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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 415 records · Page 23

Predicting the formation of fractionally doped perovskite oxides by a function-confined machine learning method

Abstract Fractionally doped perovskites oxides (FDPOs) have demonstrated ubiquitous applications such as energy conversion, storage and harvesting, catalysis, sensor, superconductor, ferroelectric, piezoelectric, magnetic, and luminescence. Hence, an accurate, cost-effective, and easy-to-use methodology to discover new compositions is much needed. Here, we developed a function-confined machine learning methodology to discover new FDPOs with high prediction accuracy from limited experimental data. By focusing on a specific application, namely solar thermochemical hydrogen production, we collected 632 training data and defined 21 desirable features. Our gradient boosting classifier model achieved a high prediction accuracy of 95.4% and a high F1 score of 0.921. Furthermore, when verified on additional 36 experimental data from existing literature, the model showed a prediction accuracy of 94.4%. With the help of this machine learning approach, we identified and synthesized 11 new FDPO compositions, 7 of which are relevant for solar thermochemical hydrogen production. We believe this confined machine learning methodology can be used to discover, from limited data, FDPOs with other specific application purposes.

08 HYDROGEN↗

Trash-to-Gas: Converting Space Trash into Useful Products

NASA's Logistical Reduction and Repurposing (LRR) project is a collaborative effort in which NASA is determined to reduce total logistical mass through reduction, reuse and recycling of various wastes and components of long duration space missions and habitats. LRR is focusing on four distinct advanced areas of study: Advanced Clothing System, Logistics-to-Living, Heat Melt Compactor and Trash to Supply Gas (TtSG). The objective of TtSG is to develop technologies that convert material waste, human waste and food waste into high-value products. High-value products include life support oxygen and water, rocket fuels, raw material production feedstocks, and other energy sources. There are multiple pathways for converting waste to products involving single or multi-step processes. This paper discusses thermal oxidation methods of converting waste to methane. Different wastes, including food, food packaging, Maximum Absorbent Garments (MAGs), human waste simulants, and cotton washcloths have been evaluated in a thermal degradation reactor under conditions promoting pyrolysis, gasification or incineration. The goal was to evaluate the degradation processes at varying temperatures and ramp cycles and to maximize production of desirable products and minimize high molecular weight hydrocarbon (tar) production. Catalytic cracking was also evaluated to minimize tar production. The quantities of CO2, CO, CH4, and H2O were measured under the different thermal degradation conditions. The conversion efficiencies of these products were used to determine the best methods for producing desired products.

Caraccio, Anne J.↗

Trash to Gas: Converting Space Trash into Useful Products

NASA's Logistical Reduction and Repurposing (LRR) project is a collaborative effort in which NASA is determined to reduce total logistical mass through reduction, reuse and recycling of various wastes and components of long duration space missions and habitats. LRR is focusing on four distinct advanced areas of study: Advanced Clothing System, Logistics-to-Living, Heat Melt Compactor and Trash to Supply Gas (TtSG). The objective of TtSG is to develop technologies that convert material waste, human waste and food waste into high-value products. High-value products include life support oxygen and water, rocket fuels, raw material production feedstocks, and other energy sources. There are multiple pathways for converting waste to products involving single or multi-step processes. This paper discusses thermal oxidation methods of converting waste to methane. Different wastes, including food, food packaging, Maximum Absorbent Garments (MAGs), human waste simulants, and cotton washcloths have been evaluated in a thermal degradation reactor under conditions promoting pyrolysis, gasification or incineration. The goal was to evaluate the degradation processes at varying temperatures and ramp cycles and to maximize production of desirable products and minimize high molecular weight hydrocarbon (tar) production. Catalytic cracking was also evaluated to minimize tar production. The quantities of C02, CO, CH4, and H20 were measured under the different thermal degradation conditions. The conversion efficiencies of these products were used to determine the best methods for producing desired products.

Trash-to-Gas↗

Data processing methods and data acquisition for samples larger than the field of view in parallel-beam tomography

Parallel-beam tomography systems at synchrotron facilities have limited field of view (FOV) determined by the available beam size and detector system coverage. Scanning the full size of samples bigger than the FOV requires various data acquisition schemes such as grid scan, 360-degree scan with offset center-of-rotation (COR), helical scan, or combinations of these schemes. Though straightforward to implement, these scanning techniques have not often been used due to the lack of software and methods to process such types of data in an easy and automated fashion. The ease of use and automation is critical at synchrotron facilities where using visual inspection in data processing steps such as image stitching, COR determination, or helical data conversion is impractical due to the large size of datasets. Here, we provide methods and their implementations in a Python package, named Algotom, for not only processing such data types but also with the highest quality possible. The efficiency and ease of use of these tools can help to extend applications of parallel-beam tomography systems.

36 MATERIALS SCIENCE↗

Polymer Solar Cells with 18.74% Efficiency: From Bulk Heterojunction to Interdigitated Bulk Heterojunction

The most popular approach to fabricating organic solar cells (OSCs) is solution processing a mixture of donor (D) and acceptor (A) materials into an active layer with a bulk heterojunction (BHJ) nanostructure. In this work, it is demonstrated that the interdigitated heterojunction (IHJ) is a more suitable nanostructure of the active layer for high-performance OSCs whereas it is a long standing challenge to realize well-defined IHJ structures. Here, a facile and versatile sequential solution processing method is developed to produce an IHJ nanostructure with power conversion efficiency reaching 18.74% (18.10% for BHJ the counterpart) by fabricating a donor film with nanopores created by a wax additive, sequentially casting the acceptor on top of infiltrating the nanopores. Compared to the BHJ, the IHJ structure with an interpillar distance within the exciton diffusion length can afford a large bulk D/A interface for efficient exciton dissociation with a minimized charge recombination while free electrons and holes can transport to the respective electrodes through more straightforward pathways, thus enhance performance. Furthermore, the D or A phase in the IHJ device contacts with only one electrode, which can prevent shunting between the anode and cathode and facilitate the industrial mass production of OSCs.

36 MATERIALS SCIENCE↗

Application of ultrathin TiO 2 layers in solar energy conversion devices

Abstract A vital pursuit in solar energy research is to achieve high efficiency and long‐term stability in energy conversion devices. Coating or sandwiching an ultrathin layer of TiO 2 onto active solar components has been demonstrated to be a remarkably effective and facile strategy to improve their stability. The TiO 2 film acts as a protection layer and enhances solar energy conversion efficiency by passivating surface recombination sites or facilitating electron transport. To date, numerous efforts have been devoted to applying ultrathin TiO 2 layers in various kinds of solar energy conversion devices. In this study, we review deposition techniques, characterization methods of the resulting ultrathin TiO 2 layer, as well as its applications in dye‐sensitized solar cells, organic–inorganic hybrid solar cells, and photoelectrochemical cells.

36 MATERIALS SCIENCE↗

Precise Colloidal Plasmonic Photocatalysts Constructed by Multistep Photodepositions

Natural photosynthesis relies on a sophisticated charge transfer pathway among multiple components with precise spatial, energetic, and temporal organizations in the aqueous environment. It continues to inspire and challenge the design and fabrication of artificial multicomponent colloidal nanostructures for solar-to-fuel conversion. Herein, we introduce a plasmonic photocatalyst synthesized with colloidal methods with five integrated components including cocatalysts installed in orthogonal locations. The precise deposition of individual inorganic components on an Au/TiO 2 nanodumbell nanostructure is enabled by photoreduction and photo-oxidation, which selectively occurs at the TiO 2 tip sites and Au lateral sites, respectively. Under visible-light irradiation, the photocatalyst exhibited activity of oxygen evolution from water without scavengers. Here, we demonstrate that each component is essential for improving the photocatalytic performance. In addition, mechanistic studies suggest that the photocatalytic reaction requires combining the hot charge carriers derived from exciting both the d-sp interband transition and the localized surface plasmon resonance of Au.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Hydrogen Production from Polyethylene Pyrolysis

Hydrogen is anticipated to play a pivotal role in the future of clean energy and decarbonization efforts, serving as an energy storage medium, a power generation source, and a clean fuel for transportation. While most hydrogen is produced from carbonaceous fossil feedstocks like natural gas, petroleum, and coal, there is growing interest in using refuse-derived fuels such as waste plastics and municipal solid waste (MSW) as alternative feedstocks. Thermochemical processes such as pyrolysis and catalytic cracking can convert nonrecyclable plastics and organic MSW components to produce hydrogen with lower life cycle greenhouse gas emissions when coupled with CO 2 capture. Such approaches not only address waste-management challenges but also reduce methane emissions from landfills. Furthermore, waste feedstocks are low cost and can support meeting demands for hydrogen across various industries. In this work we examined production of hydrogen from high-density polyethylene (HDPE) as a model polymer using pyrolysis. Analytical studies of pyrolysis utilizing gas chromatography–mass spectrometry (GC/MS) provide insights into conversion pathways for plastic waste, potentially reducing the environmental footprint of traditional hydrogen production methods. This work generates a baseline methodology for hydrogen production from plastic pyrolysis with and without a catalyst and the necessary product distribution baseline from key single plastics. The effect of pyrolysis temperature on the conversion of HDPE was evaluated both with and without a catalyst(s), and the product distributions measured via GC/MS were identified and hydrogen formation was quantified. These results will help guide future research efforts to optimize catalysts and processes for more efficient hydrogen production and mixed plastic waste management.

Catalysts↗

Synthesis pathways to thin films of stable layered nitrides

Controlled synthesis of metastable materials away from equilibrium is of interest in materials chemistry. Thin-film deposition methods with rapid condensation of vapour precursors can readily synthesize metastable phases but often struggle to yield the thermodynamic ground state. Growing thermodynamically stable structures using kinetically limited synthesis methods is important for practical applications in electronics and energy conversion. Here, in this study, we reveal a synthesis pathway to thermodynamically stable, ordered layered ternary nitride materials, and discuss why disordered metastable intermediate phases tend to form. We show that starting from elemental vapour precursors leads to a 3D long-range-disordered MgMoN 2 thin-film metastable intermediate structure, with a layered short-range order that has a low-energy transformation barrier to the layered 2D-like stable structure. This synthesis approach is extended to ScTaN 2 , MgWN 2 and MgTa 2 N 3 , and may lead to the synthesis of other layered nitride thin films with unique semiconducting and quantum properties.

36 MATERIALS SCIENCE↗

An intermediate model for fitting triplet–triplet annihilation in phosphorescent organic light emitting diode materials

Triplet–triplet annihilation (TTA) is one of the primary contributors to efficiency roll-off and permanent material degradation in phosphorescent organic light-emitting diodes. Here, the two limiting case models typically used to quantify this quenching mechanism are multi-step Dexter and single-step Förster, which, respectively, assume ideal Fickian diffusion or perfect trapping of triplet excitons. For device-relevant guest doping levels (typically 5–12 vol. %), both significant diffusion of excitons and trapping due to spatial and energetic disorder exist, so neither conventional model fits experimental data well. We develop and validate an intermediate TTA model, which is a weighted average of the limiting cases of pure radiative decay (no TTA) and multi-step Dexter based TTA that returns an effective TTA rate constant and a parameter quantifying the portion of well-isolated excitons. Kinetic Monte-Carlo simulations and time-resolved photoluminescence measurements of an archetype host–guest system demonstrate that our intermediate model provides significantly improved fits with more realistic physical values, is more robust to variations in experimental conditions, and provides an analysis framework for the effects of trapping on TTA.

30 DIRECT ENERGY CONVERSION↗

Correlating electronic properties with M-site composition in solid solution Ti y Nb 2- y CT x MXenes

High electrical conductivity is desired in MXene films for applications such as electromagnetic interference shielding, antennas, and electrodes for electrochemical energy storage and conversion applications. Due to the acid etching-based synthesis method, it is challenging to deconvolute the relative importance that factors such as chemical composition and flake size contribute to resistivity. To understand the intrinsic and extrinsic contributions to the macroscopic electronic transport properties, a systematic study controlling compositional and structural parameters was conducted with eight solid solutions in the Ti y Nb 2-y CT x system. Here, in particular, we investigated the different roles played by metal (M)-site composition, flake size, and d-spacing on macroscopic transport. Hard x-ray photoemission spectroscopy and spectroscopic ellipsometry revealed changes to electronic structure induced by the M-site alloying. Consistent with the spectroscopic results, the low- and room-temperature conductivities and effective carrier mobility are correlated with the Ti content, while the impact of flake size and d-spacing is most prominent in low-temperature transport. The results provide guidance for designing and engineering MXenes with a wide range of conductivities.

36 MATERIALS SCIENCE↗

Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators

Dilute combustion using exhaust gas recirculation (EGR) presents a cost-effective method for increasing the efficiency of spark-ignition (SI) engines. However, the maximum amount of EGR that can be used at a given condition is limited by a rapid increment of cycle-to-cycle variability (CCV). This study describes a methodology to design a model-based stochastic optimal controller to adjust the cycle-to-cycle fuel injection quantity in order to reduce CCV and further extend the dilute limit. Given the complexity and chaotic nature of combustion events, the controller was enhanced with online learning in order to identify the statistical properties of combustion efficiency, which are needed to generate predictions for next-cycle events. This study showed that a kernel density estimator (KDE) can be used to learn the combustion properties in real time and can be incorporated into the feedback policy in order to calculate the optimal control command. Experimental results suggested that the dilute limit can be extended from 18.5% to 21% EGR fraction at an operating condition relevant for highway cruising. Additionally, the proposed controller can achieve a large CCV reduction with less fuel enrichment compared to previous methods, overall contributing to an increase in 0.2% indicated fuel conversion efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Sulfur Pellets Responses to a Bare and Steel Reflected Pulse of the Oak Ridge National Laboratory Health Physics Research Reactor

The experiments analyzed in this report were conducted at the Health Physics Research Reactor (HPRR), also known as the $\textit{Fast Burst Reactor}$. The reactor was designed and built at Oak Ridge National Laboratory (ORNL) in 1961. The HPRR was an unmoderated, unshielded fast reactor that used highly enriched uranium and molybdenum alloy as fuel. The reactor was initially sent to the Nevada Test Site in 1962, where it was used to evaluate radiation doses received as a result of the Hiroshima and Nagasaki bombings during World War II. A few years later, the reactor was sent back to ORNL to be part of the Dosimetry Application Research (DOSAR) facility shown in Figure 1, which included a reactor building shown on the left (west) of the picture and a control and laboratory building in the upper right corner (northeast). The critical assembly was used for numerous technical studies, including systems calibration, dosimetry, radiobiology of plants and animals, testing of radiation alarms, as well as teaching and training in radiation dosimetry and nuclear engineering. Between 1963 and 1987, the HPRR was operated for thousands of hours, achieving criticality close to 10,000 times and motivating many publications. The HPRR was decommissioned in 1987. The goal of this effort was to use historical data from operation of the HPRR to create a criticality accident alarm system (CAAS) benchmark to be included in the $\textit{International Handbook of Evaluated Criticality Safety Benchmark Experiments}$ (ICSBEP Handbook). A thorough inspection was performed of all available documentation and information available. The most promising experiments that were selected for evaluation were those described in the 1987 ORNL report entitled $\textit{Health Physics Research Reactor Reference Dosimetry}$, ORNL-6240. The report includes reference dosimetry results of the shielded and unshielded configurations of the HPRR after burst operations. Because of changes to the reactor positioning and storage systems that were made in 1985, the previous dosimetry reports became obsolete, and the newly designed experiments were needed to create the HPRR’s adjusted dosimetry data. The various results reported in ORNL-6240 include reference doses and dose equivalents from different conventions at different distances and elevations as determined using the detected neutron fluence and conversion factors. The HPRR neutron fluence was obtained through different methods, including sulfur pellet analysis and threshold detector unit data. Information about the HPRR spectrum was also obtained through Bonner sphere measurements. This benchmark is focused on a part of the measured sulfur fluences reported in Appendix H of ORNL-6240. Standard commercial sulfur pellets were placed at different distances from the HPRR centerline during burst operation and were activated due to the 32 S(n,p) 32 P reaction. The resulting 32 P activity was then measured and the information about the corresponding sulfur fluence and/or neutron dose could be extracted. Many of those measurements have 7 been performed with the HPRR in its bare configuration or with different shields (combinations of Lucite, concrete, steel). All the necessary, precise information about material and/or dimensions of the different shields was not found, so it was decided to focus only on the unshielded and steel-shielded configurations to minimize the benchmark uncertainty. A total of 31 cases (24 unshielded and 7 shielded cases at different positions) of sulfur fluence were selected before evaluation to develop the benchmark.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SECARB-USA: Data Quality Methodology

SECARB-USA Deliverable 4.2.1 utilizes the outputs from the Needs Assessment (Subtask 2.1) to develop a data quality methodology. Many types of data are needed to evaluate a site for technical and financial viability. Several inventories of data types have been produced (for example NETL, 2010). The objective here is to organize the data types so that the needs met are specified. From this cross index (Table 1 in the Appendix), it will be possible in future tasks to (1) determine, on a site-specific basis, how much of each data type is required at each stage of a project to meet the need, and conversely (2) to further specify and define the data collection methods applied such that the data are tailored to fit that need. Derivative tables can then be developed to semi-quantitively evaluate the extent to which need is critical for early go/no-go decision points, or if it is more important than average, requiring faster or larger capitalization and spend to meet the need. In an additional step, the current availability of data for a site can be semi-quantitively assessed. From the table of data criticality and the table of data availability, site-specific cost for meeting the data needs can be determined, and allow a pre-permit spend estimated for a portfolio of projects.

54 ENVIRONMENTAL SCIENCES↗

Genetic programming for interpretable, data-driven continuum damage models.

The damage mechanisms that lead to failure in engineering alloys have been studied extensively, but converting this knowledge into constitutive models that are suitable for engineering-scale analysis remains a challenge. Evolution laws for continuum damage have been developed in the past and have proven effective but suffer from many non-physical assumptions that inhibit the overall accuracy of the model. Further, the assumptions inherent in these existing models prevent them from being applicable to a broad class of materials. At the same time, computational models of fine-scale damage mechanisms continue to advance making it tractable to generate large training data sets through computer simulation. Data-driven machine learning approaches can leverage these data sets to avoid making limiting assumptions, and instead produce models directly from the results of microstructural simulations and/or experiments. Many of these machine learning approaches are rapid and accurate, but they offer little to no insight into the underlying relationships among state variables being discovered. Conversely, genetic programming symbolic regression (GPSR) is a machine learning method that produces analytic expressions relating the state variables, allowing maximal insight and interpretability. To that end, we propose using GPSR as a data-driven method of obtaining microstructurally informed continuum damage models. Data is generated using microstructural simulations of damage evolution, parameterized over microstructural statistics (i.e., pore shape) and nominally applied deformations. Analytic expressions for damage evolution are obtained from the data using GPSR, and these expressions are then utilized within a continuum constitutive model. Overall, this approach is a promising method of automatically obtaining analytic relations describing constitutive phenomena in a material.

Buche, Michael Robert↗

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Data Quality Methodology (4.2.1)

SECARB-USA Deliverable 4.2.1 utilizes the outputs from the Needs Assessment (Subtask 2.1) to develop a data quality methodology. Many types of data are needed to evaluate a site for technical and financial viability. Several inventories of data types have been produced (for example NETL, 2010). The objective here is to organize the data types so that the needs met are specified. From this cross index (Table 1 in the Appendix), it will be possible in future tasks to (1) determine, on a site-specific basis, how much of each data type is required at each stage of a project to meet the need, and conversely (2) to further specify and define the data collection methods applied such that the data are tailored to fit that need. Derivative tables can then be developed to semi-quantitively evaluate the extent to which need is critical for early go/no decision points, or if it is more important than average, requiring faster or larger capitalization and spend to meet the need. In an additional step, the current availability of data for a site can be semi-quantitively assessed. From the table of data criticality and the table of data availability, site-specific cost for meeting the data needs can be determined, and allow a pre-permit spend estimated for a portfolio of projects. All of the data needs to evaluate a site are somewhat interconnected. We used criterion (2) above to determine if the data collection design would have to be modified to meet the need; if this was commonly true a linkage was shown. The application of this cross index to sites in the subsequent tasks will demonstrate that the demand for data types varies site-to-site and project-to-project. Examples of factors to be considered are the complexity of the geology, the injection goals such as rate and duration of the injection, and the types of risk and risk tolerance of key stakeholders. In future tasks the team will compare the demand for data with existing data availability. This will, in turn, determine when data needs to be acquired to support project development. For example, in a project area with complex structure, 3-D seismic data may be needed earlier and more urgently than in an area with simple rock body geometries. In some locations, a 3-D seismic survey has already been collected and can be purchased. In other locations the project developer will need to collect these data. For another example, a project near an urban area or near to a park may generate earlier and more substantive public concern than a site that is developed in mined lands. A calculation using the derivative from table 1 will show the different investment needs. Project cost will vary corresponding to data criticality and data availability.

42 ENGINEERING↗

Cognitive information processing

Cognitive information processing studies of digital and PCM picture and signal transmission systems, and methods for tactile display reading and magnetic tape to Braille conversion

DIGITAL TRANSDUCER↗