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At least 1,135 records · Page 63

Multi-Scale Modeling for Plasma-Enhanced Ammonia Decomposition over Carbides and Nitrides

Ammonia is a carbon-free hydrogen carrier, but its decomposition typically requires high temperatures over costly Ru-based catalysts due to the large barrier for N≡N bond formation. We develop a multiscale framework combining density functional theory, zero-dimensional plasma kinetics, and microkinetic modeling to elucidate how non-thermal plasma (NTP) enables low-temperature NH 3 decomposition over Co-based carbides and nitrides, benchmarked against Ru and Co. Under thermal conditions, all catalysts are limited by N≡N bond formation, with Co 3 C(001) most active owing to its negatively charged surface, strong N* binding, and low activation barriers of N≡N bond formation. Plasma-induced vibrational excitation of NH 3 and its reactive radicals promotes a radical-driven •NH 2 –N* coupling pathway that dominates on Co 3 C(001) and Co 3 N(001), shifting the rate-limiting step to NH 3 (v1) dissociation, increasing turnover frequencies by up to 6 orders of magnitude, and reducing the temperature needed to reach a turnover frequency of 5 s –1 from >680 °C (Ru and Co under thermal condition) to 267 °C (Co 3 C) and 415 °C (Co 3 N). These results identify Co-based carbides and nitrides as promising plasma-active catalysts for energy-efficient hydrogen production from ammonia.

ammonia decomposition↗

Engineering the radiative dynamics of thermalized excitons with metal interfaces

As a platform for optoelectronic devices based on exciton dynamics, monolayer transition metal dichalcogenides (TMDCs) are often placed near metal interfaces or inside planar cavities. While the radiative properties of point dipoles at metal interfaces has been studied extensively, those of excitons, which are delocalized and exhibit a temperature-dependent momentum distribution, lack a thorough treatment. Here, we analyze the emission properties of excitons in TMDCs near planar metal interfaces and explore their dependence on exciton center-of-mass momentum, transition dipole orientation, and temperature. Defining a characteristic energy scale k B T c = ($\hbar k$) 2 /2m (k being the radiative wavevector and m the exciton mass), we find that at temperatures T $\gg$ T c and low densities where the momentum distribution can be characterized by Maxwell-Boltzmann statistics, the modified emission rates (normalized to free space) behave similarly to point dipoles. This similarity in behavior arises due to the broad nature of wavevector components making up the exciton and point dipole emission. On the other hand, the narrow momentum distribution of excitons for T < T c can result in significantly different emission behavior as compared to point dipoles. These differences can be further amplified by considering excitons with a Bose Einstein distribution at high phase space densities, such as in a condensate phase. We find suppression or enhancement of emission relative to the point dipole case by several orders of magnitude. These insights can help optimize the performance of optoelectronic devices that incorporate 2D semiconductors near metal electrodes and can inform future studies of exciton radiative dynamics at low temperatures. Additionally, these studies show that nanoscale optical cavities are a viable pathway to generating long-lifetime exciton states in TMDCs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Monitoring the Photosynthetic Apparatus During Space Flight: Interspecific Variation in Chlorophyll Fluorescence Signatures Induced by Different Root Zone Stresses

Chlorophyll fluorescence has been used extensively as a tool to indicate stress to the photosynthetic apparatus in green plants. A rise in fluorescence has been attributed to the blockage of photosystem II photochemistry, and patterns of fluorescence decay (quenching) from dark adapted leaves can be related to specific photochemical and non-photochemical deexcitation pathways of light trapped by the photosynthetic apparatus and thus result in characteristically different fluorescence signatures. Four distantly related plant species, Hypocharis radicata (Asteraceae), Brassica rapa (Brassicaceae), Spinacea oleracea (Chenopodiaceae) and Triticum aestivum (Poaceae), were grown hydroponically for three weeks before the initiation of three different root zone stresses (10 mM Cu, 100 mM NaCl and nitrogen deficient nutrition). After 10 days, characteristic fluorescence signatures for each stress could be noted although the degree varied between species. Fast kinetics analysis showed a reduction in plastoquinone pool size for copper and nitrogen stress for all species but a more species specific result with NaCl stress. Photochemical quenching kinetics varied between species and stress treatments from no quenching in S. oleracea in copper treatments to increased photochemical quenching in NaCl treatments. Non-photochemical quenching kinetics demonstrated a distinct pattern between stresses for all species. Copper treatments characteristically exhibited a shallow, flat non-photochemical quenching profile suggesting a general blockage of electron transport whereas NaCl treatments exhibited a slow rising profile that suggested damage to thylakoid acidification kinetics and nitrogen deficiency exhibited a fast rising and declining profile that suggested an altered state 1-state 2 transition regulated by the phosphorylation of LHCII. These results demonstrate characteristic fluorescence signatures for specific plant stresses that may be applied to different, unrelated plant species. In addition, the potential use of chlorophyll fluorescence for both basic research and diagnostic physiology in space biology is presented.

Bubenheim, David L.↗

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent notions of the “things” being self-descriptive. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, identifying faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework that can verify compliance of products with semantic interoperability specifications. This strategic approach is designed to accelerate the timeline for adoption of semantic interoperability standards. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies as a necessary step in achieving an energy efficient smart grid future.

semantic interoperability, Semantic modeling, inte↗

Controlling Nb(IV) Defects in SrNbO 2 N Oxygen Evolution Photocatalyst by Ammonolysis With Dinitrogen–Ammonia Mixtures

Strontium niobium oxynitride (SrNbO 2 N) is a promising, corrosion resistant semiconductor for the visible light-driven water splitting reaction, a non-photovoltaic pathway to green hydrogen fuel. However, SrNbO 2 N materials made by ammonolysis usually contain Nb 4+ defect states that cause electron–hole recombination. Here, in this work, we demonstrate that such defects can be minimized by synthesizing SrNbO 2 N from metal oxides in a mixed 13%:87% (vol) NH 3 /N 2 atmosphere. According to electron paramagnetic resonance (EPR), SrNbO 2 N made in pure NH 3 contains paramagnetic impurities with g = 2.002 and 2.195, which can be assigned to lattice and surface Nb 4+ defects. These states also cause broad optical absorptions centered at 800 and 1020 nm, respectively, and the lattice defect produces a 1.55–1.63 eV signal in surface photovoltage spectra. The improved SrNbO 2 N contains five times fewer lattice Nb 4+ defects (8.95 × 10 15 cm −3 ), based on the integrated EPR signal intensity, and supports a water oxidation photocurrent of 1.07 mA cm −2 at 1.23 V versus RHE under simulated sunlight and an apparent quantum efficiency of 5.1% at 400 nm during photocatalytic oxygen evolution. Based on earlier results with LaTiO 2 N and BaTaO 2 N, dilution of NH 3 during synthesis appears generally beneficial to transition metal oxynitrides.

electron paramagnetic resonance↗

A decade of progress in understanding and managing legacy well integrity for geologic carbon storage

This study reviews a decade of research progress in legacy well integrity and risk management for geologic carbon storage (GCS) to commemorate the 20 th anniversary of the Intergovernmental Panel on Climate Change’s 2005 Special Report on Carbon Capture and Storage. In the past ten years, legacy well research has benefited from global efforts to constrain emissions from abandoned oil and gas wells, a continued focus on well materials performance in the presence of CO 2 -rich fluids, and practical experience gained through GCS implementation. Field measurements of abandoned well emissions show that leakage is not universal or catastrophic but forms a continuum of low-to-moderate fluxes that depend on isolation integrity and environmental attenuation. Materials research has constrained the conditions under which Portland cements exhibit self-sealing and non-sealing behaviors, and has identified the impact of geomechanical properties, non-uniform pathway apertures, multi-phase flow, and impurities in the CO 2 stream, on leakage pathways as important new areas for investigation. GCS projects at brownfield sites have inspired the creation of new workflows that integrate various tools and technologies to manage legacy well leakage risks. GCS implementation has also motivated a push towards scenario-based well modeling that directly informs permit applications. These advances inspire new research questions for the coming decade, particularly around the level of legacy well leakage risk that is environmentally acceptable and tolerable to stakeholders when sequestering millions of tonnes of CO 2 annually.

Carbon capture and storage↗

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent self-descriptive notions of the “things”. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, automatically identifying and diagnosing faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework to verify compliance of products with semantic interoperability specifications. This approach is designed to accelerate the timeline for adoption of semantic interoperability specifications. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies and use cases as a necessary step in achieving an energy efficient smart grid future.

Bergmann, Harry↗

Climate projections over the Great Lakes Region: using two-way coupling of a regional climate model with a 3-D lake model

Abstract. Warming trends in the Laurentian Great Lakes and surrounding areas have been observed in recent decades, and concerns continue to rise about the pace and pattern of future climate change over the world's largest freshwater system. To date, most regional climate models used for Great Lakes projections either neglected the lake-atmosphere interactions or are only coupled with a 1-D column lake model to represent the lake hydrodynamics. This study presents a Great Lakes climate change projection that has employed the two-way coupling of a regional climate model with a 3-D lake model (GLARM) to resolve 3-D hydrodynamics essential for large lakes. Using the three carefully selected Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs), we show that the GLARM ensemble average substantially reduces surface air temperature and precipitation biases of the driving GCM ensemble average in present-day climate simulations. The improvements are not only displayed from an atmospheric perspective but are also evident in the accurate simulations of lake temperature and ice coverage. We further present the GLARM projected climate change for the mid-21st century (2030–2049) and the late 21st century (2080–2099) in the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios. Under RCP 8.5, the Great Lakes basin is projected to warm by 1.3–2.1 ∘C by the mid-21st century and 4.1–5.0 ∘C by the end of the century relative to the early century (2000–2019). Moderate mitigation (RCP 4.5) reduces the mid-century warming to 0.8–1.8 ∘C and late-century warming to 1.8–2.7 ∘C. Annual precipitation in GLARM is projected to increase for the entire basin, varying from 0 % to 13 % during the mid-century and from 9 % to 32 % during the late century in different scenarios and simulations. The most significant increases are projected in spring and fall when current precipitation is highest and a minimal increase in winter when it is lowest. Lake surface temperatures (LSTs) are also projected to increase across the five lakes in all of the simulations, but with strong seasonal and spatial variability. The most significant LST increases occur in Lakes Superior and Ontario. The strongest warming is projected in spring that persists into the summer, resulting from earlier and more intense stratification in the future. In addition, diminishing winter stratification in the future suggests the transition from dimictic lakes to monomictic lakes by the end of the century. In contrast, a relatively smaller increase in LSTs during fall and winter is projected with heat transfer to the deep water due to the strong mixing and energy required for ice melting. Correspondingly, the highest monthly mean ice cover is projected to reduce to 3 %–15 % and 10 %–40 % across the lakes by the end of the century in RCP 8.5 and RCP 4.5, respectively. In the coastal regions, ice duration is projected to decrease by up to 60 d.

Xue, Pengfei (ORCID:000000025702421X)↗

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent self-descriptive notions of the “things”. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, automatically identifying and diagnosing faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework to verify compliance of products with semantic interoperability specifications. This approach is designed to accelerate the timeline for adoption of semantic interoperability specifications. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies and use cases as a necessary step in achieving an energy efficient smart grid future.

30 DIRECT ENERGY CONVERSION↗

From Qualitative to Quantitative AOP: A Case Study of Neurodegeneration

Adverse outcome pathways (AOPs) include a sequence of events that connect a molecular-level initiating event with an adverse outcome at the cellular level for human health endpoints, or at the population level for ecological endpoints. When there is enough quantitative understanding of the relationships between key events in an AOP, a mathematical model may be developed to connect key events in a quantitative AOP (qAOP). Ideally, a qAOP will reduce the time and resources spent for chemical toxicity testing and risk assessment and enable the extrapolation of data collected at the molecular-level by in vitro assays, for example, to predict whether an adverse outcome may occur. Here, we review AOPs in the AOPWiki, an AOP repository, to determine best practices that would facilitate conversion from AOP to qAOP. Then, focusing on a particular case study, acetylcholinesterase inhibition leading to neurodegeneration, we describe specific methods and challenges. Examples of challenges include the availability and collection of quantitative data amenable to model development, the lack of studies that measure multiple key events, and model accessibility or transferability across platforms. We conclude with recommendations for improving key event and key event relationship descriptions in the AOPWiki that facilitate the transition of qualitative AOPs to qAOPs.

Sinitsyn, Dennis↗

Spatial scale of motion segmentation from speed cues

For the accurate perception of multiple, potentially overlapping, surfaces or objects, the visual system must distinguish different local motion vectors and selectively integrate similar motion vectors over space to segment the retinal image properly. We recently showed that large differences in speed are required to yield a percept of motion transparency. In the present study, to investigate the spatial scale of motion segmentation from speed cues alone, we measured the speed-segmentation threshold (the minimum speed difference required for 75% performance accuracy) for 'corrugated' random-dot patterns, i.e. patterns in which dots with two different speeds were alternately placed in adjacent bars of variable width. In a first experiment, we found that, at large bar widths, a smaller speed difference was required to segment and perceive the corrugated pattern of moving dots, while at small bar-widths, a larger speed difference was required to segment the two speeds and perceive two transparent surfaces of moving dots. Both the perceptual and segmentation performance transitions occurred at a bar width of around 0.4 degrees. In a second experiment, speed-segmentation thresholds were found to increase sharply when dots with different speeds were paired within a local pooling area. The critical pairing distance was about 0.2 degrees in the fovea and increased linearly with stimulus eccentricity. However, across the range of eccentricities tested (up to 15 degrees ), the critical pairing distance did not change much and remained close to the receptive field size of neurons within the primate primary visual cortex. In a third experiment, increasing dot density changed the relationship between speed-segmentation thresholds and bar width. Thresholds decreased for large bar widths, but increased for small bar widths. All of these results are well fit by a simple stochastic model, which estimates the probabilities of having identical or different motion vectors within a local pooling area whose size is the same as that of primate V1 neurons. Altogether, these results demonstrate that speed-based segmentation can function well, even at small spatial scales (i.e. high-spatial frequencies of spatial corrugation) and thereby emphasizes the critical role of a local pooling process early in the cortical motion-processing pathway.

NASA Discipline Neuroscience↗

A High-Entropy Oxide as High-Activity Electrocatalyst for Water Oxidation

High-entropy materials are an emerging pathway in the development of high-activity (electro)catalysts because of the inherent tunability and coexistence of multiple potential active sites, which may lead to earth-abundant catalyst materials for energy-efficient electrochemical energy storage. In this report, we identify how the multication composition in high-entropy perovskite oxides (HEO) contributes to high catalytic activity for the oxygen evolution reaction (OER), i.e., the key kinetically limiting half-reaction in several electrochemical energy conversion technologies, including green hydrogen generation. We compare the activity of the (001) facet of LaCr 0.2 Mn 0.2 Fe 0.2 Co 0.2 Ni 0.2 O 3-δ with the parent compounds (single B-site in the ABO 3 perovskite). While the single B-site perovskites roughly follow the expected volcano-type activity trends, the HEO clearly outperforms all of its parent compounds with 17 to 680 times higher currents at a fixed overpotential. As all samples were grown as an epitaxial layer, our results indicate an intrinsic composition–function relationship, avoiding the effects of complex geometries or unknown surface composition. In-depth X-ray photoemission studies reveal a synergistic effect of simultaneous oxidation and reduction of different transition metal cations during the adsorption of reaction intermediates. The surprisingly high OER activity demonstrates that HEOs are a highly attractive, earth-abundant material class for high-activity OER electrocatalysts, possibly allowing the activity to be fine-tuned beyond the scaling limits of mono- or bimetallic oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying the Impact of Metal Population Distribution in MFI-Supported Mo Catalysts for Methane Dehydroaromatization

Precise evaluation of intrinsic kinetic behavior in Mo/MFI catalysts for methane dehydroaromatization (MDA) is confounded by variations in Mo dispersion and speciation, which are influenced by metal loading and zeolite acidity. This work advances the utility of H 2 -temperature programmed reduction (H 2 -TPR) for characterizing Mo/MFI catalysts by enabling quantitative comparison of MoO x populations distinguished by reduction behavior and linked to initial catalytic performance. A comprehensive H 2 reduction pathway is established through systematic H 2 - TPR studies varying catalyst composition (1–10 wt % Mo, Si/Al = 15, 40, ∞), supplemented by UV-Raman spectroscopy, X-ray powder diffraction, N 2 physisorption, NH 3 -TPD, and advanced spectroscopic analysis (in situ XAS with principal component analysis/multivariate curve resolution—alternating least squares). Two low-temperature H 2 -TPR regions capture distinct Mo populations undergoing initial Mo(VI)→Mo(IV) reduction: a lower-temperature population (Mo-RI) associated primarily with highly dispersed, anchored MoO x species expected to predominantly reside within MFI channels, and a higher-temperature population (Mo-RII) corresponding to a broader set of MoO x species that becomes increasingly bulk-like/extrazeolitic at higher Mo loading. Quantification of these populations provides practical, kinetically relevant descriptors for comparing initial MDA rates across catalysts with varying Mo loading, Si/Al ratio, and MoO x heterogeneity. Application of lower-temperature Mo-RI estimates to kinetic measurements reveals a minimum threshold of ∼0.12 × 10 –3 mol Mo-RI/g cat , above which initial forward benzene rates normalized to this population converge despite differences in metal loading and zeolite Brønsted acidity. This threshold coincides with a transition toward a common C 2 -mediated benzene-forming regime, as indicated by approach-to-equilibrium analysis of methane-to-ethane, ethane-to-ethylene, and ethylene-to-benzene reaction steps. Above this threshold, normalized initial benzene rates are nearly invariant with increasing Mo-RII/Mo-RI population ratio, indicating that excess Mo-RII populations, including bulk-like/extrazeolitic MoO x domains present at higher loading, do not measurably suppress benzene formation associated with anchored and mostly channel-confined Mo population under the initial-rate conditions examined.

Mo/MFI↗

Irradiation damage concurrent challenges with RAFM and ODS steels for fusion reactor first-wall/blanket: a review

Reduced activation ferritic martensitic (RAFM) and oxide dispersion strengthened (ODS) steels are the most promising candidates for fusion first-wall/blanket (FW/B) structures. The performance of these steels will deteriorate during service due to neutron damage and transmutation-induced gases, such as helium/hydrogen, at elevated operating temperatures. Here, after highlighting the operating conditions of fusion reactor concepts and a brief overview, the main irradiation-induced degradation challenges associated with RAFM/ODS steels are discussed. Their long-term degradation scenarios such as (a) low-temperature hardening embrittlement (LTHE)—including dose-temperature dependent yield stress, tensile elongations, necking ductility, test temperature effect on hardening, Charpy impact ductile-to-brittle transition temperature and fracture toughness, (b) intermediate temperature cavity swelling, (c) the effect of helium on LTHE and cavity swelling, (d) irradiation creep and (e) tritium management issues are reviewed. The potential causes of LTHE are discussed, which highlights the need for advanced characterisation techniques. The mechanical properties, including the tensile/Charpy impact of RAFM and ODS steels, are compared to show that the current generation of ODS steels also suffers from LTHE, and shows irradiation hardening up to high temperatures of ~400 °C–500 °C. To minimise this, future ODS steel development for FW/B-specific application should target materials with a lower Cr concentration (to minimise α'), and minimise other elements that could form embrittling phases under irradiation. RAFM steel-designing activities targeting improvements in creep and LTHE are reviewed. The need to better understand the synergistic effects of helium on the thermo-mechanical properties in the entire temperature range of FW/B is highlighted. Because fusion operating conditions will be complex, including stresses due to the magnetic field, primary loads like coolant pressure, secondary loads from thermal gradients, and due to spatial variation in damage levels and gas production rates, an experimentally validated multiscale modelling approach is suggested as a pathway to future reactor component designing such as for the fusion neutron science facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Future PM 2.5 emissions from metal production to meet renewable energy demand

A shift from fossil fuel to renewable energy is crucial in limiting global temperature increase to 2 °C above preindustrial levels. However, renewable energy technologies, solar photovoltaics, wind turbines, and electric vehicles are metal-intensive, and the mining and smelting processes to obtain the needed metals are emission-intensive. We estimate the future PM 2.5 emissions from mining and smelting to meet the metal demand of renewable energy technologies in two climate pathways to be 0.3–0.6 Tg yr -1 in the 2020–2050 period, which are projected to contribute 10%–30% of total anthropogenic primary PM 2.5 combustion emissions in many countries. The concentration of mineral reserves in a few regions means the impacts are also regionally concentrated. Rapid decarbonization could lead to a faster reduction of overall anthropogenic PM 2.5 emissions but also could create more unevenness in the distributions of emissions relative to where demand occurs. Options to reduce metal-related PM 2.5 emissions by over 90% exist and are well understood; introducing policy requiring their installation could avoid emission hotspots.

54 ENVIRONMENTAL SCIENCES↗

California Time-of-Use (TOU) Transition: Effects on Distributed Wind and Solar Economic Potential

Time-of-use (TOU) retail energy rates price electricity differently by the time of day, communicating to consumers the costs of supplying electricity diurnally. This study evaluates the impact of Decision D.15.07-001, which mandates a transition in 2020 to default TOU rates for residential ratepayers in California, on the economic viability of behind-the-meter distributed wind and solar systems. Previous studies have demonstrated that increasing wind and solar generation will materially affect the diurnal cost of wholesale electricity. As retail and wholesale prices become more aligned, this could affect the inter-technology economic viability of distributed generation. We assess economic viability through 'economic potential,' or the amount of generation capacity that exceeds a rate of return of 5.4%. In addition, we identify sensitivities of economic potential to capital costs and other techno-economic factors as well as the specific counties and sectors with substantial economic potential. We find that TOU implementation is projected to moderately increase economic potential of distributed wind and marginally decrease that of distributed solar. Over the long-term as variable renewable energy penetration increases in California, particularly utility-scale solar, net peak load and thus peak prices will shift later in the evening. To the extent that retail rates continue to evolve with wholesale prices, we find the changes could positively affect the value of wind generation more than that of solar generation. Over the scenarios considered, model results indicate realistic pathways to reaching a robust distributed wind market in California though solar economic potential was found to be substantially larger than that of wind.

17 WIND ENERGY↗

Understanding Instability in Formamidinium Lead Halide Perovskites: Kinetics of Transformative Reactions at Grain and Subgrain Boundaries

Transformative and reconstructive reactions impart significant structural changes at particle boundaries of hybrid perovskites, which influence environmental stability and optoelectronic properties of these materials. Here, we investigate the moisture-induced transformative reactions in formamidinium based perovskites FAPbX 3 (X=I, Br) and show that the ambient stability of these materials can be adjusted from a few hours to several months. For FAPbI 3 , roles of water vapor, particle size, and light illumination on the kinetic pathways of the cubic (a) transformation to the hexagonal (d) phase are analyzed by X-ray diffraction, optical microscopy, photoluminescence and solid-state NMR spectroscopy techniques. The grain and sub-grain boundaries exhibit different α→δ-FAPbI 3 phase transformation kinetics. Our study suggests that the dynamic transformation involves the local water-induced dissolution of the cubic phase occurring at the crystal surfaces followed by precipitation of the hexagonal phase. Insights into structures and dynamics of a kinetically trapped α-|δ-FAPbI 3 are obtained by 1 H, 2 H, and 207 Pb ssNMR spectroscopy.

36 MATERIALS SCIENCE↗

High-Rate, Selective Electrosynthesis of Cyclohexanone Oxime via In Situ Generation and Release of Hydroxylamine on Bismuth

Oxime compounds are key industrial intermediates for nylon precursors and commodity chemicals. However, conventional routes rely on multistep reactions and hydroxylamine (NH 2 OH) salts, raising significant safety and sustainability concerns. Although electrosynthesis offers an alternative, oxime formation on d-block transition metals suffers from poor selectivity, as nitrogen oxyanion intermediates bind strongly to the surface and are readily over-reduced to ammonia. Here, we report morphology-controlled p-block bismuth rhombic dodecahedra (Bi RDs) that promote in situ NH 2 OH generation and its desorption into the electrolyte, enabling an electrochemical-chemical decoupled route for cyclohexanone oxime (CHO) synthesis. Bi RDs deliver nearly 100% Faradaic efficiency (FE) at −0.5 V vs. RHE and a yield of 1.4 mmol h –1 cm –2 at −0.9 V vs. RHE in an H-cell, while maintaining a CHO selectivity of nearly 100% at 100 mA cm –2 in a flow cell. Under identical conditions, d-block electrodes (Cu, Pd, Ag) show FE below 30%. Density functional theory calculations reveal that Bi 6p orbital-derived surface states weaken intermediate binding and facilitate NH 2 OH desorption, suppressing over-reduction. Kinetic analysis, post-addition trapping experiments, and in situ ATR-FTIR and Raman spectroscopy suggest the following reaction mechanism: NH 2 OH is selectively generated at the electrode surface, released as a freely diffusing intermediate, and undergoes homogeneous condensation with cyclohexanone in the bulk electrolyte, bypassing the surface-confined Langmuir–Hinshelwood pathway. These findings demonstrate that regulating intermediate desorption through p-block orbital chemistry provides a general strategy for achieving high selectivity in electro-organic nitrogen synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗