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DOE OSTI2024

Morphological Modulation of TiO 2 Nanotube via Optimal Anodization Condition for Solar Water Oxidation

With the depletion of fossil fuels and the rising global demand for energy, photoelectrochemical (PEC) water splitting presents a promising solution to avert an energy crisis. Titanium dioxide (TiO 2 ), an n -type semiconductor, has gained popularity as a photoanode due to its remarkable PEC properties. Nevertheless, inherent challenges such as a wide band gap (~3.2 eV), charge recombination, and slow oxygen evolution reaction (OER) rates at the surface limit its practical application by constraining light absorption. To overcome these limitations, we have developed TiO 2 nanotubes (NTs) using a facile anodization method. This study examines the impact of anodization growth parameters on solar water oxidation performance. Specifically, TiO 2 NTs with modified anodization time (referred to as TiO 2 -6) showed a 3.5-fold increase in photocurrent density compared to the as-grown TiO 2 NTs. Furthermore, electrochemical analyses, such as electrochemical impedance spectroscopy (EIS), indicated a significant decrease in charge transfer resistance following the adjustment of on-off anodization time. Additionally, the TiO 2 -6 photoanode demonstrated a higher electrochemically active surface area (ECSA) than other samples. Therefore, optimal nanostructuring parameters are crucial for enhancing the PEC properties of TiO 2 NTs. Overall, our findings offer valuable insights for fabricating high-quality TiO 2 NTs photoanodes, contributing to developing efficient PEC systems for sustainable energy production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A numerical study of process complexity in permafrost dominated regions

Numerical modeling of permafrost dynamics requires adequate representation of atmospheric and surface processes, a reasonable parameter estimation strategy, and site-specific model development. The three main research objectives of the study are: (i) to propose a novel methodology that determines the required level of surface process complexity of permafrost models by conducting parameter sensitivity and calibration, (ii) to design and compare three numerical models of increasing surface process complexity, and (iii) to calibrate and validate the numerical models at the Yakou catchment on the Qinghai-Tibet Plateau as an exemplary study site. The calibration was carried out by coupling the Advanced Terrestrial Simulator (numerical model) and PEST (calibration tool). Simulation results showed that (i) A simple numerical model that considers only subsurface processes can simulate active layer development with the same accuracy as other more complex models that include surface processes. (ii) Peat and mineral soil layer permeability, Van Genuchten alpha, and porosity are highly sensitive. (iii) Liquid precipitation aids in increasing the rate of permafrost degradation. (iv) Deposition of snow insulated the subsurface during the thaw initiation period. We have developed and released an integrated code that couples the numerical software ATS to the calibration software PEST. The numerical model can be further used to determine the impacts of climate change on permafrost degradation.

Calibration↗

DOE OSTI2024

A Self Consistent 2D Simulation of Coherent Synchrotron Radiation Effects on Beam Dynamics

An increasing interest in high quality and high current electron beams necessitates a thorough understanding and prediction of coherent synchrotron radiation effects. The self-interaction of charged particles in a beam undergoing synchrotron motion is a physically significant process that is all too often computationally intensive with very little analytical results to rely on for the general case. The coherent spectrum of this interaction is of utmost importance to the design of free electron lasers (FELs) and an accurate assessment is imperative for their design. This work presents a novel implementation to the numerical simulation of charged particle beams. The simulation is a self-consistent approach including the self-fields generated by the beam of which coherent synchrotron radiation effects are of primary interest. A particle-in-cell model is used where a planar beam sampled by point particles is deposited on an encompassing grid at each timestep. The electromagnetic fields are calculated on the grid using the retarded potentials according to causality. The electromagnetic forces from the fields are interpolated on each particle which in turn advance in time. The simulation is benchmarked against well-established results for coherent synchrotron radiation effects. In addition, studies are provided that show the convergence of simulation results for increasing resolution. A study into the transverse beam size effects on beam dynamics is performed as well as a proof of concept where the simulation is used by a genetic algorithm to optimize the design parameters of a beam lattice. The results of these studies in tandem verify the efficacy of the simulation for its practical use in accelerator design or the study of synchrotron radiation effects

Duffin, Dallan [Old Dominion Univ., Norfolk, VA (U↗

DOE OSTI2025

Optimization of spray breakup model parameters for predicting fuel spray and film characteristics in gasoline direct injection engines

This study investigated the behavior of gasoline direct injection (GDI) sprays using computational fluid dynamics (CFD). The authors developed an approach to identify optimal spray breakup model parameters by evaluating an error function across numerous simulations, with the goal of minimizing discrepancies from experimental data. Using the optimal setup, the simulated spray matched well with projected liquid volume distributions, liquid penetration, and spray width measured in a constant-pressure continuous-flow chamber. To further validate the approach, the same setup was tested across various fuels, injectors, and operating conditions. Subsequently, the optimal setup, along with a recently developed spray-wall interaction model, were applied to a direct-injection spark-ignited engine under late-injection conditions to predict and evaluate fuel film formation and evolution at varying engine coolant temperatures. Here, with the centrally mounted injector directing the spray toward the piston, simulations indicated that the spray tends to impinge on the piston surface. The proposed simulation framework also accurately captured the aggregate film area on the piston surface, aligning with previously published experimental results. Moreover, simulations showed that increasing the coolant temperature from cold start conditions (333 K) to warm conditions (363 K) reduced the fuel mass deposited on the piston by roughly 50%. Furthermore, for the spray-guided engine configuration studied in this work, the CFD model predicted minimal film deposition on the spark plug electrodes regardless of the coolant temperatures due to a relatively weak in-cylinder flow during the compression phase.

Computational fluid dynamics (CFD)↗

DOE OSTI2025

Incorporating geological structure into sensitivity analysis of subsurface contaminant transport

Simulating subsurface contaminant transport at the kilometer-scale often entails modeling reactive flow and transport within and through complex geologic structures. These structures are typically meshed by hand and as a result geologic structure is usually represented by one or a few deterministically generated geological models for uncertainty studies of flow and transport in the subsurface. Uncertainty in geologic structure can have a significant impact on contaminant transport. In this study, the impact of geologic structure on contaminant tracer transport in a shale formation is investigated for a simplified generic deep geologic repository for permanent disposal of spent nuclear fuel. An open-source modeling framework is used to perform a sensitivity analysis study on transport of two tracers from a generic spent nuclear fuel repository with uncertain location of the interfaces between the stratum of the geologic structure. The automated workflow uses sampled realizations of the geological structural model in addition to uncertain flow parameters in a nested sensitivity analysis. Concentration of the tracers at observation points within, in line with, and downstream of the repository are used as the quantities of interest for determining model sensitivity to input parameters and geological realization. Finally, the results of the study indicate that the location of strata interfaces in the geological structure has a first-order impact on tracer transport in the example shale formation, and that this impact may be greater than that of the uncertain flow parameters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles

Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected to a low-dimensional subspace for accelerating convergence of the solution algorithm and consequently reducing the number of transient simulations. The proposed approach was demonstrated via two case studies associated with different VCC applications where 10 parameters were calibrated in each case using laboratory measurements. The reduced-dimension BO framework only required 1 / 8 th of the iterations associated with a standard BO method that deals with high-dimensional calibration parameters for converged solutions and yielded comparable accuracy. Furthermore, both calibrated models revealed significant accuracy improvements compared to uncalibrated models.

Ma, Jiacheng↗

DOE OSTI2024

Simulating Magnetic Reconnection in ‘Two Ribbon’ Type Solar Flares

Magnetic reconnection is an astrophysical process where neighboring magnetic field lines, facing anti-parallel, are reconfigured. This reconfiguration results in built up magnetic energy being explosively released as it is being converted to plasma kinetic and thermal energies. There are various kinds of simulations used to simulation reconnection; our work begins with Athena++, a magnetohydrodynamic (MHD) simulation code typically used for astrophysical problems, and a reconnection specific code file. The resistive MHD equations are solved with Riemann solvers. There was an initial test run without modifying the code to understand the dynamics of the simulation. We expand on the original reconnection problem file by implementing a radiative cooling term specific to the corona. The radiative cooling is theorized to have an effect on solar coronal plasma and magnetic reconnection dynamics. The cooling term will be tested with various parameters and compared to the case without cooling to study these dynamics. The condensation found in only the with cooling case emphasizes the importance of implementing this feature and will be later tested with a thermal conduction term. We want to determine the parameter regime where non-equilibrium cooling will be important for the reconnection dynamics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Dependence of divertor turbulence on plasma density and current in TCV

To reliably predict the distribution of heat and particle fluxes at the target plates of tokamaks, a comprehensive understanding of turbulence throughout the entire Scrape-Off-Layer (SOL) is imperative. This study examines divertor turbulence systematically across a broad parameter range on the TCV tokamak, including variations in magnetic field direction, plasma current I p ∈ [140,320] kA, edge safety factor q 95 ∈ [2.6,4.7] and Greenwald fraction f G ∈ [0.18,0.6]. The TCV X-point Gas Puff Imaging (GPI) system is used to measure 2D filament properties in the inner and outer divertor region. The fluctuation levels in the divertor are found to strongly increase with density (to 80% over most of the SOL) while remaining insensitive to I p . The previously identified divertor-localized filaments (DLF), located on the bad curvature side of the outer divertor leg, are found to be a common feature on TCV, while no filaments are observed in the PFR. DLFs are present over most of the parameter space and in both field directions. However, they are absent, or appear only closer to the target, for sufficiently large Λ div ≳ 10 or q 95 ≳ 3.7. Across both I p and f G scans, some clear trends with Λ div are found for divertor filament sizes and velocities, and with target fall-off lengths of density and heat flux profiles at the outer target. This study provides important experimental insights to turbulent transport in the divertor also for comparison with self-consistent, turbulence simulations and extrapolation to future reactor conditions.

cross-field transport↗

DOE OSTI2024

A Methodology for determining optimal milling parameters for low-taper microtensile sample production

Femtosecond lasers are beginning to see an increase in interest for industrial and high throughput microsample milling applications. Despite this, much of the literature regarding removal rate studies for ultrashort pulse laser milling continues to focus on single-pulse or similar experiments that have a very small time on target. The material volume removal rates of femtosecond milling can vary wildly depending on parameters like laser scan speed, hatch spacing, z-axis step size, and pulses on the material. Currently, there is no established methodology for determining the optimal values of these parameters for micromilling applications. This methodology was developed in this study. The methodology consists of a pulse study, a repeat study, and a z-step study that will return the milling parameters that resulted in the largest volume removal rate for the laser used for this research. The methodology was created for the laser system used in this study, and was tested on 316 Stainless Steel, but was developed in such a way that it may be adapted to any material, and with some tweaking of variables might be used in other laser systems. The laser system used in this study utilizes a novel positioning stage that introduces 6 degrees of freedom to the translation of laser samples, being able to tilt and move in all three axes. Using both the developed methodology and the unique capabilities of the laser microtensile samples were produced with taper angles of <1° in 316 Stainless Steel.

Barker, Zachary Wayne↗

DOE OSTI2024

Cosmological constraints from density-split clustering in the BOSS CMASS galaxy sample

We present a clustering analysis of the BOSS DR12 CMASS galaxy sample, combining measurements of the galaxy two-point correlation function and density-split clustering down to a scale of $1 \, h^{-1}\, \text{Mpc}$. Our theoretical framework is based on emulators trained on high-fidelity mock galaxy catalogues that forward model the cosmological dependence of the clustering statistics within an extended-ΛCDM framework, including redshift-space and Alcock–Paczynski distortions. Our base-ΛCDM analysis finds ω cdm = 0.1201 ± 0.0022, σ 8 = 0.792 ± 0.034, and n s = 0.970 ± 0.018, corresponding to fσ 8 = 0.462 ± 0.020 at z ≈ 0.525, which is in agreement with Planck 2018 predictions and various clustering studies in the literature. We test single-parameter extensions to base-ΛCDM, varying the running of the spectral index, the dark energy equation of state, and the density of mass-less relic neutrinos, finding no compelling evidence for deviations from the base model. We model the galaxy–halo connection using a halo occupation distribution framework, finding signatures of environment-based assembly bias in the data. We validate our pipeline against mock catalogues that match the clustering and selection properties of CMASS, showing that we can recover unbiased cosmological constraints even with a volume 84 times larger than the one used in this study.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

The DESI DR1 peculiar velocity survey: Growth rate measurements from the galaxy power spectrum

The large-scale structure of the Universe and its evolution encapsulate a wealth of cosmological information. A powerful means of unlocking this knowledge lies in measuring the auto-power spectrum and/or the cross-power spectrum of the galaxy density and momentum fields, followed by the estimation of cosmological parameters based on these spectrum measurements. In this study, we generalize the cross-power spectrum model to accommodate scenarios in which the density and momentum fields are derived from distinct galaxy surveys. The growth rate of the large-scale structures of the Universe, commonly represented as fσ 8 , was extracted by jointly fitting the monopole and quadrupole moments of the auto-density power spectrum, the monopole of the auto-momentum power spectrum, and the dipole of the cross-power spectrum. Our estimators, theoretical models, and parameter-fitting framework were tested using mocks, confirming their robustness and accuracy in retrieving the fiducial growth rate from simulation. These techniques were then applied to analyse the power spectrum of the DESI Bright Galaxy Survey and Peculiar Velocity Survey. The fit result of the growth rate is fσ8 = 0.440$^{+0.080}_{−0.096}$ at effective redshift zeff = 0.07. By synthesizing the fitting outcomes from correlation functions, maximum likelihood estimation, and the power spectrum, a consensus value is yielded of fσ 8 (z eff = 0.07) = 0.450$^{+0.055}_{−0.055}$, and correspondingly we obtain γ = 0.580$^{+0.110}_{−0.110}$, Ω m = 0.301$^{+0.011}_{−0.011}$, and σ 8 = 0.834$^{+0.032}_{−0.032}$. The measured fσ8 and γ are consistent with the prediction of the Λ cold dark matter model and general relativity.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

The DESI DR1 Peculiar Velocity Survey: Growth Rate Measurements from the Galaxy Power Spectrum

The large-scale structure of the Universe and its evolution encapsulate a wealth of cosmological information. A powerful means of unlocking this knowledge lies in measuring the auto-power spectrum and/or the cross-power spectrum of the galaxy density and momentum fields, followed by the estimation of cosmological parameters based on these spectrum measurements. In this study, we generalize the cross-power spectrum model to accommodate scenarios where the density and momentum fields are derived from distinct galaxy surveys. The growth rate of the large-scale structures of the Universe, commonly represented as $fσ_8$, is extracted by jointly fitting the monopole and quadrupole moments of the auto-density power spectrum, the monopole of the auto-momentum power spectrum, and the dipole of the cross-power spectrum. Our estimators, theoretical models and parameter-fitting framework have been tested using mocks, confirming their robustness and accuracy in retrieving the fiducial growth rate from simulation. These techniques are then applied to analyze the power spectrum of the DESI Bright Galaxy Survey and Peculiar Velocity Survey, and the fit result of the growth rate is $fσ_8=0.440^{+0.080}_{-0.096}$ at effective redshift $z_{\rm eff}=0.07$. By synthesizing the fitting outcomes from correlation functions, maximum likelihood estimation and power spectrum, yields a consensus value of $fσ_8(z_{\rm eff}=0.07) = 0.450 ^{+0.055}_{-0.055}$, and correspondingly we obtain $γ=0.580^{+0.110}_{-0.110}$, $Ω_\mathrm{m}=0.301^{+0.011}_{-0.011}$ and $σ_8=0.834^{+0.032}_{-0.032}$. The measured $fσ_8$ and $γ$ are consistent with the prediction of the $Λ$ Cold Dark Matter Model and General Relativity.

Qin, F. [Marseille, CPPM] (ORCID:0000000179507864)↗

DOE OSTI2024

A Diffusion‐Based Uncertainty Quantification Method to Advance E3SM Land Model Calibration

Abstract Calibrating land surface models and accurately quantifying their uncertainty are crucial for improving the reliability of simulations of complex environmental processes. This, in turn, advances our predictive understanding of ecosystems and supports climate‐resilient decision‐making. Traditional calibration methods, however, face challenges of high computational costs and difficulties in accurately quantifying parameter uncertainties. To address these issues, we develop a diffusion‐based uncertainty quantification (DBUQ) method. Unlike conventional generative diffusion methods, which are computationally expensive and memory‐intensive, DBUQ innovates by formulating a parameterized generative model and approximates this model through supervised learning, which enables quick generation of parameter posterior samples to quantify its uncertainty. DBUQ is effective, efficient, and general‐purpose, making it suitable for site‐specific ecosystem model calibration and broadly applicable for parameter uncertainty quantification across various earth system models. In this study, we applied DBUQ to calibrate the Energy Exascale Earth System Model land model at the Missouri Ozark AmeriFlux forest site. Results indicated that DBUQ produced accurate parameter posterior distributions similar to those from Markov Chain Monte Carlo sampling but with 30 times less computing time. This significant improvement in efficiency suggests that DBUQ can enable rapid, site‐level model calibration at a global scale, enhancing our predictive understanding of climate impacts on terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Implementing Large-Scale CCS in Complex Geologic Reservoirs: Insights from Three Appalachian Basin Case Studies

This paper presents three design case studies for implementing large-scale geologic carbon storage in the Appalachian Basin region of the midwestern United States. While the Appalachian Basin has a challenging setting for carbon storage, the three case studies detailed in this article demonstrate that there are realistic options for implementing carbon storage in the basin. Carbonate rock formations, depleted hydrocarbon reservoirs, and moderate-porosity sandstones can be utilized as carbon-storage reservoirs in the Appalachian Basin. While these are not typical concepts for CO2 storage, the storage zones have advantages such as defined trapping mechanisms, multiple caprocks, and defined boundaries that are not always present in thick, permeable sandstones being targeted for many carbon-storage projects. The geologic setting, geotechnical parameters, and hydrologic setting for the three case studies are provided, along with the results of reservoir simulations of the CO2 injection-deployment strategies. The geological rock formations available for CO2 storage in the Appalachian Basin are more localized reservoirs with defined boundaries and finite storage capacities. Simulation results showed that accessing carbon-storage resources in these fields may require wellfields with 2–10 injection wells. However, these fields would have the capacity to inject 1–3 million metric tons of CO2 per year and up to 90 million metric tons of CO2 in total. The CO2 storage resources would fulfill decarbonization goals for many of the natural-gas power plants, cement plants, hydrogen plants, and refineries in the Appalachian Basin region.

Sminchak, Joel↗

DOE OSTI2024

Optimizing the combustion synthesis of FeAlxOy catalysts for microwave-assisted thermocatalytic dehydrogenation of fossil fuels

The growing demand for hydrogen requires the development of clean and energy-efficient technologies for its synthesis. Microwave-assisted thermocatalytic dehydrogenation of fossil fuels has demonstrated the potential to produce H2 with high yield and selectivity, and simultaneously generate valuable nanostructured carbon byproducts. In prior work, iron-based alumina (FeAlxOy) catalysts for this process were made via solution combustion synthesis (SCS). However, the effect of SCS parameters on the dehydrogenation performance is not well understood. The present study investigates this by varying the SCS fuel, Fe:Al molar ratio, and heating mode. The results show subtle changes of these parameters can result in significant differences in the phase composition, specific surface area, and microwave absorbing properties of FeAlxOy, which all affect microwave-assisted dehydrogenation. Notably, H2 selectivity can be increased from 30% to 74%. Statistical testing determined that the SCS fuel used was the most significant SCS parameter affecting dehydrogenation performance.

Chanoi, Zachary A.↗

DOE OSTI2024

Implementation and Exploration of Parameterizations of Large-Scale Dynamics in NCAR's Single Column Atmosphere Model SCAM6

A single column model with parameterized large-scale (LS) dynamics is used to better understand the response of steady-state tropical precipitation to relative sea surface temperature under various representations of radiation, convection, and circulation. The large-scale dynamics are parametrized via the weak temperature gradient (WTG), damped gravity wave (DGW), and spectral weak temperature gradient (Spectral WTG) method in NCAR's Single Column Atmosphere Model (SCAM6). Radiative cooling is either specified or interactive, and the convective parameterization is run using two different values of a parameter that controls the degree of convective inhibition. Results are interpreted in the context of the Global Atmospheric System Studies -Weak Temperature Gradient (GASS-WTG) Intercomparison project. Using the same parameter settings and simulation configuration as in the GASS-WTG Intercomparison project, SCAM6 under the WTG and DGW methods produces erratic results, suggestive of numerical instability. However, when key parameters are changed to weaken the large-scale circulation's damping of tropospheric temperature variations, SCAM6 performs comparably to single column models in the GASS-WTG Intercomparison project. The Spectral WTG method is less sensitive to changes in convection and radiation than are the other two methods, performing qualitatively similarly across all configurations considered. Under all three methods, circulation strength, represented in 1D by grid-scale vertical velocity, is decreased when barriers to convection are reduced. This effect is most extreme under specified radiative cooling, and is shown to come from increased static stability in the column's reference radiative-convective equilibrium profile. This argument can be extended to interactive radiation cases as well, though perhaps less conclusively.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Uncertainty Propagation from Experiment Measurements to Modeling Approaches: A Case for SMR Steam Entrainment Testing

To license new and advanced reactor designs, regulators must be convinced that their unique safety cases—relative to existing large scale reactors—have been adequately addressed by the designed reactor protection systems. In water cooled small modular reactors (SMRs), droplet entrainment in steam flow has significant implications on the progression of accident scenarios due to its compact design features, which requires representative test data applicable to SMR designs. Computer code, modeling and simulation (M&S) tools and models require adequate verification, assessment, and qualification. This includes M&S results validation against scaled empirical data within allowable uncertainty bands to gain regulatory approvals during the various stages of reactor system design, demonstration, and commercialization. However, measurement uncertainty within the empirical datasets and test data applicability ranges requires careful consideration of M&S inputs (i.e., boundary conditions, and initial conditions), and verification and validation efforts. This study focuses on uncertainty quantification in designing scaled test facilities for SMR applications with appropriate measurements and a standard data-reduction method to estimate thermal hydraulics characteristics parameters that incorporate physics phenomena of interest. In addition, this study supports the evaluation model development and assessment process using M&S that interfaces with advanced computing tools and digital twin capabilities. This will allow synchronization between experiment and modeling approaches for droplet entrainment testing and analysis, improving diagnostics, prognostics, and decision-making to accelerate regulatory approval.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Tuning the Superconducting Transition Temperature of Co-sputtered Iridium and Platinum Films

A superconducting film with a tunable low transition temperature (Tc) is required in high-resolution Transition-Edge Sensor (TES) detectors, which have applications including dark matter detection, low threshold coherent elastic neutrino nucleus scattering measurement, and X-ray spectroscopy. We have been investigating a new approach to tune the Tc of superconducting thin films fabricated by co-sputtering Iridium and Platinum. The effects of Pt concentration and deposition parameters on the films' structural, electrical, and superconducting properties have been studied. AFM and XRD techniques and low temperature resistance measurements have been utilized for film characterization. By varying the Pt concentration and deposition parameters when co-sputtering, we have successfully achieved controllable tuning of Tc in the range of 30-200 mK. The experimental results demonstrate co-sputtering as a viable method for controlling the Tc of Ir-based thin films that can be applied to fabricating high-resolution TESs.

Yefremenko, V. G.↗