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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Characterization of Acousto-Electric Cluster and Array Levitation and its Application to Evaporation

An acousto-electric levitator has been developed to study the behavior of liquid drop and solid particle clusters and arrays. Unlike an ordinary acoustic levitator that uses only a standing acoustic wave to levitate a single drop or particle, this device uses an extra electric static field and the acoustic field simultaneously to generate and levitate charged drops in two-dimensional arrays in air without any contact to a solid surface. This cluster and array generation (CAG) instrument enables us to steadily position drops and arrays to study the behavior of multiple drop and particle systems such as spray and aerosol systems relevant to the energy, environmental, and material sciences.

Robert E. Apfel↗
DOE OSTI2021

Recent advances in nano-scale spatial resolution x-ray microscopy instrumentation at NSLS-II

X-ray microscopy is an invaluable and powerful characterization tool applied in many scientific fields, such as materials science, biology, environmental science, and energy research. In recent years it has been driven by rapid developments of novel technologies and systems resulting in imaging experiments elucidating structural inhomogeneities and chemical reactions at the nanometer scale. To obtain high spatial resolution comprehensive chemical and structural information, an X-ray microscope must be equipped with adequate capabilities and allow for simultaneous acquisition of multiple datasets. In recent years, a number of X-ray microscopes have been designed, constructed, and commissioned at NSLS-II. Here we provide an overview of the microscopy instrumentation development program at NSLS-II and specifically focus on the multilayer Laue lens-based hard X-ray nanoprobe optimized for ~10 nm spatial resolution imaging, its current status, and future upgrades along with recently constructed Kirkpatrick-Baez based scanning microscope designed for ~100 nm spatial resolution experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machine learning assisted phase and size-controlled synthesis of iron oxide particles

Synthesis of iron oxides with specific phases and particle sizes is a crucial challenge in various fields, including materials science, energy storage, biomedical applications, environmental science, and earth science. However, despite significant advances in this area, much of the current palette of particle outcomes has been based on time-consuming trial-and-error exploration of synthesis conditions. The present study was designed to explore a very different approach to 1) predict the outcome of synthesis from specified reaction parameters based on using machine learning (ML) techniques, and 2) correlate sets of parameters to obtain products with desired outcomes by a newly designed recommendation algorithm. To achieve this, four ML algorithms were tested, namely random forest, logistic regression, support vector machine, and k-nearest neighbor. Among the models, random forest outperformed the others, attaining 96% and 81% accuracy when predicting the phase and size of iron oxide particles in the test dataset. Surprisingly, the permutation feature importance analysis revealed that volume, which may strongly relate to pressure, was one of the important features, along with precursor concentration, pH, temperature, and time, influencing the phase and size of iron oxide particles during synthesis. To verify the robustness of the random forest models, prediction and experimental results were compared based on 24 randomly generated methods in additive and non-additive systems not included in the datasets. The predictions of product phase and particle size from the models agreed well with the experimental results. Furthermore, a searching and ranking algorithm was developed to recommend potential synthesis parameters for obtaining iron oxide products with the desired phase and particle size from previous studies in the dataset. Furthermore, this study lays the foundation for a closed-loop approach in materials synthesis and preparation, beginning with suggesting potential reaction parameters from the dataset and predicting potential outcomes, followed by conducting experiments and analyses, and ultimately enriching the dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Influence of Ag metal dispersion on the thermal conversion of ethanol to butadiene over Ag-ZrO 2 /SiO 2 catalysts

Atomistic scale models were developed and coupled with experimental investigation to deliver a functional understanding of catalytic activity and selectivity in the conversion of ethanol to 1,3-butadiene over Ag/ZrO 2 /SiO 2 . A detailed evaluation of the structural and electronic properties of the resultant catalyst models led to the identification of critical active sites of the catalyst. More importantly, the extent of Ag dispersion on the SiO 2 support and relative proximity to ZrO 2 were found to vary with the oxidation state of Ag and local coordination environment (Ag-O SiO2 ) allowing for critical control of ethanol conversion towards butadiene or ethylene. Simulations revealed that less dispersed or clustered Ag contain predominantly Ag 0 charge state and promote conversion of ethanol to ethylene. The well-dispersed Ag/ZrO 2 /SiO 2 catalyst instead contain a larger fraction of cationic Ag δ+ , and predominantly promote ethanol dehydrogenation and subsequent production of butadiene. The theoretical insights drawn were validated and confirmed experimentally using TEM, XRD and reactivity measurements demonstrating the effect of Ag dispersion on the selectivity of ethanol conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The fire that powers the universe: Harnessing inertial fusion energy

It was a laser shot for the ages. Finally, by achieving fusion ignition on December 5, 2022, Lawrence Livermore National Laboratory proved that recreating the “fire” that fuels the sun and the stars inside a laboratory on Earth was indeed scientifically possible.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Automated and Accelerated Continuum Model Development for Electrochemical Systems (Abbreviated Report)

Despite the availability of computational resources and advancements in numerical computing capabilities, the multiscale models core to understanding, predicting the behaviors of, and designing energy and environmental systems involving porous media are still 1.) developed through by-hand derivations and 2.) limited by many methodological assumptions employed during model derivation. As a result, the advancement of effective media models for engineering DOE mission-critical systems (e.g., batteries, flow batteries, electrolyzers, geothermal systems, subsurface chemical storage systems, etc.) is slow (i.e., it takes years for models to traverse from stages of “development” to “practical utilization”), hindering our ability to effectively optimize such systems and stay at the cutting-edge of the energy frontier. In this work, we aimed to address these limitations by 1.) automating and accelerating multiscale model derivation via symbolic computing and 2.) develop a novel multiscale modeling methodology for flow and transport through porous media that avoids the typical assumptions hindering previous models. As a result of our efforts, we 1.) developed a hybrid symbolic-numeric code called Fouriera for fully-automating the implementation of multiphysical and phase-field models via the Fourier spectral method for materials science research, and 2.) advanced a multiscale modeling methodology called The Method of Finite Averages that rigorously predicts the behaviors of flow and transport through heterogeneous porous media under the influence of non-local effects and strong advection. Ultimately, these deliverables provide strong foundations from which further efforts can advance multiscale modeling tools and capabilities that do not intrinsically rely on 1.) the speed and mathematical capabilities of humans, nor 2.) the methodological assumptions limiting current models.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Thermoelectric Materials of the Future

today, more than ever before, means must be found to apply the full power of modern materials science to the important problem of efficient and environmentally friendly energy conversion devices.

generation Kondo materials thin-films quantum well↗
DOE OSTI2026

Predictive Chemical Kinetic Modeling: Where We Succeed, Where We Struggle, and What Comes Next

Chemical kinetic modeling plays a foundational role in fields ranging from energy to environmental science, pharmaceuticals, and advanced materials. The past two decades have seen remarkable progress, particularly in modeling gas-phase reactions for thermochemical processes, leading to impactful industrial applications such as steam cracking and air quality management. However, new challenges are emerging. The successful development of systematic methodologies for the description of gas-phase kinetics opens the possibility to apply the same approach to the study of more challenging systems. Here, we review recent advances, including ab initio transition state theory-based master equation estimation of elementary rates, automated mechanism generation, machine-learning-assisted kinetics, and uncertainty quantification, and discuss the advances needed to apply the same methodological approach in areas such as heterogeneous catalysis, electrochemistry, liquid-phase and solid-state reactivity, and multiscale model integration. We advocate for the development of targeted tools, especially methods that go beyond empirical tuning toward first-principles-based predictions. We highlight the need for accessible software and AIaugmented workflows to democratize modeling for industry and academia alike. In this perspective, we call attention to not only what has worked but also what remains unsolved, advocating to avoid overemphasizing successes in scientific works at the expense of realism. The next decade should focus on predictive capability, physical accuracy, and community infrastructure (e.g., databases and services) to enable innovation across diverse fields. We argue that kinetic modeling, properly equipped, can accelerate discovery far beyond its traditional domains.

ab initio calculations↗
DOE OSTI2022

Enhancing Lifetime and Reducing Costs for Fish Diversion Netting Structures (Abstract)

This effort will focus on technology transfer and commercialization of antifouling coatings with an enthusiastic and engaged industrial team. Environmental requirements and operational demands call for a nontoxic coating/paint to prevent fouling on fish passage guidance netting at hydropower facilities. For example, one netting customer estimated the capital cost for compliance at $\$12$ million to $\$15$ million. This project will build partnerships between PNNL and private companies to optimize, demonstrate, mature, and commercialize a novel PNNL-developed technology that addresses this critical coating need of the hydropower industry. This effort will support modification of existing coatings for application to flexible netting structures. Industrial partners include commercial coating development specialist (Lorama), hydrophobic material manufacturer and paint developer (Dry Surface Technologies), aquatic applications specialists (Prometheus Innovations and River Connectivity Systems), and hydropower netting producer (Pacific Netting Products). Engagement with the U.S. Army Corps of Engineers (USACE) and Bureau of Reclamation (BOR), two hydropower operators, throughout the project will provide expertise and field test sites that will provide crucial proof of real-world performance data (additional details provided in Teaming section). Taylor Shellfish Farms will provide organisms and fouling expertise as well as a perspective of potential broader impacts for the blue economy. Sample netting will demonstrate performance in a range of environments for key hydropower applications. PNNL will work with industrial partners to overcome commercialization barriers as well as resolving any manufacturing or regulatory issues. This Phase 1 effort is focused on technology optimization for application to fish passage guidance netting and technology validation as verified by independent testing (through USACE, BOR, Taylor Shellfish and Prometheus Innovations). Through this effort, SLIC will be demonstrated for netting applications at technology readiness level (TRL) 5. The field test data will allow optimization of SLIC formulation and performance which is key to enabling technology transfer of a mature proven technology to industry and production of a viable commercial product specifically focused for hydropower needs.

13 HYDRO ENERGY↗
DOE OSTI2020

Molecular-scale origins of wettability at petroleum–brine–carbonate interfaces

Wettability control of carbonates is a central concept for enhanced petroleum recovery, but a mechanistic understanding of the associated molecular-scale chemical processes remains unclear. We directly probe the interface of calcium carbonate (calcite) with natural petroleum oil, synthetic petroleum analogues, and aqueous brines to understand the molecular scale behavior at this interface. The calcite–petroleum interface structure is similar whether or not calcite was previously exposed to an aqueous brine, and is characterized by an adsorbed interfacial layer, significant structural changes within the calcite surface, and increased surface roughness. No evidence for an often-assumed thin-brine wetting layer at the calcite–petroleum interface is observed. These features differ from those observed at the calcite–brine interface, and for parallel measurements using model synthetic petroleum mixtures (consisting of representative components, including dodecane, toluene, and asphaltene). Changes to the interface after petroleum displacement by aqueous brines are also discussed.

02 PETROLEUM↗
DOE OSTI2021

On-device lead absorbing tapes for sustainable perovskite solar cells

Perovskite solar cells are a promising technology that could facilitate and accelerate the energy transition to a sustainable future. However, the toxicity of Pb remains one of the obstacles impeding their commercialization. Here we apply on-device tapes to absorb leaked lead from damaged devices. Furthermore, our chemical approach can capture over 99.9% of leakage without compromising the performance and operation.

14 SOLAR ENERGY↗
DOE OSTI2026

In situ transmission electron microscopy observations of CaCO 3 crystallization onto polysaccharide-coated nanoparticles

Polysaccharides and proteoglycans are widely associated with the organic matrix at sites of CaCO 3 biomineralization, and previous studies indicate that these macromolecules may confer greater roles in mineral nucleation than previously recognized. This investigation uses in situ liquid-phase transmission electron microscopy (LP-TEM) to observe CaCO 3 nucleation onto aminated silica (SiO 2 –NH 3 + ) nanoparticles treated with a layer of chitosan (near-neutral derivative of chitin) or heparin (a carboxylated and highly sulfated glycosaminoglycan). In the absence of polysaccharides, few CaCO 3 particles formed and exhibited mobility. However, the SiO 2 –NH 3 + nanoparticles were enveloped in a region of higher mass density relative to the bulk solution, suggesting the development of a local solute-rich environment that surrounds the charged NH 3 + groups. The heparin- or chitosan-coated silica particles also exhibited regions of higher mass density around the nanoparticles. In the presence of these polysaccharide coatings, we observed the nucleation of abundant CaCO 3 particles whereby the polyanionic heparin promoted more nucleation than the weakly cationic chitosan. Many crystallites appeared to form at the polysaccharide–TEM cell membrane–solution interface, further indicating interfacial and macromolecule-specific control on crystallization. The combined results demonstrate that chitosan and heparin have an appreciable effect on the timing, size, and location of CaCO 3 nucleation compared to the polysaccharide-free nanoparticles.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Albedo Measurement of the Terra Pave White Albedo Product: Cooperative Research and Development Final Report

The Terra Pave team is creating an eco-friendly, cost-effective road coating that controls dust and dirt on high-traffic roads near solar field installations to reduce the dirt cover on panels, which lowers energy output. The Terra Pave White Albedo product also has the capability to increase the amount of solar radiation reflected from the ground to the backside of bifacial PV modules, thereby increasing the amount of electricity generated. This work will quantify the amount of solar radiation reflected from the Terra Pave White albedo product by measuring its albedo, which is the ratio of the reflected radiation to the incoming radiation. Albedo is measured with two horizontal pyranometers with one ground-facing and the other sky-facing.

14 SOLAR ENERGY↗
DOE OSTI2023

Cost and Life Cycle Analysis for Deep CO 2 Emissions Reduction for Steel Making: Direct Reduced Iron Technologies

Among heavy industrial sectors worldwide, the steel industry ranks first in carbon dioxide (CO 2 ) emissions. Technologies that produce direct reduced iron (DRI) enable the industry to reduce emissions or even approach net‐zero CO 2 emissions for steel production. Herein, comprehensive cradle‐to‐gate (CTG) life cycle analysis (LCA) and techno‐economic analysis (TEA) are used to evaluate the CO 2 emissions of three DRI technologies. Compared to the baseline of blast furnace and basic oxygen furnace (BF–BOF) technology for steel making, using natural gas (NG) to produce DRI has the potential to reduce CTG CO 2 emissions by 33%. When 83% or 100% renewable H 2 is used for DRI production, DRI technologies can potentially reduce CO 2 emissions by 57% and 67%, respectively, compared to baseline BF–BOF technology. However, the renewable H 2 application for DRI increases the levelized cost of steel (LCOS). When renewable natural gas (RNG) and clean electricity are used for steel production, the CTG CO 2 emissions of all the DRI technologies can potentially be reduced by more than 90% compared to the baseline BF–BOF technology, although the LCOS depends largely on the cost of RNG and clean electricity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗