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Hole-scavenging in photo-driven N 2 reduction catalyzed by a CdS-nitrogenase MoFe protein biohybrid system

The light-driven reduction of dinitrogen (N 2 ) to ammonia (NH 3 ) catalyzed by a cadmium sulfide (CdS) nanocrystal-nitrogenase MoFe protein biohybrid is dependent on a range of different factors, including an appropriate hole-scavenging sacrificial electron donor (SED). Here, the impact of different SEDs on the overall rate of N 2 reduction catalyzed by a CdS quantum dot (QD)-MoFe protein system was determined. The selection of SED was guided by several goals: (i) molecules with standard reduction potentials sufficient to reduce the oxidized CdS QD, (ii) molecules that do not absorb the excitation wavelength of the CdS QD, and (iii) molecules that could be readily reduced by sustainable processes. Earlier studies utilized buffer molecules or ascorbic acid as the SED. The effectiveness of ascorbic acid as SED was compared to dithionite (DT), triethanolamine (TEOA), and hydroquinone (HQ) across a range of concentrations in supporting N 2 reduction to NH 3 in a CdS QD-MoFe protein photocatalytic system. It was found that TEOA supported N 2 reduction rates comparable to those observed for dithionite and ascorbic acid. HQ was found to support significantly higher rates of N 2 reduction compared to the other SEDs at a concentration of 50 mM. A comparison of the rates of N 2 reduction by the biohybrid complex to the standard reduction potential (E o ) of the SEDs reveals that E o is not the only factor impacting the efficiency of hole-scavenging. These findings reveal the importance of the SED properties for improving the efficiency of hole-scavenging in the light-driven N 2 reduction reaction catalyzed by a CdS QD–MoFe protein hybrid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sub-100 mA/cm 2 CO 2 -to-CO Reduction Current Densities in Hierarchical Porous Gold Electrocatalysts Made by Direct Ink Writing and Dealloying

While most research efforts on CO 2 -to-CO reduction electrocatalysts focus on boosting their selectivity, the reduction rate, directly proportional to the reduction current density, is another critical parameter to be considered in practical applications. This is because mass transport associated with the diffusion of reactant/product species becomes a major concern at a high reduction rate. Nanostructured Au is a promising CO 2 -to-CO reduction electrocatalyst for its very high selectivity. However, the CO 2 -to-CO reduction current density commonly achieved in conventional nanostructured Au electrocatalysts is relatively low (in the range of 1–10 mA/cm 2 ) for practical applications. In this work, we combine direct ink writing-based additive manufacturing and dealloying to design a robust hierarchical porous Au electrocatalyst to improve the mass transport and achieve high CO 2 -to-CO reduction current densities on the order of 64.9 mA/cm 2 with CO partial current density of 33.8 mA/cm 2 at 0.55 V overpotential using an H-cell configuration. Although the current density achieved in our robust hierarchical porous Au electrocatalyst is one order of magnitude higher than the one achieved in conventional nanostructured electrocatalysts, we found that the selectivity of our system is relatively low, namely 52%, which suggests that mass transport remains a critical issue despite the hierarchical porous architecture. We further show that the bulk dimension of our electrocatalyst is a critical parameter governing the interplay between selectivity and reduction rate. In conclusion, the insights gained in this work shed new light on the design of electrocatalysts toward scale-up CO 2 reduction and beyond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photoelectrochemical Nitrate and Nitrite Reduction Using Cu 2 O Photocathodes

Nitrate in wastewater streams causes eutrophication, and nitrate removal is of great importance for environmental protection. Electrochemical nitrate reduction has the advantage of directly converting nitrate to benign or useful chemicals, but it typically requires a considerable overpotential. Here, in this study, photoelectrochemical nitrate reduction is investigated using a Cu 2 O photocathode, where photoexcited electrons in the conduction band inherently have an overpotential of >1.6 V for nitrate reduction. The Cu 2 O photocathode is found to reduce nitrate to nitrite selectively with a high Faradaic efficiency (>85%). More importantly, as the surface of Cu 2 O is particularly catalytic for nitrate reduction, nitrate reduction on Cu 2 O kinetically suppresses photocorrosion of Cu 2 O without the need for additional catalyst or protection layers. In addition to nitrate reduction, nitrite reduction on Cu 2 O is examined to compare the effects of nitrate and nitrite reduction kinetics on the photocurrent generation and photocorrosion of Cu 2 O photocathodes.

25 ENERGY STORAGE↗

Electron–electrophile coupled dinitrogen reduction in a cerium– meta -tetraphenolate system: a computational study

The use of lanthanide complexes for catalytic dinitrogen reduction is a new development in homogeneous catalysis. Density functional theory calculations on our recently reported cerium phenolate catalyst [K 2 Ce 2 (sol) 4 (mTP) 2 ] (mTP = {(OC 6 H 2 - 2- t Bu-4-Me) 2 CH} 2 - 1,3-C 6 H 4 ; sol = OMe 2 here; THF in the experiment) have been undertaken to elucidate the reduction, activation and silylation steps at the bound dinitrogen molecule, in the presence of the reductant, potassium metal (K 0 ) and the electrophile Me 3 SiCl (TMSCl). Out of the total of six electron reductions required to cleave the N 2 , the first two-electron reduction step was found to be highly disfavoured unless potassium cations (K + ) are included, upon which the step is rendered strongly exergonic; N–Si bond formation at the two-electron stage is predicted to be unfavourable. The three-electron-reduced N 2 -adduct is found to be at the reductive activation limit in the absence of added electrophiles, which can form N-element bonds and lower the overall charge. Added electron density beyond three-electron reduction no longer localises on N 2 , preventing formal N 2 4− formation. A pathway in which both K 0 and Me 3 SiCl work in concert was modelled, and six sequential reduction–silylation steps were calculated, showing how the N–N bond is cleaved after the third reduction, eventually releasing two equivalents of N(SiMe 3 ) 3 , and regenerating the starting complex with the highest barrier of any step being 22 kcal mol −1 . We establish alkali metal coordination and coupled electron–electrophile transfer as key factors in the design of rare-earth-mediated dinitrogen functionalisation.

Ahmad, Shahbaz [Univ. of Manchester (United Kingdo↗

HPDR: High-Performance Portable Scientific Data Reduction Framework

The rapid growth in scientific data generation is outpacing advancements in computing systems necessary for efficient storage, transfer, and analysis, particularly in the context of exascale computing. With the deployment of first-generation exascale computing systems and next-generation experimental facilities, this gap is widening and necessitates effective data reduction techniques to manage enormous data volumes. Over the past decade, various data reduction methods, including lossless compression, error-controlled lossy compression, and data refactoring, have been developed to accelerate I/O in scientific workflows. Despite significant reductions in data volume, these methods introduce considerable computational overhead, which can become the new bottleneck in data processing. To mitigate this, GPU-accelerated data reduction algorithms have been introduced. However, challenges remain in their integration into exascale workflows, including limited portability across different GPU architectures, substantial memory transfer overhead, and reduced scalability on dense multi-GPU systems. To address these challenges, we propose HPDR, a high-performance and portable data reduction framework. HPDR is designed to enable the execution of state-of-the-art reduction algorithms across diverse processor architectures while reducing memory transfer overhead to 2.3 % of the original, resulting in up to 3.5× faster throughput compared to existing solutions. It also achieves up to 96% of the theoretical speedup in multi-GPU settings. In addition, evaluations on accelerating I/O operations at scale up to 1,024 nodes of the Frontier supercomputer demonstrate that HPDR can achieve up to 103 TB/s reduction throughput, providing up to 4× acceleration in parallel I/O performance compared to existing data reduction routines. This work highlights the potential of HPDR to significantly enhance data reduction efficiency in exascale computing environments.

Chen, Jieyang [University of Oregon]↗

Evaluating the Performance of Integer Sum Reduction in SYCL on GPUs

SYCL is a promising programming model for heterogeneous computing—allowing a single-source code to target devices from multiple vendors. One significant task performed on these accelerators is a primitive operation for integer sum reduction. This paper presents several SYCL implementations of integer sum reduction—using atomic functions, shared local memory, vectorized memory accesses and parameterized workload sizes—to compare the performance and maturity of SYCL against open-source vendor-specific implementations of the same reduction. For a sufficiently large number of integers, tuning the parameters of our SYCL implementations achieves 1.4X speedup over the open-source implementations on an Intel UHD630 integrated GPU. The SYCL reduction is 3% faster than the templated reduction in Thrust, and 0.3% faster than the device reduction in CUB on an Nvidia P100 GPU. The SYCL reduction is 1.9% faster than the templated reduction in Thrust, and 0.4% faster than the device reduction in CUB on an Nvidia V100 GPU.

Jin, Zheming↗

Where Have All of the Electrons Gone? Understanding the Role of Alternative Electron Flow and O 2 Reduction in Balancing Cellular Redox (Final Technical Report)

An informed understanding of the fundamentals of light-driven electron transfer reactions in photoautotrophic organisms is necessary to enable improved photosynthetic efficiencies for the production of renewable fuels and novel biomaterials. To obtain high photosynthetic yields, light energy must be efficiently coupled to the fixation of CO 2 . Sub-optimal environmental conditions and metabolic routing (caused by blocks in biosynthetic routes) can severely impact the conversion of light energy to biomass and lead to reactive oxygen production, which in turn can cause cellular damage and productivity losses. Hence, plants, algae, and photosynthetic bacteria have evolved a network of alternative outlets to sustain the flow of photosynthetically derived-electrons. Our research was focused on the nature and integration of these outlets. The data obtained in this project will inform efforts to rationally engineer crop plants and algae to improve photosynthetic yields by enhancing electron transfer reactions to CO 2 reduction and targeted biomass accumulation. A major project research thrust was focused on identifying and quantifying the flow of photosynthetic reductant through electron transfer circuits that result in the light-dependent reduction of O 2 . New energy management strategies were identified that are used when normal carbon assimilation pathways are compromised due to nutrient deprivation, and/or by a reduction in starch synthesis/carbon storage, all conditions resulting in highly reduced intracellular redox pools. The green alga Chlamydomonas reinhardtii, and likely many other algae, have multiple O 2 -reducing pathways that play critical roles in maintaining cellular metabolic balance and scavenging electrons that could potentially cause cellular damage, which in some instances leads to reduced photosynthetic yields but increased fitness. We explored the activities of three essential outlets associated with Chlamydomonas reinhardtii photosynthetic electron transport: (1) reduction of O 2 to H 2 O through Flavodiiron proteins (FLVs) and (2) Plastid Terminal Oxidases (PTOX), and (3) the synthesis of starch. Real-time measurements of O 2 exchange demonstrated that FLVs immediately engage during dark to light transitions, allowing electron transport when the CBBC is not fully activated. Under these conditions, we quantified, for the first time, maximal FLV activity and its overall capacity to direct photosynthetic electrons towards O 2 reduction. However, when starch synthesis is compromised, a greater proportion of electrons is directed toward O 2 reduction through the FLVs, while PTOX, which is sensitive to the PQ pool redox state, is activated. This suggests, that starch synthesis has an important role in priming/regulating CBBC and electron transport. We also identified a biological ‘switch’ in the green alga Chlamydomonas reinhardtii that reversibly restricts photosynthetic electron transport (PET) at the cytochrome b 6 f complex when reductant and ATP generated by PET are in excess of the capacity of carbon metabolism to utilize these products; we specifically show a restriction at this switch when sta6 mutant cells, which cannot synthesize starch, are limited for nitrogen (growth inhibition) and subjected to a dark to light transition. This restriction causes diminished electron flow to PSI, which prevents PSI photodamage, and the plastid alternative oxidase (PTOX) becomes fully activated, serving as an electron valve that dissipates excitation energy absorbed by PSII, thereby lessening PSII photoinhibition. Furthermore, illumination of the cells following the dark acclimation gradually diminishes the restriction at the switch. Future engineering of these switches may allow more effective electron transfer to lipid (biofuel) pathways and diminish the number of electrons “wasted” in the reduction of O 2 to water. Lastly, we explored metabolic routing of electrons during algal fermentation and discovered multiple novel pathways that are activated when the preferred anoxic routes are blocked. These provide valuable products (e.g. lactate, glycerol) that can be used in broad portfolio of biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

Design of Efficient Molecular Electrocatalysts for Water and Carbon Dioxide Reduction Using Predictive Models of Thermodynamic Properties

Objectives: 1) To design and synthesize water soluble transition metal complexes that function as electrocatalysts for the reduction of water to hydrogen or carbon dioxide to formate 2) To experimentally measure thermochemical properties, such as hydride donor ability, and use these quantities to optimize catalyst performance in solutions of varying pH 3) To incorporate results from detailed mechanistic and kinetic studies to direct improvements in catalyst design 4) To use thermochemical data from objective 2 to generate predictive models for the properties of new complexes to apply to the development of catalysts for other reductive reactions, with an emphasis on carbon dioxide reduction to methanol Description: Wide-spread implementation of renewable but intermittent energy sources, such as solar, requires the development of efficient methods for energy storage. The high energy density of chemical bonds makes chemical fuels an ideal solution for energy storage. Hydrogen and reduced carbon compounds have been proposed as ideal candidates for chemical fuels. However, the generation of chemical fuels from electricity requires competent electrocatalysts. The proposed research focuses on developing electrocatalysts for the reduction of water to hydrogen, and carbon dioxide to formate. Both products can be used directly as an energy carrier in fuel cells, or as a reductant for more saturated chemical fuels. Hydrogen is the most common fuel used in current commercial fuel cells. Additionally, there is interest in formic acid as a liquid carrier for hydrogen because of its increased storage density and ease of dehydrogenation. Formate is also an intermediate in the sequential reduction of CO 2 to methanol, another potential chemical fuel with high energy storage density. Despite the utility of formate as a chemical fuel or precursor, there are very few examples of electrocatalysts for its production from CO 2 , and even fewer demonstrate high product selectivity. In heterogeneous catalysis, the Sabatier principle is used to generate volcano curves that describe optimal thermochemical properties for key intermediates that result in peak catalytic activity. In most cases, such as hydrogen production and oxidation, the most favorable metals (Pt, Re, Rh, and Ir) are rare and expensive. Molecular inorganic complexes provide an opportunity to use electronic and steric ligand effects to tune the critical thermodynamic parameters of abundant metals to values comparable to key surface intermediates on precious metals. This principle will be applied to the design of aqueous homogeneous catalysts for the reduction of H 2 O and CO 2 optimized to function at specific pH ranges. The critical intermediate in both of these reactions is a metal hydride. The strength of this bond, or hydricity (ΔGH - ) dictates the overall thermodynamics of the reduction of H + to H 2 and the sequential reduction of C1 substrates, such as CO 2 , CO, and H 2 CO (the latter to CH 3 OH). ΔGH - will be systematically measured for a series of first row metal complexes to form predictive models for metal and ligand electronic effects. Benefits and Outcomes: This approach addresses thermodynamic requirements essential for energy-efficient catalyst design and transition state barrier considerations for faster catalysis. The advancements made from this research will include the discovery of efficient, stable, and fast catalysts for hydrogen and formate generation from electricity. The ability to store energy efficiently is critical to the widespread use of renewable energy schemes. This provides a viable solution to produce high energy density fuels for stationary and mobile energy applications. The fundamental research conducted is also directly applicable to the design of catalysts for the generation of further reduced products such as methanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Manufacturing Cost Analysis for PEM Electrolyzers and Perspectives for Future Cost Reduction

Electrolyzer capital costs strongly influence the total levelized cost of hydrogen production and have implications for hydrogen deployment. Current electrolyzer costs are high, and large cost reductions may be needed to achieve competitive hydrogen costs and targets. Understanding pathways for cost reduction via R&D and deployment is a critical research area for informed energy planning and enabling hydrogen use. This work presents bottom-up cost estimates of polymer electrolyte membrane (PEM) electrolyzer systems tied to design specifications and discusses perspectives for cost reduction opportunities based on ongoing research. We use a detailed manufacturing and process model for a 1 MW PEM electrolyzer stack and balance of plant (BOP) for rigorous cost estimation. This allows for robust estimates of component and manufacturing costs and examination of key cost contributors. Stack costs are dominated by material costs such as iridium and platinum catalysts, especially at high manufacturing rates; power electronics and hydrogen purification equipment are the largest contributors to BOP cost. At higher manufacturing rates, better equipment utilization could reduce stack costs significantly, and we estimate that experience and bulk purchasing will allow for cost reductions to some BOP components. Still, many well-established BOP technologies and stack material costs are less likely to see significant cost reductions at high manufacturing rates. As such, manufacturing scale is limited in how much it can reduce electrolyzer costs, and additional advances for cost reduction may be needed to achieve cost targets. It will likely take many combined strategies to achieve significant cost reductions for electrolyzers and enable low-cost hydrogen production. We can use our manufacturing cost model to quantify potential cost reductions from the considerations described above and demonstrate pathways to lower cost electrolyzers. This allows for better understanding of cost reduction strategies and enables more informed research, development, and deployment for electrolyzers.

cost↗

Bio-reduction of ferrihydrite-montmorillonite-organic matter complexes: Effect of montmorillonite and fate of organic matter

Organic matter (OM) is often associated with Fe (hydr)oxides such as ferrihydrite (Fh) in soils and sediments, forming binary Fh-OM complexes. Microbial reduction of Fh results in destabilization of the complexes and mineral/OM transformation. However, little is known about the role of clay minerals in such processes, despite their common co-existence with Fh and OM in natural environments. Here Fh-OM complexes were synthesized in the presence of montmorillonite (SWy-2), forming ternary Fh-(SWy-2)-OM complexes. A metal-reducing bacterium Geobacter sulfurreducens was used to reduce Fh in the complexes under circumneutral pH and anoxic conditions with or without H 2 as extra electron donor. Various spectroscopy and mass spectrometry methods were used to monitor the progress of Fh bio-reduction and mineral/OM transformation. Results showed that G. sulfurreducens utilized mineral-bound OM as electron donor and/or carbon source to couple with Fh reduction. Relative to Fh-OM complex, Addition of SWy-2 to Fh-OM complex enhanced the bio-reduction extent of Fh by increasing the proportion of bioavailable OM that was weakly bound to SWy-2. However, its effect on the bio-reduction rate was variable. SWy-2 initially decreased the rate, because it spatially separated OM (electron donor) from Fh (electron acceptor). During later incubation, SWy-2 increased the reduction rate by sorbing biogenic Fe 2+ that would otherwise passivate the Fh and cell surfaces. Bio-reduction transformed mineral-bound OM to microbial products (e.g. necromass, extracellular polymeric substances), but organic compounds with aromatic structures, carboxyl groups and large molecular weight were more resistant to desorption and oxidation. The persistence of these compounds against bio-reduction induced transformation is likely due to their stronger binding with minerals and/or lower nominal oxidation states of carbon relative to other compounds. Our results provide new insights into the role of clay minerals in regulating biogeochemical cycling of solid-phase Fe and transformation of mineral-associated OM in anoxic soil environments.

58 GEOSCIENCES↗

Biomimetic Metal-Free Hydride Donor Catalysts for CO 2 Reduction

The catalytic reduction of carbon dioxide to fuels and value-added chemicals is of significance for the development of carbon recycling technologies. One of the main challenges associated with catalytic CO 2 reduction is product selectivity: the formation of carbon monoxide, molecular hydrogen, formate, methanol, and other products occurs with similar thermodynamic driving forces, making it difficult to selectively reduce CO 2 to the target product. Significant scientific effort has been aimed at the development of catalysts that can suppress the undesired hydrogen evolution reaction and direct the reaction toward the selective formation of the desired products, which are easy to handle and store. Inspired by natural photosynthesis, where the CO 2 reduction is achieved using NADPH cofactors in the Calvin cycle, in this study we explore biomimetic metal-free hydride donors as catalysts for the selective reduction of CO 2 to formate. Here, we outline our recent findings on the thermodynamic and kinetic parameters that control the hydride transfer from metal-free hydrides to CO 2 . By experimentally measuring and theoretically calculating the thermodynamic hydricities of a range of metal-free hydride donors, we derive structural and electronic factors that affect their hydride-donating abilities. Two dominant factors that contribute to the stronger hydride donors are identified to be (i) the stabilization of the positive charge formed upon HT via aromatization or by the presence of electron-donating groups and (ii) the destabilization of hydride donors through the anomeric effect or in the presence of significant structural constrains in the hydride molecule. Hydride donors with appropriate thermodynamic hydricities were reacted with CO 2 , and the formation of the formate ion (the first reduction step in CO 2 reduction to methanol) was confirmed experimentally, providing an important proof of principle that organocatalytic CO 2 reduction is feasible. The kinetics of hydride transfer to CO 2 were found to be slow, and the sluggish kinetics were assigned in part to the large self-exchange reorganization energy associated with the organic hydrides in the DMSO solvent. Finally, we outline our approaches to the closure of the catalytic cycle via the electrochemical and photochemical regeneration of the hydride (R–H) from the conjugate hydride acceptors (R + ). We illustrate how proton-coupled electron transfer can be efficiently utilized not only to lower the electrochemical potential at which the hydride regeneration takes place but also to suppress the unwanted dimerization that neutral radical intermediates tend to undergo. Overall, this account provides a summary of important milestones achieved in organocatalytic CO 2 reduction and provides insights into the future research directions needed for the discovery of inexpensive catalysts for carbon recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis and Benchmarking of feature reduction for classification under computational constraints

Abstract Machine learning is most often expensive in terms of computational and memory costs due to training with large volumes of data. Current computational limitations of many computing systems motivate us to investigate practical approaches, such as feature selection and reduction, to reduce the time and memory costs while not sacrificing the accuracy of classification algorithms. In this work, we carefully review, analyze, and identify the feature reduction methods that have low costs/overheads in terms of time and memory. Then, we evaluate the identified reduction methods in terms of their impact on the accuracy, precision, time, and memory costs of traditional classification algorithms. Specifically, we focus on the least resource intensive feature reduction methods that are available in Scikit-Learn library. Since our goal is to identify the best performing low-cost reduction methods, we do not consider complex expensive reduction algorithms in this study. In our evaluation, we find that at quadratic-scale feature reduction, the classification algorithms achieve the best trade-off among competitive performance metrics. Results show that the overall training times are reduced 61%, the model sizes are reduced 6×, and accuracy scores increase 25% compared to the baselines on average with quadratic scale reduction.

97 MATHEMATICS AND COMPUTING↗

Modeling Isothermal Reduction of Iron Ore Pellet Using Finite Element Analysis Method: Experiments & Validation

Iron ore pellet reduction experiments were performed with pure hydrogen (H2) and mixtures with carbon monoxide (CO) at different ratios. For direct reduction processes that switch dynamically between reformed natural gas and hydrogen as the reductant, it is important to understand the effects of the transition on the oxide reduction kinetics to optimize the residence time of iron ore pellets in a shaft reactor. Hence, the reduction rates were studied by varying experimental parameters such as the temperature (800, 850 & 900 °C), reactant gas flow rate (100, 150 & 200 cm3/min), pellet size and composition of the reactant gas mixture. The rate of reduction was observed to increase with an increase in temperature and reactant gas flow rate, but it decreased with an increase in pellet size. SEM greyscale analysis was performed to analyze the porosity and phase composition of partially reduced pellets. The porosity of the pellets was observed to increase from 0.3 for unreacted pellet to 0.42 for a completely reduced pellet. Energy-dispersive X-ray spectroscopy (EDAX) analysis was performed to identify the phases observed in the SEM images. The fraction of iron phase was observed to increase from the shell region of the pellet to the core region with an increase in the degree of reduction. A 2D-axisymmetric numerical model was developed on COMSOL Multiphysics, and it was validated using the conversion (X) vs. time curves obtained from each experiment. The model was able to accurately predict the total time needed for the complete conversion of a single iron ore pellet for multiple experiments. Effects of changes in the porosity and tortuosity of the pellet on the model were also studied and the rate of reduction was observed to be sensitive to changes in both porosity and tortuosity. The SEM analysis and the model results show that tortuosity is higher for pellets reduced with H2 than for pellets reduced with H2-CO gas mixtures.

08 HYDROGEN↗

CaMn 0.9 Ti 0.1 O 3 based redox catalysts for chemical looping – Oxidative dehydrogenation of ethane: Effects of Na 2 MoO 4 promoter and degree of reduction on the reaction kinetics

Reduction kinetics and stability of 20 wt% Na 2 MoO 4 -promoted CaMn 0.9 Ti 0.1 O 3 were investigated for its applications in Chemical Looping – Oxidative Dehydrogenation (CL-ODH) of ethane, a potential alternative for ethylene production with higher efficiency and lower emissions. Here, the present work reports a kinetics model and parameters for a Na 2 MoO 4 -promoted, Ti-doped CaMnO 3 (CaMn 0.9 Ti 0.1 O 3 ) redox catalyst under H 2 and C 2 H 4 . A first-order reaction model provides the best fit for the reduction of Na 2 MoO 4 /CaMn 0.9 Ti 0.1 O 3 under H 2 , while the C 2 H 4 reduction is well described by an Avrami–Erofe’ev model. The activation energy for C 2 H 4 oxidation is approximately three times higher than that for H 2 conversion, showing that the activation of C 2 H 4 is significantly more difficult on the surface of the redox catalyst. The reduction rate of Na 2 MoO 4 /CaMn 0.9 Ti 0.1 O 3 under H 2 at 750 °C is more than two orders of magnitude greater than that under C 2 H 4 , while the reduction rate of unpromoted CaMn 0.9 Ti 0.1 O 3 is comparable under H 2 and C 2 H 4 , showing that the addition of Na 2 MoO 4 effectively suppresses C 2 H 4 combustion relative to H 2 oxidation. The kinetics results for Na 2 MoO 4 /CaMn 0.9 Ti 0.1 O 3 confirm its excellent selectivity towards hydrogen combustion, making it a promising candidate under CL-ODH. Additionally, the stability of the CaMn 0.9 Ti 0.1 O 3 @ Na 2 MoO 4 core-shell structure, which was the underlying reason for the excellent selectivity, was examined under both shallow and deep reductions. It was determined that deep reduction of the redox catalyst, e.g. higher than 80% solid conversion, would lead to loss of sodium and hence to decreased selectivity for hydrogen combustion. In contrast, the core-shell structure was well-maintained, exhibiting excellent performance after 50 redox cycles when deep reduction of the redox catalyst was avoided. This study offers a basis for both the CL-ODH reactor design and redox catalyst optimizations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanistic Insights into Co and Fe Quaterpyridine-Based CO 2 Reduction Catalysts: Metal–Ligand Orbital Interaction as the Key Driving Force for Distinct Pathways

Both [Co II (qpy)(H 2 O) 2 ] 2+ and [Fe II (qpy)(H 2 O) 2 ] 2+ (with qpy = 2,2':6',2'':6'',2'''-quaterpyridine) are efficient homogeneous electrocatalysts and photoelectrocatalysts for the reduction of CO 2 to CO. The Co catalyst is more efficient in the electrochemical reduction, while the Fe catalyst is an excellent photoelectrocatalyst. This work uses density functional theory to shed light on the contrasting catalytic pathways. While both catalysts experience primarily ligand-based reductions, the second reduction in the Co catalyst is delocalized onto the metal via a metal-ligand bonding interaction, causing a spin transition and a distorted ligand framework. This orbital interaction explains the experimentally observed mild reduction potential and slow kinetics of the second reduction. The decreased hardness and doubly occupied d z 2 -orbital facilitate a σ-bond with the CO 2 -π* in an η 1 - κC binding mode. CO 2 binding is only possible after two reductions resulting in an EEC mechanism (E = electron transfer, C = chemical reaction), and the second protonation is rate-limiting. In contrast, the Fe catalyst maintains a Lewis acidic metal center throughout the reduction process because the metal orbitals do not strongly mix with the qpy-π* orbitals. Further, this allows binding of the activated CO 2 in an η 2 -binding mode. This interaction stabilizes the activated CO 2 via a π-type interaction of a Fe-t 2g orbital and the CO 2 -π* and a dative bond of the oxygen lone pair. This facilitates CO 2 binding to a singly reduced catalyst resulting in an ECE mechanism. The barrier for CO 2 addition and the second protonation are higher than those for the Co catalyst and rate-limiting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrocatalytic nitrate reduction on rhodium sulfide compared to Pt and Rh in the presence of chloride

Chloride poisoning is a serious problem for the electrocatalytic reduction of aqueous nitrate (NO 3 – ) and improved electrocatalysts are needed. Here we study the electrocatalytic activity of rhodium sulfide supported on carbon (Rh x S y /C) for the reduction of nitrate and compare it against Pt/C and Rh/C in the presence of chloride. Between 0.05–0.15 V vs. RHE, Rh x S y /C has a steady-state nitrate reduction current density in 1 M H 2 SO 4 + 1 M NaNO 3 that is 1.6–5.6 times greater than Rh/C (the most active metal electrocatalyst) and 10–24 times greater than Pt/C. Current densities are decreased by 37% for Rh x S y /C, 62% for Rh/C, and 40% for Pt/C at 0.1 V vs. RHE in the presence of 1 mM chloride. The decrease in nitrate reduction activity for Pt, Rh, and Rh x S y is due to the competitive adsorption of chloride and nitrate on the surface. Density functional theory (DFT) modeling predicts that chloride poisoning will persistently inhibit nitrate reduction on metals due to linear adsorbate scaling relations between nitrate and chloride. DFT calculations and microkinetic modeling of our experimental measurements predict that nitrate converts to nitrite via an H-assisted dissociation mechanism on Pt and direct nitrate dissociation on Rh and Rh x S y . Pristine Rh x S y (i.e., Rh 3 S 4 , Rh 2 S 3 , and Rh 17 S 15 ) terraces are predicted to be inactive toward nitrate reduction. In contrast, sulfur vacancies in Rh 3 S 4 terraces are predicted to be active for nitrate reduction, but also bind chloride strongly. Furthermore, sulfur-defected Rh 3 S 4 rationalize the experimentally observed high activity but moderate chloride poison-resistance of Rh x S y /C for nitrate reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Robust measurement of microbial reduction of graphene oxide nanoparticles using image analysis

ABSTRACT Shewanella oneidensis ( S. oneidensis ) has the capacity to reduce electron acceptors within a medium and is thus used frequently in microbial fuel generation, pollutant breakdown, and nanoparticle fabrication. Microbial fuel setups, however, often require costly or labor-intensive components, thus making optimization of their performance onerous. For rapid optimization of setup conditions, a model reduction assay can be employed to allow simultaneous, large-scale experiments at lower cost and effort. Since S. oneidensis uses different extracellular electron transfer pathways depending on the electron acceptor, it is essential to use a reduction assay that mirrors the pathways employed in the microbial fuel system. For microbial fuel setups that use nanoparticles to stimulate electron transfer, reduction of graphene oxide provides a more accurate model than other commonly used assays as it is a bulk material that forms flocculates in solutions with a large ionic component. However, graphene oxide flocculates can interfere with traditional absorbance-based measurement techniques. This study introduces a novel image analysis method for quantifying graphene oxide reduction, showing improved performance and statistical accuracy over traditional methods. A comparative analysis shows that the image analysis method produces smaller errors between replicates and reveals more statistically significant differences between samples than traditional plate reader measurements under conditions causing graphene oxide flocculation. Image analysis can also detect reduction activity at earlier time points due to its use of larger solution volumes, enhancing color detection. These improvements in accuracy make image analysis a promising method for optimizing microbial fuel cells that use nanoparticles or bulk substrates. IMPORTANCE Shewanella oneidensis ( S. oneidensis ) is widely used in reduction processes such as microbial fuel generation due to its capacity to reduce electron acceptors. Often, these setups are labor-intensive to operate and require days to produce results, so use of a model assay would reduce the time and expenses needed for optimization. Our research developed a novel digital analysis method for analysis of graphene oxide flocculates that may be utilized as a model assay for reduction platforms featuring nanoparticles. Use of this model reduction assay will enable rapid optimization and drive improvements in the microbial fuel generation sector.

Bennett, Danielle T. (ORCID:0009000188748827)↗

A Generalized Grain-Scale Model for the Non-Plasma and Plasma-Assisted Hydrogen Direct Reduction of Iron Ore

Direct Reduction of Iron ore using hydrogen (H-DRI) is a promising pathway towards efficient steelmaking and accurate predictive models are a necessity for scale-up and optimization of this technology. However, accurate models of this process remain limited because existing models oversimplify grain-scale phenomena, such as nonlinearity inside grain, self-sufficient porosity, surface reactions, and the role of plasma species. These phenomena are important for flash steelmaking and plasma-assisted H-DRI processes. To address this need, we present a phenomenological model for simulating H-DRI at the scale of a single micron-sized grain of the iron ore. We call this the Transient Reactive Grain Model (TRGM). TRGM incorporates key physical process: gas species transport, a chemical kinetics of material conversion, nanopore structural evolution and, adsorption-desorption surface kinetics at the reactive nanopore surface. The important contribution of this work is that the model provides a dependence on different reductant species, specifically hydrogen atoms versus molecules, so that role of hydrogen plasma reduction can be clarified compared to the use of pure hydrogen gas reduction. TRGM predictions agree well with experimental data for both molecular H2 reduction of Fe2O3 and plasma hydrogen reduction of Fe3O4. Results reveal species concentration gradients with a diffuse reaction zone, and enhanced hydrogen diffusion at the grain outer surface due to evolving porosity. These findings challenge common assumptions in existing models, including sharp reaction fronts, quasi-steady diffusion and kinetics, and the neglect of surface chemistry. As a generalized grain-scale model for H-DRI processes, TRGM has practical applications in flash steelmaking and in-flight reduction using both molecular and plasma hydrogen.

08 HYDROGEN↗