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DOE OSTI2025

Spin‐State and Clustering Effects in Fe‐Complex Negolytes for Near‐Neutral Aqueous Redox Flow Batteries

Cost-effective redox-active materials are essential for advancing redox flow batteries (RFBs). Iron, with its abundance and suitability as a redox couple, is a promising candidate; however, achieving stable and fast redox reactions in aqueous RFBs remains a challenge. Here, this study presents an Fe-based negolyte stabilized by a hexadentate ligand, where Fe–ligand bonds are enhanced through intermolecular interactions. The sulfonate-substituted Fe complex exhibits a formal potential of −0.44 V versus Ag/AgCl and an exceptionally high rate constant of 0.69 cm s −1 . Near-neutral RFBs incorporating 0.5 M Fe complex show excellent cycling stability, with no discernible capacity fading over 300 cycles. This performance is attributed to intermolecular hydrogen bonds that reinforce Fe–ligand coordination and promote the formation of stable trimeric clusters. Operando electrochemical Raman spectroscopy and density functional theory reveal that π-backdonation from Fe(II) to the imino-phenolate moiety further stabilizes the complex after reduction. In contrast, the hydroxyl-substituted complex exhibits inferior stability due to weaker hydrogen bonding and less pronounced π-backdonation. These findings underscore the importance of ligand design and intermolecular interactions in developing cost-effective, high-performance redox-active materials for aqueous RFBs.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Inverse Compton Cooling in the Coronae of Simulated Black Hole Accretion Flows

Here we present a formulation for a local cooling function to be employed in the diffuse, hot corona region of 3D GRMHD simulations of accreting black holes. This new cooling function calculates the cooling rate due to inverse Compton scattering by considering the relevant microphysics in each cell in the corona and approximating the radiation energy density and Compton temperature thereby integrating over the thermal seed photon flux from the disk surface. The method either assumes the ion and electron temperatures are equal (1T) or calculates them separately (2T) using an instantaneous equilibrium approach predicated on the actual relevant rate equations (Coulomb and Compton). The method is shown to be consistent with a more detailed ray-tracing calculation where the bulk of the cooling occurs, but is substantially less costly to perform. As an example, we apply these methods to a harm3d simulation of a 10M⊙, non-spinning black hole, accreting at nominally 1% the Eddington value. This new approach leads to radiative efficiency values sime65% above Novikov–Thorne, with a larger fraction of total cooling in the corona as compared to simulations performed using the original target-temperature cooling function. Time-averaged post-processing reveals that the continuum spectral observations predicted from these simulations are qualitatively similar to actual X-ray binary data, especially so for the 1T approach, which yields a harder power-law component (Γ = 2.25) compared to the 2T version (Γ = 2.53).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

A Multi-Objective Bayesian Optimized Human Assessed Multi-Target Generated Spectral Recommender System for Rapid Pareto Discoveries of Material Properties

Optimization for different tasks like material characterization, synthesis, and functional properties for desired applications over multi-dimensional control parameter and function spaces need a rapid strategic search through active learning. However, in all cases prior to optimization, the target material properties are assumed known and fixed, which mostly deviates from real-world scenarios in material synthesis. This can be critical for running expensive experiments on new materials, when the experimental results are fuzzy for any scientific outcomes due to improper target setting, ultimately wasting time and cost. The failure rate and cost are even higher over exploring on multi-target space, where we want to learn the pareto among multiple properties, to jointly optimize during material synthesis for desired applications. To address the challenge, here we introduce the human-operator attempt flexibility in the active learning based automated experiment framework, with generating multiple human assessed targets through a voting-based recommender system during real-time microscope measurements over the large material image space, sequentially learn/update multiple desired targets through a weighting system, and adaptively search in multiple material properties functional space for non-dominated pareto discoveries to maximize the custom structural similarity based acquisition function. We term this a multi-objective Bayesian optimized human assessed multi-target generated spectral recommender systems (MOBO-HAM-SRS). The approach has been demonstrated to peizoresponse force spectroscopy of a ferroelectric thin film, exploring with different kernels and acquisition functions. This work shows an advancement towards human-AI collaborated automated experiments, steering optimization trajectories through human overpowering AI at the early stage when uncertainty is high and AI overpowering human at the later stage with rapid exploration towards optimal goal, following human-assessed multiple targets properties.

Biswas, Arpan↗

DOE OSTI2024

Rationalizing Acidic Oxygen Evolution Reaction over IrO 2 : Essential Role of Hydronium Cation

Abstract The development of active, stable, and more affordable electrocatalysts for acidic oxygen evolution reaction (OER) is of great importance for the practical application of electrolyzers and the advancement of renewable energy conversion technologies. Currently, IrO 2 is the only catalyst with high stability and activity, but a high cost. Further optimization of the catalyst is limited by the lack of understanding of catalytic behaviors at the acid‐IrO 2 interface. Here, in strong interaction with the experiment, we develop an explicit model based on grand‐canonical density function theory (GC‐DFT) calculations to describe acidic OER over IrO 2 . Compared to the explicit models reported previously, hydronium cations (H 3 O + ) are introduced at the electrochemical interface in the current model. As a result, a variation in stable IrO 2 surface configuration under the OER operating condition from previously proposed complete *O‐coverage to a mixture coverage of *OH and *O is revealed, which is well supported by in situ Raman measurements. In addition, the accuracy of predicted overpotential is increased in comparison with the experimentally measured. More importantly, an alteration of the potential limiting step from previously identified *O→*OOH to *OH→*O is observed, which opens new opportunities to advance the IrO 2 ‐based catalysts for acidic OER.

Mou, Tianyou↗

DOE OSTI2025

Microstructure‐Dependent Sodium Storage Mechanisms in Hard Carbon Anodes

Sustainable energy storage is essential to support the transition to renewables and meet the increasing demand for energy. Sodium‐ion batteries (NIBs) are attractive for grid‐scale energy storage due to the abundance and low cost of sodium, sustainability of other battery components, and electrochemical performance. Hard carbon (HC) is a leading anode material for NIBs, but its complex microstructure complicates the understanding of sodium storage mechanisms. Using X‐ray total scattering and density functional theory calculations, this study clarifies how HC's microstructural variations influence sodium storage across the slope (high potential) and plateau (low potential) regions of the potential capacity curve. In the slope region, sodium initially adsorbs at high‐binding energy defect sites and subsequently intercalates between graphene layers, adsorbing at low‐binding energy defect sites, correlating with different slopes observed during initial sodiation. Initial irreversibility arises from sodium trapping at surface defects and solid electrolyte interface formation. In the plateau region, sodium simultaneously intercalates and fills pores, influenced by pore size, interlayer spacing, and defect concentration. HCs with larger pore sizes form larger sodium clusters. In conclusion, the proposed mechanism underscores the role of microstructure engineering in enhancing HC performance and advancing NIBs for grid‐scale energy storage.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Electrochemical Reduction Selectivity of Crotonaldehyde on Copper

Lignocellulosic waste is a potential feedstock for the generation of fuels and commodity chemicals, but existing conversion methods are too cost-intensive to be viable long-term solutions. Electrochemical reductions are promising for decentralized biomass valorization due to their modular scaling and capacity to run intermittently and without high temperatures or pressures. Using crotonaldehyde as a multi-functional model compound for the many partially unsaturated oxygenates found in processed biomass, we here demonstrate the production of butanal, butanol, butene, and butane (variously useful as commodity chemicals and major components of liquified petroleum gas) under ambient conditions by reductive bulk electrolysis with a copper mesh working electrode. We identify an optimum potential for reduced organic production under the reaction conditions and compare product distributions from reductions of intermediate species to further propose branching reaction pathways. Though butanal is typically the most abundant product from crotonaldehyde reduction, most of the butene and butane appear to result from a pathway involving initial reduction of the aldehyde group. We discuss evidence that selectivity is driven by interplay between crotonaldehyde reduction, local pH shifts due to the hydrogen evolution reaction, and changes in site reactivity and availability due to electrode fouling. This demonstration of model electrochemical biomass valorization also serves to inform further exploration into reduction of multi-functional molecules and electrochemical biomass processing in general.

biomass↗

DOE OSTI2025

Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems

In this work, the integrated design and dispatch of behind-the-meter or distributed resources (e.g. stationary battery storage and solar PV generation) is considered. A simulation-based framework is employed, generating high-fidelity results with closed-loop predictive control at a fine resolution, at the expense of high computational cost (several minutes to a few hours per design point). To address this challenge, parallel derivative-free design methods are considered. Four methods are compared, including state-of-the-art surrogate-based methods (Radial-Basis Functions and Gaussian processes) and sampling strategies, an evolutionary-based method, and a simple sequential grid refinement method. As a case study, two types of design problem with increasing complexity are considered, namely, the design of behind-the-meter resources (three design variables) and the inclusion of grid capacity (four design variables). The second yields a constrained design problem for which violations can only be determined after solving the computationally expensive simulation. For the three-dimensional case, all methods present a good performance, achieving a solution within 1% of the optimum after the first iteration, with the sequential grid refinement exhibiting the fastest convergence and achieving the best final objective value. This indicates that the parallel evaluation of multiple sampling points may be more important than the choice of method for small decision spaces. For the four-dimensional constrained case, the Genetic Algorithm presents the best tradeoff between performance and computational effort, while the rough objective function terrain generated by constraint violation penalties reduces the performance of surrogate-based methods. Contour plots with flat regions indicate flexibility in the optimal design and highlight the importance of characterizing the solution space.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Inadequacy of current approaches for characterizing membrane transport properties at high salinities

Cost optimal design of osmotic membrane processes requires an accurate estimate of membrane transport parameters across their full operational range. However, standard approaches for estimating these parameters rely on empirical methods, the accuracy of which remains unquantified as a function of temperature, salinity, and measurement error. Herein, we present a systematic accuracy analysis of previously developed methods for estimation of membrane transport properties in reverse osmosis, high-pressure reverse osmosis, forward osmosis, pressure retarded reverse osmosis, and osmotically assisted reverse osmosis. We use a Monte Carlo approach to sample the full range of feasible membrane water permeabilities, salt permeabilities, structural parameters, and operating conditions for these processes. These material and process parameters are then incorporated into a physical transport model for each process. Our analysis shows that the statistical uncertainty of current empirical methods for estimating membrane parameters increases by 5 times from low-salinity to high-salinity conditions. Here, the result of this work demonstrates that empirical methods are inadequate for precisely estimating membrane transport properties at high salinity and highlight a critical need for the development of statistically validated higher accuracy methods.

42 ENGINEERING↗

DOE OSTI2022

Generalized large optics fabrication multiplexing

High precision astronomical optics are manufactured through deterministic computer controlled optical surfacing processes, such as subaperture small tool polishing, magnetorheological finishing, bonnet tool polishing, and ion beam figuring. Due to the small tool size and the corresponding tool influence function, large optics fabrication is a highly time-consuming process. The framework of multiplexed figuring runs for the simultaneous use of two or more tools is presented. This multiplexing process increases the manufacturing efficiency and reduces the overall cost using parallelized subaperture tools.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Potential high-performance magnet materials: Co- and Al-alloyed Sm 2 Fe 17

Sm 2 Fe 17 has long been known as a potential high-performance magnet whose deficiencies—planar anisotropy and lower-than-optimal T c —can be remedied by nitrogen addition, but which presents synthesis difficulties. In this work, we apply first-principles calculations to search for alternative low-cost, high-performance permanent magnets in this family, by exploring simultaneous Fe and Al substitution. Specifically, the goal is to improve properties of Sm 2 Fe 14 Al 3 easy-plane magnet at the stoichiometric composition. Density functional theory calculations were executed for three series of compounds, i.e., Sm 2 (Fe 1-x Co x ) 14 Al 3 , Sm 2 (Fe 1-x Co x ) 15 Al 2 , and Sm 2 (Fe 1-x Cox) 16 Al. We find that substitution of Fe with 12–18 of Co in % Sm 2 Fe 14 Al 3 modifies the magnetic anisotropy type from easy plane to easy axis with a substantial anisotropy of 7.1 MJ/m 3 . We also demonstrate that the largest part of magnetic anisotropy is introduced by 4f Sm atom electrons. Thus the rotation of magnetic moment orientation from $\langle$$1\bar10$$\rangle$ to $\langle$111$\rangle$ is followed by an increase of the occupied 4f state number and, as a result, the orbital part of the magnetic moment of one of the Sm atoms. This increase of the occupied 4f state number at an energy ~ -4.3 eV results in a significant reduction of band structure energy. The substitution of Fe by Co does not significantly reduce the magnetization of the compound and keeps it slightly above 1 T. This combination of magnetic anisotropy and magnetization makes the compound a promising candidate for a permanent magnet.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A Cost-Effective Electro-Hydraulic Actuator Solution with Open Circuit Architecture

With the recent electrification trend in the fluid power area, more research has been incentivized to propose cost-effective and energy-efficient solutions for hydraulic systems. Hence, electro-hydraulic actuator (EHA) architectures receive increasing attention. The paper proposes a novel open-circuit EHA architecture, with the goal to obtain a cost-effective solution for mobile applications while maximizing the overall system efficiency. The proposed EHA is capable of meeting or exceeding traditional off-road machine performance, therefore enabling further electrification of off-road machines. Four-quadrant functionality, covering the full speed range, is achieved by a combination of a variable electro-hydraulic drive and valves with different functions. Focusing on the steady-state performance, the functionality is validated by numerical as well as experimental methods. A simulation model based on the Amesim environment and a dedicated test setup was developed to verify the performance. Furthermore, the good match between simulation and experimental results confirms the potential of the formulation approach of the proposed EHA for applications with different duty cycles and power levels.

4-quadrant functionality↗

DOE OSTI2022

The waterSHED Model: User Guide

The ideal design and operation of small hydropower plants is a complex optimization problem with economic, social, and environmental objectives. The waterSHED (Water Allocation Tool Enabling Rapid Small Hydropower Environmental Design) model is a user-friendly tool that allows hydropower stakeholders to model the trade-offs among these objectives using the Standard Modular Hydropower (SMH) framework. The SMH framework employs modular technologies that can be represented as blackbox objects and combined within a river to create a hydropower facility. For a given site, the waterSHED model aims to determine which modules should be placed in a facility and how those modules should be operated. This user guide describes how to use the graphical user interface and related functionalities. This document also summarizes the background research and mathematical formulations that are explained indepth in the accompanying doctoral dissertation. This model is an early step toward a new hydropower design process that employs standardization and modularity to reduce costs, development timelines, and challenges regarding social and environmental mitigation measures for low-head, small hydropower development. The waterSHED model is a Python application that will require the ability to download a GitHub repository, import the necessary packages, and run a set of Python script files using an integrated development environment. The script produces a graphical user interface to coordinate inputs, simulate operation, and visualize results, so no coding experience is needed once the script is running. Additionally, the waterSHED Workbook is a Microsoft Excel file that works with the Python script to facilitate data entry

13 HYDRO ENERGY↗

DOE OSTI2026

A&L Annual Report: Kapton Strength

Exploding Foil Initiator (EFI) systems function by launching a polymer flyer (often referred to as a slapper) at a high explosive (HE) pellet, which is intended to shock-initiate the HE. Flyer characteristics (e.g., shape, planarity, etc.) are extremely important in this respect, governing their ability to initiate the HE. Polymer models currently used in these systems are largely unvalidated, potentially compromising the integrity of magneto-hydrodynamic (MHD) predictions of EFI function. An improved EFI MHD modelling capability is expected to: (1) expedite optimization of EFI-based initiation system design, (2) enable consideration of EFI-related aging and corresponding lifetime predictions, and (3) potentially minimize the number of costly experiments required to certify EFI designs. To address this knowledge gap, several years ago we began a computational project to develop a higher-fidelity model for Kapton, a Polyimide copolymer most commonly employed as the flyer material in EFI devices.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Hybrid Energy-Powered Electrochemical Direct Ocean Capture Model

Offshore synthetic fuel production and marine carbon dioxide removal can be enabled by direct ocean capture, which extracts carbon dioxide from the ocean that then can be used as a feedstock for fuel production or sequestered underground. To maximize carbon capture, plants require a variety of low-carbon energy sources to operate, such as variable renewable energy. However, the impacts of variable power on direct ocean capture have not yet been thoroughly investigated. To facilitate future deployments, a generalizable model for electrodialysis-based direct ocean capture plants is created to evaluate plant performance and electricity costs under intermittent power availability. This open-source Python-based model captures key aspects of the electrochemistry, ocean chemistry, post-processing, and operation scenarios under various conditions. To incorporate realistic energy supply dynamics and cost estimates, the model is coupled with the National Renewable Energy Laboratory’s H2Integrate tool, which simulates hybrid energy system performance profiles and costs. This integrated framework is designed to provide system-level insights while maintaining computational efficiency and flexibility for scenario exploration. Initial evaluations show similar results to those predicted by the industry, and demonstrate how a given plant could function with variable power in different deployment locations, such as with wind energy off the coast of Texas and with wind and wave energy off the coast of Oregon. The results suggest that electrochemical systems with greater tolerances for power variability and low minimum power requirements may offer operational advantages in variable-energy contexts. However, further research is needed to quantify these benefits and evaluate their implications across different deployment scenarios.

16 TIDAL AND WAVE POWER↗

DOE OSTI2023

Pool-Based Tow System for Testing Tethered Hydrokinetic Devices Being Developed to Harvest Energy From Ocean Currents

Abstract The immense potential for ocean current energy harvesting is being actively explored as the push for renewable energy becomes more urgent. This paper demonstrates a tow testing platform built to examine and validate mathematical models related to the performance of tethered, underwater, hydrokinetic devices in development to harvest energy from ocean currents, and presents experimental results illustrating how such a system can be used. The platform has been modularly designed to allow for the testing of various tethered, underwater energy-generation systems, including kite-based systems, coaxial turbines, and duct sails. Previous research on tethered energy-generating systems has primarily been focused on airborne systems. Additionally, the limited experimental research on tethered, underwater energy-generation systems has relied on a rigid rod for mechanical and electrical connections between the test articles and instrumentation. The tow testing platform presented in this paper accomplishes the mechanical and electrical connection through a dual-function tether, featuring internal conductors and an external sheath to support towing loads. The goal of this platform was to enable the emulation of ocean currents, which are largely unidirectional, and to retrofit a regular pool into a cost-effective, adaptable, small-scale tow tank test bed. The capabilities of the system include two-way communication with tethered devices, multiple towing profiles in order to emulate different flow regimes, real-time control, and differential velocities via dual winch operation.

Engineering↗

DOE OSTI2022

Stout Smearing on a Quantum Computer

Smearing of gauge-field configurations in lattice field theory improves the results of lattice simulations by suppressing high energy modes from correlation functions. In quantum simulations, high kinetic energy eigenstates are introduced when the time evolution operator is approximated such as Trotterization. While improved Trotter product formulae exist to reduce the errors, they have diminishing accuracy returns with respect to resource costs. Therefore having an algorithm that has fewer resources than an improved Trotter formula is desirable. In this work I develop a representation agnostic method for quantum smearing and show that it reduces the coupling to high energy modes in the discrete nonabelian gauge theory $D_4$

Gustafson, Erik J.↗

DOE OSTI2025

Novel Electrowinning Reactor for the Energy-Efficient, Low- Cost Production of Rare Earth Metals

This project developed a novel neodymium (Nd) electrowinning reactor for energy-efficient electrowinning of Nd metal. Throughout this project we have developed an alternative chloride based molten salt electrolysis process. Our process lowers the specific electrical energy consumption compared to the state of the art, while producing reusable chlorine gas and eliminating direct CO2 and PFC emissions. Facilities required for implementing the project were setup and designs were finalized, and a standard operating procedure for safe operation of high temperature electrolysis cells was written. The electrowinning reactor was designed and constructed. Electrolysis experiments confirmed the ability to reproducibly electrowin Nd metal on a Mo cathode. The current efficiency for Nd electrowinning was measured as a function of applied current density in the presence of the separator. Successful electrowinning of Nd sponge at high current densities (200 mA/cm2 and above) at a current efficiency >80% was demonstrated using multiple techniques. Stable Nd electrowinning up to 10h at 250 mA/cm2 was demonstrated. All of these design advancements were used to develop a techno-economic and life cycle assessment model that demonstrated that our process could be operated at cost of less than $0.20/kg-Nd (~30% lower compared to state of the art when comparing electrolysis energy cost) with a >20% total reduction in global warming potential compared to the state of the art while generating no direct CO2 or perfluorocarbon emissions.

42 ENGINEERING↗

DOE OSTI2022

Molecular-based analysis of nanoparticle solvation: Classical density functional approach

Proper statistical mechanics understanding of nanoparticle solvation processes requires an accurate description of the molecular structure of the solvent. Achieving this goal with standard molecular dynamics (MD) simulation methods is challenging due to large length scales. An alternative approach to this problem can be formulated using classical density functional theory (cDFT), where a full configurational description of the positions of all the atoms is replaced by collective atomic site densities in the molecule. Using an example of the negatively charged silica-like system in an aqueous polar environment represented by a two-site water model, we demonstrate here that cDFT can reproduce MD data at a fraction of the computational cost. An important implication of this result is the ability to understand how the solvent molecular features may affect the system’s properties at the macroscopic scale. A concrete example highlighted in this work is the analysis of nanoparticle interactions with sizes of up to 100 nm in diameter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗