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At least 685 records · Page 38

Gas-Phase Formation of 1,3,5,7-Cyclooctatetraene (C 8 H 8 ) through Ring Expansion via the Aromatic 1,3,5-Cyclooctatrien-7-yl Radical (C 8 H 9 • ) Transient

Gas-phase 1,3,5,7-cyclooctatetraene (C 8 H 8 ) and triplet aromatic 1,3,5,7-cyclooctatetraene (C 8 H 8 ) were formed for the first time through the bimolecular methylidyne radicals (CH) - 1,3,5-cycloheptatriene (C 7 H 8 ) reactions under single collision conditions on the doublet surface. The reaction involves methylidyne radical addition to the olefinic pi electron system of 1,3,5-cycloheptatriene followed by isomerization and ring expansion to aromatic 1,3,5-cyclooctatrien-7-yl radical (C 8 H 9 •). The chemically activated doublet radical intermediate undergoes unimolecular decomposition to 1,3,5,7-cyclooctatetraene. Substituted 1,3,5,7-cyclooctatetraene molecules can be prepared in the gas phase with hydrogen atom(s) in the 1,3,5-cycloheptatriene reactant being replaced by organic side groups. Furthermore, these findings are also of potential interest to organometallic chemists by expanding the synthesis of exotic transition metal complexes incorporating substituted 1,3,5,7-cyclooctatetraene dianion (C 8 H 8 2- ) ligands and to untangle the unimolecular decomposition of chemically activated and substituted 1,3,5-cyclooctatrien-7-yl radical eventually gaining a fundamental insight of their bonding chemistry, electronic structures, and stabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of defect properties in concentrated solid solutions using a Langmuir-like model

The alleged existence of sluggish diffusion in high-entropy alloys has drawn controversy. In high-entropy alloys and, in general, in all solids, transport properties are controlled by point defect concentration, which must be known before performing atomistic simulations to compute transport coefficients. In this work, we present a general Langmuir-like model for defect concentration in an arbitrarily complex solid solution and apply this model to generate expressions for concentrations of vacancies and small interstitial atoms. We then calculate the vacancy concentration as a function of temperature in the equiatomic CoNiCrFeMn and FeAl alloys with modified embedded-atom-method potentials for various chemical orderings, showing there is no clear correlation between vacancy thermodynamics and chemical ordering in the CoNiCrFeMn alloy, but clear systematic patterns for FeAl. We believe this is due to the high stability of disordered, random, and ordered intermetallic phases, respectively, in the CoNiCrFeMn and FeAl systems. Finally, this work provides future avenues to the prediction of thermal interstitials and vacancies in solid solutions, which is necessary for models of nonequilibrium behavior of solid solutions.

composition↗

Accurate Free Energies for Complex Condensed-Phase Reactions Using an Artificial Neural Network Corrected DFTB/MM Methodology

Semiempirical methods like density functional tight-binding (DFTB) allow extensive phase space sampling, making it possible to generate free energy surfaces of complex reactions in condensed-phase environments. Such a high efficiency often comes at the cost of reduced accuracy, which may be improved by developing a specific reaction parametrization (SRP) for the particular molecular system. Thiol–disulfide exchange is a nucleophilic substitution reaction that occurs in a large class of proteins. Its proper description requires a high-level ab initio method, while DFT-GAA and hybrid functionals were shown to be inadequate, and so is DFTB due to its DFT-GGA descent. We develop an SRP for thiol–disulfide exchange based on an artificial neural network (ANN) implementation in the DFTB+ software and compare its performance to that of a standard SRP approach applied to DFTB. Furthermore, as an application, we use both new DFTB-SRP as components of a QM/MM scheme to investigate thiol–disulfide exchange in two molecular complexes: a solvated model system and a blood protein. Demonstrating the strengths of the methodology, highly accurate free energy surfaces are generated at a low cost, as the augmentation of DFTB with an ANN only adds a small computational overhead.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elucidation of the Reaction Mechanisms of Autooxidative Processes in Complex Condensed-Phase Mixtures

In this report, we discuss the oxidative processes of gasoline surrogate fuels comprised of a neat olefin, such as 1-hexene. Oxidative reactions are thought to involve the peroxyl radical and peroxide chemistry with initial hydrogen abstraction by O 2 , followed by addition of O 2 or HOO· to the hydrocarbon to form unstable peroxy radicals and peroxides that result in a chain reaction. In the condensed phase environment (liquid), we also consider polymeric-forming chain reactions, such as hydrocarbon radical-radical carbon chain growth. We present our experimental results showing the reaction products resulting from 1-hexene oxidation, along with chemical kinetic modeling of the system showing product ratios as a function of time. Applicability of our observations to oxidation-promoted fouling in hydrocarbon fuels (i.e., formation of gum) and radical-promoted polymerizations will also be discussed.

10 SYNTHETIC FUELS↗

Understanding initial zeolite oligomerization steps with first principles calculations

Zeolites are porous aluminosilicate materials that find various applications in the chemical industry in separations, catalysis, ion exchange, and so forth. However, despite their widespread use, the reaction mechanisms occurring during zeolite growth are still unclear. In the study, we use density functional theory calculations to gain insights into the thermodynamics of oligomerization, which constitute the initial steps of zeolite growth. By taking into consideration solvent and temperature effects, our results demonstrate that the growth of aluminosilicate systems is significantly more exothermic than their pure silicate counterparts. Under pH neutral conditions, water prefers to dissociate on the early-growth-stage aluminosilicate complexes rather than desorb, thus generating potential Brønsted acid sites on the oligomers. Additionally, (alumino)silicate growth pathways are evaluated in the presence of Na + cation, as well as the Ca 2+ cation for the pure silicate pathway. The presence of cations increases the exothermicity of growth, with Ca 2+ exhibiting the most energetically favorable growth environment for the silicate systems. Importantly, we demonstrate through reaction extent analysis that the presence of cations modulates the speciation of the formed oligomers, with Na + favoring linear species in addition to the generally preferred cyclic ones. Overall, this work provides a fundamental understanding of the thermodynamics of complex reaction paths that occur during early stages of zeolite growth and suggests that the initial growth steps can have significant impact on the final zeolite structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of machine learning interatomic potentials in heterogeneous catalysis

Heterogeneous catalysts are crucial in modern societies as they promote sustainability by enabling lower-energy pathways for various chemical reactions. While Density Functional Theory (DFT) computations can provide critical insights into how heterogeneous catalysts operate at the atomic level, they are limited by computational costs and unfavorable scaling with system size. Recently, machine learning interatomic potentials (MLIPs) have emerged as a promising alternative to DFT, offering near-DFT accuracy at significantly reduced cost. Here, in this perspective, we discuss the application of MLIPs in heterogeneous catalyst modeling as a surrogate for DFT. We detail how MLIPs have been applied in thermal catalysis to probe active sites, enable studying complex metallic and nanoporous catalysts, and investigate the reconstruction of catalytic surfaces. We review the use of MLIPs in electrocatalysis and photocatalysis, emphasizing their capabilities in studying transition metal oxide surfaces and solid–liquid interfaces. We also discuss the current limitations of MLIPs, particularly their challenges with transferability and description of non-local interactions. Finally, we conclude by identifying promising and underexplored domains in which MLIPs can further advance our understanding of heterogeneous catalysts.

Catalytic surfaces↗

COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry

The computational power increases over the past decades have greatly enhanced the ability to simulate chemical reactions and understand ever more complex transformations. Tensor contractions are the fundamental computational building block of these simulations. These simulations have often been tied to one platform and restricted in generality by the interface provided to the user. The expanding prevalence of accelerators and researcher demands necessitate a more general approach which is not tied to specific hardware or requires contortion of algorithms to specific hardware platforms. In this paper we present COMET, a domain-specific programming language and compiler infrastructure for tensor contractions targeting heterogeneous accelerators. We present a system of progressive lowering through multiple layers of abstraction and optimization that achieves up to 1.98×speedup for 30 tensor contractions commonly used in computational chemistry and beyond.

Mutlu, Erdal↗

Electroanalytical characterization of Np( VI )/Np( V ) redox in a pentadentate ligand environment and stabilization of [Np V O 2 ] + by hydrogen bonding

The redox chemistry of the actinyl cations (AnO 2 n+ ) heavily influences their reactivity and speciation in solution, but the redox properties of the actinyls in non-aqueous media have received far less attention than they deserve. Here, the non-aqueous electrochemistry of a chemically reversible Np(VI)/Np(V) redox manifold is reported in both protic (CH 3 OH) and aprotic (CH 3 CN) organic media. Using a neutral Np(VI) complex supported by a chelating and strongly donating pentadentate ligand that was fully characterized in prior work, a clean Np(VI)/Np(V) redox couple was found to be accessible under ambient conditions. Coupled electrochemical and spectroscopic studies, as well as simulations of cyclic voltammetry data, confirm the 1e− nature of this couple and establish it to be chemically reversible and nearly electrochemically reversible as well. Bulk electrolysis of a solution of the neutral Np(VI) complex facilitated isolation of the corresponding anionic and monomeric Np(V) species. Data from X-ray diffraction analysis as well as optical and vibrational spectroscopies provide strong evidence in support of metal-centered reduction and the Np(V) oxidation state, findings that are in accord with the measured reduction potentials. Distinctive hydrogen bonding interactions between the terminal (yl) oxo groups and water molecules appear to stabilize the isolated Np(V) species in the solid state, providing insight into the features that afford the uncommon chemically reversible redox encountered in this system.

Mikeska, Emily R.↗

Mineral and fluid transformation of hydraulically fractured shale: case study of Caney Shale in Southern Oklahoma

This study explores the geochemical reactions that can cause permeability loss in hydraulically fractured reservoirs. The experiments involved the reaction of powdered-rock samples with produced brines in batch reactor system at temperature of 95 °C and atmospheric pressure for 7-days and 30-days respectively. Results show changes in mineralogy and chemistry of rock and fluid samples respectively, therefore confirming chemical reactions between the two during the experiments. The mineralogical changes of the rock included decreases of pyrite and feldspar content, whilst carbonate and illite content showed an initial stability and increase respectively before decreasing. Results from analyses of post-reaction fluids generally corroborate the results obtained from mineralogical analyses. Integrating the results obtained from both rocks and fluids reveal a complex trend of reactions between rock and fluid samples which is summarized as follows. Dissolution of pyrite by oxygenated fluid causes transient and localized acidity which triggers the dissolution of feldspar, carbonates, and other minerals susceptible to dissolution under acidic conditions. The dissolution of minerals releases high concentrations of ions, some of which subsequently precipitate secondary minerals. On the field scale, the formation of secondary minerals in the pores and flow paths of hydrocarbons can cause significant reduction in the permeability of the reservoir, which will culminate in rapid productivity decline. This study provides an understanding of the geochemical rock–fluid reactions that impact long term permeability of shale reservoirs.

58 GEOSCIENCES↗

Ab Initio Study of Vibronic and Magnetic 5f-to-5f and Dipole-Allowed 5f-to-6d and Charge-Transfer Transitions in [UX 6 ] n – (X = Cl, Br; n = 1, 2)

The absorption spectra of the octahedral [UX 6 ] n– (X = Cl, Br; n = 1, 2) complexes in the near-infrared (NIR) and UV–vis spectral regions were studied theoretically, using a relativistic restricted active space second-order perturbation theory (RASPT2) wavefunction framework, with the spin–orbit (SO) coupling treated by state interaction, in conjunction with Kohn–Sham density functional theory calculations for determining the vibrational normal modes. The electric-dipole-allowed ligand-to-metal charge-transfer (LMCT) and 5f-to-6d transitions, and the electric-dipole-forbidden 5f-to-5f ligand field (LF) transitions, are thereby obtained within the same theoretical framework. For the 5f-to-5f LF transitions, the observed absorption intensity is mostly due to vibronic coupling with low-energy electric-dipole-allowed transitions, but in some cases, the magnetic dipole intensity of the purely electronic transition has comparable intensity to the vibronic transitions. Here, experimental LF spectra of 5f 2 open-shell systems have been reported decades back, but ab initio calculations of their vibronic intensity have not yet been reported in the literature. Although the LF spectra for the 5f 2 systems can be assigned in detail, based on the calculations, the spectra are very complex and the underlying electronic states are strongly multiconfigurational. Therefore, the usefulness of the LF spectra beyond serving as a “fingerprint” of the LF and the metal oxidation state appears to be limited.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemistry and Interfacial Structure Promoting Quasi-van der Waals Epitaxial Growth of WS 2 Nanosheets on Sapphire for Prospective Application in Field-Effect Transistors

How do chemical and structural modifications to the supporting crystal surface affect the subsequent van der Waals (vdW) or quasi(Q)-vdW epitaxial growth of 2D nanocrystals? Developing an atomic-scale picture of such an interfacial system is crucial for understanding its impact on the physical and chemical properties of the supported 2D materials. The elucidation of the interfacial structure and chemistry needed to promote the Q-vdW epitaxial growth of 2D tungsten disulfide (WS 2 ) nanocrystals contributes to the growth mechanism understanding, thus pushing forward the integration of such atomically thin semiconductors toward real field-effect transistor applications. In addition to an atomic-force microscopy top view, we showcase a combination of X-ray techniques for a top-to-bottom investigation of the complexities of the buried interface structures. Furthermore, this approach uses X-ray photoelectron spectroscopy, X-ray standing wave excited X-ray fluorescence, and crystal truncation rod scattering to produce a highly resolved chemical-state-specific 3D atomic map for the extended interface structure of WS 2 /α-Al 2 O 3 (001). Employing these detailed analysis methods, along with density functional theory to further refine the picoscale structure, we demonstrate how two different types of interface engineering during the pregrowth stage lead to significant differences in the chemical and structural modifications to the terminal surface of c-face sapphire, which in turn leads to substantial differences in the submonolayer growth of supported WS 2 2D nanocrystals in terms of lateral domain sizes, epitaxial registry, vdW gaps, and stability.

36 MATERIALS SCIENCE↗

General Kinetic Model for pH Dependence of Proton-Coupled Electron Transfer: Application to an Electrochemical Water Oxidation System

The pH dependence of proton-coupled electron transfer (PCET) reactions, which are critical to many chemical and biological processes, is a powerful probe for elucidating their fundamental mechanisms. Herein, a general, multichannel kinetic model is introduced to describe the pH dependence of both homogeneous and electrochemical PCET reactions. According to this model, a weak pH dependence can arise from the competition among multiple sequential and concerted PCET channels involving different forms of the redox species, such as protonated and deprotonated forms, as well as different proton donors and acceptors. The contribution of each channel is influenced by the relative populations of the reactant species, which often depend strongly on pH, leading to complex pH dependence of PCET apparent rate constants. This model is used to explain the origins of the experimentally observed weak pH dependence of the electrochemical PCET apparent rate constant for a ruthenium-based water oxidation catalyst attached to a tin-doped In2O3 (ITO) surface. The weak pH dependence is found to arise from the intrinsic differences in the rate constants of participating channels and the dependence of their relative contributions on pH. This model predicts that the apparent maximum rate constant will become pH-independent at higher pH, which is confirmed by experimental measurements. Our analysis also suggests that the dominant channels are electron transfer at lower pH and sequential PCET via electron transfer followed by fast proton transfer at higher pH. Furthermore, this work highlights the importance of considering multiple competing channels simultaneously for PCET processes.

Catalysts↗

Reactions of Np(VI) and Pu(VI) with Phenanthroline Result in Bending the [NpVIO2]2+ Unit and a Reduced Pu(V) Species

Despite decades of actinyl chemistry, genuinely bent actinyl structures remain rare beyond uranium. We report the first crystallographic characterization of a bent neptunyl(VI) complex, NpO 2 Cl 2 (phen) 2, along with a linear plutonyl species that, unexpectedly, adopts the +V oxidation state. Coordination of two 1,10-phenanthroline ligands to NpO 2 2+ enforces pronounced bending of the O yl –Np–O yl unit to 162° through steric clashes with the axial phenathroline ligand, representing the sharpest angle reported for any neptunyl(VI) complex. In contrast, synthesis with PuO 2 2+ produces a reduced linear Pu(V) species, PuO 2 Cl(phen) 2, underscoring the redox lability and the reluctance of plutonium to distort. Raman and IR spectra yield the first experimental stretching and interaction force constants for plutonyl(V). Comparison with values for plutonyl(VI) and bent and linear uranyl(VI) and neptunyl(VI) compounds shows that reduction perturbs the actinyl bond more than bending within one oxidation state. Electrochemical and spectroscopic studies clarify phenanthroline binding to Pu(VI) and the system’s reactivity. Quantum chemical calculations indicate that bending is energetically favored in the U–Np–Pu series, but the stabilization energy decreases as the actinide atomic number increases. NBO and QTAIM analyses reveal systematic trends: increasing 5f occupancy and decreasing An–O yl bond covalency from U to Pu. These results demonstrate that ligand-induced bending in neptunyl(VI) species is not only electronically feasible but also synthetically achievable, though plutonyl(VI) is constrained by redox reactivity. This work expands the frontier of nonlinear actinyl chemistry and illuminates how structure, oxidation state, and electronic configuration interrelate across the actinyl series.

actinides↗

Synchrotron fluorescence imaging of individual mouse beta-cells reveals changes in zinc, calcium, and iron in a model of low-grade inflammation

Pancreatic beta-cells synthesize and secrete insulin maintaining an organism's energy homeostasis. In humans, beta-cell dysfunction and death contribute to the pathogenesis of type 2 diabetes (T2D). Although the causes of beta-cell dysfunction are complex, obesity-induced low-grade systemic inflammation plays a role. For example, obese individuals exhibiting increased levels of proinflammatory cytokines IL-6 and IL-1beta have a higher risk of beta-cell dysfunction and T2D. Interestingly, obesity-induced inflammation changes the expression of several cellular metal regulating genes, prompting this study to examine changes in the beta-cell metallome after exposure to proinflammatory-cytokines. Here, primary mouse beta-cells were exposed to a combination of IL-6 and IL-1beta for 48 hours, were chemically fixed and imaged by synchrotron X-ray fluorescent microscopy. Quantitative analysis showed a surprising 2.4-fold decrease in the mean total cellular content of zinc from 158 ± 57.7 femtograms (fg) to 65.7 ± 29.7 fg; calcium decreased from 216 ± 67.4 to 154.3 ± 68.7 fg (control vs. cytokines, respectively). The mean total cellular iron content slightly increased from 30.4 ± 12.2 to 47.2 ± 36.4 fg after cytokine treatment; a sub-population of cells (38%) exhibited larger increases of iron density. Changes in the subcellular distributions of zinc and calcium were observed after cytokine exposure. Beta-cells contained numerous iron puncta that accumulated still more iron after exposure to cytokines. These findings provide evidence that exposure to low levels of cytokines is sufficient to cause changes in the total cellular content and/or subcellular distribution of several metals known to be critical for normal beta-cell function.

59 BASIC BIOLOGICAL SCIENCES↗

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗

Adsorbate chemical environment-based machine learning framework for heterogeneous catalysis

Abstract Heterogeneous catalytic reactions are influenced by a subtle interplay of atomic-scale factors, ranging from the catalysts’ local morphology to the presence of high adsorbate coverages. Describing such phenomena via computational models requires generation and analysis of a large space of atomic configurations. To address this challenge, we present Adsorbate Chemical Environment-based Graph Convolution Neural Network (ACE-GCN), a screening workflow that accounts for atomistic configurations comprising diverse adsorbates, binding locations, coordination environments, and substrate morphologies. Using this workflow, we develop catalyst surface models for two illustrative systems: (i) NO adsorbed on a Pt 3 Sn(111) alloy surface, of interest for nitrate electroreduction processes, where high adsorbate coverages combined with low symmetry of the alloy substrate produce a large configurational space, and (ii) OH* adsorbed on a stepped Pt(221) facet, of relevance to the Oxygen Reduction Reaction, where configurational complexity results from the presence of irregular crystal surfaces, high adsorbate coverages, and directionally-dependent adsorbate-adsorbate interactions. In both cases, the ACE-GCN model, trained on a fraction (~10%) of the total DFT-relaxed configurations, successfully describes trends in the relative stabilities of unrelaxed atomic configurations sampled from a large configurational space. This approach is expected to accelerate development of rigorous descriptions of catalyst surfaces under in-situ conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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↗