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At least 667 records · Page 37

Understanding Dynamics and Thermodynamics of ENSO and Its Complexity Simulated by E3SM and Other Climate Models

Despite the seeming success of most state-of-the-art climate models in simulating the El Niño-Southern Oscillation (ENSO), there is strong evidence that models achieve realistic levels of ENSO activity do so often for wrong reasons. This is owing to an often occurred near cancelation of large errors in terms of contributions to ENSO growth rate from coupled dynamic and thermodynamic feedback processes. Climate models remain deficient in simulating the observed ENSO’s spatial and temporal complexity that involves interplays of coupled dynamic and thermodynamic feedbacks, interactions across multiple scales, nonlinear processes in the tropical atmosphere and ocean system, biases in mean sate and physical processes, and influences external to equatorial Pacific coupled ENSO dynamics. Our proposed research aims at advancing predictive and process-level understandings of ENSO simulated in E3SM and other climate models under current and future climate conditions with two main objectives: (i) better understanding the aforementioned broad range interactive processes and sources that control fundamental properties of ENSO in E3SM and CIMP6 outputs as well as in observational (reanalysis) data sets, using a hierarchical of coupled dynamical frameworks consisting of theoretical analysis, intermediate complexity modeling, and coupled dynamic diagnostics; (ii) to use this understanding to explore pathways towards improving E3SM’s capability of simulating ENSO and its complexity. More specifically, we will focus on four main thrusts of research: (1) ENSO’s dynamic and thermodynamic feedbacks; (2) the across-scale interactions of ENSO with annual cycle and MJO/WWB/TIW (Madden Julian Oscillation/Westerly Wind Burst/Tropical Instability Wave) activity; (3) key nonlinear processes of ENSO involving atmospheric convective thresholds, nonlinear ocean dynamic heating, and thermocline outcropping; and (4) the impacts of climate mean-state biases/changes and perturbed physical processes on simulated ENSO and its complexity.

54 ENVIRONMENTAL SCIENCES↗

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Needs Assessment Framework for Storage Complexes Contributed to EDX (Work Product 2.1.c)

On September 30, 2021, a Needs Assessment Framework for Storage Complexes was completed for the SECARB-USA region by the Southern States Energy Board (SSEB) and The University of Texas at Austin Bureau of Economic Geology (UT-BEG). The Needs Assessment Framework for Storage Complexes documented a region-wide assessment to identify data needed to advance storage projects at sites of relevance to industrial, academic, and government stakeholders. The region-wide assessment addresses the needs of CO2 source, storage, and utilization stakeholders, finance and insurance institutions, state and local government agencies, local stakeholders at prospective storage complexes, environmental non-governmental organizations (NGOs), and others as identified by the Partners. This assessment was tested against various potential storage sites and modified to include site-specific issues, such as surface or pore space rights. The framework was provided to stakeholders for review and then used in other tasks, such as the ML initiative (Subtask 3.4) and storage complex readiness evaluation (Subtask 4.2). In accordance with the SOPO, this assessment satisfied completion of Work Product 2.1.b. The OSTI ID is 3015803, and the DOI link is https://doi.org/10.2172/3015803. On February 28, 2022, SSEB uploaded Work Product 2.1.b to NETL’s Energy Data eXchange (EDX). As such, Work Product 2.1.c is completed as documented below.

42 ENGINEERING↗

A general quantum algorithm for open quantum dynamics demonstrated with the Fenna-Matthews-Olson complex

Using quantum algorithms to simulate complex physical processes and correlations in quantum matter has been a major direction of quantum computing research, towards the promise of a quantum advantage over classical approaches. In this work we develop a generalized quantum algorithm to simulate any dynamical process represented by either the operator sum representation or the Lindblad master equation. We then demonstrate the quantum algorithm by simulating the dynamics of the Fenna-Matthews-Olson (FMO) complex on the IBM QASM quantum simulator. This work represents a first demonstration of a quantum algorithm for open quantum dynamics with a moderately sophisticated dynamical process involving a realistic biological structure. We discuss the complexity of the quantum algorithm relative to the classical method for the same purpose, presenting a decisive query complexity advantage of the quantum approach based on the unique property of quantum measurement.

97 MATHEMATICS AND COMPUTING↗

Hydrated Metal and Metal-Nitrate Complexes in Water: Full Lanthanide(III) Series plus Miscellaneous Metal Ions

This is a dataset of hydrated metal complexes and metal–nitrate hydrated complexes intended for public use, reproducibility, and downstream structural analysis. A key feature is coverage across the full lanthanide(III) series (La–Lu), enabling systematic comparisons of coordination motifs and bonding trends across the entire lanthanide sequence. In addition to the lanthanides, the dataset also includes other metal ions such as UO2(VI), Fe(II), and Fe(III). The dataset provides optimized geometries for hydrated and nitrate-containing hydrated complexes, together with representative ab initio molecular dynamics (AIMD) trajectories saved in standard XYZ formats. The accompanying NWChem input decks enable reproduction of the reported calculations and provide a starting point for extending the simulations to related coordination environments. Computationally, DFT calculations employ the B3LYP functional with DFT-D3BJ dispersion corrections and a COSMO continuum solvent model (dielectric constant 78.4) to represent solvation beyond the explicitly treated first hydration shell. AIMD simulations are performed with the NWChem qmd module at 298 K, integrating nuclear motion with the velocity-Verlet algorithm and controlling temperature using a Nosé–Hoover thermostat. Trajectories are approximately 4.8 ps in length and are used primarily to assess short-time stability of candidate coordination motifs, including (for lanthanides) differences between 8- versus 9-water coordination and comparisons between nitrate-bound and nitrate-free hydrated complexes.

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗

Influences of Alkali Metal Cation Interactions on N2 Coordination to Iron(I) Beta-Diketiminate Complexes in Electrolyte Solutions

N2 functionalization reactions often use stable, isolable N2-bound complexes and low temperatures or highly activated reagents. However, little work has focused on systems where N2 binds weakly, and the N2 binding equilibrium can be modulated. Here, we describe analysis of surprising trends in alkali metal cation solvation on the formation of an anionic iron(I) beta-diketiminate complex and the subsequent N2 binding equilibrium. Variable temperature UV-vis spectroscopy shows that increased ionic strength in the coordinating solvent tetrahydrofuran promotes N2 coordination. Additionally, less solvated alkali metal cations in noncoordinating 2-methyltetrahydrofuran (MeTHF) stabilize N2 coordination, likely through the formation of contact ion pairs in solution that have enhanced N2 binding. Ionic strength has little effect on the energetics of N2 coordination to these proposed contact ion pairs in MeTHF. When the electrochemical analysis is done at –78 °C, there is an irreversible reduction of iron(II) and an anodically shifted oxidation, which is attributed to the formation of the spectroscopically observed N2 complex. Finally, bulk electrolysis is used to verify the electrochemical formation of the N2-bound anionic iron(I) complex. These studies demonstrate a new strategy for promoting N2 coordination by changing solution properties, which is relevant to homogeneous electrochemical N2 reduction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanisms for the Generation of Complex Fracture Networks: Observations From Slant Core, Analog Models, and Outcrop

We use observations of hydraulic fractures in core, outcrop attributes of natural hydraulic fractures, and analogue models, to address how hydraulic fracture networks evolve. A slant core from the Wolfcamp Formation—an unconventional shale hydrocarbon reservoir in the Permian Basin of West Texas—collected within 18 m and 30 m of two hydraulically stimulated horizontal wells, provided an opportunity to examine hydraulic fractures directly. In approximately 183 m of core, 309 calcite-sealed natural opening-mode fractures and 375 hydraulic fractures were identified. Many hydraulic fractures in the core show complex morphology, including twist-hackle segmentation, diversion, and bifurcation; these structures most commonly develop at lithological bed boundaries and mechanical heterogeneities such as natural fractures and concretions. An outcrop of bed-parallel pavements in the Cretaceous Boquillas Formation in West Texas contains opening-mode fractures that likely formed by natural hydraulic fracturing. Fracture traces provide evidence of twist-hackle segmentation, and are typically associated with bed boundaries and preexisting bed-parallel stylolites. A laboratory study of hydraulic fracturing of 33 synthetic blocks of gypsum and hydrostone revealed fracture steps, diversions, twist hackles, and multiple overlapping fractures together with information on fracture growth directions. These complexities in the fracture network were dominantly nucleated at inclusions used to simulate pre-existing fractures, and as a result of mechanical heterogeneity introduced by the wellbore and perforations. Collectively, our results show that complex fracture networks are produced in hydraulic fracturing of self-sourced reservoir strata. Mechanical stratigraphic boundaries and other heterogeneities are likely to enhance fracture network complexity through the processes of segmentation, diversion, and bifurcation. These processes create multiple fracture strands, resulting in an increased number of hydraulic fractures over those initiated, thereby increasing total fracture surface area. Our study provides insight into hydraulic fracture network propagation, and has applications for evaluation, completion, production, and fracture modeling of unconventional reservoirs.

54 ENVIRONMENTAL SCIENCES↗

Structural complexity and primary production resistance are coupled in a temperate forest

The capacity of forests to resist structural change and retain material legacies–the biotic and abiotic resources that persist through disturbance–is crucial to sustaining ecosystem function after disturbance. However, the role of forest structure as both a material legacy and feature supporting carbon (C) cycling stability following disturbance has not been widely investigated. We used a large-scale disturbance manipulation to ask whether legacies of lidar-derived canopy structures drive 3-year primary production responses to disturbance. As part of the Forest Resilience Threshold Experiment (FoRTE) in northern Michigan, USA we simulated phloem-disrupting disturbances producing a range of severities and affecting canopy trees of different sizes. We quantified the legacies of forest structure using two approaches: one measuring the change in structure and primary production from pre-to post-disturbance and the second estimating resistance as log transformed ratios of control and treatment values. We found that total aboveground wood net primary production (ANPP w ) was similar across disturbance severities as legacy trees rapidly increased rates of primary production. Experiment-wide, the disturbance had limited effects on change in mean structural complexity values; however, high variance underscored large differences in the magnitude and direction of complexity's response at the plot-scale. Plot-scale structural complexity, but not vegetation area index (VAI), resistance strongly predicted ANPP w resistance while temporal VAI and structural complexity changes did not. We conclude that the presence of material legacies in the form of forest structure may affect primary production stability following disturbance and that how legacies are quantified may affect the interpretation of disturbance response.

lidar—remote sensing↗

The effect of monitoring complexity on stakeholder acceptance of CO2 geological storage projects in the US gulf coast region

Environmental monitoring at geologic CO 2 storage sites is required by regulations for the purposes of environmental protection and emissions accounting in the case of leakage to surface. However, another very important goal of environmental monitoring is to assure stakeholders that the project is monitored for safety and effectiveness. With current efforts to optimize monitoring for cost-effectiveness, the question remains: will optimization of monitoring approaches degrade stakeholder assurance, or do heavily-instrumented sites communicate higher risk to a stakeholder? We report the results of a stakeholder survey in Gulf Coast states of the US where carbon capture and storage (CCS) is developing quickly. We rely on a 2 by 2 factorial experiment in which we manipulate message complexity (complex v. simple) and social norm (support from scientists v. support from community members). Subjects were randomly assigned to one of four conditions: 1) complex message with scientist support; 2) complex message with community member support; 3) simple message with scientist support; or 4) simple message with community member support. In addition to the experimental stimuli, subjects were also asked about their need for cognition, attitudes toward science and scientists, attitudes about climate change and support for carbon capture and storage (CCS). Our sample is drawn from residents in states bordering the western Gulf of Mexico (Texas, Louisiana, Florida) where CO 2 geologic storage is being planned both onshore and offshore. The results offer important implications for public outreach efforts to key stakeholders.

54 ENVIRONMENTAL SCIENCES↗

Petroleum pollution changes microbial diversity and network complexity of soil profile in an oil refinery

Petroleum pollution resulting from spills and leakages in oil refinery areas has been a significant environmental concern for decades. Despite this, the effects of petroleum pollutants on soil microbial communities and their potential for pollutant biodegradation still required further investigation. In this study, we collected 75 soil samples from 0 to 5 m depths of 15 soil profiles in an abandoned refinery to analyze the effect of petroleum pollution on soil microbial diversity, community structure, and network co-occurrence patterns. Our results suggested soil microbial a-diversity decreased under high C10–C40 levels, coupled with significant changes in the community structure of soil profiles. However, soil microbial network complexity increased with petroleum pollution levels, suggesting more complex microbial potential interactions. A module specific for methane and methyl oxidation was also found under high C10–C40 levels of the soil profile, indicating stronger methanotrophic and methylotrophic metabolic activities at the heavily polluted soil profile. The increased network complexity observed may be due to more metabolic pathways and processes, as well as increased microbial interactions during these processes. These findings highlight the importance of considering both microbial diversity and network complexity in assessing the effects of petroleum pollution on soil ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling the Influenza A NP-vRNA-Polymerase Complex in Atomic Detail

Seasonal flu is an acute respiratory disease that exacts a massive toll on human populations, healthcare systems and economies. The disease is caused by an enveloped Influenza virus containing eight ribonucleoprotein (RNP) complexes. Each RNP incorporates multiple copies of nucleoprotein (NP), a fragment of the viral genome (vRNA), and a viral RNA-dependent RNA polymerase (POL), and is responsible for packaging the viral genome and performing critical functions including replication and transcription. A complete model of an Influenza RNP in atomic detail can elucidate the structural basis for viral genome functions, and identify potential targets for viral therapeutics. In this work we construct a model of a complete Influenza A RNP complex in atomic detail using multiple sources of structural and sequence information and a series of homology-modeling techniques, including a motif-matching fragment assembly method. Our final model provides a rationale for experimentally-observed changes to viral polymerase activity in numerous mutational assays. Further, our model reveals specific interactions between the three primary structural components of the RNP, including potential targets for blocking POL-binding to the NP-vRNA complex. The methods developed in this work open the possibility of elucidating other functionally-relevant atomic-scale interactions in additional RNP structures and other biomolecular complexes.

59 BASIC BIOLOGICAL SCIENCES↗

Towards Reconstruction of Complex Flow Fields Using Unit Flows

Many complex turbulent flows in nature and engineering can be qualitatively regarded as being constituted of multiple simpler unit flows. The objective of this work is to characterize the coherent structures in such complex flows as a combination of constituent unitary flow structures for the purpose of reduced-order representation. While turbulence is clearly a non-linear phenomenon, we aim to establish the degree to which the optimally weighted superposition of unitary flow structures can represent the complex flow structures. The rationale for investigating such superposition stems from the fact that the large-scale coherent structures are generated by underlying flow instabilities that may be reasonably described using linear analysis. Clearly, the degree of validity of superposition will depend on the flow under consideration. In this work, we take the first step toward establishing a procedure for investigating superposition. Experimental data of single and triple tandem jets in crossflow are used to demonstrate the procedure. A composite triple tandem jet flow field is generated from optimal superposition of single jet data and compared against ‘true’ triple jet data. Direct comparisons between the true and composite fields are made for spatial, temporal, and kinetic energy content. The large-scale features (obtained from proper orthogonal decomposition or POD) of true and composite tandem jet wakes exhibit nearly 70% agreement in terms of modal eigenvector correlation. Corresponding eigenvalues reveal that the kinetic energy of the flow is also emulated with only a slight overprediction. Temporal frequency features are also examined in an effort to completely characterize POD modes. The proposed method serves as a foundation for more rigorous and robust dimensional reduction in complex flows based on unit flow modes.

Kristo, Paul J.↗

Exploring the Limits of Biological Complexity Amenable to Studies by Incoherent Neutron Spectroscopy

The wavelengths of neutrons available at neutron scattering facilities are comparable with intra- and inter-molecular distances, while their energies are comparable with molecular vibrational energies, making such neutrons highly suitable for studies of molecular-level dynamics. The unmistakable trend in neutron spectroscopy has been towards measurements of systems of greater complexity. Several decades of studies of dynamics using neutron scattering have witnessed a progression from measurements of solids to liquids to protein complexes and biomembranes, which may exhibit properties characteristic of both solids and liquids. Over the last two decades, the frontier of complexity amenable to neutron spectroscopy studies has reached the level of cells. Considering this a baseline for neutron spectroscopy of systems of the utmost biological complexity, we briefly review what has been learned to date from neutron scattering studies at the cellular level and then discuss in more detail the recent strides into neutron spectroscopy of tissues and whole multicellular organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

Chemistry↗

Earth Abundant Oxidation Catalysts for Removal of Contaminants of Emerging Concern from Wastewater: Homogeneous Catalytic Screening of Monomeric Complexes

Twenty novel Mn, Fe, and Cu complexes of ethylene cross-bridged tetraazamacrocycles with potentially copolymerizable allyl and benzyl pendant arms were synthesized and characterized. Multiple X-ray crystal structures demonstrate the cis-folded pseudo-octahedral geometry forced by the rigidifying ethylene cross-bridge and show that two cis coordination cites are available for interaction with substrate and oxidant. The Cu complexes were used to determine kinetic stability under harsh acidic and high-temperature conditions, which revealed that the cyclam-based ligands provide superior stabilization with half-lives of many minutes or even hours in 5 M HCl at 50–90 °C. Cyclic voltammetry studies of the Fe and Mn complexes reveal reversible redox processes indicating stabilization of Fe 2+ /Fe 3+ and Mn 2+ /Mn 3+ /Mn 4+ oxidation states, indicating the likelihood of catalytic oxidation for these complexes. Finally, dye-bleaching experiments with methylene blue, methyl orange, and rhodamine B demonstrate efficient catalytic decolorization and allow selection of the most successful monomeric catalysts for copolymerization to produce future heterogeneous water purification materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Complex plant-derived organic aerosol as ice-nucleating particles – more than the sums of their parts?

Quantifying the impact of complex organic particles on the formation of ice crystals in clouds remains challenging, mostly due to the vast number of different sources ranging from sea spray to agricultural areas. In particular, there are many open questions regarding the ice nucleation properties of organic particles released from terrestrial sources such as decaying plant material. In this work, we present results from laboratory studies investigating the immersion freezing properties of individual organic compounds commonly found in plant tissue and complex organic aerosol particles from vegetated environments, without specifically investigating the contribution from biological particles, which may contribute to the overall ice nucleation efficiency observed at high temperatures. To characterize the ice nucleation properties of plant-related aerosol samples for temperatures between 242 and 267 K, we used the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) cloud chamber and the Ice Nucleation SpEctrometer of the Karlsruhe Institute of Technology (INSEKT), which is a droplet freezing assay. Individual plant components (polysaccharides, lignin, soy and rice protein) were mostly less ice active, or similarly ice active, compared to microcrystalline cellulose, which has been suggested by recent studies to be a proxy for quantifying the primary cloud ice formation caused by particles originating from vegetation. In contrast, samples from ambient sources with a complex organic matter composition (agricultural soils and leaf litter) were either similarly ice active or up to 2 orders of magnitude more ice active than cellulose. Of all individual organic plant components, only carnauba wax (i.e., lipids) showed a similarly high ice nucleation activity as that of the samples from vegetated environments over a temperature range between 245 and 252 K. Hence, based on our experimental results, we suggest considering cellulose as being representative for the average ice nucleation activity of plant-derived particles, whereas lignin and plant proteins tend to provide a lower limit. In contrast, complex biogenic particles may exhibit ice nucleation activities which are up to 2 orders of magnitude higher than observed for cellulose, making ambient plant-derived particles a potentially important contributor to the population of ice-nucleating particles in the troposphere, even though major uncertainties regarding their transport to cloud altitude remain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response

Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1°C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2°C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3°C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23°C(±0.12°C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

54 ENVIRONMENTAL SCIENCES↗

Metal-Complex Inks for Lower Cost and Improved Passivation for Silicon Photovoltaic Metallization

This contribution introduces the silicon PV community to screen-printable metal-complex inks that potentially will reduce Ag usage in Si PV metallization to one-quarter and costs to one-third that of traditional particle-based pastes while also improving passivation. Metal-complex inks are formulated using a Tollen’s reaction to produce inks with a high percentage of diamminesilver (I) cations (22 wt %) in a solution of acetate and formate anions. When printed and dried, labile ammonia ligands evaporate, leaving behind silver cations which, when reduced by formate anions and acetic acid, plate out silver and silver acetate. When annealed to just 300 °C a dense metallic silver film forms with excellent conductivity, and adhesion to silicon. When compared to traditional particle-based screen-printing pastes, the metal-complex inks are much denser, have higher conductivity, use less Ag, and are a fraction of the cost. Importantly, the inks anneal from 90 – 450 °C allowing for improved passivation schemes compared with fired SiNx. This contribution highlights first experiments on the improved passivation of metallized poly-Si/SiO2 passivated contacts using metal-complex Ag inks.

Young, David L. (ORCID:0000000340970493)↗

The anaerobic fungus Caecomyces churrovis produces H 2 via a non-bifurcating NADH-dependent enzyme complex

ABSTRACT Hydrogenosomes are mitochondria-derived organelles that produce ATP and H 2 to support energy metabolism in anaerobic eukaryotes. H 2 production allows reoxidation of reduced cofactors generated during fermentative metabolism; however, the metabolic mechanisms for H 2 production in anaerobic eukaryotes remains incompletely understood. In particular, it remains unclear whether anaerobic fungi (AF) hydrogenosomes use a ferredoxin-dependent pathway or a distinct mechanism to regenerate NAD(P) + and link electron transfer to H 2 formation. Here, by combining genomic search, proteomic analysis, and enzymology, we reveal the molecular mechanism for H 2 production in the AF strain Caecomyces churrovis . Our enzyme assays on the organelle fraction of C. churrovis revealed the activity of H 2 :NAD + oxidoreductase but not pyruvate:ferredoxin oxidoreductase, which is usually linked to H 2 formation. We identified genes encoding [FeFe] hydrogenase (Hyd) and NADH dehydrogenase subunits E and F (NuoE, NuoF) in C. churrovis , and confirmed their expression in the isolated hydrogenosomal fractions by proteomic analysis. Combining the individually purified enzymes, we found Hyd and NuoEF proteins formed H 2 directly from NADH independently of ferredoxin, functioning as a non-bifurcating NADH-dependent enzyme rather than an electron-bifurcating enzyme. We identified homologs of hydrogenosomal NuoE, NuoF, and Hyd in many other AF, indicating this pathway is commonly shared among the AF. This work demonstrates the existence of a non-bifurcating NADH-dependent enzyme complex in eukaryotes. Moreover, this complex could potentially be exploited as a target for controlling AF H 2 production and altering fungal metabolism. IMPORTANCE H 2 production is a prominent feature of anaerobic energy metabolism, yet our understanding of eukaryotic mechanisms remains limited. Anaerobic fungi (AF) are key decomposers of lignocellulose and contribute to hydrogen flux in anaerobic environments. Although it has been more than 40 years since the H 2 production from AF was first reported, the molecular mechanism for hydrogenosomal H 2 production and redox balance remains unclear. We demonstrate that AF produce H 2 from NADH utilizing a non-bifurcating NADH-dependent enzyme complex rather than an electron-bifurcating, ferredoxin-dependent variant. We show that this enzyme complex is conserved across multiple AF lineages and thus demonstrate the occurrence of a non-bifurcating NADH-dependent enzyme in eukaryotes. This discovery expands our understanding of eukaryotic hydrogenosomal metabolism, reveals a previously unknown strategy for redox balancing, and highlights potential targets for manipulating H 2 production. These insights have broad implications for microbial energy metabolism, anaerobic ecosystems, and bioengineering of H 2 -producing systems.

Zhang, Bo [Department of Chemical Engineering, Uni↗