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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

1987/88 Metropolitan Washington Council of Governments/National Capital Region Transportation Planning Board Home Interview Survey

The Metropolitan Washington Council of Governments/National Capital Region Transportation Planning Board periodically conducts regional household travel surveys to monitor changes in daily travel and to gather information on the demographic, socioeconomic, and trip-making characteristics of Washington, D.C.-area residents. Information collected in the 1987/88 Home Interview Survey was an important component in the development of regional travel demand forecasting models used to predict changes in daily travel in response to current development trends and changes in regional transportation policies and programs. The survey sampled 8,000 households residing in eight jurisdictions comprising the greater Washington, D.C. region (an approximately 1-in-166 sample).

1Hz data↗
DOE OSTI2021

Characterization and QC practice of 16-channel ADC ASIC at cryogenic temperature for Liquid Argon TPC front-end readout electronics system in DUNE experiment

ColdADC is a low-noise 16-channel analog-to-digital converter ASIC designed for cold readout electronics of Liquid Argon Time Projection Chambers (LArTPCs) in the Deep Underground Neutrino Experiment (DUNE). ColdADC was specifically designed for operation at cryogenic temperatures (77 K–89 K). Cold electronics is considered to be an enabling technology for liquid argon detectors in neutrino experiments. The main function of the chip is to digitize signals from the 16-channel charge-sensitive amplifier designed at BNL (LArASIC) and send digitized signals to the data aggregator and serializer chip (COLDATA). ColdADC operates with a resolution of 12 bits and a sampling rate of 2 MS/s per channel. A complete characterization of prototype chips was conducted at cryogenic temperature, involving power consumption, noise and linearity performance. In the first DUNE Far-Detector module, 384000 data channels will be read out, corresponding to 24000 ColdADC chips. Therefore, systematic testing of ColdADC chips at cryogenic temperature is vital for the quality and reliability of DUNE Single-Phase modules. We have developed a Quality Control (QC) test stand that includes ColdADC evaluation and characterization at cryogenic temperature. The QC procedure was applied to a first batch of 33 chips, corresponding to 528 data channels. The obtained results meet all the required DUNE specifications for ColdADC. Moreover, the testing outcome allowed us to identify possibilities of performance optimization that are currently being addressed in the design of the next version of the chip. The Quality Control procedure is proved to be successful and will be a reference design for future large-batch production testing of final ColdADC ASICs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Enhanced Sustainability in Treatment of Contaminated Metals for Clearance and Recycling - 20290

Cyclife Sweden AB has, for more than 30 years, provided metal treatment services to the domestic and international nuclear industry with the aim of creating value through metal clearance and recycling. These operations are to a large extent based on the concept that the materials, after pre-treatment, including decontamination, will be melted for clearance. During the melting process, some nuclides separate from the metal while the remaining radioactivity becomes fully homogenized in the metal bath and the resulting ingots, along with the samples taken before casting At a time when activities to fight Climate Challenge are in focus, any savings in energy consumption, in addition to the positive environmental effect of recycling metals back to industry, is more than welcome. If the clearance of certain metallic items can be achieved safely, without using melting, it is the environmentally preferred option provided it carries a reasonable cost. It is even better if an object can go through a decontamination and clearance process prior to re-use inside or outside the nuclear sector. Cyclife Sweden is currently investing in a direct clearance process, to be operated in parallel with the melting process. This new process is expected to be fully operational in the late summer of 2020 and includes pre-treatment, decontamination and heavily shielded clearance measurement installations. The treatment will also allow clearance measurements of larger objects without the need for segmentation, along with allowing objects composed of different materials, like electric motors can be accepted for treatment. This paper gives an overview of the circular economy aspects in a nuclear back-end context, the Cyclife approach to further implement a circular economy approach in the processes, Material Acceptance Criteria for treatment, the facility set-up for the new process and how the melting route and the direct route can be combined in an efficient industrial scale process. To put the new capabilities into perspective, the two different treatment and clearance approaches, i.e. direct clearance and melting, are to be compared. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Tracking the PACE of household energy usage: Energy usage impacts of projects financed through Property Assessed Clean Energy programs in California

This report examines the household-level energy impacts of residential property assessed clean energy (R-PACE) projects using normalized metered energy consumption methods. Our analysis covers projects that occurred through an R-PACE program between 2009 and 2017 and includes more than 25,000 electricity meters and 15,000 gas meters. We employ a comparison group, drawn from other R-PACE households with similar locational and usage characteristics whose projects were implemented at different times, to control for some non-project and non-weather factors that may impact energy use. We find that projects consisting of energy efficiency technologies save, on average, about 3% of household electricity usage and 3.5% of household gas usage. R-PACE financing, however, can be used to install central heating or air conditioning equipment for the first time. These projects would be expected to increase energy consumption. Since our data do not directly indicate which projects are new installations, we develop a simple algorithm for identifying them. Removing these inferred installation projects yields average savings of about 5% for electricity and 6% for gas for those households that remain in the sample. Given the mild California climate and the results of another study of similar California projects using similar methods, these results are in line with expectations. Solar PV projects yield large reductions in grid electricity use, averaging 69% of household consumption. We estimate that, collectively, all R-PACE projects installed in California through 2019 would generate annual reductions in grid-tied electricity consumption of 506 GWh (mostly due to solar PV) and gas consumption reductions of 2 million therms in a normal weather year. These impacts are equivalent to the electricity consumption of about 74,000 California households (including both efficiency and PV generation) and the gas consumption of about 4700 California households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Identifying Potential Geochemical and Microbial Impacts of Hydrogen Storage in a Deep Saline Aquifer

Hydrogen is valuable commodity and a promising energy carrier for variable energy production. Storage of hydrogen may occur through injection of hydrogen or a hydrogen/methane gas blend in subsurface reservoirs. However, the geochemical and biological reactions that may impact the stored hydrogen are not yet understood. Therefore, we collected samples from a deep storage aquifer located in the St. Peter Formation in southern Illinois. The reservoir material was primarily quartz with sulphur and iron deposits, while the major constituents of the fluid were chloride and sulphate. 16S rRNA gene amplicon sequencing revealed a low biomass microbial community that contained no obvious hydrogen-consuming bacteria. Next, we enriched a field sample to increase the biomass and completed a metagenomic analysis, finding a low number of genes present that are associated with hydrogen consumption. Then, we completed a series of reactor experiments under reservoir conditions with 15% H2/85% CH4 gas simulating a short-term hydrogen storage, high withdrawal scenario. We found minimal changes in the geochemistry or microbiology for the reactor experiments. This work suggests that short-term storage may be highly successful, although significant additional work needs to be completed in order to accurately evaluate the risks associated with long-term hydrogen storage scenarios. It is essential we continue to expand our understanding of the dynamics present in saline aquifers and provide new insights into how hydrogen storage may impact underground geological storage environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A High-Granularity Approach to Modeling Energy Consumption and Savings Potential in the U.S. Residential Building Stock: Preprint

Building simulations are increasingly used in various applications related to energy efficient buildings. For individual buildings, applications include: design of new buildings, prediction of retrofit savings, ratings, performance path code compliance and qualification for incentives. Beyond individual building applications, larger scale applications (across the stock of buildings at various scales: national, regional and state) include: codes and standards development, utility program design, regional/state planning, and technology assessments. For these sorts of applications, a set of representative buildings are typically simulated to predict performance of the entire population of buildings. Focusing on the U.S. single-family residential building stock, this paper will describe how multiple data sources for building characteristics are combined into a highly-granular database that preserves the important interdependencies of the characteristics. We will present the sampling technique used to generate a representative set of thousands (up to hundreds of thousands) of building models. We will also present results of detailed calibrations against building stock consumption data.

building stock↗
DOE OSTI2020

Isolation and characterization of lignocellulosic nanofibers from four kinds of organosolv-fractionated lignocellulosic materials

The objective of this research was to investigate the presence of residual lignin in cellulose fibers on the efficiency and energy consumption during nanofibers processing. Four kinds of lignin-containing cellulose nanofibers (LCNFs) from switchgrass, yellow poplar, hybrid poplar, and pine, respectively, were isolated via organosolv fractionation coupling mechanical grinding. Nanofibrils were observed after organosolv fractionation. The details of their morphological features, chemical structures, water retention value (WRV), and thermal degradation characteristics were revealed and compared. Mean diameters of nanofibers separated from switchgrass, yellow poplar, hybrid poplar, and pine were 27.9 nm, 25.4 nm, 24.6 nm, and 21.5 nm, respectively. The presence of lignin for the four types of LCNFs led to a decrease in energy consumption and an increase in WRV, among which pine nanofibers show the best with an average energy consumption of 0.511 kWh/kg and a WRV of 537%. It was also demonstrated that increasing lignin content for LCNFs could contribute to the sample’s thermal stability. In conclusion, exact benefits of residual lignin for nanofiber will facilitate its preparation process and extend its application.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A semiparametric latent factor model for large scale temporal data with heteroscedasticity

Large scale temporal data have flourished in a vast array of applications, and their sophisticated structures, especially the heteroscedasticity among subjects with inter- and intra-temporal dependence, have fueled a great demand for new statistical models. In this paper, with covariate information, we consider a flexible model for large scale temporal data with subject-specific heteroscedasticity. Formally, the model employs latent semiparametric factors to simultaneously account for the subject-specific heteroscedasticity and the contemporaneous and/or serial correlations. The subject-specific heteroscedasticity is modeled as the product of the unobserved factor process and subject’s covariate effect, which is further characterized via additive models. For estimation, we propose a two-step procedure. First, the latent factor process and nonparametric loading are recovered through projection-based methods, and following, we estimate the regression components by approaches motivated from the generalized least squares. By scrupulously examining the non-asymptotic rates for recovering the factor process and its loading, we show the consistency and efficiency of estimated regression coefficients in the absence of prior knowledge of latent factor process and subject’s covariate effect. Here, the statistical guarantees remain valid even for finite time points that makes our method particularly appealing when the subjects significantly outnumber the observation time points. Using comprehensive simulations, we demonstrate the finite sample performance of our method, which corroborates the theoretical findings. Finally, we apply our method to a data set of air quality and energy consumption collected at 129 monitoring sites in the United States in 2015.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Trust Model System for the Energy Grid of Things Network Communications

Network communication is crucial in the Energy Grid of Things (EGoT). Without a network connection, the energy grid becomes just a power grid where the energy resources are available to the customer uni-directionally. A mechanism to analyze and optimize the energy usage of the grid can only happen through a medium, a communications network, that enables information exchange between the grid participants and the service provider. Security implementers of EGoT network communication take extraordinary measures to ensure the safety of the energy grid, a critical infrastructure, as well as the safety and privacy of the grid participants. With the dynamic nature of network communication of the EGoT, the information provided by the customer or the service provider can be falsified by a malicious attacker. Therefore, a trust model is necessary to monitor any abnormal activities. This paper describes a distributed trust model system that meets the need of the EGoT. This paper describes methods for evaluating and improving the distributed trust model using standard hypothesis testing metrics such as true positive, false positive, true negative, false negative, equal error rate, and F1 score. Example calculations are shown based on generated sample data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Evaluating Energy Efficiency Opportunities from Connected and Automated Vehicle Deployments Coupled with Shared Mobility in California

Connected and Automated Vehicles (CAVs) can be considered to be a disruptive transportation technology, with the potential to significantly improve overall transportation system efficiency; however, CAVs may increase induce vehicle miles traveled (VMT) and bring on greater energy consumption. Further, shared mobility is another disruptive transportation event that is reshaping our travel patterns. The primary goal of this project was to extensively collect data from vehicles and associated infrastructure equipped with CAV technologies from both real-world experiments and simulation studies mainly deployed in California, and develop a comprehensive framework for evaluating energy efficiency opportunities from large-scale (e.g., statewide) introduction of CAVs and a wide deployment of shared mobility systems in a variety of scenarios. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance, and energy efficiency, a unique mesoscopic simulation-based model was developed for mobility and energy efficiency evaluation considering these disruptive transportation technologies. As a complement to existing studies on nationwide evaluation of CAVs’ energy impacts, this project was focused on data collection efforts and CAV applications under congested traffic environments that are frequently experienced on a massive scale across the major metropolitan areas in California. Extensive real-world data collection supplemented with simulation studies were conducted to cover a variety of CAV and shared mobility scenarios, particularly on scenarios less-explored in the existing research. Another key component of this project was to consider the interaction between different CAV technologies and shared mobility models, and the compound effect on energy efficiency. A comprehensive modeling suite was developed to quantify the impact of new mobility technologies on travel behavior and traffic performance. The developed modeling framework includes an energy intensity module, mode choice module and activity generation module that are integrated into an agent-based BEAM simulation platform to perform impact analysis based on a variety of scenarios. In addition, the RouteE model has been upgraded to incorporate the impact of CAVs on traffic flow, VMT and energy intensity, using micro-simulation data collected from both freeways and urban arterials. A novel fundamental influencing factor (FIF) mode choice model was developed to link CAV and shared mobility components with travel behaviors, and adapted into the BEAM-centered model framework. A statewide energy inventory was constructed under various CAV technology deployment scenarios by incorporating datasets and models for predicting vehicle market share and vehicle usage, which are tightly associated with the penetration of shared mobility systems. Based applying this modeling suite to a calibrated network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes. The statewide analysis based on the National Household Travel Survey (NHTS) sample data is consistent with the findings from the Riverside network and validate the developed clustering-prediction modeling methodology. The outcomes from this project will help close the knowledge gap on recognizing the potential performance and energy impacts of a broad deployment of CAV and shared mobility technologies across a wide range of roadway infrastructure with varying levels of congestion. Results from this project: 1) will support policymakers in steering CAV development and deployment towards an energy favorable direction; 2) reduce uncertainties in estimating energy saving opportunities from new mobility technologies and services; 3) increase the confidence of CAV technology investors both on the infrastructure side (i.e., transportation agencies) and on the vehicle side (i.e., OEMs); and 4) expedite the deployment of energy-efficient CAV and shared mobility applications.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Seasonal and Interspecific Variation in Frugivory by a Mixed Resident-Migrant Overwintering Songbird Community

Many temperate passerine bird species switch from diets of mostly invertebrates in the spring and summer to diets that include fruit and seeds in the fall and winter. However, relatively few studies have quantified diet composition or the extent of seasonal shifts during the non-breeding period, particularly among species and across communities with both residents and migrants. We measured carbon and nitrogen stable isotope values in food items (fruits, C3 and C4 seeds, and insects from various trophic levels and plant communities) and in multiple tissues (feathers and plasma/whole blood) from 11 species of songbirds wintering in the southeastern U.S. We combined these diet and tissue values with empirically derived discrimination factors and used concentration-dependent mixing models to quantify seasonal diet shifts. We also validated mixing model results with data from fecal samples. Diets in this bird community, as delineated N and C isotopic space, diverged in the fall and winter relative to the summer as consumption of fruits and seeds increased. Across this songbird community, estimated contributions of fruit to plasma/whole blood increased from 16.2 ± 7.5% in the fall (mean ± SD; range: 4–26%) to 21.7 ± 10.3% (range: 9–37%) in the winter, while contributions of seeds increased from 29.4 ± 2.6% (range: 28–32%) in the fall to 36.6 ± 4.8% (range: 32–42%) in the winter. Fecal data showed qualitatively similar trends to mixing models, but consistently estimated higher contributions of fruit. Our work indicates that fruits and seeds constitute substantial sources of sustenance for non-breeding songbirds, there is considerable separation of resource use among species in the fall and winter, and fecal estimates of contributions to songbird tissues should be interpreted cautiously.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗
DOE OSTI2021

Assessment of the Impact of the Single Stream Recycling on Paper Contamination in Recovery Facilities and Paper Mills

Contaminated recyclables pose one of the largest roadblocks to an effective implementation of a circular economy system. Current knowledge surrounding the effects of various recycling methods on contamination rates is limited, thus preventing effective quantification of contamination effects. This study aims to fill this knowledge gap by assessing the impact of single stream recycling on paper contamination in MRFs and their end-products based on different composition studies conducted by facilities nationwide. This project expects to provide the foundational knowledge that could catalyze significant cost savings and energy consumption at MRFs and paper mills by understanding the levels of inbound and outbound contamination rates in SSR systems. Statistical analysis conducted in this project utilizes the available nationwide inbound and outbound samples collected as part of material composition and audit studies to identify and measure the significance of various factors on the resultant contamination levels. The research results provide benefits to both the recycling industry and its customers by addressing the causes and impact of contamination in recycled products, particularly with the wide applicability of single stream recycling within the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Microbial O 2 consumption as a function of pore structure in soils of sorghum, switchgrass, and prairie vegetation systems

Abstract Microscale O 2 availability in soil, a main factor influencing microbial processing of soil carbon and nitrogen, is a function of O 2 diffusion and microbial O 2 consumption. While O 2 diffusivity is widely studied, it is difficult to quantify the rate of microbial O 2 consumption ( MO ). In this study, we quantified the MO using O 2 microsensor profiling to compare MO in different soils and vegetation systems while manipulating the soil pore structure. Soil samples were collected from three bioenergy vegetation systems, sorghum ( Sorghum bicolor L. Moench), switchgrass ( Panicum virgatum L.), and prairie, at an experimental site in Southeast Michigan, and from switchgrass and prairie systems at two sites in South and North Wisconsin. We prepared soil cores with two contrasting pore structures, that is, large (>30 µm Ø) pore‐dominated soil (LP) and small (<10 µm Ø) pore‐dominated soil (SP), from the same 1‐ to 2‐mm soil size fraction. We quantified MO (nmol O 2 cm −3 s −1 ) using a microprofiler with an oxygen (OX‐100 µm) microsensor (Unisense) pre‐ and post‐38‐day incubation. Across all studied systems, there was a trend for a decrease in SP MO post‐incubation, suggesting a change in microbial metabolism to lower O 2 utilization. However, sizeable microbial O 2 consumption continued in the LP soils, further corroborated by a positive correlation between the C‐CO 2 emission rate and the post‐incubation MO , highlighting that LP provided a better physical microenvironment for the soil microbes.

Chakraborty, Poulamee [Department of Plant Soil an↗
DOE OSTI2022

Degradation mechanism of blended cement pastes in sulfate-bearing environments under applied electric fields: Sulfate attack vs. decalcification

Applied electric fields, the reason behind stray currents, accelerate the ingress of sulfate into cementitious materials. To identify mitigation approaches, this study investigates the effects of slag and fly ash on sodium sulfate attacks of cement pastes under a constant electric current. The mineralogical alterations induced by the attacks were analyzed using X-ray diffractometry, thermogravimetric analysis, scanning electron microscopy, and thermodynamic modeling. The dissolution of aluminates in the slag and fly ash induced a monosulfate-rich area (>~20 mm from the cathode surface) to form next to the ettringite-rich area on the sample surface (<~20 mm). This effect reduced the availability of SO 4 2– in the pore solution, thereby hindering the penetration of sulfate. Meanwhile, the consumption of portlandite by the pozzolanic reaction lowered the decalcification resistance of the materials. This produced a wide area that endured the decomposition of portlandite and carbonate-AFm. Altogether, blending 30% fly ash did not improve the resistance of the material to either sulfate attacks or decalcification; blending 50% slag can effectively mitigate sulfate ingress, though decalcification may become a governing mechanism in the degradation process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Oxidation of porous stainless steel supports for metal-supported solid oxide electrolysis cells

Oxidation behavior of porous P434L ferritic stainless steel, used for the fabrication of metal-supported solid oxide electrolysis cells (MS-SOEC), is studied under oxygen-side and steam-side conditions. The impact of oxygen content on the oxygen side and steam:hydrogen ratio on the steam side is determined at 700°C for bare, as-sintered samples. For these conditions, oxidation is more aggressive in the steam-side atmosphere. Oxygen with 3% humidification and steam:hydrogen ratio of 90:10 are selected for further assessment with pre-oxidized, catalyst-coated, and CuMn1·8O4-coated samples. The rapid oxidation at 700°C and breakaway oxidation at 600 °C observed for bare stainless steel in 90:10 steam:hydrogen is mitigated by pre-oxidizing the sample in air before exposure. In oxygen, addition of the catalyst or CuMn 1·8 O 4 coatings moderately increases the oxidation rate, due to consumption of Cr via reaction between the coatings and Cr-oxide scale. In conclusion, the results for ex-situ controlled oxidation are similar to oxidation observed after 1000h operation of a full MS-SOEC. In general, the oxidation behavior at 700°C is found to be acceptable.

08 HYDROGEN↗
DOE OSTI2023

FTR for: Reducing plug-load electricity footprint of residential buildings through low-cost, non-intrusive sub-metering and personalized feedback technology

The project started in October 2016 and ended in December 2022. The project's principal goals and achievements were: (i) Measure real and reactive electric power consumption in ~400 apartments in multifamily settings of varying size and vintage and publish the data; data was published according to New York State's recommended 15x15 rule continuously from Jan 2019 through December 2022 (10 second time resolution); with the combination of large number of apartments, real and reactive power, as well as high time resolution (10-seconds), the dataset is first of its kind worldwide; because the dataset New York City apartment consumption pre, during, and post pandemic, it further offers unique insights into changes in residential electricity consumption during lockdowns and after modified work from home schedules. (ii) Measure effectiveness of different feedback types to prompt residents to lower their electricity consumption; achieved 11% (kWh-weighted) reduction versus baseline consumption; confirmed previous studies that social comparisons elicit above average responses; showed, for the first time, that the so called boomerang effect in power consumption feedback projects can be explained by a previously hypothesized norm-conforming "magnet effect" (rather than a non-conforming defiance effect), thus substantially advancing the research in the field. (iii) Disaggregate apartment-level consumption to appliance level; because the hardware for electricity consumption unexpectedly allowed only for 10-second time resolution (rather than the 1-second resolution we had planned on), the disaggregation algorithms we developed on sample data could not be applied to the actual field data we collected. The project has yielded high visibility, with a total of 17 publications, from peer reviewed journals, published data sets (free access), blog posts, NY Times, National Public Radio, and CNN.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Grafted nickel-promoter catalysts for dry reforming of methane identified through high-throughput experimentation

High-throughput synthesis of a series of monometallic and bimetallic catalysts (45 bimetallic and 50 monometallic samples) consisting of nickel and one of nine different metal promoters (B, Co, Cu, Fe, Mg, Mn, Sn, V and Zn) supported on one of six different metal oxides alumina, ceria, magnesia, silica and titania) is carried out via organometallic grafting using a robotic platform. The catalysts are evaluated for their activity and selectivity for the dry reforming of methane at a feed ratio of CH 4 :CO 2 of 1 at 650–800 °C in a parallel flow reactor system. The type of oxide support prevails over the type of additive for both catalyst activity and stability. On Al 2 O 3 and MgO, Fe was found to be the best promoter; on SiO 2 , Cu is the best promoter at 700 °C and higher, while on TiO 2 , Mn is found to enhance the conversion at 800 °C. On CeO 2 , all additives except Fe have beneficial effects. Twenty-five catalysts show > 90% methane conversion with ten catalysts showing > 95% conversion at 800 °C with the H 2 :CO ratios ranging from 0.8 to 1.2. Amongst the ten highest performers, NiFe/Al 2 O 3 and NiFe/MgO are more active than Ni/Al 2 O 3 and Ni/MgO, respectively and were stable over a period of 25 h at 800 °C. Characterization on the as-prepared samples reveals highly dispersed phase, while after reduction in H 2 , highly dispersed and reduced nickel particles up to 10 nm are formed. The particles do not increase in size under dry reforming reaction conditions at 800 °C. An increased hydrogen consumption observed during H 2 -TPR of the nickel particles is positively correlated with methane conversion for Al 2 O 3 -based catalysts. The resistance to deactivation by coking and variation in coke structure are investigated by spectroscopic and microscopic methods to identify the relationship between metal promoters, alloy formation, and type of surface carbon deposits. Carbon whiskers were observed on the ten selected spent samples and are preferentially deposited on Ni rather than on the promoters. Carbon nanotube formation and metal particle removal from support were not observed to cause deactivation while amorphous carbon formation was clearly linked to catalyst deactivation, as amorphous carbon could encapsulate nickel, either on the support or at the end of the carbon nanotube. Furthermore, the organometallic grafting technique is an efficient and suitable technique for synthesizing highly dispersed and homogeneous phases which lead to high conversion and high durability for dry reforming of methane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗