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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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9 records

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Low-cost buffer storage for solar industrial steam applications

Motivation and importance: Many industrial process heat consumers operate throughout the day, and deep decarbonization with solar energy requires thermal energy storage. Thermal energy storage provides an additional operational benefit of firm delivery of steam – essential to reducing the risk of costly production interruptions. The group of process heat consumers that use steam for biofuels production for the California transportation fuels market is incentivized through the Low Carbon Fuel Standard (LCFS) to reduce their carbon intensity through the use of solar steam. Examples include ethanol and dimethyl ether production. The production of these and other fuels involves distillation driven by steam reboilers with steam pressures in the range 100-280 psig. These pressures can be delivered from the type of thermal energy storage that has been the focus of this project – a steam accumulator Sunvapor, Inc. (SVI) calls a “Bullet Steam Accumulator” or “BSA TM ”. Our project adds to the understanding of the design and integration of steam accumulators charged by solar thermal energy in a biofuels production facility, and similar facilities that consume process steam. The fuel application requires a demanding level of Process Safety Management not found in other steam applications. The type of steam accumulator SVI engineered and built integrates steam generation and storage in one vessel to reduce cost. Achieving a first of a kind permit to operate such a first device has also added to the understanding of the industrial application of such systems. Goals: The overall goal of the project has been to demonstrate the advantages that a “Bullet Steam Accumulator” (BSA™) can provide to solar steam integration with a manufacturing process. The industrial host has already been convinced of the potential of the available solar steam to lower than carbon intensity score. They have been interviewed for a number of publications such as that tout the advantages SVI’s system brings to their operations. Accomplishments: At the end of 2023 Sunvapor placed in service the country’s first industrial solar boiler with thermal energy storage. At the same time, this placement in service represents the first pilot commercial system to decarbonize biofuels production through the use of solar thermal energy. While the full technical effectiveness will be shown as soon as the customer’s plant is able to consume the available steam, the economic feasibility was indicated early in the project when the combination of costs and steam pricing required to meet investor expectations was determined. The project represents a reference pilot from which a full-scale commercial system may be expanded. This pilot is a necessary first step in providing the full potential benefits to the public, including decarbonization of transportation fuels. The decarbonization of the separation steps in fuels production may be the most cost-effective and nearest term solar fuel. Co-benefits include a reduction of air pollutants such as NOx and particulate matter, and job creation for the construction, operation and maintenance of industrial solar facilities.

14 SOLAR ENERGY↗

DOE OSTI2025

Harnessing Nanobodies for Precision Targeting of Proteoforms: Opportunities and Challenges in Therapeutics and Diagnostics

Proteoforms are biologically distinct yet structurally similar proteins that play key roles in driving disease progression but are rarely accounted for in the development of therapeutics and diagnostics. Nanobodies (Nbs) have emerged as a therapeutic and diagnostic “silver bullet” as they possess unique structural and functional attributes that offer advantages over traditional antibodies. One of the most profound advantages of Nbs is the heightened sensitivity and ability to distinguish subtle changes in the conformation of a given protein. Thus, Nbs have significant potential as therapeutic and diagnostic agents that can identify and distinguish specific pathological proteoforms that underlie a given disease. However, there remain significant challenges in obtaining sufficient quantities and purities of specific proteoform antigens that are required for engineering proteoform-specific Nbs. Recent advancements in chemical biology tools for precision proteoform synthesis have made this task feasible for the first time. In this perspective, we discuss the advantages and challenges associated with developing proteoform-specific Nbs and how success in this endeavor will significantly advance the fields of therapeutics and diagnostics.

Antigens↗

DOE OSTI2025

A Machine Learning Framework for Predicting Microphysical Properties of Ice Crystals From Cloud Particle Imagery

The microphysical properties of ice crystals are important because they significantly alter the radiative properties and spatiotemporal distributions of clouds, which in turn strongly affect Earth's climate. However, it is challenging to measure key properties of ice crystals, such as mass or morphological features. Here, we present a proof-of-concept framework for predicting three-dimensional (3D) microphysical properties of ice crystals from in situ two-dimensional (2D) imagery. First, we computationally generated synthetic ice crystals using 3D modeling software along with geometric parameters estimated from the 2021 Ice Cryo-Encapsulation Balloon (ICEBall) field campaign. Then, we used synthetic crystals to train machine learning (ML) models to predict effective density ($ρ_e$), effective surface area ($A_e$), and number of bullets ($N_b$) from synthetic rosette imagery. On unseen synthetic images, our ML models accurately predicted ice crystal properties. ResNet-18 performed best, achieving $R^2$ values of 0.99 and 0.98 for $ρ_e$ and $A_e$, respectively, and MAE of 0.10 for mathematical equation in single view tasks. Stereo view ResNet-18 further reduced RMSE by 40% for $ρ_e$ and $A_e$ and reduced MAE by 0.08 for $N_b$. This work provides a novel ML-driven framework for estimating ice microphysical properties from in situ imagery, which will allow for downstream constraints on microphysical parameterizations, such as the mass-size relationship.

Ko, J. [Columbia Univ., New York, NY (United State↗

DOE OSTI2026

Targeted delivery of genome editors in vivo

Genome editing has revolutionized the treatment of genetic diseases, yet the difficulty of tissue-specific delivery currently limits applications of editing technology. Here, in this Review, we discuss preclinical and clinical advances in delivering genome editors with both established and emerging delivery mechanisms. Targeted delivery promises to considerably expand the therapeutic applicability of genome editing, moving closer to the ideal of a precise ‘magic bullet’ that safely and effectively treats diverse genetic disorders.

Ngo, Wayne [University of California, Berkeley, CA↗

DOE OSTI2024

Dark matter relic density in strongly interacting dark sectors with light vector mesons

Stable dark matter particles may arise as pseudo-Goldstone bosons from the confinement of dark quarks interacting via a non-Abelian gauge force. Their relic abundance is determined not by annihilations into visible particles but by dark pion number-changing processes within the dark sector, such as 3 π D → 2 π D . However, if the dark vector mesons ρ D are light enough for 3 π D → π D ρ D annihilations to be kinematically allowed, this process dominates and significantly delays freeze-out. As a result, the preferred dark matter mass scale increases and bounds from the Bullet Cluster can be evaded. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

TalkPipe Writing Assistant

SAND2025-14316O TalkPipe Writing Assistant offers AI assistance, providing help on a point-by-point basis. Authors can start with their own ideas—whether bullet points, partial paragraphs, or phrases—and specify the document type, desired tone, audience, and any other relevant context. As they write, the assistant provides tailored suggestions for each paragraph. They can request high-level concepts, draft a paragraph, or proofread existing text. The large language model (LLM) considers both preceding and following paragraphs to ensure coherence and flow. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Bauer, Travis [Sandia National Lab. (SNL-CA), Live↗

DOE OSTI2024

Small arms suppression project (LLNL final report)

US Special Operations Command (USSOCOM) was seeking a technological leap in small firearms weapon suppressor technology, because anticipated enemy capabilities are requiring the operators to have smaller detection cross sections to ensure the safe execution of missions. Suppressors have been developed almost exclusively through trial-and-error methods since the time of the original design by Hiram Maxim over one hundred years ago. Consequently USSOCOM deemed it prudent to perform a physicsbased study of weapon suppression to understand performance limits and possibly identify breakthrough technologies. Lawrence Livermore National Laboratory’s (LLNL’s) high performance production level computational tool called ALE3D (Arbitrary Lagrangian-Eulerian 3D and 2D) has unique physics models and numerical algorithms for modeling suppressor dynamics. The flexible and extendable code framework supports fully integrated hydrodynamics, heat transfer, solid and fluid dynamics, and chemistry that can be applied to simulating propellant-driven motion of a bullet down a gun barrel, the transfer of heat from the burning propellant to the barrel and suppressor, the chemistry of muzzle flash, and the shock/acoustic/optical signatures in the near-field. LLNL’s originally anticipated role was to augment ALE3D for this task, by developing the software and analysis methodologies specific to the simulation of blast and muzzle flash phenomena. It was believed that insights provided by our ALE3D simulations in tandem with a coordinated experimental component by our other team members from Oak Ridge National Laboratory (ORNL) and the U. S. Army Armament, Research, Development and Engineering Center (ARDEC), would have excellent prospects of yielding useful suppressor design improvements that could be transitioned to industry and utilized by US Special Operations Command. The three year effort has come to fruition with the development of revolutionary suppressor designs that far outperform any previous or current design by anyone outside this multi-lab team.

42 ENGINEERING↗

DOE OSTI2025

Modeling and Design of a Sub-Nyquist PDV Digitization System

Photon-Doppler Velocimetry (PDV) uses interferometry of a transmitted optical signal reflected from a fast-moving device under test (DUT) to generate a product signal at a doppler shifted frequency which is proportional to the velocity of the object being measured. The technique has applications in shock physics, where it is used to measure fast-moving objects over a short lifespan of travel, such as a bullet, shrapnel, or other shock accelerated object.

42 ENGINEERING↗

DOE OSTI2026

Scaling Spectroradiometric Monitoring to an Algal Factory Farm

This report briefly summarizes the spectroradiometric approach adapted and deployed as part of Task 4.2 within the BETO-funded D evelopment of I ntegrated S creening, C ultivar O ptimization, and V erification R esearch (DISCOVR) project, specifically task 4, “Increase crop protection and culture stability.” The goals of this subtask were to monitor ponds cultivating a variety of DISCOVR strains at the Arizona Center for Algae Technology and Innovation (AzCATI) with spectroradiometric technology to: • Predict biomass concentrations with high temporal frequency. • Optimize automated analysis methods that enabled feedback for pond automation strategies • Identify pond crash indicators from primary (pest/predator) and indirect (change in algal host) spectroscopic signals with potential for early treatment/intervention • Provide recommendations for technology deployment at scale. This report fulfills the deliverable requirement for the final bullet “provide recommendations for technology deployment at scale”.

09 BIOMASS FUELS↗