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NASA NTRS2018

Remote Sensing Based Yield Monitoring: Application to Winter Wheat in United States and Ukraine

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Earth observation data from space can contribute to agricultural monitoring, including crop yield assessment and forecasting. In this study, we present a new crop yield model based on the Difference Vegetation Index (DVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1 km resolution and the un-mixing of DVI at coarse resolution to a pure wheat signal (100 percent of wheat within the pixel). The model was applied to estimate the national and subnational winter wheat yield in the United States and Ukraine from 2001 to 2017. The model at the subnational level shows very good performance for both countries with a coefficient of determination higher than 0.7 and a root mean square error (RMSE) of lower than 0.6 t/ha (tonnes per hectare) (15-18 percent). At the national level for the United States (US) and Ukraine the model provides a strong coefficient of determination of 0.81 and 0.86, respectively, which demonstrates good performance at this scale. The model was also able to capture low winter wheat yields during years with extreme weather events, for example 2002 in US and 2003 in Ukraine. The RMSE of the model for the US at the national scale is 0.11 t/ha (3.7 percent) while for Ukraine it is 0.27 t/ha (8.4 percent).

DVI↗
NASA NTRS2018

Remote Sensing Based Yield Monitoring: Application to Winter Wheat in United States and Ukraine

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Earth observation data from space can contribute to agricultural monitoring, including crop yield assessment and forecasting. In this study, we present a new crop yield model based on the Difference Vegetation Index (DVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1 km resolution and the un-mixing of DVI at coarse resolution to a pure wheat signal (100% of wheat within the pixel). The model was applied to estimate the national and subnational winter wheat yield in the United States and Ukraine from 2001 to 2017. The model at the subnational level shows very good performance for both countries with a coefficient of determination higher than 0.7 and a root mean square error (RMSE) of lower than 0.6 t/ha (15–18%). At the national level for the United States (US) and Ukraine the model provides a strong coefficient of determination of 0.81 and 0.86, respectively, which demonstrates good performance at this scale. The model was also able to capture low winter wheat yields during years with extreme weather events, for example 2002 in US and 2003 in Ukraine. The RMSE of the model for the US at the national scale is 0.11 t/ha (3.7%) while for Ukraine it is 0.27 t/ha (8.4%).

remote sensing↗
NASA NTRS2024

Quantifying Food Security and Mitigation Risks Consequential to Climate Change Impacts on Crop Yields

Climate change is expected to impact crop yields globally, with some regions benefiting from favorable conditions and CO2 fertilization, while others face adverse effects from altered precipitation and higher temperatures. Changes in crop yields can destabilize the global food system and pose challenges to food security. Moreover, crop production is crucial, as biofuels are becoming increasingly important contributors to climate change mitigation measures aimed at limiting global warming. This study uses the Integrated Model to Assess the Global Environment integrated assessment model framework to analyze different indicators related to food security and climate change mitigation under varying climate change impacts on crop yields. Twelve spatially explicit crop productivity projections were taken from the full archive of the Global Gridded Crop Model Intercomparison of 120 climate-crop model combinations, forced by CMIP6-based climate scenarios. The selection includes two average-performing climate-crop model combinations, two pessimistic combinations that perform one standard deviation below the mean, and two optimistic model combinations that perform one standard deviation above the mean. To single out the effect of climate change on productivity changes, we drew samples from two representative concentration pathways (RCP2.6 and RCP8.5). These productivity projections were applied within an otherwise uniform scenario (SSP2) and analyzed for their effect on total calorie demand, crop prices, and number of people at risk of undernourishment to quantify food security. Risks to climate change mitigation targets were explored by modeling the total bioenergy supply, emissions, and global mean temperature. The results revealed significant differences in the risk of food security and mitigation potential between different regions and climate change scenarios. Across scenarios, the crop area extent can vary up to 2 million km2 due to changing crop yields. The projected change in global hunger ranges from 60 to 160 million undernourished people, indicating uncertainty between climate and crop model combinations. Low-income regions are especially impacted because of their high sensitivity to changes in food prices. Global climate change mitigation ambitions can also deviate by the latter part of the 21st century, as changes in yields will impact biofuel production as well as agriculture, forestry and other land use emissions. The quantitative insights generated by this study highlight the need for global policy efforts to make the agricultural system more adaptive to climate change to handle potential negative impacts.

crop yields↗
DOE OSTI2012

Assessment of fission product yields data needs in nuclear reactor applications

Studies on the build-up of fission products in fast reactors have been performed, with particular emphasis on the effects related to the physics of the nuclear fission process. Fission product yields, which are required for burn-up calculations, depend on the proton and neutron number of the target nucleus as well as on the incident neutron energy. Evaluated nuclear data on fission product yields are available for all relevant target nuclides in reactor applications. However, the description of their energy dependence in evaluated data is still rather rudimentary, which is due to the lack of experimental fast fission data and reliable physical models. Additionally, physics studies of evaluated JEFF-3.1.1 fission yields data have shown potential improvements, especially for various fast fission data sets of this evaluation. In recent years, important progress in the understanding of the fission process has been made, and advanced model codes are currently being developed. This paper deals with the semi-empirical approach to the description of the fission process, which is used in the GEF code being developed by K.-H. Schmidt and B. Jurado on behalf of the OECD Nuclear Energy Agency, and with results from the corresponding author's diploma thesis. An extended version of the GEF code, supporting the calculation of spectrum weighted fission product yields, has been developed. It has been applied to the calculation of fission product yields in the fission rate spectra of a MOX fuelled sodium-cooled fast reactor. Important results are compared to JEFF-3.1.1 data and discussed in this paper. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Artificial ground reflector size and position effects on energy yield and economics of single‐axis‐tracked bifacial photovoltaics

Abstract Artificial ground reflectors improve bifacial energy yield by increasing both front and rear‐incident irradiance. Studies have demonstrated an increase in energy yield due to the addition of artificial reflectors; however, they have not addressed the effect of varying reflector dimensions and placement on system performance and the impact of these parameters on the reflectors' financial viability. We studied the effect of high albedo (70% reflective) artificial reflectors on single‐axis‐tracked bifacial photovoltaic systems through ray‐trace modeling and field measurements. In the field, we tested a range of reflector configurations by varying reflector size and placement and demonstrated that reflectors increased daily energy yield up to 6.2% relative to natural albedo for PERC modules. To confirm the accuracy of our model, we compared modeled and measured power and found a root mean square error (RMSE) of 5.4% on an hourly basis. We modeled a typical meteorological year in Golden, Colorado, to demonstrate the effects of artificial reflectors under a wide range of operating conditions. Seventy percent reflective material can increase total incident irradiance by 1.9%–8.6% and total energy yield by 0.9%–4.5% annually after clipping is considered with a DC–AC ratio of 1.2. Clipping has a significant effect on reflector impact and must be included when assessing reflector viability because it reduces reflector energy gain. We calculated a maximum viable cost for these improvements of up to $2.50–4.60/m 2 , including both material and installation, in Golden. We expanded our analysis to cover a latitude range of 32–48°N and demonstrated that higher‐latitude installations with lower energy yield and higher diffuse irradiance content can support higher reflector costs. In both modeling and field tests, and for all locations, the ideal placement of the reflectors was found to be directly underneath the module due to the optimized rear irradiance increase.

14 SOLAR ENERGY↗
DOE OSTI2018

A sorghum NAC gene is associated with variation in biomass properties and yield potential

Abstract Sorghum bicolor is a C 4 grass widely cultivated for grain, forage, sugar, and biomass. The sorghum Dry Stalk (D) locus controls a qualitative difference between juicy green (dd) and dry white (D‐) stalks and midribs, and co‐localizes with a quantitative trait locus for sugar yield. Here, we apply fine‐mapping and genome‐wide association study ( GWAS ) to identify a candidate gene underlying D , and use nearly isogenic lines (NILs) to characterize the transcriptional, compositional, and agronomic effects of variation at the D locus. The D locus was fine‐mapped to a 36 kb interval containing four genes. One of these genes is a NAC transcription factor that contains a stop codon in the NAC domain in the recessive (dd) parent. Allelic variation at D affects grain yield, sugar yield, and biomass composition in NILs. Green midrib ( dd) NIL s show reductions in lignin in stalk tissue and produce higher sugar and grain yields under well‐watered field conditions. Increased yield potential in dd NIL s is associated with increased stalk mass and moisture, higher biomass digestibility, and an extended period of grain filling. Transcriptome profiling of midrib tissue at the 4–6 leaf stages, when NIL s first become phenotypically distinct, reveals that dd NIL s have increased expression of a miniature zinc finger ( MIF ) gene. MIF genes dimerize with and suppress zinc finger homeodomain ( ZF ‐ HD ) transcription factors, and a ZF ‐ HD gene is associated with midrib color variation in a GWAS analysis across 1,694 diverse sorghum inbreds. A premature stop codon in a NAC gene is the most likely candidate polymorphism underlying the sorghum D locus. More detailed understanding of the sorghum D locus could help improve agronomic potential in cereals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Genotype-Environment-Management Interactions in Biomass Yield and Feedstock Composition of Photoperiod-Sensitive Energy Sorghum

Recently introduced photoperiod-sensitive (PS) biomass sorghum (Sorghum bicolor L. Moench) needs to be investigated for their yield potential under different cultivation environments with reasonable nitrogen (N) inputs. The objectives of this study were to (1) evaluate the biomass yield and feedstock quality of four sorghum hybrids with different levels of PS ranging from very PS (VPS) hybrids and to moderate PS (MPS) hybrids, and (2) determine the optimal N inputs (0~168 kg N ha -1 ) under four environments: combinations of both temperate (Urbana, IL) and subtropical (College Station, TX) regions during 2018 and 2019. Compared to TX, the PS sorghums in central IL showed higher yield potential and steady feedstock production with an extended day length and with less precipitation variability, especially for the VPS hybrids. The mean dry matter (DM) yields of VPS hybrids were 20.5 Mg DM ha -1 and 17.7 Mg DM ha -1 in IL and TX, respectively. The highest N use efficiency occurred at a low N rate of 56 kg N ha -1 by improving approximately 33 kg DM ha -1 per 1.0 kg N ha -1 input. Approximately 70% of the PS sorghum biomass can be utilized for biofuel production, consisting of 58-65% of the cell-wall components and 4-11% of the soluble sugar. Finally, this study demonstrated that the rainfed temperate area (e.g., IL) has a great potential for the sustainable cultivation of PS energy sorghum due to their observed high yield potential, stable production, and low N requirements.

09 BIOMASS FUELS↗
DOE OSTI2025

Soil fertility management for sustainable Miscanthus × giganteus production: Increased tiller weight from nitrogen management explains yield gains in aged miscanthus

Aging-related yield decline in Miscanthus × giganteus (miscanthus) remains a major constraint to sustainable biomass production. This study evaluated how nitrogen (N) management and soil fertility influence yield-component traits and productivity in aging miscanthus. Trials were conducted at two sites established in 2008 at the University of Illinois Energy Farm, Urbana, IL. (i) The Sun Grant trial received 0, 60, and 120 kg N ha −1 annually until 2015. Starting 2021, half of each plot received 60 or 120 kg N ha −1 , resulting in six legacy-contemporary treatments: 0N–0N, 0N–120N, 60N–0N, 60N–60N, 120N–0N, 120N–120N. (ii) The Energy Farm trial remained unfertilized until 2014, when one half of each plot received 56 kg N ha −1 , forming two treatments: 0N–0N, 0N–56N. Sun Grant trial results showed N fertilization increased tiller density (tillers m −2 ) and tiller weight (g tiller −1 ) in juvenile to early-mature miscanthus (2011–2015). After N withdrawal, both traits declined (20 % and 40 %), though legacy effects persisted in tiller weight in the aging stands (2020–2023). Contemporary N had little effect on tiller density but increased tiller weight by 34 %–77 %, resulting in 23 %–106 % higher machine-harvested biomass yield in 0–120N, 60-60N, and 120-120N plots. At the Energy Farm trial, 0N–56N plots yielded 59 %–108 % more biomass than 0N–0N. Soil total N increased (Sun Grant: 47 % by 2020; Energy Farm: 58 % by 2023), while Mehlich-3 P (42 %–44 %) and K (21 %–46 %) declined. These findings identify tiller weight as a key determinant of biomass yield in aging miscanthus and highlight the need for P and K management for long-term productivity.

09 BIOMASS FUELS↗
DOE OSTI2023

Influence of graphite geography on the yield of mechanically exfoliated few-layer graphene

Some of graphene's exciting properties that inspired countless studies over the last two decades are exclusive to defect-free, few-layer graphene (FLG, ≤4 layers) produced by mechanical exfoliation. Despite graphite exfoliation having been thoroughly studied, the influence of the graphite source on the successful exfoliation of FLG remains unexplored. Here, in this work, we examine the physicochemical properties and exfoliation performance of various graphite types (e.g., natural crystalline flake, natural vein, and synthetic) from around the globe (e.g., Alaska, Tanzania, China, etc.). We first established a normalization method for the facile comparison of FLG (Φ) yields between separately exfoliated graphites. Using this approach, we find that the relative yield of FLG ranges from 0% to 22% across graphite types, with regular natural crystalline flakes (NCF-R) performing the best overall (Φ NCF-R = 16% ± 5%). FLG yield was also found to depend on source geography, evidenced by Φ NCF-R ranging from 8% to 22% for NCF-R sourced from Alabama and Canada, respectively. We employed machine learning and Pearson correlation analysis to determine the graphite characteristics that govern FLG yield. Graphite source-dependent properties such as graphite surface area and mineral impurities, including aluminum and calcium, were found to be critically important. Our findings highlight the importance of the graphite source when trying to maximize the yield of mechanically exfoliated FLG and represent an important step toward producing higher quantities of defect-free FLG for graphene-based research.

42 ENGINEERING↗
DOE OSTI2022

Predicting the rheology of limestone calcined clay cements (LC 3 ): Linking composition and hydration kinetics to yield stress through Machine Learning

The physicochemical characteristics of calcined clay influence yield stress of limestone calcined clay cements (LC 3 ), but the independent influences the clay's physical and chemical characteristics as well as the effect of other variables on LC 3 rheology are less well-understood. Further, a relationship between LC 3 hydration kinetics and yield stress – important for informing mixture design – has not yet been established. Here, rheological properties were determined in pastes with varying water-to-solid ratio (w/s), constituent mass ratios (PC:metakaolin:limestone), limestone particle size and gypsum content. From these data, an ML model developed allowed the independent examination of the different mechanisms by which metakaolin fraction influences yield stress of LC 3 , identifying four predictors – packing index, Al 2 O 3 /SO 3 , total particle density and metakaolin fraction relative to limestone (MK/LS) – most significant for predicting LC 3 yield stress. A methodology based on kernel smoothing also identified hydration kinetics parameters best correlated with yield stress.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The role of specimen size and grain boundary characteristics in the yield strength of tungsten in microtensile tests

To effectively use the measured properties from small-scale tensile tests for bulk material performance predictions, it is essential to understand the threshold of specimen size-effect strengthening and the interaction between dislocations and microstructures within miniaturized specimens. This study uses pure tungsten to investigate the size effect in terms of specimen size, grain size, and grain boundary characteristics relative to the yield strength of tungsten at room temperature. We evaluate the transition from miniaturized specimen properties to bulk properties and the deformation behavior through small-scale tensile tests of three specimen sizes (large: 80 × 100 × 233 µm³; medium: 7 × 7 × 18 µm³; and small: 2 × 2 × 5 µm³). The testing results reveal that the small and medium specimens exhibit high yield strength with ductile behavior, while the large specimens exhibit brittle failure, consistent with the room temperature strength of tungsten, indicating bulk behavior. We further explore the specimen size-effect sensitivity to yield stress and the scaling relationship between yield strength and the number of grains involved in the deformation. A power-law relationship with the exponent value of approximately -0.5 was found in the yield strength–grain number scaling, implying the Hall-Petch like behavior. A minimum of 7–17 effective grain boundaries across the tensile gauge dimension is required to accurately measure bulk properties.

36 - MATERIALS SCIENCE↗
DOE OSTI2014

Effects of growth parameters on the yield and morphology of Si{sub 3}N{sub 4} microcoils prepared by chemical vapor deposition

Highlights: • CVD method was successfully applied to obtain Si{sub 3}N{sub 4} microcoils in high yield without the presence of catalyst. • The process was systematically investigated through a series of control experiments. • The effects of synthesis parameters on the yield and morphology of Si{sub 3}N{sub 4} microcoils were found. • The growth mechanism of the Si{sub 3}N{sub 4} microcoils could be explained by the different growth rates between the amorphous layer and the crystalline layer. - Abstract: In this study, we provided a reliable chemical vapor deposition (CVD) method to synthesize high-purity Si{sub 3}N{sub 4} microcoils in high yield without the presence of catalyst. The achieved products were characterized by X-ray diffraction, scanning electron microscopy, and transmission electron microscope. The results indicated that the yield and morphology of Si{sub 3}N{sub 4} products were influenced by the synthesis parameters such as reaction temperature, reaction time and gas flow rate. The particular conditions favorable to high yield synthesis of Si{sub 3}N{sub 4} microcoils were obtained through a series of control experiments. Furthermore, the growth of Si{sub 3}N{sub 4} microcoils was supposed to be in accord with vapor-solid (VS) growth process and the different growth rates between the amorphous layer and the crystalline layer were used to explain the formation of the coil geometry.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sensitivity of the simulation of passive neutron emission from UF 6 cylinders to the uncertainties in both 19 F(α,n) energy spectrum and thick target yield of 234 U in UF 6

Interest in safeguards verification measurements using passive thermal neutron counting to assay 235 U content in large 30B UF 6 canisters has grown in recent years. Here, the prohibitively high cost and impracticality of using reference 30B calibration cylinders extensively will likely make accurate simulations of increasing interest. Accuracy of the simulated response will define the confidence in the predicted response and the extent to which simulations can reasonably be relied upon. With 234 U driven 19 F(α, n) reactions being the main neutron source in low enriched UF 6 the uncertainties of the 19 F(α, n) energy spectrum and the thick target yield of 234 U in UF 6 propagate into the uncertainty in the predicted response and represent a major influence of basic nuclear data. Here sensitivity of the simulated total (Singles) and coincidence (Doubles) count rates are assessed for the Passive Neutron Enrichment Meter using six potential 19 F(α, n) neutron energy spectra over a range of enrichments and material distributions. The results indicate that variations in the Singles and Doubles due to simulated (α, n) neutron spectrum are less than 1.5% for this set of simulated neutron spectra, with dependence varying inversely with enrichment. Singles uncertainty is only slightly less than that of the thick target 19 F(α, n) yield corresponding to the primary neutron source, whereas the 19 F(α, n) yield dependence of the Doubles is reduced by the non-negligible 238 U(SF) coincident neutron emissions. Based on available thick target 19 F(α, n) yield estimates the uncertainty is on the order of 5%, establishing this as the main nuclear data limitation when simulating thermal neutron detectors response for 30B UF 6 storage cylinders. Based on these findings, it appears that the measurement and evaluation of the thick target 19 F(α, n) yield for uranium hexafluoride is due.

19F(α,n) neutron spectrum↗
DOE OSTI2019

Influences of nitrogen fertilization and climate regime on the above-ground biomass yields of miscanthus and switchgrass: A meta-analysis

Perennial grasses are touted as sustainable feedstocks for energy production. Such benefits, however, may be offset if excessive nitrogen (N) fertilization leads to economic and environmental issues. Moreover, as yields respond to changes in climate, nutrient requirements will change, and thus guidance on minimal N inputs is necessary to ensure sustainable bioenergy production. Here, a pairwise meta-analysis was conducted to investigate the effects of N fertilization (amount and duration) and climate on the above-ground biomass yields of miscanthus ( Miscanthus x giganteus ) and switchgrass ( Panicum virgatum L. ). Both regression models and meta-analyses showed that switchgrass was more responsive to N than miscanthus, although both showed significant and positive N effects. Meta-analysis further showed that the positive growth response of miscanthus to N application increased with N addition rates of 60–300 kg N ha -1 year -1 , but the magnitude of the response decreased with the number of years of fertilization (duration). N effects on switchgrass biomass increased and peaked at rates of 120–160 kg N ha -1 year -1 and 5–6 years of N inputs, but diminished for rates >300 kg N ha -1 year -1 and >7 years. Meta-analysis further revealed that the influences of N on switchgrass increased with both mean annual temperature and precipitation. Miscanthus yields were less responsive to climate than switchgrass yields. This meta-analysis helps fill a gap in estimation of biofeedstock yields based on N fertilization and could help better estimate minimum N requirements and soil management strategies for miscanthus and switchgrass cultivation across climatic conditions, thereby improving the efficiency and sustainability of bioenergy cropping systems.

09 BIOMASS FUELS↗
DOE OSTI2015

Elimination of metabolic pathways to all traditional fermentation products increases ethanol yields in Clostridium thermocellum

Clostridium thermocellum has the natural ability to convert cellulose to ethanol, making it a promising candidate for consolidated bioprocessing (CBP) of cellulosic biomass to biofuels. To further improve its CBP capabilities, we study a mutant strain of C. thermocellum that was constructed (strain AG553; C. thermocellum Δhpt ΔhydG Δldh Δpfl Δpta-ack ) to increase flux to ethanol by removing side product formation. Strain AG553 showed a two- to threefold increase in ethanol yield relative to the wild type on all substrates tested. On defined medium, strain AG553 exceeded 70% of theoretical ethanol yield on lower loadings of the model crystalline cellulose Avicel, effectively eliminating formate, acetate, and lactate production and reducing H 2 production by fivefold. On 5 g/L Avicel, strain AG553 reached an ethanol yield of 63.5% of the theoretical maximum compared with 19.9% by the wild type, and it showed similar yields on pretreated switchgrass and poplar. The elimination of organic acid production suggested that the strain might be capable of growth under higher substrate loadings in the absence of pH control. Final ethanol titer peaked at 73.4 mM in mutant AG553 on 20 g/L Avicel, at which point the pH decreased to a level that does not allow growth of C. thermocellum , likely due to CO 2 accumulation. In comparison, the maximum titer of wild type C. thermocellum was 14.1 mM ethanol on 10 g/L Avicel. In conclusion, with the elimination of the metabolic pathways to all traditional fermentation products other than ethanol, AG553 is the best ethanol-yielding CBP strain to date and will serve as a platform strain for further metabolic engineering for the bioconversion of lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2023

Co-Hydrotreatment of Yellow Greases and the Water-Insoluble Fraction of Pyrolysis Oil. Part I: Experimental Design to Increase Kerosene Yield and Reduce Coke Formation

Here, this paper reports the co-hydrotreatment of Biomass Technology Group commercial pyrolysis oil water-insoluble (WIS) phase (also known as pyrolytic lignin) and yellow greases (waste cooking oil), aiming to produce sustainable aviation fuels (SAFs). We use a sulfided NiMo/Al 2 O 3 blend with 16 wt % WIS and a central composite experimental design to identify processing conditions increasing kerosene yield and reducing coke formation. The input variables were: (1) reaction temperature (320, 350, and 380 °C), (2) initial hydrogen pressure (5, 6, and 7 MPa), and (3) amount of catalyst (0.7, 1.0, and 1.3 g). The hydrotreated oily phases were distilled to obtain gasoline (<150 °C), kerosene (150–250 °C), diesel (250–350 °C), and residual oil (>350 °C). The reaction temperature is the main factor affecting the yield of gaseous, solid, and liquid products. Meanwhile, a higher initial hydrogen pressure and catalyst loading increased the yield of kerosene and other distillates and decreased the coke formation. A high temperature correlated with a lower content of oxygenates in kerosene cuts. Based on our experimental results, we propose to conduct hydrotreatment studies at 380 °C, initial H 2 pressure of 7 MPa, and 1.3 g of catalyst. Under the identified conditions, it was possible to improve the kerosene yield to more than 20 wt % and reduce the yield of coke to close to 2.0 wt %. The chemical composition and fuel properties of the gasoline, kerosene, and diesel cuts were thoroughly analyzed. The content of aromatics and phenols in the kerosene fraction produced at the conditions identified in this project exceeded the recommended values for SAFs. New strategies (such as blending and more intense hydrotreatment to remove oxygenated compounds) need to be implemented to reduce the content of these molecules in our final product.

09 BIOMASS FUELS↗
DOE OSTI2022

Monoterpene Photooxidation in a Continuous-Flow Chamber: SOA Yields and Impacts of Oxidants, NO x , and VOC Precursors

We report monoterpene photooxidation plays an important role in secondary organic aerosol (SOA) formation in the atmosphere. The low-volatility products can enhance new particle formation and particle growth, and thus have influences on climate feedbacks. Here, we present the results of α-pinene and Δ-3-carene photooxidation experiments conducted in continuous-flow mode in an environmental chamber under several reaction conditions. The roles of oxidants, addition of NO, and VOC molecular structure in influencing SOA yield are illustrated. SOA yield from α-pinene photooxidation shows a weak dependence on H 2 O 2 concentration, which is a proxy for HO 2 concentration. The high O/C ratios observed in the a-pinene photooxidation products suggest the production of highly oxygenated organic molecules (HOM). Addition of ozone to the chamber during low-NO x photooxidation experiments leads to higher SOA yield. With the addition of NO, the production of N-containing HOMs is enhanced and the SOA yield shows a modest, non-linear dependence on input NO concentration. Carene photooxidation leads to higher SOA yield than α-pinene under similar reaction conditions, which agrees with the lower volatility retrieved from evaporation kinetics experiments. These results improve the understanding of SOA formation from monoterpene photooxidation and could be applied to refine the representation of biogenic SOA formation in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Yielding Behavior of Bottlebrush and Linear Block Copolymers

Block copolymers can exhibit a pronounced yield stress, but the impact of molecular architecture, chemistry, and self-assembly on macroscopic rheology remains poorly understood. Here, we study the linear-viscoelastic and yield-stress fluid behavior of two architectures—bottlebrush copolymers (with statistical or blocky sequences) and linear diblocks—that self-assemble into body-centered cubic (BCC) spheres and hexagonally close-packed cylinders (HEX). The dynamic properties of these polymers were probed by oscillatory frequency and amplitude sweeps at temperatures well below the order–disorder transition (TODT) to furnish insights into the yielding transition. All BCC-forming polymers have a similar signature of yielding: smaller yield strains (γ yBCC ≈ 0.053 < γ y,HEX ≈ 0.18), sharper solid–liquid transitions, and better reversibility than HEX. Statistical bottlebrushes show the most frequency-independent structural modulus (G 0 ) and no signs of defect relaxation. A simple power-law relationship captures the dependence of the normalized structural modulus (G 0 /RT) on the inter-micelle distance (d) across different architectures and morphologies [G 0 /(RT) = 1.31 × 10 4 (nm 2.6 mol/m 3 ) d –2.6 ]. These studies establish quantitative structure–property relationships that are relevant in contemporary applications, for example, extrusion-based 3D printing.

36 MATERIALS SCIENCE↗