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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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53 records · Page 3

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Process Systems Engineering-Informed Design and Scale-Up of Multi-stage Diafiltration Cascades for Lithium and Cobalt Recovery from Spent Lithium-Ion Batteries

These slides present work jointly completed by Tasks in PrOMMiS. The first half of the presentation motivates the importance of critical materials for national security and how the recovery of critical minerals via membrane separations can be more cost effective than currently used technology. The second half of the presentation presents cost-optimal results for the custom cost model for diafiltration using the superstructure flowsheet developed by CMU. These results highlight how PSE can inform process targets (i.e., product purity targets) and suitable design strategies for scaled-up membrane cascades.

critical materials↗

DOE OSTI2024

Opportunities for Process Intensification with Membranes to Promote Circular Economy Development for Critical Minerals

Critical minerals are essential to the future of clean energy, especially energy storage, electric vehicles, and advanced electronics. In this paper, we argue that process systems engineering (PSE) paradigms provide essential frameworks for enhancing the sustainability and efficiency of critical mineral processing pathways. As a concrete example, we review challenges and opportu-nities across material-to-infrastructure scales for process intensification (PI) with membranes. Within critical mineral processing, there is a need to reduce environmental impact, especially con-cerning chemical reagent usage. Feed concentrations and product demand variability require flex-ible, intensified processes. Further, unique feedstocks require unique processes (i.e., no one-size-fits-all recycling or refining system exists). Membrane materials span a vast design space that allows significant optimization. Therefore, there is a need to rapidly identify the best opportunities for membrane implementation, thus informing materials optimization with process and infrastructure scale performance targets. Finally, scale-up must be accelerated and de-risked across the materials-to-process levels to fully realize the opportunity presented by membranes, thereby fostering the development of a circular economy for critical minerals. Tackling these challenges requires integrating efforts across diverse disciplines. We advocate for a holistic molecular-to-systems perspective for fully realizing PI with membranes to address sustainability challenges in critical mineral processing. The opportunities for PI with membranes are excellent applications for emerging research in machine learning, data science, automation, and optimization.

Dougher, Molly↗

DOE OSTI2021

Machine Learning Tools Set for Natural Gas Fuel Cell System Design

This study is focusing on leveraging the system design tools set for the next-generation solid oxide fuel cell (SOFC) based natural gas fuel cell (NGFC) system. Conventionally, system design and optimization of NGFC systems rely heavily on traditional reduced order model (ROM) techniques and designers’ experience level. For overcoming the technical barriers of system design, multiple multi-physics models and machine learning (ML) tools have been utilized to automate the conceptual design process and enhance the reliability of solutions for the NGFC system. The proposed tools set includes a physics-informed ML tool for automated ROM construction that leverages advances in deep neural networks to significantly reduce ROM prediction error for the NGFC power island compared to traditional approaches. The constructed physics-informed ML ROM can be used in system design, and optimization tools set Institute for the Design of Advanced Energy Systems (IDAES) Process Systems Engineering (PSE) framework. The tools set also provides a user-friendly graphic user interface built within Jupyter Notebooks, and the complete tools set is open-source public available.

Wang, Dewei↗

DOE OSTI2022

Dynamic Simulation and Optimization of a Subcritical Coal-Fired Power Plant During Load-Ramping Operations

Paper for presentation at The 14th International Symposium on Process Systems Engineering (PSE 2021+), Kyoto, Japan, June 19-23, (2022).

Ma, Jinliang N.↗

DOE OSTI2025

Kinetic Modeling of Secondary Organic Aerosol in a Weather-Chemistry Model: Parameterizations, Processes, and Predictions for GOAmazon

Secondary organic aerosol (SOA) forms and evolves in the atmosphere through many pathways and processes, over diverse spatial and time scales. Hence, there is a need to represent these widely-varying kinetic processes in large-scale atmospheric models to allow for accurate predictions of the abundance, properties, and impacts of SOA. In this work, we integrated a kinetic, process-level model (simpleSOM-MOSAIC) into a weather-chemistry model (WRF-Chem) to simulate the oxidation chemistry and microphysics of atmospheric SOA. simpleSOM-MOSAIC simulates multigenerational gas-phase chemistry, autoxidation reactions, heterogeneous oxidation, oligomerization, and phase-state-influenced gas/particle partitioning of SOA. As a case study, the integrated WRF-Chem-simpleSOM-MOSAIC (WC-SSM) model was used to simulate the photochemical evolution downwind of a large city (Manaus, Brazil) in the Amazon and, in turn, study the anthropogenic and biogenic interactions in an otherwise pristine environment. Consistent with previous work, we found that OA was enhanced by up to a factor of four in the urban plume due to elevated hydroxyl radical (OH) concentrations, relative to the background, and that this OA was dominated by SOA from biogenic precursors (80%). Further, in addition to accurately simulating the OA enhancement in the urban plume, the model reproduced the magnitude of the OA oxygen-to-carbon (O:C) ratio and broadly tracked the evolution of the aerosol size distribution. Our work highlights the importance of including an integrated, kinetic representation of SOA processes in an atmospheric model

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

High average-flux laser-driven neutron source

Laser-driven neutron generation is an attractive alternative to more established methods for compact, short-pulse-duration neutron sources with applications in medical science, material science and imaging. Despite extensive investigation of various techniques, achieving performance comparable to nuclear reactors or conventional accelerators remains challenging. In this work, we generate a stable, high-repetition-rate laser-driven neutron source reaching a record average flux of 7.8 × 10 7 n/sr/s, improving on other existing laser-based sources by more than one order of magnitude. Our approach is based on a two-step process where electrons are accelerated to relativistic energies via laser wakefield acceleration (LWFA), and subsequently generate neutrons through Bremsstrahlung emission followed by photonuclear reactions in a tungsten converter. Experimental results, supported by Monte Carlo simulations, show a neutron flux of 3.0 × 10 7 n/cm 2 /s near the target, on par with some compact accelerator-based neutron sources. Additionally, a direct comparison with the target-normal sheath acceleration (TNSA) pitcher-catcher scheme, performed on the same laser system, reveals a significantly higher total neutron yield of 3.9 × 10 8 neutrons per shot, outperforming the TNSA scheme by several orders of magnitude. These findings represent a significant advancement towards the development of practical laser-driven neutron sources and highlight the advantages of LWFA-based neutron generation for future applications.

Vallières, Simon [Institut National de la Recherch↗

DOE OSTI2024

PARETO UI 24.01.24 (0.9.0) Release

This is a standalone release of PARETO UI using the previously released PARETO version 0.9.0 for the backend.. New features in this version of PARETO UI are: - Added functionality to upload GIS map network visualizations and auto generate input templates - Added map visualizations based on GIS data