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CsO x Nanostructures on Au(111): Morphology- and Size-dependent Activity for the Water–Gas Shift Reaction

Alkali oxides are typically used as promoters of heterogeneous catalysts for the water–gas shift (WGS; H 2 O + CO → H 2 + CO 2 ) reaction. On Au(111), CsO x exhibits diverse nanostructures at varying coverages, as revealed by scanning tunneling microscopy. Clusters of cesium oxide (Cs 2 O 2 ) nucleate at elbow sites of the Au(111) herringbone when θ Cs is less than 0.1 ML. Subsequently, these clusters transform into two-dimensional (2D) islands (Cs 2 O, Cs 2 O 2 , CsO 2 ) as the cesium coverage increases (θ Cs > 0.1 ML). Both types of CsO x nanostructures enable the WGS process on Au(111). The highest activity was seen for the cesium oxide clusters which facilitated the partial dissociation of water and binding of CO. The CO ads and OH ads groups were not strongly bound and probably reacted to yield a short-lived HOCO intermediate that led to gaseous H 2 and CO 2 . The 2D islands of CsO x also enabled the WGS but their efficiency was reduced due to the formation of cesium hydroxide compounds (limiting mobility of OH groups) and the generation of CO 3 and C species (blocking of active centers). The fact that the performance of the CsO x /Au(111) catalysts changed dramatically with variations in the chemical properties of the CsO x nanostructures indicates that the alkali oxide was an integral part of the active phase, playing a central role in the activation and conversion of the reactants. To attach the label of “promoter” to CsO x is a simplification that does not help in the design and optimization of catalysts for C1 chemistry. In conclusion, to achieve a rational design, one must consider the structural and chemical properties of the alkali oxide.

36 MATERIALS SCIENCE↗

Low thermal conductivity in Bi 8 CsO 8 SeX 7 (X = Cl, Br) by combining different structural motifs

Understanding the structure–property relationships of materials in order to supress thermal conductivity is crucial for developing efficient thermoelectric generators and thermal barrier coatings. Low thermal conductivity materials can often contain a single dominant phonon scattering mechanism. Here, we highlight how combining different structural features into one material can aid in the design and identification of new materials with low thermal conductivities. We synthesise two new mixed-anion materials, Bi 8 CsO 8 SeX 7 (X = Cl and Br), with low thermal conductivities of 0.27(2) and 0.22(2) W m -1 K -1 respectively, measured along their c-axes at room temperature. The Bi 8 CsO 8 SeX 7 materials possess a combination of bond strength hierarchies, Cs + vacancies, and low frequency Cs + rattling. These different features significantly inhibit phonon transport along different crystallographic directions. Due to sharp bond strength contrast between the van der Waals gaps and [Bi 2 O 2 ] 2+ layers, the Bi 8 CsO 8 SeX 7 materials exhibit thermal conductivities <50% of the theoretical minimum when measured along the stacking direction. Conversely, the thermal conductivity associated with the ab-plane is reduced by Cs + rattling when compared to the structurally and compositionally related BiOCl.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Materials Data on CSO by Materials Project

CSO crystallizes in the trigonal R3m space group. The structure is one-dimensional and consists of three CSO ribbons oriented in the (0, 0, 1) direction. C4+ is bonded in a distorted linear geometry to one S2- and one O2- atom. The C–S bond length is 1.56 Å. The C–O bond length is 1.18 Å. S2- is bonded in a linear geometry to one C4+ and one O2- atom. The S–O bond length is 3.34 Å. O2- is bonded in a single-bond geometry to one C4+ and one S2- atom.

36 MATERIALS SCIENCE↗

Materials Data on CSO by Materials Project

CSO crystallizes in the triclinic P1 space group. The structure is one-dimensional and consists of one CSO ribbon oriented in the (1, 1, 1) direction. C4+ is bonded in a distorted linear geometry to one S2- and one O2- atom. The C–S bond length is 1.56 Å. The C–O bond length is 1.18 Å. S2- is bonded in a 2-coordinate geometry to one C4+ and one O2- atom. The S–O bond length is 3.22 Å. O2- is bonded in a single-bond geometry to one C4+ and one S2- atom.

36 MATERIALS SCIENCE↗

Morphology Dependent Reactivity of CsO $x$ Nanostructures on Au(111): Binding and Hydrogenation of CO 2 to HCOOH

Cesium oxide (CsO $x$ ) nanostructures grown on Au(111) behave as active centers for CO 2 binding and hydrogenation reactions. The morphology and reactivity of these CsO $x$ systems were investigated as a function of alkali coverage using scanning tunnelling microscopy (STM), ambient pressure X-ray photoelectron spectroscopy (AP-XPS), and density functional theory (DFT) calculations. STM results show that initially (0.05 - 0.10 ML) cesium oxide clusters (Cs 2 O 2 ) grow at the elbow sites of the herringbone of Au(111), subsequently transforming into two-dimensional islands with increasing cesium coverage (> 0.15 ML). XPS measurements reveal the presence of suboxidic (Cs $y$ O; $y$ ≥ 2) species for the island structures. The higher coverages of cesium oxide nanostructures contain a lower O/Cs ratio resulting in a stronger binding of CO 2 . Moreover, the O atoms in the Cs $y$ O structure undergo a rearrangement upon the adsorption of CO 2 which is a reversible phenomenon. Under CO 2 hydrogenation conditions, the small Cs 2 O 2 clusters are hydroxylated, thereby preventing the adsorption of CO 2 . However, the hydroxylation of the higher coverages of Cs $y$ O did not prevent CO 2 adsorption, and the adsorbed CO 2 transformed to HCOO species that eventually yield HCOOH. DFT calculations further confirm that the dissociated H 2 attacks the C in the adsorbate to produce formate, which is both thermodynamically and kinetically favored during the CO 2 reaction with hydroxylated Cs $y$ O. These results demonstrate that cesium oxide by itself is an excellent catalyst for CO 2 hydrogenation that could produce formate, an important intermediate for the generation of value-added species. The role of the alkali oxide nanostructures as active centers, not merely as promoters, may have broad implications wherein the alkali oxides can be considered in the design of materials tuned for specific applications in heterogeneous catalysis.

03 NATURAL GAS↗

A comparison of compact, presumably young with extended, evolved radio active galactic nuclei

Context.The triggering and evolution of active galactic nuclei (AGNs) and the interaction of the AGN with its host galaxy is an important topic in extragalactic astrophysics. Radio sources with peaked spectra (peaked spectrum sources, PSS) and compact symmetric objects (CSO) are powerful, compact, and presumably young AGNs and therefore particularly suitable to study aspects of the AGN-host connection. Aims.We use a statistical approach to investigate properties of a PSS-CSO sample that are related to host galaxies and could potentially shed light on the link between host galaxies and AGNs. The main goal is to compare the PSS-CSO sample with a matching comparison sample of extended sources (ECS) to see if the two have significant differences. Methods.We analysed composite spectra, diagnostic line diagrams, multi-band spectral energy distributions (MBSEDs), star formation (SF) indicators, morphologies, and cluster environments for a sample of 121 PSSs and CSOs for which spectra are available from the Sloan Digital Sky Survey (SDSS). The statistical results were compared with those of the ECS sample, where we generally considered the two subsamples of quasi-stellar objects (QSOs) and radio galaxies separately. The analysis is based on a large set of archival data in the spectral range from the ultraviolet to mid-infrared. Results.We find significant differences between the PSS-CSO and the ECS sample. In particular, we find that the ECS sample has a higher proportion of passive galaxies with a lower star formation activity. This applies to both sub-samples (QSOs or radio galaxies) as well as to the entire sample. The star formation rates of the PSS-CSO host galaxies with available data are typically in the range ∼0 to 5 ℳ ⊙ yr −1 , and the stellar masses are in the range 3 × 10 11 to 10 12 ℳ ⊙ . Secondly, in agreement with previous results, we find a remarkably high proportion of PSS-CSO host galaxies with merger signatures. The merger fraction of the PSS-CSO sample is 0.61 ± 0.07, which is significantly higher than that of the comparison sample (0.15 ± 0.06). We suggest that this difference can be explained by assuming that the majority of the PSSs and CSOs cannot evolve to extended radio sources and are therefore not represented in our comparison sample.

Astronomy & Astrophysics↗

A Predictive Prescription Framework for Stochastic Unit Commitment Using Boosting Ensemble Learning Algorithms

To take unit commitment (UC) decisions under uncertain load, most existing stochastic optimization (SO) frameworks adopt a generic representation of uncertainty. While load levels that materialize on a particular day are influenced by various covariates (such as the day of the week or temperature), SO frameworks typically disregard such side observations, wasting actionable information that could significantly enhance decision quality. Here, this article proposes a contextual SO (CSO) framework for UC under uncertain load, which can effectively exploit covariate observations in conjunction with a class of machine learning (ML) algorithms to improve the out-of-sample performance of UC decisions. It shows how three ML algorithms, adaptive boosting, gradient boosted trees, and extreme gradient boosting, can be used to this end, constituting the first application of these algorithms in any CSO framework. Using real-world data harvested from the New York ISO grid, we measure the out-of-sample performance of the framework in terms of total operation cost, shed load values, locational marginal prices, and total payments by the loads, against several benchmark methods proposed in the literature. The article has an online companion (Yurdakul et al.), wherein we present additional results and lay out further mathematical formulations used in this work.

42 ENGINEERING↗

Motivation and Design of the OCPP Security Service

Pacific Northwest National Laboratory is conducting in-depth research aimed at exploring how zero trust security principles can be effectively applied to electric vehicle charging infrastructure. This investigation seeks to enhance the resilience and reliability of these systems against cyber threats, ensuring secure and uninterrupted access to charging services for electric vehicle users and electric supply. Zero trust is a security concept centered on the belief that system operators should not automatically trust users or systems based on their location, whether inside or outside the organization, but instead must verify everything trying to connect to their systems before granting access. A key aspect of the project is to demonstrate and validate zero trust approaches targeted to electric vehicle (EV) charging infrastructure. It has been observed that both open-source and commercial solutions often overlook the specific protocols employed in managing EV charging stations and proceeded with a general, protocol-agnostic approach. While these strategies effectively block non-authorized routes to the charging infrastructure, they do not tackle the situations where attackers may exploit legitimate access channels, such as the inattentive operator model posited by the Idaho National Laboratory. To address this gap, this paper proposes and discusses a new security service targeted to the Open Charge Point Protocol (OCPP), which is the de facto protocol for the management of charging stations and serves a critical role in the broader adoption of electric vehicles. The design and architecture of the proposed OCPP security service are discussed in detail, outlining how it aims to safeguard charging station management system (CSMS) functions. The service is particularly important in scenarios where the charging station operator (CSO), responsible for the maintenance and operation of charging stations, and the charging network provider (CNP), which manages the charging network's accessibility and billing, are separate entities. This distinction is crucial because CSOs and CNPs often have different priorities, objectives, and operational responsibilities, which may not always align perfectly. For instance, a CSO might prioritize uptime and customer satisfaction, while a CNP might focus on maximizing revenue and network utilization. Such misalignment can create security vulnerabilities, as each entity might implement different policies and standards, potentially leaving gaps in the overall security posture.

33 ADVANCED PROPULSION SYSTEMS↗

CalderaCast User Manual Version 1.0

CalderaCast is a user-friendly web-based tool for electrical-load forecast, providing stakeholders with a fully customizable decision-support framework that estimates the likely power draw from a possible future electric-vehicle (EV) charging station at a given location on a given day along an alternative fuel corridor (AFC). These EV charging profiles are accurately modeled in CalderaCast using the Caldera software framework developed by Idaho National Laboratories (INL), reflecting the realistic charging levels observed in actual charge events. This tool was developed as part of the National Electric Vehicle Infrastructure (NEVI) program, which is quickly generating substantial interest from would-be charging station operators (CSO), large and small electric utilities, and state transportation planners, some of whom had not seriously considered EV charging previously. All these entities—with or without background in EV infrastructure—must estimate the electricity load that a proposed charging station will generate. This load forecast is critically important for a utility to properly assess the capacity of their distribution network to support the proposed station or properly size grid upgrades for potential load growth due to future EV adoption, vehicle technology improvements, or station growth. This document describes each aspect of the CalderaCast tool and provides guidance to users who are interested in utilizing the tool for their work.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Assimilation of citizen science data in snowpack modeling using a new snow data set: Community Snow Observations

A physically based snowpack evolution and redistribution model was used to test the effectiveness of assimilating crowd-sourced snow depth measurements collected by citizen scientists. The Community Snow Observations project gathers, stores, and distributes measurements of snow depth recorded by recreational users and snow professionals in high mountain environments. These citizen science measurements are valuable since they come from terrain that is relatively undersampled and can offer in situ snow information in locations where snow information is sparse or nonexistent. The present study investigates (1) the improvements to model performance when citizen science measurements are assimilated, and (2) the number of measurements necessary to obtain those improvements. Model performance is assessed by comparing time series of observed (snow pillow) and modeled snow water equivalent values, by comparing spatially distributed maps of observed (remotely sensed) and modeled snow depth, and by comparing fieldwork results from within the study area. The results demonstrate that few citizen science measurements are needed to obtain improvements in model performance, and these improvements are found in 62 % to 78 % of the ensemble simulations, depending on the model year. Model estimations of total water volume from a subregion of the study area also demonstrate improvements in accuracy after CSO measurements have been assimilated. These results suggest that even modest measurement efforts by citizen scientists have the potential to improve efforts to model snowpack processes in high mountain environments, with implications for water resource management and process-based snow modeling.

54 ENVIRONMENTAL SCIENCES↗