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DOE OSTI2022

Leakoff assessment of nanoparticle-stabilized CO 2 foams for fracturing applications

The leakoff of multiphase systems through porous media is a complicated process. In this study, we have designed an experimental setup that is used to assess the leakoff of the liquid and gas phase under pressurized conditions. The novelty of this study is that while most previous studies utilized fluid/gas in the aqueous phase, nanoparticles are introduced in this study, which formed a solid/fluid/gas multiphase system to boost foam performance and reduce leakoff. In the parametric experimental analysis, the effects of foam quality, core permeability, surfactant concentration, and polymer concentration on the dynamic and static leakoff rates of liquid and gas are evaluated. It was found that core permeability affects the leakoff of foam the most with a leakoff coefficient of up to 1.37015 $ft/\sqrt{min}$ for gas and up to 0.1056 $ft/\sqrt{min}$ for liquid under the experiment settings herein. The leakoff rate of gas is generally several magnitudes higher than that of the liquid. When CO 2 gas is present in the foam, the leakoff coefficient falls in the range between 0 and 1.37015 $ft/\sqrt{min}$ for gas, and between 0.0005 and 0.1056 $ft/\sqrt{min}$ for liquid. Finally, the methodology and results of this study shed light on the mechanistic understanding of the leakoff properties of multiphase systems and could be used to assist the design of foam fracturing for reservoir stimulation.

03 NATURAL GAS↗

DOE OSTI2021

Thermodynamic Analysis of Thermo-vacuum Clothes Drying Operation

Clothes drying accounts for a significant amount of energy consumed in residential and commercial sectors. A thermal vacuum clothes drying technology (TVCD) is proposed as an advanced clothes dryer which can significantly reduce the energy requirements by expediting the drying process. In the conventional convective clothes dryer, hot dry air is introduced into the drum which gets in direct contact to dry the clothes. This process is energy inefficient since the significant amount of heat and the water carried out with the exhaust stream are wasted. In contrast to the conventional convective drying technique, the drying mechanism of TVCD is through nucleate boiling at low temperature due to reduced vessel pressure. The process is not only efficient but also reduces the required time for drying. The objective of this paper is to develop a comprehensive thermodynamic model to predict the transient drying process of TVCD. The three-stage system model including the detail analysis of individual components is capable of simulating the variation of the water content in the textile under various operational conditions. The preliminary results show that the drying time of 3 lb textile from 70% to 2.5% in TVCD is approximately four times less than the time required in the conventional clothes dryer. Parametric studies are carried out to understand the effect of operation conditions and component geometry on the system performance. Energy consumption of the system is also analyzed.

Yang, Cheng-Min↗

DOE OSTI2022

Application of a Novel Heat Pump Model for Estimating Economic Viability and Barriers of Heat Pumps in Dairy Applications in the United States

Heat pumps represent an important opportunity for energy savings and decarbonization. This work investigates the techno-economic performance of high-temperature heat pumps (HTHPs) for use in the U.S. dairy industry. The studied heat pump performs a 50 °C temperature lift on a waste heat stream of cleaning water and applies the upgraded heat stream to a fluid milk pasteurization process. This work involved the creation of a HTHP model that estimated the coefficient of performance (COP), internal rate of return (IRR), net present value (NPV), and payback period (PBP), and emissions saved for a heat pump replacing a natural gas boiler. Capital costs, operations, and maintenance (O&M) cost, heat pump lifetime, electricity prices, natural gas prices, and a cost of carbon were varied to perform a parametric study on the factors affecting the break-even price of HTHPs. The results show that HTHP economics are highly sensitive to COP and energy price environment, and less sensitive to capital and O&M cost variance, leading to a large scatter of positive and negative NPVs based on U.S. location. PBPs demonstrate a defined threshold, based on energy price environment, below which favorable two-to-three-year PBPs predominate. This work is focused on the U.S. dairy industry, but international application in relation to fossil vs. electricity price regimes. Heat pumps have seen wider adoption in regions with a high ratio of fossil energy to electricity prices ($/MMBTU vs. $/kWh). The U.S. has plentiful natural gas resulting in lower fossil energy prices which has reduced heat pump adoption. This paper identifies potential first mover industries for HTHP adoption and their associated price regimes even in regions with lower ratios of fossil energy to electricity prices that exist many places globally.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗

DOE OSTI2022

Modeling and Analysis of a Polyphase Wireless Power Transfer System for EV Charging Applications

Extreme fast charging is an emerging technology targeting to significantly decrease charging times of electric vehicles to 10–20 minutes, similar to an interstate gas refueling practice. High-power wireless power transfer (WPT) systems with polyphase electromagnetic couplers can be an attractive solution for these applications due to the very high surface power density of polyphase coils with reduced ripple current characteristics on both the primary and secondary sides that result in more compact designs with reduced dc bus bar capacitor requirements. In addition, WPT systems offer automated charging process, which can be an enabling technology for connected and automated vehicles, with high-efficiency, convenience, safety, and flexibility. This study presents a matrix representation of a mathematical model for a three-phase WPT system with series-series connected three-phase resonant compensation networks. Nonzero interphase mutual inductances between the same side phase windings are considered for tuning to obtain a circuit model for parametric sensitivity. Simulation and experimental results presented for a 50-kW experimental prototype to demonstrate the operation of the polyphase WPT system.

Zeng, Rong↗

DOE OSTI2023

Modification of Lie's transform perturbation theory for charged particle motion in a magnetic field

It is pointed out that the conventional Lie transform perturbation theory for the guiding center motion of charged particles in a magnetic field needs to be modified for ordering inconsistency. There are two reasons. First, the ordering difference between the temporal variation of gyrophase and that of the other phase space coordinates needs to be taken into account. Second, it is also important to note that the parametric limit of the derivative of a function is not equivalent to the derivative of the limit function. When these facts are taken into account, the near identity transformation rule for one form related to the Lagrangian is modified. With the modified near identity transformation rule, the drift motion of charged particles can be described in the first order, instead of the second order and beyond through a tedious expansion process as in the conventional formulation. Here, this resolves the discrepancy between the direct and Lie transform treatments in the Lagrangian perturbation theory for charged particle motion in a magnetic field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

LENS: Learning Enabled Network Synthesis

RTRC and UMD have developed novel machine learning based methods under the ARPA-E DIFFERENTIATE program for rapid acceleration of hypothesis generation in complex architecture design spaces involving both discrete choices of component inclusion and interconnection and continuous parametric decisions. The project named Learning Enabled Network Synthesis (LENS) further demonstrated the developed methods on challenging electrical power converter design problems by identifying the most suitable circuit topologies and simultaneously selecting the most appropriate components to achieve optimized design of power converter with improved performances. We demonstrated that LENS could enable exploration of very large design space of circuit topologies and components by addressing the limitations of conventional design process in non-linear, high switching speed, multi-dimensional power converter design and optimization. The key innovation developed in LENS is the seamless integration of statistical learning and logical reasoning techniques and building on the individual strengths of these techniques for rapid hypothesis discovery. The main component of LENS comprises of: 1) Graph Reasoning Engine (GRE) to enforce composition rules that rapidly reject all discrete architectures that are composed incorrectly and generates an adaptive database of feasible designs which can be used by ML modules, 2) Graph Generative Learning module which is a deep neural network based generative model for graph architectures which can enable design space exploration beyond the dataset generated by the GRE, 3) Graph Reduced Order Model (ROM) for graph domains for accelerating computation of output metrics, and 4) Active learning and Rule Discovery module for sample efficient learning and extracting logical rules from the learned ML models which will be integrated in the GRE to enhance the filtering effectiveness. LENS approach can be applied to any design domains where designs can be represented as multi-attribute graphs. The LENS team integrated the various technical innovations listed above into an optimization pipeline and exercised the optimization pipeline on the converter design problem. The LENS project demonstrated that the developed AI/ML technologies can be used to generate novel converter circuits >45x faster than experts on chosen use-cases. This can enable faster design space exploration and identification of new designs which are not considered by experts due to the increasing design space complexity. This has significant potential impact on the public and energy needs of the country. It is currently estimated that 30% of all electrical powers generated passes through power converters. The future estimate is that 80% of all power generated would be passing through converters. LENS fills a critical gap in this space since by accelerating the design process the designers would be able to generate more efficient converters which can lead to significant energy savings for the country.

42 ENGINEERING↗

DOE OSTI2021

Plasma-catalyst modeling for materials selection: challenges and opportunities in nitrogen oxidation

Reliable kinetic models are essential to rationalize observations and to guide the selection of appropriate plasma-catalyst combinations. Kinetic models coupling plasma- and heterogeneous-catalytic-chemistries, however, are primitive. Here, we combine reduced plasma chemistries and density functional theory parameterized surface reactions to model NO formation from N2 oxidation, an alternative nitrogen fixation process. We first show plasma excited species can enhance turnover frequencies of both Pt and Au. The enhancing potential is a function of plasma species and their densities. We then compare NO production between plasma/Pt and plasma/Au with an integral reactor model and explore the dependence of NO production as a function of plasma conditions, reactor configurations and chemical compositions. Plasma/Pt generates more NO than plasma/Au under most thermal and plasma parametric conditions. Plasma/Au outperforms plasma/Pt under high plasma excitations at low temperatures. Furthermore, these results highlight that selection of plasma-catalyst combinations should consider the properties of plasmas, materials and the coupling of the two.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

A first principles framework to predict the transient performance of latent heat thermal energy storage

Thermal energy storage (TES) is increasingly recognized as an essential component of efficient Combined Heat and Power (CHP), Concentrated Solar Power (CSP), Heating Ventilation and Air Conditioning (HVAC), and refrigeration as it reduces peak demand while helping to manage intermittent availability of energy (e.g., from solar or wind). Latent Heat Thermal Energy Storage (LHTES) is a viable option because of its high energy storage density. Parametric analysis of LHTES in terms of dimensionless numbers is highly desired as a tool to model LHTES systems. One approach is to develop a model equation so as to minimize the error between the model and data obtained from experiments or simulations. While this approach can produce an accurate correlation applicable within the range of data used for its creation, it does not provide physical understanding of the rate-limiting process controlling the transient behavior of the device. In this paper we present an alternative approach whereby the potential rate-limiting processes are identified from first principles and then the key process is determined as a function of time as a LHTES device is charged. For example, in a simple geometry, the melt-fraction can be expected to vary linearly in time if the heat transfer rate is limited by natural convection of the phase changing material and we show it scales with the PCM Grashof number as $Gr^1_p$ and PCM Prandtl number as $Pr_p^{(1/3)}$. On the other hand, if surface area of solid PCM limits the heat transfer rate, the melt fraction increases asymptotically to reach full melting. The existence of these linear and asymptotic regions and the $Gr^1_pP r^{1/3}_p$ shape of the melt fraction curve is verified using our database of 64 simulations. Of practical importance in designing LHTES devices is the melt fraction at which the heat transfer rate ceases to be limited by convection, after which the heat storage rate deteriorates. For our geometry, this is found to be about 90%. This test case of our methodology shows the value of our approach, that predicting heat storage rate based on the rate-limiting physical phenomenon as a function of time is an effective approach to modeling LHTES devices.

25 ENERGY STORAGE↗

DOE OSTI2020

Three-colour digital holographic microscopy based on a Mach – Zender interferometer and a solid-state RGB laser

We have developed a facility for recording colour digital holograms involving a Mach – Zender interferometer and a pulsed solid-state RGB laser, which radiates simultaneously at three wavelengths: 451, 532, and 634 nm. These wavelengths are obtained in the conversion of the radiation of a pulsed Nd{sup 3+} : YAG laser (1064 nm), which operates in the regime of intracavity parametric oscillation at a wavelength of 1570 nm, with the subsequent conversion of its frequencies to the red, green, and blue spectral regions in nonlinear KTP-crystal elements. The combination of this three-wavelength pulsed light source with the Mach – Zender interferometer provides the simultaneous recording of three spectral digital holograms with one matrix RGB radiation detector. Pulsed three-colour digital holography shows promise for the analysis of fast processes and rapidly varying colour phase objects. (paper)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

A multiscale packed-bed reactor model for sustainable ethylene production via chemical looping oxidative coupling of methane

The rising global warming concerns and shale gas discovery have prompted research in the direction of greenhouse gas (GHG), such as methane, reduction and conversion. Oxidative coupling of methane (OCM) offers a pathway to low carbon-intense valorization of methane while producing ethylene, a chemical regarded as central to the petrochemical industry. Even after decades of OCM discovery, researchers keep understanding the process and underlying chemical reactions in a pursuit to achieve industrial viability for OCM. Here, in general, OCM suffers from low C 2 selectivity, yield and reactor temperature runaways due to highly exothermic nature of its reactions. Computational Fluid Dynamics (CFD) tools help analyze spatial gradients within the reactor to deeply understand the diffusion of species, mass and heat transfer phenomena. Furthermore, challenges associated with scaling up such as hot spot formation and parametric sensitivity can be addressed without having to expend on costly experiments. The current paper presents a multiscale packed-bed reactor CFD model coupled with a chemical kinetic model for the chemical looping OCM. The CFD model includes two scales i.e., macroscale for catalyst bed and microscale for individual pellets. Moreover, a chemical kinetic model based on 10 gas-phase reactions is integrated with the CFD model. An additional surface reaction for the formation of gas-phase oxygen from catalyst surface is added to account for the absence of feed oxygen. The model is calibrated against experimental results. The calibrated model captures trends in CH 4 conversion, C 2 selectivity and C 2 yield within a ± 4.35 % range across a temperature range of 700-900 °C. Moreover, model fidelity is evaluated by varying key computational parameters such as mesh resolution and time step size. The model is also verified by varying the inlet methane concentration and the gas hourly space velocity (GHSV) and comparing the results with literature. A sensitivity analysis and scale-up of the current model is undergoing.

Chemical looping↗

DOE OSTI2023

Insights into Waterflooding in Hydrocarbon-Bearing Nanochannels of Varying Cross Sections from Mesoscopic Multiphase Flow Simulations

Waterflooding is one of the geotechnique used to recover fuel sources from nanoporous geological formations. The scientific understanding of the process that involves the multiphase flow of nanoconfined fluids, however, has lagged, mainly due to the complex nanopore geometries and chemical compositions. To enable benchmarked flow of nanoconfined fluids, the architected geomaterials, such as synthesized mesoporous silica with tunable pore shapes and surface chemical properties, are used for designing and conducting experiments and simulations. This work uses a modified many-body dissipative particle dynamics (mDPD) model with accurately calibrated parameters to perform parametric flow simulations for studying the influences of waterflooding driven power, pore shape, surface roughness, and surface wettability on the multiphase flow in heptane-saturated silica nanochannels. Remarkably, up to 80\% reduction in the effective permeability is found for water-driven heptane flow in a baseline 4.5 nm-wide slit channel, when compared with the Hagen–Poiseuille equation. In the 4.5 nm-wide channels with architected surface roughness, the flow rate is found either higher or lower than the baseline case, depending on the shape and size of cross-sections. High wettability of the solid surface to water is essential for achieving high recovery of heptane, regardless of surface roughness. When the solid surface is less wetting or non-wetting to water, the existence of an optimal waterflooding driven power is found to allow for the highest possible recovery. A detailed analysis on the evolution of the transient water-heptane interface in those nanochannels is presented to elucidate the underlying mechanisms that impact or dictate the multiphase flow behaviors.

58 GEOSCIENCES↗

DOE OSTI2020

Data-driven recovery of hidden physics in reduced order modeling of fluid flows

In this article, we introduce a modular hybrid analysis and modeling (HAM) approach to account for hidden physics in reduced order modeling (ROM) of parameterized systems relevant to fluid dynamics. The hybrid ROM framework is based on using first principles to model the known physics in conjunction with utilizing the data-driven machine learning tools to model the remaining residual that is hidden in data. This framework employs proper orthogonal decomposition as a compression tool to construct orthonormal bases and Galerkin projection (GP) as a model to build the dynamical core of the system. Our proposed methodology hence compensates structural or epistemic uncertainties in models and utilizes the observed data snapshots to compute true modal coefficients spanned by these bases. The GP model is then corrected at every time step with a data-driven rectification using a long short-term memory (LSTM) neural network architecture to incorporate hidden physics. A Grassmannian manifold approach is also adopted for interpolating basis functions to unseen parametric conditions. The control parameter governing the system's behavior is thus implicitly considered through true modal coefficients as input features to the LSTM network. The effectiveness of the HAM approach is then discussed through illustrative examples that are generated synthetically to take hidden physics into account. Furthermore, our approach thus provides insights addressing a fundamental limitation of the physics-based models when the governing equations are incomplete to represent underlying physical processes.

42 ENGINEERING↗

DOE OSTI2022

Sinter formation during directed energy deposition of titanium alloy powders

During directed energy deposition (DED) additive manufacturing, powder agglomeration and sintering can occur outside of the melt pool when using titanium alloy powders. Using in situ synchrotron radiography we investigate the mechanisms by which sintering of Ti6242 powder occurs around the pool, performing a parametric study to determine the influence of laser power and stage traverse speed on sinter build-up. The results reveal that detrimental sinter can be reduced using a high laser power or increased stage traverse speed, although the latter also reduces deposition layer thickness. The mechanism of sinter formation during DED was determined to be in-flight heating of the powder particles in the laser beam. Calculations of particle heating under the processing conditions explored in this study confirm that powder particles can reasonably exceed 700 °C, the threshold for Ti surface oxide dissolution, and thus the powder is prone to sintering if not incorporated into the melt pool. The build-up of sinter powder layer on deposit surfaces led to lack of fusion pores. To mitigate sinter formation and its detrimental effects on DED component quality, it is essential that the powder delivery spot area is smaller than the melt pool, ensuring most powder lands in the melt pool.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A universal variational quantum eigensolver for non-Hermitian systems

Abstract Many quantum algorithms are developed to evaluate eigenvalues for Hermitian matrices. However, few practical approach exists for the eigenanalysis of non-Hermintian ones, such as arising from modern power systems. The main difficulty lies in the fact that, as the eigenvector matrix of a general matrix can be non-unitary, solving a general eigenvalue problem is inherently incompatible with existing unitary-gate-based quantum methods. To fill this gap, this paper introduces a Variational Quantum Universal Eigensolver (VQUE), which is deployable on noisy intermediate scale quantum computers. Our new contributions include: (1) The first universal variational quantum algorithm capable of evaluating the eigenvalues of non-Hermitian matrices—Inspired by Schur’s triangularization theory, VQUE unitarizes the eigenvalue problem to a procedure of searching unitary transformation matrices via quantum devices; (2) A Quantum Process Snapshot technique is devised to make VQUE maintain the potential quantum advantage inherited from the original variational quantum eigensolver—With additional $$O(log_{2}{N})$$ O ( l o g 2 N ) quantum gates, this method efficiently identifies whether a unitary operator is triangular with respect to a given basis; (3) Successful deployment and validation of VQUE on a real noisy quantum computer, which demonstrates the algorithm’s feasibility. We also undertake a comprehensive parametric study to validate VQUE’s scalability, generality, and performance in realistic applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Study of γ γ → γ ψ ( 2 S ) at Belle

Using 980 fb -1 of data at and around the Υ(nS)(n = 1, 2, 3, 4, 5) resonances collected with the Belle detector at the KEKB asymmetric-energy e+e- collider, the two-photon process γγ → γψ(2S) is studied from the threshold to 4.2 GeV for the first time. Two structures are seen in the invariant mass distribution of γψ(2S): one at M R 1 = 3922.4 ± 6.5 ± 2.0 MeV/c 2 with a width of Γ R 1 = 22 ± 17 ± 4 MeV, and another at M R 2 = 4014.3 ± 4.0 ± 1.5 MeV/c 2 with a width of Γ R 2 = 4 ± 11 ± 6 MeV; the signals are parametrized with the incoherent sum of two Breit- Wigner functions. The first structure is consistent with the X(3915) or the χ c2 (3930), and the local statistical significance is determined to be 3.1σ with the systematic uncertainties included. The second matches none of the known charmonium or charmonium like states, and its global significance is determined to be 2.8σ including the look-elsewhere effect. The production rates are Γ γγ B(R 1 → γψ(2S)) = 9.8 ± 3.6 ± 1.2 eV assuming (J PC , |λ|) = (0 ++ , 0) or 2.0 ± 0.7 ± 0.2 eV with (2 ++ , 2) for the first structure and Γ γγ B(R 2 → γψ(2S)) = 6.2 ± 2.2 ± 0.8 eV with (0 ++ , 0) or 1.2 ± 0.4 ± 0.2 eV with (2 ++ , 2) for the second one. Furthermore, the first errors are statistical and the second systematic, and λ is the helicity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Study of effect of PWR cold leg temperature gradient on reactor core condition

Effects of temperature and flow gradients in Westinghouse designed three-loop Pressurized Water Reactor (PWR) cold legs, the piping between the main coolant pump and the reactor vessel, were evaluated using Computational Fluid Dynamics (CFD) code STAR CCM+ and coupled neutronic and thermal-hydraulic (T/H) code system VERA. In the parametric study, several symmetric and asymmetric temperature gradients that were significantly larger than those observed from plant measurements were applied to the cold leg inlets for comparison with the base case without any temperature gradient. A CFD model using the STAR-CCM+ code was developed for a portion of the RCS region between the Reactor Coolant Pump (RCP) and the core inlet based on previously validated modeling approach. The CFD simulation results were processed for the temperature and flow rate distributions at the core inlet as input to the VERA calculations. The VERA code system consists of COBRA-TF (CTF) for thermal-hydraulics, MPACT for reactor physics and neutron transport, and ORIGEN for isotopic depletion. The VERA model was for depletion calculations of a high-burnup loading pattern with the reactor core in pin-by-pin and subchannel resolution. The results of the study indicate that the postulated temperature gradients within the PWR cold legs do not result in any significant changes in the core inlet temperature distributions and the core power distributions during the reactor operation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Dynamic Promotion of the Oxygen Evolution Reaction via Programmable Metal Oxides

Hydrogen gas is a promising renewable energy storage medium when produced via water electrolysis, but this process is limited by the sluggish kinetics of the anodic oxygen evolution reaction (OER). Herein, we used a microkinetic model to investigate promoting the OER using programmable oxide catalysts (i.e., forced catalyst dynamics). We found that programmable catalysts could increase current density at a fixed overpotential (100–600× over static rates) or reduce the overpotential required to reach a fixed current density of 10 mA cm –2 (45–140% reduction vs static). In our kinetic parametrization, the key parameters controlling the quality of the catalytic ratchet were the O*-to-OOH* and O*-to-OH* activation barriers. Furthermore, our findings indicate that programmable catalysts may be a viable strategy for accelerating the OER or enabling lower-overpotential operation, but a more accurate kinetic parametrization is required for precise predictions of performance, ratchet quality, and resulting energy efficiency.

Catalysts↗