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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Collaboration on SBIR/TTO Phase II Project for Optical QC Device and Collaboration on SBIR/TTO Phase II-b Project for Advanced Quality Inspection Device Development: Cooperative Research and Development CRADA Number CRD-16-00652 (Final Report)

The overall goal of this program is to develop and commercialize a turnkey quality control solution for the entire PEM fuel cell manufacturing process including membrane, gas diffusion layers, catalyst, and assembled systems. This quality control solution is unique to each customer’s specific needs but includes a suite of in-line quality control systems for roll-to-roll manufacturing that can target thin, transparent membrane as well as opaque membrane, catalyst, and GDLs. The Phase II developed the CPNUVV system for thin, transparent membrane that operates using polarized filters to enhance defect resolution and determine thickness. However, PEM material manufacturers want a complete, turnkey solution for all components of the PEM fuel cell. In the Phase IIB, Mainstream will partner with NREL, and transition reflectance technology NREL developed (US Patent 9,234,843) to operate in real-time on a web-line to develop a total solution to PEM quality control. The device will identify and mark defects as well as monitor materials thickness in real-time to improve line efficiency and to reduce waste. The research performed at NREL under this CRADA increases the basis of knowledge about optical inspection methods, how they perform with regards to fuel cell component materials, and how they can be implemented in in-line, real-time configurations to provide quality inspection for roll-to-roll (R2R) manufacturing. Methods explored were found to be sensitive to catalyst loading in electrodes on both membrane and gas diffusion media substrates and to membrane thickness, across a broad range of thickness. The latter capability is novel and now patented and provides a previously unstudied and undemonstrated capability for R2R manufacturing of membranes.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2015

Liquid-phase-deposited siloxane-based capping layers for silicon solar cells

We apply non-vacuum processing to deposit dielectric capping layers on top of ultrathin atomic-layer-deposited aluminum oxide (AlO{sub x}) films, used for the rear surface passivation of high-efficiency crystalline silicon solar cells. We examine various siloxane-based liquid-phase-deposited (LPD) materials. Our optimized AlO{sub x}/LPD stacks show an excellent thermal and chemical stability against aluminum metal paste, as demonstrated by measured surface recombination velocities below 10 cm/s on 1.3 Ωcm p-type silicon wafers after firing in a belt-line furnace with screen-printed aluminum paste on top. Implementation of the optimized LPD layers into an industrial-type screen-printing solar cell process results in energy conversion efficiencies of up to 19.8% on p-type Czochralski silicon.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Developing a laser shockwave model for characterizing diffusion bonded interfaces

The US National Nuclear Security Agency has a Global Threat Reduction Initiative (GTRI) with the goal of reducing the worldwide use of high-enriched uranium (HEU). A salient component of that initiative is the conversion of research reactors from HEU to low enriched uranium (LEU) fuels. An innovative fuel is being developed to replace HEU in high-power research reactors. The new LEU fuel is a monolithic fuel made from a U-Mo alloy foil encapsulated in Al-6061 cladding. In order to support the fuel qualification process, the Laser Shockwave Technique (LST) is being developed to characterize the clad-clad and fuel-clad interface strengths in fresh and irradiated fuel plates. LST is a non-contact method that uses lasers for the generation and detection of large amplitude acoustic waves to characterize interfaces in nuclear fuel plates. However, because the deposition of laser energy into the containment layer on a specimen's surface is intractably complex, the shock wave energy is inferred from the surface velocity measured on the backside of the fuel plate and the depth of the impression left on the surface by the high pressure plasma pulse created by the shock laser. To help quantify the stresses generated at the interfaces, a finite element method (FEM) model is being utilized. This paper will report on initial efforts to develop and validate the model by comparing numerical and experimental results for back surface velocities and front surface depressions in a single aluminum plate representative of the fuel cladding.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Mode conversion in cold low-density plasma with a sheared magnetic field

Here, a theory is proposed that describes mutual conversion of two electromagnetic modes in cold low-density plasma, specifically, in the high-frequency limit where the ion response is negligible. In contrast to the classic (Landau–Zener-type) theory of mode conversion, the region of resonant coupling in low-density plasma is not necessarily narrow, so the coupling matrix cannot be approximated with its first-order Taylor expansion; also, the initial conditions are set up differently. For the case of strong magnetic shear, a simple method is identified for preparing a two-mode wave such that it transforms into a single-mode wave upon entering high-density plasma. The theory can be used for reduced modeling of wave-power input in fusion plasmas. In particular, applications are envisioned in stellarator research, where the mutual conversion of two electromagnetic modes near the plasma edge is a known issue.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Characterization of Fe-6Si Soft Magnetic Alloy Produced by Laser-Directed Energy Deposition Additive Manufacturing

Abstract Commercial electrical steels, Fe-Si alloys with < 4 wt.% Si, are inexpensive and efficient materials for electrical power conversion. Further efficiency improvements require increasing the silicon concentration to 6 wt.%, at which point the material becomes brittle and difficult to form by conventional rolling and sheet fabrication methods. Additive manufacturing stands to overcome challenges with commercial manufacturing techniques by leveraging near-net-shape fabrication. The wide array of process conditions provides additive manufacturing with increased flexibility, enabling control over the microstructure and mechanical properties. This work explores the microstructures and magnetic properties of ring-shaped Fe-Si alloys produced using concentric and cross-hatch tool paths on a laser-directed energy deposition additive manufacturing system. Concentric-built samples exhibit elongated grain structures while cross-hatch-built samples comprise lower aspect ratio grain structures. Thermal finite element analysis simulations model the stress conditions produced by the different scan path geometries. Microhardness measurements probe the mechanical properties as a function of anneal temperature, providing a qualitative understanding of the intergranular defect density. Soft magnetic properties measured under quasistatic and AC conditions show frequency- and microstructure-dependent coercivity and permeability. Finally, analysis of the core loss quantifies how the build strategies and thermal treatments influence efficiency in electrical power conversion applications. Understanding the influences of scan path geometry and thermal treatment provides a pathway towards application of additively manufactured soft magnetic materials.

Adamczyk, Jesse M.↗
DOE OSTI2020

Modeling Photovoltaics Innovation and Deployment Dynamics

PV’s historically rapid cost reduction is exceptional among technologies. Further cost reductions could play a major role in increasing deployment in the future. To enable such cost reductions, new modeling frameworks are needed to understand the determinants of innovation in PV. In this project, we study the mechanisms driving PV module and system cost reductions, delving deeply into the specific technological innovations that have occurred in the past and the policies that encouraged them, and also opportunities for future cost reduction and widespread deployment. The project contributes new fundamental insight on the determinants of technological innovation by developing novel methods and insights that are generalizable and can therefore be applied to other technologies. The results will allow policy makers, engineers, and other stakeholders to better prioritize their efforts and investments in the future. The project is organized around four journal articles as described below. The first article [1] identifies ‘low-level’ (e.g. conversion efficiency improvement) and ‘high- level’ (e.g. R&D efforts) mechanisms of cost reduction in PV systems (Tasks 1-4). This work builds on a previous DOE grant, where we developed a framework for technological innovation leading to PV module cost reduction [2]. We advance a method to disentangle the contributions of physical (‘hardware’) and non-physical (‘soft technology’) changes. Our results uncover reasons behind the relatively slow evolution of soft technology and can inform new innovation approaches to these technologies. The second article [3] identifies specific engineering or institutional innovations that enabled the low-level mechanisms of cost reduction in PV module and balance-of-systems (BOS) (Tasks 5, 9, 10). We identify 85 innovations and connect them to the cost variables they affected. By developing an innovations typology, this study shows the differences between the types of innovations affecting PV modules and BOS components. Finally, by analyzing the industry origins of innovations, this study also finds that PV was well-positioned within an ecosystem of continuously advancing technologies. The third article [4] studies prospective cost reduction opportunities (Task 10). We explore how design approaches that emphasize standardization and automation, such as plug-and-play PV systems, can create cost reduction opportunities by reducing interactions and speeding up activities with high process costs. We show that this can lead to cost reduction in cost components with the most untapped opportunity for improvement such as installation labor, overhead, electrical BOS, and customer acquisition. The fourth article [5] analyzes how various policies supporting PV deployment and R&D contributed to PV’s cost improvement by enabling high-level mechanisms, specific innovations, and ultimately low-level mechanisms of cost reduction (Tasks 8, 13, 14). We investigate examples from different countries and connect these policies to quantifiable cost change mechanisms. Our study sheds light on the roles that different nations played over time, through a diverse set of policy approaches.

14 SOLAR ENERGY↗
DOE OSTI2015

Short-time dynamics of 2-thiouracil in the light absorbing S{sub 2}(ππ{sup ∗}) state

Ultrahigh quantum yields of intersystem crossing to the lowest triplet state T{sub 1} are observed for 2-thiouracils (2TU), which is in contrast to the natural uracils that predominantly exhibit ultrafast internal conversion to the ground state upon excitation to the singlet excited state. The intersystem crossing mechanism of 2TU has recently been investigated using second-order perturbation methods with a high-level complete-active space self-consistent field. Three competitive nonadiabatic pathways to the lowest triplet state T{sub 1} from the initially populated singlet excited state S{sub 2} were proposed. We investigate the initial decay dynamics of 2TU from the light absorbing excited states using resonance Raman spectroscopy, time-dependent wave-packet theory in the simple model, and complete-active space self-consistent field (CASSCF) and time dependent-Becke’s three-parameter exchange and correlation functional with the Lee-Yang-Parr correlation functional (TD-B3LYP) calculations. The obtained short-time structural dynamics in easy-to-visualize internal coordinates were compared with the CASSCF(16,11) predicted key nonadiabatic decay routes. Our results indicate that the predominant decay pathway initiated at the Franck-Condon region is toward the S{sub 2}/S{sub 1} conical intersection point and S{sub 2}T{sub 3} intersystem crossing point, but not toward the S{sub 2}T{sub 2} intersystem crossing point.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Electrochemical Electron Transfer and Proton-Coupled Electron Transfer: Effects of Double Layer and Ionic Environment on Solvent Reorganization Energies

Electron transfer and proton coupled electron transfer (PCET) reactions at electrochemical interfaces play an essential role in a broad range of energy conversion processes. The reorganization energy, which is a measure of the free energy change associated with solute and solvent rearrangements, is a key quantity for calculating rate constants for these reactions. We present a computational method for including the effects of the double layer and ionic environment of the diffuse layer in calculations of electrochemical solvent reorganization energies. This approach incorporates an accurate electronic charge distribution of the solute within a molecular-shaped cavity in conjunction with a dielectric continuum treatment of the solvent, ions, and electrode using the integral equations formalism polarizable continuum model. The molecule-solvent boundary is treated explicitly, but the effects of the electrode-double layer and double layer-diffuse layer boundaries, as well as the effects of the ionic strength of the solvent, are included through an external Green’s function. The calculated total reorganization energies agree well with experimentally measured values for a series of electrochemical systems, and the effects of including both the double layer and ionic environment are found to be very small. This general approach was also extended to electrochemical PCET and produced total reorganization energies in close agreement with experimental values for two experimentally studied PCET systems. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center, funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences.

Ghosh, Soumya↗
DOE OSTI2025

A case study in contrastive learning information combination: Application to technical forensics of additive manufacturing filament source identification

Combination of information from disparate data sources into a single decision is a core challenge in many fields, including the field of technical forensics. Technical forensics (TF) utilizes technical characterization of questioned samples to determine properties of that sample; these properties are then used to infer information of forensic interest, such as provenance, age, or attribution. TF is utilized in traditional forensic applications, such as the attribution of material fragments from an explosive, and in nuclear forensic applications, such as the attribution of actinides which have been interdicted out of regulatory control. The challenge of combining information from disparate sources, described alternately by many terms including “Data Fusion” and “Data Integration”, is exacerbated in the technical forensics domain due to at least two factors: the challenge of interpreting each information source singularly, and the relatively small data set sizes available. Extensive literature exists attempting to combine technical forensics information sources, both in manual and automated processes. These attempts are often bespoke to the specific information sources (such as the bi-, tri-, or quad-isotope chart (Moody, Grant, and Hutcheon 2005)), with some emerging examples of simple early- and late- fusion (, respectively). Simultaneous to the information combination efforts described in the previous paragraph, the field of natural language processing attempted (and largely succeeded) in combining information from multiple non-technical information sources. The ecosystem of “multi-modal” language models, which can take text and images as input, and generate text and images as output, became large and diverse by 2025 (Khan et al. 2025). In a generalized sense, many of these methods are trained by learning neural networks which can convert raw text or images into a vector of numbers describing the text or image, hereafter called “embeddings” and the neural networks performing the conversion are called “embedders”. By using a separate embedder for text and images, finding coincident text and images (such as images with their captions), and optimizing the parameters of the embedders such that the embeddings for the text and the image are similar, the field has found a bridge between text and images (Girdhar et al. 2023). It is the contention of the authors of this report that this insight is not limited to text and images but instead can be extended to any modality which can be found coincidently. The subject of the rest of this report is the application of this method to example multi-modal technical forensic data. Some details about the data used in this report are not appropriate for this report, and are included in a companion report (PNNL-38669).

36 MATERIALS SCIENCE↗
DOE OSTI2015

Oxidation characteristics of gasoline direct-injection (GDI) engine soot: Catalytic effects of ash and modified kinetic correlation

In this paper, experimental analyses are conducted into the GDI soot oxidation characteristics as dependent on engine operating conditions. Soot is sampled at various engine operating conditions of a commercial 2.4 L GDI engine with a naturally aspirated, homogeneous, and stoichiometric operation strategy. The oxidation reactivity, ash composition, and carbon nanostructure of the GDI soot samples are analyzed using thermogravimetric analysis (TGA), scanning electron microscope–energy-dispersive spectroscopy (SEM-EDS), high-resolution transmission electron microscopy (HR-TEM), and Raman spectroscopy. Based on the analyses, a global GDI soot oxidation mechanism is proposed which includes the effects of soluble organic fractions (SOF)/weakly bonded carbon (WBC), and three types of ash on GDI soot oxidation. The results show that GDI soot contains an order of magnitude higher ash fraction than does conventional diesel soot, and oxidation reactivity is significantly enhanced by the catalytic effects of ash, as a function of ash content in soot. A modified empirical kinetic correlation for GDI soot oxidation is suggested on the basis of the results, and the modified kinetic correlation predicts the GDI soot oxidation rate accurately for various engine operation points at wide ranges of soot conversion and temperature without modifying kinetic parameters. The kinetic parameters are determined from isothermal and non-isothermal thremogravimetric analysis (TGA) soot oxidation tests; the methods are elucidated in detail.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Emerging platforms for co-utilization of one-carbon substrates by photosynthetic organisms

One-carbon substrates have generated increasing attention as long-term sustainable feedstocks for biobased production of fuels and chemicals. However, their physicochemical properties present significant biological and operational challenges for commercial bioprocesses including kinetically slower substrate activation, high energetic cost of assimilation, low mass transfer, substrate toxicity, and low productivity titers. Several different routes including optimization of native pathways, synthetic pathways, and hybrid methods are being explored to overcome these challenges. Integration of emerging biological solutions with process improvements is enabling faster bioprocess development for cost-effective conversion of one-carbon substrates into fuels and chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Designing clay-polymer nanocomposite sorbents for water treatment: A review and meta-analysis of the past decade

Clay-polymer nanocomposites (CPNs) have been studied for two decades as sorbents for water pollutants, but their applicability remains limited. Our aim in this review is to present the latest progress in CPN research using a meta-analysis approach and identify key steps necessary to bridge the gap between basic research and CPN application. Based on results extracted from 99 research articles on CPNs and 8 review articles on other widely studies sorbents, CPNs had higher adsorption capacities for several inorganic and organic pollutant classes (including heavy metals, oxyanions, and dyes, n = 308 observations). We applied principal component analysis, analysis of variance, and multiple linear regressions to test how CPN and pollutant properties correlated with Langmuir adsorption model coefficients. While adsorption was, surprisingly, not influenced by mineral properties, it was influenced by CPN fabrication method, polymer functional groups, and pollutant properties. For example, among the pollutant classes, heavy metals had the highest adsorption capacity but the lowest adsorption affinity. Conversely, dyes had high adsorption affinities, as reflected by the linear correlation between adsorption affinity and pollutant molecular weight. Scaling from ‘basic research’ to ‘technological application’ requires testing CPN performance in real water, application in columns, comparison to commercial sorbents, regeneration, and cost evaluation. However, our survey indicates that of the 158 observations, only 20 compared the CPN's performance to that of a commercial sorbent. We anticipate that this review will promote the design of smart and functional CPNs, which can then evolve into an effective water treatment technology.

42 ENGINEERING↗
DOE OSTI2017

Chlorination of low-band-gap polymers: Toward high-performance polymer solar cells

Here, halogenation is an effective way to tune the energy levels of organic semiconducting materials. To date, fluorination of organic semiconducting materials to fabricate polymer solar cells (PSCs) has been used far more than chlorination; however, fluorine exchange reactions suffer from low yields and the resulting fluorinated polymer always comes with higher price, which will greatly hinder their commercial applications. Herein, we designed and synthesized a series of chlorinated donor-acceptor (D-A) type polymers, in which benzo[1,2-b:4,5- b]dithiophene and chlorinated benzothiadiazole units are connected by thiophene π-bridges with an asymmetric alkyl chain. These chlorinated polymers showed deep highest occupied molecular orbital energy levels, which promoted the efficiency of their corresponding PSCs by increasing the device open circuit voltage. The asymmetric alkyl chain on the thiophene moieties gave the final polymer sufficient solubility for solution processing and strong π-π stacking in films allowed for high mobility. Although the introduction of a large chlorine atom increased the torsion angle of the polymer backbone, the chlorinated polymers maintained high crystallinity and a favorable backbone orientation in the blended films. These factors contributed to respectable device performances from thick-film devices, which showed PCEs as high as 9.11% for a 250 nm-thick active layer. These results demonstrate that chlorination is a promising method to fine tune the energy levels of conjugated polymers, and chlorinated benzothiadiazole may be a versatile building block in materials for efficient solar energy conversion.

36 MATERIALS SCIENCE↗
DOE OSTI2017

High-Performance Flexible Perovskite Solar Cells on Ultrathin Glass: Implications of the TCO

For halide perovskite solar cells (PSCs) to fulfill their vast potential for combining low-cost, high efficiency, and high throughput production they must be scaled using a truly transformative method, such as roll-to-roll processing. Bringing this reality closer to fruition, the present work demonstrates flexible perovskite solar cells with 18.1% power conversion efficiency on flexible Willow Glass substrates. Here, we highlight the importance of the transparent conductive oxide (TCO) layers on device performance by studying various TCOs. And while tin-doped indium oxide (ITO) and indium zinc oxide (IZO) based PSC devices demonstrate high photovoltaic performances, aluminum-doped zinc oxide (AZO) based devices underperformed in all device parameters. Analysis of X-ray photoemission spectroscopy data shows that the stoichiometry of the perovskite film surface changes dramatically when it is fabricated on AZO, demonstrating the importance of the substrate in perovskite film formation.

14 SOLAR ENERGY↗
DOE OSTI2024

Unlocking the potential of biogas systems for energy production and climate solutions in rural communities

On-site conversion of organic waste into biogas to satisfy consumer energy demand has the potential to realize energy equality and mitigate climate change reliably. However, existing methods ignore either real-time full supply or methane escape when supply and demand are mismatched. Here, we show an improved design of community biogas production and distribution system to overcome these and achieve full co-benefits in developing economies. We take five existing systems as empirical examples. Mechanisms of synergistic adjusting out-of-step biogas flow rates on both the plant-side and user-side are defined to obtain consumption-to-production ratios of close to 1, such that biogas demand of rural inhabitants can be met. Furthermore, carbon mitigation and its viability under universal prevailing climates are illustrated. Coupled with manure management optimization, Chinese national deployment of the proposed system would contribute a 3.77% reduction towards meeting its global 1.5 °C target. Additionally, fulfilling others’ energy demands has considerable decarbonization potential.

09 BIOMASS FUELS↗
DOE OSTI2023

Performance characterization of freeform finished surfaces of potassium dihydrogen phosphate using fluid jet polishing with a nonaqueous slurry

Abstract Potassium dihydrogen phosphate (KDP) and its deuterated analog (DKDP) are unique nonlinear optical materials for high power laser systems. They are used widely for frequency conversion and polarization control by virtue of the ability to grow optical-quality crystals at apertures suitable for fusion-class laser systems. Existing methods for freeform figuring of KDP/DKDP optics do not produce surfaces with sufficient laser-induced–damage thresholds (LIDT’s) for operation in the ultraviolet portion of high-peak-power laser systems. In this work, we investigate fluid jet polishing (FJP) using a nonaqueous slurry as a sub-aperture finishing method for producing freeform KDP surfaces. This method was used to selectively polish surface areas to different depths on the same substrate with removals ranging from 0.16 μm to 5.13 μm. The finished surfaces demonstrated a slight increase in roughness as the removal depth increased along with a small number of fracture pits. Laser damage testing with 351 nm, 1 ns pulses demonstrated excellent surface damage thresholds, with the highest values in areas devoid of fracture pits. This work demonstrates, for the first time, a method that enables fabrication of a waveplate that provides tailored polarization randomization that can be scaled to meter-sized optics. Furthermore, this method is based on FJP technology that incorporates a nonaqueous slurry specially designed for use with KDP. This novel nonaqueous FJP process can be also used for figuring other types of materials that exhibit similar challenging inherent properties such as softness, brittleness, water-solubility, and temperature sensitivity.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning

Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.

Adsorption↗