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At least 685 records · Page 38

State-by-state energy-water-land-health impacts of the US net-zero emissions goal

As decisionmakers at various scales begin to design strategies to implement the US net-zero goal, a holistic understanding of its broader economic and sustainability implications at subnational scales is important to shape public support and facilitate implementation. Here, we use an integrated assessment model to explore four different pathways toward the US net-zero goal and investigate their energy-water-land-health implications at the state level. In this study, we show that achieving the net-zero goal implies significant capital turnover (170–200 billion USD/year capital investment and 16–29 billion USD/year stranded assets in the power sector), reduced water withdrawal (120–210 km 3 /year), avoided air pollution damages (220–300 billion USD/year), and expanded forests (300–500 thousand km 2 ). However, the economic and sustainability implications of achieving the net-zero goal at the state-level may not be correlated to a state's contribution to national emission reductions. Our study lays the foundations for a deeper understanding of the broader implications of the US net-zero goal to facilitate cost-effective and environmentally sustainable transitions toward that goal.

54 ENVIRONMENTAL SCIENCES↗

Bayesian calibration and uncertainty quantification of a rate-dependent cohesive zone model for polymer interfaces

In this work we present a rate-dependent cohesive zone model for the fracture of polymeric interfaces and performs a Bayesian calibration, an uncertainty quantification, and a sensitivity analysis for the model. The proposed cohesive zone model accounts for both reversible elastic and irreversible rate-dependent separation sliding deformation at the interface. The viscous dissipation due to the irreversible opening at the interface is modeled using elastic-viscoplastic kinematics that incorporates the effects of strain rate. Inverse calibration of parameters for such complex models through trial and error is challenging due to the large number of parameters of the model. Moreover, the calibrated parameter values are often non-unique and uncertain when the available experimental data is limited. To tackle this challenge, we employ a Bayesian calibration approach to identify parameters from experimental data, the resulting parameters significantly enhance the accuracy of the model. To quantify the uncertainty associated with the inverse parameter estimation, a modular Bayesian approach is employed to calibrate the unknown model parameters, accounting for the parameter uncertainty of the cohesive zone model. The advantages of the Bayesian calibration over a deterministic parameter fit are demonstrated. Further, to quantify the model uncertainties, such as incorrect assumptions or missing physics, a discrepancy function is introduced, which significantly improves the model’s prediction. Finally, the total uncertainty of the model is quantified in a predictive setting. A sensitivity analysis is performed to assess how changes in the input variables of the model affect the peak load, facilitating the identification of a concise set of highly influential parameters. The present approach can be used for calibration and uncertainty quantification for other complex computational mechanics models. It should also facilitate the designing of interface materials under uncertainty.

42 ENGINEERING↗

Regulated lithium ionic flux through well-aligned channels for lithium dendrite inhibition in solid-state batteries

The utilization of solid electrolyte (SE) to suppress lithium (Li) dendrites is promising but still far from satisfactory due to the inhomogeneous Li plating/stripping. In this paper, we demonstrated a novel strategy to inhibit Li dendrites via regulating Li-ion flux in SE by using vertically aligned channels. The ion-insulating walls facilitated uniform distribution of Li-ion flux through the channels, leading to a homogeneous Li deposition, thus alleviating Li dendrite formation. As a result, symmetric cells with this SE exhibited excellent long-term stability (1000 h) against Li metal. In addition, Li4Ti5O12 (LTO)/Li cell with the developed SE achieved good battery performance over 100 cycles. The mechanism for dendrite suppression was further investigated by phase-field simulation. This work provides a novel strategy by manipulating uniform Li-ion flux to fabricate SE to inhibit Li dendrites and facilitates the development of high-performance rechargeable Li batteries.

25 ENERGY STORAGE↗

JTAG-based PLC memory acquisition framework for industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLC) are the embedded devices that directly control and monitor critical industrial infrastructure processes such as nuclear plants and power grid stations. Cyberattacks often target PLCs to sabotage a physical process. A memory forensic analysis of a suspect PLC can answer questions about an attack, including compromised firmware and manipulation of PLC control logic code and I/O devices. Given physical access to a PLC, collecting forensic information from the PLC memory at the hardware-level is risky and challenging. It may cause the PLC to crash or hang since PLCs have proprietary, legacy hardware with heterogeneous architecture. This paper addresses this research problem and proposes a novel JTAG (Joint Test Action Group)-based framework, Kyros, for reliable PLC memory acquisition. Kyros systematically creates a JTAG profile of a PLC through hardware assessment, JTAG pins identification, memory map creation, and optimizing acquisition parameters. It also facilitates the community of interest (such as ICS owners, operators, and vendors) to develop the JTAG profiles of PLCs. Further, we present a case study of Kyros implementation over Allen-Bradley 1756-A10/B to help understand the framework's application on a real-world PLC used in industry settings. The sample PLC memory dumps are shared with the research community to facilitate further research.

Rais, Muhammad Haris↗

Catalytic monoterpenes conversion over Pd and zeolite to sustainable aviation fuel

Waste terpenes from wood drying are typically processed using a Regenerative Thermal Oxidizer (RTO) and converted to CO2 which is then released to the atmosphere. A novel alternative to this approach is to capture these terpenes using Fluidized Bed Concentrator (FBC) technology developed by CaptisAire which provides a useful waste carbon feedstock for subsequent upgrading. We have developed a catalytic approach where these waste terpenes (comprised of pinenes, limonene, and camphene), are converted to aromatic, and cycloalkane hydrocarbons suitable for use as a Sustainable Aviation Fuel (SAF) blendstock without the need for additional hydrogen. This provides a renewable source for aviation fuel aromatics and increases the potential blend content of renewably sourced alkanes from Hydroprocessed Esters and Fatty Acids (HEFA) and Alcohol to Jet (ATJ) processes. Terpenes were converted in a batch reactor at 260 °C and 120 psi N2 using a combination of Pd/C and H-BEA zeolite. Experimental results infer the role of the zeolite Brønsted acid to facilitate isomerization of pinenes and camphene to limonene, which then undergoes subsequent dehydro-aromatization to p-cymene using Pd/C. Hydrogen release from the dehydro-aromatization process, enables inert conversion of monoterpenes to cycloalkanes without additional hydrogen. Monoterpenes conversion to C10 aromatics (60%) and C10 cycloalkanes (40%) in an inert environment, provides a viable route for SAF blendstock sourced directly from captured waste terpenes. Transition to commercial off-the-shelf catalysts, facilitates scale-up of the terpene conversion process and improves commercial viability. We subsequently created hydrocarbon blends using HEFA or ATJ and converted terpenes, providing a 100% SAF blend with potential to replace traditional Jet-A.

Lawal, Ajibola [ORNL] (ORCID:0000000187266570)↗

Quasi-optical beam tracing module development for millimeter-wave high-wavenumber collective scattering on the NSTX-U and EAST tokamaks

A Python3-based beam tracing code utilizing Quasi-Optics has been developed to track both incident and receiving beams in high-k collective millimeter wave scattering systems within magnetic fusion plasmas. In contrast to existing ray tracing codes that solely consider refraction, this beam tracing code incorporates diffraction phenomena, providing a more comprehensive calculation. Here, this enhanced capability allows for a more accurate calculation of the scattering volume and spatial resolution in high-k collective scattering systems, crucial for evaluating system performance and facilitating data analysis. Unlike Geometrical Optics, Quasi-Optics employs the complex eikonal method, representing a Gaussian beam as a collection of coupled rays to accurately preserve diffraction characteristics. The developed code is intended for application in NSTX-Upgrade and EAST high-k beam tracing analyses, targeting frequencies of 693 GHz and 270 GHz, respectively. The high-k system's primary objective is the observation of electron-scale instabilities. Employing a symplectic integrator, the code ensures numerical accuracy, assessed through the conservation of the Hamiltonian. With its precision and efficiency, the code facilitates rapid inter-shot analyses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Shadow of the Future: Developing Trust and Software within the Exascale Computing Project

Collaboration and team science are emerging areas of interest in software production. Historically, multi-institutional research collaborations are difficult to initiate and maintain, negatively impacting communication, negotiation, and dialogue between industry, government, and academic researchers. The Exascale Computing Project (ECP), a massive, multi-team, high-stakes initiative, facilitated broader research collaboration under a shared funding structure and extended timeline to support scientific discovery. Here, we conducted interviews with ECP teams, representing a variety of domain specialties, research institutions, and programming backgrounds. Using thematic analysis, we assessed how ECP’s structure created an environment of increased trust among projects and how software shared between teams facilitated sustained collaboration. We found that the expectation of future collaboration, i.e., the shadow of the future, greatly enhanced trust among teams and the quality of scientific software produced. Based on our findings within ECP projects, we connect to the existing literature on trust in software engineering and share recommendations for sustainable multi-institutional collaboration and shared best software practices.

Exascale computing project↗

Effects of particle size and AQDS on the flow of electron equivalents between magnetite and aqueous Fe2+

Magnetite can occur naturally in nano- to micro-size regimes and widely coexists with aqueous Fe2+ (Fe2+ (aq)) in natural environments. However, the effects of magnetite particle size on its interaction with Fe2+ (aq) in anoxic subsurface environments, particularly with redox-active organics, remain unclear. In this study, the interactions of Fe2+ (aq) with magnetite particles of 12 nm versus 109 nm (Mag-12 vs. Mag-109), with/without anthraquinone- 2,6-disulfonate (AQDS), were studied based on equilibrium Fe2+ (aq) concentrations, kinetics of AQDS reduction, and structural versus surface-localized Fe(II)/Fe(III) ratios (xstru and xsurf) of magnetite. In the absence of AQDS, Mag-12 tends to release Fe2+ (aq) at pH 7 but sorb Fe2+ (aq) at pH 8, while Fe2+ (aq) uptake by Mag-109 is observed at both pH 7 and 8. The amounts of Fe2+ (aq) adsorbed per unit area of Mag-109 is higher than that of Mag-12, due to the higher electron-accepting capacity of Mag-109 that facilitates interfacial electron transfer (IET) from surfaceassociated Fe(II) to structural Fe(III). The increases of xstru and xsurf in Mag-109 after reaction with Fe2+ (aq) at pH 7 and 8 suggest Fe2+ (aq) incorporation or electron injection into the structure of Mag-109. The presence of AQDS promotes Fe2+ (aq) uptake by both Mag-12 and Mag-109. However, AQDS reduction by Fe2+-amended Mag-12 results in the decrease of xstru and inhibits Fe2+ (aq) incorporation or electron injection into the structure. On the contrary, the increase of xstru observed in Fe2+-amended Mag-109 after reaction with AQDS suggests that Fe2+ (aq) incorporation or electron injection into the surface structure and then consequently into the interiors is more favorable for magnetite with larger particle sizes. The different flow directions of electron equivalents across the solid-solution interfaces can be attributed to the relatively higher electron-accepting capacity, i.e. redox potential, of Mag-109 than Mag-12; larger particle sizes facilitate IET from surface-associated Fe(II) to structural Fe(III) and promotes further Fe2+ (aq) uptake, culminating in the pronounced changes of redox potentials in magnetitebearing solutions. The results demonstrate that particle size and redox-active organics are important factors to affect reductive activity of Fe2+-magnetite system in redox-oscillating environments.

Peng, Huan↗

Investigation of methane mass transfer and sorption in Marcellus shale under variable net-stress

Natural gas in shale exists as free and adsorbed gas, subject to prevailing pore pressures and stress conditions. Accordingly, to accurately estimate/predict the shale gas recovery potential, a central requirement is to represent gas transport and sorption behavior under varying stress conditions. The objective of this work is to facilitate the interpretation of laboratory-scale experiments, at relevant conditions, in an attempt to bridge the gap in scales between laboratory- and field-scale observations. We have conducted a series of high-pressure experiments on a full-diameter core sample from the Marcellus shale. These include gas loading (pressure-decay) and depletion (production) experiments with pure methane (CH 4 ) at variable stress conditions to characterize transport and sorption behavior under reservoir-relevant conditions. Here we have formulated and applied a novel integral model for mass transfer and storage in multi-porosity shale systems that allows us to effectively investigate transport and sorption phenomena: We delineate gas transport by interpreting helium (He) pressure-decay experiments and demonstrate how to use the information gained to calculate the relevant transport coefficients of CH 4 and other gases. A separate measurement of the CH 4 sorption isotherm on a smaller sample (a shale cube) was interpreted and combined with the transport description to predict the production behavior of CH 4 from the experiments with the full-diameter core. Our experiments demonstrate that the representation of sorption hysteresis is crucial for predicting and guiding shale gas production: At the end of both gas production experiments, approximately 20% of the initial gas in place remained in the core. Without accounting for sorption hysteresis, our modeling demonstrates that the CH 4 production could be overestimated by 10%. We demonstrate that our integral, triple-porosity model provides an effective approach for the interpretation and prediction of gas transport and sorption behavior during loading and production experiments on shale cores under variable net-stress conditions. In summary, our work combines measurements and modeling of mass transfer and sorption in shales at different scales to validate a characterization approach that facilitates an improved understanding of shale gas production. Furthermore, the triple-porosity model utilized in our work defines a potential pathway for the translation of laboratory-scale experimentation to larger-scale applications.

58 GEOSCIENCES↗

Self-reported health impacts of do-it-yourself air cleaner use in a smoke-impacted community

Smoke exposure from wildfires or residential wood burning for heat is a public health problem for many communities. Do-It-Yourself (DIY) portable air cleaners (PACs) are promoted as affordable alternatives to commercial PACs, but evidence of their effect on health outcomes is limited. Pilot test an evaluation of the effect of DIY PAC usage on self-reported symptoms, and investigate barriers and facilitators of PAC use, among members of a tribal community that routinely experiences elevated concentrations of fine particulate matter (PM 2.5 ) from smoke. We conducted studies in Fall 2021 (“wildfire study”; N = 10) and Winter 2022 (“wood stove study”; N = 17). Each study included four sequential one-to-two-week phases: 1) initial, 2) DIY PAC usage ≥8 h/day, 3) commercial PAC usage ≥8 h/day, and 4) air sensor with visual display and optional PAC use. We continuously monitored PAC usage and indoor/outdoor PM 2.5 concentrations in homes. Concluding each phase, we conducted phone surveys about participants’ symptoms, perceptions, and behaviors. We analyzed symptoms associated with PAC usage and conducted an analysis of indoor PM 2.5 concentrations as a mediating pathway using mixed effects multivariate linear regression. We categorized perceptions related to PACs into barriers and facilitators of use. No association was observed between PAC usage and symptoms, and the mediation analysis did not indicate that small observed trends were attributable to changes in indoor PM 2.5 concentrations. Small sample sizes hindered the ability to draw conclusions regarding the presence or absence of causal associations. DIY PAC usage was low; loud operating noise was a barrier to use. This research is novel in studying health effects of DIY PACs during wildfire and wood smoke exposures. Such research is needed to inform public health guidance. Recommendations for future studies on PAC use during smoke exposure include building flexibility of intervention timing into the study design.

54 ENVIRONMENTAL SCIENCES↗

Incentivizing Cooperative Merging Control: Insights from Multi-Agent Deep Reinforcement Learning

Cooperative driving automation enables connected and automated vehicles (CAVs) to devise cooperative merging control, introducing great potentials to alleviate traffic congestion, reduce energy consumption, and enhance safety for highway on-ramp operations. Although numerous CAV cooperative merging algorithms have been developed to improve energy and traffic performance, the agreement-seeking among CAV users and their local benefits have been understudied. This can lead to rejections of cooperative merging plans and jeopardizing CAV performance, as a cooperation may entail certain CAVs to sacrifice their local benefits to achieve a system optimum. To address this issue, the study first leverages multi-agent deep reinforcement learning (MADRL) factoring both local reward and regional reward to demonstrate the discrepancies between CAV users’ local benefits and system optimum. Next, the existence of a correlated equilibrium is proved to characterize the convergence of MADRL training. This further facilitates the incorporation of incentives (computed based on reward discrepancies) to compensate for CAV users’ local benefits and facilitate system-optimal agreements in cooperative merging operations.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗

Bridging microscale to macroscale mechanical property measurements of FeCrAl alloys by crystal plasticity modeling

FeCrAl alloys are candidates for accident tolerant fuel cladding of light water reactors. In this work, a microstructure- and temperature-dependent crystal plasticity model is employed to bridge microscale to macroscale mechanical property measurements of FeCrAl alloys. With the visco-plastic self-consistent (VPSC) polycrystal plasticity framework, a mechanism-based single crystal plasticity (MSCP) model adopts the Arrhenius type rate equation to describe the dependence of the critical resolved shear stress for dislocation slips on their temperature-dependent intrinsic frictional resistance and the microstructure-dependent irradiation hardening. The intrinsic frictional resistance associated with {110}<111> and {112}<111> slip systems were measured by in-situ micromechanical testing on unirradiated/irradiated samples at 25-500 °C. The irradiation hardening is estimated by the Bacon-Kocks-Scattergood (BKS) model with density and size of radiation-induced defects measured from microstructural characterization. Several features associated with thermo-mechanical behavior of unirradiated/irradiated polycrystalline FeCrAl alloys are captured. High density of deformation-induced dislocations and radiation-induced defects results in obvious hardening at room temperature, which is weakened at high temperature, and facilitates damage evolution during deformation. Moreover, both high temperature and radiation-induced defects, which facilitate dislocation multiplication, trigger large hardening rate. Finally, the proposed method together with application of accelerator-based ion irradiation technique is a surrogate approach to simulate neutron damage, improving the efficiency associated with evaluation of mechanical properties of FeCrAl alloys exposed to temperature, stress and radiation conditions.

36 MATERIALS SCIENCE↗

Probing the surface chemistry for reverse water gas shift reaction on Pt(1 1 1) using ambient pressure X-ray photoelectron spectroscopy

Using ambient pressure XPS (APXPS), we explored carbon dioxide (CO 2 ) adsorption and CO 2 hydrogenation on Pt(1 1 1) single crystal surface to observe the activation of CO 2 and the subsequent reaction mechanism. In pure CO 2 , we observed CO adsorbates and adsorbed oxygen on Pt(1 1 1) derived from CO 2 dissociation at room temperature. The introduction of H 2 (at a pressure ratio of 1:1 (H 2 :CO 2 )) increased the production of CO across all temperatures by facilitating the removal of surface oxygen. As a consequence, the surface could expose sites that could then be utilized for producing CO. Under these conditions, the reverse water–gas shift (RWGS) reaction was observed starting at 300 °C. At higher H 2 partial pressure (10:1 (H 2 :CO 2 )), the RWGS reaction initiated at a lower temperature of 200 °C and continued to enhance the conversion of CO 2 with increasing temperatures. Our results revealed that CO 2 was activated on a clean Pt(1 1 1) surface through the dissociation mechanism to form adsorbed CO and O at room temperature and at elevated temperatures. Introducing H 2 facilitated the RWGS as adsorbed oxygen was consumed continuously to form H 2 O, and adsorbed CO desorbed from the surface at elevated temperatures. This work clearly provides direct experimental evidence for the surface chemistry of CO 2 dissociation and demonstrates how hydrogen impacts the RWGS reaction on a platinum surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synergistic Ru Co atomic pair with enhanced activity toward levulinic acid hydrogenation

Development of efficient metal-based catalysts is of great importance for levulinic acid (LA) hydrogenation to γ-valerolactone (GVL). The widely employed Ru-based catalysts are advantageous for H 2 dissociation, however, the steric hindrance for large Ru particles hampers their coordination to C=O moiety in LA, and thereby decreasing the activity. Herein, we report a Ru 1 Co 1 -N-C double single-atom catalyst (DSAC) with synergistic Ru and Co atomic pairs for LA hydrogenation into GVL. The Ru and Co doped zeolitic imidazole frameworks (RuCo-doped ZIF-8) precursor was rationally designed ((Ru+Co)/(Zn+Ru+Co) = 2 at.%), where the Zn node spatially isolates Ru and Co species, expanding the adjacent Ru-Co distance and facilitating the formation of the Ru-Co atomic pair upon pyrolysis, with each atom coordinated with three nitrogen atoms (N 3 -Ru 1 Co 1 -N 3 ). The Ru 1 Co 1 -N-C catalyst exhibits outstanding catalytic activity, with a turnover frequency (TOF) of 1980 h –1 , surpassing previously reported Ru-based catalysts. Experimental investigation and density functional theory (DFT) calculations reveal that the electron-rich Ru induced by less electronegative Co facilitates H 2 dissociation, while atomic Ru in dual-atomic pairs promotes C=O activation, Ru and Co atomic pairs synergistically enhancing LA conversion to GVL. In conclusion, this research will shed light on the precise control of active sites at atomic scale, and also provides a new concept for designing high-performance Ru-based catalysts towards LA hydrogenation to GVL.

Double single-atom catalysts↗

Class-based separations of mixed solid–liquid systems with condensable solvent washing and extraction: The dilemma of pizza box recycling

As primary feedstocks deplete across the world, raw material extraction becomes increasingly expensive. Awareness of the environmental impact of primary extraction has motivated the development of energy- and reagent-efficient methods for material reuse. This work confronts an emblematic challenge of modern recycling: the soiled pizza box. While the fibers constituting corrugated cardboard are generally recyclable, pizza contaminants such as sauces and oils complicate their reuse, resulting in municipal prohibitions on the recycling of used pizza boxes in cardboard recycling streams and a representative of 275 kg/year per US household of food waste that is directed to landfill. This challenge is common to many materials, and engineering strategies must be developed to tackle complex/mixed feedstocks. To address the mixed composition of the pizza box (and similar materials), an environmentally benign, non-toxic organic solvent is applied to remove and fractionate components from mixed materials. The solvent employed in this process, dimethyl ether (DME), is a condensable hygroscopic gas, which facilitates its removal and recovery for reuse. Further, the results of this study indicate that 1) DME is capable of solubilizing and extracting components from soiled cardboard and other materials, (resulting in cardboard drier than new/unused cardboard) facilitating its recycling, and 2) the DME-soluble components of the system phase separate into aqueous and fatty acid/oil fractions (potentially ~27.5 kg/year per US household). Condensable solvent-driven washing and extraction enable the efficient separation of multiple intermediate product streams, suggesting a pathway to enable technology development necessary for achieving clean production in a circular economy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

58 GEOSCIENCES↗

Characterization of ferredoxins involved in electron transfer pathways for nitrogen fixation implicates differences in electronic structure in tuning 2[4Fe 4S] Fd activity

Ferredoxins (Fds) are small proteins which shuttle electrons to pathways like biological nitrogen fixation. Physical properties tune the reactivity of Fds with different pathways, but knowledge on how these properties can be manipulated to engineer new electron transfer pathways is lacking. Recently, we showed that an evolved strain of Rhodopseudomonas palustris uses a new electron transfer pathway for nitrogen fixation. This pathway involves a variant of the primary Fd of nitrogen fixation in R. palustris, Fer1, in which threonine at position 11 is substituted for isoleucine (Fer1 T11I ). To understand why this substitution in Fer1 enables more efficient electron transfer, we used in vivo and in vitro methods to characterize Fer1 and Fer1 T11I . Electrochemical characterization revealed both Fer1 and Fer1 T11I have similar redox transitions (–480 mV and – 550 mV), indicating the reduction potential was unaffected despite the proximity of T11 to an iron-sulfur (Fe—S) cluster of Fer1. Additionally, disruption of hydrogen bonding around an Fe—S cluster in Fer1 by substituting threonine with alanine (T11A) or valine (T11V) did not increase nitrogenase activity, indicating that disruption of hydrogen bonding does not explain the difference in activity observed for Fer1 T11I . Electron paramagnetic resonance spectroscopy studies revealed key differences in the electronic structure of Fer1 and Fer1 T11I , which indicate changes to the high spin states and/or spin-spin coupling between the Fe—S clusters of Fer1. Finally, our data implicates these electronic structure differences in facilitating electron flow and sets a foundation for further investigations to understand the connection between these properties and intermolecular electron transfer.

59 BASIC BIOLOGICAL SCIENCES↗