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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 595 records · Page 33

Machine-Learned Force Field for Molecular Dynamics Simulations of Nonequilibrium Ammonia Synthesis on Iron Catalysts

Ammonia (NH 3 ) is one of the most important industrial chemicals. The conventional NH 3 synthesis method-the Haber–Bosch process-converts atmospheric nitrogen (N 2 ) into NH 3 using H 2 with an iron (Fe) catalyst. However, this process requires high pressures (100–200 atm) and temperatures (700–800 K) near thermal equilibrium. Recently, Fe-based nanocatalysts have been reported to produce promising NH 3 yields under atmospheric pressures and temperature-modulated nonequilibrium conditions. Understanding the mechanism of nonequilibrium catalysis with programmed temperature variation could help to optimize this fully electrified and less energy-intensive process. Although reactive molecular dynamics (RMD) simulations can be a useful tool to model nonequilibrium catalytic processes, they require the development of accurate force fields (i.e., interatomic potentials). Here, we present a machine-learned (ML) force field within the Deep Potential MD (DPMD) framework, trained using periodic density functional theory (DFT) calculations, to model NH 3 synthesis on Fe catalysts with various surface adsorbates such as *N, *H, *N 2 , *H 2 , *NH, *NH 2 , and *NH 3 . Here, we generated the DFT data from static models of elementary reactions on the most stable (110) surface of body-centered cubic Fe, which then were augmented by data from constant number of particles–volume–temperature (NVT) DFT-MD trajectories at various temperatures. Finally, we utilized the fully optimized ML force field to investigate reaction dynamics at an Fe(110) surface at linearly increasing temperatures using NVT-DPMD simulations. Our simulations indicate that pulsed temperature ramping could prove favorable for NH3 synthesis. For example, we conducted ramping under multiple sets of conditions: (i) from 900 to 1200 K over periods of 0.1–0.3 ns for Fe surfaces precovered with N or NH along with H; and (ii) from 300 to 600 K over 0.1–0.3 ns for Fe surfaces precovered with NH 3 . While our simulations so far are limited to short time scales (very rapid heating), these observations shed light on the mechanism of the high NH 3 synthesis rate achieved in a novel temperature-modulated nonequilibrium catalytic reactor using pulsed heating and cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Performance Portable, Fully Implicit Landau Collision Operator with Batched Linear Solvers

Modern accelerators use hierarchical parallel programming models that enable massive multithreading within a processing element (PE), with multiple PEs per device driven by traditional processes. Batching is a technique for exposing PE-level parallelism in algorithms that have traditionally run on MPI processes or multiple threads within a single process. Opportunities for batching arise in, for example, kinetic discretizations of magnetized plasmas where collisions are advanced in velocity space at each spatial point independently. This paper builds on previous work on a high-performance, fully nonlinear, Landau collision operator by batching the linear solver, as well as batching the spatial point problems and adding new support for multiple grids for multiscale, multispecies problems. An anisotropic relaxation verification test that agrees well with previously published results and analytical models is presented. The performance results from NVIDIA A100 and AMD MI250X nodes are presented with hardware utilization analysis for each architecture. Finally, the entire implicit Landau operator time advance is implemented in Kokkos for performance portability, running entirely on the device and is available in the PETSc numerical library.

97 MATHEMATICS AND COMPUTING↗

Business Case Analysis for Artificial Intelligence-Large Language Model Technology Integration

AI-assisted processes are expected to enhance operational efficiency and improve decision-making, supporting the long-term economic viability of nuclear power plants. However, detailed business analyses of AI-generated cost savings are rarely performed. Given the recent industry interest in Large Language Model (LLM), the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program has conducted a comprehensive business case analysis of LLM Artificial Intelligence (AI) implementation in nuclear plant engineering workflows. The research employed three complementary business case approaches to evaluate impact of an LLM, using three representative engineering processes as use-cases: Boric Acid Corrosion (BAC) Evaluations, Maintenance Rule Evaluations, and 10 CFR 50.59 Screenings. Through detailed workload analyses and structured interviews, the study quantified significant efficiency improvements ranging from 11% to 59% across these processes. The research further considers how these efficiency gains could translate into tangible reliability improvements through enhanced engineering capacity. Analysis of historical plant trip data indicates that enabling engineers to focus on proactive reliability activities could provide substantial financial benefits through avoided outages, potentially generating greater value than the direct efficiency improvements alone. By documenting successful applications, implementation challenges, and strategic opportunities, this research provides nuclear utilities with a practical framework for evaluating the value of AI technology to support long-term operations through advanced digital technologies.

97 MATHEMATICS AND COMPUTING↗

Fuel Salt Synthesis for the Molten Chloride Reactor Experiment: Scale-up, Operations, and Production Update

Over the previous 5 years, Idaho National Laboratory (INL) has been working with Southern Co. and TerraPower on the Advanced Reactor Demonstration Program (ARDP) funded Molten Chloride Reactor Experiment (MCRE) project. As part of this effort, INL has developed a fuel synthesis process to produce the NaCl-UCl3 fuel salt that MCRE will need for operation. Dr. Phillips will present on process development and scale-up testing and results, as well as provide an update on the current status of fuel production for MCRE. To date, the fuel synthesis process has been demonstrated at full scale using depleted uranium, and the equipment necessary for production of the fuel for MCRE has been installed in the Fuel Manufacturing Facility (FMF) at the INL’s Materials and Fuels Complex (MFC). The NaCl-UCl3 produced to-date has been shown to be of 99.99% purity or greater, and be within tolerance for all relevant parameters. Overall process efficiency in terms of uranium utilization has been demonstrated to be above 90%. The synthesis operation has also been shortened to allow for completion of the reaction within a single 10 hour working shift. Consequently, the process developed is expected to be capable of meeting all project objectives for efficiency, purity, scale, and scheduling. Production of NaCl-UCl3 fuel salt for MCRE is projected to begin during the Summer of 2025.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Temperature effects on Thermal Neutron Scattering in Beryllium Metal

Many advanced reactor concepts being considered are characterized by a thermal neutron energy spectrum, which traditional light water reactor systems utilized. Beryllium metal, a material with a long-standing operational history in reactor environments, continues to be of significant interest due to its large scattering cross section, low absorption cross section, and well-characterized behavior under irradiation conditions.

GASKET↗

Radioisotope Power System Cask Trailer Chiller Low Heat Load Study

This report documents the study of the Radioisotope Thermoelectric Generator Transport System (RTGTS) chillers capability to transport a Radioisotope Power System (RPS) with low heat loads in the cask. Tests of the RTGTS chillers included setting the glycol/water (coolant) temperature to a control set point of 40° and 60°F while applying heat loads ranging from 2500 to 0 W heat load. The tests performed showed that the chiller systems could handle the entire range of heat loads. However, a noise/vibration started to occur when the set point was 60°F with low heat loads. Three recommended changes to the RTGTS chillers are recommended with varying implementation windows. The first is an operational change that can be implemented immediately. The RTGTS chillers should have a set point of 40°F when transporting an RPS less than 1500 W. The second is a short-term change (within the next two years) augmenting RPS heat by utilizing one RTGTS onboard heater (2500 W) while transporting an RPS with less than 1500 W which will also require a change to the Instrument and Data Acquisition System (IDAS) to allow monitoring and possible control of power to the onboard heaters. However, if the heater does fail during transport, no emergency actions or immediate repairs will be required due to the chillers’ ability to handle low heat loads. Running a 2500 W heater when transporting low heat loads aids in prolonging the life of the chillers. The remaining recommended long-term change is to replace the current chillers with a new portable or permanently installed chiller system in the next five to ten years. This time frame takes advantage of the proven reliability and durability of the current chillers while the new chillers are phased in and proven to the RPS program.

42 ENGINEERING↗

DOE Zero Energy Ready Manufactured Housing: Subject Matter Expert Technical Assistance Summary

Manufactured homes offer American consumers an affordable option for decent single-family detached housing. For working-class American families in many U.S. markets, manufactured homes are the first step toward home ownership. They now make up 10% of all new homes constructed in the United States, with higher percentages in the south and in rural communities. To help encourage the production of homes that are more durable, healthy, efficient, and disaster resistant, the U.S. Department of Energy is bringing its building science research to the manufactured housing industry through DOE’s Zero Energy Ready Manufactured Home (ZER-MH) program, which provides technical assistance and voluntary guidelines to manufactured home builders. Homes built to these guidelines are better able to handle power outages and less likely to experience moisture issues, offering a better product option for American families. This higher quality is evidenced by energy modeling which shows homes manufactured to these voluntary guidelines will typically use half the energy of manufactured homes built to the current minimum requirements of the U.S. Department of Housing and Urban Development (HUD)’s Manufactured Housing and Construction Safety Standard (MHCSS). These homes can also reduce critical energy demand during the busiest hours of the day, typically late afternoon and early evening in the summer when air conditioning demand is highest and mornings in the winter when furnaces and heaters are heating up. Reducing electricity demand during these peak periods when electricity rates are at their highest reduces costs for American families while freeing up capacity on overburdened energy distribution networks. Builders participating in the DOE ZER-MH program are eligible for a tax incentive via the 45L tax credit, which helps to offset the costs of ZER-MH upgrades, enabling builders to offer these certified homes at no additional cost. Together these factors enable manufactured homes to offer home buyers a housing option that is both affordable to finance and affordable to operate, with lower monthly mortgage payments and lower monthly energy bills.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

PACT Center: Perovskite PV Accelerator for Commercializing Technologies (Final Technical Report)

The Perovskite PV Accelerator for Commercializing Technologies (PACT) center was established in July 2021 as a national resource to accelerate the commercialization of perovskite photovoltaic (PV) technology in the United States. Since its inception, PACT has been led by Sandia National Laboratories (Sandia) in partnership with the National Laboratory of the Rockies (NLR), formerly known as NREL. From FY20-FY23, Los Alamos National Laboratory (LANL), CFV Labs, Black & Veatch (B&V), and the Electric Power Research Institute (EPRI) were part of the project team. LANL brought expertise in perovskite PV device designs and processing, CFV Labs (now GroundWork Renewables) provided initial indoor and outdoor measurement hardware technology, B&V led the initial effort on perovskite PV bankability, and EPRI worked on reviewing testing standards, identifying commercialization gaps, and helping to run PACT’s Industry Advisory Board, a group including representatives from commercial testing labs, independent engineering firms, insurance companies, state regulators, and electric utilities. To source perovskite PV module samples, PACT contracted with the University of North Carolina (UNC), the University of Toledo, the University of Washington, and SLAC/Stanford University to provide a steady stream of research-grade perovskite mini modules, enabling protocol development in advance of commercial module availability. The project period ran from July 1, 2021, through December 31, 2025, including a No Cost Extension. Starting in FY25, the project was continued as a Core Capability in the Lab Call portfolio and continues at a reduced budget with only Sandia and NLR as funded recipients. Notably, starting in FY25 PACT expanded its scope beyond MHP modules to accept all emerging PV mini module technologies for testing, including organic PV (OPV) and all-thin-film tandems, with the aim of supporting commercialization across the broader emerging PV ecosystem. With this change in scope the program was renamed the PV Accelerator for Commercializing Technologies, dropping perovskite from the name.

14 SOLAR ENERGY↗

A Measurement of the Pion-Energy Dependence of Muon Neutrino Charged-Current Scattering to Final States With One Charged Pion in NOvA

The study of neutrino oscillations is a main priority for particle physics as the most immediately tractable lever on physics beyond the Standard Model. In particular, more insight into violation of the combined symmetry of charge-conjugation plus parity could yield clues to the origin of matter-antimatter asymmetry, and in some theoretical frameworks the neutrino mass could give insights into dark matter. NOvA is a long-baseline accelerator neutrino experiment with both a near and far detector that seeks to measure several of the parameters of the neutrino mixing matrix, as well as carry out a broad program of additional physics. NOvA has innovated and developed a variety of techniques in the space of neutrino physics, including expanding the use of machine learning techniques in reconstruction. NOvA has also set the stage for the next generation US-based long baseline experiment, DUNE. This dissertation details the creation of a new neutrino interaction vertex reconstruction package for NOvA, which offers enormous improvements in accuracy above the previous vertexer it replaces. This is accomplished using a Convolutional Visual Network trained on large datasets of simulated events. The vertexer is validated thoroughly against data. This dissertation also presents a cross-section measurement for $\nu_\mu + N \rightarrow \mu^- + 1\pi^\pm + X$ (where X does not include additional charged pions) binned in pion kinetic energy, a challenging measurement in general and for NOvA in particular. Measurements like this provide crucial inputs for neutrino interaction models utilized by neutrino oscillation experiments. This measurement in particular is important to the energy ranges relevant for DUNE in a band not well-covered by any other experiment.

Ewart, Erin [Indiana U., Bloomington (main)]↗

Emigration and Survival of Hatchery‐Reared Coho Salmon Released as Parr and Smolts in a Reintroduction Program

ABSTRACT Releasing fish at varied life stages is an underutilized hatchery‐rearing practice. Columbia River Treaty tribes have been working to reintroduce extirpated Coho Salmon to historical habitats in upper watersheds. This effort has included the release of hatchery‐origin fish at both the parr and smolt life stages in the Yakima River Basin (Washington State USA), a tributary to the Columbia River. We evaluated releases of parr and smolts tagged with passive integrated transponders over 11 brood years. We assessed emigration timing, fish survival, and age‐at‐return for the two release groups. Emigrating juveniles released as smolts had higher survival and arrived downstream earlier than fish released as parr. Survival from release locations to adult return did not significantly differ for the two release groups. However, we observed a difference in apparent marine survival as fish released as parr had mean juvenile‐to‐adult return rates greater than fish released as smolts. Parr releases also tended to return at older age than smolt releases. Our results indicate that implementing practices to reduce homogenization of hatchery releases may produce survival and diversity benefits as fish mature to later life stages. Given the rapid ecosystem changes Pacific Salmon are experiencing throughout their life cycles, practices such as this may have increasing utility and import.

Bosch, William J. [Yakama Nation Fisheries Toppeni↗

Cardinal: Seismic and Geoacoustic Array Processing

Data collected via seismic and infrasound array deployments are leveraged in the geosciences to detect and characterize a myriad of natural and anthropogenic sources. These deployments consist of numerous sensors placed in a predetermined configuration to amplify signal strength and improve the efficacy of array processing techniques used to measure signal directionality and waveform coherence. High‐fidelity feature extraction is often predicated on interstation distance as well as the frequency content and wavelength of an incident signal. Numerous array processing softwares analyze data in sequential frequency bands to obtain a more detailed characterization of a signal. However, current algorithms are limited in their ability to determine optimal array configuration for each band. We introduce an open‐source Python code, called Cardinal, to process seismic and infrasound array data in discretized time–frequency space with the option of applying an adaptive array design to determine optimal subarray configuration for each frequency band. To reduce computational time, the array processing step can be run in parallel using multithreading. Furthermore, the software has the capability to aggregate array processing results from different time–frequency pixels to produce separate sets of detections, or families, with added utility via the application of an adaptive semblance threshold, which aids in isolating signals‐of‐interest from coherent background noise. Upon appropriate configuration, Cardinal exhibits the potential to combine distinct seismic and infrasound phases into separate families.

Adaptive Array↗

Winnett Public School District Energy Improvements

The Winnett Public School District Energy Improvement Project was funded through the U.S. Department of Energy's Renew America's Schools Program, which supports rural and underserved school districts in upgrading aging facilities and improving energy performance. The completed improvements directly advance the program's objectives by replacing the District's outdated coal-fired heating system with a modern, high-efficiency propane boiler system, while also enhancing ventilation systems and building envelope performance throughout the school. These upgrades provide a more reliable heating system and improved indoor air quality, creating a healthier and more comfortable environment for students and staff. In addition, replacing the aging boiler system has reduced long-term maintenance demands for one of Montana's most rural school districts, allowing the District to redirect limited financial resources toward other critical needs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

State of Innovation 2025: Progress in Accelerating Next-Generation Cement and Concrete Technologies

The cement and concrete sectors are entering a decisive period as next-generation technologies advance from laboratory research to demonstration, early deployment, and first-of-a-kind commercial plants. Building on the 2024 State of Innovation report, the 2025 outlook highlights both the rapid acceleration of innovation and the urgent need for coordinated action across the value chain. Venture capital activity into the cement and concrete space stabilized following the record surge of 2022-2023, yet landmark financings, such as Sublime Systems' $200 million round and Terra CO2's $124 million Series B, signal continued investor confidence in companies approaching commercialization. Corporate procurement has become a powerful new catalyst, with Microsoft, Amazon, and CRH (Cement Roadstone Holdings) Ventures providing long-term commitments that underpin the first wave of next-generation cementitious products. The sector is shifting from early-stage experimentation toward the scaling of well-capitalized leaders capable of bridging the critical "capitalization gap." Early innovators continue to expand the toolkit through novel binders, electrochemical cements, biogenic limestone, and carbonate mineralization pathways. Going into 2026, cost competitiveness, durability validation, and scalability enabled by resilient supply chains remain the decisive factors for market adoption. At the 2025 Next Generation Cement and Concrete Critical Technologies Meeting, attendees emphasized dual-track funding strategies that integrate federal grants with private capital as key to enabling market breakthrough. State programs and corporate demand are sustaining momentum, while successful companies increasingly demonstrate both economic value and reduced dependence on imported materials. The National Concrete Pavement Technology Center and others underscored that broad integration of next-generation materials will hinge on standards compatibility, verified field performance, and workforce readiness. Colorado continues to serve as a proving ground through pilot programs that combine supplier training, phased implementation, and real-world data to de-risk innovation and provide replicable models for other regions. The 2025 Cement and Concrete Critical Technologies Workshop reinforced that scaling next-generation materials will require alignment among technology innovation, performance validation, and market demand. Stakeholders must move beyond siloed efforts toward collaborative frameworks that coordinate standards, funding, and infrastructure deployment. As a neutral convener and technical validator, the National Laboratory of the Rockies (NLR) plays a pivotal role in bridging innovation and market adoption through collaborative research, technology validation, and entrepreneurship programs. By uniting innovators, incumbents, policymakers, contractors, and investors, NLR and its partners are helping chart a credible pathway toward widespread commercialization in the decade ahead.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Comparison of GPU-Accelerated Multiphase CFD Solvers on the Polaris Supercomputer: Part 1

This report is in support of the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program sponsored by the U.S. Department of Energy (USDOE). With INCITE-level resources, one project, titled BubblyFlow, was granted computational resources for the 2025 calendar year on the Polaris supercomputer at the Argonne Leadership Computing Facility (ALCF). The project aims to conduct simulations to understand the fundamental characteristics of turbulent bubbly flow phenomena in nature. Staff at the ALCF and Argonne’s Computational Science division, along with collaborators at the City College of New York and University of Illinois at Chicago, helped a summer student to assess the accuracy and performance of two high performance computing (HPC) codes. Both codes, ImExLBM and FluTAS, are fundamentally different in their mathematical and numerical modeling. However, both may be used to solve the same physical problem. The collaboration sought to better understand the differences between both codes in terms of accuracy and efficiency. This would ultimately help the BubblyFlow project better utilize resources and establish a knowledge-base of code capabilities in future simulation campaigns. We compare ImExLBM and FluTAS, two high-performance multiphase computational fluid dynamics (CFD) solvers, in terms of physical fidelity, time-to-solution, and parallel efficiency. We validate ImExLBM (Implicit-Explicit Lattice Boltzmann Method) against a canonical benchmark and assess it’s performance relative to FluTAS (Fluid Transport Accelerated Solver), a well-established open-source CFD code.

97 MATHEMATICS AND COMPUTING↗

Optimizing Power Line Undergrounding Decisions under Varying Wildfire Risk and Weather Scenarios

Abstract—The threat of wildfire ignitions from electric power equipment has led utilities to increasingly turn to preemptive power shutoffs, which, while effective in reducing grid-induced wildfire risk, can cause significant load loss. Undergrounding power lines is an alternative strategy for preventing grid-induced wildfires. However, undergrounding lines is costly, so an efficient undergrounding plan must balance reductions in wildfire risk and load loss with the cost of undergrounding lines. We propose a robust optimization model to identify which power lines to underground to maximize load served while limiting wildfire risk across a range of wildfire risk and weather scenarios. Since solving this problem may be computationally heavy for large power grids and many operating scenarios, we present a delayed constraint generation algorithm to iteratively add scenarios until an optimal solution is found. We evaluate the performance of this framework on the RTS-GMLC with scenarios representing a year of operating conditions and compare it with a stochastic programming formulation. Our results indicate that our undergrounding model is successful in reducing load shed and risk compared to baseline cases in which no mitigation action is taken and only power shutoffs are implemented (no undergrounding). The robust formulation also reduces more load shed than the stochastic formulation in the most extreme scenarios. Index Terms—grid resilience, optimization, transmission systems, underground power lines, wildfire risk.

Taylor, S. [Department of Electrical and Computer ↗

Bench-Scale Testing of Monolithic PPI Structured Contactors for Direct Air Capture of CO 2

The overall project objective was to develop, optimize and bench-scale test the integrated embodiment of a leading direct air capture (DAC) sorbent composition, linear-poly(propylenimine) (l-PPI), in a structured material system, specifically a monolithic contactor for achieving low pressure drop, to justify its further scale-up in a subsequent program. The project team was led by CORMETECH, a leading monolithic gas/solid contactor manufacturer for environmental applications, and included Global Thermostat, a well-known DAC start-up, and Georgia Tech, a prominent US academic institution in carbon capture and DAC. The monolithic contactor for l-PPI in this project employed an advanced, cost-effective fabrication technique from CORMETECH, namely a porous monolith substrate directly impregnated with the amine, an approach contrasting to the traditional wash-coating methods used for activating monoliths. The l-PPI monolithic contractor is targeted for use in DAC systems such as the Global Thermostat DAC process, which involves the cyclic operation of ambient air flow over a monolithic amine contactor followed by steam-mediated thermal desorption and CO 2 collection, maximizing volumetric productivity while reducing the auxiliary power required to capture CO 2 from air. The Global Thermostat DAC process currently utilizes poly(ethyleneimine) (PEI) materials as baseline sorbents, which are subject to oxidative degradation and slow capacity fade at the elevated temperature required for efficient CO 2 removal. Georgia Tech, with Global Thermostat, had discovered in lab-scale efforts that l-PPI had superior resistance to oxidative degradation compared to PEI, with similar CO 2 adsorption capacity. While the novel l-PPI sorbent offers significant advantages over PEI for DAC, including potential design simplification and increased process efficiency, it is not commercially available, and prior to this project, had not yet been evaluated on the bench-scale in a structured contactor.

36 MATERIALS SCIENCE↗

Deconvoluting XPS Spectra of La-Containing Perovskites from First-Principles

Perovskite-based oxides are used in electrochemical CO 2 and H 2 O reduction in electrochemical cells due to their compositional versatility, redox properties and stability. However limited knowledge exists on the mechanisms driving these processes. Toward this understanding, herein we probe the core level binding energy shifts of water-derived adspecies (H, O, OH, H 2 O) as well as the adsorption of CO 2 on LaCoO 3 and LaNiO 3 and we correlate the simulated peaks with experimental Temperature Programmed X-ray Photoelectron Spectroscopy (TPXPS) results. We find the strong adsorption of such chemical species can affect the antiferromagnetic ordering of LaNiO 3 . The adsorption of such adspecies is further quantified through Bader and differential charge analyses. We find the higher O 1s core level binding energy peak for both LaCoO 3 and LaNiO 3 corresponds to adsorption of water-related species and CO 2 , while the lower energy peak is due to lattice oxygen. We further correlate these DFT-based core level O 1s binding energies with the TPXPS measurements to quantify the decrease of the O 1s contribution due to desorption of adsorbates and the apparent increase of the lattice oxygen (both bulk and surface) with temperature. Finally, we quantify the influence of adsorbates on the La 4d, Co 2p and the Ni 3p core level binding energy shifts. This work demonstrates how theoretically generated XPS data can be utilized to predict species-specific binding energy shifts to assist in the deconvolution of the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrifying Critical Mineral Refinement in the US (CRADA Final Report)

The technical founder of Aepnus Technology Inc. was competitively selected for support by Cyclotron Road, a U.S. Department of Energy (DOE) Lab-Embedded Entrepreneurship Program (LEEP) through an approved merit review process. Through this program, Aepnus Technology has collaborated with Lawrence Berkeley National Laboratory (LBNL) to develop and validate a novel electrolysis platform targeting the recycling of sodium sulfate waste, a pervasive byproduct in the battery supply chain. The platform aims to address inefficiencies in conventional electrolysis by leveraging Aepnus' proprietary gas diffusion electrode (GDE) technology, which replaces precious metal catalysts, such as iridium, to achieve high efficiency, reduced operational costs, and enhanced durability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗