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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Lake Biogeochemistry Model for Global Methane Emissions: Model Development, Site‐Level Validation, and Global Applicability

Abstract Lakes are important sentinels of climate change and may contribute over 30% of natural methane (CH 4 ) emissions; however, no earth system model (ESM) has represented lake CH 4 dynamics. To fill this gap, we refined a process‐based lake biogeochemical model to simulate global lake CH 4 emissions, including representation of lake bathymetry, oxic methane production (OMP), the effect of water level on ebullition, new non‐linear CH 4 oxidation kinetics, and the coupling of sediment carbon pools with in‐lake primary production and terrigenous carbon loadings. We compiled a lake CH 4 data set for model validation. The model shows promising performance in capturing the seasonal and inter‐annual variabilities of CH 4 emissions at 10 representative lakes for different lake types and the variations in mean annual CH 4 emissions among 106 lakes across the globe. The model reproduces the variations of the observed surface CH 4 diffusion and ebullition along the gradients of lake latitude, depth, and surface area. The results suggest that OMP could play an important role in surface CH 4 diffusion, and its relative importance is higher in less productive and/or deeper lakes. The model performance is improved for capturing CH 4 outgassing events in non‐floodplain lakes and the seasonal variability of CH 4 ebullition in floodplain lakes by representing the effect of water level on ebullition. The model can be integrated into ESMs to constrain global lake CH 4 emissions and climate‐CH 4 feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Feasibility of an Accelerometer-Based Structural Health Monitoring System for the LANL Blast Tube

A modeling- and simulation-based study was conducted on the feasibility of implementing an accelerometer-based SHM system on the Los Alamos National Laboratory blast tube. A blast tube experiment was modeled using the Abaqus explicit finite element solver. A custom user subroutine was written to apply test-like pressure loading to the inside surface of the blast tube. The subroutine applies analytically defined pressure loads derived from tracer output taken from a Compressible Flow Computational Fluid Dynamics Solver model of the blast tube. Five unique versions of the model were created: an undamaged reference model at 65°F was used as the baseline and compared to equivalent models at 10°F and 100°F. These three models were compared to models with small damage at the reference temperature. The two types of damage considered were a radial (circumferential) crack in the main tube body and a longitudinal crack in the supports. Acceleration outputs were extracted from accelerometer bodies included in the model and were post processed using a variety of standard SHM techniques. Different potential features signaling failure were extracted and compared using statistical methods in the time and frequency domains. A method was identified that clearly shows that differences in structural response resulting from the modeled damage can be differentiated from the structural response resulting from changing environmental conditions. However, the amount of damage applied to create observable differences in the accelerometer data was so large that simpler methods of damage detection would be more cost effective in locating damage.

42 ENGINEERING↗
DOE OSTI2025

The decay of HIV under anti-retroviral therapy is biphasic even in humanized mice with just T cells

HIV-1 plasma viral load decays in a biphasic manner during antiretroviral therapy (ART). It was hypothesized that this is due to infection of different cell types, namely CD4+ T cells and macrophages. We studied this possibility directly by modeling the decay of HIV-1 in humanized mice. We utilized previously published data from humanized T-cell only mice (TOM) and myeloid-only mice (MOM) infected with HIV-1 and treated with a potent ART regimen. Viral load decay dynamics were modeled using either a single or a biexponential decay fitted using nonlinear mixed effects techniques. Fits were compared using the corrected Bayesian information criterion (BICc). In TOM, the biphasic model was significantly better than a single-phase decay model (ΔBICc ≈ 16) despite additional parameters. In MOM, the biphasic decay was statistically better, but there was substantial uncertainty because the virus goes below detection very fast. The first-phase half-life was consistent between groups (1.2 days in MOM and 1.3 days in TOM) and similar to the half-life estimated in human infection. The second-phase decay in these mice was minimal likely due to low initial viral loads. Additional analyses with mice containing both CD4+ T cells and macrophages or X4-tropic virus-infected MOM mice confirmed the biphasic pattern, demonstrating the robustness of this result. The biphasic decline in HIV-1 occurs, even with only CD4+ T cells, refuting the hypothesis that distinct cell populations (CD4+ T cells and macrophages) drive each decay phase. These findings support an alternative model in which the observed dynamics arise from intrinsic properties of the viral infection lifecycle rather than from cellular compartmentalization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Feedforward-feedback ammonia control at a water resource recovery facility based on a digital twin with hybrid model

Ammonia-based aeration control (ABAC) at full-scale Water Resource Recovery Facilities (WRRFs) can be challenged by diurnal loading and transport delays. This work addressed these challenges using a hybrid feedforward–feedback controller built on Activated Sludge Model 1 (ASM1), marking the first full-scale deployment to pair a mechanistic feedforward core with data-driven corrections. The objectives were to improve ammonia setpoint tracking, assess performance of the mechanistic model when enhanced with data-driven corrections, and document full-scale operation. The hybrid model incorporates two data-driven components: (1) a Mechanistic Error Forecasting Engine (MEFE), consisting of a multivariate linear regressor and a long short-term memory (LSTM) ensemble. Defying expectations, low-parameter models outperformed more complex alternatives, reducing the mechanistic error by 71%. (2) A Residual Oscillation Forecasting Engine (ROFE), based on Fast Fourier Transform, reduced the remaining error by another 35%. Two proportional–integral (PI) feedback loops further (i) trim the feedforward output and (ii) eliminate residual controller error in the final aerobic zone. In full-scale operation, the controller reduced mean-squared error (MSE) by 94% over the baseline and produced more stable dissolved oxygen (DO) setpoints. Overall, it was proven that layering multi-timescale data-driven models on a mechanistic core can yield reliable ABAC performance at WRRFs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Multi-Objective design of interlocking metasurfaces using conditional diffusion models

Unit cell design remains a major challenge for interlocking metasurfaces, a promising joining technology for dissimilar materials, due to the complex, competing, multivariate design space and the need for rapid adaptation to varying performance requirements. This study explores Conditional Diffusion Models as a design optimization tool for interlocking metasurfaces. Given the complex, competing, multivariate design space for interlocking metasurfaces, unit cell design remains a major challenge for this joining technology. We trained a conditional diffusion model on 25,000 finite element analysis-simulated interlocking metasurface unit cells to generate designs with tailored thermo-mechanical properties (tensile strength, shear strength, and thermal conductivity) based on specified performance criteria. The model demonstrated a success rate of approximately 72 % in producing designs that met specified property bounds. The conditional diffusion model generated both thermally resistive and conductive designs, revealing clear trends in design characteristics: taller, dendritic structures were advantageous for tensile loads, while shorter, robust designs excelled in shear applications. Our findings indicate that the model's performance is more influenced by the breadth of the design space than by the quantity of training data, highlighting the importance of expansive design domains for generating innovative solutions. This work establishes conditional diffusion models as a highly efficient and adaptable tool for rapid interlocking metasurface unit cell design, paving the way for advancements in multi-material joining technologies, as well as highlighting the justification to leverage conditional diffusion models as design tools across complex design domains.

Conditional diffusion models↗
DOE OSTI2026

AMAROK: A Radio Frequency Development Platform for High-Power, Full-Scale Positive Ion Sources for DIII-D Neutral Beam Injectors

Next-generation neutral beam injection (NBI) systems demand RF ion sources capable of efficiently coupling >120 kW at 2–4-MHz frequencies, yet existing designs face voltage standoff and impedance-matching challenges. To address this, the advanced multicoil antenna for RF operations at kilowatts (AMAROK) was developed as a high-power RF inductively coupled plasma (ICP) source delivering up to 200 kW in the 2–4-MHz range via four phase-controlled generators for flexible power sharing. Two antenna designs—a single-strap multiturn (MT) and a multistrap single-turn (ST) design—were evaluated to optimize resonance, impedance matching, and power coupling across plasma loads. Here, a semi-analytical self-resonant frequency (SRF) model, validated experimentally, predicts resonance trends for arbitrary turn counts and tubing diameters, enabling rapid antenna optimization. Strap-to-strap mutual inductance in the ST configuration showed strong spatial dependence, guiding generator operation and total load inductance. These insights informed a custom π -topology matching network, achieving stable impedance matching over a wide range of plasma-driven loads. Collectively, these results position AMAROK as a versatile testbed for advancing high-power RF source technology in fusion NBI applications.

DIII-D↗
DOE OSTI2026

A Physics-Based Digital Twin for Wave Elevation and Seabed Moment Estimation of Offshore Monopiles: Preprint

In this work, we present a proof of concept of a physics-based digital twin for a monopile structure (with overhead inertia) subjected to wave loading. The digital twin is formulated using reduced-order models derived from first principles and combined with a Kalman filter for state estimation. The proposed framework estimates the monopile top motion, the wave elevation, and the section forces and moments along the pile using primarily acceleration measurements at the monopile top. Key innovations include the use of a hydrodynamic shape function to represent distributed wave loading in a compact and computationally efficient manner, and the introduction of a shaping filter to augment the state-space with wave kinematics. Synthetic measurement data are generated using OpenFAST and used as a reference to assess the performance of the digital twin. Results demonstrate that the wave elevation can be accurately reconstructed without direct sea-state measurements as long as the wave regime is inertia-dominated. Under the ideal tested conditions, the total hydrodynamic force and sea-bed bending moment are estimated with relative errors on the order of 1% and correlation coefficients exceeding 96%. Future work will evaluate the estimator's performance under operational uncertainties and more complex loading conditions.

17 WIND ENERGY↗
DOE OSTI2026

Digital Assurance for Grid Reliability in the Era of Large Load Growth

The rapid expansion of large electric loads is reshaping the operational and regulatory landscape of the U.S. electric grid. These facilities are reaching new scales of expansion, now exceeding a gigawatt per site, and their highly sensitive, digitally driven behaviors introduce new reliability risks. Recent grid events, including large load losses following routine transmission disturbances, highlight the consequences of limited ride-through capability, inconsistent protection settings, inadequate modeling, and lack of behind-the-meter visibility. Parallels to earlier integration challenges of new grid technologies suggest that the grid’s existing processes, standards, and interconnection frameworks are no longer adequate for emerging large loads. This brief synthesizes lessons from the evolution of inverter-based resource regulation and applies them to large-load integration. It identifies critical gaps in modeling accuracy, interconnection processes, performance standards, and compliance mechanisms. Technical recommendations emphasize advanced monitoring, improved modeling, coordinated communication protocols, modernized substations, and structured behind-the-meter control schemes. Collectively, these measures provide a roadmap to maintain bulk power system reliability while enabling the continued growth of large, electrified digital infrastructure.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Test of Functional Balance Theory for Wetland Biomass Allocation in a Global Change Experiment

Abstract Forecasts of root growth and carbon sequestration under global change are compromised by uncertainty in how plants will allocate biomass between above and belowground pools. Here, we develop a simple model to assess whether functional balance theory can explain a complex biomass allocation response observed in a brackish marsh under experimental warming and elevated CO 2 . Our model shows how treatment‐driven changes in nitrogen supply and demand can explain divergent observations of root growth (i.e., maximum responses under intermediate warming and elevated CO 2 ). The model also reveals a surprising interaction between warming and eutrophication, where enhanced N loading to coastal marshes may reduce adverse impacts of warming on root growth. Our findings provide a mechanistic basis for incorporating biomass allocation into forecast models of marsh evolution. They also provide a general example of using ecological theory to decompose complex net responses observed in multi‐factor global change experiments into constituent processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Development of a high current density, high temperature superconducting cable for pulsed magnets

Abstract A low AC loss Rare Earth Barium Copper Oxide (REBCO) cable, based on the VIPER cable technology has been developed by Commonwealth Fusion Systems for use in high field, REBCO based tokamaks. The new cable is composed of partitioned and transposed copper ‘petals’ shaped to fit together in a circular pattern with each petal containing a REBCO tape stack and insulated from each other to reduce AC losses. A stainless steel jacket adds mechanical robustness—also serving as a vessel for solder impregnation—while a tube runs through the middle for cooling purposes. Additionally, fiber optic sensors are placed under the tape stacks for quench detection. To qualify this design, a series of experiments were conducted as part of the SPARC tokamak Central Solenoid Model Coil program—to retire the risks associated with full scale, fast ramping, high flux HTS Central Solenoid (CS) and Poloidal Field (PF) coils for tokamak fusion power plants and net energy demonstrators. These risk study and risk reduction experiments include (1) AC loss measurement and model validation in the range of ~5 T/s, (2) an IxB electromagnetic loading of over 850 kN/m at the cable level and up to 300 kN/m at the stack level, (3) a transverse compression resilience of over 350 MPa, (4) manufacturability at tokamak relevant speeds and scales, (5) cable to cable joint performance, (6) fiber optic based quench detection speed, accuracy, and feasibility, and (7) overall winding pack integration and magnet assembly. The result is a cable technology, now referred to as PIT VIPER, with AC losses that measure fifteen times lower (at ~5 T/s) than its predecessor technology; a 2% or lower degradation of critical current (Ic) at high IxB electromagnetic loads; no detectable Ic degradation up to 570 MPa of transverse compression on the cable unit cell; end to end magnet manufacturing, consistently producing Ic values within 7% of the model prediction; cable to cable joint resistances at 20 K on the order of ~15 nΩ; and fast, functional quench detection capabilities that do not involve voltage taps. This cable technology will be tested comprehensively in a Central Solenoid Model Coil to prove its readiness for compact, high field tokamak operation.

Sanabria, Charlie (ORCID:0000000150175309)↗
DOE OSTI2026

VRN3P: Variational Recurrent Neural Network Based Net-Load Prediction under High Solar Penetration

This is the final technical report for the SETO-funded VRN3P project (PNNL# 76914). The goal of this project, led by Pacific Northwest National Laboratory (PNNL), in collaboration with Lawrence Livermore National Laboratory (LLNL) and Portland General Electric (PGE), was to develop and validate a deep variational recurrent neural network-based net-load prediction (VRN3P) framework for probabilistic time-series forecasting of day-ahead net-load under high solar penetration scenarios. The project team reports successful design of a novel probabilistic net-load forecasting architecture, comprising of a variational autoencoder and a recurrent neural network, which demonstrates 30% improvement in forecast performance, 60% improvement in training time, and consumes 44% less memory, when compared with conventional baseline models. The team tested the VRN3P model performance on GridLAB-D test-cases representing varying BTM solar penetration levels of 20%, 30%, and 50%, with integrated time-series net-load profiles provided by the utility partner (PGE). The VRN3P model demonstrate <2% hourly MAPE (averaged over the year) for day- ahead net-load forecast on the test scenario with 20% BTM solar. Transfer learning extension of the VRN3P model has demonstrated 8.33× speed-up in training, while still achieving acceptable forecast performance of 2.24% hourly MAPE on the 30% BTM solar penetration test-scenario. A preliminary version of the VRN3P GridAPPS-D™has been developed, along with a web-based interactive user-interface (named ‘Forte’) which has made available on GitHub for public use.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Energy characteristics of multi-chiller load distribution algorithms in a large office building

Here, this study evaluates the energy efficiency of multi-chiller systems in large office buildings, focusing on their optimization across various climate zones as defined by ASHRAE. Using EnergyPlus for simulations, the research examines five different load distribution algorithms in multi-chiller systems that range from one to ten chillers, aiming to understand their effectiveness in 15 distinct climate zones. The primary objectives of the study include identifying the energy efficiency of multi-chiller systems in each climate zone, determining the appropriate number of chillers for each zone, and evaluating the performance of the load distribution algorithms. Based on the U.S. Department of Energy’s commercial building model, the results suggest that multi-chiller systems can significantly reduce cooling energy consumption in various climates. Among the algorithms evaluated, the Sequential Uniform Part Load Ratio (SUPLR) algorithm demonstrates notable efficiency, especially in the 4A climate zone (Baltimore), where it achieves substantial energy savings. Applying the SUPLR algorithm in a multi-chiller setup with four chillers in this zone leads to an estimated 24.5 % reduction in energy usage, equivalent to 183 MW annually. The research indicates that a range of 3 to 5 chillers is typically optimal for most climate zones. In-depth analysis in the 4A climate zone highlights the importance of minimizing operation hours at low Part Load Ratios (PLR) to ensure that chillers operate at a high Coefficient of Performance (COP). This strategy underscores the potential of well-designed multi-chiller systems to reduce cooling energy demand, particularly in climates with transitional seasons. This study provides an overview of the energy-saving potential of multi-chiller systems, applicable across a variety of climatic scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Evaluation of 1/100-Scale Mooring Systems for Wave Energy Converters

This study evaluates the feasibility, accuracy, and limitations of using 1/100th scale physical mooring systems to represent full-scale mooring behavior for wave energy converters (WECs) during small-scale tank testing. The work focuses on an RM3-style point absorber deployed in conditions representative of the PacWave South test site and examines whether small-scale physical testing can reliably inform numerical modeling, design decisions, and future prototype development. Overall, this study concludes that small-scale (1/100th) physical mooring models can provide valuable qualitative insights, including relative comparisons between mooring types and trends in device behavior, but cannot reliably replicate full-scale mooring loads or dynamic response without significant scaling distortion. Physical tests at this scale are most appropriate for motion characterization and model validation within known limitations, not for deriving absolute mooring loads or final engineering design values. Key lessons learned emphasize the importance of improved instrumentation strategies, iterative wave tank tuning, more precisely manufactured scaled mooring components, and enhanced anchoring systems to reduce experimental uncertainty.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Material Control & Accounting Modeling Developments for a Generic TRISO Fuel Fabrication Facility

The Material Protection, Accounting, and Control Technologies (MPACT) program utilizes modeling and simulation to assess Material Control and Accountability (MC&A) concerns for a variety of nuclear facilities. The Sandia National Laboratories (SNL)-developed Fissile Facility Flow Modeler (F3M) and the Material Accountancy Performance Indicator Toolkit (MAPIT) have historically provided MPACT with the capability to analyze MC&A approaches for nuclear facilities to determine that these facilities meet regulatory requirements. In FY25, improvements on the application of the F3M and MAPIT tools to simulate a generic TRi-structural ISOtropic (TRISO) fuel fabrication facility were successfully completed. The generic TRISO fuel fabrication F3M model captures the entire TRISO fuel fabrication process and is adaptable to any final TRISO fuel form, including spherical pebbles and cylindrical compacts loaded into graphite prismatic blocks. Comprehensive F3M/MAPIT functionality for the generic TRISO fuel fabrication model has been demonstrated. This modeling framework can be applied to support the U.S. Department of Energy and domestic nuclear industry stakeholders in developing MC&A approaches for advanced fuel fabrication facilities via statistical tests that demonstrate compliance to regulatory requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

How robust are estimates of key parameters in standard viral dynamic models?

Mathematical models of viral infection have been developed, fitted to data, and provide insight into disease pathogenesis for multiple agents that cause chronic infection, including HIV, hepatitis C, and B virus. However, for agents that cause acute infections or during the acute stage of agents that cause chronic infections, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the initial phase of viral growth, i.e., when pre-symptomatic transmission events occur. Missing data may make estimating the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. However, having extra information, such as the average time to peak viral load, may improve the robustness of the estimation. Here, we evaluated the robustness of estimates of key model parameters when viral load data prior to the viral load peak is missing, when we know the values of some parameters and/or the time from infection to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, particularly pre-peak, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. Viral infectivity and the viral production rate are key parameters affecting the robustness of data fits. Fixing their values to literature values can help estimate the remaining model parameters when pre-peak data is missing or limited. We find a lack of data in the pre-peak growth phase underestimates the time to peak viral load by several days, leading to a shorter predicted growth phase. On the other hand, knowing the time of infection (e.g., from epidemiological data) and fixing it results in good estimates of dynamical parameters even in the absence of early data. While we provide ways to approximate model parameters in the absence of early viral load data, our results also suggest that these data, when available, are needed to estimate model parameters more precisely.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Recrystallization driven softening and heating rate dependencies of FeCrAl nuclear fuel cladding during accident transients

A refined understanding of FeCrAl cladding behavior during rapid transients is critical for its potential deployment in light-water reactors. Current assessments focus on transient burst testing metrics such as balloon geometry, burst temperature, and hoop stress, often used as proxies for simpler conventional tensile properties. However, directly correlating isothermal tensile and creep data with accident transient scenarios remains a challenge, although it is essential for high fidelity model development. Recent modeling based on tensile tests up to 800 °C, conducted with both immediate loading and a 10-minute soak, showed that immediate loading better predicts experimental burst temperatures, indicating a thermal softening effect. Building upon this observation, the current study connects transient performance, microstructural evolution, and high-temperature tensile properties by leveraging results from C26M claddings burst tests performed at heating rates of 1–50 °C/s and hoop stresses from 25 to 100 MPa. At 25 MPa, rupture temperatures varied by only 6 °C, but at 100 MPa, the difference reached 116 °C, with faster heating yielding higher burst temperatures. Microstructural analysis identified recrystallization as the primary cause of heating rate-dependent softening, eliminating prior cold-working. In-situ thermomechanical data linked ballooning onset to localized instabilities, similar to ultimate tensile strength behavior in conventional tensile tests. High heating rates correlated with immediate loading tensile data, while lower rates matched soaked data. Furthermore, by linking burst performance to microstructural evolution and tensile properties, this work provides a foundation for more accurate modeling of FeCrAl claddings and potentially other Fe-based materials under accident conditions.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Co-Design of Charge Transport Superhighways to Connect Catalytic Sites in Soft Photoelectrochemical Systems

Efficient photon-to-electron-to-molecule conversion requires multi-length scale control over charge transport pathways, where electronic charges are delivered to catalytic sites under high mass transport flux. A fundamental question is how can we co-design charge transport pathways to promote efficient charge transfer to/from catalytic sites in complex three-dimensional architectures? Soft conducting polymer systems offer exceptional promise to provide three-dimensional charge transport networks, where electrolyte (ion and solvent) can interdiffuse to promote long-lived charge carriers and the molecular nature allows for strategic synthetic design of catalytic sites. Herein we combine theoretical and experimental approaches to investigate the earliest stages of photoelectrochemical deposition of near-surface catalytic sites (Pt) on soft bulk heterojunction polymeric semiconductors composed of a prototype donor (PTB7-Th) and a prototype acceptor (N2200) as a model system towards better understanding molecular catalyst-polymer site interactions. We focus initially on photoelectrochemical deposition of low Pt loadings, nanoparticle sizes (formed by progressive nucleation) below 20 nm, for both density functional theory (DFT) modeling studies and for spectroscopic characterization using surface-sensitive X-ray and UV-photoemission (XPS/UPS). DFT modeling of “n-type” N2200 slabs reveal for the first time that sulfur atoms in the thiophene units serve as the lowest-energy adsorption sites for single Pt atoms, while larger Pt clusters engage more complexly with both thiophene and naphthalene diimide (NDI) core sites. Changes in chemical composition observed by X-ray photoelectron spectroscopy (XPS) support the DFT predictions, and the angle-resolved measurements reveal that Pt nucleation initiates at subsurface sites which appear to be localized active domains that promote charge transport/transfer and enable vertical growth toward the surface. These results suggest that light-activated Pt nanoparticle deposition decorates energetically distinct sites, where photoactivity is dictated by the local energetics of those sites, and the fact that they represent the termini of charge transport “super-highways” – a small percentage of the total volume of the donor/acceptor polymeric active layer which carries most of the photocurrent generated during both Pt deposition and photoelectrochemical HER. We posit that these initial studies provide a foundational strategy for design of catalytic sites in the near surface regions of complex polymeric materials and advancing soft semiconductor-based photoelectrochemical systems. Achieving a nanometer-scale understanding of catalyst deposition and the impact of local composition and energetics on that placement, should ultimately provide the design guidelines (co-design) for a broad array of catalysts at sites that optimize that efficiency and maximize platform durability.

14 SOLAR ENERGY↗
DOE OSTI2025

Cross-Scale Catalyst Modeling Applied to H 2 Storage and Release via Formic Acid

Here, we propose the Systems-to-Atoms (S2A) modeling framework that integrates the kinetics of reaction chemistry and structural configurations across various length scales with the aim of establishing a versatile template for multiscale modeling of reactive flow problems and to predict the operando activity of catalyst materials. The approach encompasses a microkinetic model to analyze surface reactions on individual facets of catalyst nanoparticles coupled with the computation of average surface reaction rates for catalyst nanoparticles of specific size distributions. Macro-homogeneous surface reaction kinetics are derived as a function of catalyst loading and used as input parameters for the continuum-scale reactor model. The cross-scale framework enables the optimization of catalyst utilization through reactor design and operating strategy. To demonstrate the framework, we studied the storage and release of hydrogen from formic acid, a promising liquid organic hydrogen carrier (LOHC), over Pd, Pt, and Cu catalysts. The framework predicts observed trends in formic acid dehydrogenation activity for catalysts with comparable weight loadings and metal particle diameters, demonstrating satisfactory quantitative alignment. Finally, the seamless transmission of parameter uncertainties between scales is also discussed.

08 HYDROGEN↗