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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The 5 Cs of Agrivoltaic Success Factors in the United States: Lessons from the InSPIRE Research Study

The concept of agrivoltaics (combining agriculture and solar photovoltaics technologies on the same land in novel configurations) has emerged as an approach to mitigate conflicts between solar and agricultural activities by providing mutual benefits and added values to each sector. The U.S. Department of Energy has supported agrivoltaics research since 2015 through its Innovative Solar Practices Integrated with Rural Economies and Ecosystems (InSPIRE) research project (National Renewable Energy Laboratory 2022). The InSPIRE project is the most comprehensive coordinated research effort on agrivoltaics in the United States and has examined opportunities and tradeoffs at over 25 sites across the country that span crop production, pollinator habitat, ecosystem services, animal husbandry, and d. Integrating research sites with active commercial agricultural operations can introduce unique challenges for conducting research. This synthesis aims to highlight the technical and non-technical insights from InSPIRE agrivoltaic field research sites from 2015-2021 to support i) appropriate deployment of agrivoltaic projects; ii) more successful research on agrivoltaics; and iii) more effective partnerships on agrivoltaic projects. The synthesized lessons discussed here are focused less on specific case study outcomes (i.e., the percent change in crop yield in an agrivoltaics configuration), and instead more on the elements that enable and facilitate agrivoltaics projects to be installed and operated along with research to be conducted at those sites. We find that there are some insights that are applicable across all types of agrivoltaic projects, while ecosystem service projects and crop production agrivoltaic projects can often have other unique considerations.

14 SOLAR ENERGY↗
DOE OSTI2025

Coupling Amorphization and Compositional Optimization of Ternary Metal Phosphides toward High-Performance Electrocatalytic Hydrogen Production

Amorphous materials, with abundant active sites and unique electronic configurations, have the potential to outperform their crystalline counterparts in high-performance catalysis for clean energy. However, their synthesis and compositional optimization remain underexplored due to the strict conditions required for their formation. Here, in this study, we report the synthesis of ternary platinum-nickel-phosphorus (PtNiP) amorphous nanoparticles (ANPs) within milliseconds by flash Joule heating, which features ultrafast cooling that enables the vitrification of metal precursors. Through compositional optimization, the Gibbs free energy of hydrogen adsorption for Pt 4 Ni 4 P 1 ANPs is optimized at 0.02 eV, an almost ideal value, even surpassing that of the benchmark metallic platinum catalyst. As a result, the PtNiP ANPs exhibited superior activity in electrocatalytic hydrogen evolution in acid electrolyte (η 10 ∼ 14 mV, Tafel slope ∼ 18 mV dec –1 , and mass activity 5× higher than state-of-the-art Pt/C). Life-cycle assessment and technoeconomic analysis suggest that, compared to existing processes, our approach enables notable reductions in greenhouse gas emission, energy consumption, and production cost for practical electrolyzer catalyst manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Identifying biomass yield potential of tetra, hexa, and octoploid prairie cordgrass populations grown on marginal lands

As the demand for renewable energy sources with reduced carbon emissions to the atmosphere increases, bioenergy crops remain an attractive alternative to fossil fuels. Another appeal of bioenergy crops is the potential utilization of marginal lands not suitable for food crops. Prairie cordgrass is a perennial warm season polyploid grass species being considered as a bioenergy crop that also exhibits a high tolerance for salinity and flooding. The ploidy level of prairie cordgrass has previously been suggested to correlate with agronomic traits. However, little is known about the agricultural performance of prairie cordgrass on marginal lands and if a correlation of ploidy level to stress tolerance exists. In this experiment, the productivity of tetraploids, hexaploids, and octoploids was investigated when grown on three different marginal sites including waterlogged, saline, and low-nutrient gravelly soils. Here we found that prairie cordgrass populations annually produced dry biomass on a wet marginal site comparable to normal cropland. However, the productivity was remarkedly decreased at both a salt-affected site and a limestone mine reclamation site. We were unable to conclude that different ploidy levels affected the biomass yield of prairie cordgrass grown under abiotic stress. However, there was a differential response of populations to various types of marginal sites. Finally, these results indicate potential genetic resources for developing breeding targets and identifying mechanisms of abiotic stress tolerance. Moreover, we highlight the need to generate diverse ploidy levels of prairie cordgrass in the same genetic backgrounds for future testing.

09 BIOMASS FUELS↗
DOE OSTI2020

Science-informed Machine Learning to Increase Recovery Efficiency in Unconventional Reservoirs

Production of hydrocarbons from fractured, unconventional reservoirs is inherently inefficient. But machine learning offers a pathway both to increasing recovery efficiency at a site and to improving forecasts of production, thereby improving the economics of operations in unconventional reservoirs. Los Alamos—in partnership with DOE, NETL, and WVU—has been developing a science-informed workflow and platform for optimizing pressure-drawdown at a site, which will allow an operator to make reservoir-management decisions that optimize recovery in consideration of future production. This work relies on a hybridization of physics-based prediction and machine learning, whereby accurate synthetic data (in combination with available site data) can enable the application of machine learning methods for rapid forecasting and optimization. The physics-based prediction is built upon experimental and theoretical work to determine transport characteristics in shale at various scales, with an emphasis on materials from MSEEL-I; this fundamental shale R&D was conducted in partnership with DOE, NETL, and several other national labs. This work has resulted from a coordinated leveraging of developments across several projects within DOE FE30, along with internal investments from Los Alamos via LDRD. The development has utilized data from the MSEEL–I site for calibration and demonstration; however, the workflow and platform are readily extendable to operations at other sites, plays, and basins. This machine-learning method can aid operators to improve both recovery efficiency and competitiveness; to this end, future work would quantify processes for other plays/basins and integrate production details with economics.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2020

Infrastructure and DFLAW Support at Hanford - 20443

Manhattan Project era infrastructure systems are degrading at an accelerated pace across the Department of Energy's (DOE) Environmental Management complex. Revitalizing, rejuvenating and right-sizing these systems to ensure reliability for ongoing cleanup missions is a major focus at the 580-square- mile Hanford Site in southeast Washington State. The push to complete construction, commissioning, startup, and operation of facilities and systems in the Direct-Feed Low-Activity Waste (DFLAW) program at Hanford by 2023 requires considerable coordination among site contractors and a significant investment in infrastructure. The passage of time also poses a challenge. It has been about 75 years since facilities were first operated at the site, and approximately 40 years of plutonium production created a legacy of unidentified active and abandoned underground obstacles and waste sites that must be avoided when building and upgrading the infrastructure. Converting infrastructure systems originally built to support plutonium production from the 1940's to the 1980's and upgrading those systems to optimize technology is an ever-changing balance of funding profiles, available resources and execution strategies. The DOE Richland Operations Office (RL) has long recognized the need for increased investment in Hanford Site infrastructure to support the future processing of approximately 56 million gallons of waste currently stored in large underground tanks. When DFLAW is fully operational, safe and reliable infrastructure systems will be needed to ensure continuity of operations around the clock, 365 days a year. These include roadways, water, power, sewer, information technology systems and facilities. To ensure the readiness of Hanford's infrastructure to support treating tank waste in the next three years, 15 projects were identified with a combined value of $133.8 million. Through calendar year 2019, 7 infrastructure projects have been substantially completed and the remaining 8 projects, with a remaining value of $103.8 million, are scheduled to be completed by December 2023. RL and its site services/infrastructure contractor, Mission Support Alliance (MSA), regularly evaluate the needs of the DFLAW program and other Hanford Site missions to ensure the highest priority systems are addressed. In addition to a fast-approaching deadline for round-the-clock treatment operations, RL and MSA face another significant infrastructure challenge. As cleanup is being completed in a 220-square-mile area called the River Corridor, most of the cleanup operations going forward will occur in a 20-square-mile area in the center of the Hanford Site, known as the Central Plateau. Infrastructure systems are becoming more congested in an already overcrowded area. This paper/presentation will outline some of the challenges Hanford faces while executing infrastructure reliability projects. (authors)

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

Machine Learning Modeling Pipeline for Extracting Nuclear Proliferation Events of Interest from Open Data Sources (U)

In FY2020, the Savannah River National Laboratory (SRNL) and the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Polytechnic Institute and State University entered a collaboration funded by Department of Energy’s (DOE) Office of Defense Nuclear Nonproliferation Research and Development. The project’s mission was to take the first steps toward developing a demonstration prototype system that uses multiple machine learning and data analytics methods on largescale open data sources to identify new, developing, and/or undeclared nuclear programs. Given the SRNL team’s on-site perspective of events culminating in the DOE’s decision to pursue the Savannah River Plutonium Processing Facility (SRPPF), the team targeted the identification of events and indicators in retrospective datasets that pointed to the activity of “fissile core fabrication at the Savannah River Site” prior to the official announcement in May of 2018. A preliminary modeling pipeline was developed in FY20 that showed the datasets contained adequate signal for continuation of efforts. In FY21, a modular demonstration prototype modeling pipeline has continued in development for two text-based data sources: a broad internet archive (Webhose Ltd.) and a decahose Twitter database (i.e., a global sampling of one in every ten Tweets). The techniques that have been developed rely on graph theory and anomaly detection to identify contextual shifts in key words and phrases at various points in time such that indicators of events of interest could be identified and subsequently, events could be extracted from the corpuses. The foundational concept behind the approaches is that contextual shifts in key words and phrases can act as indicators of events of interest. Both datasets have proven successful in extracting events of interest related to pit production at the Savannah River Site prior to the official announcement. In addition, the pipelines have generated a wide range of events broadly summarized as: the awarding of DOE contracts at major sites, DOE investments in various programs, accidents at DOE national laboratories, speculations about the fate of pit production in the DOE complex, domestic and international shipments and receipts of nuclear materials at DOE sites, termination of non-proliferation agreements with Russia, termination of MOX, new weapons development approvals/testing, nuclear posture reviews, major DOE cleanup/production milestones, political opinions, and nuclear watch groups’ opinions, among many others.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Los Alamos National Laboratory Campus Master Plan Communication Strategy

The purpose of this Campus Master Plan (CMP) Communication Strategy is to establish an appropriate approach to communication that ensures the comprehensive site planning (henceforth campus master planning) process and associated products for the Los Alamos National Laboratory (LANL) site are effective and sustainable.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

A global gridded dataset for cloud vertical structure from combined CloudSat and CALIPSO observations

Abstract. The vertical structure of clouds has a profound effect on the global energy budget, the global circulation, and the atmospheric hydrological cycle. The CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) missions have taken complementary, colocated observations of cloud vertical structure for over a decade. However, no globally gridded dataset is available to the public for the full length of this unique combined data record. Here we present the 3S-GEOPROF-COMB product (Bertrand et al. 2023, https://doi.org/10.5281/zenodo.8057791), a globally gridded (level 3S) community data product summarizing geometrical profiles (GEOPROF) of hydrometeor occurrence from combined (COMB) CloudSat and CALIPSO data. Our product is calculated from the latest release (R05) of per-orbit (level-2) combined cloud mask profiles. We process a set of cloud cover, vertical cloud fraction, and sampling variables at 2.5, 5, and 10° spatial resolutions and monthly and seasonal temporal resolutions. We address the 2011 reduction in CloudSat data collection with Daylight-Only Operations (DO-Op) mode by subsampling pre-2011 data to mimic DO-Op collection patterns, thereby allowing users to evaluate the impact of the reduced sampling on their analyses. We evaluate our data product against CloudSat-only and CALIPSO-only global-gridded data products as well as four comparable surface-based sites, underscoring the added value of the combined product. Interest in the product is anticipated for the study of cloud processes, cloud–climate interactions, and as a candidate baseline climate data record for comparison to follow-up satellite missions, among other uses.

Bertrand, Leah (ORCID:0009000001607558)↗
DOE OSTI2025

Direct Comparison of the Activity and Selectivity of Rh 1 Cu and Ni 1 Cu Single-Atom Alloy Sites for Ethanol Decomposition

Ethanol is an important source of clean hydrogen, acetaldehyde, acetic acid, acetate esters, and light hydrocarbons. Controlling the divergent reaction pathways to these products requires understanding how different active sites influence the elementary steps involved. Herein, we present a combined surface science, theory, and nanoparticle catalysis study demonstrating how two single-atom dopants (Rh and Ni) in a Cu host can distinctively alter the selectivity of alcohol conversion. Specifically, our model studies reveal that ethanol reacts on Ni 1 Cu single-atom alloys to selectively produce acetaldehyde, whereas methane and CO are also formed on Rh 1 Cu single-atom alloys. Interestingly, these different reactivities are in contrast to the behavior of the pure metals as Ni(111) and Rh(111) surfaces favor methane/CO and surface carbon/CO, respectively. DFT calculations of reaction pathways and simulated product desorption based on microkinetic analyses explain these reactivity differences, demonstrating that C–C cleavage leading to methane formation has a lower barrier on Rh single-atom sites. To test the catalytic relevance of these fundamental results we synthesized and characterized supported Ni 1 Cu and Rh 1 Cu single-atom alloy nanoparticles with dopant:Cu ratios of 1:200. Flow reactor results revealed that both Ni and Rh increased ethanol conversion over Cu and that Ni 1 Cu catalysts were >99.9% selective to acetaldehyde, while Rh 1 Cu also produced 0.6%–2.6% of equimolar methane and CO between 433 and 493 K, demonstrating that C–C bond cleavage is enabled by isolated Rh sites. Furthermore, these catalytic results bridge the pressure and materials gaps, and together, this study provides insights into how different isolated dopant sites promote different catalytic pathways.

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

Comparative productivity of six bioenergy cropping systems on marginal lands in the Great Lakes Region, United States

Abstract Growing lignocellulosic crops on marginal lands is a promising solution for sustainable biofuel production. We evaluated the productivity of bioenergy cropping systems (switchgrass [ Panicum virgatum L., var. Cave‐In‐Rock], miscanthus [ Miscanthus × giganteus , ‘Illinois clone’], hybrid poplar [ Populus nigra × P. maximowiczii A. Henry ‘NM6’], native grasses [five species], early successional vegetation, and restored prairie vs. historical vegetation [as reference control]) with and without nitrogen fertilization on low‐fertility former cropland at five sites in the Great Lakes Region, United States. We reported biomass yields for the first 7 years after establishment. Switchgrass was most consistently productive across all sites but miscanthus was more productive at three of the five sites. When averaged across sites, years, and nitrogen (N) treatments, biomass yields followed the order miscanthus > switchgrass > hybrid poplar ≈ native grasses > restored prairie > early successional vegetation ≈ historical vegetation, but varied substantially by crop and site, with a significant crop by site interaction. Yields of miscanthus and switchgrass peaked after four–five growing seasons and declined thereafter, while yields of both native grasses and restored prairie increased throughout 6 years with no sign of follow‐on decline, suggesting that polycultures may outperform monocultures over the long term. Yields of early successional vegetation—similar in composition to historical vegetation at each site—did not improve with time. Nitrogen fertilization increased the yields of all cropping systems at all sites. Our results demonstrate the viability of low‐productivity former cropland for long‐term bioenergy production and suggest there is no single crop best suited for all low fertility soils.

Jayawardena, Dileepa M.↗
DOE OSTI2024

Exploring the role of biotic factors in regulating the spatial variability in land surface phenology across four temperate forest sites

Here, land surface phenology (LSP), the characterization of plant phenology with satellite data, is essential for understanding the effects of climate change on ecosystem functions. Considerable LSP variation is observed within local landscapes, and the role of biotic factors in regulating such variation remains underexplored. In this study, we selected four National Ecological Observatory Network terrestrial sites with minor topographic relief to investigate how biotic factors regulate intra-site LSP variability. We utilized plant functional type (PFT) maps, functional traits, and LSP data to assess the explanatory power of biotic factors for the start and end of season (SOS and EOS) variability. Our results indicate that PFTs alone explain only 0.8–23.4% of intra-site SOS and EOS variation, whereas including functional traits significantly improves explanatory power, with cross-validation correlations ranging from 0.50 to 0.85. While functional traits exhibited diverse effects on SOS and EOS across different sites, traits related to competitive ability and productivity were important for explaining both SOS and EOS variation at these sites. These findings reveal that plants exhibit diverse phenological responses to comparable environmental conditions, and functional traits significantly contribute to intra-site LSP variability, highlighting the importance of intrinsic biotic properties in regulating plant phenology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Automated Generation of Weather and Climate Analysis Products

Wind roses are an important part to site operations as they depict the wind speed and direction percentage over a time period. In this project, I automated the production of wind roses for SRS meteorological towers. I developed a script to sequence through the dataset by period and create a wind rose for each of those period sets. Graphics were generated for every 4-hour period of the day, for each of the 4 heights of the instruments, for every half of each month. A 10-year climatological period consisted of wind speed and directions measurements at 15-minute intervals. We used the years 2014-2024 as the wind instruments on the tower were upgraded to sonic anemometers in early 2014. I then compared these wind roses to those from a previous study done in 2003 to analyze the differences and similarities in the wind patterns. The wind roses are also used to understand environmental transport conditions at SRS. When comparing the different heights of the anemometers to the 2003 report, there is a similarity in the fact that the direction is relatively the same across the levels, with the wind speeds increasing as you get higher in the air. When comparing the season of our graphs against the 2003 report, we noticed that the winter and summer months appear to have very similar wind directions. However, in the spring we noticed that there were more southerly winds compared to the 2003 report which had more westerly winds. Finally, in the fall months, we noticed that there was a higher percentage of northeasterly winds, while the 2003 report showed more southeasterly winds. We can use these summaries to estimate the directional dependence of dose that the surrounding areas receive throughout the year according to time of day.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Extreme drought impacts have been underestimated in grasslands and shrublands globally

Climate change is increasing the frequency and severity of short-term (~1 y) drought events—the most common duration of drought—globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function—aboveground net primary production (ANPP)—was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A redox model for NO oxidation, NH 3 oxidation and high temperature standard SCR over Cu-SSZ-13

A kinetic model is developed to predict the influence of temperature and hydrothermal aging on the redox of active Cu sites under standard SCR, NO oxidation and NH 3 oxidation conditions over a practically relevant fully-formulated Cu-SSZ-13 catalyst. NO 2 /N 2 production during NO/NH 3 titration of Cu II sites is utilized to identify rate parameters associated with NO-only RHC (reduction half cycle) and NH 3 -only RHC respectively. Integral N 2 formation during subsequent NO + NH 3 titration is consistent with the production of one NO 2 per two CuII sites reduced during NO-only RHC and one N 2 per six Cu II sites reduced during NH 3 -only RHC. Decreased reduction of Cu II sites by NO/NH 3 upon hydrothermal aging, along with the production of one NO 2 per two CuII sites during NO-only RHC, is accordant with the involvement of proximal ZCuOH and oxygen-bridged dimeric Cu II sites. Oxidation of partially solvated and framework coordinated ZCu (Cu I ) sites occurs in presence of O 2 , does not produce N 2 and can lead to the consumption of Brønsted acid sites. A global OHC kinetic model is developed to predict transient and integral N 2 formation during exposure of CuI sites to a mixture of NO and O 2 . The resulting redox kinetic model quantitatively predicts NO and NH 3 consumption during isothermal transient response Cu redox (TRCR) protocols, along with temperature and age dependent steady-state standard SCR and oxidation conditions. The redox model presented in this work synthesizes recent kinetic, spectroscopic and computational findings to provide a foundational description of active site redox during standard SCR, NO oxidation and NH3 oxidation over Cu-SSZ-13.

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

Contribution of Microorganisms with the Clade II Nitrous Oxide Reductase to Suppression of Surface Emissions of Nitrous Oxide

The sources and sinks of nitrous oxide, as control emissions to the atmosphere, are generally poorly constrained for most environmental systems. Initial depth-resolved analysis of nitrous oxide flux from observation wells and the proximal surface within a nitrate contaminated aquifer system revealed high subsurface production but little escape from the surface. Further, to better understand the environmental controls of production and emission at this site, we used a combination of isotopic, geochemical, and molecular analyses to show that chemodenitrification and bacterial denitrification are major sources of nitrous oxide in this subsurface, where low DO, low pH, and high nitrate are correlated with significant nitrous oxide production. Depth-resolved metagenomes showed that consumption of nitrous oxide near the surface was correlated with an enrichment of Clade II nitrous oxide reducers, consistent with a growing appreciation of their importance in controlling release of nitrous oxide to the atmosphere. Our work also provides evidence for the reduction of nitrous oxide at a pH of 4, well below the generally accepted limit of pH 5.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Site and Bioenergy Cropping System Similarly Affect Distinct Live and Total Soil Microbial Communities

Bioenergy crops are a promising energy alternative to fossil fuels. During bioenergy feedstock production, crop inputs shape the composition of soil microbial communities, which in turn influences nutrient cycling and plant productivity. In addition to cropping inputs, site characteristics (e.g., soil texture, climate) influence bacterial and fungal communities. We explored the response of soil microorganisms to bioenergy cropping system (switchgrass vs. maize) and site (sandy loam vs. silty loam) within two long-term experimental research stations. The live and total microbial community membership was investigated using 16S and ITS amplicon sequencing of soil RNA and DNA. For both nucleic acid types, we expected fungi and prokaryotes to be differentially impacted by crop and site due their dissimilar life strategies. We also expected live communities to be more strongly affected by site and crop than the total communities due to a sensitivity to recent stimuli. Instead, we found that prokaryotic and fungal community composition was primarily driven by site with a secondary crop effect, highlighting the importance of soil texture and fertility in shaping both communities. Specific highly abundant prokaryotic and fungal taxa within live communities were indicative of site and cropping systems, providing insight into treatment-specific, agriculturally relevant microbial taxa that were obscured within total community profiles. Within live prokaryote communities, predatory Myxobacteria spp. were largely indicative of silty and switchgrass communities. Within live fungal communities, Glomeromycota spp. were solely indicative of switchgrass soils, while a few very abundant Mortierellomycota spp. were indicative of silty soils. Site and cropping system had distinct effects on the live and total communities reflecting selection forces of plant inputs and environmental conditions over time. Comparisons between RNA and DNA communities uncovered live members obscured within the total community as well as members of the relic DNA pool. The associations between live communities and relic DNA are a product of the intimate relationship between the ephemeral responses of the live community and the accumulation of DNA within necromass that contributes to soil organic matter, and in turn shapes soil microbial dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Engineering a Cu‐Pd Paddle‐Wheel Metal–Organic Framework for Selective CO 2 Electroreduction

Optimizing the binding energy between the intermediate and the active site is a key factor for tuning catalytic product selectivity and activity in the electrochemical carbon dioxide reduction reaction. Copper active sites are known to reduce CO 2 to hydrocarbons and oxygenates, but suffer from poor product selectivity due to the moderate binding energies of several of the reaction intermediates. Here, we report an ion exchange strategy to construct Cu−Pd paddle wheel dimers within Cu-based metal–organic frameworks (MOFs), [Cu 3-x Pd x (BTC) 2 ] (BTC=benzentricarboxylate), without altering the overall MOF structural properties. Compared to the pristine Cu MOF ([Cu 3 (BTC) 2 ], HKUST-1), the Cu−Pd MOF shifts CO 2 electroreduction products from diverse chemical species to selective CO generation. In situ X-ray absorption fine structure analysis of the catalyst oxidation state and local geometry, combined with theoretical calculations, reveal that the incorporation of Pd within the Cu−Pd paddle wheel node structure of the MOF promotes adsorption of the key intermediate COOH* at the Cu site. This permits CO-selective catalytic mechanisms and thus advances our understanding of the interplay between structure and activity toward electrochemical CO 2 reduction using molecular catalysts.

CO2 electroreduction reaction↗
DOE OSTI2021

Modeled Surface-Atmosphere Fluxes From Paired Sites in the Upper Great Lakes Region Using Neural Networks

The eddy covariance (EC) method is one of the most widely used approaches to quantify surface-atmosphere fluxes. However, scaling up from a single EC tower to the landscape remains an open challenge. To address this, we used 63 site years of data to examine simulated annual and growing season sums of carbon fluxes from three paired land-cover type sites of corn, restored-prairie, and switchgrass ecosystems. This was also done across the landscape by modeling fluxes using different land-cover type input data. An artificial neural network (ANN) approach was used to model net ecosystem exchange (NEE), ecosystem respiration (R eco ), and gross primary production (GPP) at one paired site using environmental observations from the second site only. With a mean spatial separation of 11 km between paired sites, we were able to model annual sums of NEE, R eco , and GPP with uncertainties of 20%, 22%, and 8%, respectively, relative to observation sums. When considering the growing season only, model uncertainties were 17%, 22%, and 9%, respectively for the three flux terms. We also show that ANN models can estimate sums of R eco and GPP fluxes without needing the constraint of similar land-cover-type, with annual uncertainties of 12% and 10%. These results provide new insights to scaling up observations from one EC site beyond the footprint of the EC tower to multiple land-cover types across the landscape.

54 ENVIRONMENTAL SCIENCES↗