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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Light Water Reactor Sustainability Program Modeling of Cu Precipitate Contributions to Reactor Pressure Vessel Steel Microstructure Evolution and Embrittlement

This report summarizes the lower-length-scale effort during FY 2017 in developing simulation capabilities for the mesoscale: models for microstructure evolution and plasticity in reactor pressure vessel steels. During operation, reactor pressure vessels undergo hardening and embrittlement caused by irradiation induced defect accumulation and irradiation enhanced solute precipitation. Both defect production and solute precipitation initiate on the atomic scale and manifest their eventual effects as degradation in the engineering scale properties. To predict the engineering scale property degradation, multiscale modeling and simulation capabilities are needed to better understand the microstructure evolution and to connect the microstructure feature evolution to the engineering scale material properties. In this report the development of coupling across different length scale models to understand the multi-physics property dedgration problem is discussed. The development of coupling a lattice kinetic Monte Carlo code to cluster dynamics to capture irradiation enhanced diffusion in the formation of defects is summarized. The implementation of a cluster dynamics model with Grizzly to predict Cu percipitate formation is discussed. A summary of the coupling of crystal plasticity and cluster dynamics to predict the effect on reactor pressure steel hardening is given.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Coupling of Spark Plasma Sintering with Advanced Modeling to Enable Process Scale-Up: Presentation to DOE-NE [Slides]

The research goal of this project is to develop at Idaho National Laboratory (INL) a first-of-its-kind Multiphysics Object-Oriented Simulation Environment (MOOSE)-based, multiscale, multiphysics spark plasma sintering (SPS) modeling and simulation code application, termed “Freya.” Freya will simulate the thermo-mechanical-electrical aspects of the SPS fabrication process and will be paired with lower length scale sub-models, such as phase-field, to predict the resulting microstructure. SPS is an advanced manufacturing process that can be used to solve a variety of material manufacturing challenges; however, this process is an extremely challenging problem for modeling and simulation. The SPS process is inherently multiphysics and multi-scale, with the macroscale electro-thermo-mechanical behavior linked intricately to the microstructure evolution of the part being sintered. Accurate modeling and simulation tools, specifically geared towards the SPS process, are needed to predict the influence of the multiple variables involved in the manufacturing process. Modeling and simulation accuracy is achieved and demonstrated through comparison to multiple validation experiments. The validation efforts for Freya include both separate effects and complete multiphysics SPS process experiments. One of the key benefits this Laboratory Directed Research & Development (LDRD) project offers stems from the emphasis placed on experimental validation of the Freya models, both on the individual length scales and of the final coupled multiscale multiphysics simulations. Experimental validation of Freya’s multiscale coupling capability provides the technical credibility necessary for potential future industry and research partners to accept the simulation predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Multiscale Toxicology - Building the Next Generation Tools for Toxicology

A Cooperative Research and Development Agreement (CRADA) was sponsored by Battelle Memorial Institute (Battelle, Columbus), to initiate a collaborative research program across multiple Department of Energy (DOE) National Laboratories aimed at developing a suite of new capabilities for predictive toxicology. Predicting the potential toxicity of emerging classes of engineered nanomaterials was chosen as one of two focusing problems for this program. PNNL’s focus toward this broader goal was to refine and apply experimental and computational tools needed to provide quantitative understanding of nanoparticle dosimetry for in vitro cell culture systems, which is necessary for comparative risk estimates for different nanomaterials or biological systems. Research conducted using lung epithelial and macrophage cell models successfully adapted magnetic particle detection and fluorescent microscopy technologies to quantify uptake of various forms of engineered nanoparticles, and provided experimental constraints and test datasets for benchmark comparison against results obtained using an in vitro computational dosimetry model, termed the ISSD model. The experimental and computational approaches developed were used to demonstrate how cell dosimetry is applied to aid in interpretation of genomic studies of nanoparticle-mediated biological responses in model cell culture systems. The combined experimental and theoretical approach provides a highly quantitative framework for evaluating relationships between biocompatibility of nanoparticles and their physical form in a controlled manner.

Thrall, Brian D.↗
DOE OSTI2015

Sparsity-based acoustic inversion in cross-sectional multiscale optoacoustic imaging

Purpose: With recent advancement in hardware of optoacoustic imaging systems, highly detailed cross-sectional images may be acquired at a single laser shot, thus eliminating motion artifacts. Nonetheless, other sources of artifacts remain due to signal distortion or out-of-plane signals. The purpose of image reconstruction algorithms is to obtain the most accurate images from noisy, distorted projection data. Methods: In this paper, the authors use the model-based approach for acoustic inversion, combined with a sparsity-based inversion procedure. Specifically, a cost function is used that includes the L1 norm of the image in sparse representation and a total variation (TV) term. The optimization problem is solved by a numerically efficient implementation of a nonlinear gradient descent algorithm. TV–L1 model-based inversion is tested in the cross section geometry for numerically generated data as well as for in vivo experimental data from an adult mouse. Results: In all cases, model-based TV–L1 inversion showed a better performance over the conventional Tikhonov regularization, TV inversion, and L1 inversion. In the numerical examples, the images reconstructed with TV–L1 inversion were quantitatively more similar to the originating images. In the experimental examples, TV–L1 inversion yielded sharper images and weaker streak artifact. Conclusions: The results herein show that TV–L1 inversion is capable of improving the quality of highly detailed, multiscale optoacoustic images obtained in vivo using cross-sectional imaging systems. As a result of its high fidelity, model-based TV–L1 inversion may be considered as the new standard for image reconstruction in cross-sectional imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Multiscale real-space quantum-mechanical tight-binding calculations of electronic structure in crystals with defects using perfectly matched layers

Graphical abstract: - Abstract: We consider the scattering of incident plane-wave electrons from a defect in a crystal modeled by the time-harmonic Schrödinger equation. While the defect potential is localized, the far-field potential is periodic, unlike standard free-space scattering problems. Previous work on the Schrödinger equation has been almost entirely in free-space conditions; a few works on crystals have been in one-dimension. We construct absorbing boundary conditions for this problem using perfectly matched layers in a tight-binding formulation. Using the example of a point defect in graphene, we examine the efficiency and convergence of the proposed absorbing boundary condition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Three-wave scattering in magnetized plasmas: From cold fluid to quantized Lagrangian

Large amplitude waves in magnetized plasmas, generated either by external pumps or internal instabilities, can scatter via three-wave interactions. While three-wave scattering is well known in collimated geometry, what happens when waves propagate at angles with one another in magnetized plasmas remains largely unknown, mainly due to the analytical difficulty of this problem. In this study, we overcome this analytical difficulty and find a convenient formula for three-wave coupling coefficient in cold, uniform, magnetized, and collisionless plasmas in the most general geometry. This is achieved by systematically solving the fluid-Maxwell model to second order using a multiscale perturbative expansion. The general formula for the coupling coefficient becomes transparent when we reformulate it as the scattering matrix element of a quantized Lagrangian. Using the quantized Lagrangian, it is possible to bypass the perturbative solution and directly obtain the nonlinear coupling coefficient from the linear response of the plasma. To illustrate how to evaluate the cold coupling coefficient, we give a set of examples where the participating waves are either quasitransverse or quasilongitudinal. In these examples, we determine the angular dependence of three-wave scattering, and demonstrate that backscattering is not necessarily the strongest scattering channel in magnetized plasmas, in contrast to what happens in unmagnetized plasmas. Finally, our approach gives a more complete picture, beyond the simple collimated geometry, of how injected waves can decay in magnetic confinement devices, as well as how lasers can be scattered in magnetized plasma targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Accurate chemical master equation solution using multi-finite buffers

Here, the discrete chemical master equation (dCME) provides a fundamental framework for studying stochasticity in mesoscopic networks. Because of the multiscale nature of many networks where reaction rates have a large disparity, directly solving dCMEs is intractable due to the exploding size of the state space. It is important to truncate the state space effectively with quantified errors, so accurate solutions can be computed. It is also important to know if all major probabilistic peaks have been computed. Here we introduce the accurate CME (ACME) algorithm for obtaining direct solutions to dCMEs. With multifinite buffers for reducing the state space by $O(n!)$, exact steady-state and time-evolving network probability landscapes can be computed. We further describe a theoretical framework of aggregating microstates into a smaller number of macrostates by decomposing a network into independent aggregated birth and death processes and give an a priori method for rapidly determining steady-state truncation errors. The maximal sizes of the finite buffers for a given error tolerance can also be precomputed without costly trial solutions of dCMEs. We show exactly computed probability landscapes of three multiscale networks, namely, a 6-node toggle switch, 11-node phage-lambda epigenetic circuit, and 16-node MAPK cascade network, the latter two with no known solutions. We also show how probabilities of rare events can be computed from first-passage times, another class of unsolved problems challenging for simulation-based techniques due to large separations in time scales. Overall, the ACME method enables accurate and efficient solutions of the dCME for a large class of networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The AQUA-MER databases and aqueous speciation server: A web resource for multiscale modeling of mercury speciation

To assess the chemical reactivity, toxicity, and mobility of pollutants in the environment, knowledge of their species distributions is critical. Because their direct measurement is often infeasible, speciation modeling is widely adopted. Mercury (Hg) is a representative pollutant for which study of its speciation benefits from modeling. However, Hg speciation modeling is often hindered by a lack of reliable thermodynamic constants. Although computational chemistry (e.g., density functional theory [DFT]) can generate these constants, methods for directly coupling DFT and speciation modeling are not available. Here, we combine computational chemistry and continuum-scale modeling with curated online databases to ameliorate the problem of unreliable inputs to Hg speciation modeling. Our AQUA-MER databases and web server (https://aquamer.ornl.gov) provides direct speciation results by combining web-based interfaces to a speciation calculator, databases of thermodynamic constants, and a computational chemistry toolkit to estimate missing constants. Lastly, although Hg is presented as a concrete use case, AQUA-MER can also be readily applied to other elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics

The heterogeneity in mechanical fields introduced by microstructure plays a critical role in the localization of deformation. In order to resolve this incipient stage of failure, it is therefore necessary to incorporate microstructure with sufficient resolution. On the other hand, computational limitations make it infeasible to represent the microstructure in the entire domain at the component scale. Here, the authors demonstrate the use of concurrent multiscale modeling to incorporate explicit, finely resolved microstructure in a critical region while resolving the smoother mechanical fields outside this region with a coarser discretization to limit computational cost. The microstructural physics is modeled with a high-fidelity model that incorporates anisotropic crystal elasticity and rate-dependent crystal plasticity to simulate the behavior of a stainless steel alloy. The component-scale material behavior is treated with a lower fidelity model incorporating isotropic linear elasticity and rate-independent J 2 plasticity. The microstructural and component scale subdomains are modeled concurrently, with coupling via the Schwarz alternating method, which solves boundary-value problems in each subdomain separately and transfers solution information between subdomains via Dirichlet boundary conditions. In this study, the framework is applied to model incipient localization in tensile specimens during necking.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Concurrent two-way coupling of global and local models across internal boundaries with non-matching discretizations

Coupling local and global models enables efficient simulation of multiscale systems, where global models capture large-scale behavior and local models, with enhanced physics, resolve finer details over a smaller region. Here, this paper presents a mathematically consistent method for coupling physics-based models of varying fidelity across adjacent, non-overlapping subdomains, even when discretizations do not match at the immersed interdomain interfaces. Incompressible Navier-Stokes equations (NSE) constitute the global model while residual-based turbulence model serves as the local high-fidelity model. In addition, a scalar advection-diffusion equation that models the convection of an active scalar field is appended to the turbulence model in the local domain. This scalar field does not have its complement in the global model, giving rise to unequal number of equations at the immersed boundary between local and global models. Interdomain coupling terms are derived via the Variational Multiscale Discontinuous Galerkin (VMDG) method with new developments in scale representation and efficient fine-scale estimation. While transient laminar flows modeled with NSE in the global domain can be resolved with relatively coarse mesh, turbulent flow calculations in the local model require much finer spatial discretizations as well as smaller time-step for appropriately resolving the turbulent flow physics. The proposed framework also accommodates non-matching meshes at the immersed boundaries. Test problems in 2D and 3D numerically showcase the concurrent two-way coupling of unknown fields across the immersed boundaries. The 3D test presents a case with an unequal number of equations, where the scalar field represents the convection of contaminant concentration. This provides more detailed physics in the local region and highlights its application in climate modeling and atmospheric sciences.

Variational Multiscale Discontinuous Galerkin (VMD↗
DOE OSTI2014

Ensemble Kalman filters for dynamical systems with unresolved turbulence

Ensemble Kalman filters are developed for turbulent dynamical systems where the forecast model does not resolve all the active scales of motion. Coarse-resolution models are intended to predict the large-scale part of the true dynamics, but observations invariably include contributions from both the resolved large scales and the unresolved small scales. The error due to the contribution of unresolved scales to the observations, called ‘representation’ or ‘representativeness’ error, is often included as part of the observation error, in addition to the raw measurement error, when estimating the large-scale part of the system. It is here shown how stochastic superparameterization (a multiscale method for subgridscale parameterization) can be used to provide estimates of the statistics of the unresolved scales. In addition, a new framework is developed wherein small-scale statistics can be used to estimate both the resolved and unresolved components of the solution. The one-dimensional test problem from dispersive wave turbulence used here is computationally tractable yet is particularly difficult for filtering because of the non-Gaussian extreme event statistics and substantial small scale turbulence: a shallow energy spectrum proportional to k{sup −5/6} (where k is the wavenumber) results in two-thirds of the climatological variance being carried by the unresolved small scales. Because the unresolved scales contain so much energy, filters that ignore the representation error fail utterly to provide meaningful estimates of the system state. Inclusion of a time-independent climatological estimate of the representation error in a standard framework leads to inaccurate estimates of the large-scale part of the signal; accurate estimates of the large scales are only achieved by using stochastic superparameterization to provide evolving, large-scale dependent predictions of the small-scale statistics. Again, because the unresolved scales contain so much energy, even an accurate estimate of the large-scale part of the system does not provide an accurate estimate of the true state. By providing simultaneous estimates of both the large- and small-scale parts of the solution, the new framework is able to provide accurate estimates of the true system state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Coherent structures, intermittent turbulence, and dissipation in high-temperature plasmas

An unsolved problem in plasma turbulence is how energy is dissipated at small scales. Particle collisions are too infrequent in hot plasmas to provide the necessary dissipation. Simulations either treat the fluid scales and impose an ad hoc form of dissipation (e.g., resistivity) or consider dissipation arising from resonant damping of small amplitude disturbances where damping rates are found to be comparable to that predicted from linear theory. Here, we report kinetic simulations that span the macroscopic fluid scales down to the motion of electrons. We find that turbulent cascade leads to generation of coherent structures in the form of current sheets that steepen to electron scales, triggering strong localized heating of the plasma. The dominant heating mechanism is due to parallel electric fields associated with the current sheets, leading to anisotropic electron and ion distributions which can be measured with NASA's upcoming Magnetospheric Multiscale mission. The motion of coherent structures also generates waves that are emitted into the ambient plasma in form of highly oblique compressional and shear Alfven modes. In 3D, modes propagating at other angles can also be generated. This indicates that intermittent plasma turbulence will in general consist of both coherent structures and waves. However, the current sheet heating is found to be locally several orders of magnitude more efficient than wave damping and is sufficient to explain the observed heating rates in the solar wind.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Massively parallel phase-field simulations targeting exascale

The interface thickness in the phase-field (PF) method limits its simulation scales. Consequently, large-scale PF simulations become prohibitively expensive for resolving the extremely fine microstructures that typically form during rapid solidification processing. This challenge is significant in predicting microstructure evolution in metal additive manufacturing and has been identified by the United States Department of Energy’s Exascale Computing Project. Here, to address this, we develop a multi-GPU and MPI-based massively parallel simulation code, utilizing state-of-the-art algorithms, software, and libraries, for large-scale three-dimensional (3D) PF simulations. We report the first GPU-parallel PF simulations on Frontier (currently the second TOP500 exascale cluster) and Summit machines, taking dendritic growth as an example problem. We evaluate the parallel performance of our implementation using scaling studies with more than 24 000 GPUs (among the largest known computations to date) and the acceleration performance using large-scale simulations of dendritic growth in 3D. Finally, massively parallel GPUs in these supercomputers enabled the first coupled multiscale simulations of laser melting and subsequent dendritic solidification on the scale of a full melt-pool, demonstrating the feasibility of performing PF simulations with a point total over 2 billion grid points within an acceptable time.

Exascale↗
DOE OSTI2022

Magnetic reconnection in the era of exascale computing and multiscale experiments

Astrophysical plasmas have the remarkable ability to preserve magnetic topology, which inevitably gives rise to the accumulation of magnetic energy within stressed regions including current sheets. This stored energy is often released explosively through the process of magnetic reconnection, which produces a reconfiguration of the magnetic field, along with high-speed flows, thermal heating and nonthermal particle acceleration. Either collisional or kinetic dissipation mechanisms are required to overcome the topological constraints, both of which have been predicted by theory and validated with in situ spacecraft observations or laboratory experiments. However, major challenges remain in understanding magnetic reconnection in large systems, such as the solar corona, where the collisionality is weak and the kinetic scales are vanishingly small in comparison with macroscopic scales. The plasmoid instability or formation of multiple plasmoids in long, reconnecting current sheets is one possible multiscale solution for bridging this vast range of scales, and new laboratory experiments are poised to study these regimes. In conjunction with these efforts, we anticipate that the coming era of exascale computing, together with the next generation of observational capabilities, will enable new progress on a range of challenging problems, including the energy build-up and onset of reconnection, partially ionized regimes, the influence of magnetic turbulence and particle acceleration.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Final Report for Project "Framework Application for Core-Edge Transport Simulations (FACETS)"

This is the final report for the Colorado State University Component of the FACETS Project. FACETS was focused on the development of a multiphysics, parallel framework application that could provide the capability to enable whole-device fusion reactor modeling and, in the process, the development of the modeling infrastructure and computational understanding needed for ITER. It was intended that FACETS be highly flexible, through the use of modern computational methods, including component technology and object oriented design, to facilitate switching from one model to another for a given aspect of the physics, and making it possible to use simplified models for rapid turnaround or high-fidelity models that will take advantage of the largest supercomputer hardware. FACETS was designed in a heterogeneous parallel context, where different parts of the application can take advantage through parallelism based on task farming, domain decomposition, and/or pipelining as needed and applicable. As with all fusion simulations, an integral part of the FACETS project was treatment of the coupling of different physical processes at different scales interacting closely. A primary example for the FACETS project is the coupling of existing core and edge simulations, with the transport and wall interactions described by reduced models. However, core and edge simulations themselves involve significant coupling of different processes with large scale differences. Numerical treatment of coupling is impacted by a number of factors including, scale differences, form of information transferred between processes, implementation of solvers for different codes, and high performance computing concerns. Operator decomposition involving the computation of the individual processes individually using appropriate simulation codes and then linking/synchronizing the component simulations at regular points in space and time, is the defacto approach to high performance simulation of multiphysics, multiscale systems. Various forms of operator decomposition are used in nearly all fusion simulations. However, operator decomposition generally has a complex effect on accuracy and stability of numerical simulations. Yet, these effects can be difficult to detect. The Colorado State University component of the FACETS team led by P.I.D. Estep was focused on analyzing the effects of operator decomposition on fusion simulations. The approach was based on a posteriori error analysis employing adjoint problems, computable residuals, and variational analysis to produce accurate computational error estimates for quantities of interest. Computable residuals are used to quantify the effects of various discretization choices. The generalized Greens function satisfying the adjoint problem quantities the effects of stability. Technical issues to be addressed included: (1) defining appropriate adjoint operators for operator decomposition discretizations; (2) determining the appropriate residuals for the multifaceted aspects involved with multiphysics discretizations; (3) producing the estimates within the computational framework of existing fusion codes; (4) carrying out the analysis for discretizations used in fusion simulations; and (5) devising efficient approaches to mitigating the effects of discretization. This report provides a summary of the accomplished research and a detailed description of personnel, activities, outcomes and achievements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

MedNAS: Multiscale Training-Free Neural Architecture Search for Medical Image Analysis

Deep neural networks have demonstrated impressive results in medical image analysis, but designing suitable architectures for each specific task is expertise dependent and time consuming. Neural architecture search (NAS) offers an effective means of discovering architectures. It has been highly successful in numerous applications, particularly in natural image classification. Yet, medical images possess unique characteristics, such as small regions and a wide variety of lesion sizes, that differentiate them from natural images. Furthermore, most current NAS methods struggle with high computational costs, especially when dealing with high-resolution image datasets. In this article, we present a novel evolutionary NAS method called multiscale training-free neural architecture search (MSTF-NAS) to address these challenges. Specifically, to accommodate the broad range of lesion region sizes in disease diagnosis, we develop a new reduction cell search space that enables the search algorithm to explicitly identify the optimal scale combination for multiscale feature extraction. Further, to overcome the issue of high computational costs, we utilize training-free indicators as performance measures for candidate architectures, which allows us to search for the optimal architecture more efficiently. More specifically, by considering the capability and simplicity of various networks, we formulate a multiobjective optimization problem that involves two training-free indicators and model complexity for candidate architectures. Extensive experiments on a large medical image benchmark and a publicly available breast cancer detection dataset are conducted. The empirical results demonstrate that our MSTF-NAS outperforms both human-designed architectures and current state-of-the-art NAS algorithms on both datasets, indicating the effectiveness of our proposed method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

A multiresolution spatial parametrization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions.

The estimation of fossil-fuel CO2 emissions (ffCO2) from limited ground-based and satellite measurements of CO2 concentrations will form a key component of the monitoring of treaties aimed at the abatement of greenhouse gas emissions. To that end, we construct a multiresolution spatial parametrization for fossil-fuel CO2 emissions (ffCO2), to be used in atmospheric inversions. Such a parametrization does not currently exist. The parametrization uses wavelets to accurately capture the multiscale, nonstationary nature of ffCO2 emissions and employs proxies of human habitation, e.g., images of lights at night and maps of built-up areas to reduce the dimensionality of the multiresolution parametrization. The parametrization is used in a synthetic data inversion to test its suitability for use in atmospheric inverse problem. This linear inverse problem is predicated on observations of ffCO2 concentrations collected at measurement towers. We adapt a convex optimization technique, commonly used in the reconstruction of compressively sensed images, to perform sparse reconstruction of the time-variant ffCO2 emission field. We also borrow concepts from compressive sensing to impose boundary conditions i.e., to limit ffCO2 emissions within an irregularly shaped region (the United States, in our case). We find that the optimization algorithm performs a data-driven sparsification of the spatial parametrization and retains only of those wavelets whose weights could be estimated from the observations. Further, our method for the imposition of boundary conditions leads to a 10 computational saving over conventional means of doing so. We conclude with a discussion of the accuracy of the estimated emissions and the suitability of the spatial parametrization for use in inverse problems with a significant degree of regularization.

Ray, Jaideep↗
DOE OSTI2023

Electrodeposited nickel coatings for exceptional corrosion mitigation in industrial grade molten chloride salts for concentrating solar power

Molten chloride salt eutectics are attractive candidates for use as thermal energy storage media and heat transfer fluids in generation-three concentrating solar thermal power (Gen3 CSP) plants. However, corrosion of alloys in molten chloride salts, especially at high temperatures, is an extremely challenging problem that studies focus on lower temperatures, shorter durations, or analytical grade, and high-purity, salts. To date, there has been no study on corrosion or corrosion mitigation in an industrial-grade salt at a high temperature such as 750 °C. To alleviate this knowledge gap, the study presents new multiscale fractal-textured Ni coatings on various alloy surfaces for effective corrosion mitigation at 750 °C in molten chloride salts. Using the electrodeposition method, durable double-layer textured coatings were formed on stainless steel alloys (SS316, SS310, and SS347) and In800H. The corrosion performance of the coatings is investigated in both analytical-grade purity and, for the first time, practically relevant industrial-grade chloride salts. Ni-coated ferrous alloys showed an exceptionally reduced corrosion rate in the range of 350–480 μm/y in analytical-grade salts, and between 450 and 490 μm/y in purified industrial-grade salts at 750 °C. Ni coatings on ferrous alloys reduced corrosion rates by as much as 70% compared to uncoated surfaces and were comparable to the expensive Ha230 alloy with a high Ni content. As a result, by the use of innovative fractal corrosion mitigation coatings, for the first time, low-cost structural alloys are rendered viable for use with industrial-grade chloride salts, which is profoundly beneficial in practical systems.

14 SOLAR ENERGY↗