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DOE OSTI2026

Data for Impacts of Legacy and Contemporary Nitrogen Inputs on N2O and CO2 Emissions in Miscanthus and Maize Cultivated Soils

Nutrient inputs influence the sustainability of bioenergy crop production through contemporary (shortly after addition) and legacy effects (persisting over years) on microbial nitrogen (N) and carbon cycling, which contribute to greenhouse gas emissions. However, the relative importance of contemporary and legacy effects and how that could vary by crop functional types is poorly understood. Considering its rhizomatous roots and perennial growth, we hypothesized that Miscanthus × giganteu s ( M × g ) would be more sensitive to legacy N fertilization and the historical context of its environment than an annual crop like maize. To test this hypothesis, we examined the effects of legacy and contemporary N inputs on nitrous oxide (N2O) and carbon dioxide (CO2) emissions, as well as key N cycling genes in soils where M × g and maize were grown. A 150-day soil incubation experiment was conducted using soils from a long-term M × g and maize fertility experiment with three historic N fertilization rates (0, 112, and 336 kg N ha−1 year−1) and a contemporary amendment (60 mg N kg−1) with negative control (0 mg N kg−1). We observed significant increases in cumulative N2O emissions in M × g soils relative to maize soils, particularly at higher legacy fertilization rates, while contemporary N had no significant effect. Bacterial amoA gene abundance, which plays a significant role in nitrification in nutrient-rich soils, also increased with higher legacy fertilization rates in M × g soils but was unaffected by the contemporary N. In maize soils, legacy and contemporary N did not significantly affect N2O emissions, but cumulative CO2 emissions and amoA gene abundance significantly increased. The abundances of norB genes were not significantly influenced by either legacy fertilization or contemporary N amendments in either soil. Our findings demonstrate the greater importance of fertilization history over contemporary N in mediating soil N2O emissions, particularly for perennial bioenergy crops.

Carbon↗

DOE OSTI2023

Changes in soil pore structure generated by the root systems of maize , sorghum and switchgrass affect in situ N 2 O emissions and bacterial denitrification

Due to the heterogeneous nature of soil pore structure, processes such as nitrification and denitrification can occur simultaneously at microscopic levels, making prediction of small-scale nitrous oxide (N 2 O) emissions in the field notoriously difficult. We assessed N 2 O+N 2 emissions from soils under maize (Zea mays L.), switchgrass (Panicum virgatum L.), and energy sorghum (Sorghum bicolor L.), three potential bioenergy crops in order to identify the importance of different N 2 O sources to microsite production, and relate N 2 O source differences to crop-associated differences in pore structure formation. The combination of isotopic surveys of N 2 O in the field during one growing season and X-ray computed tomography (CT) enabled us to link results from isotopic mappings to soil structural properties. Further, our methodology allowed us to evaluate the potential for in situ N 2 O suppression by biological nitrification inhibition (BNI) in energy sorghum. Our results demonstrated that the fraction of N 2 O originating from bacterial denitrification and reduction of N 2 O to N 2 is largely determined by the volume of particulate organic matter occluded within the soil matrix and the anaerobic soil volume. Bacterial denitrification was greater in switchgrass than in the annual crops, related to changes in pore structure caused by the coarse root system. This led to high N-loses through N 2 emissions in the switchgrass system throughout the season a novel finding given the lack of data in the literature for total denitrification. Isotopic mapping indicated no differences in N 2 O-fluxes or their source processes between maize and energy sorghum that could be associated with the release of BNI by the investigated sorghum variety. The results of this research show how differences in soil pore structures among cropping systems can determine both N 2 O production via denitrification and total denitrification N losses in situ.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Origins of wear-induced tungsten corrosion defects in semiconductor manufacturing during tungsten chemical mechanical polishing

During chemical mechanical polishing (CMP) process optimization, a unique corrosion defect was identified in the tungsten (W) contact plugs, which were investigated to develop practical solutions to improve CMP mass productivity. The corrosion defect occurred in the absence of external incident energy and was observed to occur only at the W plugs connected to the P + /n-well close to the wafer edge. To examine the root cause of the corrosion, a series of experiments was carried out at each W CMP step, using in-line defect inspection. Additional experiments were conducted using on-line inductively coupled plasma mass spectrometry (ICP-MS) to understand pH- and potential-dependent electrochemical dissolution behaviors of W. Experimentally, W corrosion was confirmed to be exacerbated if the surface oxide of the W plugs is removed by the deionized water (DIW) rinsing step under wafer pressurization, then exposed to DIW and alkaline cleaning solution. Although the DIW rinsing step is commonly performed to clean polishing pads right after the main polishing, a small amount of applied pressure (0.5 psi) without slurry supply can lead to corrosion defects. Finally, this wear-induced corrosion of the W plugs can be prevented by removing the applied pressure during the post DIW rinsing step of W CMP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A machine learning approach for clinker quality prediction and nonlinear model predictive control design for a rotary cement kiln

Abstract Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard “Bogue’ model”. The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges.

Ali, Asem M.↗

DOE OSTI2020

Advances in catalytic production processes of biomass-derived vinyl monomers

Plastic industries currently source the majority of monomers from crude oil substances. Although we have witnessed a significant interest of companies in the utilization of sustainable feedstock materials for bio-based compound synthesis in the past decade, the transition to photosynthetic or chemosynthetic plant-based production in a circular carbon economy is largely slow due to complex biomass processing, costs and related reaction factors. The upgrade of the separated platform chemicals with a deeper supporting understanding of processes, models and a root–cause analysis about the underlying distribution challenges of engineered transformation mechanisms, catalyzed conversion pathways and selectivity would be beneficial to advance applied scientific development, bio-refining and manufacturing output amount. This review provides a summary, assessment and perspective for three important polymer-forming vinyl molecules, i.e. acrylic acid, methacrylic acid and styrene. These provide a backbone to produce acrylates, polystyrene, resins, rubbers, protective surface coatings, adhesives, textiles and other obtained copolymers. A succinct analytical overview on the thermo-catalytic intermediate routes for property-wise drop-in alternatives is presented. Sugars, acrolein, allyl alcohol, ethylbenzene, glycerol, 3-hydroxypropionic acid, isobutene, itaconic acid and lactic acid are considered as the main starting reactants. Catalysts span mixed metal oxides, silicates, native or impregnated zeolite frameworks (HBEA, HZSM, and MFI) and hetero-poly acids as well as homogeneous base hydroxides or platinum group metals, supported on carbon, alumina and sulfates. Finally, the article concludes with a brief state sum-up of the results, topics and opportunities for systematic future research or scaling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Transcriptional, metabolic, physiological and developmental responses of switchgrass to phosphorus limitation

Abstract Knowing how switchgrass ( Panicum virgatum L . ) responds and adapts to phosphorus (P)‐limitation will aid efforts to optimize P acquisition and use in this species for sustainable biomass production. This integrative study investigated the impacts of mild, moderate, and severe P‐stress on genome transcription and whole‐plant metabolism, physiology and development in switchgrass. P‐limitation reduced overall plant growth, increased root/shoot ratio, increased root branching at moderate P‐stress, and decreased root diameter with increased density and length of root hairs at severe P‐stress. RNA‐seq analysis revealed thousands of genes that were differentially expressed under moderate and severe P‐stress in roots and/or shoots compared to P‐replete plants, with many stress‐induced genes involved in transcriptional and other forms of regulation, primary and secondary metabolism, transport, and other processes involved in P‐acquisition and homeostasis. Amongst the latter were multiple miRNA399 genes and putative targets of these. Metabolite profiling showed that levels of most sugars and sugar alcohols decreased with increasing P stress, while organic and amino acids increased under mild and moderate P‐stress in shoots and roots, although this trend reversed under severe P‐stress, especially in shoots.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Topographical Controls on Hillslope-Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska

Observations indicate shrubs are expanding across the Arctic tundra, mainly on hillslopes and primarily in response to climate warming. However, the impact topography exerts on hydrology, nutrient dynamics, and plant growth can make untangling the mechanisms behind shrub expansion difficult. We examined the role topography plays in determining shrub expansion by applying a coupled transect version of a mechanistic ecosystem model (ecosys) in a tundra hillslope site in the Seward Peninsula, Alaska. Modeled biomass of the dominant plant functional types agreed well with field measurements (R 2 = 0.89) and accurately represented shrub expansion over the past 30 years inferred from satellite observations. In the well-drained crest position, canopy water potential and plant nitrogen (N) uptake was modeled to be low from plant and microbial water stress. Intermediate soil water content in the mid-slope position enhanced mineralization and plant N uptake, increasing shrub biomass. The deciduous shrub growth in the mid-slope position was further enhanced by symbiotic N 2 fixation primed by increased root carbon allocation. The gentle slope in the poorly drained lower-slope position resulted in saturated soil conditions that reduced soil O 2 concentrations, leading to lower root O 2 uptake and lower nutrient uptake and plant biomass. Additionally, a simulation that removed topographical interconnectivity between grid cells resulted in (1) a 28% underestimate of mean shrub biomass and (2) over or underestimated shrub productivity at the various hillslope positions. Our results indicate that land models need to account for hillslope-scale coupled surface and subsurface hydrology to accurately predict current plant distributions and future trajectories in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Soil Moisture Buffers the Impact of Precipitation Variability on Ecosystem Productivity

Water availability governs ecosystem productivity, yet estimates of vegetation sensitivity to water can differ greatly depending on whether the sensitivity is examined spatially or temporally. In particular, the spatial sensitivity is often reported to be much stronger than temporal sensitivities, leading to highly uncertain projections of ecosystem responses to future climate change when using space-for-time substitution. The large difference between spatial and temporal sensitivities remains unexplained. Prior research, however, primarily relied on precipitation as the water availability proxy, whereas vegetation responds to soil moisture. Here, we combined satellite estimates of vegetation productivity with soil moisture data across water-limited ecosystems of the continental United States (CONUS) to identify a convergent sensitivity of productivity to water availability. Using precipitation, we show that temporal sensitivity is 66% lower than spatial sensitivity overall. Our analysis identified the cause of the difference to be primarily driven by the seasonal variability of water availability, rooting depth, and soil properties. When using soil moisture instead of precipitation, we observed widespread convergence in the spatial and temporal sensitivities—that is, the two sensitivities became much more similar in magnitude across all water-limited ecosystems within CONUS. These results show that overlooking soil hydrology can inflate perceived discrepancies between spatial and temporal vegetation sensitivities, leading to biased projections of ecosystem dynamics under future hydro-climatic change.

Wang, Huiqi [University of California, Berkeley, C↗

DOE OSTI2023

Tigers at a crossroads: Shedding light on the role of Bangladesh in the illegal trade of this iconic big cat

Abstract Unsustainable wildlife trade is a major threat to many species, but quantifying trade remains challenging, as seizure data provides an incomplete understanding. For this reason, integrating multiple types of information, including interviews with actors involved in trade, is crucial if we are to understand the problem better. Hence, in this study, we digitized Bangladesh Forest Department tiger seizure records to identify trade routes and interviewed 163 individuals involved in trafficking tigers through Bangladesh's air, sea and land ports, including poachers, smugglers, and traders. We identified six ports used to import tigers, 14 ports used for tiger export and three ports showing bi‐directional trade. Elite Bangladeshis were the most important consumer group, and tigers were sourced from populations in NE India, Myanmar and Bangladesh Sundarbans to supply domestic demand. Tiger products were exported to 14 countries, including seven G20 nations, with Bangladeshi expatriates as the consumer group in three countries (United Kingdom, Germany and Qatar). Rising economic development in Bangladesh over the last decade, combined with deep‐rooted cultural ties to tiger consumption, has led to a rise in domestic demand. Additionally, rapid growth in international transport links has increased smuggling and connected local traders with global markets, increasing the complexity of global trade. These findings suggest Bangladesh is poised to play a pivotal role in tiger conservation over the next decade, requiring strong national strategies to reduce trade opportunities, disrupt networks and weaken demand.

Uddin, Nasir↗

DOE OSTI2024

Transgenic Sugarcane–Oilcane: An Alternative Feedstock for the Production of Drop-in Fuel and Value-Added Bioproducts

The utilization of plants and other agricultural produce can partly offset petroleum dependency for energy requirements and can potentially provide sustainable solutions to global environmental problems. To this end, synthetic biology has shown great potential in developing transgenic bioenergy grasses such as sugarcane, sorghum, miscanthus, and energy cane that hyperaccumulate energy-rich lipid molecules in their vegetative tissues, such as leaves, stems, and roots. These perennial high-biomass transgenic C4 grasses are not targeted to grow on prime agricultural land and can be dedicatedly used to produce biofuels and other value-added bioproducts. Recently, sugarcane has been metabolically engineered to sequestrate carbon from juice towards biosynthesis of lipid molecules in the vegetative tissues. Transgenic sugarcane is referred to as “oilcane.” Transgenic sugarcane–oilcane has improved energy density due to an elevated lipid content in the vegetative tissues. Transgenic bioenergy crops cater to both cellulosic sugars and vegetative lipids, hence resulting in higher biofuel yield (biodiesel/renewable diesel and bioethanol) per unit area of cultivable land. In this book chapter, the genetic engineering of sugarcane and its bioprocessing are discussed to illustrate its development and use as an alternative feedstock for the production of biofuels (bio-jet fuel, biodiesel, and bioethanol) and value-added bioproducts.

Maitra, Shraddha↗

DOE OSTI2021

A decreasing carbon allocation to belowground autotrophic respiration in global forest ecosystems

Belowground autotrophic respiration (RAsoil) depends on carbohydrates from photosynthesis flowing to roots and rhizospheres, and is one of the most important but least understood components in forest carbon cycling. Carbon allocation plays an important role in forest carbon cycling and reflects forest adaptation to changing environmental conditions. However, carbon allocation to RAsoil has not been fully examined at the global scale. To fill this knowledge gap, first, the spatio-temporal patterns of RAsoil from 1981 to 2017 were predicted by a Random Forest (RF) algorithm using the most updated Global Soil Respiration Database (v5) with global environmental variables; second, carbon allocation from photosynthesis to RAsoil (CAB), was calculated as the ratio of RAsoil to gross primary production; and its temporal and spatial patterns were assessed in global forest ecosystems. . Globally, mean RAsoil from forests was 8.9 ± 0.08 Pg C yr-1 (mean ± standard deviation) from 1981 to 2017 with strong spatial variabilities. Temporally, RAsoil increased at a rate of 0.0059 Pg C yr-2, paralleling broader soil respiration changes and indicating increasing carbon respired by roots. Mean CAB was 0.243 ± 0.016 and decreased over time. The temporal trend of CAB varied greatly in space, reflecting uneven responses of CAB to environmental changes. This study is the first attempt to predict global CAB and analyze its temporal and spatial patterns. With the linkage of carbon use efficiency, the developed CAB offers an completely independent approach to quantify global aboveground autotropic respiration spatially and temporally, which could provide crucial insights into carbon flux partition and global carbon cycling under climate change.

Tang, Xiaolu↗

DOE OSTI2023

Modulation of polar auxin transport identifies the molecular determinants of source–sink carbon relationships and sink strength in poplar

Abstract Source-to-sink carbon (C) allocation driven by the sink strength, i.e., the ability of a sink organ to import C, plays a central role in tissue growth and biomass productivity. However, molecular drivers of sink strength have not been thoroughly characterized in trees. Auxin, as a major plant phytohormone, regulates the mobilization of photoassimilates in source tissues and elevates the translocation of carbohydrates toward sink organs, including roots. In this study, we used an ‘auxin-stimulated carbon sink’ approach to understand the molecular processes involved in the long-distance source–sink C allocation in poplar. Poplar cuttings were foliar sprayed with polar auxin transport modulators, including auxin enhancers (AE) (i.e., IBA and IAA) and auxin inhibitor (AI) (i.e., NPA), followed by a comprehensive analysis of leaf, stem and root tissues using biomass evaluation, phenotyping, C isotope labeling, metabolomics and transcriptomics approaches. Auxin modulators altered root dry weight and branching pattern, and AE increased photosynthetically fixed C allocation from leaf to root tissues. The transcriptome analysis identified highly expressed genes in root tissue under AE condition including transcripts encoding polygalacturonase and β-amylase that could increase the sink size and activity. Metabolic analyses showed a shift in overall metabolism including an altered relative abundance levels of galactinol, and an opposite trend in citrate levels in root tissue under AE and AI conditions. In conclusion, we postulate a model suggesting that the source–sink C relationships in poplar could be fueled by mobile sugar alcohols, starch metabolism-derived sugars and TCA-cycle intermediates as key molecular drivers of sink strength.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Intraspecific Variation for Leaf Physiological and Root Morphological Adaptation to Drought Stress in Alfalfa ( Medicago sativa L.)

Drought stress reduces crop biomass yield and the profitability of rainfed agricultural systems. Evaluation of populations or accessions adapted to diverse geographical and agro-climatic environments sheds light on beneficial plant responses to enhance and optimize yield in resource-limited environments. This study used the morphological and physiological characteristics of leaves and roots from two different alfalfa subspecies during progressive drought stress imposed on controlled and field conditions. Two different soils (Experiments 1 and 2) imposed water stress at different stress intensities and crop stages in the controlled environment. Algorithm-based image analysis of leaves and root systems revealed key morphological and physiological traits associated with biomass yield under stress. The Medicago sativa subspecies (ssp.) sativa population, PI478573, had smaller leaves and maintained higher chlorophyll content (CC), leaf water potential, and osmotic potential under water stress. In contrast, M. sativa ssp. varia, PI502521, had larger leaves, a robust root system, and more biomass yield. In the field study, an unmanned aerial vehicle survey revealed PI502521 to have a higher normalized difference vegetation index (vegetation cover and plant health characteristics) throughout the cropping season, whereas PI478573 values were low during the hot summer and yielded low biomass in both irrigated and rainfed treatments. RhizoVision Explorer image analysis of excavated roots revealed a smaller diameter and a narrow root angle as target traits to increase alfalfa biomass yield irrespective of water availability. Root architectural traits such as network area, solidity, volume, surface area, and maximum radius exhibited significant variation at the genotype level only under limited water availability. Different drought-adaptive strategies identified across subspecies populations will benefit the plant under varying levels of water limitation and facilitate the development of alfalfa cultivars suitable across a broad range of growing conditions. The alleles from both subspecies will enable the development of drought-tolerant alfalfa with enhanced productivity under limited water availability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Belowground Biomass and Root:Shoot Ratios of Three Willow Cultivars at Two Sites

Belowground biomass is an important but less studied component of energy crop systems that is essential in understanding the greenhouse gas benefits of these systems. In this study, a complete above- and belowground biomass inventory (foliage, stems, stools, coarse and fine roots) was performed on three cultivars of short-rotation willow biomass crops at two sites. Mixed models were used to analyze the proportion of biomass allocated to each component and the ratios between different components. The root:shoot (R:S) ratio, defined here as the stable unharvested biomass (stool and coarse roots) divided by the shoot biomass, averaged 0.63 (SE: +0.04). Though the portion of the plant where the willows distributed their belowground biomass varied, the R:S ratio was not significantly different across sites (p = 0.8970), cultivars (p = 0.2834), nor in the site × cultivar interaction (p = 0.8481). These results may be associated with the consistently good growth across sites and limited differences in site conditions. However, the R:S ratios were affected by the overall productivity of the stand (p = 0.0978), with higher producing stands having moderately lower ratios. This information on biomass allocation between components is essential for understanding and estimating the carbon balance of these systems and breeding and selection programs.

09 BIOMASS FUELS↗

DOE OSTI2025

Modular Processing of Flare Gas for Carbon Nanoproducts

This project demonstrated the technical viability and economic promise of a modular system for converting flared natural gas into valuable carbon nanoproducts (CNPs) through catalytic chemical vapor deposition (CVD). All major project milestones were successfully completed, including reactor design and commissioning, catalyst development, process optimization, technoeconomic analysis, and application testing in concrete systems. The overarching goal was to create a scalable, field-deployable process that valorizes stranded methane by producing high-value carbon materials for use in cementitious composites. At the lab scale, the team designed and built a fluidized bed reactor optimized for use with silica fume-supported nickel catalysts synthesized via atomic layer deposition (ALD). A statistically designed sintering study enabled precise tuning of nickel nanoparticle size, identifying the influence of oxygen partial pressure, time, and temperature on catalyst morphology and performance. These insights allowed the team to target catalyst conditions that maximize carbon nanofilament growth. Subsequent CVD experiments achieved up to 31.8 wt% carbon deposition under optimized conditions, with TEM confirming the presence of nanofilament structures and sustained hydrogen evolution during reaction. Reactor upgrades and empirical fluidization studies supported the development of reliable, repeatable experimental protocols. The modular pilot-scale skid reactor was fully constructed, instrumented, and commissioned. Capable of operating at 675–800°C and pressures up to 290 psig, the system was designed for continuous operation at a carbon production rate of 1 kg/hr. Initial demonstration runs confirmed solids handling, thermal control, and system leak-tightness, although a critical reactor component (the downfeed tube) was inadvertently omitted during final assembly. This omission limited gas–solid contact and prevented meaningful carbon deposition during pilot-scale CVD runs. Nonetheless, the system operated safely under design conditions, and the root cause of performance limitations was clearly identified. Complementary work on UHPC formulations demonstrated that small additions of carbon nanoproducts, including those derived from flare gas, can significantly enhance mechanical performance while preserving workability. A comprehensive study of CNF dispersion techniques and mix design optimization led to a clear protocol for integrating these nanomaterials into concrete. Incorporation of CNPs improved flexural toughness and reduced porosity, supporting their use in high-performance infrastructure applications. A technoeconomic analysis (TEA) confirmed that this process can produce CNP-loaded catalyst material at a levelized cost below $\$$7/kg across a range of catalyst loadings and reaction yields. With estimated market values for the carbon composite product ranging from $\$$14 to over $\$$60/kg, and the ability to blend CNPs into concrete at sub-percent levels with less than 10% added cost, the system presents a compelling economic case. While additional engineering work is needed to optimize fluidization and heat transfer at scale, this project establishes a strong foundation for commercial development. The process is not only technically sound but also economically promising, representing a viable pathway for flare gas mitigation through modular carbon nanomaterial production.

03 NATURAL GAS↗

DOE OSTI2021

Loss and Isotopic Fractionation of Alkali Elements during Diffusion-Limited Evaporation from Molten Silicate: Theory and Experiments

Moderately volatile elements (MVEs) are variably depleted in planetary bodies, reflecting the imprints of nebular and planetary processes. Among MVEs, Na, K, and Rb are excellent tracers for unraveling the history of MVE depletion in planetary bodies because they have similar geochemical behaviors but can be chemically fractionated by evaporation and condensation processes. Furthermore, K and Rb are amenable to high-precision isotopic analyses, which can help constrain the conditions of evaporation and condensation. To quantitatively understand why Na, K, and Rb are depleted in planetary bodies, we have carried out vacuum evaporation experiments from basaltic melt at 1200 and 1400 °C to study their evaporation kinetics and isotopic fractionations. We chose this composition because it is relevant to evaporation from small differentiated planetesimals. The Rb isotopic compositions of the evaporation residues were measured by multicollector inductively coupled plasma mass spectrometry (MC-ICPMS), and the K isotopic compositions were measured along profiles across the residues by secondary ion mass spectrometry (SIMS). In the 1400 °C run products, we found that the concentrations of both K and Rb in the run products decreased from core to rim, which was accompanied by a heavy K isotope enrichment near the surface. This indicates that, in this run, evaporation was limited by diffusion. To use those data quantitatively, we derive analytical equations that describe the evaporation rate and isotopic fractionation associated with diffusion-limited evaporation from a sphere, slab, and cylinder in transient and quasi-steady state regimes. This model is used to tease out the roles that diffusive transport in the melt and evaporation at the melt/gas interface play in setting the elemental depletion and isotopic composition of the residue. Under our experimental conditions, volatility decreases in the order of Na, Rb, and K. Using our experimental results in a thermodynamic model, we have estimated the product γΓ of activity coefficients × evaporation coefficients of Na, Rb, and K. The measured isotopic compositions of the residues are well explained using Rayleigh distillations, whereby the relative volatilities of K and Rb isotopes are given by the square root of their masses. We use our results and previously published data to predict how K and Rb could have been lost as a function of temperature, melt composition, oxygen fugacity, and saturation degree relevant to Vesta’s building blocks. We find that the K and Rb depletions, K/Rb elemental fractionation, and δ 41 K and δ 87 Rb isotopic fractionations of Vesta (as sampled by howardite-eucrite-diogenite (HED) meteorites) are best explained by evaporation of submillimeter size objects for 0.1-10 years at moderate temperatures (~1050 °C) in a medium ~98.8% saturated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Origin of Selective Production of Hydrogen Peroxide by Electrochemical Oxygen Reduction

Oxygen reduction reaction (ORR) is one of the most important electrochemical reactions. Starting from a common reaction intermediate *–O–OH, the ORR splits into two pathways, either producing hydrogen peroxide (H 2 O 2 ) by breaking the *–O bond or leading to water formation by breaking the O–OH bond. However, it is puzzling why many catalysts, despite the strong thermodynamic preference for the O–OH breaking, exhibit high selectivity for hydrogen peroxide. Moreover, the selectivity is dependent on the potential and pH, which remain not understood. Here, for this work, we develop an advanced first-principles model for effective calculation of the electrochemical reaction kinetics at the solid–water interface, which were not accessible by conventional models. Using this model to study representative catalysts for H 2 O 2 production, we find that breaking the O–OH bond can have a higher energy barrier than breaking *–O, due to the rigidity of the O–OH bond. Importantly, we reveal that the selectivity dependence on potential and pH is rooted into the proton affinity to the former/later O in *–O–OH. For single cobalt atom catalyst, decreasing potential promotes proton adsorption to the former O, thereby increasing the H 2 O 2 selectivity. In contrast, for the carbon catalyst, the proton prefers the latter O, resulting in a lower H 2 O 2 selectivity in acid condition. These findings explain the experiments and highlight the kinetic origins of the selectivity. Our work improves the understanding of ORR by uncovering the proton affinity as a new factor and provides a new model to effectively simulate the atomic-level kinetics of heterogeneous electrochemistry.

08 HYDROGEN↗

DOE OSTI2025

Predictive links between microbial communities and biological oxygen utilization in the Arctic Ocean

Microbial metabolism influences rates of net community production (NCP), exerting a direct biological control on marine oxygen and carbon fluxes. In the Arctic, it is increasingly important to understand and quantify this process, as ecological and oceanographic conditions shift due to changing climate. Here, we describe potential ecological links between pelagic microbial diversity and an NCP precursor, biological oxygen utilization, using machine learning and paired observations of community structure and metabolic activity from a seasonally and spatially variable transect of the Arctic Ocean (2019–2020 MOSAiC Expedition). Community structure was determined using 16S (prokaryotic) and 18S (eukaryotic) rRNA gene amplicon sequencing, and metabolic activity was derived from ΔO 2 /Ar. Using self-organizing maps, we identified clear successional patterns in observed microbial community structure that were seasonally driven in the upper ocean and vertically stratified with depth. Metabolic activity was also stratified, with a primarily net heterotrophic water column (median −1.5% biological oxygen saturation), excepting periodic oxygen supersaturation (maximum: 13.6%) within the mixed layer. Using DNA sequences as predictor variables, we then constructed a random forest regression model that reliably reconstructed biological oxygen concentrations (root mean squared error = 4.14 μmol kg −1 ). Top predictors from this model were from heterotrophic (bacteria) or potentially mixotrophic (dinoflagellate) taxa. These analyses highlight biologically driven diagnostic tools that can be used to expand biogeochemical datasets and improve the microbial perspectives and metabolisms represented in ecological models of net productivity and carbon flux in a changing Arctic Ocean.

Chamberlain, Emelia J. [Univ. of San Diego, San Di↗