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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Chapter 2: Evaluating a Concentrating Solar Power Plantas an Extended-Duration Peaking Resource

We explore the ability of a concentrating solar power (CSP) plant with thermal energy storage (TES) to provide peaking capacity. We focus on future power systems, wherein net load patterns may be significantly different than they are today (e.g., due to higher renewable-energy penetrations). We examine 28 locations in the southwestern United States over an 18-year period. The hourly operation of the CSP plants are simulated to determine their potential to provide energy during an eight-hour peak-load window for each day up to 365 days per year. Our result shows that for the large majority of locations and years, CSP plants with certain configurations (i.e., in terms of solar field and TES sizes) can provide nearly 100% peak-load capacity. We examine also the amount of supplemental energy (e.g.,by using natural gas as a supplemental thermal-energy source) that would be required to ensure that a CSP plant could serve the eight highest-load hours of every day of the year. We find that in most cases, a CSP plant supplemented with natural gas would require less than 5% of the fuel that is used by a natural-gas fired power plant providing the same level of reliable capacity. A series of sensitivity analyses show that these results are robust to the number of peak-load hours and days that are considered and the configuration of the CSP plant.

capacity value↗
DOE OSTI2025

ROOT RNTuple and EOS: The Next Generation of Event Data I/O

For several years, the ROOT team is developing the new RNTuple I/O subsystem in preparation of the next generation of collider experiments. Both HL-LHC and DUNE are expected to start data taking by the end of this decade. They pose unprecedented challenges to event data I/O in terms of data rates, event sizes, and event complexity. At the same time, the I/O landscape is becoming more diverse. HPC cluster file systems and object stores, NVMe disk cache layers in analysis facilities, and S3 storage on cloud resources are mixing with traditional XRootD-managed spinning disk pools.The ROOT team will finalize a first production version of the RNTuple binary format by the end of 2024. After this point, ROOT will provide backward compatibility for RNTuple data. This contribution provides an overview of the RNTuple feature set, the related R&D activities and the long-term vision for RNTuple. We report on performance, interface design, tooling, robustness, integration with experiment frameworks, and validation results, as well as recent R&D on parallel reading and writing and exploitation of modern hardware and storage systems. We will give an outlook on possible future features after a first production release.Collaboratively, the IT and EP departments at CERN have launched a formal project within the Research and Computing sector to evaluate the novel data format for physics analysis data utilized in LHC experiments and other fields. This part of the project focuses on validating the scalability of the EOS storage backend during the transition from the over 25 years old TTree production format to the newly developed RNTuple format, using both replicated and erasure-coded storage profiles.

Blomer, Jakob [CERN]↗
DOE OSTI2024

A Pro‐Angiogenic Immunoprotective Membrane for Cell Therapies

Abstract Immunoisolation strategies that rely on porous membranes play an important role in cell transplantation therapies to protect cells from the host's immune system. These membranes must possess immunoprotective properties while facilitating the transport of nutrients and cell products to maintain the functional integrity of encapsulated cells. An easy and scalable process is described to fabricate a dual function porous polymeric membrane that shields cells against immune cell attack and promotes vascularization to address the nutritional and oxygen requirements of transplanted cells. The fabrication process results in a membrane cross‐section with a gradient of nanopores to micropores that support cell immunoisolation and interfacial vascularization requirements, respectively. The membranes demonstrate excellent cell compatibility and effectively prevent T cell transmigration without compromising glucose diffusion and oxygen permeability. In a murine subcutaneous implantation model, membranes are stable for 60 days and exhibit significantly reduced fibrous capsules, with enhanced vascularization near the membrane. These porous polymeric membranes can potentially be used as pro‐angiogenic immunoprotective membranes for cell transplantation applications where maximizing cell viability and function is of critical importance.

Engineering↗
DOE OSTI2026

Online task-space motion control for positioner-coordinated multi-robot manufacturing systems

Incorporating multiple robotic manipulators into large-scale manufacturing systems enhances production efficiency and expands manufacturing capabilities beyond those of single-robot systems. Workpiece positioners in robotic manufacturing have demonstrated significant benefits for process optimization, but coordination strategies for multi-robot systems with shared positioners have received limited attention. This work presents a task-space coordinated trajectory-tracking control framework for multi-robot manufacturing systems, in which robots coordinate their motions within a shared, dynamic workpiece positioning frame. A workpiece positioner actively adjusts the pose of the manufactured component to enable greater operational concurrency and improve overall production efficiency. The proposed motion-coordination scheme employs a distributed and scalable architecture, supporting coordination across heterogeneous multi-robot systems. Two optimization methodologies are introduced to manage kinematic redundancies and maintain continuous, near-optimal operation throughout the manufacturing process. The first strategy exploits a task-space dimensionality reduction to achieve locally optimal configurations by leveraging symmetry-axis rotations of the tool. The second strategy utilizes the workpiece positioner to drive the coordinated robots toward stable and kinematically favorable configurations. For both optimization strategies, multiple objectives are defined to improve key performance metrics, including manipulability, configuration consistency, proximity to mechanical limits, and motion efficiency. Addressing a key limitation of existing coordination approaches, the framework is designed around online setpoint modification, allowing coordinated robots to respond effectively to in-situ process feedback. The proposed control framework is validated using the Robot Operating System (ROS) middleware on a combination of physical and simulated multi-robot system hardware.

Arbogast, Alex [ORNL] (ORCID:0000000154740723)↗
DOE OSTI2025

Manufacturing of Continuous Microporous Polymeric Fibers for Separation Applications

Polyolefin plastic waste, particularly polypropylene, is one of the most prevalent components in the plastic waste stream generated globally. However, only a small fraction of this waste is recycled and reintegrated into second applications. These materials have significant embedded energy that could be used for additional productivity if recycled properly. Therefore, there is a critical need to develop scalable processing techniques with high throughput to effectively recycle it. We report the continuous manufacturing of microporous fibers using waste polypropylene plastic and melt-processable lignin, a plant biomass constituent produced as a byproduct in paper mills or biorefineries, as a template to create pores. Further, these filaments with hierarchical porosity─created by controlled microphase separation during high-speed extensional flow followed by removal of lignin─exhibit exceptional capillary action for hydrophobic liquids. The resulting porous fibers can be used for various separation applications. For example, the oil uptake of the fibers is 9.59 ± 0.82 g/g for applications in oil recovery in bodies of water. In addition, polyethylenimine infiltration within these nanoporous fibers introduces cyclic room temperature sorption and thermal desorption potential of acidic gases such as CO 2 in a bench-scale experiment. The fibers exhibit multiple cycles of CO 2 absorption, with a range of 0.15 to 0.17 mmol/g. Thus, these polyethylenimine-infiltered nanoporous polypropylene fibers can also be used in removing acidic gases from a gas mixture.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ChatHPC: Building the Foundations for a Productive and Trustworthy AI-Assisted HPC Ecosystem

ChatHPC democratizes large language models for the high-performance computing (HPC) community by providing the infrastructure, ecosystem, and knowledge needed to apply modern generative AI technologies to rapidly create specific capabilities for critical HPC components while using relatively modest computational resources. Our divide-and-conquer approach focuses on creating a collection of reliable, highly specialized, and optimized AI assistants for HPC based on the cost-effective and fast Code Llama fine-tuning processes and expert supervision. We target major components of the HPC software stack, including programming models, runtimes, I/O, tooling, and math libraries. Thanks to AI, ChatHPC provides a more productive HPC ecosystem by boosting important tasks related to portability, parallelization, optimization, scalability, and instrumentation, among others. With relatively small datasets (on the order of KB), the AI assistants, which are created in a few minutes by using one node with two NVIDIA H100 GPUs and the ChatHPC library, can create new capabilities with Meta’s 7-billion parameter Code Llama base model to produce high-quality software with a level of trustworthiness of up to 90% higher than the 1.8-trillion parameter OpenAI ChatGPT-4o model for critical programming tasks in the HPC software stack.

Young, Aaron [ORNL] (ORCID:0000000254484667)↗
DOE OSTI2026

Challenging conventional assumptions in PV: a high-throughput open-air approach to low-cost perovskite module production

Perovskite solar modules (PSMs) offer a promising pathway to low-cost photovoltaics, yet their commercialization is challenged by manufacturing scalability, device uniformity, additive costs, interlayer complexity, and module stability. This study introduces a comprehensive technoeconomic analysis of single junction PSM's and projections for tandem perovskite-Si modules that integrate all materials and manufacturing steps, module performances, projected lifetimes, and manufacturing costs across scales. Here, we highlight an open-air manufacturing approach to fabricate all active layers of serially interconnected PSMs, including electrodes and charge transport layers, enabling high-throughput production without inert or vacuum environments. The analysis reveals two orders of magnitude throughput enhancement and cost reductions of 24% in all-open-air production, escalating to over 60% at 1 GW factory capacity compared to conventional methods. Levelized cost of energy (LCOE) projections for utility-scale installations over 30 years, accounting for module replacement and recycling, demonstrate the potential to achieve the 2030 US target of $0.03 per kWh with realistic 7–11-year PSM lifetimes, outperforming incumbent silicon-based modules. Neither four terminal (4T) nor two terminal (2T) tandem-Si PSMs improve over single junction perovskite or silicon LCOE regardless of higher efficiencies at any modeled lifetime. Addressing PSM technical challenges with a cost-modeling framework guides commercialization efforts and provides a convincing pathway for challenging incumbent Si-based PV.

14 SOLAR ENERGY↗
DOE OSTI2021

Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery

Non-Ribosomal Peptides (NRPs) represent a biomedically important class of natural products that include a multitude of antibiotics and other clinically used drugs. NRPs are not directly encoded in the genome but are instead produced by metabolic pathways encoded by biosynthetic gene clusters (BGCs). Since the existing genome mining tools predict many putative NRPs synthesized by a given BGC, it remains unclear which of these putative NRPs are correct and how to identify post-assembly modifications of amino acids in these NRPs in a blind mode, without knowing which modifications exist in the sample. To address this challenge, here we report NRPminer, a modification-tolerant tool for NRP discovery from large (meta)genomic and mass spectrometry datasets. We show that NRPminer is able to identify many NRPs from different environments, including four previously unreported NRP families from soil-associated microbes and NRPs from human microbiota. Furthermore, in this work we demonstrate the anti-parasitic activities and the structure of two of these NRP families using direct bioactivity screening and nuclear magnetic resonance spectrometry, illustrating the power of NRPminer for discovering bioactive NRPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Small tensor product distributed active space (STP-DAS) framework for relativistic and non-relativistic multiconfiguration calculations: Scaling from 10 9 on a laptop to 10 12 determinants on a supercomputer

Despite the power and flexibility of configuration interaction (CI) based methods in computational chemistry, their broader application is limited by an exponential increase in both computational and storage requirements, particularly due to the substantial memory needed for excitation lists that are crucial for scalable parallel computing. Here, the objective of this work is to develop a new CI framework, namely, the small tensor product distributed active space (STP-DAS) framework, aimed at drastically reducing memory demands for extensive CI calculations on individual workstations or laptops, while simultaneously enhancing scalability for extensive parallel computing. Moreover, the STP-DAS framework can support various CI-based techniques, such as complete active space (CAS), restricted active space, generalized active space, multireference CI, and multireference perturbation theory, applicable to both relativistic (two- and four-component) and non-relativistic theories, thus extending the utility of CI methods in computational research. We conducted benchmark studies on a supercomputer to evaluate the storage needs, parallel scalability, and communication downtime using a realistic exact-two-component CASCI (X2C-CASCI) approach, covering a range of determinants from 10 9 to 10 12 . Additionally, we performed large X2C-CASCI calculations on a single laptop and examined how the STP-DAS partitioning affects performance.

Complete-active space self-consistent field↗
DOE OSTI2020

Roll-to-roll production of catalyst coated membranes for low-temperature electrolyzers

Here we demonstrate a roll-to-roll (R2R) process for direct coating of anode catalyst layers on a polymer electrolyte membrane for low-temperature water electrolysis. To develop this process, we studied catalyst ink formulation, ink-membrane interactions, and coating quality. The catalyst inks were a mixture of iridium oxide (IrO2) and Nafion in a water and alcohol dispersion medium. The type of alcohol (methanol, ethanol, propanols) and water-to-alcohol ratio were varied to determine their influence on membrane swelling, dispersion quality, and coatability. Interactions of the ink dispersion medium with the membrane were characterized using sessile-drop contact-angle measurements. These measurements show that the ratio of water to alcohol has a strong influence on how rapidly the dispersion media is absorbed by the membrane. Rheology of the catalyst inks was measured to understand the microstructure of the catalyst particles in the ink. This analysis found that 1-propanol leads to better dispersion of the IrO2 particles than ethanol. Small-scale coating samples were prepared to understand coating uniformity and formation of irregularities. Subsequently, two water/1-propanol ratios (90:10 and 75:25) were down-selected for large-scale R2R slot die coating. The R2R catalyst-coated membrane (CCM) coating process increased catalyst layer production throughput by over 500x compared to our standard lab-scale spray coating. The CCMs obtained from this process were tested as single-cell membrane electrode assemblies. They exhibited a cell voltage of 1.91 V at a current density of 2 A/cm2, which is comparable to spray-coated CCMs. In conclusion, the work presented here demonstrates a continuous, scalable manufacturing process that eliminates the need for the decal transfer step typically used in CCM production.

42 ENGINEERING↗
DOE OSTI2024

Amorphous Iridium Oxide-Integrated Anode Electrodes with Ultrahigh Material Utilization for Hydrogen Production at Industrial Current Densities

Herein, ionomer-free amorphous iridium oxide (IrO x ) thin electrodes are first developed as highly active anodes for proton exchange membrane electrolyzer cells (PEMECs) via low-cost, environmentally friendly, and easily scalable electrodeposition at room temperature. Combined with a Nafion 117 membrane, the IrO x -integrated electrode with an ultralow loading of 0.075 mg cm –2 delivers a high cell efficiency of about 90%, achieving more than 96% catalyst savings and 42-fold higher catalyst utilization compared to commercial catalyst-coated membrane (2 mg cm –2 ). Additionally, the IrO x electrode demonstrates superior performance, higher catalyst utilization and significantly simplified fabrication with easy scalability compared with the most previously reported anodes. Notably, the remarkable performance could be mainly due to the amorphous phase property, sufficient Ir 3+ content, and rich surface hydroxide groups in catalysts. Overall, due to the high activity, high cell efficiency, an economical, greatly simplified and easily scalable fabrication process, and ultrahigh material utilization, the IrO x electrode shows great potential to be applied in industry and accelerates the commercialization of PEMECs and renewable energy evolution.

08 HYDROGEN↗
DOE OSTI2025

Enhancing lipid production in plant cells through automated high-throughput genome engineering and phenotyping

Plant bioengineering is a time-consuming and labor-intensive process with no guarantee of achieving desired traits. Here, we present a fast, automated, scalable, high-throughput pipeline for plant bioengineering (FAST-PB) in maize (Zea mays) and Nicotiana benthamiana. FAST-PB enables genome editing and product characterization by integrating automated biofoundry engineering of callus and protoplast cells with single-cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrated that FAST-PB could streamline Golden Gate cloning, with the capacity to construct 96 vectors in parallel. Using FAST-PB in protoplasts, we found that PEG2050 increased transfection efficiency by over 45%. For proof-of-concept, we established a reporter-gene-free method for CRISPR editing and phenotyping via mutation of high chlorophyll fluorescence 136. We show that diverse lipids were enhanced up to 6-fold using CRISPR activation of lipid controlling genes. In callus cells, an automated transformation platform was employed to regenerate plants with enhanced lipid traits through introducing multigene cassettes. Lastly, FAST-PB enabled high-throughput single-cell lipid profiling by integrating MALDI-MS with the biofoundry, protoplast, and callus cells, differentiating engineered and unengineered cells using single-cell lipidomics. Furthermore, these innovations massively increase the throughput of synthetic biology, genome editing, and metabolic engineering and change what is possible using single-cell metabolomics in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Data for "Enhancing Lipid Production in Plant Cells through Automated High-Throughput Genome Engineering and Phenotyping"

Plant bioengineering is a time-consuming and labor-intensive process with no guarantee of achieving desired traits. Here, we present a fast, automated, scalable, high-throughput pipeline for plant bioengineering (FAST-PB) in maize (Zea mays) and Nicotiana benthamiana. FAST-PB enables genome editing and product characterization by integrating automated biofoundry engineering of callus and protoplast cells with single-cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrated that FAST-PB could streamline Golden Gate cloning, with the capacity to construct 96 vectors in parallel. Using FAST-PB in protoplasts, we found that PEG2050 increased transfection efficiency by over 45%. For proof-of-concept, we established a reporter-gene-free method for CRISPR editing and phenotyping via mutation of high chlorophyll fluorescence 136. We show that diverse lipids were enhanced up to 6-fold using CRISPR activation of lipid controlling genes. In callus cells, an automated transformation platform was employed to regenerate plants with enhanced lipid traits through introducing multigene cassettes. Lastly, FAST-PB enabled high-throughput single-cell lipid profiling by integrating MALDI-MS with the biofoundry, protoplast, and callus cells, differentiating engineered and unengineered cells using single-cell lipidomics. These innovations massively increase the throughput of synthetic biology, genome editing, and metabolic engineering and change what is possible using single-cell metabolomics in plants.

AI/ML↗
DOE OSTI2021

Fast and Scalable Synthesis of LiNi 0.5 Mn 1.5 O 4 Cathode by Sol–Gel-Assisted Microwave Sintering

High-voltage spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) is a promising cathode material for high-energy-density and high-power-density lithium-ion batteries (LIBs). The high cost of the currently available LIBs needs to be addressed urgently for wide application in the transport sector (electric vehicles, buses) and large-scale energy storage systems (ESS). Of significance, herein, novel fast and scalable microwave-assisted synthesis of LNMO is reported, which leads to a production cost cut. X-ray diffraction (XRD) analysis confirms the formation of the desired phase with high crystallinity. Field emission scanning (FE-SEM) and transmission electron microscopy (TEM) analyses indicate that the synthesized phase is of nanometric size (50–150 nm) due to an extremely short sintering time (20 min). The material synthesized at 750 °C shows a higher initial discharge capacity (130 mA h g -1 ) than that synthesized at 650 °C (115 mA h g -1 ). The materials heat treated at higher temperatures show better electrochemical performance in terms of initial capacity, rate capability, and improved cycling. The improved electrochemical performance of LNMO at 750 °C is attributed to the formation of a stable crystal structure, low charge transfer resistance at the electrode/electrolyte interface, high electrical conductivity due to the presence of a disorder structure, and improved ionic diffusivity.

25 ENERGY STORAGE↗
DOE OSTI2026

Through‐Plane Conductive Hydrophobic Electrodes for CO 2 Electrolysis to Ethylene

Copper catalyst gas diffusion electrodes (GDEs) have demonstrated unique electrochemical selectivity converting CO 2 to C 2 -hydrocarbons such as ethylene and ethanol but have been challenged by their hydrophobic chemical stability and internal electrical resistance leading to low energy efficiency. Carbon-supported GDEs have low electrical resistance but lack sufficient stability at industrially relevant current densities. While polymer-supported GDEs have improved hydrophobicity, they also display high in-plane electrical resistance, particularly at industrial scales. Here, in this work, we demonstrate a composite gas diffusion layer that combines hydrophobic porous polymers with an electrically conductive backbone addressing these core gas diffusion electrode (GDE) scaling challenges. We investigate the material properties of standalone porous perfluoropolyether (PFPE) polymers, including porosity and surface morphology, under varying processing conditions and then incorporate these polymers into a porous copper foam. This composite enhances the mechanical rigidity necessary for cell assembly and provides a through-plane electrical conduction path to reduce electrical resistive losses. This enhanced PFPE composite GDE displays efficient CO 2 reduction, achieving 15% ethylene energy efficiency at 100 cm 2 . These findings contribute to the development of advanced catalyst materials and electrode architectures and promote scalable strategies for electrochemical conversion of CO 2 into high-value carbon products.

Chemistry↗
DOE OSTI2026

Depolymerization of Vinyl Polymers

Depolymerization is a promising approach to reduce plastic waste by regenerating monomers from polymers, presenting a compelling solution to maintain a circular polymer economy. However, vinyl polymers with all-carbon backbones are especially difficult to depolymerize due to significant thermodynamic and kinetic barriers. Developments in reversible-deactivation radical polymerization and catalytic methods demonstrate how tuning polymer structure and reaction conditions can address these challenges. This Viewpoint revisits early studies on radical depolymerization and recent advances enabling monomer recovery at lower temperatures. Exciting current trends to utilize depolymerization as a strategy for tuning polymer material properties and upcycling waste polymer to high-value products are discussed. Finally, we outline key directions to make vinyl polymer depolymerization scalable, efficient, and economically viable.

depolymerization↗
DOE OSTI2024

Edible mycelium bioengineered for enhanced nutritional value and sensory appeal using a modular synthetic biology toolkit

Filamentous fungi are critical in the transition to a more sustainable food system. While genetic modification of these organisms has promise for enhancing the nutritional value, sensory appeal, and scalability of fungal foods, genetic tools and demonstrated use cases for bioengineered food production by edible strains are lacking. Here, we develop a modular synthetic biology toolkit for Aspergillus oryzae, an edible fungus used in fermented foods, protein production, and meat alternatives. Our toolkit includes a CRISPR-Cas9 method for gene integration, neutral loci, and tunable promoters. We use these tools to elevate intracellular levels of the nutraceutical ergothioneine and the flavor-and color molecule heme in the edible biomass. The strain overproducing heme is red in color and is readily formulated into imitation meat patties with minimal processing. These findings highlight the promise of synthetic biology to enhance fungal foods and provide useful genetic tools for applications in food production and beyond.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A MultiGPU Performance-Portable Solution for Array Programming Based on Kokkos

Today, multiGPU nodes are widely used in high-performance computing and data centers. However, current programming models do not provide simple, transparent, and portable support for automatically targeting multiple GPUs within a node on application areas of array programming. In this paper, we describe a new application programming interface based on the Kokkos programming model to enable array computation on multiple GPUs in a transparent and portable way across both NVIDIA and AMD GPUs. We implement different variations of this technique to accommodate the exchange of stencils (array boundaries) among different GPU memory spaces, and we provide autotuning to select the proper number of GPUs, depending on the computational cost of the operations to be computed on arrays, that is completely transparent to the programmer. We evaluate our multiGPU extension on Summit (#5 TOP500), with six NVIDIA V100 Volta GPUs per node, and Crusher that contains identical hardware/software as Frontier (#1 TOP500), with four AMD MI250X GPUs, each with 2 Graphics Compute Dies (GCDs)for a total of 8 GCDs per node. We also compare the performance of this solution against the use of MPI + Kokkos, which is the cur-rent de facto solution for multiple GPUs in Kokkos. Our evaluation shows that the new Kokkos solution provides good scalability for many GPUs and a faster and simpler solution (from a programming productivity perspective) than MPI + Kokkos.

Valero Lara, Pedro↗