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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Effective Lanthanide Diffusivity through U-Zr Metallic Fuel

Fuel-cladding chemical interaction (FCCI) is one of the main concerns for the performance of U-Zr metallic fuels. Although FCCI results in complex phase transformations and morphological changes in both the fuel and cladding sides of the interface, the formation of a brittle layer in the cladding side of the interface (sometimes referred to as wastage) has one of the most significant impacts on the cladding mechanical integrity. This brittle layer is associated with the formation of intermetallic compounds between the cladding constituents Fe, Cr and the lanthanide fission product species. The formation of this cladding wastage layer has been the focus of recent efforts to develop a mechanistic modeling framework, including production of lanthanides in the fuel, transport through the fuel to the fuel-cladding interface, and phase transformation to form intermetallic phases. To calculate the rate of transport of lanthanides through the fuel, a multi-scale computational approach has been used. Atomistic calculations have been performed to determine the diffusivities of Nd, the most prevalent lanthanide species, through the solid fuel matrix and along pore surfaces. These diffusivities have been used as input parameters for a mesoscale model to determine an effective diffusion coefficient that accounts for the formation of porosity, its interconnection, and infiltration with bond sodium from the fuel-cladding gap. The effective diffusivity has been used in engineering-scale simulations using the BISON fuel performance code, and BISON simulations have been compared to representative validation cases from the EBR-II reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

An agent-based approach to study the diffusion rate and the effect of policies on joint placement of photovoltaic panels and green roof under climate change uncertainty

As two of the highest trending green technologies, photovoltaic panels and green roofs are proven to be effective practices for energy generation and energy saving. The achievable impact from the widespread installation of such technologies is, however, not clearly established. This is mainly because the degree of this impact highly depends on the inherently uncertain environmental and climate factors, as well as the unknown adoption rates of these technologies, which in turn depend on different characteristics of decision makers and interactions among them. To that end, this study aims to investigate the diffusion rate of these green technologies under uncertainties caused by climate change, characteristics of adopters, and their interactions. An integrated framework is developed to capture the interplay between financial and attitudinal aspects, as well as the uncertainties due to both the stochastic nature of system parameters and the interactions among agents involving human beings. Specifically, this framework consists of a integer programming model to optimize the green roof and/or photovoltaic panel installation settings for a given building under climate change uncertainty, and an agent-based model to factor in the role of human behavior and interactions. A case study for the city of Knoxville, TN, is presented to evaluate the effects of different policies on the diffusion rate of the green technologies of interest. The results show that the affordability of green technologies and public awareness are the key drivers of the adoption of these technologies, which highlight the important role of the decision makers in impacting the diffusion rate.

14 SOLAR ENERGY↗
DOE OSTI2024

Reduction of vanadium diffusivity within copper grain boundaries due to enhanced binding

We investigate permeation of vanadium (V) through copper (Cu) layers in V/Cu/niobium (Nb) and molybdenum (Mo)/Cu/V tri-layer composites and compare it with the permeation behavior of Nb. Despite their low solubility in single-crystal Cu, both V and Nb permeate readily due to short-circuit transport through Cu grain boundaries (GBs). However, Nb permeates preferentially to V. Atomistic simulations suggest that this difference is due to lower V diffusivity at general GBs in Cu, compared to Nb. Here, the lower V diffusivity, in turn, arises from stronger V binding to the boundary, which manifests as a greater equilibrium GB concentration as well as a higher activation energy for GB diffusion.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Sequential Infiltration Synthesis of Multinary Metal Oxides: The Role of Precursor Diffusion and Reactivity

Understanding volatile metal–organic precursor transport in polymer matrices during sequential infiltration synthesis (SIS) is critical to the design of hybrid materials of tailored composition and uniform structure. Here, we investigate the diffusion and reaction behavior of diethylzinc (DEZ) in poly(methyl methacrylate) (PMMA) matrices with variable indium and zinc incorporation. Unlike conventional SIS where precursors adduct or react directly with the polymer backbone, DEZ shows minimal interaction with PMMA. However, DEZ may interact strongly with In–OH or Zn–OH moieties that are previously incorporated into a PMMA thick film. Using spectroscopic ellipsometry, X-ray photoelectron spectroscopy depth profiling, and EDX line scans, we quantify Zn incorporation as a function of exposure time, polymer thickness, and previous infiltration steps. The Zn distribution evolves from surface-localized to deep within the ∼1 μm thick film with increasing DEZ exposures up to 30 min. A reaction-diffusion model incorporating a hindering factor to capture diffusivity decay due to product accumulation reproduces the Zn depth profile and yields physically meaningful parameters to guide future growth. Furthermore, this study provides a framework for interpreting metal–organic precursor infiltration behavior and highlights the utility of model-guided SIS process design.

diethylzinc↗
DOE OSTI2024

Moisture Performance of Unvented Attics With Vapor Diffusion Ports and Buried Ducts in Hot, Humid Climates

Energy efficiency measures, such as cool roofs, radiant barriers, interior radiative control coatings, and buried ducts are increasing in popularity and are promoted by energy codes because of their energy-saving potential. However, these strategies can also pose moisture risks in attics by lowering surface temperatures and increasing condensation potential and moisture accumulation. Of particular concern in hot-humid climates is dripping condensation on cold air-conditioning ductwork in the summer - commonly referred to as duct "sweating" - which threatens the attic floor with conditions conducive to mold growth and rot. One strategy to mitigate these moisture issues is to wrap ductwork in thicker duct-wrap insulation with an integrated exterior vapor barrier, but thick duct wrap can be difficult to come by, expensive, and unwieldy to work with. This study explores an alternative strategy of reducing moisture issues while embracing energy efficiency by using unvented attics with vapor diffusion ports and buried ductwork in hot-humid climates. Vapor diffusion ports have been studied so far in a wide range of U.S. climates, mostly in the context of conditioned attics. In this study, the strategy is implemented in the novel context of hot-humid climates with ductwork sitting atop blown-in attic floor insulation in unconditioned attics. Using a combination of field experiments and hygrothermal modeling, the findings of this project indicate that an unvented attic with vapor diffusion ports and buried ducts may be a key part of a successful low-cost method for reducing the attic moisture load by venting excess moisture out of the attic, keeping duct-jacket surfaces above dew point temperature, and keeping the roof deck safe from winter moisture accumulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Structural Tuning of Self‐Conductive Polymer as Gas Diffusion Layer for Electrocatalytic Reactions at High Current

Electrocatalytic conversions offer a promising route for sustainable chemical production using renewable energy. Gas diffusion layers (GDLs) enable selective product formation at high current densities but suffer from electrolyte flooding, and polytetrafluoroethylene (PTFE)-based GDLs typically require metal conductive layers, which constrain catalyst development. A recently developed GDL configuration, electropolymerized poly(3,4-ethylenedioxythiophene) (PEDOT)-coated PTFE, demonstrates notable flooding resistance, but suffers from gas diffusion limitations at elevated currents due to limited gas diffusion through the PEDOT layer. Here, different dopants in PEDOT are exploited to modify the physical properties and enhance gas transport. ClO 4 − -doped PEDOT exhibits superior performance due to optimized physical structure, leading to increased gas permeance and faradaic efficiency (FE) for CO production during electrocatalytic CO 2 reduction. Further optimization of coverage and thickness achieved by adjusting charge density led to an optimal configuration at 33 mC cm −2 . This GDL supports various metal electrocatalysts and demonstrates FE CO of > 90% for over 150 h at −200 mA cm −2 using a commercial silver electrocatalyst. This work highlights the importance of GDL engineering in enhancing performance and durability for long-term electrocatalytic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A GPU Accelerated Mixed‐Precision Finite Difference Informed Random Walker (FDiRW) Solver for Strongly Inhomogeneous Diffusion Problems

In nature, many complex multi‐physics coupling problems exhibit significant diffusivity inhomogeneity, where one process occurs several orders of magnitude faster than others temporally. Simulating rapid diffusion alongside slower processes demands intensive computational resources due to the necessity for small time steps. To address these computational challenges, we have developed an efficient numerical solver named Finite Difference informed Random Walker (FDiRW). In this study, we propose a GPU‐accelerated, mixed‐precision configuration for the FDiRW solver to maximize efficiency through GPU multi‐threaded parallel computation and lower precision computation. Numerical evaluation results reveal that the proposed GPU‐accelerated mixed‐precision FDiRW solver can achieve a 117× speedup over the CPU baseline, while an additional 1.75× speedup is achieved by employing lower precision GPU computation. Notably, for large model sizes, the GPU‐accelerated mixed‐precision FDiRW solver demonstrates strong scaling with the number of nodes used in simulation. When simulating radionuclide absorption processes by porous wasteform particles with a medium‐sized model of 192 × 192 × 192, this approach reduces the total computational time to 10 min, enabling the simulation of larger systems with strongly inhomogeneous diffusivity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Grassmannian diffusion maps based surrogate modeling via geometric harmonics

Abstract A novel surrogate model based on the Grassmannian diffusion maps (GDMaps) and utilizing geometric harmonics (GH) is developed for predicting the response of complex physical phenomena. The method utilizes GDMaps to obtain a low‐dimensional representation of the underlying behavior of physical/mathematical systems with respect to uncertain input parameters. Using this representation, GH, an out‐of‐sample extension technique, is employed to create a global map from the input parameter space to a Grassmannian diffusion manifold. GH is further employed to locally map points on the diffusion manifold onto the tangent space of a Grassmann manifold. The exponential map is then used to project the points in the tangent space onto the Grassmann manifold, where reconstruction of the full solution is performed. The performance of the proposed surrogate model is verified with three examples. The first problem is a toy example used to illustrate the technique. In the second example, errors associated with the various mappings are assessed by studying response predictions of the electric potential of a dielectric cylinder in a homogeneous electric field. The last example applies the method for uncertainty prediction in the strain field evolution in a model amorphous material using the shear transformation zone theory of plasticity.

42 ENGINEERING↗
DOE OSTI2022

Manning condensation in ion exchange membranes: A review on ion partitioning and diffusion models

Here, the rational design of ion exchange membranes (IEMs) is becoming more pertinent as their usage becomes broader and as their staple applications (i.e., electrodialysis, flow batteries, and fuel cells) improve in commercial viability. Such efforts would be catalyzed by an improved fundamental understanding of ion transport in IEMs. This review discusses recent progress in modeling ion partitioning and diffusion in IEMs in an effort to relate IEM performance metrics to fundamental membrane properties over which researchers and membrane manufacturers possess direct and sometimes precise control. Central focus is given to the Donnan-Manning model for ion partitioning and the Manning-Meares model for ion diffusion in IEMs. These two frameworks, which are derived from Manning's counter-ion condensation theory for polyelectrolyte solutions, have been widely used within the IEM literature since their recent introduction. To explore this topic, the mathematical derivation of both models is revisited, followed by a survey of experimental and computational discussions of counter-ion condensation in IEMs. Alternative models which fulfill similar roles in predicting IEM transport properties are compared. This review concludes by highlighting the uniquely favorable positions of the Donnan-Manning and Manning-Meares models and discussing their prospects as leading predictors of IEM partitioning and diffusive properties.

25 ENERGY STORAGE↗
DOE OSTI2021

Predicting Fluid Flow Regime, Permeability, and Diffusivity in Mudrocks from Multiscale Pore Characterisation

In geoenergy applications, mudrocks prevent fluids to leak from temporary (H 2 , CH 4 ) or permanent (CO 2 , radioactive waste) storage/disposal sites and serve as a source and reservoir for unconventional oil and gas. Understanding transport properties integrated with dominant fluid flow mechanisms in mudrocks is essential to better predict the performance of mudrocks within these applications. In this study, small-angle neutron scattering (SANS) experiments were conducted on 71 samples from 13 different sets of mudrocks across the globe to capture the pore structure of nearly the full pore size spectrum (2 nm–5 μm). We develop fractal models to predict transport properties (permeability and diffusivity) based on the SANS-derived pore size distributions. The results indicate that transport phenomena in mudrocks are intrinsically pore size-dependent. Depending on hydrostatic pore pressures, transition flow develops in micropores, slip flow in meso- and macropores, and continuum flow in larger macropores. Fluid flow regimes progress towards larger pore sizes during reservoir depletion or smaller pore sizes during fluid storage, so when pressure is decreased or increased, respectively. Capturing the heterogeneity of mudrocks by considering fractal dimension and tortuosity fractal dimension for defined pore size ranges, fractal models integrate apparent permeability with slip flow, Darcy permeability with continuum flow, and gas diffusivity with diffusion flow in the matrix. This new model of pore size-dependent transport and integrated transport properties using fractal models yields a systematic approach that can also inform multiscale multi-physics models to better understand fluid flow and transport phenomena in mudrocks on the reservoir and basin scale.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Performance of fly ash concrete with ferronickel slag fine aggregate against alkali-silica reaction and chloride diffusion

Ferronickel slag (FNS) is an industrial by-product of ferronickel alloy production at a high temperature which can be a promising potential to be used as fine aggregate to produce more sustainable concrete. In this study, the performance of concrete containing ferronickel slag sand and fly ash relating to alkali-silica reaction (ASR) and chloride contamination was investigated. ASR-induced expansion, chloride diffusion resistance, and chloride binding capacity of FNS concrete were determined through concrete prism tests (CPT), accelerated diffusion test, and bulk diffusion test. Thermogravimetric analysis (TGA) was conducted to measure the amount of Portlandite and Friedel's salt in concrete. Concrete with 50 wt% FNS sand as fine natural aggregate replacement and 25 wt% of cement replacement by fly ash showed a remarkable potential to be used not only as a low-carbon concrete with comparable mechanical properties to conventional concrete but also with a better performance against ASR and chloride contamination.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cs retention and diffusion in C-S-H at different Ca/Si ratio

Cement and concrete are commonly used in the construction of repository sites for radioactive wastes. The correct isolation of those contaminants requires good adsorption and low diffusion rates. Both parameters are highly affected by many factors, such as pH, temperature or composition. The large variability of experimental conditions and formulations makes it extraordinarily difficult to tackle the influence of each of them independently in experimental samples. To this effect, molecular dynamics simulations have been employed in this study to investigate the role of the composition in the capacity to retain Cs and diffusivity of these ions in calcium silicate hydrate (C-S-H) gel pores. The results indicate that the adsorption of Cs ions is worsened at high Ca/Si ratios due to a lower interaction of the cations with the C-S-H surface, while hydrophilicity of the C-S-H nanopore rises, resulting in higher long-range ordering and lower diffusion coefficients of Cs ions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A time-dependent chloride diffusion model for predicting initial corrosion time of reinforced concrete with slag addition

The effect of granulated blast furnace slag (GBFS) addition on the threshold chloride concentration (TCC) for rebar corrosion was investigated. A modified diffusion model, coupled with a time-dependent effective diffusion coefficient and surface chloride concentration, was proposed to predict the chloride profile. The corrosion initiation time was estimated based on the model predictions and the measured TCC. The results indicate that adding GBFS decreases the TCC by lowering the pH value of the pore solution. The evolution of corrosion potential and current density is found to obey a 3-parameter Weibull distribution. MIP tests show that adding GBFS contributes to refinement of pore structure by decreasing the fraction of large capillary pores. The time-dependent model exhibits good predictive strength and helps understand how GBFS addition delays the corrosion initiation by retarding the chloride diffusion, though a lower TCC is obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Long carrier diffusion length in two-dimensional lead halide perovskite single crystals

Ruddlesden-Popper (RP) perovskites are two-dimensional semiconductors for high-performance optoelectronic devices. In this work, we report a long in-plane carrier diffusion length in 2D RP perovskite single crystals probed by scanning photocurrent microscopy. Carrier diffusion lengths of 7–14μm are observed when the number of PbI 6 –2 octahedra between organic spacers increases from 1 to 3. Using detailed light intensity and electric-field-dependent photocurrent measurements, we attribute the observed long diffusion length to the dominating dissociated free carrier transport. This is further validated by time-resolved photoluminescence measurements, where the decay lifetime increases in the presence of an electric field. From our experiments, we conclude that the in-plane transport in RP perovskites is efficient because of the partial free carrier generation, which overcomes strong excitonic effects. In conclusion, our results suggest that semiconducting devices fabricated from RP perovskite single crystals can be as efficient as their 3D counterparts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Boron capture stabilizing the diffusion barriers in a two-step Mo-Si-B coated refractory multi-principal element alloy

A Mo-Si-B based coating has been applied on a refractory multi-principal element alloy (RMPEA) using a two-step coating strategy and has endured more than 750 hours of thermal cycling oxidation exposure between room temperature to 1300°C with a minimal weight change. Here, the formation of the Mo 5 SiB 2 diffusion barrier in the coating prevents the inward diffusion of the coating components. Then, boron is captured by the RMPEA, resulting in the formation of a solid solution X 5 SiB 2 (X= W, Mo, Ta, Nb, V) layer and an RMPEA-B boride layer underneath it that acts as the second diffusion barrier.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Conditional distribution estimation of building characteristics with diffusion models for urban energy modeling

Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models, which are used to simulate these energy use patterns, require large datasets with detailed building characteristics for accurate outcomes. However, such detailed characteristics at the individual building level are often unknown and costly to acquire, or unavailable. Through this work, we propose using a generative modeling approach to generate realistic building attributes to fill in the data gaps and finally provide complete characteristics as inputs to energy models. Our model learns complex, building-level patterns from training on a large-scale residential building stock model containing 2.2 million buildings. We employ a tabular diffusion-based framework that is designed to handle heterogeneous (discrete and continuous) features in tabular building data, such as occupancy, floor area, heating, cooling, and other equipment details. We develop a capability for conditional diffusion, enabling the imputation of missing building characteristics conditioned on known attributes. We conduct a comprehensive validation of our conditional diffusion model, firstly by comparing the generated conditional distributions against the underlying data distribution, and secondly, by performing a case study for a Baltimore residential region, showing the practical utility of our approach. Our work is one of the first to demonstrate the potential of generative modeling to accelerate building energy modeling workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Adaptive Interface-PINNs (AdaI-PINNs) for transient diffusion: Applications to forward and inverse problems in heterogeneous media

We model transient diffusion in heterogeneous materials using a novel physics-informed neural networks framework (PINNs) termed Adaptive interface physics-informed neural networks or AdaI-PINNs (Roy et al. arXiv preprint arXiv:2406.04626, 2024). AdaI-PINNs utilize different activation functions with trainable slopes tailored to each material region within the computational domain, allowing for a fully automated and adaptive PINNs approach to model interface problems with strongly and weakly discontinuous solutions. To enhance its performance in highly heterogeneous transient diffusion systems, we prescribe a suite of robust practices, including appropriate non-dimensionalization of equations, a biased sampling method, Glorot initialization, and the hard enforcement of boundary and initial conditions. Here we evaluate the efficacy of the proposed method on several benchmark forward and inverse problems. Comparative studies on one-dimensional and two-dimensional benchmark problems reveal that the modified AdaI-PINNs outperform its unmodified counterpart, achieving root-mean-square errors that are at least two orders of magnitude better in forward problems. For inverse problems, the maximum errors in the approximated diffusion coefficients by modified AdaI-PINNs are four orders of magnitude better than those of the unmodified version. Additionally, modified AdaI-PINNs demonstrate improved stability in problems with large material mismatches.

42 ENGINEERING↗
DOE OSTI2023

Acceleration of Pd-V intermetallic diffusion by hydrogen

Vanadium-based membranes have great potential for hydrogen purification due to their perfect selectivity, high permeability, and relatively low cost. With appropriate surface cleaning, V efficiently permeates hydrogen at elevated temperature, but performance declines due to its affinity to absorb impurities. Here, the application of palladium thin films maintains a clean surface that catalyzes hydrogen dissociation and recombination. Hydrogen permeation in Pd-V-Pd membranes initially reach theoretical permeability, but declines due to Pd-V interdiffusion. The objective of this work was to quantify the intermetallic diffusion process as a function of temperature and ambient. Pd-V composites were subjected to various annealing treatments and characterized using Auger electron spectroscopy, X-ray diffraction, and energy dispersive X-ray spectroscopy, as well as correlated to measurements of membrane permeability. In an inert environment Pd-V interdiffusion was observable as low as 300 °C, and the diffusion coefficient had an activation energy of 44 kJ/mol. Furthermore, the presence of hydrogen at partial pressures > 10 kPa accelerated interdiffusion six-fold at T = 400 °C. Membrane performance degraded with an activation energy 75 kJ/mol, suggesting that intermetallic diffusion leads to both a loss of catalytic activity and as well as degradation of bulk permeability. These findings provide a baseline for evaluating hydrogen permeable interdiffusion barriers to overcome these challenges.

08 HYDROGEN↗