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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 181 records · Page 10

Reversible and Selective CO 2 to HCO 2 − Electrocatalysis near the Thermodynamic Potential

Abstract Reversible catalysis is a hallmark of energy‐efficient chemical transformations, but can only be achieved if the changes in free energy of intermediate steps are minimized and the catalytic cycle is devoid of high transition‐state barriers. Using these criteria, we demonstrate reversible CO 2 /HCO 2 − conversion catalyzed by [Pt(depe) 2 ] 2+ (depe=1,2‐ bis (diethylphosphino)ethane). Direct measurement of the free energies associated with each catalytic step correctly predicts a slight bias towards CO 2 reduction. We demonstrate how the experimentally measured free energy of each step directly contributes to the <50 mV overpotential. We also find that for CO 2 reduction, H 2 evolution is negligible and the Faradaic efficiency for HCO 2 − production is nearly quantitative. A free‐energy analysis reveals H 2 evolution is endergonic, providing a thermodynamic basis for highly selective CO 2 reduction.

Cunningham, Drew W.↗

Phase Diagrams of Alloys and Their Hydrides via On-Lattice Graph Neural Networks and Limited Training Data

Efficient prediction of sampling-intensive thermodynamic properties is needed to evaluate material performance and permit high-throughput materials modeling for a diverse array of technology applications. To alleviate the prohibitive computational expense of high-throughput configurational sampling with density functional theory (DFT), surrogate modeling strategies like cluster expansion are many orders of magnitude more efficient but can be difficult to construct in systems with high compositional complexity. We therefore employ minimal-complexity graph neural network models that accurately predict and can even extrapolate to out-of-train distribution formation energies of DFT-relaxed structures from an ideal (unrelaxed) crystallographic representation. This enables the large-scale sampling necessary for various thermodynamic property predictions that may otherwise be intractable and can be achieved with small training data sets. Two exemplars, optimizing the thermodynamic stability of low-density high-entropy alloys and modulating the plateau pressure of hydrogen in metal alloys, demonstrate the power of this approach, which can be extended to a variety of materials discovery and modeling problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reversible and Selective CO 2 to HCO 2 - Electrocatalysis near the Thermodynamic Potential

Reversible catalysis is an emblem of energy-efficient chemical transformations, but can only be achieved if the changes in free energy of intermediate steps are minimized and the catalytic cycle is devoid of high transition-state barriers. Using these criteria, we show reversible CO 2 /HCO 2 - conversion catalyzed by [Pt(depe) 2 ] 2+ (depe=1,2- bis (diethylphosphino)ethane). Direct measurement of the free energies associated with each catalytic step correctly predicts a slight bias towards CO 2 reduction. We demonstrate how the experimentally measured free energy of each step directly contributes to the <50mV overpotential. We also find that for CO 2 reduction, H 2 evolution is negligible and the Faradaic efficiency for HCO 2 - production is nearly quantitative. A free-energy analysis reveals H 2 evolution is endergonic, providing a thermodynamic basis for highly selective CO 2 reduction.

10 SYNTHETIC FUELS↗

Determining the bubble nucleation efficiency of low-energy nuclear recoils in superheated C 3 F 8 dark matter detectors

The bubble nucleation efficiency of low-energy nuclear recoils in superheated liquids plays a crucial role in interpreting results from direct searches for weakly interacting massive particle (WIMP) dark matter. Here, the PICO collaboration presents the results of the efficiencies for bubble nucleation from carbon and fluorine recoils in superheated C 3 F 8 from calibration data taken with five distinct neutron spectra at various thermodynamic thresholds ranging from 2.1 to 3.9 keV. Instead of assuming any particular functional forms for the nuclear recoil efficiency, a generalized piecewise linear model is proposed with systematic errors included as nuisance parameters to minimize model-introduced uncertainties. A Markov chain Monte Carlo routine is applied to sample the nuclear recoil efficiency for fluorine and carbon at 2.45 and 3.29 keV thermodynamic thresholds simultaneously. The nucleation efficiency for fluorine was found to be ≥ 50% for nuclear recoils of 3.3 keV (3.7 keV) at a thermodynamic Seitz threshold of 2.45 keV (3.29 keV), and for carbon the efficiency was found to be ≥ 50% for recoils of 10.6 keV (11.1 keV) at a threshold of 2.45 keV (3.29 keV). Simulated datasets are used to calculate a p value for the fit, confirming that the model used is compatible with the data. The fit paradigm is also assessed for potential systematic biases, which although small, are corrected for. Additional steps are performed to calculate the expected interaction rates of WIMPs in the PICO-60 detector, a requirement for calculating WIMP exclusion limits.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Evaluation of Nanaerobic Digestion as a Mechanism to Explain Surplus Methane Production in Animal Rumina and Engineered Digesters

Nanaerobes are a newly described class of microorganisms that use a unique cytochrome bd oxidase to achieve nanaerobic respiration at <2 μM dissolved oxygen (~1% of atmospheric oxygen) but are not viable above this value due to the lack of other terminal oxidases. Although sharing an overlapping ecological niche with methanogenic archaea, the role of nanaerobes in methanogenic systems has not been studied so far. To explore their occurrence and significance, we re-analyzed published meta-omic datasets from animal rumina and waste-to-energy digesters, including conventional anaerobic digesters and anaerobic digesters with ultra-low oxygenation. Results show that animal rumina share broad similarities in the microbial community and system performance with oxygenated digesters, rather than with conventional anaerobic digesters, implying that trace levels of oxygen drive the efficient digestion in ruminants. The rumen system serves as an ideal model for the newly named nanaerobic digestion, as it relies on the synergistic co-occurrence of nanaerobes and methanogens for methane yield enhancement. The most abundant ruminal bacterial family Prevotellaceae contains many nanaerobes, which perform not only anaerobic fermentation but also nanaerobic respiration using cytochrome bd oxidase. These nanaerobes generally accompany hydrogenotrophic methanogens to constitute a thermodynamically and physiologically consistent framework for efficient methane generation. Our findings provide new insights into ruminal methane emissions and strategies to enhance methane generation from biomass.

59 BASIC BIOLOGICAL SCIENCES↗

Determining the bubble nucleation efficiency of low-energy nuclear recoils in superheated C$_3$F$_8$ dark matter detectors

The bubble nucleation efficiency of low-energy nuclear recoils in superheated liquids plays a crucial role in interpreting results from direct searches for weakly interacting massive particle (WIMP) dark matter. The PICO Collaboration presents the results of the efficiencies for bubble nucleation from carbon and fluorine recoils in superheated C$_3$F$_8$ from calibration data taken with 5 distinct neutron spectra at various thermodynamic thresholds ranging from 2.1 keV to 3.9 keV. Instead of assuming any particular functional forms for the nuclear recoil efficiency, a generalized piecewise linear model is proposed with systematic errors included as nuisance parameters to minimize model-introduced uncertainties. A Markov-Chain Monte-Carlo (MCMC) routine is applied to sample the nuclear recoil efficiency for fluorine and carbon at 2.45 keV and 3.29 keV thermodynamic thresholds simultaneously. The nucleation efficiency for fluorine was found to be $\geq 50\, \%$ for nuclear recoils of 3.3 keV (3.7 keV) at a thermodynamic Seitz threshold of 2.45 keV (3.29 keV), and for carbon the efficiency was found to be $\geq 50\, \%$ for recoils of 10.6 keV (11.1 keV) at a threshold of 2.45 keV (3.29 keV). Simulated data sets are used to calculate a p-value for the fit, confirming that the model used is compatible with the data. The fit paradigm is also assessed for potential systematic biases, which although small, are corrected for. Additional steps are performed to calculate the expected interaction rates of WIMPs in the PICO-60 detector, a requirement for calculating WIMP exclusion limits.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Efficient separation of xylene isomers by using a robust calcium-based metal–organic framework through a synergetic thermodynamically and kinetically controlled mechanism

Adsorptive separation of physically and chemically similar molecules and understanding the underlying host–guest interactions at the molecular level are of significant scientific and practical importance. Here we report the development of a novel calcium-based metal–organic framework, formulated as Ca 3 (Htcpp) 2 (H 4 tcpp = 2,3,5,6-tetrakis(4-carboxyphenyl)-pyrazine) featuring microporosity and high stability. This compound shows distinct adsorption behavior toward xylene isomers and is capable of separating them efficiently at an industrially relevant temperature. The selective adsorption is attributed to a synergetic thermodynamic and kinetic effect. Here, the host–guest interactions were probed directly by single-crystal X-ray diffraction analysis and the adsorption affinity was evaluated through computational molecular simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carbonate Management to Enable Energy- and Carbon-Efficient CO 2 Electrolysis (Final Technical Report)

The rapid growth and plummeting cost of solar energy have spurred growing interest in using CO 2 electrolysis to produce chemicals and fuels as an alternative to conventional petrochemical processes. High-temperature (>800 °C) solid oxide electrolyzers that convert CO 2 into CO and O 2 have recently become commercially available. Low-temperature electrolysis cells offer the prospect of more convenient and flexible operation, which is critical for utilizing intermittent solar energy, and provide access to more valuable C 2+ products such as ethylene, ethanol, and propanol. Over the past 10 years, research in this area has yielded substantial progress in both fundamental understanding of the requisite electrocatalytic reactions and design of prototype devices. Leveraging insights from fuel cells and membrane water electrolyzers, researchers have developed electrolysis cells with gas diffusion electrodes (GDE) that have demonstrated high CO 2 electrolysis current densities (>100 mA cm –2 ) as well as promising selectivity and stability. Despite these advances, the energy efficiency (electrical energy-to-product) and carbon efficiency (CO 2 -to-product) of low-temperature CO 2 electrolysis remain far too low for large-scale deployment. A preponderance of evidence indicates that the principal source of efficiency losses is the rapid and thermodynamically favorable reaction of CO 2 with hydroxide (OH – ) to form carbonate (CO 3 2– ). Carbonate formation imposes steady-state electrolysis conditions that result in large voltage and CO 2 losses for all known (photo)electrochemical CO 2 cells. While much current research remains focused on CO 2 reduction catalyst design, this largely overlooked CO 3 2– problem presents a fundamental scientific barrier to creating a viable electrochemical option for converting solar energy into chemicals and fuels. The project pursues an integrated, multi-PI research effort that establishes a fundamental science of CO 3 2– management. PI Kanan and Co-PI Mani’s contribution to the project is to evaluate strategies to mitigate the CO 3 2– problem by changing the properties of the electrolyte and the environment in which CO 2 reduction catalysis takes place. Experimental studies showed that electrolytes composed of a high concentration of both CO 3 2– and HCO 3 – , which serve as moderately alkaline buffers, improved the cell voltage by compared to all-HCO 3 – electrolytes, but these buffered systems still show substantial CO 2 uptake that reduces pH over time. Computational studies developed a homogenized model of a CO 2 reduction catalyst layer that permits a low-cost exploration of the high-dimensional parameter space associated with catalyst layers on gas diffusion electrodes. The model was validated by accurately reproducing experimental data for the related but simpler reaction of CO reduction and then used to probe the effects of catalyst layer architecture on CO 2 reduction. Minimizing the size of catalyst and hydrophobic domains in the catalyst layer is predicted to mitigate CO 3 2– formation and thereby enable prolonged operation at elevated pH. In support of the CO 2 electrolysis studies, a new method for rapidly prototyping electrochemical cells was developed and validated. The method uses a combination of 3D printing and electroless plating to generate conductive cell components for evaluating new cell designs. The carbonate problem encompasses mass transport processes and acid-base reactions that are relevant to many other electrochemical systems. Investigation of strategies to address the carbonate problem led to an additional line of inquiry into the physicochemical phenomena that determine the efficiency of electrochemical acid-base production, which has numerous applications in the broader field of carbon management. New strategies for using the supporting electrolyte to inhibit H + /OH – recombination in electrochemical acid-base production were evaluated, leading to the development of a novel acid-base producing system that eliminates the need for ion exchange membranes and exhibits promising efficiency and current densities for scalable applications.

25 ENERGY STORAGE↗

Thermodynamically Stable, Plasmonic Transition Metal Oxide Nanoparticle Solar Selective Absorbers towards 95% Optical-to-Thermal Conversion Efficiency at 750 °C

Generation 3 (Gen) concentrating solar power (CSP) systems requires a high operation temperature ≥750°C to increase the power-cycle efficiency towards ≥50%. However, such a high operation temperature poses a notable challenge to high temperature materials. On the receiver side, a critical challenge is the lack of solar selective absorbers that demonstrate both high optical-to-thermal energy conversion efficiency η therm approaching 95% and long-term thermal stability at >750°C in air. Existing solar absorbers either have limited η therm ≤89% or deteriorate significantly within 500 h at 750°C; some of these also require costly vacuum deposition for stringent thickness control. Therefore, it is highly desirable to simultaneously achieve η therm ~95% AND high thermal stability at 750°C for future generations of CSP receivers. This project has investigated and developed low-cost, highly scalable spray-coated transition metal oxide nanoparticle (NP) pigmented solar selective coatings on various types of Inconel alloy tube sections that are thermodynamically stable at 750-800°C in air, maintaining η therm >94.3%(93.2%) under a solar concentration ratio of C=1000 after 60 simulated day-night cycles at 750ºC (800ºC) (1 cycle=12 h at 750 or 800°C and 12h ramping down to 25°C). We have also coated up to 48 inches long receiver tubes for preliminary solar testing under Norwich Technology’s parabolic trough systems, demonstrating notably improved performance in solar heating compared to benchmark Pyromark 2500 coatings. Two key innovations have been developed in this project: (1) We achieved an unprecedented high thermal efficiency >94% by optimizing the d-band optical absorption spectra of transition metal ions, engineering their valences and stoichiometry; (2) We were able to maintain or even slightly increase the efficiency when operating at 750°C in air by engineering the interdiffusion of transition metal ions between the coating and the Inconel substrate to our advantage. Featuring high-temperature solar spectral selectivity and thermodynamic stability in air, as well as low-cost, highly scalable solution-chemical synthesis and spray coating techniques, this innovation in solar selective absorber technology alone accounts for nearly 40% of the targeted reduction in the levelized cost of electricity (LCOE) from the receiver, thermal energy storage, and operation & maintenance combined by 2030, as proposed by the U.S. Department of Energy. For a 110 MWe CSP power plant, this LCOE reduction from the solar selective coating alone transfers to ~$\$ $1.9 M increase in annual profit based on a sales price of 10¢/kWh (or an annual sale of $50 M/year). The high solar absorptance (~98%) NP pigment materials developed in this project are equally applicable to volumetric receivers either as a coating or as bigger ceramic microspheres after sintering, potentially benefiting Gen3 falling particle CSP technologies. All these contributions facilitate the larger scale deployment of CSP systems with energy storage capability to address the intermittency issue of solar energy towards dispatchable solar electricity, bridging the temporal gap between peak solar electricity production and peak electricity consumption. The collaboration with Norwich Technologies and Brayton Energy in this project will also facilitate the future commercialization of this new solar selective coating technology developed in this SIPS project.

14 SOLAR ENERGY↗

First Principles Simulations of Electrified Interfaces in Electrochemistry

This chapter discusses some of the recent advances made in the first principles modeling of electrochemical catalysts. It also discusses the key development, namely the ability to explicitly treat the effects of surface electrification due to electrochemical processes and applied voltages in a computationally efficient manner. The chapter introduces the thermodynamics and statistical mechanics of electrified metal-solution interfaces. It then discusses the structure of the electrode-electrolyte interface and the effects of applied voltages, followed by an overview of the first-principles model and a motivating example. The chapter also provides a brief summary of classical thermodynamics and describes the basics of thermodynamic detour. It considers the thermodynamics of macroscopic systems and introduces several useful fundamental relations. Here, the chapter also considers a system to exist in a certain macrostate, which is a particular thermodynamic state specified by a set of fixed properties such as constant particle number, constant volume, and constant temperature.

36 MATERIALS SCIENCE↗

Using X-ray radiography to study oxygen flow in a proton exchange membrane electrolyzer operating under balanced pressure conditions

Of the various water electrolyzer technologies, the proton exchange membrane electrolyzer (PEMWE) is one of the best solutions for producing clean hydrogen without releasing CO 2 . In order to allow for widespread use of clean hydrogen, it is necessary to decrease its cost, which is intrinsically related to system operation. Current PEMWE plants operate in differential mode, directly pressurizing hydrogen and benefiting from thermodynamic compression, which increases overall system efficiency. However, high differential pressure above 30 bar can cause membrane stress, resulting in membrane creeping and failure. Pressurizing the water and operating at balanced pressure allows hydrogen to be produced at higher pressures while preserving the integrity of the membrane and porous layers. Nevertheless, the impact of pressurizing water on PEMWE performance must be better understood to maximize performance under balanced pressure conditions. Here, this study examined the impact of water pressure on two-phase flow. A high-pressure electrolyzer setup was developed to perform operando X-ray radiography and examine oxygen transport with high temporal resolution. The imaging segmentation process, developed to capture bubble properties in the channel, was applied to a specific experiment. The results clearly showed that as pressure increased up to 30 bars, the initial bubbly flow transitioned to slug flow, which led to channel saturation with oxygen. This work demonstrates that two-phase flow in an electrolyzer can be studied using X-ray radiography, which has the advantages of fast measurements and the ability to probe dense materials, such as those required for pressurized electrolyzers.

Balanced high pressure operation↗

Revising the dynamic energy budget theory with a new reserve mobilization rule and three example applications to bacterial growth

Dynamic energy budget (DEB) theory has been applied to model a wide range of organisms, including microbes. In the standard DEB model, biomass is partitioned into reserve and structural compartments, where reserve biomass is mobilized in a pseudolinear manner (while the reserve biomass density, defined as the ratio between reserve and structural biomass, decays linearly) to drive maintenance and the growth of structural biomass (and extracellular enzyme production if it is considered). However, the linear dynamics of the reserve biomass density makes the standard DEB model incapable of explaining the slowdown of microbial growth at high reserve density that is caused by macromolecular crowding effect which reduces biochemical reaction rates (a typical situation occurs when microbes are experiencing severe moisture stress) and is inconsistent with the observation that intracellular enzymatic reactions generally follow non-linear kinetics. By partitioning biomass into reserve, kinetic, and structural compartments, we show here that the Equilibrium Chemistry Approximation (ECA) kinetics can be used to represent enzymatically catalyzed reserve biomass mobilization that can then drive the kinetic and structural biomass synthesis. This revised DEB model better represents the tradeoff in ribosome allocation for structural growth and internal enzyme production, is structurally compatible with metabolic models of cell individuals, and includes the standard DEB model and the popular compromise model as special cases for representing population growth. We then applied the revised DEB model to interpret components of bacterial respiration, their dependence on substrate availability, and emergent microbial carbon use efficiency dynamics for an exponentially growing population. We found that the revised DEB model enables a better understanding of bacterial substrates use (carbon in our examples) than that can be derived from a few other models in the literature. In particular, the revised DEB model explains why carbon use efficiency may first increase, then plateau, and finally decrease with growth rate (and substrate uptake rate), as a function of proteomics. Additionally, the revised DEB model explains why the kinetic biomass compartment needs to be divided to reasonably incorporate proteomic control of microbial growth.

59 BASIC BIOLOGICAL SCIENCES↗

Catalytic bias in oxidation–reduction catalysis

Cataytic bias refers to the propensity of a reaction catalyst to effect a different rate acceleration in one direction versus the other in a chemical reaction under non-equilibrium conditions. In biocatalysis, the inherent bias of an enzyme is often advantagous to augment the innate thermodynamics of a reaction to promote efficiency and fidelity in the coordination of catabolic and anabolic pathways. In industrial chemical catalysis a directional cataltyic bias is a sought after property in facilitating the engineering of systems that couple catalysis with harvest and storage of for example fine chemicals or energy compounds. Interestingly, there is little information about catalytic bias in biocatalysis likely in large part due to difficulties in developing tractible assays sensitive enough to study detailed kinetics. For oxidation–reduction reactions, colorimetric redox indicators exist in a range of reduction potentials to provide a mechanism to study both directions of reactions in a fairly facile manner. The current short review attempts to define catalytic bias conceptually and to develop model systems for defining the parameters that control catalytic bias in enzyme catalyzed oxidation–reduction catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Active learning of polarizable nanoparticle phase diagrams for the guided design of triggerable self-assembling superlattices

Polarizable nanoparticles are of interest in materials science because of their rich and complex phase behavior that can be used to engineer nanostructured materials with long-range crystalline order. To understand and rationally navigate the design space of polarizable nanoparticles for self-assembling highly ordered superlattices, we developed a coarse-grained computational model to describe the nanoparticle-nanoparticle interactions in implicit solvent and employ the computationally efficient image method to model many-body polarization interactions. We conducted high-throughput virtual screening over a five-dimensional particle design space spanned by temperature, particle size, particle charge, particle dielectric, and solvent dielectric using enhanced sampling molecular dynamics calculations within an active learning framework to efficiently map out the regions of thermodynamic stability of the self-assembled aggregates. We validate our predictions in comparisons against small angle x-ray scattering measurements of gold nanoparticles surface functionalized with metal chalcogenide ligands. Lastly, we use our validated phase maps to computationally design switchable nanostructured materials capable of triggered assembly and disassembly as a function of temperature and solvent dielectric with potential applications as sensors, smart windows, optoelectronic devices, and in medical diagnostics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhancing the inherent catalytic activity and stability of TiO 2 supported Pt single-atoms at CeO x –TiO 2 interfaces

Single-atoms (SAs) with atomically coordinated reaction centers are considered the next generation of catalysts that can exhibit exceptional catalytic efficiency. However, the general concern about thermodynamic vulnerabilities of SAs questions their practical value. Moreover, whether the inherent catalytic nature of SAs is superior compared with that of larger nanoparticles is still under debate. Here, we address two controversies by a comparative study using two catalysts: Pt/TiO 2 and Pt/CeO x –TiO 2 . Based on a hierarchical study of density functional theory, time-resolved catalysis performance test, in situ infrared spectroscopy, and operando X-ray absorption spectroscopy, we could unveil the catalytic nature of Pt-SAs and their stability. By utilizing the heterogeneous interface formed between TiO 2 supporting particles and CeO x clusters formed on the surface of TiO 2 , we preferentially synthesized Pt-SAs pinned at the CeO x –TiO 2 interfaces on CeO x –TiO 2 hybrid-oxide supports. The strong electronic coupling between the Pt-SAs and the Ce ions at the CeO x –TiO 2 interfaces enhanced the catalytic activity toward CO oxidation of Pt-SAs and improved the long-term stability under CO oxidation conditions. The CO oxidation activity of Pt-SAs stabilized at CeO x –TiO 2 was improved by 13.5 times at 200 °C compared with the Pt-SAs on TiO 2 . The results present how to easily improve the activity and stability of Pt-SAs using a simple interface control method. Moreover, we demonstrate that the catalytic activity and the stability of Pt-SAs can be monitored through the chemical state of the interfaces. Finally, our study provides comprehensive understanding about the catalytic nature as well as a novel strategy toward applications of Pt-SAs, enabling sustainable use of Pt in heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Physics-informed transformation toward improving the machine-learned NLTE models of ICF simulations

The integration of machine-learning techniques into inertial confinement fusion (ICF) simulations has emerged as a powerful approach for enhancing computational efficiency. By replacing the costly nonlocal thermodynamic equilibrium (NLTE) model with machine-learning models, significant reductions in calculation time have been achieved. However, determining how to optimize machine-learning-based NLTE models in order to match ICF simulation dynamics remains challenging, underscoring the need for physically relevant error metrics and strategies to enhance model accuracy with respect to these metrics. Thus, we propose novel physics-informed transformations designed to emphasize energy transport, use these transformations to establish new error metrics, and demonstrate that they yield smaller errors within reduced principal-component spaces compared to conventional transformations. Published by the American Physical Society 2025

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Potential bioavailability of representative pyrogenic organic matter compounds in comparison to natural dissolved organic matter pools

Abstract. Pyrogenic organic matter (PyOM) from wildfires impacts river corridors globally and is widely regarded as resistant to biological degradation. Though recent work suggests PyOM may be more bioavailable than historically perceived, estimating bioavailability across its chemical spectrum remains elusive. To address this knowledge gap, we assessed potential bioavailability of representative PyOM compounds relative to ubiquitous dissolved organic matter (DOM) with a substrate-explicit model. The range of potential bioavailability of PyOM was greater than natural DOM; however, the predicted thermodynamics, metabolic rates, and carbon use efficiencies (CUEs) overlapped significantly between all OM pools. Compound type (e.g., natural versus PyOM) had approximately 6-fold less impact on predicted respiration rates than simulated carbon and oxygen limitations. Within PyOM, the metabolism of specific chemistries differed strongly between unlimited and oxygen-limited conditions – degradations of anhydrosugars, phenols, and polycyclic aromatic hydrocarbons (PAHs) were more favorable under oxygen limitation than other molecules. Notably, amino sugar-like, protein-like, and lignin-like PyOM had lower carbon use efficiencies relative to natural DOM of the same classes, indicating potential impacts in process-based model representations. Overall, our work illustrates how similar PyOM bioavailability may be to that of natural DOM in the river corridor, furthering our understanding of how PyOM may influence riverine biogeochemical cycling.

59 BASIC BIOLOGICAL SCIENCES↗

The UF6 Breeder - A solution to the problems of nuclear power

One of the major advantages of uranium hexafluoride reactors for power generation is the simplified fuel reprocessing scheme which the gaseous fuel makes possible. Critical experiments related to the development of the reactors for electric power generation are discussed along with UF6 breeder reactor studies. Previous energy conversion studies are reported, taking into account gas turbine power plants, thermionic conversion, and MHD conversion. Thermodynamic cycle analyses show that high efficiencies can be achieved using UF6 as the working fluid for Rankine or Brayton cycles without requiring excessive temperatures.

Williams, J. R.↗