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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Kinetics of solid–liquid interface motion in molecular dynamics and phase-field models: crystallization of chromium and silicon

The results of molecular dynamics (MD) simulations of the crystallization process in one-component materials and solid solution alloys reveal a complex temperature dependence of the velocity of the crystal–liquid interface featuring an increase up to a maximum at 10–30% undercooling below the equilibrium melting temperature followed by a gradual decrease of the velocity at deeper levels of undercooling. At the qualitative level, such non-monotonous behaviour of the crystallization front velocity is consistent with the diffusion-controlled crystallization process described by the Wilson–Frenkel model, where the almost linear increase of the interface velocity in the vicinity of melting temperature is defined by the growth of the thermodynamic driving force for the phase transformation, while the decrease in atomic mobility with further increase of the undercooling drives the velocity through the maximum and into a gradual decrease at lower temperatures. At the quantitative level, however, the diffusional model fails to describe the results of MD simulations in the whole range of temperatures with a single set of parameters for some of the model materials. The limited ability of the existing theoretical models to adequately describe the MD results is illustrated in the present work for two materials, chromium and silicon. It is also demonstrated that the MD results can be well described by the solution following from the hodograph equation, previously found from the kinetic phase-field model (kinetic PFM) in the sharp interface limit. The ability of the hodograph equation to describe the predictions of MD simulation in the whole range of temperatures is related to the introduction of slow (phase field) and fast (gradient flow) variables into the original kinetic PFM from which the hodograph equation is obtained. The slow phase-field variable is responsible for the description of data at small undercoolings and the fast gradient flow variable accounts for local non-equilibrium effects at high undercoolings. The introduction of these two types of variables makes the solution of the hodograph equation sufficiently flexible for a reliable description of all nonlinearities of the kinetic curves predicted in MD simulations of Cr and Si. This article is part of the theme issue ‘Transport phenomena in complex systems (part 1)’.

Science & Technology - Other Topics↗
DOE OSTI2025

Thermo-hydraulic steam pipe models for district heating simulations: Simplifications to balance accuracy and simulation speed

Steam piping networks are essential for optimizing performance in industrial processes and district heating systems. However, dynamic models that balance thermo-hydraulic accuracy with computational efficiency remain limited. In response, this paper presents a new discretized steam pipe model based on the plug flow approach, capturing key thermo-hydraulic behaviors while simplifying steam phase change processes. Implemented in Modelica, the model accurately calculates temperature and pressure distributions along steam pipelines. To improve computational efficiency for district-scale simulations, five model simplifications are introduced: lumped thermo-hydraulic functions, empirical correlations, fluid state approximations, steady-state dynamics and inclusion of flow derivatives. These simplified models achieve 85%-98% accuracy in predicting pressure drop and condensation losses, including dynamic condensate behavior during pipe warm-up—a factor often overlooked in existing models. The models support diverse network configurations, scaling effectively to systems with multiple distribution pipes and connected building loads. Discrete models provide detailed insights but exhibit a cubic increase in simulation time as the network scales by N connected building O(N 2.42 ). In contrast, lumped models simulate 10–28 times faster than discrete, offering quadratic scaling of simulation time O(N 1.73 ). However, they still require 6 times more computation time than a lossless network, highlighting the inherent computational challenges of modeling compressible fluid flow. In conclusion, the steady-state lumped variant, with its near-linear scalability in computational time O(N 1.01 ), emerges as an efficient solution for preliminary design evaluations and extensive parametric studies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Extended isogeometric analysis of multi-material and multi-physics problems using hierarchical B-splines

Here, this paper presents an immersed, isogeometric finite element framework to predict the response of multi-material, multi-physics problems with complex geometries using locally refined discretizations. To circumvent the need to generate conformal meshes, this work uses an extended finite element method (XFEM) to discretize the governing equations on non-conforming, embedding meshes. A flexible approach to create truncated hierarchical B-splines discretizations is presented. This approach enables the refinement of each state variable field individually to meet field-specific accuracy requirements. To obtain an immersed geometry representation that is consistent across all hierarchically refined B-spline discretizations, the geometry is immersed into a single mesh, the XFEM background mesh, which is constructed from the union of all hierarchical B-spline meshes. An extraction operator is introduced to represent the truncated hierarchical B-spline bases in terms of Lagrange shape functions on the XFEM background mesh without loss of accuracy. The truncated hierarchical B-spline bases are enriched using a generalized Heaviside enrichment strategy to accommodate small geometric features and multi-material problems. The governing equations are augmented by a formulation of the face-oriented ghost stabilization enhanced for locally refined B-spline bases. We present examples for two- and three-dimensional linear elastic and thermo-elastic problems. The numerical results validate the accuracy of our framework. The results also demonstrate the applicability of the proposed framework to large, geometrically complex problems.

42 ENGINEERING↗
DOE OSTI2023

Effect of coherent edge-localized mode on transition to high-performance hybrid scenarios in KSTAR

This paper deals with one of the origins and trigger mechanisms responsible for the observed performance enhancements in the hybrid scenario experiments conducted in Korea Superconducting Tokamak Advanced Research (KSTAR). The major contribution to the performance improvement comes from a broader and higher pedestal formation. The increase of fast ion pressure due to a plasma density decrease also contributes substantially to the global beta. Although the reduced core plasma volume resulting from the pedestal expansion has a negative effect on the core thermal energy, a considerable confinement improvement observed in the inner core region limits the degradation. The one significant characteristic of high-performance discharges is the presence of Coherent Edge-localized Mode (CEM) activity. CEM is triggered during the pedestal recovery phase between typical ELM crashes and has been found to be related to the increase of particle and heat transport. It appears to underlie two commonly observed phenomena in high-performance hybrid scenario discharges in KSTAR; pedestal broadening and continuous density decrease. Despite the associated transport increase, CEM activities can induce performance enhancement. With the pedestal broadening, ELM crashes become delayed and weakened, which, in turn, allows for a higher pedestal. Moreover, the density decrease directly increases fast ion pressure by extending the beam-slowing-down time. The linear gyrokinetic analysis reveals that the increase of fast ions could initiate positive feedback loops, leading to the stabilization of Ion Temperature Gradient mode in the inner core region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Insights into the hydro-mechanical behavior of a decimeter-scale fracture using the mini-SIMFIP probe

ABSTRACT: Understanding hydro-mechanical couplings in fractured rocks is essential for predicting the rock mass response during high-pressure fluid injection, including the stimulation of enhanced geothermal systems. However, fluid-driven fracture dislocations are challenging to measure due to the need for local displacement data at high fluid pressures. In this study, fluid-driven displacement across a decimeter-scale laboratory fracture was investigated using the mini-SIMFIP (step rate injection method for fracture in-situ properties) probe, which is a smaller version of the SIMFIP tool (Guglielmi et al., 2014). The mini-SIMFIP probe is able to resolve the full 3D displacement vector of a fracture. The probe was installed in one of two boreholes across a decimeter-scale saw-cut granite fracture. Two pressure step injection tests were conducted under the same isotropic stress conditions. By varying injection between the boreholes, we estimated the aperture profile across the fracture. The results show a consistent pressure-dependent opening as long as steady-state flow was maintained. At a certain pressure step, steady-state conditions were no longer achievable and the fracture opened rapidly. The pressure-opening relationship diverged between the two tests and indicated a homogenization of the aperture profile and an increase in the non-linearity of the flow regime.

Osten, J↗
DOE OSTI2022

Entropic order parameters in weakly coupled gauge theories

The entropic order parameters measure in a universal geometric way the statistics of non-local operators responsible for generalized symmetries. In this article, we compute entropic order parameters in weakly coupled gauge theories. To perform this computation, the natural route of evaluating expectation values of physical (smeared) non-local operators is prevented by known difficulties in constructing suitable smeared Wilson loops. We circumvent this problem by studying the smeared non-local class operators in the enlarged non-gauge invariant Hilbert space. This provides a generic approach for smeared operators in gauge theories and explicit formulas at weak coupling. In this approach, the Wilson and ’t Hooft loops are labeled by the full weight and co-weight lattices respectively. We study generic Lie groups and discuss couplings with matter fields. Smeared magnetic operators, as opposed to the usual infinitely thin ones, have expectation values that approach one at weak coupling. The corresponding entropic order parameter saturates to its maximum topological value, except for an exponentially small correction, which we compute. On the other hand, smeared ’t Hooft loops and their entropic disorder parameter are exponentially small. We verify that both behaviors match the certainty relation for the relative entropies. In particular, we find upper and lower bounds (that differ by a factor of 2) for the exact coefficient of the linear perimeter law for thin loops at weak coupling. This coefficient is unphysical/non-universal for line operators. We end with some comments regarding the RG flows of entropic parameters through perturbative beta functions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Incorporating the Impacts of Climate Change on Hydrology in a Performance Assessment Model - 20403

The evidence of climate change is increasingly well-documented and impacts should be incorporated in performance assessment studies. The current climate literature provides both observational evidence and climate model projections of climate trends and/or climate change in the late 20. and early 21. centuries for North America and the northeast United States. Probabilistic modeling is a core requirement for quantifying uncertainty and evaluating its impacts. Not evaluating future climate states in a performance assessment because of the existence of uncertainty is contradictory to good modeling practices - the most uncertain issues and parameters require the most attention in effective probabilistic modeling. Excluding climate change limits development of modeling information that could aid in effective decision making. In this work we develop methods to use the output from hydrologic models and analysis of historical aerial imagery to quantify and implement the impacts of climate change on hydrologic processes at a nuclear waste site in West Valley, New York. Specifically, we used the HELP (Hydraulic Performance of Landfill Performance) model to characterize key hydrologic processes under both current and future climate conditions to assess the impacts of changing climate on hydrology. A suite of previous climatic models were reviewed and synthesized to produce a cohesive representation of the current state of knowledge of the impact of climate change on important model inputs such as precipitation. Output from the HELP simulations was coupled to the GoldSim model that was used to develop the Probabilistic Performance Assessment (PPA) approach through the application of a novel 'nearest neighbor' technique. First, several thousand realizations were generated from the HELP model using a Latin Hypercube experimental design to ensure adequate coverage of the parameter space of explanatory variables used to drive HELP. For example, porosity is a physical parameter that is used as an input to both HELP and the GoldSim PA model. We then ran sensitivity analysis (SA) algorithms on the output of HELP for each of the responses of interest. For each predictor, each time we build an SA model we get a different value for the sensitivity index (SI). From the collection of all the SA models, the average was computed among all of the SIs to represent the predictor within the context of the nearest neighbor approach. That is, we conduct SA on each HELP outcome for each scenario. This gives us parameter sensitivity indices for the outcomes. We average the parameter sensitivity indices across the outcomes to get the average SI for a scenario. For each realization that is generated from the Goldsim PA model, Goldsim generates random values for physical/empirical parameters that HELP uses as well. For each vector of physical/empirical parameters that Goldsim generates, the vector from the 5,000 HELP runs that is most 'similar' to the Goldsim vector is computed using the nearest neighbor approach. In this context 'similar' means minimization of the SA-weighted sum of the absolute differences among the 5,000 values computed for this statistic, where each value corresponds to a different HELP realization. In order to account for the impacts of climate change, this process was repeated using the spatially downscaled future climate projections. For each of the key parameters of interest, it was assumed that a linear change depicted the relationship between the values for the present day and those for 2100. In this way, the climatically-driven changes in key parameters used to inform the GoldSim model are quantified and incorporated into the PA model output for the future. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Crystal structure of a far-red–sensing cyanobacteriochrome reveals an atypical bilin conformation and spectral tuning mechanism

Significance Phytochromes are well-known far-red-light sensors found in plants that trigger adaptive responses to facilitate competition for light capture with neighboring plants. Red- and far-red sensing are also critical for cyanobacteria living in the far-red–enriched shade of plants. This work reports the crystal structure of a far-red–sensing cyanobacteriochrome, a distant cyanobacterial relative of phytochrome. These studies shed insights into the molecular basis of far-red-sensing by phycobilin-based photoreceptors. Owing to the deep tissue penetration of far-red light, far-red–sensing cyanobacteriochromes are promising protein scaffolds for developing genetically encoded photoswitches, optoacoustic contrast agents, and fluorescent probes for in situ imaging and optogenetic applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Type-II Weyl nodes, flat bands, and evidence for a topological Hall-effect in the new ferromagnet FeCr 3 Te 6

The interplay between linearly dispersing, or Dirac-like, and flat electronic bands, for instance, in the kagome ferromagnets, has attracted attention due to a possible interplay between topology and electronic correlations. Here, we report the synthesis, structural, electrical, and magnetic properties of a single-crystalline ferromagnetic compound, namely Fe 1/3 ⁢CrTe 2 or FeCr 3 ⁢Te 6 , which crystallizes in the 𝑃$\overline{3}$⁢𝑚⁢1 space group instead of the 𝐼⁢2/𝑚 previously reported for FeCr 2 ⁢Te 4 . Electronic band structure calculations reveal type-II Dirac nodes and relatively flat bands near the Fermi level (ε 𝐹 ). This compound shows onset Curie temperature 𝑇 c ≃ 120K, followed by an additional ferromagnetic transition near 𝑇 c2 ∼ 92.5K. Below 𝑇 c , FeCr 3 ⁢Te 6 displays a pronounced anomalous Hall effect, as well as sizable coercive fields that exceed 𝜇 0 ⁢𝐻=1 T at low 𝑇⁢s. However, a scaling analysis indicates that the anomalous Hall effect results from a significant intrinsic contribution, as expected from the calculations, and also from the extrinsic mechanism, i.e., scattering. The extrinsic contribution probably results from occupational disorder at the 1b Fe-site within the van der Waals gap of the CrTe 2 host. We also observe evidence for a topological Hall component superimposed onto the overall Hall response, suggesting the presence of chiral spin textures akin to skyrmions in this centrosymmetric system. Their possible presence will require experimental confirmation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Physics–Informed Neural Networks of the Saint–Venant Equations for Downscaling a Large–Scale River Model

Large-scale river models are being refined over coastal regions to improve the scientific understanding of coastal processes, hazards and responses to climate change. However, coarse mesh resolutions and approximations in physical representations of tidal rivers limit the performance of such models at resolving the complex flow dynamics near the river-ocean interface, resulting in inaccurate simulations of flood inundation. In this research, we propose a machine learning (ML) framework based on the state-of-the-art physics-informed neural network (PINN) to simulate the downscaled flow at the subgrid scale. First, we demonstrate that PINN is able to assimilate observations of various types and solve the one-dimensional (1-D) Saint-Venant equations (SVE) directly. We perform the flow simulations over a floodplain and along an open channel in several synthetic case studies. The PINN performance is evaluated against analytical solutions and numerical models. Our results indicate that the PINN solutions of water depth have satisfactory accuracy with limited observations assimilated. In the case of flood wave propagation induced by storm surge and tide, a new neural network architecture is proposed based on Fourier feature embeddings that seamlessly encodes the periodic tidal boundary condition in the PINN's formulation. Furthermore, we show that the PINN-based downscaling can produce more reasonable subgrid solutions of the along-channel water depth by assimilating observational data. The PINN solution outperforms the simple linear interpolation in resolving the topography and dynamic flow regimes at the subgrid scale. This study provides a promising path towards improving emulation capabilities in large-scale models to characterize fine-scale coastal processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Injection data analysis using material balance time for CO 2 storage capacity estimation in deep closed saline aquifers

Estimating the ultimate storage capacity of deep saline aquifers is important to address the formation potential to store the envisioned large volumes of CO 2 . Injection data (i.e. injection rate, bottomhole pressure, and cumulative injected volume of CO 2 ) are routinely recorded during storage operations. These data contain valuable information on the subsurface (e.g. the reservoir pore volume and the formation storage capacity) that can be extracted. In this paper, we present a two-step graphical technique to infer the pore volume and the ultimate storage capacity of closed saline aquifers by analyzing the available injection data. First, the pore volume is inferred through adapting the concept of the material balance time. Material balance time is an approximate superposition time function developed to interpret production data from oil and gas wells operating at variable pressure/rate conditions during the boundary-dominated flow period. Using material balance techniques, the ultimate storage capacity is then estimated through linear extrapolation of the average pressure trend to the maximum allowable pressure the formation can withstand. The average pressure is not available in practice, but is can be obtained from the injection data. Two approaches are presented in this study to calculate the average pressure; namely the rigorous and the approximate approaches. Unlike the rigorous approach, the approximate approach does not require a prior knowledge of some reservoir properties (e.g. relative permeability, absolute permeability, formation porosity and thickness) to calculate the average pressure. To investigate its potential and reliability in analyzing CO 2 injection data, the proposed technique is applied to four synthetic cases representing different well operating conditions. Results indicate that the approximate approach consistently overestimates the actual (simulated) storage capacity as compared to the rigorous approach. The agreement - between the inferred and the simulated reservoir pore volume, and between the analytical and numerical estimates of storage capacity - validates the potential application of the technique to CO 2 storage in closed saline aquifers. The technique is further substantiated through application to a field data set utilized from a commercial-scale geological storage (CGS) project. Finally, field data interpretation shows that the proposed technique can be utilized to identify the degree of hydraulic continuity and reservoir compartmentalization within a target formation by interpreting the corresponding pressure and rate responses.

02 PETROLEUM↗
DOE OSTI2021

Synthesis, structure, linear and nonlinear optical properties of noncentrosymmetric quaternary diamond-like semiconductors, Cu 2 ZnGeSe 4 (CZGSe) and the novel Cu 4 ZnGe 2 Se 7

In this work, two quaternary diamond-like semiconductors (DLSs) in the Cu-Zn-Ge-Se system, the known Cu 2 ZnGeSe 4 (also referred to as CZGSe) and the new Cu 4 ZnGe 2 Se 7 , are compared in terms of their crystal structures, electronic structures and physicochemical properties. Both compounds were prepared by high-temperature, solid-state synthesis at 800 degrees C. Single crystal X-ray diffraction was used to determine the structure of Cu 4 ZnGe 2 Se 7 . The structures of both Cu 2 ZnGeSe 4 and Cu 4 ZnGe 2 Se 7 can be considered as derivatives of cubic diamond. Cu 4 ZnGe 2 Se 7 , with a reduced symmetry due to the cation ordering pattern, adopts the Cu 4 NiSi 2 S 7 structure type, with space group C2. The corner-sharing tetrahedra in Cu 4 ZnGe 2 Se 7 are slightly distorted because the charge for some of the S 2 - anions is not compensated by the first-nearest-neighbor cations. Rietveld refinements using synchrotron X-ray powder diffraction data were used to assess the phase purity of the samples and confirm the bulk structural behavior. Diffuse reflectance UV/Vis/NIR spectroscopy shows that Cu 2 ZnGeSe 4 and Cu 4 ZnGe 2 Se 7 have direct optical bandgaps of 1.38 and 0.91 eV, respectively. Electronic structure calculations implementing density functional theory confirm the direct bandgap for Cu 4 ZnGe 2 Se 7 , with a calculated value of 0.62 eV. Both compounds are air stable, thermally stable up to relatively high temperatures, undergo phase transitions and have wide windows of optical clarity. The Kurtz-Perry powder technique was used to determine the second harmonic generation (SHG) responses using a commercial AgGaSe 2 standard. While Cu 4 ZnGe 2 Se 7 displays a weak SHG response, Cu 2 ZnGeSe 4 exhibits a response that is greater than several benchmark materials, with a large SHG coefficient, χ (2) , of 43 ± 6 pm/V at λ = 2900 nm.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Event-Based Energy Impact Tracking and Forecasting with Limited Measurements for Rooftop Units

Packaged air conditioning units and heat pumps, also known as rooftop units (RTUs), are responsible for almost 133 billion kWh of electricity usage annually on site for space cooling U.S. commercial buildings. In addition, the use of heat pumps is a trend we expect to accelerate as buildings transition from fossil fuel-based heating to electricity as a key step for decarbonizing the U.S. commercial buildings sector. However, the operation conditions and energy use of RTUs and heat pumps are usually not well monitored as they are not commonly integrated with building automation systems and lack exposed sensing and control points. To fill this gap, this paper proposes a framework for tracking and forecasting energy impacts resulting from degradation of performance and improved performance for unit servicing using limited data. The proposed framework makes use of a constrained dataset, specifically measurements of the outdoor air temperature and the power demand of individual RTUs, to track and forecast changes in energy use associated with changes in performance over various temporal horizons ranging from days to weeks. Following the detection of an RTU fault, performance degradation, or performance improvement, the framework employs a prediction model to assess the cumulative energy impact. We demonstrate the effectiveness of the method with field-collected data for servicing and degradation examples and compare the predicting accuracy of Gradient Boosting Decision Tree (GBDT) Regression models to Support Vector Regression and Linear Regression models. The results show that GBDT achieved the best accuracy for time-series validation datasets for the servicing and degradation cases, and the prediction model was able to track the cumulative energy impacts of events. The proposed framework can inform building owners of the cumulative change in energy usage of RTUs associated with performance degradation, performance improvement, or a fault.

packaged air conditioners, packaged heat pumps, ro↗
DOE OSTI2025

National serosurvey and risk mapping reveal widespread distribution of Coxiella burnetii in Kenya

Coxiella burnetii, the causative agent of Q fever, is an emerging pathogen that has the potential to cause severe chronic infections in animals and humans worldwide. The detrimental impact on public health is projected to be higher in the low- and middle-income countries given their lower capacity to sustain effective surveillance and response measures. We implemented a national serosurvey of cattle in Kenya to map the spatial distribution of the pathogen. The study used serum samples that were collected from randomly selected cattle in different ago-ecological zones across the country. These samples were screened for the pathogen using PrioCHECK Ruminant Q Fever AB Plate ELISA kit. The laboratory findings were analyzed using INLA package to identify risk factors for C. burnetii exposure from herd- and animal-level factors, area, and bioclimatic datasets accessed from online databases. A total of 6,593 cattle were recruited for the study; of these, 7.9% (95% CI; 7.2–8.5) were seropositive. Outputs from the multivariable analysis revealed that the animal age and some of the geographical variables including wind speed, area under shrubs and “petric calcisols” type of soil were significantly associated with C. burnetii seropositivity. Being a calf, weaner or subadult was associated with lower odds of exposure compared to being an adult by 0.24 (credibility interval: 2.5% and 97.5%), 0.41 (0.30–0.55) and 0.51 (0.38–0.69), respectively. In addition, a unit increase in the wind speed increased the odds of C. burnetii seropositivity by 1.27 (1.05–1.52) while an increase on the land area under shrubs was associated with lower odds of exposure (0.67 [0.47–0.69]). The effect of petric calcisols was non-linear; an increase of the land area with this soil type was associated with an exponential increase in C. burnetii seropositivity. This study provides new data on C. burnetii seroprevalence, information of its risk factors and a prevalence map that can be used for C. burnetii risk surveillance and control. The identification of environmental risk factors for C. burnetii exposure, and the increasing awareness of the zoonotic potential of the pathogen, calls for the need to enhance the existing collaborations for the surveillance and control of C. burnetii in line with the One Health framework. The evidence generated on the potential role of environmental factors can also be used to design nature-based interventions, such as replacement of vegetation in denuded areas, to reduce potential for the aerosolization of the pathogen. Livestock vaccination in the hotspots would also reduce animal infections and hence the contamination of the environment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Beam results for the new super-conducting booster at Jefferson Lab

The performance results of a new super-conducting booster for the CEBAF injector at Jefferson Lab, could be of interest for other similar electron injectors. A recent addition of this new booster has provided us the ability to achieve a more adiabatic acceleration and therefore an improvement to the beam dynamics and beam brightness. It has also simplified the design and operation of the section of the injector responsible for accelerating the electron beam from a few hundred keV to several MeV (typically 6.7 MeV). The addition of the new booster was part of an upgrade to the CEBAF injector to improve the beam quality for future physics experiments with high sensitivity to beam quality. The booster consists of two cavities: a 2-cell cavity followed by a 7-cell cavity. This combination allows for a wide range of input electron beam energies, from 130 keV to more than 300 keV. In fact, during the last year, the booster was successfully operated with 140,180, and 200 keV input beam energies as the electron gun was being upgraded. This paper describes the new booster, presents beam optics data results from different beam studies, commissioning, and the physics quality beam operation.

Accelerator Physics↗
DOE OSTI2024

Importance of Site Diversity and Connectivity in Electrochemical CO Reduction on Cu

Electrochemical CO 2 reduction on Cu is a promising approach to produce value-added chemicals using renewable feedstocks, yet various Cu preparations have led to differences in activity and selectivity toward single and multicarbon products. Here, we find, surprisingly, that the effective catalytic activity toward ethylene improves when there is a larger fraction of less active sites acting as reservoirs of *CO on the surface of Cu nanoparticle electrocatalysts. In an adaptation of chemical transient kinetics to electrocatalysis, we measure the dynamic response of a gas diffusion electrode (GDE) cell when the feed gas is abruptly switched between Ar (inert) and CO. When switching from Ar to CO, CO reduction (COR) begins promptly, but when switching from CO to Ar, COR can be maintained for several seconds (delay time) despite the absence of the CO reactant in the gas phase. A three-site microkinetic model captures the observed dynamic behavior and shows that Cu catalysts exhibiting delay times have a less active *CO reservoir that exhibits fast diffusion to active sites. The observed delay times and the estimated *CO reservoir sizes are affected by catalyst preparation, applied potential, and microenvironment (electrolyte cation identity, electrolyte pH, and CO partial pressure). Notably, we estimate that the *CO reservoir surface coverage can be as high as 88 ± 7% on oxide-derived Cu (OD-Cu) at high overpotentials (–1.52 V vs SHE) and this increases in reservoir coverage coincide with increased turnover frequencies to ethylene. We also estimate that *CO can travel substantial distances (up to 10s of nm) prior to desorption or reaction. It appears that active C–C coupling sites by themselves do not control selectivity to C 2+ products in electrochemical COR; the supply of CO to those sites is also a crucial factor. More generally, the overall activity of Cu electrocatalysts cannot be approximated from linear combinations of individual site activities. Future designs must consider the diversity of the catalyst network and account for intersite transportation pathways.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Constitutive Model Development for Aging Polymer Encapsulants (ASC P&EM FY2021 L2 Milestone 7836)

This SAND report fulfills the completion requirements for the ASC Physics and Engineering Modeling Level 2 Milestone 7836 during Fiscal Year 2021. The Sandia Simplified potential energy clock (SPEC) non-linear viscoelastic constitutive model was developed to predict a whole host of polymer glass physical behaviors in order to provide a tool to assess the effects of stress on these materials over their lifecycle. Polymer glasses are used extensively in applications such as electronics packaging, where encapsulants and adhesives can be critical to device performance. In this work, the focus is on assessing the performance of the model in predicting material evolution associated with long-term physical aging, an area that the model has not been fully vetted in. These predictions are key to utilizing models to help demonstrate electronics packaging component reliability over decades long service lives, a task that is very costly and time consuming to execute experimentally. The initiating hypothesis for the work was that a model calibration process can be defined that enables confidence in physical aging predictions under ND relevant environments and timescales without sacrificing other predictive capabilities. To test the hypothesis, an extensive suite of calibration and aging data was assembled from a combination of prior work and collaborating projects (Aging and Lifetimes as well as the DoD Joint Munitions Program) for two mission relevant epoxy encapsulants, 828DGEBA/DEA and 828DGEBA/T403. Multiple model calibration processes were developed and evaluated against the entire set of data for each material. A qualitative assessment of each calibration's ability to predict the wide range of aging responses was key to ranking the calibrations against each other. During this evaluation, predictions that were identified as non-physical, i.e., demonstrated something that was qualitatively different than known material behavior, were heavily weighted against the calibration performance. Thus, unphysical predictions for one aspect of aging response could generate a lower overall rating for a calibration process even if that process generated better quantitative predictions for another aspect of aging response. This insurance that all predictions are qualitatively correct is important to the overall aim of utilizing the model to predict residual stress evolution, which will depend on the interplay amongst the different material aging responses. The DSC-focused calibration procedure generated the best all-around aging predictions for both materials, demonstrating material models that can qualitatively predict the whole host of different physical aging responses that have been measured. This step forward in predictive capability comes from an unanticipated source, utilization of calorimetry measurements to specify model parameters. The DSC-focused calibration technique performed better than compression-focused techniques that more heavily weigh measurements more closely related to the structural responses to be predicted. Indeed, the DSC-focused calibration procedure was only possible due to recent incorporation of the enthalpy and heat capacity features into SPEC that was newly verified during this L2 milestone. Fundamentally similar aspects of the two material model calibrations as well as parametric studies to assess sensitives of the aging predictions are discussed within the report. A perspective on the next steps to the overall goal of residual stress evolution predictions under stockpile conditions closes the report.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Physics-based compact modeling of electro-thermal memristors: Negative differential resistance, local activity, and non-local dynamical bifurcations

Leon Chua's Local Activity theory quantitatively relates the compact model of an isolated nonlinear circuit element, such as a memristor, to its potential for desired dynamical behaviors when externally coupled to passive elements in a circuit. However, the theory's use has often been limited to potentially unphysical toy models and analyses of small-signal linear circuits containing pseudo-elements (resistors, capacitors, and inductors), which provide little insight into required physical, material, and device properties. Furthermore, the Local Activity concept relies on a local analysis and must be complemented by examining dynamical behavior far away from the steady-states of a circuit. In this work, we review and study a class of generic and extended one-dimensional electro-thermal memristors (i.e., temperature is the sole state variable), re-framing the analysis in terms of physically motivated definitions and visualizations to derive intuitive compact models and simulate their dynamical behavior in terms of experimentally measurable properties, such as electrical and thermal conductance and capacitance and their derivatives with respect to voltage and temperature. Within this unified framework, we connect steady-state phenomena, such as negative differential resistance, and dynamical behaviors, such as instability, oscillations, and bifurcations, through a set of dimensionless nonlinearity parameters. In particular, we reveal that the reactance associated with electro-thermal memristors is the result of a phase shift between oscillating current and voltage induced by the dynamical delay and coupling between the electrical and thermal variables. We thus, demonstrate both the utility and limitations of local analyses to understand non-local dynamical behavior. Critically for future experimentation, the analyses show that external coupling of a memristor to impedances within modern sourcing and measurement instruments can dominate the response of the total circuit, making it impossible to characterize the response of an uncoupled circuit element for which a compact model is desired. However, these effects can be minimized by proper understanding of the Local Activity theory to design and utilize purpose-built instruments.

Brown, Timothy D. (ORCID:0000000347068355)↗