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DOE OSTI2020

Fast and Accurate Core Analysis by the Full-Immersion Pressure-Pulse Decay: Part 2—Practice and Demonstration

Summary This study continues the work of presenting a novel approach for making petrophysical assessments of tight core samples. This method, the full-immersion pressure-pulse decay (Hannon 2019), involves applying a rapid increase in pressure in a chamber surrounding the entire outer surface area of a cylindrical sample, shutting the system in, and monitoring the pressure decay in the chamber as it reaches a new equilibrium. A precursor article covered the numerical simulator designed to model flow through the sample, demonstrating its performance and accuracy in addition to providing a first-order comparison between the speed and shape of the pressure-decay responses of the full-immersion method with those of other similar transient methods. This study covers the parameter-estimation procedure and experimental verification through a proof-of-concept laboratory investigation. The investigations provided here demonstrate that under appropriate, achievable experimental conditions, the pressure data can be analyzed in such a way that returns an estimate of the porosity and apparent permeabilities both parallel and perpendicular to bedding from a single test performed on a single cylindrical sample. After determining these experimental conditions (the uniqueness window), this report outlines a data-inversion strategy to estimate the petrophysical properties (porosity, horizontal permeability, and vertical permeability) from each test. This strategy is put to the test through comparisons with measurements performed by a commercial core laboratory. A common set of samples recovered from an outcrop of a tight-gas sandstone formation were investigated using the full-immersion method, and their results are compared with those from conventional steady-state measurement procedures performed by the commercial laboratory. Comparisons between petrophysical characterizations of these samples, which had permeabilities between 25 nd and 2.3 μd, demonstrated close agreement in most cases. However, whereas steady-state measurements performed at the professional laboratory required 4 to 5 hours of testing time per measurement of a single permeability, similar assessments using the full-immersion technique, requiring approximately 5 to 10 minutes to complete, returned estimates of the horizontal and vertical permeability simultaneously. Additional analyses are provided to determine principal reasons of discrepancies in instances where agreement was not as strong. Based on lessons learned from these experiences, the report closes with suggestions on areas of improvement in the experimental approach. Once complete, these developments should propel this technology to fill a critical need to determine petrophysical properties (porosity and permeability) of tight rocks in a time-efficient manner and in a way that does not compromise their accuracy.

Energy & Fuels↗

DOE OSTI2023

Modeling the Amplfied OSC Experiment at IOTA

Optical Stochastic Cooling (OSC), a beam cooling technique based on Stochastic Cooling, is in the early stages of experimental development. It uses radiation produced by the beam in an undulator magnet (the pickup) to correct the momentum deviation of particles downstream in another undulator (the kicker). The OSC mechanism was recently demonstrated at Fermilabʼs IOTA ring using a passive conﬁguration. However, the cooling rate of OSC can be dramatically increased by ﬁrst amplifying the undulator radiation before applying the corrective kick. In collaboration with the IOTA experiment, we developed a computational model of the OSC mechanism. This work presents beam‐dynamics simulations of the ampliﬁed‐OSC conﬁguration. We implement a model of intrabeam scattering and study the eﬀects on beam equilibrium and diﬀusion rate as a function of bunch charge. Finally, we investigate the phase‐space dynamics with various coupling conﬁgurations between the transverse and longitudinal planes.

Dick, A. J.↗

DOE OSTI2023

SCALE Modeling of the Sodium Cooled Fast-Spectrum Advanced Burner Test Reactor

This report documents the modeling and simulation of a sodium-cooled fast reactor (SFR) as part of a U.S. Nuclear Regulatory Commission–sponsored project to assess the modeling and simulation capabilities for accident progression, source term, and consequence analysis for advanced reactor technologies with the Oak Ridge National Laboratory code SCALE and the Sandia National Laboratories (SNL) code MELCOR. Based on publicly available benchmark specifications, a fully heterogeneous 3D SCALE model of the 250 MWth Advanced Burner Test Reactor (ABTR) was developed to demonstrate SCALE’s capabilities for full-core reactivity analysis, fuel inventory prediction, and decay heat analysis of an SFR. The benchmark specifications contain modeling details for the ABTR core at the beginning of equilibrium cycle (BOEC) at operating conditions; they were derived from a 2006 preconceptual design report produced by Argonne National Laboratory. The ABTR was designed to demonstrate reactor-based transmutation of transuranics, that is, to “burn” transuranics recovered from light-water reactor (LWR) spent fuel. The ABTR’s fuel is designed to operate in 4 month cycles using uranium/transuranic (U/TRU) metallic fuel, with a TRU content of approximately 20%, at a conversion ratio of approximately 0.6. Various reactivity calculations were performed with SCALE for the ABTR and, where possible, compared with results available in the open literature. Additionally, SCALE was used to perform a full-core depletion calculation over the 4 month cycle to obtain the nuclide inventory at the end of equilibrium cycle (EOEC). These nuclide inventories, decay heat, power profiles, and reactivity feedback coefficients at EOEC represent the initial conditions for analyzing severe accident scenarios with MELCOR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Equilibration and “Thermalization” in the Adapted Caldeira–Leggett Model

I explore the processes of equilibration exhibited by the Adapted Caldeira–Leggett (ACL) model, a small unitary “toy model” developed for numerical studies of quantum decoherence between an SHO and an environment. I demonstrate how dephasing allows equilibration to occur in a wide variety of situations. While the finite model size and other “unphysical” aspects prevent the notions of temperature and thermalization from being generally applicable, certain primitive aspects of thermalization can be realized for particular parameter values. I link the observed behaviors to intrinsic properties of the global energy eigenstates, and argue that the phenomena I observe contain elements which might be key ingredients that lead to ergodic behavior in larger more realistic systems. The motivations for this work range from curiosity about phenomena observed in earlier calculations with the ACL model to much larger questions related to the nature of equilibrium, thermalization, and the emergence of physical laws.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Adsorption of neodymium, dysprosium, and ytterbium to goethite under varying aqueous chemistry conditions [dataset]

The adsorption of rare earth elements (REEs) to iron oxides can regulate the mobility of REEs in the environment and is heavily influenced by water chemistry. This study utilized batch experiments to examine the adsorption of Nd, Dy, and Yb to goethite under varying pH, electrolyte (type and concentration), and concentrations of dissolved inorganic carbon and citrate. REE adsorption was strongly influenced by pH, with an increase from essentially no adsorption at pH 3.0 to nearly complete adsorption at pH 6.5 and higher. Citrate enhanced the adsorption of REEs at low pH (< 5.0), likely by forming goethite-REE-citrate ternary surface complexes. However, citrate inhibited the adsorption of REEs at higher pH (> 5.0) by forming aqueous REE-citrate complexes. Ionic strength had a small influence on REE adsorption, and the presence of dissolved inorganic carbon had no discernible effect. Equilibrium adsorption was interpreted with a triple layer surface complexation model (SCM). The selection of surface complexation reactions was guided by extended X-ray absorption fine structure spectra. A SCM with a single bidentate inner-sphere surface complexation reaction for Nd and two inner-sphere surface complexation reactions (one monodentate and one bidentate reaction) for Dy and Yb effectively simulated adsorption across a broad range of conditions in the absence of citrate. Accounting for the effects of citrate on REE adsorption required the addition of up to two ternary REE-citrate-goethite surface complexes. The SCM can enable predictions of REE transport in subsurface environments that have goethite as an important adsorbent mineral. This predictive capability could contribute to identifying potential REE sources and facilitating efficient extraction of REEs.

58 GEOSCIENCES↗

DOE OSTI2022

Co-Based superalloy morphology evolution: A phase field study based on experimental thermodynamic and kinetic data

Cobalt-based superalloys with two phase $\gamma$/$\gamma '$ microstructures offer great promise as candidates for next-generation high-temperature alloys for applications, such as turbine blades. It is essential to understand the thermodynamic and kinetic factors that influence the microstructural evolution of these alloys in order to optimize the alloy compositions and processing steps with a goal to improve their coarsening, creep and rafting behavior. We are using a continuum phase field approach to study the diffusion process and to predict the equilibrium shapes of Co-Al-W $\gamma '$ precipitates. In order to obtain quantitatively predictive capabilities, we extract chemical free energies for the $\gamma$/$\gamma '$ phases based on CALculation of PHAse Diagrams (CALPHAD) thermodynamic data and diffusion mobilities for Co alloys based on CALPHAD kinetic data. We also use experimental or first-principles data for other quantities, such as misfit strain and interface information, for the parameterization of our model. A particular focus of our study is to understand how different energy balances, misfit strain and kinetics affect the coarsening and rafting behavior of $\gamma '$ precipitates, and the sensitivity of the final precipitate shape to materials parameters. Here, we find that the equilibrium shape of the precipitate results from a delicate competition between chemical, interfacial, and elastic energies, and it is very sensitive to changes in model parameters. Here, we examine how modeling input parameters affect the equilibrium shape of precipitates and relate these parameters to experimentally available values.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Design and evaluation of a dilute flow particle-to-air heat exchanger for energy storage applications

The use of inert and redox-active particles for high-temperature energy storage requires the development of components that can efficiently transfer energy to high-pressure working fluids like supercritical carbon dioxide (sCO 2 ). Dilute flow reactors can enable high working fluid outlet temperatures and minimal parasitic losses compared to moving packed bed and fluidized bed reactors. This research uses both computational and experimental methods to explore the design trade-offs and practical challenges of a novel component for transferring energy from dilute flows of hot, reduced metal oxide (MO x ) particles to sCO 2 in tubes. A discretized thermal resistance network model, which accounts for particle hydrodynamics, multi-mode heat transfer, and reaction equilibrium, guides the design of a prototype device. This device is experimentally tested with a surrogate heat transfer fluids and inert particle temperatures up to 400°C and a heat duty exceeding 1 kW. The data are used to validate the thermal hydraulic sub-models, allowing for the simulation of reacting particle scenarios. Under nominal design conditions, the flow rate of reactive particles is predicted to be 30% lower than that of inert particles for the same energy recovered, with over 70% of the stored particle energy transferred to the sCO 2 . Furthermore, these findings can inform the design of more efficient energy recovery reactors for particle-based systems and can be integrated into system-level concentrated solar power models with thermal storage to optimize operating conditions.

14 SOLAR ENERGY↗

DOE OSTI2020

Projected changes in the terrestrial and oceanic regulators of climate variability across sub-Saharan Africa

Future changes in the sign and intensity of ocean–land–atmosphere interactions have been insufficiently studied, despite implications for regional climate change projections, extreme event statistics, and seasonal climate predictability. In response to this deficiency, the present study focuses on projected responses to the enhanced greenhouse effect in: (1) the mean state of the atmosphere and land surface; (2) oceanic and terrestrial drivers of sub-Saharan climate variability; and (3) total seasonal climate predictability of sub-Saharan Africa, a region known for its pronounced land–atmosphere coupling. Analysis focuses on output from 23 Earth System Models in the Coupled Model Intercomparison Project Phase Five for the late twentieth and twenty-first centuries. It is projected that the greatest warming across sub-Saharan Africa will occur over the Sahel, the monsoon season will become more persistent into late summer and autumn, short rains in the Horn of Africa (HOA) will intensify, and leaf area index will increase across the HOA. Stepwise Generalized Equilibrium Feedback Assessment, i.e. a multivariate statistical approach, is applied to the model output over sub-Saharan Africa in order to explore the oceanic and terrestrial drivers of regional climate. The models indicate that the study region’s climate variability is dominated by oceanic drivers, with secondary contributions from soil moisture and very modest impacts from vegetation. Overall, the general model consensus of future projections indicates a concerning diminished seasonal predictability of sub-Saharan African regional climate based on key oceanic and terrestrial predictors and an elevated role of the land surface (associated with soil moisture anomalies) compared to oceanic drivers in regulating regional climate variability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Investigating the collective nature of cavity-modified chemical kinetics under vibrational strong coupling

Abstract In this paper, we develop quantum dynamical methods capable of treating the dynamics of chemically reacting systems in an optical cavity in the vibrationally strong-coupling (VSC) limit at finite temperatures and in the presence of a dissipative solvent in both the few and many molecule limits. In the context of two simple models, we demonstrate how reactivity in the collective VSC regime does not exhibit altered rate behavior in equilibrium but may exhibit resonant cavity modification of reactivity when the system is explicitly out of equilibrium. Our results suggest experimental protocols that may be used to modify reactivity in the collective regime and point to features not included in the models studied, which demand further scrutiny.

Lindoy, Lachlan P.↗

DOE OSTI2025

Spatially Patterned Architectures to Modulate CO 2 Reduction Cascade Catalysis Kinetics

Electrochemical CO 2 reduction using renewable sources of electrical energy holds promise for converting CO 2 into fuels and chemicals. The complex interactions among chemical/electrochemical reactions and mass transport make it difficult to analyze the effect of an individual process on electrode performance based only on experimental methods. Here, we developed a generalized steady-state simulation to describe an electrode surface in which sequential cascade catalysts are patterned in a periodic trench design. If appropriately constructed, this trench geometry is hypothesized to be able to yield a higher net current density for a CO 2 reduction (CO 2 R) cascade reaction. We have used realistic experimental reaction kinetics to investigate the role of trench geometry in mass transport, local microenvironments, and selectivity for a model CO 2 R cascade reaction. The model considers local concentration gradients of bicarbonate species at quasi-equilibrium and catalytic surface reactions based on concentration-dependent Butler–Volmer kinetics. Our results suggest that varying the spatial distribution of active sites plays a significant role in facilitating effective mass transport between active sites, modulating selectivity for the cascade reaction, and enhancing the yield of desirable cascade products. Moreover, we observe that this trench geometry significantly alters the cascade reaction rate by affecting the local pH, which can cause inadvertent depletion of available aqueous CO 2 to limit the CO 2 R cascade kinetics and modest suppression of the hydrogen evolution reaction (HER). The results highlight the trade-offs between mass transport, pH, and reaction kinetics that become apparent only when considering the coupled physics of all processes at the electrode surface. Here, this model can thus serve as a primary tool to build more selective and efficient patterned architectures for the CO 2 R cascade catalysis.

CO2 reduction↗

DOE OSTI2022

Exploring far-from-equilibrium ultrafast polarization control in ferroelectric oxides with excited-state neural network quantum molecular dynamics

Ferroelectric materials exhibit a rich range of complex polar topologies, but their study under far-from-equilibrium optical excitation has been largely unexplored because of the difficulty in modeling the multiple spatiotemporal scales involved quantum-mechanically. To study optical excitation at spatiotemporal scales where these topologies emerge, we have performed multiscale excited-state neural network quantum molecular dynamics simulations that integrate quantum-mechanical description of electronic excitation and billion-atom machine learning molecular dynamics to describe ultrafast polarization control in an archetypal ferroelectric oxide, lead titanate. Far-from-equilibrium quantum simulations reveal a marked photo-induced change in the electronic energy landscape and resulting cross-over from ferroelectric to octahedral tilting topological dynamics within picoseconds. The coupling and frustration of these dynamics, in turn, create topological defects in the form of polar strings. The demonstrated nexus of multiscale quantum simulation and machine learning will boost not only the emerging field of ferroelectric topotronics but also broader optoelectronic applications.

36 MATERIALS SCIENCE↗

DOE OSTI2021

CryoFold: Determining protein structures and data-guided ensembles from cryo-EM density maps

Cryoelectron microscopy requires molecular modeling for refinement of structures. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins. Here, we introduce CryoFold, a pipeline of molecular dynamics simulations that determines ensembles of protein structures by integrating density data of varying sparsity at 3–5 Å resolution with sequence information and coarse-grained topological knowledge of the protein folds. We present six examples, folding proteins between 72 and 2,000 residues, including large membrane and multi-domain systems, and results from two Electron Microscopy Data Bank (EMDB) competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python graphical user interface (GUI).

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Realization of two-dimensional discrete time crystals with anisotropic Heisenberg coupling

A discrete time crystal (DTC) is an out-of-equilibrium phase of matter that spontaneously breaks discrete time-translation symmetry. Previous studies have been limited to a set of models with Ising-like couplings - and mostly only in one dimension - thus precluding our understanding of the existence (or not) of DTCs in models with more realistic interactions. In this work, by combining the latest generation of IBM quantum processors with state-of-the-art tensor network methods, we demonstrate the existence of a DTC in a two-dimensional system governed by anisotropic Heisenberg interactions. We uncover a rich phase diagram encompassing spin-glass, ergodic, and time-crystalline phases, and identify the interplay of initialization, interaction anisotropy, and driving protocols in stabilizing the DTC phase. By extending the study of Floquet matter beyond simplified models, we lay the groundwork for exploring how driven systems bridge the gap between quantum coherence and emergent non-equilibrium thermodynamics.

Phase transitions and critical phenomena↗

DOE OSTI2020

Photochemical reactions on aerosols at West Antarctica: A molecular case-study of nitrate formation among sea salt aerosols

Environmental implications of climate change are complex and exhibit regional variations both within and between the polar regions. The increase of solar UV radiation flux over Antarctica due to stratospheric ozone depletion creates the optimal conditions for photochemical reactions on the snow. Modeling, laboratory, and indirect field studies suggest that snowpack process release gases to the atmosphere that can react on sea salt particles in remote regions such as Antarctica, modifying aerosol composition and physical properties of aerosols. Here, we present evidence of photochemical processing in West Antarctica aerosols using microscopic and chemical speciation of individual atmospheric particles. Individual aerosol particles collected at the Brazilian module Criosfera 1 were analyzed by scanning transmission X-ray microscopy with near edge X-ray absorption fine structure spectroscopy (STXM/NEXAFS) combined with computer controlled scanning electron microscopy (CCSEM) with energy-dispersive X-ray (EDX) microanalysis. The displacement of chlorine relative to sodium was observed over most of the sea salt particles. Particles with a chemical composition consistent with NaCl-NO3 contributed up to 30% of atmospheric particles investigated. Overall, this study provides evidence that the snowpack and particulate nitrate photolysis should be considered in dynamic partition equilibrium in the troposphere. Finally, these findings may assist in reducing modeling uncertainties and present new insights into the aerosol chemical composition in the polar environment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗

DOE OSTI2024

Coupling strongly correlated electron systems to a tunable electronic reservoir

Here, we study the effect of coupling an electronic reservoir to a Hubbard model and to a dimer Hubbard model. This is motivated by recent experiments on the effect of illumination on the insulator-metal transition in a vanadium oxides and photoconductive cadmium sulfide heterostructure. We model the system as an electronic reservoir hybridized to the correlated system. We assume that the light intensity controls the hybridization coupling strength. We find that the light intensity acts similarly as the temperature in the weak interaction regime. This is consistent with the role played by electronic reservoirs in out-of-equilibrium systems. In contrast, qualitative differences appear at strong coupling. We show that modeling the V 2 ⁢O 3 compound with a Hubbard model, our results describe qualitatively well the observed illumination-driven suppression of the insulator-metal transition. In contrast, in the DHM results fail to capture the mild suppression observed in the case of VO 2 . This indicates that the lattice may play an important role in this case.

Materials Science↗

DOE OSTI2021

Approximating Nash Equilibrium in Day-ahead Electricity Market Bidding with Multi-agent Deep Reinforcement Learning

In this paper, a day-ahead electricity market bidding problem with multiple strategic generation company (GEN-CO) bidders is studied. The problem is formulated as a Markov game model, where GENCO bidders interact with each other todevelop their optimal day-ahead bidding strategies. Considering unobservable information in the problem, a model-free and data-driven approach, known as multi-agent deep deterministic policy gradient (MADDPG), is applied for approximating the Nash equilibrium (NE) in the above Markov game. The MADDPG algorithm has the advantage of generalization due to the automatic feature extraction ability of the deep neural networks. The algorithm is tested on an IEEE 30-bus system with three competitive GENCO bidders in both an uncongested caseand a congested case. Comparisons with a truthful bidding strategy and state-of-the-art deep reinforcement learning methods including deep Q network and deep deterministic policy gradient (DDPG) demonstrate that the applied MADDPG algorithm can find a superior bidding strategy for all the market participants with increased profit gains. In addition, the comparison with a conventional model-based method shows that the MADDPG algorithm has higher computational efficiency, which is feasible for real-world applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Sterile neutrino dark matter in left-right theories

SU(2) L × SU(2) R gauge symmetry requires three right-handed neutrinos (N i ), one of which, N 1 , can be sufficiently stable to be dark matter. In the early universe, W R exchange with the Standard Model thermal bath keeps the right-handed neutrinos in thermal equilibrium at high temperatures. N 1 can make up all of dark matter if they freeze-out while relativistic and are mildly diluted by subsequent decays of a long-lived and heavier right-handed neutrino, N 2 . We systematically study this parameter space, constraining the symmetry breaking scale of SU(2) R and the mass of N 1 to a triangle in the (v R , M 1 ) plane, with v R = (10 6 - 3 × 10 12 ) GeV and M 1 = (2 keV–1 MeV). Much of this triangle can be probed by signals of warm dark matter, especially if leptogenesis from N 2 decay yields the observed baryon asymmetry. The minimal value of v R is increased to 10 8 GeV for doublet breaking of SU(2) R , and further to 10 9 GeV if leptogenesis occurs via N 2 decay, while the upper bound on M 1 is reduced to 100 keV. In addition, there is a component of hot N 1 dark matter resulting from the late decay of N 2 → N 1 ℓ+ℓ- that can be probed by future cosmic microwave background observations. Interestingly, the range of v R allows both precision gauge coupling unification and the Higgs Parity understanding of the vanishing of the Standard Model Higgs quartic at scale vR. Finally, we study freeze-in production of N 1 dark matter via the WR interaction, which allows a much wider range of (v R , M 1 ).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗