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DOE OSTI2024

RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project

Abstract. The radiative–convective equilibrium (RCE) model intercomparison project (RCEMIP) leveraged the simplicity of RCE to focus attention on moist convective processes and their interactions with radiation and circulation across a wide range of model types including cloud-resolving models (CRMs), general circulation models (GCMs), single-column models, global cloud-resolving models, and large-eddy simulations. While several robust results emerged across the spectrum of models that participated in the first phase of RCEMIP (RCEMIP-I), two points that stand out are (1) the strikingly large diversity in simulated climate states and (2) the strong imprint of convective self-aggregation on the climate state. However, the lack of consensus in the structure of self-aggregation and its response to warming is a barrier to understanding. Gaining a deeper understanding of convective aggregation and tropical climate will require reducing the degrees of freedom with which convection can vary. Therefore, we propose phase II of RCEMIP (RCEMIP-II) that utilizes a prescribed sinusoidal sea surface temperature (SST) pattern to provide a constraint on the structure of convection and move one critical step up the model hierarchy. This so-called “mock-Walker” configuration generates features that resemble observed tropical circulations. The specification of the mock-Walker protocol for RCEMIP-II is described, along with example results from one CRM and one GCM. RCEMIP-II will consist of five required simulations: three simulations with the same three mean SSTs as in RCEMIP-I but with an SST gradient and two additional simulations at one of the mean SSTs with different values of the SST gradients. We also test the sensitivity to the imposed SST gradient and the domain size. Under weak SST gradients, unforced self-aggregation emerges across the entire domain, similar to what was found in RCEMIP. As the SST gradient increases, the convective region narrows and is more confined to the warmest SSTs. At warmer mean SSTs and stronger SST gradients, low-frequency variability in the convective aggregation emerges, suggesting that simulations of at least 200 d may be needed to achieve robust equilibrium statistics in this configuration. Simulations with different domain sizes generally have similar mean statistics and convective structures, depending on the value of the SST gradient. The prescribed SST boundary condition is the only difference in the set-up between RCEMIP-II and RCEMIP-I, which enables comparison between the two; however, we also welcome participation in RCEMIP-II from models that did not participate in RCEMIP-I.

Geology↗

DOE OSTI2022

Renewable Thermal Energy Systems Designed for Industrial Process Solutions in Multiple Industries

Industrial decarbonization is a key area that must be accelerated, to foster the removal of fossil fuels from the provision of heat, especially at low temperatures less than 300 degrees C. This paper looks at the results of two case studies for understanding the economics and potential for renewable thermal energy systems (RTES), particularly in hybrid configurations to provide industrial process heat (IPH). The first case study looks at heat pumps for district heating, and the second, the use of linear Fresnel collectors (LFCs) coupled with phase change material (PCM) thermal energy storage (TES) for direct steam generation (DSG). Using district heat as an input for the heat pump, three cases were run harvesting energy from ambient water (5 degrees C), sewage water (20 degrees C), and a solar collector (35 degrees C). Accounting for elevated costs of infrastructure for each heat source, the levelized cost of heat (LCOH) of the first case study ranged from $4-$15 per million British Thermal Units (MMBTU). For the second case study modeling LFCs with PCM and TES, the results show that a LCOH of $9-$15 per MMBTU is possible, depending on the direct normal irradiance.

concentrated solar thermal↗

DOE OSTI2022

Renewable Thermal Energy Systems Designed for Industrial Process Solutions in Multiple Industries: Preprint

Industrial decarbonization is a key area that must be accelerated, to foster the removal of fossil fuels from the provision of heat, especially at low temperatures less than 300 degrees C. This paper looks at the results of two case studies for understanding the economics and potential for renewable thermal energy systems (RTES), particularly in hybrid configurations to provide industrial process heat (IPH). The first case study looks at heat pumps for district heating, and the second, the use of linear Fresnel collectors (LFCs) coupled with phase change material (PCM) thermal energy storage (TES) for direct steam generation (DSG). Using district heat as an input for the heat pump, three cases were run harvesting energy from ambient water (5 degrees C), sewage water (20 degrees C), and a solar collector (35 degrees C). Accounting for elevated costs of infrastructure for each heat source, the levelized cost of heat (LCOH) of the first case study ranged from $4-$10 per million British Thermal Units (MMBTU). For the second case study modeling LFCs with PCM and TES, the results show that a LCOH of $9-$15 per MMBTU is possible, depending on the direct normal irradiance.

concentrated solar thermal↗

DOE OSTI2020

Charge transfer rate constants for the carotenoid-porphyrin-C 60 molecular triad dissolved in tetrahydrofuran: The spin-boson model vs the linearized semiclassical approximation

Charge transfer rate constants were calculated for the carotenoid-porphyrin-C 60 (CPC 60 ) molecular triad dissolved in explicit tetrahydrofuran. The calculation was based on mapping the all-atom anharmonic Hamiltonian of this system onto the spin-boson Hamiltonian. The mapping was based on discretizing the spectral density from the time correlation function of the donor–acceptor potential energy gap, as obtained from all-atom molecular dynamics simulations. Different spin-boson Hamiltonians were constructed for each of the possible transitions between the three excited electronic states in two different triad conformations. The rate constants of three possible transitions were calculated via the quantum-mechanically exact Fermi’s golden rule (FGR), as well as a progression of more approximate expressions that lead to the classical Marcus expression. The advantage of the spin-boson approach is that once the mapping is established, the quantum-mechanically exact FGR and the hierarchy of approximations are known in closed form. The classical Marcus charge transfer rate constants obtained with the spin-boson Hamiltonians were found to reproduce those obtained from all-atom simulations with the linearized semiclassical approximation, thereby confirming the equivalence of the two approaches for this system. Furthermore, within the spin-boson Hamiltonian, we also found that the quantum-mechanically exact FGR rate constants were significantly enhanced compared to the classical Marcus theory rate constants for two out of three transitions in one of the two conformations under consideration. The results confirm that mapping to the spin-boson model can yield accurate predictions for charge transfer rate constants in a system as complex as CPC 60 dissolved in tetrahydrofuran.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A New Recycled Al–Si–Mg Alloy for Sustainable Structural Die Casting Applications

The use of secondary aluminum for structural components in the automotive industry is limited by the high Fe contents in recycled alloys which often result in the formation of brittle β-Al 5 FeSi phase which reduces the ductility of aluminum castings. In this study, a new secondary Al-Si-Mg alloy with high Fe content (about 0.44 wt.%) was developed for die casting applications. Based on thermodynamic modeling, manganese was added to obtain a designed Fe-to-Mn ratio of 2 which successfully suppressed the formation of β-Al 5 FeSi phase, by forming α-Al 15 (Fe,Mn) 3 Si 2 phase with rounded or hexagonal morphology. Additionally, a fine needle-like π-Al 8 FeMg 3 Si 2 phase was also formed within the eutectic regions. The new recycled alloy showed comparable mechanical properties in as-cast and heat treated (T5 and T6) conditions to three major primary die cast alloys (≤ 0.2 wt.% Fe) with similar composition. Ductility up to 7.4% from tensile elongation was achieved in as-cast recycled alloy due to the modification and refinement of α-Al 15 (Fe,Mn) 3 Si 2 by Mn and Sr additions. Tensile elongation was further improved to 9.1% after T6 treatment as a result of dissolution of π-Al 8 FeMg 3 Si 2 phase, defragmentation of α-Al 15 (Fe,Mn) 3 Si 2 and the spheroidization of Si phase. This new alloy provides a promising path for increasing usage of recycled aluminum with high Fe content in structural die castings for automotive and other applications.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Using Ambient Noise Seismic Interferometry and Local and Teleseismic Earthquakes to Determine Crustal Thickness and Moho Structure of the Northwestern Gulf of Mexico Margin

Abstract The northwestern part of the Gulf of Mexico has undergone two episodes of continental rifting and collision and produced structural artifacts that are now buried under many kilometers of sediments, complicating investigations of the region. The deep sedimentary package precludes outcrops and points to a need for the application of seismic techniques, but low rates of seismicity in the region and sparse seismic monitoring limit the utility of traditional seismic methods. We therefore use diverse data to perform two‐dimensional seismic tomography across the dry land portion of the margin. Data are gleaned from teleseismic and regional earthquakes, postcritical SsPmp arrivals, and direct P wave energy identified with seismic interferometry that were recorded by a broadband, three‐component array and partially overlapping short‐period, vertical‐component array. The Pn and postcritical SsPmp phase help constrain the Moho discontinuity, which a previous receiver function study suggested was absent beneath the seaward portion of this transect. A high‐velocity body is observed in the crust at the same location as the Houston Magnetic Anomaly, possibly marking rocks from the Alleghenian continental assembly. The crust thins from NW to SE, indicating that extension occurred mostly to the south of the Ouachita orogeny. Our model indicates that the margin's sediment package reaches a maximum thickness of ~15 km at the coast and becomes unresolvably thin near the Llano Uplift.

58 GEOSCIENCES↗

DOE OSTI2022

An End-To-End Earthquake Detection Method for Joint Phase Picking and Association Using Deep Learning

Earthquake monitoring by seismic networks typically involves a workflow consisting of phase detection/picking, association, and location tasks. In recent years, the accuracy of these individual stages has been improved through the use of machine learning techniques. Here, in this study, we introduce a new end-to-end approach that improves overall earthquake detection accuracy by jointly optimizing each stage of the detection pipeline. We propose a neural network architecture for the task of multi-station processing of seismic waveforms recorded over a seismic network. This end-to-end architecture consists of three sub-networks: a backbone network that extracts features from raw waveforms, a phase picking sub-network that picks P- and S-wave arrivals based on these features, and an event detection sub-network that aggregates the features from multiple stations to associate and detect earthquakes across a seismic network. We use these sub-networks together with a shift-and-stack module based on back-projection that introduces kinematic constraints on arrival times, allowing the neural network model to generalize to different velocity models and to variable station geometry in seismic networks. We evaluate our proposed method on the STanford EArthquake Dataset (STEAD) and on the 2019 Ridgecrest, CA earthquake sequence. The results demonstrate that our end-to-end approach can effectively pick P- and S-wave arrivals and achieve earthquake detection accuracy rivaling that of other state-of-the-art approaches. Because our approach preserves information across tasks in the detection pipeline, it has the potential to outperform approaches that do not.

58 GEOSCIENCES↗

DOE OSTI2025

Multipoint Correlations in Poisson Media

Multipoint correlations in randomly heterogeneous composite media are determined by the probability that a set of points belong to specific phases. They determine a wide range of macroscopic transport properties such as conductivity, dielectric constant, diffusion coefficient, and transmittance. The Poisson model—a random tesselation of space by hyperplanes—provides realistic descriptions of heterogeneous media in, e.g., radiation-transport applications; yet, until now, it has lacked closed-form expressions for its multipoint correlations. We resolve this problem by presenting an exact solution for the multipoint correlations in the Poisson model. By comparing it to Monte Carlo simulations of four-point correlations in three dimensions, we demonstrate the accuracy of our solution. In conclusion, we visualize the multipoint correlations and discuss their features.

Amorphous materials↗

DOE OSTI2024

Understanding spatial and temporal drivers of variation in tree hydraulic processes and their consequences for climate feedbacks (Final Technical Report)

This is the final technical report from the first phase of a project that changed institutions. The grant was titled “Understanding spatial and temporal drivers of variation in tree hydraulic processes and their consequences for climate feedbacks.” The overall objectives of this project were to (1) provide model‐compatible datasets of key plant hydraulic traits and status for model evaluation, parameterization and validation and (2) use these data to pinpoint ecosystem responses to a changing hydroclimate by addressing both long‐term climatic drying and episodic extreme droughts. We planned to address the objectives with three research activities to quantify plant responses to chronic water stress and episodic drought: (1) generate high frequency observations of soil and plant hydraulic data across different landscape positions at multiple sites, (2) quantify plant hydraulic trait plasticity in response to experimental soil moisture reduction in situ in two central hardwood forests, and (3) simulate the carbon consequences of incorporating plant hydrodynamics and plant acclimation to water stress in the DOE‐sponsored plant hydrodynamics model FATES‐HYDRO. As of the transfer of this project to another institution, we had made substantial progress on activities 1 and 2, and started activity 3.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Lepton-Nucleus Scattering Measurements for Neutrino Interactions and Oscillations

Currently running and forthcoming precision neutrino oscillation experiments aim to unambiguously determine the neutrino mass ordering, the charge-parity violating phase in the lepton sector and the possible existence of physics Beyond the Standard Model. To have an understanding of all the effects necessary for the success of these experiments, lepton-nucleus interactions must be modeled in unprecedented detail. With this thesis, expertise in both neutrino and electron cross-section modeling and analysis was leveraged in order to make fundamental and critical improvements to our understanding of these interactions. The outlined work takes a significant step towards this high-precision measurement era with three complementary approaches. Cross sections are reported using neutrino data sets from the MicroBooNE liquid argon time projection chamber detector at Fermi National Laboratory, as well as electron scattering data from the CLAS detector at Thomas Jefferson National Laboratory. Furthermore, the modeling development of the commonly used GENIE event generator is presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Lepton-Nucleus Scattering Measurements for Neutrino Interactions and Oscillations

Papadopoulou, Afroditi↗

DOE OSTI2020

Performance and Techno-Economic Evaluation of a Three-Phase, 50-kW SiC-Based PV Inverter

The technical capabilities and benefits of silicon carbide (SiC) compared to silicon (Si) based power electronics converters as well as the premium associated with using SiC instead of Si are well understood. This work proves that the benefits provided by SiC, such as increased efficiency, would result in a lower levelized cost of energy (LCOE) compared to both commercially available, state-of-the-art inverters and the benchmark commercial system cost calculated for the U.S. Department of Energy Solar Energy Technologies Office's SunShot program. The LCOE is calculated to be same as the commercial benchmark despite the installed system cost being 8% more than the benchmark. The LCOE calculation is based on both experiential values obtained from testing the SiC photovoltaic (PV) inverter and on the bottoms-up modeled volume cost for the same 50-kW SiC-based inverter. The PV system used for the LCOE model is also explained, and the system cost breakout is presented in this paper. Furthermore, multiple scenarios with variations in the PV system are presented to show their effect on the system LCOE.

14 SOLAR ENERGY↗

DOE OSTI2020

Computational modeling of charge hopping dynamics along a disordered one-dimensional wire with energy gradients in quantum environments

This computational study investigates the effects of energy gradients on charge hopping dynamics along a one-dimensional chain of discrete sites coupled to quantum bath, which is modeled at the level of Pauli master equation (PME). This study also assesses the performance of different approximations for the hopping rates. Three different methods for solving the PME, a fourth order Runge–Kutta method, numerical diagonalization of the rate matrix followed by analytic propagation, and kinetic Monte Carlo simulation method, are tested and confirmed to produce virtually identical values of time dependent mean square displacement, diffusion constant, and mobility. Five different rate expressions, exact numerical evaluation of Fermi’s Golden Rule (FGR) rate, stationary phase interpolation (SPI) approximation, semiclassical approximation, classical Marcus rate, and Miller–Abrahams rate, are tested to help understand the effects of approximations in representing quantum environments in the presence of energy gradients. The results based on direct numerical evaluation of FGR rate exhibit transition from diffusive to non-diffusive behavior with the increase in the gradient and show that the charge transport in the quantum bath is more sensitive to the magnitude of the gradient and the disorder than in the classical bath. Among all the four approximations for the hopping rates, the SPI approximation is confirmed to work best overall. A comparison of two different methods to calculate the mobility identifies drift motion of the population distribution as the major source of non-diffusive behavior and provides more reliable information on the contribution of quantum bath.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

2D photofragmentation LIF imaging of H 2 O 2 and HO 2 in the effluent of an atmospheric-pressure plasma jet: effects of solid and liquid interfaces

Two-dimensional (2D) absolute measurements of hydrogen peroxide (H 2 O 2 ) and approximations of the hydroperoxyl radical (HO 2 ) in the effluent of a COST Reference Microplasma Jet operated with a He/H 2 O feed gas are presented. Gas-phase densities are mapped using photofragmentation laser-induced fluorescence (PF-LIF) under three boundary conditions: open effluent, a solid target, and a liquid target. A novel method is presented for separating PF-LIF signals from H 2 O 2 and HO 2 using comparative measurements in oxygen-rich and oxygen-free environments to exploit the preferential formation of HO 2 in the presence of molecular oxygen. This separation strategy is supported by results from a plug-flow plasma chemistry model. Measured densities agree closely with model predictions in both magnitude and trend, while the 2D experimental distributions provide additional insight into the spatial dependencies of these species. In particular, the results show distinct differences in species transport depending on the target type: solid surfaces induce lateral deflection and reduced centerline densities, whereas liquid interfaces promote axial accumulation and higher near-axis concentrations.

atmospheric-pressure plasma jet (APPJ)↗

DOE OSTI2023

Ti-6Al-4V to over 1.2 TPa: Shock Hugoniot experiments, ab initio calculations, and a broad-range multiphase equation of state

Titanium alloys are used in a large array of applications. In this work we focus our attention on the most used alloy, Ti-6Al-4V (Ti64), which has excellent mechanical and biocompatibility properties with applications in aerospace, defense, biomedical, and other fields. Here we present high-fidelity experimental shock compression data measured on Sandia’s Z machine. We extend the principal shock Hugoniot for Ti64 to more than threefold compression, up to over 1.2 TPa. We use the data to validate our ab initio molecular dynamics simulations and to develop a highly reliable, multiphase equation of state (EOS) for Ti64, spanning a broad range of temperature and pressures. The first-principles simulations show very good agreement with Z data and with previous three-stage gas gun data from Sandia’s STAR facility. The resulting principal Hugoniot and the broad-range EOS and phase diagram up to 10 TPa and 10 5 K are suitable for use in shock experiments and in hydrodynamic simulations. The high-precision experimental results and high-fidelity simulations demonstrate that the Hugoniot of the Ti64 alloy is stiffer than that of pure Ti and reveal that Ti64 melts on the Hugoniot at a significantly lower pressure and temperature than previously modeled.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Stability margin analysis of the Holos-quad microreactor design

A simplified point model of the Holos-Quad microreactor is introduced. The model is based on the point kinetics equations coupled to three heat balance equations, representing the mean temperatures of the fuel particles, the graphite moderator and the helium coolant. The differential equations are converted to the frequency domain, enabling the construction of the closed-loop reactor transfer function. Using this function the stability margins of the core design is analyzed for various power levels. It is shown that the gain margins approaches infinity, demonstrating the stability of the reactor for all power levels. The phase margin at nominal power is about 60 degrees, however it shows a non-monotonous dependence on power, with minimal value obtained for about 10% of nominal power. As power level is further increased, the phase margin also increases, demonstrating the reactor becomes more stable. This behavior may be of high importance in load-follow scenarios, where the power level of the reactor changes with time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Computational Approaches for Clean Energy Materials

Currently, 80% of the global final energy consumption occurs in form of fuels and only 20% as electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, a successful energy transition will require enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies. As much as photovoltaic capacities have grown over the past 20 years, it is far from clear that current technologies and materials are up to the task to grow from here by yet another factor 100 until 2050. Therefore, sustained research efforts on emerging inorganic semiconductors for solar electricity and fuels are essential for facing the double challenge of climate change and energy security. Computational materials science can make important contributions, guiding and supporting research activities through both materials search and discovery and through detailed studies that help to develop a mechanistic understanding of materials performance and bottlenecks. This presentation will highlight three recent computational projects with relevance for photovoltaics and solar fuels (1) Defect graph neural networks (dGNN) for materials discovery in solar thermochemical hydrogen (STCH) [1]. The dGNN approach facilitates broad and fast materials screening for defect properties. (2) Modeling highly off-stoichiometric systems by evaluating the free energy of defect interaction [2]. This approach allows quantitative prediction of H2 production in complex STCH oxides. (3) First-principles atomic structure prediction for interfaces [3]. This work showed how an atomically thin CdCl2 interlayer phase enables in principle ideal electron transport across the incommensurate SnO2/CdTe interface. [1] M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. (2023). https://doi.org/10.1038/s43588-023-00495-2. [2] A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024). https://doi.org/10.1103/PRXEnergy.3.013008. [3] A. Sharan, M. Nardone, D. Krasikov, N. Singh, S. Lany, Appl. Phys. Rev. 9, 041411 (2022). https://doi.org/10.1063/5.0104008.

density functional theory↗

DOE OSTI2022

Versatile Sequential Casting Processing for Highly Efficient and Stable Binary Organic Photovoltaics

Forming an ideal bulk heterojunction (BHJ) morphology is a critical issue governing the photon to electron process in organic solar cells (OSCs). Complementary to the widely-used blend casting (BC) method for BHJ construction, sequential casting (SC) can also enable similar or even better morphology and device performance for OSCs. Here, BC and SC methods on three representative donor:acceptor (D:A) blends are utilized, that is, PM6:PC 71 BM, PM6:IT-4F and PM6:L8-BO. Higher power conversion efficiencies (PCEs) in all cases by taking advantage of beneficial morphology from SC processing are achieved, and a champion PCE of 18.86% (certified as 18.44%) based on the PM6:L8-BO blend is reached, representing the record value among binary OSCs. The observations on phase separation and vertical distribution inspire the proposal of the swelling–intercalation phase-separation model to interpret the morphology evolution during SC processing. Further, the vertical phase segregation is found to deliver an improvement of device performance via affecting the charge transport and collection processes, as evidenced by the D:A-ratio-dependent photovoltaic properties. Besides, OSCs based on SC processing show advantages on device photostability and upscale fabrication. Finally, this work demonstrates the versatility and efficacy of the SC method for BHJ-based OSCs.

14 SOLAR ENERGY↗