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At least 397 records · Page 22

Zinc aluminate (ZnAl 2 O 4 ) refractory aggregates: Dilatometric sintering studies and thermal expansion coefficient

ZnAl 2 O 4 has recently been reported to enhance thermomechanical properties and slag corrosion resistance of refractory castables. The pore generation and deleterious expansion during in situ ZnAl 2 O 4 formation can limit their amount in a refractory composition. A comprehensive dilatometric study is presented, identifying the optimum raw materials and processing conditions. Preformed ZnAl 2 O 4 refractory aggregates were synthesized from industrial ZnO and reactive Al 2 O 3 by two-stage firing at 1050 °C and 1700 °C resulting in 0% open porosity. The ZnAl 2 O 4 powder calcined at 1050 °C is also a good refractory matrix material as it has better sinterability than preformed refractory-grade MgAl 2 O 4 and calcined alumina. The thermal expansion coefficient of ZnAl 2 O 4 aggregate in the range of 70–1600 °C was found to be 10.7 × 10 –6 K –1 , which is similar to tabular Al 2 O 3 (10.3 × 10 –6 K –1 ) and MgAl 2 O 4 (10.3 × 10 –6 K –1 ), but lower than dead burned MgO (16.4 × 10 –6 K –1 ), creating the possibility of developing thermal shock resistant refractories by utilizing this mismatch.

36 MATERIALS SCIENCE↗

Influence of cation species on thermal expansion of Y 2 Si 2 O 7 –Gd 2 Si 2 O 7 solid solutions

Mixtures of Y 2 Si 2 O 7 and Gd 2 Si 2 O 7 were synthesized by solid-state reaction at 1600°C and characterized via in situ x-ray diffraction (XRD) to determine their coefficients of thermal expansion (CTE). All solid solutions within the system exhibited the orthorhombic δ-RE 2 Si 2 O 7 (Pna2 1 ) structure. Thermal expansion measurements of Y 2 Si 2 O 7 and Gd 2 Si 2 O 7 correlated well with reported values in literature, and all synthesized solid solutions exhibited CTEs between Y 2 Si 2 O 7 and Gd 2 Si 2 O 7 . Generally, there was a slight decrease in CTE exhibited by the materials with increasing Gd 2 Si 2 O 7 content, with Gd 2 Si 2 O 7 having the lowest CTEs and Y 2 Si 2 O 7 the highest CTEs. Here, the decrease in CTE was attributed to stronger bonds of Gd-O over Y-O, as determined by calculated crystal orbital Hamilton populations using density functional theory. However, such differences were very small and crystal structure was the dominating factor in CTE trends.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural Distortions and Uniaxial Negative Thermal Expansion in the Polar Dion–Jacobson Oxide RbNdTa 2 O 7

We provide deeper insight into the crystal structures, sequential structural phase transitions (I2cm → Cmce → I4/mcm → P4/mmm), thermal expansion, and electronic properties of the n = 2 Dion–Jacobson polar oxide RbNdTa 2 O 7 , through X-ray powder diffraction, neutron powder diffraction, Raman studies, and density functional theory calculations. We observed a uniaxial negative thermal expansion (NTE) across the first-order transition, I2cm → Cmce, where the unit cell contracts along the c-axis, which is driven by a contraction of the NdTa 2 O 6 layer. Here, this NTE occurs within the temperature range of the first-order phase transition and contrasts with the corkscrew mechanism typically observed in Ruddlesden–Popper phases. In RbNdTa 2 O 7 , the I2cm (hybrid improper ferroelectric) → Cmce (antipolar) transition involves crucial changes in the bond lengths of Nd and Ta polyhedra, coupled with polar to antipolar displacement of the Nd ions, leading to a net contraction in the NdTa 2 O 6 layer along the c-axis, while preserving the overall octahedral tilting magnitude. This transition highlights the intricate interplay between the Nd and Ta coordination and the associated TaO 6 distortions. Temperature-dependent Raman spectra analysis further confirms the first-order structural transition and associated NTE, providing evidence for increased bond stiffness across this transition. Additionally, using neutron powder diffraction, we have determined that the transition I4/mcm → P4/mmm occurs at approximately 1150 K. Finally, we have calculated from DFT + U, the partial density of states, the energy bandgaps, and effective masses of the charge carriers of the polar ground structure.

Chemical structure↗

Mixed Precision Fermi-Operator Expansion on Tensor Cores from a Machine Learning Perspective

Here we present a second-order recursive Fermi-operator expansion scheme using mixed precision floating point operations to perform electronic structure calculations using tensor core units. A performance of over 100 teraFLOPs is achieved for half-precision floating point operations on Nvidia’s A100 tensor core units. The second-order recursive Fermi-operator scheme is formulated in terms of a generalized, differentiable deep neural network structure, which solves the quantum mechanical electronic structure problem. We demonstrate how this network can be accelerated by optimizing the weight and bias values to substantially reduce the number of layers required for convergence. We also show how this machine learning approach can be used to optimize the coefficients of the recursive Fermi-operator expansion to accurately represent the fractional occupation numbers of the electronic states at finite temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Facile Interfacial Reduction Suppresses Redox Chemical Expansion and Promotes the Polaronic to Ionic Transition in Mixed Conducting (Pr,Ce)O 2−δ Nanoparticles

Mixed ionic/electronic conductors (MIECs) are essential components of solid-state electrochemical devices, such as solid oxide fuel/electrolysis cells. For efficient performance, MIECs are typically nanostructured, to enhance the reaction kinetics. However, the effect of nanostructuring on MIEC chemo-mechanical coupling and transport properties, which also impact cell durability and efficiency, has not yet been well understood. Here, in this work, Pr 0.2 Ce 0.8 O 2−δ (PCO20) nanopowders were prepared by coprecipitation, then sintered in a modified dilatometer at three different temperatures (600, 725, and 850 °C) for microstructure evolution, resulting in three samples with different average particle sizes (23, 30, and 53 nm). The chemical strain and electronic/ionic conductivity were then measured simultaneously on stable nanostructures in four isotherms from 550 to 400 °C with steps in pO 2 (1 to 10 –4 atm O 2 ). A microcrystalline bar was prepared and measured for comparison. Particle size reduction led to a monotonically decreasing isothermal redox chemical strain, confirmed by in situ high-temperature, controlled-atmosphere XRD measurements. The corresponding conductivity measurements provided defect chemical insight into the particle size-dependent chemical expansion behavior. The significant weakening of the pO 2 dependence and decreased activation energy for electrical conduction with decreasing particle size indicated a decrease in the reduction enthalpy of PCO, shifting the transition from (Pr) polaronic to ionic behavior to higher pO 2 . STEM-EELS measurements confirmed the majority of Pr was reduced to 3+ in the nanoparticles, while Ce remained 4+. These results demonstrate suppression of deleterious chemical expansion and tailoring of the dominant charge carrier simply through controlling the particle size, providing insights for MIEC microstructural design.

ceria↗

Improving the accuracy and efficiency of quantum connected moments expansions

The still-maturing noisy intermediate-scale quantum technology faces strict limitations on the algorithms that can be implemented efficiently. In the realm of quantum chemistry, the variational quantum eigensolver (VQE) algorithm has become ubiquitous, with many variations. Alternatively, a promising new avenue has been unraveled by the quantum variants of techniques grounded on expansions of the moments of the Hamiltonian, notably the connected moments expansion (CMX) and the Peeters–Devreese–Soldatov (PDS) energy functional. Common to those approaches is that, upon preparing an approximate ground state used to compute the necessary moments, the accuracy of the estimated ground state energy depends on the degree of overlap between the prepared state and the true ground state. Thus, we use the ADAPT-VQE algorithm to test shallow circuit construction strategies for the purpose of increasing the overlap with the exact ground state, validated by the sizable accuracy improvement herein reported in the PDS and CMX ground state energies. We also show that we can take advantage of the fact that the terms to be measured are highly recurring in different moments, incurring a substantial reduction in the number of necessary measurements. Finally, by coupling this measurement caching with a threshold that determines whether a given term is to be measured based on its associated scalar coefficient, we observe a further reduction in the number of circuit implementations while allowing for tunable accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Empty perovskites as Coulomb floppy networks: Entropic elasticity and negative thermal expansion

Floppy networks (FNs) provide valuable insight into the origin of anomalous mechanical and thermal properties in soft matter systems, from polymers, rubber, and biomolecules to glasses and granular materials. Here, we use the same FN concept to construct a quantitative microscopic theory of empty perovskites, a family of crystals with ReO 3 structure, which exhibit a number of unusual properties. One remarkable example is ScF 3 , which shows a near-zero-temperature structural instability and large negative thermal expansion (NTE). Furthermore, we trace these effects to an FN-like crystalline architecture formed by strong nearest-neighbor bonds, which is stabilized by net electrostatic repulsion that plays a role similar to osmotic pressure in polymeric gels. NTE in these crystalline solids, which we conceptualize as Coulomb floppy networks, emerges from the tension effect of Coulomb repulsion combined with the FN's entropic elasticity and has the same physical origin as in gels and rubber. Our theory provides an accurate, quantitative description of phonons, thermal expansion, compressibility, and structural phase diagram, all in excellent agreement with experiments. The entropic stabilization of critical soft modes, which play only a secondary role in NTE, explains the observed phase diagram. Significant entropic elasticity resolves the puzzle of a marked, ≈50% discrepancy between the experimentally observed bulk modulus and ab initio calculations. The Coulomb FN approach is potentially applicable to other important materials with markedly covalent bonds, from perovskite oxides to iron chalcogenides, whose anomalous vibrational and structural properties are still poorly understood.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

An ℓ 0 ℓ 2 -norm regularized regression model for construction of robust cluster expansions in multicomponent systems

In this work we introduce ℓ 0 ℓ 2 -norm regularization and hierarchy constraints into linear regression for the construction of cluster expansions to describe configurational disorder in materials. The approach is implemented through mixed integer quadratic programming (MIQP). The ℓ 2 -norm regularization is used to suppress intrinsic data noise, while the ℓ 0 -norm is used to penalize the number of nonzero elements in the solution. The hierarchy relation between clusters imposes relevant physics and is naturally included by the MIQP paradigm. As such, sparseness and cluster hierarchy can be well optimized to obtain a robust, converged set of effective cluster interactions with improved physical meaning. We demonstrate the effectiveness of ℓ 0 ℓ 2 -norm regularization in two high-component disordered rocksalt cathode material systems, where we compare the cross-validation, convergence speed, and the reproduction of phase diagrams, voltage profiles, and Li-occupancy energies with those of the conventional ℓ 1 -norm regularized cluster expansion models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Endogenizing Probabilistic Resource Adequacy Risks in Deterministic Capacity Expansion Models

In this work, we demonstrate how power system capacity expansion models can understate the stochastic effects of thermal outages when considering resource availabilities on an hourly expected value basis, yielding system designs with multiple orders of magnitude more shortfall risk than stated adequacy targets. We develop a novel approximation approach to efficiently endogenize awareness of this risk in a deterministic, linear capacity expansion framework. We compare this approach to exogenous tuning of an energy reserve margin, the leading alternative method to compensate for unmodeled probabilistic shortfall risk. Empirical results from a test system show that the new endogenous method cost-effectively meets all regional reliability targets with a single optimization solve, and produces a near-identical system design as the incumbent method without the need for repeated re-optimizations to find an appropriate reserve level. The endogenous method may also use iterative re-optimizations to further improve solution quality, although these incremental benefits were modest in the system studied.

capacity expansion modeling↗

Representing DC-Coupled PV+Battery Hybrids in a Capacity Expansion Model

Recent technology cost and performance improvements and the federal investment tax credit (ITC) have driven growing interest in coupling solar photovoltaic (PV) and battery systems. Combining these technologies into co-located or hybridized PV+battery systems has the potential to lower costs and increase energy output relative to multiple independent systems. In this work, we provide an overview of PV+battery systems and demonstrate methods for incorporating them into NREL’s Regional Energy Deployment System (ReEDS) capacity expansion model. Although the methods are applied to a specific model, we anticipate that the approaches used here can be useful for informing PV+battery method development for other capacity expansion models. The implemented method relies heavily on the native representations of PV and battery technologies; therefore, the focus of this work is on capturing and parameterizing the interactions between them for a configuration in which the PV and battery technologies share a single bi-directional inverter. This work also demonstrates the impacts of including PV+battery systems in the ReEDS optimization for the conterminous United States through 2050. In particular, we perform parametric sensitivities for input assumptions that are uncertain and expected to influence PV+battery deployment levels, including (a) the cost of PV+battery systems relative to independent PV and battery systems, (b) the battery component’s qualification for the ITC, and (c) future cost trajectories for PV and battery systems. We find that PV+battery deployment could occur throughout the conterminous United States if there are cost savings associated with DC coupling PV and battery technologies. If even modest (5%) cost savings can be achieved (through a shared inverter and balance-of-system costs), then approximately one-third of utility-scale PV deployment through 2050 adopts the DC-coupled hybrid configuration, resulting in total PV+battery deployment that exceeds the magnitude of PV+battery projects in U.S. interconnection queues in 2020. If greater cost savings can be achieved through DC coupling (e.g., due to a growing amount of shared balance-of-system costs, reduced financial risk, or modularity) or more rapid cost and performance improvements are realized for PV and battery technologies, then total PV+battery deployment and the share of PV and battery deployment that adopts the hybrid configuration grows (to >50%). In all cases, growing PV+battery deployment primarily displaces independent PV and battery technologies, indicating the strong competition between the hybrid and independent configurations comprising technologies with similar performance characteristics.

14 SOLAR ENERGY↗

Nodal Capacity Expansion Modeling with ReEDS: A Case Study of the RTS-GMLC Test System

Test systems play an important role in power systems analysis and are used extensively for a wide range of purposes like reliability analysis, production cost modeling, studying the impacts of load shifting, and many more. These test systems have continued to evolve over the years to keep pace with changing system compositions due to technology and policy changes. In this work, we apply the Regional Energy Deployment System (ReEDS) model, a large-scale capacity expansion model (CEM), on the nodal RTS-GMLC system to perform capacity expansion of the bus-level test system. This work both demonstrates that a large-scale CEM can successfully be applied to nodal systems, and that the CEM can allow a test system to be evolved to meet desired criteria. The process allowed the coupling of CEM data not available in the test system (such as capital costs) with test system data to provide plausible system evolutions in line with scenario specifications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Direct measurement of the thermal expansion coefficient of epitaxial WSe 2 by four-dimensional scanning transmission electron microscopy

Current reports of thermal expansion coefficients (TEC) of two-dimensional (2D) materials show large discrepancies that span orders of magnitude. Determining the TEC of any 2D material remains difficult due to approaches involving indirect measurement of samples that are atomically thin and optically transparent. We demonstrate a methodology to address this discrepancy and directly measure TEC of nominally monolayer epitaxial WSe 2 using four-dimensional scanning transmission electron microscopy (4D-STEM). Experimentally, WSe 2 from metal-organic chemical vapor deposition (MOCVD) was heated through a temperature range of 18- 564 °C using a barrel-style heating sample holder to observe temperature-induced structural changes without additional alterations or destruction of the sample. By combining 4D-STEM measurements with quantitative structural analysis, the thermal expansion coefficient of nominally monolayer polycrystalline epitaxial 2D WSe 2 was determined to be (3.5 ± 0.9) × 10 -6 K -1 and (5.7 ± 2) × 10 -5 K -1 for the in- and out-of-plane TEC, respectively, and (3.6 ± 0.2) × 10 -5 K -1 for the unit cell volume TEC, in good agreement with historically determined values for bulk crystals.

2D materials↗

Leveraging Cell Expansion Sensing in State of Charge Estimation: Practical Considerations

Measurements such as current and terminal voltage that are typically used to determine the battery’s state of charge (SOC) are augmented with measured force associated with electrode expansion as the lithium intercalates in its structure. The combination of the sensed behavior is shown to improve SOC estimation even for the lithium ion iron phosphate (LFP) chemistry, where the voltage–SOC relation is flat (low slope) making SOC estimation using measured voltage difficult. For the LFP cells, the measured force has a non-monotonic F–SOC relationship. This presents a challenge for estimation as multiple force values can correspond to the same SOC. The traditional linear quadratic estimator can be driven to an incorrect SOC value. To address these difficulties, a novel switching estimation gain is used based on determining the operating region that corresponds to the actual SOC. Moreover, a drift in the measured force associated with a shift of the cell SOC–expansion behavior over time is addressed with a bias estimator for the force signal. The performance of Voltage-based (V) and Voltage and Force-based (V&F) SOC estimation algorithms are then compared and evaluated against a desired ±5% absolute error bound of the SOC using a dynamic stress test current protocol that tests the proposed estimation scheme across wide range of SOC and current rates.

25 ENERGY STORAGE↗

GRIDCERF - Geospatial Raster Input Data for Capacity Expansion Regional Feasibility

The Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package is a high-resolution product to evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States. GRIDCERF offers hundreds of individual suitability layers for use with both renewable and non-renewable power plant technology configurations in a harmonized format that can be easily ingested by geospatially-enabled modeling software. It also provides pre-compiled technology-specific suitability layers and allows for user customization to robustly address science objectives when evaluating varying future conditions. GRIDCERF data can be directly used with the CERF (Capacity Expansion Regional Feasibility) model to site power plants at a 1km resolution. GRIDCERF includes composite technology siting suitability raster layers for the following utility scale technology configurations. Note that, in addition to technology sub-types shown below, various cooling types are also included (recirculating, pond, once-through, recirculating-seawater, dry-hybrid, or dry) for various technologies. Biomass Conventional (with or without CCS) IGCC (with or without CCS) Coal Conventional (with or without CCS) IGCC (with or without CCS) Natural Gas Combined-cycle (CC) (with or without CCS) Turbine Geothermal Enhanced Geothermal Systems (EGS) - Class 1 through Class 5 resource potential Nuclear Gen 2 Light Water Reactor (LWR) Gen 3 Small Modular Reactor (SMR) Gen 3 AP1000 Refined Liquids Combined-cycle (CC) (with or without CCS) Turbine Solar Photovoltaic (PV) - for capacity factors in the range of 6-18% Utility-scale Concentrating Solar Power (CSP) - for capacity factors in the range of 24-46% Tower Wind (Onshore) - for capacity factors in the range of 5-50% 80m hub height 100m hub height 120m hub height 140m hub height Wind (Offshore) - for capacity factors in the range of 25-60% 100m hub height 140m hub height 160m hub height

capacity expansion↗

GRIDCERF - Geospatial Raster Input Data for Capacity Expansion Regional Feasibility

The Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package is a high-resolution product to evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States. GRIDCERF offers hundreds of individual suitability layers for use with both renewable and non-renewable power plant technology configurations in a harmonized format that can be easily ingested by geospatially-enabled modeling software. It also provides pre-compiled technology-specific suitability layers and allows for user customization to robustly address science objectives when evaluating varying future conditions. GRIDCERF data can be directly used with the CERF (Capacity Expansion Regional Feasibility) model to site power plants at a 1km resolution. GRIDCERF includes composite technology siting suitability raster layers for the following utility scale technology configurations. Note that, in addition to technology sub-types shown below, various cooling types are also included (recirculating, pond, once-through, recirculating-seawater, dry-hybrid, or dry) for various technologies. Biomass Conventional (with or without CCS) IGCC (with or without CCS) Coal Conventional (with or without CCS) IGCC (with or without CCS) Natural Gas Combined-cycle (CC) (with or without CCS) Turbine Geothermal Enhanced Geothermal Systems (EGS) - Class 1 through Class 5 resource potential Nuclear Gen 2 Light Water Reactor (LWR) Gen 3 Small Modular Reactor (SMR) Gen 3 AP1000 Refined Liquids Combined-cycle (CC) (with or without CCS) Turbine Solar Photovoltaic (PV) - for capacity factors in the range of 6-18% Utility-scale Concentrating Solar Power (CSP) - for capacity factors in the range of 24-46% Tower Wind (Onshore) - for capacity factors in the range of 5-50% 80m hub height 100m hub height 120m hub height 140m hub height Wind (Offshore) - for capacity factors in the range of 25-60% 100m hub height 140m hub height 160m hub height

capacity expansion↗

Two-point Taylor series expansions

Coefficients calculated for Taylor series expansion about two points - application of Taylor expansion to two-body problem

TWO-BODY PROBLEM↗

The JPL Cryogenic Dilatometer: Measuring the Thermal Expansion Coefficient of Aerospace Materials

This slide presentation details the cryogenic dilatometer, which is used by JPL to measure the thermal expansion coefficient of materials used in Aerospace. Included is a system diagram, a picture of the dilatometer chamber and the laser source, a description of the laser source, pictures of the interferometer, block diagrams of the electronics and software and a picture of the electronics, and software. Also there is a brief review of the accurace.error budget. The materials tested are also described, and the results are shown in strain curves, JPL measured strain fits are described, and the coefficient of thermal expansion (CTE) is also shown for the materials tested.

dilatometer↗