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At least 73 records · Page 4

Impacts of long-term temperature change and variability on electricity investments

Long-term temperature change and variability are expected to have significant impacts on future electric capacity and investments. This study improves upon past studies by accounting for hourly and monthly dynamics of electricity use, long-term socioeconomic drivers, and interactions of the electric sector with rest of the economy for a comprehensive analysis of temperature change impacts on cooling and heating services and their corresponding impact on electric capacity and investments. Using the United States as an example, here we show that under a scenario consistent with a socioeconomic pathway 2 (SSP2) and representative concentration pathway 8.5 (RCP 8.5), mean temperature changes drive increases in annual electricity demands by 0.5-8% across states in 2100. But more importantly, peak temperature changes drive increases in capital investments by 3-22%. Moreover, temperature-induced capital investments are highly sensitive to both long-term socioeconomic assumptions and spatial heterogeneity of fuel prices and capital stock characteristics, which underscores the importance of a comprehensive approach to inform long-term electric sector planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Analytical Model for the Higher Order Moments of Midlatitude Atmospheric Temperature Distributions

Observed distributions of atmospheric temperature are non-Gaussian. Therefore, moments beyond variance are necessary in determining the frequency of extreme temperature events. Here we propose a simple kinematic model for atmospheric mid-latitude temperature variability based on symmetric advection from a non-symmetric background temperature profile. We then use this model to derive analytical expressions for the higher order moments of temperature distributions. Our results show that nonzero skewness and kurtosis arise due to the nonlinearity of the time-mean meridional temperature profile. The analytical model matches an idealized Held-Suarez atmospheric model, indicating nonlinearity of time-mean temperature in latitude is the dominant contribution to nonzero skewness and kurtosis in synoptic temperature variations. Model analysis further shows decrease in higher order moments due to climate change come roughly equally from changes in mixing length and changes in the background temperature profiles.

54 ENVIRONMENTAL SCIENCES↗

Challenges and perspectives for large-scale temperature reconstructions of the past two millennia

Knowledge of the temperature variability during the last one to two millennia is important for providing a perspective to present-day climate excursions, for assessing the sensitivity of the climate to different forcings, and for providing a test bed for climate models. Since systematic instrumental temperature records only extend back to the nineteenth century, such knowledge mainly relies on climate-sensitive proxy data. Here we critically assess some of the many challenges related to large-scale multiproxy temperature reconstructions. We begin with a review of available large-scale temperature reconstructions, focusing on the differences in low-frequency variability and the response to natural forcings such as major volcanic eruptions and changes in total solar irradiance. Then, we discuss different proxy selection strategies, review previously used reconstruction methods, and discuss their ability to reconstruct the amplitude of the low-frequency variability. To shed additional light on the challenges of large-scale reconstructions, we investigate the spatial and temporal correlation structures in the observed temperature field and discuss the implications of these correlation structures regarding the required number and positions of proxies. We demonstrate how the unavoidable uncertainty related to noisy proxies will show up as bias and variance in the reconstruction and that the partition between these forms of errors depends on the reconstruction method. Pseudo-proxy experiments are conducted to further discuss the influence of noise and the requirements regarding the geographical location and number of proxies necessary for reliably reconstructing the low-frequency variability. Finally, we conclude with recommendations for future large-scale temperature reconstructions.

54 ENVIRONMENTAL SCIENCES↗

Rare Earth Nitrate Hybrid Double Perovskites [Me 4 N] 2 [MLn(NO 3 ) 6 ] (M = Na–Cs; Ln = La–Gd, ex. Pm)

An exploration of the synthetic and structural phase space of rare earth hybrid double perovskites A 2 B'BX 6 (A = organocation, B' = M + , B = M 3+ , X = molecular bridging anion) that include X = NO 3 – and B' = alkali metal is reported, complementing earlier studies of the [Me 4 N] 2 [KB(NO 3 ) 6 ] (B = Am, Cm, La–Nd, Sm–Lu, Y) (Me 4 N = (CH 3 ) 4 N + ) compounds. In the present efforts, the synthetic phase space of these systems is explored by varying the identity of the alkali metal ion at the B'-site. Herein, we report three new series of the form [Me 4 N] 2 [B'B(NO 3 ) 6 ] (B = La–Nd, Sm–Gd; B' = Na, Rb, Cs). The early members of the Na-series crystallize in the trigonal space group R3̅ from La to Nd where a phase transition occurs in the phase between 273 and 300 K, going from R3̅ to the high-symmetry, cubic space group Fm3̅m. The preceding trigonal members of the Na-series also undergo phase transitions to cubic symmetry at temperatures above 300 K, establishing a decreasing trend in the phase-transition temperature. The remainder of the Na-series, as well as the Rb- and Cs-series, all crystallize in Fm3̅m at 300 K. The temperature-dependent phase behavior of the synthesized phases is studied via variable-temperature spectroscopic methods and high-resolution powder X-ray diffractometry. All phases were characterized via single-crystal and powder X-ray diffraction and Fourier transform infrared (FT-IR) and Raman spectroscopic methods. These results demonstrate the versatility of the perovskite structure type to include rare earth ions, nitrate ions, and a suite of alkali metal ions and serve as a foundation for the design of functional rare earth hybrid double perovskite materials such as those possessing useful multiferroic, optical, and magnetic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Winter precipitation predictability in Central Southwest Asia and its representation in seasonal forecast systems

In Central Southwest Asia (CSWA; 22°N to 40°N and 30°E to 70°E), winter (November to February) precipitation contributes up to 70% of the annual mean, but substantial interannual variations exist. Dynamical models exhibit subpar predictability in this region, but the limits of their skills are not well established. Here, we identify the tropical and extratropical forcings that explain ~75% of area-averaged seasonal variability in CSWA winter precipitation. Tropical forcing comes from the indirect El Niño-Southern Oscillation (ENSO) pathway, the leading mode of tropical Indian Ocean precipitation variability. This mode is coupled with ENSO-related Pacific Ocean sea surface temperature variability. A direct ENSO influence on CSWA does not extend beyond its Indian Ocean connection. Extratropical forcing comes from a large-scale mode of internal atmospheric variability. The spatial structure, variability of tropical forcing, and teleconnection with CSWA winter precipitation are skillfully depicted in two seasonal forecasting systems: the fifth-generation seasonal forecasting system (SEAS5) and Seamless System for Prediction and Earth System Research (SPEAR). Extratropical forcing’s spatial structure is also produced skillfully in the two modelling systems; however, the representation of its interannual variability and teleconnection requires improvement. While SEAS5 displays skill in representing extratropical forcing influence on CSWA winter precipitation and marginal skill in reproducing interannual variability, SPEAR has negligible ability in both areas. Consequently, these models have limited predictive skills over CSWA in winter. While improvements in representing extratropical forcing may be inherently limited as it arises from internal atmospheric variability, further research is needed to establish its predictability limits fully.

54 ENVIRONMENTAL SCIENCES↗

Cooperativity and Metal–Linker Dynamics in Spin Crossover Framework Fe(1,2,3-triazolate) 2

Cooperative interactions are responsible for the useful properties of spin crossover (SCO) materials–large hysteresis windows, critical temperatures near room temperature, and abrupt transitions–with hybrid framework materials exhibiting the greatest cooperativity and hysteresis of all SCO systems. However, little is known about the chemical origin of cooperativity in frameworks. Here, we present a combined experimental–computational approach for identifying the origin of cooperativity in the metal–organic framework (MOF) Fe(1,2,3-triazolate) 2 (Fe(TA) 2 ), which exhibits the largest known hysteresis window of all SCO materials and unusually high transition temperatures, as a roadmap for understanding the manipulation of SCO behavior in general. Variable-temperature vibrational spectroscopy provides evidence that “soft modes” associated with dynamic metal–linker bonding trigger the cooperative SCO transition. Thermodynamic analysis also confirms a cooperativity magnitude much larger than those of other SCO systems, while electron density calculations of Fe(TA) 2 support previous theoretical predictions that large cooperativity arises in materials where SCO produces considerable differences in metal–ligand bond polarities between different spin states. Taken together, this combined experimental–computational study provides a microscopic basis for understanding cooperative magnetism and highlights the important role of dynamic bonding in the functional behavior of framework materials.

36 MATERIALS SCIENCE↗

The varying temperature- and pressure-induced phase transition pathways in hybrid improper ferroelectric Sr 3 Sn 2 O 7

A variable-temperature and pressure single-crystal diffraction study of hybrid improper ferroelectric Sr 3 Sn 2 O 7 is reported. In combination with symmetry analysis, we reveal that the application of pressure and temperature induce distinct phase transition pathways, driven by a differing response of the octahedral rotations to these stimuli. Contrary to what has been previously predicted, we observe the ferroelectric to paraelectric phase transition between 10.17(18) and 12.13(14) GPa, meaning the hybrid improper ferroelectric phase remains stable to significantly higher pressures than expected.

Ferroelectrics↗

Variability in Diurnal and Seasonal Ambient Conditions on Geothermal Plant Performance and Cost

Geothermal plant performance is bounded by the second law efficiency, which accounts for the quantity of exergy that can be converted into useful work. This, in turn, is dependent on the geothermal resource temperature and the temperature of the heat sink (i.e., the ambient temperature). In this study, we show that ambient temperature variability on a diurnal and seasonal basis can affect performance and cost estimations for geothermal plants. We have utilized the updated System Advisor Model (SAM) to assess nine geothermal sites with existing resource capacities across three climate zones. Our analysis shows that both evaporatively-cooled flash and air-cooled binary cycle plants are affected by temperature, with a slightly higher effect in enhanced geothermal system binary sites. By assuming an ambient (wet bulb) temperature baseline of 15.6 degrees C (60 degrees F) and comparing baseline results to those from site-specific data, we observe up to 15% underestimation of plant performance and up to 20% overestimation of cost. These results make a case for the inclusion of location-based weather data as inputs to supply curves that are used in capacity expansion models for the prediction of future geothermal deployment scenarios.

ambient temperature↗

High-Resolution Meteorology with Climate Change Impacts from Global Climate Model Data Using Generative Machine Learning

As renewable energy generation increases, the impacts of weather and climate on energy generation and demand become critical to the reliability of the energy system. However, these impacts are often overlooked. Global climate models (GCMs) can be used to understand possible changes to our climate, but their coarse resolution makes them difficult to use in energy system modelling. Here we present open-source generative machine learning methods that produce meteorological data at a nominal spatial resolution of 4 km at an hourly frequency based on inputs from 100 km daily-average GCM data. These methods run 40 times faster than traditional downscaling methods and produce data that have high-resolution spatial and temporal attributes similar to historical datasets. We demonstrate that these methods can be used to downscale projected changes in wind, solar and temperature variables across multiple GCMs including projections for more frequent low-wind and high-temperature events in the Eastern United States.

climate change↗

Variability in Diurnal and Seasonal Ambient Conditions on Geothermal Plant Performance and Cost: Preprint

Geothermal plant performance is bounded by the second law efficiency, which accounts for the quantity of exergy that can be converted into useful work. This in turn is dependent on the geothermal resource temperature and the temperature of the heat sink (i.e., the ambient temperature). In this study we show that ambient temperature variability on a diurnal and seasonal basis can affect performance and cost estimations for geothermal plants. We have utilized the updated System Advisor Model (SAM) to assess nine geothermal sites with existing resource capacities across three climate zones. Our analysis shows that both evaporatively-cooled flash and air-cooled binary cycle plants are affected by temperature, with a slightly higher effect in EGS binary sites. By assuming an ambient (wet bulb) temperature baseline of 15.6 degrees C (60 degrees F) and comparing baseline results to those from site-specific data we observe up to 15% underestimation of plant performance and up to 20% overestimation of cost.

ambient temperature↗

Asymmetric temperature equilibration with heat flow from cold to hot in a quantum thermodynamic system

A model computational quantum thermodynamic network is constructed with two variable temperature baths coupled by a linker system, with an asymmetry in the coupling of the linker to the two baths. It is found in computational simulations that the baths come to “thermal equilibrium” at different bath energies and temperatures. In a sense, heat is observed to flow from cold to hot. Additionally, a description is given in which a recently defined quantum entropy S univ Q for a pure state “universe” continues to increase after passing through the classical equilibrium point of equal temperatures, reaching a maximum at the asymmetric equilibrium. Thus, a second law account Δ S univ Q ≥ 0 holds for the asymmetric quantum process. In contrast, a von Neumann entropy description fails to uphold the entropy law, with a maximum near when the two temperatures are equal, then a decrease Δ S v N < 0 on the way to the asymmetric equilibrium.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Decoding the Mechanisms of Phase Transitions from In Situ Microscopy Observations

Abstract Analysis of the temperature‐ and stimulus‐dependent imaging data toward elucidation of the physical transformations is an ubiquitous problem in multiple fields. Here, temperature‐induced phase transition in BaTiO 3 is explored using the machine learning analysis of domain morphologies visualized via variable‐temperature scanning transmission electron microscopy (STEM) imaging data. This approach is based on the multivariate statistical analysis of the time or temperature dependence of the statistical descriptors of the system, derived in turn from the categorical classification of observed domain structures or projection on the continuous parameter space of the feature extraction‐dimensionality reduction transform. The proposed workflow offers a powerful tool for the exploration of the dynamic data based on the statistics of image representation as a function of the external control variable to visualize the transformation pathways during phase transitions and chemical reactions. This can include the mesoscopic STEM data as demonstrated here, but also optical, chemical imaging, etc., data. It can further be extended to the higher dimensional spaces, for example, analysis of the combinatorial libraries of materials compositions.

Valleti, Sai Mani Prudhvi↗

Mechanistic Pathways for N 2 O Elimination from trans -R 3 Sn-O-N=N-O-SnR 3 and for Reversible Binding of CO 2 to R 3 Sn-O-SnR 3 (R = Ph, Cy)

The rate and mechanism of the elimination of N 2 O from trans-R 3 Sn-O-N=N-O-SnR 3 (R = Ph ( 1 Ph ) and R = Cy ( 1 Cy )) to form R 3 Sn-O-SnR 3 (R = Ph ( 2 Ph ) and R = Cy ( 2 Cy )) have been studied using both NMR and IR techniques to monitor the reactions in the temperature range of 39–79 °C in C 6 D 6 . Activation parameters for this reaction are ΔH ‡ = 15.8 ± 2.0 kcal·mol –1 and ΔS ‡ = –28.5 ± 5 cal·mol –1 ·K –1 for 1 Ph and ΔH ‡ = 22.7 ± 2.5 kcal·mol –1 and ΔS ‡ = –12.4 ± 6 cal·mol –1 ·K –1 for 1 Cy . Addition of O 2 , CO 2 , N 2 O, or PPh 3 to sealed tube NMR experiments did not alter in a detectable way the rate or product distribution of the reactions. Computational DFT studies of elimination of hyponitrite from trans-Me 3 Sn-O-N=N-O-SnMe 3 ( 1 Me ) yield a mechanism involving initial migration of the R 3 Sn group from O to N passing through a marginally stable intermediate product and subsequent N 2 O elimination. Reactions of 1 Ph with protic acids HX are rapid and lead to formation of R 3 SnX and trans-H 2 N 2 O 2 . Reaction of 1 Ph with the metal radical •Cr(CO) 3 C 5 Me 5 at low concentrations results in rapid evolution of N 2 O. At higher •Cr(CO) 3 C 5 Me 5 concentrations, evolution of CO 2 rather than N 2 O is observed. Addition of 1 atm or less CO 2 to benzene or toluene solutions of 2 Ph and 2 Cy resulted in very rapid reaction to form the corresponding carbonates R 3 Sn-O-C(=O)-O-SnR 3 (R = Ph ( 3 Ph ) and R = Cy ( 3 Cy )) at room temperature. Evacuation results in fast loss of bound CO 2 and regeneration of 2 Ph and 2 Cy . Variable temperature data for formation of 3 Cy yield ΔH o = –8.7 ± 0.6 kcal·mol –1 , ΔS o = –17.1 ± 2.0 cal·mol –1 ·K –1 , and ΔG o 298K = –3.6 ± 1.2 kcal·mol –1 . Furthermore, DFT studies were performed and provide additional insight into the energetics and mechanisms for the reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low Thermal Conductivity in Heteroanionic Materials with Layers of Homoleptic Polyhedra

Although BiAgOSe, an analogue of a well-studied thermoelectric material BiCuOSe, is thermodynamically stable, its synthesis is complicated by the low driving force of formation from the stable binary and ternary intermediates. Here we have developed a “subtraction strategy” to suppress byproducts and produce pure phase BiAgOSe using hydrothermal methods. Electronic structure calculations and optical characterization show that BiAgOSe is an indirect bandgap semiconductor with a bandgap of 0.95 eV. The prepared sample exhibits lower lattice thermal conductivities (0.61 W·m –1 ·K –1 at room temperature and 0.35 W·m –1 ·K –1 at 650 K) than BiCuOSe. Further, lattice dynamical simulations and variable temperature diffraction measurements demonstrate that the low lattice thermal conductivity arises from both the low sound velocity and high phonon–phonon scattering rates in BiAgOSe. These in turn result primarily from the soft Ag–Se bonds in the edge-sharing AgSe 4 tetrahedra and large sublattice mismatch between the quasi-two-dimensional [Bi 2 O 2 ] 2+ and [Ag 2 Se 2 ] 2– layers. These results highlight the advantages of manipulating the chemistry of homoleptic polyhedra in heteroanionic compounds for electronic structure and phonon transport control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SULI Technical Report: WIRE (Draft)

Local climate undoubtedly affects facility maintenance requirements; however, knowledge of the link between weather and facility condition over time is grounded in the 1990s and needs to be updated. WIRE aims to quantify the relationship between climate and infrastructure by calculating climate-based service life estimates to be used in BUILDER, a program the Department of Energy (DOE) uses for facility management. Phase One of this project is a case study on window-or-wall-mounted AC units. The independent variables influencing service life are load, maintenance quality, and effective age, with load calculated from three weather variables: temperature, humidity, and solar radiation. Given sufficient data, service life can be calculated as a function of these variables via regression. WIRE is currently collecting data. Preliminary estimated service life projections as a function of load derived from Lawrence Livermore National Laboratory (LLNL) data support the need for updated analysis on the relationship between climate and facility condition. With the groundwork laid, WIRE can generate deliverables immediately upon arrival of data. The methods used for this case study constitute a framework for deriving the relationship between weather variables and service life for other components.

42 ENGINEERING↗

Al 0.7 Ga 0.3 N MESFET With All-Refractory Metal Process for High Temperature Operation

In this work, ultrawide bandgap Al 0.7 Ga 0.3 N MESFETs with refractory Tungsten Schottky and Ohmic contacts are studied in 300–675 K environments. Variable-temperature dc electrical transport reveals large ON-state drain current densities for an AlGaN device: 209 mA/mm at 300 K and 156 mA/mm at 675 K in the ON-state (25% reduction). Drain and gate currents are only weakly temperature-dependent, suggesting potential for engineering temperature invariant operation. The ON-/ OFF-ratio is limited by OFF-state leakage through the gate, which is attributed to damage from sputter deposition. Future work using refractory metals with larger work functions that are deposited by electron beam deposition is proposed.

36 MATERIALS SCIENCE↗

Discovery of chalcogenides structures and compositions using mixed fluxes

Advancements in many modern technologies rely on the continuous need for materials discovery. However, the design of synthesis routes leading to new and targeted solid-state materials requires understanding of reactivity patterns. Advances in synthesis science are necessary to increase efficiency and accelerate materials discovery. We present a highly effective methodology for the rational discovery of materials using high-temperature solutions or fluxes having tunable solubility. This methodology facilitates product selection by projecting the free-energy landscape into real synthetic variables: temperature and flux ratio. We demonstrate the effectiveness of this technique by synthesizing compounds in the chalcogenide system of A(Ba)-Cu-Q(O) (Q = S or Se; A = Na, K or Rb) using mixed AOH/AX (A = Li, Na, K or Rb; X = Cl or I) fluxes. We present 30 unreported compounds or compositions, including more than ten unique structural types, by systematically varying the temperature and flux ratios without requiring changing the proportions of starting materials. Additionally, we found that the structural dimensionality of the compounds decreases with increasing reactant solubility and temperature. This methodology serves as an effective general strategy for the rational discovery of inorganic solids.

36 MATERIALS SCIENCE↗

Photosynthetic responses to temperature across the tropics: a meta-analytic approach

Background and Aims Tropical forests exchange more carbon dioxide (CO 2 ) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three times greater for the tropics than other for ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink. Methods Here, we used a meta-analytic approach, focusing on tropical photosynthetic temperature responses, to address this knowledge gap. Our dataset, gleaned from 18 independent studies, included leaf-level light-saturated photosynthetic (A sat ) temperature responses from 108 woody species, with additional temperature parameters (35 species) and rates (250 species) of both maximum rates of electron transport (J max ) and Rubisco carboxylation (V cmax ). We investigated how these parameters responded to mean annual temperature (MAT), temperature variability, aridity and elevation, as well as also how responses differed among successional strategy, leaf habit and light environment. Key Results Optimum temperatures for A sat (T optA ) and J max (T optJ ) increased with MAT but not for V cmax (T optV ). Although photosynthetic rates were higher for ‘light’ than ‘shaded’ leaves, light conditions did not generate differences in temperature response parameters. T optA did not differ with successional strategy, but early successional species had ~4 °C wider thermal niches than mid/late species. Semi-deciduous species had ~1 °C higher T optA than broadleaf evergreen species. Most global modelling efforts consider all tropical forests as a single ‘broadleaf evergreen’ functional type, but our data show that tropical species with different leaf habits display distinct temperature responses that should be included in modelling efforts. Conclusions This novel research will inform modelling efforts to quantify tropical ecosystem carbon cycling and provide more accurate representations of how these key ecosystems will respond to altered temperature patterns in the face of climate warming.

Carter, Kelsey R. [Oak Ridge National Laboratory (↗