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At least 235 records · Page 13

Reactions of concerted decomposition of cyclic molecules, as studied by the quantum chemistry methods and parabolic model

Reactions of concerted decomposition of cyclic molecules (Diels—Alder retro-reactions) were studied using quantum chemical modeling and the method of intersecting parabolas (M3IP model). According to results of quantum chemical calculations and topological analysis of transition states (TSs) of five concerted decomposition reactions of cyclic molecules, all TSs represent six-membered rings in which the bonds being cleaved are weak covalent ones. The presence of ring heteroatoms (N, O, or S) has a strong impact on the TS geometry and on the energy characteristics of the reactions. The M3IP model was used to process the experimental results to develop an algorithm for calculating the activation energies (E) of the reactions in question and the classical potential barriers to thermally neutral reaction (E{sub e}{sup 0}). Factors influencing the energies E were determined and assessed. These include the enthalpy of reaction, substituents, ring heteroatoms, the force constants of bonds, and the bond dissociation energies. A comparison of the activation energies E and the enthalpies of reaction ΔH obtained from the M3IP and density functional B3LYP/6-311++G** calculations revealed good agreement between them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decomposition Algorithms for Solving NP-hard Problems on a Quantum Annealer

NP-hard problems such as the maximum clique or minimum vertex cover problems, two of Karp’s 21 NP-hard problems, have several applications in computational chemistry, biochemistry and computer network security. Adiabatic quantum annealers can search for the optimum value of such NP-hard optimization problems, given the problem can be embedded on their hardware. However, this is often not possible due to certain limitations of the hardware connectivity structure of the annealer. This paper studies a general framework for a decomposition algorithm for NP-hard graph problems aiming to identify an optimal set of vertices. Our generic algorithm allows us to recursively divide an instance until the generated subproblems can be embedded on the quantum annealer hardware and subsequently solved. Furthermore, the framework is applied to the maximum clique and minimum vertex cover problems, and we propose several pruning and reduction techniques to speed up the recursive decomposition. The performance of both algorithms is assessed in a detailed simulation study.

97 MATHEMATICS AND COMPUTING↗

Graph-Based Modeling and Decomposition of Hierarchical Optimization Problems

We present a graph-theoretic modeling approach for hierarchical optimization that leverages the OptiGraph abstraction implemented in the Julia package Plasmo.jl. We show that the abstraction is flexible and can effectively capture complex hierarchical connectivity that arises from decision-making over multiple spatial and temporal scales (e.g., integration of planning, scheduling, and operations in manufacturing and infrastructures). We also show that the graph abstraction facilitates the conceptualization and implementation of decomposition and approximation schemes. Specifically, we propose a graph-based Benders decomposition (gBD) framework that enables the exploitation of hierarchical (nested) structures and that uses graph aggregation/partitioning procedures to discover such structures. In addition, we provide a Julia implementation of gBD, which we call PlasmoBenders.jl. We illustrate the capabilities using examples arising in the context of energy and power systems.

97 MATHEMATICS AND COMPUTING↗

Detecting Thermally-Induced Spinodal Decomposition with Picosecond Ultrasonics in Cast Austenitic Stainless Steels

Destructive techniques to monitor nuclear reactor component health may not always be available during service, as they are time-consuming and often require pre-installed inspection coupons. Non-destructive evaluation (NDE) techniques can bridge this gap by rapidly identifying the state of mission-critical reactor components, via inference between NDE-measurable material properties and those of ultimate interest, such as ductility and toughness. Here, we demonstrate one such inference about the health of thermally aged cast austenitic stainless steels. Observations of surface acoustic wave peak (SAW) splitting correlate with spinodal decomposition-induced embrittlement as destructively measured by Charpy impact energy. Elastodynamic calculations and molecular dynamics simulations of the effects of spinodal decomposition on elastic moduli support that the new acoustic modes present are due to stiffening in the δ-ferrite domains. Finally, this discovery enables one to probe structure-property relationships in materials in a greatly accelerated manner, suggesting that similar inference methods can be used to determine material fitness-for-service, or to quickly uncover new structure-property relationships.

304-type stainless steel↗

Kinetic study of Ni-M/CNT catalyst in methane decomposition under microwave irradiation

Methane catalytic decomposition has been studied with catalysts that can attenuate the energy of electromagnetic waves to heat and drive the reaction. Herein, we report, for the first time, a comprehensive kinetic study of Ni-M (M=Pd, Cu, or Fe)-CNT catalysts under microwave irradiation. These binary metal alloy nanoparticles have been synthesized on multiwalled carbon nanotube support with solvothermal process. These catalysts showed incredible performance for both absorbing microwave energy and catalyzing the reaction to form carbon nanotubes and hydrogen. Ni-M-CNT has a reaction order of 0.74. 10Ni-1 Pd-CNT, 10Ni-1Cu-CNT, and 10Ni-1Fe-CNT have activation energies at 87, 75, and 69 kJ/mol. The investigation was carried out in a differential reactor. The results indicated that 10Ni-1Fe-CNT had the lowest activation energy due to the increase in microwave susceptibility. Here, this work pioneered the microwave catalytic methane decomposition field as well as paving the way for future electrification of CO x -free hydrogen production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Online randomized interpolative decomposition with a posteriori error estimator for temporal PDE data reduction

Traditional low-rank approximation is a powerful tool for compressing large data matrices that arise in simulations of partial differential equations (PDEs), but suffers from high computational cost and requires several passes over the PDE data. The compressed data may also lack interpretability thus making it difficult to identify feature patterns from the original data. Here, to address these issues, we present an online randomized algorithm to compute the interpolative decomposition (ID) of large-scale data matrices in situ. Compared to previous randomized IDs that used the QR decomposition to determine the column basis, we adopt a streaming ridge leverage score-based column subset selection algorithm that dynamically selects proper basis columns from the data and thus avoids an extra pass over the data to compute the coefficient matrix of the ID. In particular, we adopt a single-pass error estimator based on the non-adaptive Hutch++ algorithm to provide real-time error approximation for determining the best coefficients. As a result, our approach only needs a single pass over the original data and thus is suitable for large and high-dimensional matrices stored outside of core memory or generated in PDE simulations. A strategy to improve the accuracy of the reconstructed data gradient, when desired, within the ID framework is also presented. We provide numerical experiments on turbulent channel flow and ignition simulations, and on the NSTX Gas Puff Image dataset, comparing our algorithm with the offline ID algorithm to demonstrate its utility in real-world applications.

Column subset selection↗

Optimizing the design and operation of water networks: Two decomposition approaches

We consider the design and operation of water networks simultaneously. Water network problems can be divided into two categories: the design problem and the operation problem. The design problem involves determining the appropriate pipe sizing and placements of pump stations, while the operation problem involves scheduling pump stations over multiple time periods to account for changes in supply and demand. Our focus is on networks that involve water co-produced with oil and gas. While solving the optimization formulation for such networks, we found that obtaining a primal (feasible) solution is more challenging than obtaining dual bounds using off-the-shelf mixed-integer nonlinear programming solvers. Therefore, we propose two methods to obtain good primal solutions. One method involves a decomposition framework that utilizes a convex reformulation, while the other is based on time decomposition. To test our proposed methods, we conduct computational experiments on a network derived from the PARETO case study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Local reduced-order modeling for electrostatic plasmas by physics-informed solution manifold decomposition

Despite advancements in high-performance computing and modern numerical algorithms, computational cost remains prohibitive for multi-query kinetic plasma simulations. Here, in this work, we develop data-driven reduced-order models (ROMs) for collisionless electrostatic plasma dynamics, based on the kinetic Vlasov-Poisson equation. Our ROM approach projects the equation onto a linear subspace defined by the proper orthogonal decomposition (POD) modes. We introduce an efficient tensorial method to update the nonlinear term using a precomputed third-order tensor. We capture multiscale behavior with a minimal number of POD modes by decomposing the solution manifold into multiple time windows and creating temporally local ROMs. We consider two strategies for decomposition: one based on the physical time and the other based on the electric field energy. Applied to the 1D1V Vlasov–Poisson simulations, that is, prescribed E-field, Landau damping, and two-stream instability, we demonstrate that our ROMs accurately capture the total energy of the system both for parametric and time extrapolation cases. The temporally local ROMs are more efficient and accurate than the single ROM. In addition, in the two-stream instability case, we show that the energy-windowing reduced-order model (EW-ROM) is more efficient and accurate than the time-windowing reduced-order model (TW-ROM). With the tensorial approach, EW-ROM solves the equation approximately 90 times faster than Eulerian simulations while maintaining a maximum relative error of 7.5% for the training data and 11% for the testing data.

Electrostatic plasmas↗

Stochastic scheduling of generating units with weekly energy storage: A hybrid decomposition approach

We propose a solution method for the large-scale stochastic unit commitment (SUC) problem with weekly-dispatched energy storage and significant weather-dependent stochastic generating capacity. Weekly storage facilities that mostly charge during weekends and discharge during weekdays require a weekly scheduling of generating units, which result in a large-scale optimization problem. This SUC problem is formulated as a two-stage stochastic model and we use the conditional value-at-risk as a risk measure. Using a Benders framework, the proposed solution method decomposes the problem into a mixed-integer linear master problem and linear and continuous subproblems. The master problem corresponds to the first-stage decisions throughout the week and includes all the commitment (binary) variables and their corresponding constraints. The subproblems correspond to the actual dispatch of the generating units on a weekly basis. Based on the success of column-and-constraint generation algorithms to solve robust optimization problems, we improve the low communication between the master problem and the subproblems in the standard Benders decomposition by adding primal variables and constraints from the subproblems to the master problem, which provides a better approximation of the recourse function. Furthermore, our computational experiments demonstrate the effectiveness of the proposed decomposition method using an instance of the South Carolina synthetic system with 90 generating units under 40 scenarios.

25 ENERGY STORAGE↗

Microwave-assisted ammonia decomposition over metal nitride catalysts at low temperatures

The negative environmental impact of fossil fuel-based energy systems has unveiled the need to develop a CO x -free sustainable hydrogen (H 2 ) economy. Employing a microwave-assisted route, a ternary metal nitride catalyst (i.e., Co 2 Mo 3 N), and a low-temperature-pressure NH 3 decomposition process, this study investigated the possibility of developing a distributed H 2 production process. Here, this study not only explored lower cost-based catalyst systems but also the use of a microwave reactor to increase the energy efficiency of the process. Results from catalytic NH 3 decomposition experiments, performed in microwave reactors on Co 2 Mo 3 N catalyst, demonstrated the peak energy efficiency (of ~0.006 kgH 2 /kWh) at 400 °C in ambient pressure (with an NH 3 conversion >90%) which was around ninety times (~90 x) more efficient than a conventional system. Activation energy calculation also displayed a 20% less energy requirement for the microwave-based process (~31 kJ mol -1 ) than the conventional system (~37 kJ mol -1 ), indicating the advantage of the microwave-based process. Further microwave-assisted catalytic measurements and characterization of the Co 2 Mo 3 N catalyst, using x-ray diffraction (XRD) technique and scanning electron microscopic (SEM) images, revealed the excellent stability of this material at its peak performance (at 400 °C) and illustrated the potential of using this catalyst for a sustainable, economic, and energy-efficient approach for producing CO x -free H 2 .

08 HYDROGEN↗

Parametric dynamic mode decomposition for reduced order modeling

Dynamic Mode Decomposition (DMD) is a model-order reduction approach, whereby spatial modes of fixed temporal frequencies are extracted from numerical or experimental data sets. The DMD low-rank or reduced operator is typically obtained by singular value decomposition of the temporal data sets. For parameter-dependent models, as found in many multi-query applications such as uncertainty quantification or design optimization, the only parametric DMD technique developed was a stacked approach, with data sets at multiple parameter values were aggregated together, increasing the computational work needed to devise low-rank dynamical reduced-order models. Here in this paper, we present two novel approach to carry out parametric DMD: one based on the interpolation of the reduced-order DMD eigen-pair and the other based on the interpolation of the reduced DMD (Koopman) operator. Numerical results are presented for diffusion-dominated nonlinear dynamical problems, including a multiphysics radiative transfer example. All three parametric DMD approaches are compared.

97 MATHEMATICS AND COMPUTING↗

Evolution of the role of molybdenum in duplex stainless steels during thermal aging: From enhancing spinodal decomposition to forming heterogeneous precipitates

Thermal aging of ferrite in duplex stainless steels leads to a complex microstructural evolution that can give way to large deleterious changes in mechanical properties. The microstructural evolution mechanisms that happen concurrently are strongly linked to minor changes in composition. By characterizing duplex stainless steels with various compositions over a range of aging conditions, it was revealed that adding a modest amount of Mo to cast austenitic stainless steel (such as changing from grade CF3 to grade CF3M) not only increases the kinetics of spinodal decomposition and Ni-Si-Mn-rich G-phase precipitation, but it also forms a separate Mo-rich phase. At shorter equivalent aging times, Mo segregates from Fe and towards Cr accelerating spinodal decomposition. At longer aging times, Mo enriches in the Ni-Si-Mn clusters before phase separating into an adjoined Mo-rich cluster. We found that these phase changes and precipitation events result in a rather steep drop in fracture and impact toughness. These results will inform the design of similar alloys for use at high temperatures.

36 MATERIALS SCIENCE↗

From phase decomposition to evaporation: A multi-modal evaluation of thermally degraded model lightweight high-entropy alloy

Lightweight high-entropy alloys (LHEAs) have the potential to replace conventional lightweight materials due to their superior mechanical properties and thermal stability. However, the thermal degradation pattern of LHEAs from phase decomposition to evaporation is not clear. We develop a new Al-based dual phase (FCC + HCP) LHEA—AlTi 0.45 CuZn, and further investigate its thermal degradation behavior for potential high-temperature structural applications. Using multimodal advanced characterization techniques such as differential scanning calorimetry/thermogravimetric analysis, scanning/transmission electron microscopy, and synchrotron X-ray diffraction/pair distribution function (XRD/PDF), a sequence of thermal degradation events beyond the thermal phase stability limit—between 250 and 360 °C—is observed. These include phase decomposition at ~360 °C, Zn evaporation at ~750 °C, and LHEA melting at 880 °C which results in ~25% cumulative weight loss. The formation of Al-Ti phase off the AlTi 0.45 CuZn matrix is due to the largest negative mixing enthalpy for Al-Ti than other binary pairs. Similarly, Zn evaporation from AlTi 0.45 CuZn LHEA is due to its faster evaporation rate than other constituent elements. The high-resolution synchrotron XRD and PDF results support the aforementioned observations; in addition, they reveal local atomic arrangements, local strain, and sluggish grain growth in the LHEA. Among other LHEAs of close density range (5.55 ≤ ρ ≤ 5.85 g/cc), the investigated LHEA exhibits outstanding nano-indentation hardness values due to the coupled grain size effect and HCP phase strengthening of the FCC matrix. As the search for LHEAs for lightweight applications grows, this study shows the potential use of AlTi 0.45 CuZn LHEA for structural applications even at elevated temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dynamics of organic matter molecular composition under aerobic decomposition and their response to the nitrogen addition in grassland soils

Grassland soils store a substantial proportion of the global soil carbon (C) stock. The transformation of C in grassland soils with respect to chemical composition and persistence strongly regulate the predicted terrestrial-atmosphere C flux in global C biogeochemical cycling models. In addition, increasing atmospheric nitrogen (N) deposition alters C chemistry in grassland soils. However, there remains controversy about the importance of mineralogical versus biochemical preservation of soil C, as well as uncertainty regarding how grassland soil C chemistry responds to elevated N. This study used grassland soils with diverse soil organic matter (SOM) chemistries in an 8-month aerobic incubation experiment to evaluate whether the chemical composition of SOM converged across sites over time, and how SOM persistence responded to the N addition. This study demonstrates that over the course of incubation, the richness of labile compounds decreased in soils with less ferrihydrite content, whereas labile compounds were more persistent in ferrihydrite rich soils. In contrast, we found that the richness of more complex compounds increased over the incubation in most sites, independent of soil mineralogy. Moreover, we demonstrate the extent to which the diverse chemical composition of SOM converged among sites in response to microbial decomposition. N fertilization decreased soil respiration and inhibited the convergence of molecular composition across ecosystems by altering N demand for microbial metabolism and chemical interactions between minerals and organic molecules. This study provides original evidence that the decomposition and metabolism of labile organic molecules were largely regulated by soil mineralogy (physicochemical preservation), while the metabolism of more complex organic molecules was controlled by substrate complexity (biochemical preservation) independent to mineral-organic interactions. This study advanced our understanding of the dynamic biogeochemical cycling of C by unveiling that N addition dampened C respiration and diminished the convergence of SOM chemistry across diverse grassland ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Air-Stable Calcium Cyanamide-Supported Ruthenium Catalyst for Ammonia Synthesis and Decomposition

Efficient ammonia synthesis and decomposition processes under mild conditions are important to meet the expanding demand in major applications of ammonia as the energy carrier and to provide feedstock for chemical industry. In this study, we report that air-stable calcium cyanamide-supported ruthenium (Ru/CaCN 2 ) works as an efficient and stable catalyst for ammonia synthesis and decomposition. Ru/CaCN 2 exhibits greater catalytic performances for both reactions than Ru/Ca 2 N electride and Ru–Cs/MgO. The kinetic analysis for ammonia synthesis suggests that Ru/CaCN 2 exhibits low apparent activation energy and high resistance to hydrogen poisoning, which has characteristics similar to the kinetic parameters of Ru-supported electride catalyst. H 2 -temperature programmed reaction and temperature programmed desorption revealed that Ru promoted the formation of CN 2 vacancies on the CaCN 2 surface which in turn capture hydrogen as H – ions during the reaction. Density functional theory calculations provide insights into how the formation of CN 2 vacancies is promoted by Ru, which leads to the decrease in the work function of the CaCN 2 surface and the hydrogen capture at the Ru-support interface. These results suggest that the high catalytic performance of Ru/CaCN 2 can be attributed to the formation of a quasi-electride structure at the Ru–CaCN 2 interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Steering the Methane Dry Reforming Reactivity of Ni/La 2 O 3 Catalysts by Controlled In Situ Decomposition of Doped La 2 NiO 4 Precursor Structures

The influence of A- and/or B-site doping of Ruddlesden-Popper perovskite materials on the crystal structure, stability, and dry reforming of methane (DRM) reactivity of specific A 2 BO 4 phases (A = La, Ba; B = Cu, Ni) has been evaluated by a combination of catalytic experiments, in situ X-ray diffraction, X-ray absorption spectroscopy (XAS), X-ray photoelectron spectroscopy (XPS), and aberration-corrected electron microscopy. At room temperature, B-site doping of La 2 NiO 4 with Cu stabilizes the orthorhombic structure ( Fmmm ) of the perovskite, while A-site doping with Ba yields a tetragonal space group ( I 4/ mmm ). We observed the orthorhombic-to-tetragonal transformation above 170 °C for La 2 Ni 0.9 Cu 0.1 O 4 and La 2 Ni 0.8 Cu 0.2 O 4 , slightly higher than for undoped La 2 NiO 4 . Loss of oxygen in interstitial sites of the tetragonal structure causes further structure transformations for all samples before decomposition in the temperature range of 400 °C-600 °C. Controlled in situ decomposition of the parent or A/B-site doped perovskite structures in a DRM mixture (CH 4 :CO 2 = 1:1) in all cases yields an active phase consisting of exsolved nanocrystalline metallic Ni particles in contact with hexagonal La 2 O 3 and a mixture of (oxy)carbonate phases (hexagonal and monoclinic La 2 O 2 CO 3 , BaCO 3 ). Differences in the catalytic activity evolve because of (i) the in situ formation of Ni-Cu alloy phases (in a composition of >7:1 = Ni:Cu) for La 2 Ni 0.9 Cu 0.1 O 4 , La 2 Ni 0.8 Cu 0.2 O 4 , and La 1.8 Ba 0.2 Ni 0.9 Cu 0.1 O 4 , (ii) the resulting Ni particle size and amount of exsolved Ni, and (iii) the inherently different reactivity of the present (oxy)carbonate species. Based on the onset temperature of catalytic DRM activity, the latter decreases in the order of La 2 Ni 0.9 Cu 0.1 O 4 ~ La 2 Ni 0.8 Cu 0.2 O 4 ≥ La 1.8 Ba 0.2 Ni 0.9 Cu 0.1 O 4 > La 2 NiO 4 > La 1.8 Ba 0.2 NiO 4 . Simple A-site doped La 1.8 Ba 0.2 NiO 4 is essentially DRM inactive. The Ni particle size can be efficiently influenced by introducing Ba into the A site of the respective Ruddlesden-Popper structures, allowing us to control the Ni particle size between 10 nm and 30 nm both for simple B-site and A-site doped structures. Hence, it is possible to steer both the extent of the metal-oxide-(oxy)carbonate interface and its chemical composition and reactivity. Counteracting the limitation of the larger Ni particle size, the activity can, however, be improved by additional Cu-doping on the B-site, enhancing the carbon reactivity. Exemplified for the La 2 NiO 4 based systems, we show how the delicate antagonistic balance of doping with Cu (rendering the La 2 NiO 4 structure less stable and suppressing coking by efficiently removing surface carbon) and Ba (rendering the La 2 NiO 4 structure more stable and forming unreactive surface or interfacial carbonates) can be used to tailor prospective DRM-active catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the Reactivity and Decomposition of a Highly Active Iron Pincer Catalyst for Hydrogenation and Dehydrogenation Reactions

The iron pincer complex ( iPr PNP)Fe(H)(CO) (1, iPr PNP – = N(CH 2 CH 2 PiPr 2 ) 2 - ) is an active (pre)catalyst for many hydrogenation and dehydrogenation reactions. This is in part because 1 can reversibly add H 2 across the iron-amide bond to form ( iPr PN H P)Fe(H) 2 (CO) (2, iPr PN H P = HN(CH 2 CH 2 P i Pr 2 ) 2 ). However, rapid decomposition limits the catalytic performance of 1 and related complexes. We explored the pathways through which catalytic intermediates related to 1 and 2 undergo decomposition. This involved characterizing the unstable and previously unobserved complexes [( iPr PN H P)Fe(H)(CO)(L)] + (5-L; L = THF or N 2 ) and [( iPr PN H P)Fe(H)(H 2 )(CO)] + (8), which are proposed as intermediates when 1 and 2 are used as catalysts. Compound 8 was synthesized through the reaction of ( iPr PN H P)Fe(H)(CO)(PF 6 ) (6) with H 2 , and the solid-state structure was established using both X-ray and neutron diffraction. As part of our studies on understanding the reactivity of 5-L, we determined the thermodynamic hydricity of 2, which is valuable for predicting its reactivity as a hydride donor. Further, it is shown that species such as 5-L decompose to the same inactive species observed in catalysis using 1 and 2, and theoretical calculations suggest that this likely occurs via a bimolecular pathway. To provide support for this hypothesis, we isolated the dimeric species [{( iPr PN H P)Fe(H)(CO)} 2 {μ-CN}] + (11) and [{( iPr PN H P)Fe(H)(CO)} 2 {μ-OC(H)O}] + (12), which show that catalytic intermediates ligated by iPr PN H P can form dimeric species. Our results provide general strategies for improving catalysis using 1 and 2, and we used this information to rationally increase the performance of 1 in formic acid dehydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-Scale Modeling for Plasma-Enhanced Ammonia Decomposition over Carbides and Nitrides

Ammonia is a carbon-free hydrogen carrier, but its decomposition typically requires high temperatures over costly Ru-based catalysts due to the large barrier for N≡N bond formation. We develop a multiscale framework combining density functional theory, zero-dimensional plasma kinetics, and microkinetic modeling to elucidate how non-thermal plasma (NTP) enables low-temperature NH 3 decomposition over Co-based carbides and nitrides, benchmarked against Ru and Co. Under thermal conditions, all catalysts are limited by N≡N bond formation, with Co 3 C(001) most active owing to its negatively charged surface, strong N* binding, and low activation barriers of N≡N bond formation. Plasma-induced vibrational excitation of NH 3 and its reactive radicals promotes a radical-driven •NH 2 –N* coupling pathway that dominates on Co 3 C(001) and Co 3 N(001), shifting the rate-limiting step to NH 3 (v1) dissociation, increasing turnover frequencies by up to 6 orders of magnitude, and reducing the temperature needed to reach a turnover frequency of 5 s –1 from >680 °C (Ru and Co under thermal condition) to 267 °C (Co 3 C) and 415 °C (Co 3 N). These results identify Co-based carbides and nitrides as promising plasma-active catalysts for energy-efficient hydrogen production from ammonia.

ammonia decomposition↗