead contractor, LANL's role in UGTA has evolved over time from an initial focus on geologic characterization, to conducting field and laboratory experiments, and finally to its current role of providing modeling and geochemistry expertise to characterize the rates and directions of groundwater and radionuclide movement. In its current role, LANL has either developed or provided the numerical tools for developing flow and transport models in each of the four major testing areas. In addition, LANL has provided an independent assessment of future groundwater flow and transport behavior through the analysis of naturally-occurring geochemical and isotopic tracers in groundwater. The five major testing areas are now in different stages of investigation or closure: (1) Frenchman Flat is in its fifth year of post closure modeling; (2) The Rainier Mesa/Shoshone Mountain Closure Report has been submitted to NDEP and is awaiting approval; (3) The Yucca Flat/Climax Mine Closure Report is under development; and (4) Central and (5) Western Pahute Mesa is still undergoing investigation and flow and transport model development. The success of the UGTA Activity in reaching or approaching closure in three of the five major testing areas is primarily due to the DoE's focus on regulatory closure requirements, but also is in part attributable to a rigorous internal review process and the involvement of NDEP and Nye County water professionals as participants and observers in the reviews. County and state involvement in the internal review process has promoted trust that the U.S. DOE is deeply committed to ensuring the present and future safely of NNSS workers and the surrounding communities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Natural Language Processing for Text Based Event Extraction: Identifying Events of Interest Related to Worldwide State-Sponsored Civil Nuclear Power

Beginning in FY20, SRNL was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development to develop a prototype natural language processing/natural language understating machine learning-based modeling and analysis pipeline to extract and forecast events of interest from massive open data sources. The working hypothesis within the approach is that contextual shifts in key words and phrases act as indicators of events of interest over time. Therefore, by identifying points in time where contextual shifts occur, events of interest can be extracted along with explicit and implicit connections of entities and activities. The development of the preliminary prototype pipeline proved successful, meriting further testing of the pipeline on more broad topical domains and in a worldwide data environment. Therefore, SRNL, in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, have continued development with a test case of identifying events of interest related to worldwide state-sponsored civil nuclear power in open data sources. In the first year of this follow-on effort, the team has curated domain-specific data corpuses using an automated scheme and applied the modeling and analysis pipeline. This robust, focused, and efficient approach consists of an ensemble of analyses applied to time dependent word embedding models that are trained on the data corpuses. In this report, the team has demonstrated the capability of the existing pipeline (as development has continued in parallel) by exploring several specific case-studies centered around Rosatom’s international activities regarding the planning, construction, operation, and/or shutdown of nuclear reactors. A basic timeline events has been generated by manually cataloging known “milestone” events that have occurred at reactors in Turkey, Finland, Hungary, and Egypt and compared with the output of the modeling pipeline. In this approach, the team has characterized the lead time using the prototype pipeline, as well as the ability to capture relevant information, which proved 100% successful. A deep dive example of the Akkuyu reactor (Turkey) is presented that shows the breadth of information that can be captured using the approach. In this case study, events were extracted pertaining to the planning/construction of Akkuyu including protests from the population, information campaigns in response to the protests, forged regulatory documents and lawsuits, budgetary/shareholder information, geopolitical tensions, and the various construction milestones. This has demonstrated the pipeline’s utility as a research aid or real-time event extraction tool, where summary-level information and detailed text extractions from millions of articles or Tweets across long time periods can be generated with significantly less effort than current techniques.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Direct Conversion of Methane to Ethylene and Acetylene over an Iron-Based Metal–Organic Framework

Conversion of methane (CH 4 ) to ethylene (C 2 H 4 ) and/or acetylene (C 2 H 2 ) enables routes to a wide range of products directly from natural gas. However, high reaction temperatures and pressures are often required to activate and convert CH 4 controllably, and separating C 2+ products from unreacted CH 4 can be challenging. Here, we report the direct conversion of CH 4 to C 2 H 4 and C 2 H 2 driven by non-thermal plasma under ambient (25 °C and 1 atm) and flow conditions over a metal–organic framework material, MFM-300(Fe). The selectivity for the formation of C 2 H 4 and C 2 H 2 reaches 96% with a high time yield of 334 μmol g cat –1 h –1 . At a conversion of 10%, the selectivity to C 2+ hydrocarbons and time yield exceed 98% and 2056 μmol g cat –1 h –1 , respectively, representing a new benchmark for conversion of CH 4 . In situ neutron powder diffraction, inelastic neutron scattering and solid-state nuclear magnetic resonance, electron paramagnetic resonance (EPR), and diffuse reflectance infrared Fourier transform spectroscopies, coupled with modeling studies, reveal the crucial role of Fe–O(H)–Fe sites in activating CH 4 and stabilizing reaction intermediates via the formation of an Fe–O(CH 3 )–Fe adduct. In addition, a cascade fixed-bed system has been developed to achieve online separation of C 2 H 4 and C 2 H 2 from unreacted CH 4 for direct use. Integrating the processes of CH 4 activation, conversion, and product separation within one system opens a new avenue for natural gas utility, bridging the gap between fundamental studies and practical applications in this area.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

External Magnetic Field Suppression of Carbon Diffusion in Iron

External magnetic fields reduce diffusion of carbon in BCC iron, but the physical mechanism is not understood. Using DFT calculations with magnetic moments sampled from a Heisenberg model, we calculate diffusivities of carbon in iron at high temperatures and with field. Our model reproduces the measured suppression of diffusivity from field. Here, we find that increasing magnetic disorder flattens the electron density of states compared with the ferromagnetic case, which distorts the octahedral cages around carbon, lowering the activation barrier to diffusion; an applied field reverses these trends.

36 MATERIALS SCIENCE↗

Artificial Iron Proteins: Modeling the Active Sites in Non-Heme Dioxygenases

An important class of non-heme dioxygenases contains a conserved Fe binding site that consists of a 2-His-1-carboxylate facial triad. Results from structural biology show that, in the resting state, these proteins are six-coordinate with aqua ligands occupying the remaining three coordination sites. Here, we have utilized biotin–streptavidin (Sav) technology to design new artificial Fe proteins (ArMs) that have many of the same structural features found within active sites of these non-heme dioxygenases. An Sav variant was isolated that contains the S 112 E mutation, which installed a carboxylate side chain in the appropriate position to bind to a synthetic Fe II complex confined within Sav. Structural studies using X-ray diffraction (XRD) methods revealed a facial triad binding site that is composed of two N donors from the biotinylated ligand and the monodentate coordination of the carboxylate from S 112 E. Two aqua ligands complete the primary coordination sphere of the Fe II center with both involved in hydrogen bond networks within Sav. The corresponding Fe III protein was also prepared and structurally characterized to show a six-coordinate complex with two exogenous acetato ligands. The Fe III protein was further shown to bind an exogenous azido ligand through replacement of one acetato ligand. Spectroscopic studies of the ArMs in solution support the results found by XRD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation into Na and Cs activity coefficients in high salt solutions to support Cs removal in Hanford tank waste

The treatment of Hanford tank waste is one of the most technically challenging environmental cleanup activities for the U.S. Department of Energy to date. To expedite the processing of liquid waste stored in underground tanks in southeastern Washington state, it is necessary to remove the significant dose contributor, 137 Cs. Toward this effort, ion exchange with crystalline silicotitanate (CST) has been employed as part of the Tank Side Cesium Removal system. The model used to predict Cs exchange onto CST was developed using activity coefficients calculated from the Bromley equation. A series of batch contact tests that varied in [Na] were conducted to look at the impact of Na concentration on Cs distribution. Experimental distribution ratios ( K d ) were compared to the distribution ratios predicted using three different activity coefficient models: (1) commercially available HSC software, (2) the Bromley equation, and (3) a simplified approach adapted from Marcos-Arroyo et al. Ultimately, the Bromley method underpredicted the effect of ionic strength on the Na activity coefficient ( γ Na+ ), HSC overestimated the impact of ionic strength on the expected performance due to the Cs activity coefficient ( γ Cs+ ), but the simplified approach predicted the experimental K d values quite well in a binary matrix. In conclusion, expansion of this approach in complex matrices is necessary for application to Hanford tank waste.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Widespread Wildfires Over the Western United States in 2020 Linked to Emissions Reductions During COVID-19

Widespread wildfires struck western United States in 2020, directly damaging properties and threatening human lives. Meanwhile, the COVID-19 pandemic rapidly spread across the globe in 2020, which disrupted human activities and resulted in substantial reductions in anthropogenic emissions. Here, we investigate the effects of the emissions reductions of aerosols, precursors, and greenhouse gases during the pandemic on wildfire weather conditions in 2020 over western United States by using an earth system model together with observational data. We show that the COVID-19 emissions reductions in model experiments increased surface air temperature and decreased precipitation and relative humidity due to a weakened moisture transport, which explains 10-40% of the observed increase in the risk of wildfires over western United States in 2020. In conclusion, this study suggests that COVID-19-related abrupt emissions reductions have an unexpected influence on wildfires, highlighting a different but important role of human activities in affecting wildfire risks.

54 ENVIRONMENTAL SCIENCES↗

A general mechanistic framework for cross-scale understanding of hot spots and hot moments in carbon and water fluxes

Semi-arid ecosystems, like those in the American Southwest, exert a massive impact on the interannual variability of carbon and water cycling. Unfortunately, these carbon and water fluxes are notoriously difficult to predict due to their high spatial and temporal variability, which is poorly captured by the current generation of vegetation models. Indeed, this region is exemplified by the ‘hot spots and hot moments’ concept, which states that small areas in space (‘hot spots’) and transient moments in time (‘hot moments’) exert an outsized influence on biogeochemical cycling. However, the factors that regulate these pulses in biogeochemical activity are unknown, as is their variability across space and time. These uncertainties severely limit efforts to better represent hot spots and hot moments in models. Here, we seek to develop a generalized method for detecting and quantifying the importance of hot spots and hot moments from individual plant to regional scales. Underpinning this method is our recently developed statistical approach for identifying hot spots and hot moments. By applying this method to semi-continuous measurements of plant water status, a depth profile of soil water potential, and ecosystem fluxes via eddy covariance, we will track the fate of water through the soil-plant-atmosphere continuum and identify the mechanistic drivers of these transient pulses in biogeochemical activity. Then, we will expand this approach across a broad network of Ameriflux towers, and apply a machine learning approach that will allow us to upscale measurements of hot spots and hot moments across the American Southwest and quantify their impact on carbon and water cycles. These products will allow us to identify hot spots and hot moments across spatio-temporal scales and will serve as crucial data sources for validating a new generation of models that can better capture highly dynamic carbon and water fluxes. The proposed method will be easily transferable across biomes and will serve as a framework for future research on hot spots and hot moments across the plant ecophysiology, biometeorology, and vegetation modeling communities.

54 ENVIRONMENTAL SCIENCES↗

Using ethanol and isopropanol as biomass model compounds for understanding bond scission mechanisms over Cu/Mo 2 N catalysts

The conversion of biomass compounds into fuels and chemicals is an important step towards a more sustainable future. This work combines results from model surfaces and powder catalysts to demonstrate Cu-modified mo- lybdenum nitride (Cu/Mo 2 N) as a selective catalyst for dehydrogenation of the biomass model compounds, ethanol and isopropanol. Results from model surfaces showed that while Mo2N led to unselective decomposition via both dehydrogenation and dehydration, the addition of Cu increased the dehydrogenation activity and selectivity. DFT calculations showed how Cu influenced the structures of active sites, adsorbate interactions, and thus the product selectivity. Batch reactor studies on corresponding powder catalysts confirmed the trend that Cu modification increased dehydrogenation activity, and in situ X-ray absorption spectroscopy elucidated the Cu oxidation state under reaction conditions. Further, this work demonstrates a strategy for promoting dehydrogenation over Mo 2 N-based catalysts, as well as the feasibility of using model surfaces to guide the design of industrially relevant catalysts.

09 BIOMASS FUELS↗

A Right-handed neutrino portal to the hidden sector: active neutrinos and their twins in an F-theory model

We analyze the neutrino phenomenology in an SU(5) F-theory model with both a visible sector and a twin hidden sector. At low energies, the strong and weak scales of the two sectors may differ but the spectrum of states is described by the MSSM (MSSM') in the visible (twin) sectors. What is special about the model is that there are right-handed neutrinos which couple to both sectors via Yukawa couplings. As a result, assuming 3 right-handed neutrinos with a large mass much greater than the weak scale, at tree-level the seesaw mechanism results in 3 massive Majorana neutrinos and 3 massless ones. The massless neutrinos acquire mass via radiative corrections. In our analysis, the massless neutrinos are predominantly active neutrinos, while the massive neutrinos are predominantly sterile neutrinos. We fit the active neutrino masses and mixing angles and discuss the phenomenology of the lightest sterile neutrino. Finally we consider some possible scenarios for cosmology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations

Immersion freezing, initiated by ice-nucleating particles (INPs) in supercooled aqueous droplets, plays an important role in the formation of ice crystals within clouds. The efficiency of immersion freezing depends strongly on INP composition and, crucially, on the mixing state – how chemical species are distributed across the particle population. Here, we quantify the impact of aerosol mixing state on immersion freezing using a combined theoretical and particle-resolved modeling approach. We derive analytical expressions for the frozen fraction of internally and externally mixed INP populations based on classical nucleation theory, showing that the frozen fraction is sensitive to whether ice-active species are present in all particles or only in a subset of the population. We introduce a multi-species immersion freezing scheme into the particle-resolved model PartMC, using the water activity-based immersion freezing model (ABIFM) to compute freezing probabilities for mixed-composition particles. To improve computational efficiency, we implement a Binned Tau-Leaping algorithm and demonstrate an order-of-magnitude speedup with minimal accuracy loss. Simulations reproduce the analytical trends in limiting cases and extend the analysis to more general aerosol populations, where mixing state continues to exert a substantial control on frozen fraction. Sensitivity analyses across particle size, species type, and cooling condition reveal that the mixing state effect is most pronounced when small amounts of highly efficient INPs are mixed with less efficient materials. These findings underscore the need to represent aerosol mixing state explicitly in models of heterogeneous ice nucleation to reduce uncertainty in cloud-phase partitioning.

54 ENVIRONMENTAL SCIENCES↗

Real-Time Atomic-Scale Structural Analysis Resolves the Amorphous to Crystalline CaCO 3 Mechanism Controversy

Amorphous calcium carbonate (ACC) occurs as a precursor to geological and biogenic calcium carbonate (CaCO 3 ), yet its transformation pathways and reaction mechanisms remain inconsistent and controversial. In this study, we investigated the transformation of ACC to calcite under both solution and dry conditions, in the presence and absence of impurity ions, utilizing operando time-resolved synchrotron X-ray diffraction (TRXRD) and reactive transport modeling. Results demonstrate that TRXRD techniques allow us to differentiate dissolution-reprecipitation versus solid-state transformation mechanisms for amorphous to crystalline phase transitions. Specifically, we observe that in environments with abundant water, ACC transforms to calcite through a dissolution-reprecipitation mechanism. This features an activation energy of 63 ± 2 kJ/mol and unit cell volume contraction during calcite crystal growth. Conversely, under water-limited conditions, ACC to calcite transformation proceeds via a solid-state transformation mechanism, with an activation energy of 210 ± 2 kJ/mol, three times greater than the dissolution-reprecipitation route, and a unit cell expansion during crystalline calcite growth. Further, to illustrate the magnitude of these effects, the rates of calcite growth were similar during dissolution-reprecipitation at 3 °C [0.00207(35) s –1 ] and solid-state transformation at 280 °C [0.00134(11) s –1 ]. Moreover, the incorporation of an impurity, strontium, significantly retards the rate of calcite growth while expanding its unit cell but whose incorporation is history dependent. Reactive transport modeling of the dissolution–precipitation kinetics suggests that ACC must be dissolving as compact aggregates. These various transformation mechanisms drive diverse geological and biological carbonate formations, impacting their use as paleoenvironmental markers and functional materials synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Access to Ru(IV)–Ru(V) and Ru(V)–Ru(VI) Redox in Layered Li 7 RuO 6 via Intercalation Reactions

The push to increase the capacity of oxides to store charge as Li-ion battery cathodes has challenged our knowledge of the boundaries of redox chemistry and its relationship to the atomic structure. Layered phases with Ru are now classical models in the quest for refined theories. Current understanding dictates that the highest formal state that can be reached in them is Ru(V), after which activity centered at the oxide anions is triggered. Yet, this picture is challenged by this investigation of the intercalation chemistry of Li 7 RuO 6 . Coupling structural and spectroscopic analysis with computational simulations, we show that Li 7 RuO 6 is capable of highly reversible lithiation to Li 8 RuO 6 through the Ru(V)/Ru(IV) redox couple. Further, Li 7 RuO 6 can also undergo anodic Li deintercalation, showing clear evidence of the reversible formation of Ru(VI) with octahedral coordination, an unusual state that is not accessible in other layered oxides. The results highlight the versatility of the Ru-O bond to undergo distinct redox transitions depending on the specific layered arrangements. They enrich our understanding of redox chemistry in solids while underscoring the need for descriptions of charge compensation that reflect the nuance of covalent interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carrier capture and emission by substitutional carbon impurities in GaN vertical diodes

A model was developed for the operation of a GaN pn junction vertical diode which includes rate equations for carrier capture and thermally activated emission by substitutional carbon impurities and carrier generation by ionizing radiation. The model was used to simulate the effect of ionizing radiation on the charge state of carbon. These simulations predict that with no applied bias, carbon is negatively charged in the n-doped layer, thereby compensating n-doping as experimentally observed in diodes grown by metal-organic chemical vapor deposition. With reverse bias, carbon remains negative in the depletion region, i.e., compensation persists in the absence of ionization but is neutralized by exposure to ionizing radiation. This increases charge density in the depletion region, decreases the depletion width, and increases the capacitance. The predicted increase in capacitance was experimentally observed using a pulsed 70 keV electron beam as the source of ionization. In additional confirming experiments, the carbon charge-state conversion was accomplished by photoionization using sub-bandgap light or by the capture of holes under forward bias.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

In situ ambient pressure XPS study of Pt/Cu(111) single-atom alloy in catalytically relevant reaction conditions

The presence of multiple reactant gases as well as reaction intermediates in a heterogeneous catalytic reaction results in a complex interaction between different components of the catalyst with each gas, which can alter the surface and chemical state of the catalyst differently than in the presence of an individual gas alone. In this study, we used in situ ambient pressure x-ray photoelectron spectroscopy to study the surface state of Pt/Cu(111) single-atom alloy model system in two catalytically relevant reaction conditions: CO 2 hydrogenation and CO oxidation. We found that the activation of CO 2 results in the formation of CO, which adsorbs on Pt sites at up to 400 K. In the presence of CO 2 and H 2 , Pt catalyzes the reverse water–gas shift reaction, which produces more CO and further stabilizes surface Pt atoms at 450 K. On the other hand, in CO oxidation condition, the presence of O 2 results in the formation of a thick Cu 2 O layer at higher temperatures, and Pt atoms are no longer detected in the surface and subsurface layers. When O 2 is introduced to the sample before CO, the formation of a complete Cu 2 O layer that covers all Pt atoms occurs immediately at room temperature. Finally, however, when CO is introduced at room temperature before O 2 , the presence of adsorbed CO on Pt sites stabilizes the surface Pt atoms and prevents the formation of a complete Cu 2 O layer, thus exposing the Pt atoms in 'holes' in the Cu 2 O layer.

36 MATERIALS SCIENCE↗