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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancement of Superconductivity in WP via Oxide-Assisted Chemical Vapor Transport

Tungsten monophosphide (WP) has been reported to superconduct below 0.8 K, and theoretical work has predicted an unconventional Cooper pairing mechanism. Here we present data for WP single crystals grown by means of chemical vapor transport (CVT) of WO3, P, and I2. In comparison to synthesis using WP powder as a starting material, this technique results in samples with substantially decreased low-temperature scattering and favors a more three-dimensional morphology. We also find that the resistive superconducting transitions in these samples begin above 1 K. Variation in Tc is often found in strongly correlated superconductors, and its presence in WP could be the result of influence from a competing order and/or a non-s-wave gap.

Chemistry↗
DOE OSTI2026

Controlling homogenization length scales and microstructure in additively manufactured Ti-Ta functionally graded materials

Materials with smooth compositional gradients or functionally grade materials (FGMs) produced via additive manufacturing (AM), enables joining dissimilar materials and optimizing multiple properties in advanced engineering applications. However, as-printed AM microstructures exhibit micro-segregation and solidification defects which, when combined with controlling macroscale gradient properties, complicates necessary post-processing. Here, we use CALPHAD-informed diffusion modelling to design post-processing heat treatments for lightweight to refractory FGMs. Ti-Ta (0 to 85 at. % Ta) FGMs were fabricated using laser-based directed energy deposition AM. Post-processing heat treatments at 1000° C and 1500° C were designed to promote homogenization across specific length scales and experimentally validated. Investigation of chemical segregation and microstructures demonstrated that the length scale of homogenization is controlled as a function of time, temperature, and local composition. Ta-rich regions exhibited incomplete homogenization compared to Ti-rich layers. Unmelted Ta particles were found to completely dissolve at 1500 °C. By controlling cooling rate (200 °C/min), martensitic structures were produced between 14–36 at. % Ta, consistent with martensite-start temperatures calculations, while furnace cooling (2 °C/min) produced α+β morphologies. This work establishes a validated predictive framework for designing post-processing to tailor microstructure and chemical architecture in AM FGMs, facilitating their deployment in demanding environments.

Materials science↗
DOE OSTI2024

Intelligent, grid-friendly, modular extreme fast charging system with solid-state DC protection

The development of electric vehicle (EV) charging infrastructure is crucial for the widespread adoption of electric transportation. However, implementing such infrastructure is a complex task that requires consideration of factors such as space limitations, adherence to industry standards, grid capacity, and other technical and policy issues. This project seeks to create a framework for the efficient design of compact medium voltage (MV) extreme fast charging (XFC) stations for EVs. The station design involves the use of a solid-state transformer (SST) that connects to the MV distribution network, delivering power to a shared DC bus. This innovative approach eliminates the need for a step-down transformer to provide low-voltage service by connecting directly to the MV distribution network. Eliminating the low-frequency transformer not only reduces the system footprint and losses but also eliminates inrush currents during grid black-start. Additionally, placing power electronics directly on the distribution system allows for high-bandwidth filtering and power factor correction. The inclusion of a shared DC bus enables multiple charging dispensers and DC storage/generation units to connect, forming a DC microgrid. This setup facilitates power sharing with minimal conversion stages. The project showcases a DC distribution network protected by intelligent solid-state (SS) DC circuit breakers (DCCB) capable of isolating the smallest section of the faulted circuit much faster than existing mechanical solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A Comparison of Machine Learning Methods of Association Tested on Dense Nodal Arrays

The association of phase picks to form events is one of the fundamental components of seismology. Large and dense sensor networks, such as >1000 geophone arrays (and distributed acoustic sensing), offer unique challenges in association due to the vast numbers of observations and high likelihood of errant picks. In addition, the large number of stations can greatly increase the time it takes to perform the association. For this reason, machine learning (ML) methods might provide a more optimal method of association for such networks. In this work, we examine how well ML methods (e.g., Gaussian mixture model association, PhaseLink, and Graph Earthquake Neural Interpretation Engine) can incorporate dense seismic arrays into regional networks and how well they handle the increasing numbers of stations. Here, we test their capabilities on two dense seismic deployments, one within Rock Valley Nevada (52 nodes and a 9-station sparse local network), and the LArge-n Seismic Survey in Oklahoma dense nodal array (>1800 vertical-component geophones). Processing data from these two different styles of dense seismic deployments allows testing of how the ML algorithms can merge array data with a broader regional network, how they deal with poorly picked phases, and how they handle anthropogenic noise. We compare the ML-associated bulletins to those obtained using the Rapid Earthquake Association and Location algorithm, a more traditional method of association. We find that there are very small differences in results between the methods for small networks (<100 stations) with low pick rates. For large networks (>1000), there are enough errant picks that some of the ML methods start to create false events out of noise. We also find that the ML methods vary in computation time significantly but are all faster than the traditional method tested here.

58 GEOSCIENCES↗
DOE OSTI2026

A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part I: Lagrangian and indirect Euler AMR algorithms

Many applications of physics and engineering involve wide ranges of time and spatial scales. The numerical simulation of localized small scales such as shock waves and material interfaces requires a large number of computational cells in these regions. For these applications, Lagrangian and Arbitrary-Lagrangian-Eulerian (ALE) related methods are engaging since the moving mesh feature naturally brings mesh cells on shock discontinuities and material interfaces are carefully captured. In addition, Adaptive-Mesh-Refinement (AMR) strategies aim to optimize computational resources by concentrating finer mesh cells only in areas of interest while using coarser cells elsewhere. A key but challenging AMR requirement consists in efficiently distributing the computational effort to achieve high accuracy without the prohibitive computational costs associated with uniformly fine grids. Here, in this document, the coupling of the p4est AMR library with a cell-centered Lagrangian scheme is presented with the goal to perform reliable 3D Lagrangian-AMR and indirect Euler-AMR multi-material simulations. In particular, it is shown that starting from a 3D indirect ALE code, the memory management and load balancing requirements can be delegated to an external library (here the p4est library) to unlock ALE-AMR capabilities. First, we present a strategy to transcribe the octant-based connectivity of the 3D AMR framework with that of an unstructured mesh of polygonal cells used in Lagrangian hydrodynamics. Then, we show how refinement and coarsening operations must be adapted to the particular Lagrangian framework to ensure the conservation of volume during those steps. Finally, several numerical test cases are presented that demonstrate the capabilities of the Lagrangian-AMR and indirect Euler-AMR algorithms.

3D cell-centered Lagrangian numerical scheme↗
DOE OSTI2026

PowerAmerica (Final Technical Report)

The U.S. Department of Energy’s Advanced Manufacturing Office (predecessor to AMMTO) established PowerAmerica in December 2014 to develop and accelerate the adoption of wide bandgap (WBG) semiconductor chips and power electronics in manufacturing. The objective was to spark early commercialization of energy efficient products; educate and train the workforce; create high-tech jobs; and nurture the growth of the U.S. WBG semiconductor manufacturing industry. PowerAmerica isled by North Carolina State University by way of a five-year, $140M cooperative agreement with DoE. This private-public partnership with DoE includes member companies ranging from startups and small-medium enterprises to large system integrators, world-class universities, and national labs. The WBG power electronic ecosystem formed by our diverse membership is focused on using advanced manufacturing to 1) lower the cost of silicon carbide and gallium nitride semiconductor devices to be comparable to silicon devices; 2) demonstrate the system benefits and energy efficiency advantages of WBG semiconductor power electronics through system demonstrations that validate their effectiveness; and 3) build an education pipeline for a skilled workforce to meet the future demand for emerging WBG semiconductor markets — and enhance U.S. economic competitiveness globally. PowerAmerica was initially funded in six budget periods, each lasting 12 to 18 months. By the end of Budget Period 6 (August 2023), PowerAmerica had achieved its major objectives in technology development, semiconductor device cost reduction, ecosystem growth and engagement, and education and workforce development. Through strategic foundry investments, we helped to establish the first U.S. SiC foundry (X-FAB) and supported a lab (Microchip) to start SiC volume production. We’ve helped bring together companies from different parts of the supply chain, resulting in several successful new partnerships and business relationships. Through projects with some of the largest manufacturers of energy-intensive equipment in the U.S. — John Deere, GE, United Technologies, Raytheon, Carrier, Toshiba, and others — we have successfully demonstrated the energy and system benefits of WBG technology. We have also harnessed the unique capabilities and facilities of national labs — the Naval Research Laboratory, National Renewable Energy Laboratory, and Argonne National Laboratory — to help solve challenging technical problems for industry. Thanks to our many webinars, tutorials, annual events, and presence at major energy and electronics conferences around the world, the PowerAmerica name has become synonymous with WBG technology advancement. The commercial interest in WBG technology is higher than ever; companies and governments around the world have announced hundreds of millions of dollarsin future investment to build capacity — and compete with silicon in many markets and applications. We have trained hundreds of engineering students, from universities across the U.S., through hands-on projects and WBG coursework. Working professionals have also benefited through the years from our many targeted short courses, tutorials, and technical webinars. In short, PowerAmerica has made great strides in each of our key objectives, and the organization has been operating without government or NC State

14 SOLAR ENERGY↗
DOE OSTI2026

Expanding the genetic toolkit: adenine and cytosine base editors for gene disruption in Aspergillus niger

Despite revolutionizing fungal genetic engineering, conventional CRISPR/Cas9-mediated knockouts rely on DNA double-strand breaks (DSBs), which can cause unwanted insertions and deletions, chromosomal abnormalities, and cytotoxicity. Base editors such as adenine base editors (ABEs), which convert A‧T to G‧C, and cytosine base editors (CBEs), which convert C‧G to T‧A, offer a safer alternative by enabling predictable, target-specific single-nucleotide changes without introducing DSBs. To overcome the limitations of traditional genome editing in filamentous fungi, we developed efficient base-editing systems in Aspergillus niger . For the first time, we constructed an ABE in A. niger , achieving up to 80% editing efficiency and inducing predictable A-to-G mutations at the intended intron sites, disrupting gene function through mRNA mis-splicing. We also developed a highly efficient CBE system, capable of introducing premature stop codons with 50–100% efficiency. To broaden the editing scope, we implemented a Cas9-NG variant recognizing a relaxed PAM sequence requiring only a single guanine (G), enabling editing at start codons and splice sites. Leveraging this expanded scope, we established gene disruption approaches by targeting start codons via ABE-mediated A-to-G conversions (ATG-to-GTG and ATG-to-ACG) and CBE-mediated C-to-T conversion (ATG-to-ATA). Additionally, our base-editing systems enable multiplex gRNA delivery and marker-free editing of multiple genes. Collectively, the scope-expanding strategies increase the number of genes targetable for disruption by base-editing in A. niger by 26.3% and enable near-complete coverage of 96% of the coding genes. Overall, this work demonstrates the potential of ABE and CBE systems as versatile, efficient, and safer alternatives to DSBs-based gene disruption in filamentous fungi.

Aspergillus↗
DOE OSTI2025

A Route to Design Novel Functional Peptides by Applying a Denoising Diffusional Model to mRNA Display Libraries

In vitro directed evolution techniques, such as mRNA display, enable peptide ligand discovery and optimization. However, physical libraries that rely on a genetic code can only search a small fraction of sequence space due to inherent biases in the genetic code and experimental limitations. To address this challenge, denoising diffusion implicit models (DDIMs) are applied to generate novel peptide ligands against B‐cell lymphoma extra‐large (Bcl‐x L ), a key cancer target. Starting with high‐throughput sequencing data from previous selections, a DDIM is trained to produce novel sequences with high affinity binding. Experimental validation confirms that most generated sequences are functionally equivalent to the original library members for Bcl‐x L binding and demonstrated comparable binding kinetics and affinity relative to the wildtype and nearest original neighbors. Importantly, this approach generated rare sequences not easily accessible via mutation and directed evolution. These results indicate that DDIMs can complement and expand directed evolution data, efficiently exploring underrepresented regions of sequence space. This approach provides a broadly applicable framework for accelerating ligand discovery and optimizing molecular properties across diverse targets.

Qi, Pearl [Mork Family Department of Chemical Engi↗
DOE OSTI2026

Enhanced Component Performance Study: Turbine-Driven Pumps 1998-2024

This report presents an enhanced performance evaluation of turbine driven pumps (TDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2024 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The TDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR=1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10 year period while yearly estimates for reliability are provided for the entire study period. No increasing trends were identified for TDPs for the most recent 10 year period.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Evaluating pulse-shaping capabilities of next-generation pulsed power architectures

This project evaluated the pulse shaping capabilities of next-generation pulsed power (NGPP) architectures. NGPP architectures share several common attributes including multiple independent pulse-generation lines, a radial water-insulated impedance transformer, and a central vacuum insulated load region. A multi-module circuit model was developed, incorporating independent pulse-generation lines and a 2-D transmission line mesh of the radial impedance transformer to assess the effects of azimuthal asymmetry in pulse-shaped experiments. Circuit model simulations demonstrated that NGPP architectures are able to produce the the desired current pulse shapes for exemplar NGPP experiments. Additionally, the project explored automated methods for experiment design, including derivative -ree optimization and machine learning. Pulse-shaped experiments require designers to determine machine parameters that reliably produce the desired current pulse at the load, a process that typically relies on expert knowledge and iterative adjustments using the Z circuit model. Given the increased complexity of NGPP systems, this manual approach may be impractical. While the evaluated methods do not eliminate the need for manual iteration, they can reduce the time required for experiment design. Derivative-free optimization automates much of the trial-and-error process, providing a close starting point for manual adjustments or making small modifications to near-final designs. Meanwhile, deep neural network methods can generate a good qualitative match to the desired current pulse in under one second without requiring circuit model simulations.

42 ENGINEERING↗
DOE OSTI2024

12th World Conference on Neutron Radiography Program

This program is for the 12th Annual World Neutron Conference hosted by INL, held in Idaho Falls. Included is the conference schedule, abstracts from presenters, outings, a tour of EBR-1, and facilities at MFC including: TREAT, HFEF, and IMCL. INL researcher abstracts are found on the following pgs: 26, 42, 52, 103, 119, 169, 170, 173, and 182. The 12th World Conference on Neutron Radiography (WCNR-12) is an international forum that brings together researchers, engineers, industry practitioners and university students to promote, discuss and disseminate a wide range of topics in neutron imaging. This weeklong conference focuses on the latest methods, instrumentation and facilities, improvements in data processing and interpretation, and new applications of neutron imaging. Ever-improving neutron imaging instruments and new methods push the frontiers of science and address industrial needs. Many user facilities at large research centers with powerful neutron imaging beamlines address the research needs of an increasingly diverse range of applications. Recent developments in accelerator-based sources could expand the user base for neutron imaging by making compact neutron sources available at facilities beyond large neutron sources at major research centers. Industrial practitioners continue to use neutron imaging for practical industrial applications following industry standards. The World Conference on Neutron Radiography series is organized by the International Society for Neutron Radiography (ISNR) to promote the field of neutron imaging and foster interaction and communication between experts and users in the field (see isnr.de). WCNR-12 continues a series of meetings initiated and started in San Diego, California, in December 1981. In intervals of about four years, the conference moved between the United States, Japan and Europe until the most recent one (WCNR-11) in Sydney, Australia, in 2018 (see previous ISNR proceedings here: https://www.isnr.de/index.php/conferences.)

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

DistOPF: Advanced Solutions for Distribution Optimal Power Flow Analysis - DistOPF v0.2 Documentation

To achieve an affordable and reliable energy system, research on power distribution system is often focused on integration of distributed generators, energy storage solution, EV charging, smart meters, and other advanced assets that may benefit from or require more advanced control and optimization techniques. Despite this focus on advanced distribution system topics, early researchers and grid scientists often start from scratch when developing optimization programs for power distribution systems. This report introduces DistOPF, a Python package that consolidates years of research into a versatile and modular tool. DistOPF provides researchers with essential capabilities to solve distribution system Optimal Power Flow (OPF) problems using standard network models. Additionally, it offers a platform to benchmark both new and existing algorithms against established test systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Atomic view of photosynthetic metabolite permeability pathways and confinement in synthetic carboxysome shells

Carboxysomes are protein microcompartments found in cyanobacteria, whose shell encapsulates rubisco at the heart of carbon fixation in the Calvin cycle. Carboxysomes are thought to locally concentrate CO 2 in the shell interior to improve rubisco efficiency through selective metabolite permeability, creating a concentrated catalytic center. However, permeability coefficients have not previously been determined for these gases, or for Calvin-cycle intermediates such as bicarbonate (HCO$^–_3$), 3-phosphoglycerate, or ribulose-1,5-bisphosphate. Starting from a high-resolution cryogenic electron microscopy structure of a synthetic β-carboxysome shell, we perform unbiased all-atom molecular dynamics to track metabolite permeability across the shell. The synthetic carboxysome shell structure, lacking the bacterial microcompartment trimer proteins and encapsulation peptides, is found to have similar permeability coefficients for multiple metabolites, and is not selectively permeable to HCO$^–_3$ relative to CO 2 . To resolve how these comparable permeabilities can be reconciled with the clear role of the carboxysome in the CO 2 -concentrating mechanism in cyanobacteria, complementary atomic-resolution Brownian Dynamics simulations estimate the mean first passage time for CO 2 assimilation in a crowded model carboxysome. Despite a relatively high CO 2 permeability of approximately 10 -2 cm/s across the carboxysome shell, the shell proteins reflect enough CO 2 back toward rubisco that 2,650 CO 2 molecules can be fixed by rubisco for every 1 CO 2 molecule that escapes under typical conditions. The permeabilities determined from all-atom molecular simulation are key inputs into flux modeling, and the insight gained into carbon fixation can facilitate the engineering of carboxysomes and other bacterial microcompartments for multiple applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hydrodynamic fluctuations near a Hopf bifurcation: Stochastic onset of vortex shedding behind a circular cylinder

Here, we investigate hydrodynamic fluctuations in the flow past a circular cylinder near the critical Reynolds number Re c for the onset of vortex shedding. Starting from the fluctuating Navier-Stokes equations, we perform a perturbation expansion around Re c to derive analytical expressions for the statistics of the fluctuating lift force. Molecular-level simulations using the direct simulation Monte Carlo method support the theoretical predictions of the lift power spectrum and amplitude distribution. Notably, we have been able to collect sufficient statistics at distances Re ⁡/ Re c – 1 = O ⁡(10 –3 ) from the instability that confirm the appearance of non-Gaussian fluctuations, and we observe that they are associated with intermittent vortex shedding. These results emphasize how unavoidable thermal-noise-induced fluctuations become dramatically amplified in the vicinity of oscillatory flow instabilities and that their onset is fundamentally stochastic.

42 ENGINEERING↗
DOE OSTI2026

Design Considerations for Phase Change Material-Incorporated Heat Exchangers in Water Heating

In recent years, the buildings sector has seen major pushes towards decarbonization through innovations that promote deep electrification. 20% of an average household's energy use comes from water heating, and in the US, over half of all households still use gas water heaters. Of those that use electricity for water heating, the majority use resistive elements rather than heat pump water heaters (HPWHs), the latter of which use 60-70% less energy than the former. However, HPWHs tend to have larger dimensions, preventing current 50-80-gallon tanks on the market from fitting into smaller utility closets sized for 30-40 gallons, such as those found in manufactured housing. Additionally, these smaller HPWHs tend to underperform relative to their larger counterparts. One solution that addresses both space and performance concerns is thermal energy storage, and in particular, phase change materials (PCMs). This study outlines the design process used to produce novel PCM heat exchangers for use in small-volume HPWH tanks, including the identification of design constraints and performance targets relevant to real-world applications. To ensure optimal PCM utilization and tank storage capacity, this works seeks to co-maximize surface area and PCM volume; therefore, this research targets triply periodic minimal surface (TPMS) lattices, which boast enhanced heat transfer capabilities compared to traditional heat exchanger geometries. Starting with a suite of TPMS lattices, we demonstrate a systematic approach for narrowing down feasible designs that comply with identified constraints while meeting PCM performance objectives. Our current results indicate that tuning lattice properties can effectively produce geometries that provide enough energy storage to achieve a 50-gallon capacity out of a 40-gallon HPWH, even when placing the PCM heat exchanger inside the tank. Additionally, we demonstrate successful fabrication of lattices with these tuned properties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Estimating Total Methane Emissions from the Denver-Julesburg Basin Using Bottom-Up Approaches

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.

03 NATURAL GAS↗
DOE OSTI2024

Additive manufacturing of multiscale NiFeMn multi-principal element alloys with tailored composition

Nanostructured multi-principal element alloys (MPEAs) have been explored as next-generation engineering materials due to unique mechanical and functional properties which have significant advantages over traditional dilute alloys. However, the practical applications of nanostructured MPEAs are still limited due to the lack of scalable processing approaches to prepare a large quantity of nanostructured MPEAs, as well as lack of an efficient pathway for high-throughput discovery of better functional nanostructured MPEAs within their vast compositional space. Here we tackle these challenges by presenting an integrated approach by combining direct-ink-writing-based additive manufacturing, solid-state sintering, and chemical dealloying to manufacture hierarchically porous MPEAs. The hierarchical structure is comprised of macro- and micro-scale pores introduced via extrusion printing and polymer decomposition during sintering, as well as nanoscale pores formed via chemical dealloying. The macro- and micro-scale pores allow efficient dealloying of a large mass of material as the diffusion length that the corroding medium must penetrate remains at the scale of the ligaments formed after sintering (∼10 μm), despite the large volume of the 3D-printed samples. In addition, this integrated approach enables versatile control of the alloy composition via precisely tuning the ratio of elemental powders in the starting ink, thus offering a pathway for high-throughput discovery of novel functional MPEAs. As a case study, multiscale macro/micro/nanoporous NiFeMn MPEAs with three different compositions were investigated as catalysts to reduce the overpotential of oxygen evolution reaction (OER), where NiFeMn-based electrocatalysts display composition-dependent performance such that the overpotential measured at a current of 0.5 A g −1 for OER increases in the order of Ni 58 Fe 29 Mn 13 ⩽ Ni 64 Fe 26 Mn 10 < Ni 76 Fe 18 Mn 6 . This introduced manufacturing process offers new opportunities for scalable fabrication and rapid screening of nanostructured multi-component complex alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of Biological and Electrochemical Technologies for the Clean Extraction of Copper and Critical Materials from Low Grade Ores

As we transition toward renewable energy resources and electrification, there will be an increasing demand for critical materials, including copper. While copper is currently mined in the US, processing capacity is not sufficient, and intermediate mining products are shipped to Asia for further processing. The goal of this research was to develop a transformative hydrometallurgical process for the production of copper from low-grade ores that would eliminate the need for smelting and would increase the domestic processing capacity in the US, The project initially focused on the electrochemical reduction of copper concentrate using vanadium, followed by the biological oxidation to produce a stream compatible with existing solvent extraction and electrowinning operations. We discovered an efficient electrochemical process that could produce copper salts from concentrate without the need for biological oxidation, and this technology has been licensed and spun-off into a start-up company. The microbes involved in the current state-of-the-art bioleaching processes were genetically modified to introduced a number of new traits, including increased sulfur oxidation, salt-tolerance, and binding of other critical metals such as cobalt, molybdenum, rhenium, and the rare earth elements. The project was extended to also explore the electrochemical oxidation of copper concentrate using cerium which would potentially eliminate production of hydrogen sulfide that occurs with the reductive leaching process. This technology was found to have slower kinetics, however could it still be developed as an alternative process for domestic copper production and has been found to be applicable to other critical minerals.

42 ENGINEERING↗