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665 records · Page 37

Synergistic Electrocatalytic Syngas Production from Carbon Dioxide by Bi‐Metallic Atomically Dispersed Catalysts

Abstract The production of syngas by traditional processes such as steam methane reforming is energetically intensive and produces a large amount of CO 2 emissions. In contrast, the electrochemical CO 2 reduction reaction (CO 2 RR) enables the carbon neutral production of syngas at ambient conditions. Among non‐precious metal catalysts, metal‐nitrogen‐carbon electrocatalysts are inexpensive and highly selective towards syngas production. This study examined the selectivity of mono‐ and bi‐metallic (M−N−C, M=Fe, Mo or FeMo) electrocatalysts towards syngas production. The ratio of the CO : H 2 in the syngas was tuned by modifying the ratio of the metallic precursors in the bi‐metallic FeMo−N−C catalysts, tailoring the catalysts’ selectivity towards the CO 2 RR or the hydrogen evolution reaction (HER). The catalyst synthesis temperature(s) were considered as they influence the catalyst morphology and activity. Further, the dependence of the ratio of CO : H 2 in the syngas as a function of the potential was explored for the different bi‐metallic catalysts. This work showed that by tailoring both the ratio of Fe : Mo in the bi‐metallic catalyst and optimizing the reductive potential, a CO : H 2 ratio between 0.25 to 5 was achievable. This study demonstrated a novel approach in which the ratio of the product syngas composition could be tailored in a single reaction, without the need for further downstream processing to reach a desired composition.

Delafontaine, Laurent↗

Methanol carbonylation to acetaldehyde on Au particles supported by single-layer MoS 2 grown on silica

Homogenous single-layer MoS 2 films coated with sub-single layer amounts of gold are found to isolate the reaction of methanol with carbon monoxide, the fundamental step toward higher alcohols, from an array of possible surface reactions. Active surfaces were prepared from homogenous single-layer MoS 2 films coated with sub-single layer amounts of gold. These gold atoms formed clusters on the MoS2 surface. A gas mixture of carbon monoxide (CO) and methanol (CH 3 OH) was partially converted to acetaldehyde (CH 3 CHO) under mild process conditions (308 kPa and 393 K). This carbonylation of methanol to a C 2 species is a critical step toward the formation of higher alcohols. Density functional theory modeling of critical steps of the catalytic process identify a viable reaction pathway. Imaging and spectroscopic methods revealed that the single layer of MoS 2 facilitated formation of nanoscale gold islands, which appear to sinter through Ostwald ripening. Here, the formation of acetaldehyde by the catalytic carbonylation of methanol over supported gold clusters is an important step toward realizing controlled production of useful molecules from low carbon-count precursors.

2D catalyst↗

Ensembles of Metastable States Govern Heterogeneous Catalysis on Dynamic Interfaces

Heterogeneous catalysis is at the heart of chemical industry. Being able to tune and design efficient catalysts for processes of interest is of an utmost importance, and for this, the molecular-level understanding of heterogeneous catalysts is the first step, and indeed a prime focus of the modern catalysis research. For a long time, a single most thermodynamically stable structure of the catalytic interface attained in reaction conditions had been envisioned as the reactive phase. However, some catalytic interfaces continue to undergo structural dynamics in the steady state, triggered by high temperatures, pressures, and binding and changing reagents. Among particularly dynamic interfaces are such widely-used catalysts as crystalline and amorphous surfaced supporting (sub-)nano metallic clusters. Recently, it became clear that this dynamic fluxionality causes the supported clusters to populate many distinct structural and stoichiometric states in catalytic conditions. Hence, the catalytic interface should be viewed as an evolving statistical ensemble of many (not one) structures. As such, every member in the ensemble contributes to the properties of the catalyst differently, and in proportion to its probability to be populated. This new notion flips the established paradigm and calls for new theory, modeling approaches, operando measurements, and updated design strategies. The statistical ensemble nature of surface-supported sub-nano cluster catalysts can be exemplified by oxide-supported and adsorbate-covered Pt, Pd, Cu, CuPd clusters, catalytic toward oxidative and non-oxidative dehydrogenation. They have access to a variety of 3D and quasi-2D shapes. The compositions of their thermal ensembles are dependent on the cluster size, leading to size-specific catalytic activities and the famous “every atom counts” phenomenon. The support and adsorbates affect catalyst structures, and state of the reacting species causes the ensemble to change in every reaction intermediate. The most stable member of the ensemble dominates the thermodynamic properties of the corresponding intermediate, whereas the kinetics can be determined by more active but less populated metastable catalyst states, and that suggests that many earlier studies might have overlooked the actual active sites. Both effects depend on the relative time-scales of catalyst restructuring and reaction dynamics. The catalyst may routinely operate off-equilibrium. Ensemble phenomena lead to surprising exceptions from established rules of catalysis, such as scaling relations, and Arrhenius behavior. Catalyst deactivation is also an ensemble property, and its extent of mitigation can be predicted through the new paradigm. These findings were enabled by advances in theory, such as global optimization and subsequent utilization of multiple local minima, and pathways sampling, as well as operando catalyst characterization. The fact that the per-site and per-species resolution is needed for the description and predicting of catalyst properties gives theory the central role in catalysis research, as most experiments provide ensemble-average information and cannot detect the crucial minority species that may be responsible for the catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Site heterogeneity and broad surface-binding isotherms in modern catalysis: Building intuition beyond the Sabatier principle

Learning the science of heterogeneous catalysis and electrocatalysis always starts with the simple case of a flat, uniform surface with an ideal adsorbate. It has of course been recognized for a century that real catalysts are more complicated. For the increasingly complex catalysts of the 21st century, this Perspective argues that surface heterogeneity and non-ideal binding isotherms are central features, and their implications need to be incorporated in current thinking. A variety of systems are described herein where catalyst complexity leads to broad, non-Langmuirian surface isotherms for the binding of hydrogen atoms – and this occurs even for ideal, flat Pt(111) surfaces. Modern catalysis employs nanoscale materials whose surfaces have substantial step, edge, corner, impurity, and other defect sites, and they increasingly have both metallic and non-metallic elements M n X m , including metal oxides, chalcogenides, pnictides, carbides, doped carbons, etc. The surfaces of such catalysts are often not crystal facets of the bulk phase underneath, and they typically have a variety of potential active sites. Catalytic surfaces in operando are often non-stoichiometric, amorphous, dynamic, and impure, and often vary from one part of the surface to another. Understanding of the issues that arise at such nanoscale, multi-element catalysts is just beginning to emerge. Yet these catalysts are widely discussed using Brønsted/Bell-Evans-Polanyi (BEP) relations, volcano plots, Tafel slopes, the Butler-Volmer equation, and other linear free energy relations (LFERs), which all depend on the implicit assumption that the active sites are “similar” and that surface adsorption is close to ideal. These assumptions underly the ubiquitous intuition based on the Sabatier Principle, that the fastest catalysis will occur when key intermediates have free energies of adsorption that are not too strong nor too weak. Current catalysis research often aims to minimize the complexity of non-ideal isotherms through experimental and computational design (e.g., the use of single crystal surfaces), and these studies are the foundation of the field. In contrast, this Perspective argues that the heterogeneity of binding sites and binding energies is an inherent strength of these catalysts. Here, this diversity makes many nanoscale catalysts inherently a high-throughput screen wrapped in a tiny package. Only by making the heterogeneity part of the foundation of catalysis models, sorting the types of active sites and dissecting non-ideal binding isotherms, will modern catalysis learn to harness the inherent diversity of real catalysts. Controlling and exploiting diversity rather than avoiding it will help to optimize complex modern catalysts and catalytic conditions.

Mayer, James M.↗

Nickel(ii) complexes based on dithiolate–polyamine binary ligand systems: crystal structures, hirshfeld surface analysis, theoretical study, and catalytic activity study on photocatalytic hydrogen generation

To ascertain the influence of binary ligand systems [1,1-dicyanoethylene-2,2-dithiolate (i-mnt -2 ) and polyamine {tetraen = tris(2-aminoethyl)amine, tren = diethylene triamine and opda = o-phenylenediamine}] on the coordination modes of the Ni(II) metal center and resulting supramolecular architectures, a series of nickel(II) thiolate complexes [Ni(tetraen)(i-mnt)](DMSO) (1), [Ni 2 (tren) 2 (i-mnt) 2 ] (2), and [Ni 2 (i-mnt) 2 (opda) 2 ] n (3) have been synthesized in high yield in one step in water and structurally characterized by single crystal X-ray crystallography and spectroscopic techniques. X-ray diffraction studies disclose the diverse i-mnt -2 coordination to the Ni +2 center in the presence of active polyamine ligands, forming a slightly distorted octahedral geometry (NiN 4 S 2 ) in 1, square planar (NiS 4 ) and distorted octahedral geometries (NiN 6 ) in the bimetallic co-crystallized aggregate of cationic [Ni(tren) 2 ] +2 and anionic [Ni(i-mnt) 2 ] -2 in 2, and a one dimensional (1D) polymeric chain along the [100] axis in 3, having consecutive square planar (NiS 4 ) and octahedral (NiN 6 ) coordination kernels. The N–H···O, N–H···S, N–H···N, N–H···S, N–H···N, and N–H···O type hydrogen bonds stabilize the supramolecular assemblies in 1, 2, and 3 respectively imparting interesting graph-set-motifs. The molecular Hirshfeld surface analyses (HS) and 2D fingerprint plots were utilized for decoding all types of non-covalent contacts in the crystal networks. Atomic HS analysis of the Ni +2 centers reveals significant Ni–N metal–ligand interactions compared to Ni–S interactions. We have also studied the unorthodox interactions observed in the solid state structures of 1–3 by QTAIM and NBO analyses. Moreover, all the complexes proved to be highly active water reduction co-catalysts (WRC) in a photo-catalytic hydrogen evolution process involving iridium photosensitizers, wherein 2 and 3 having a square planar arrangement around the nickel center(s) – were found to be the most active ones, achieving 1000 and 1119 turnover numbers (TON), respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Engineering Nanostructured Interfaces of Hexagonal Boron Nitride-Based Materials for Enhanced Catalysis

Hexagonal boron nitrides (h-BNs) are attractive two-dimensional (2D) nanomaterials that consist of alternating B and N atoms and layered honeycomb-like structures similar to graphene. They have exhibited unique properties and promising application potentials in the field of energy storage and transformation. Recent advances in utilizing h-BN as a metal-free catalyst in the oxidative dehydrogenation of propane have triggered broad interests in exploring h-BN in catalysis. However, h-BN-based materials as robust nanocatalysts in heterogeneous catalysis are still underexplored because of the limited methodologies capable of affording h-BN with controllable crystallinity, abundant porosity, high purity, and defect engineering, which played important roles in tuning their catalytic performance. Here, in this account, our recent progress in addressing the above issues will be highlighted, including the synthesis of high-quality h-BN-based nanomaterials via both bottom-up and top-down pathways and their catalytic utilization as metal-free catalysts or as supports to tune the interfacial electronic properties on the metal nanoparticles (NPs). First, we will focus on the large-scale fabrication of h-BN nanosheets (h-BNNSs) with high crystallinity, improved surface area, satisfactory purity, and tunable defects. h-BN derived from the traditional approaches using boron trioxide and urea as the starting materials generally contains carbon/oxygen impurities and has low crystallinity. Several new strategies were developed to address the issues. Using bulk h-BN as the precursor via gas exfoliation in liquid nitrogen, single- or few-layered h-BNNS with abundant defects could be generated. Amorphous h-BN precursors could be converted to h-BN nanosheets with high crystallinity assisted by a magnesium metallic flux via a successive dissolution/precipitation/crystallization procedure. The as-fabricated h-BNNS featured high crystallinity and purity as well as abundant porosity. An ionothermal metathesis procedure was developed using inorganic molten salts (NaNH 2 and NaBH 4 ) as the precursors. The h-BN scaffolds could be produced on a large scale with high yield, and the as-afforded materials possessed high purity and crystallinity. Second, utilization of the as-prepared h-BN library as metal-free catalysts in dehydrogenation and hydrogenation reactions will be summarized, in which they exhibited enhanced catalytic activity over the counterparts from the previous synthesis method. Third, the interface modulation between metal NPs with the as-prepared defects’ abundant h-BN support will be highlighted. The h-BN-based strong metal–support interaction (SMSI) nanocatalysts were constructed without involving reducible metal oxides via the ionothermal procedure we developed by deploying specific inorganic metal salts, acting as robust nanocatalysts in CO oxidation. Under conditions simulated for practical exhaust systems, promising catalytic efficiency together with high thermal stability and sintering resistance was achieved. Across all of these examples, unique insights into structures, defects, and interfaces that emerge from in-depth characterization through microscopy, spectroscopy, and diffraction will be highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamically Unveiling Metal–Nitrogen Coordination during Thermal Activation to Design High-Efficient Atomically Dispersed CoN 4 Active Sites

We elucidate the structural evolution of CoN 4 sites during thermal activation by developing a zeolitic imidazolate framework (ZIF)-8-derived carbon host as an ideal model for Co 2+ ion adsorption. Subsequent in situ X-ray absorption spectroscopy analysis can dynamically track the conversion from inactive Co-OH and Co-O species into active CoN 4 sites. The critical transition occurs at 700 °C and becomes optimal at 900 °C, generating the highest intrinsic activity and four-electron selectivity for the oxygen reduction reaction (ORR). DFT calculations elucidate that the ORR is kinetically favored by the thermal-induced compressive strain of Co-N bonds in CoN 4 active sites formed at 900 °C. Further, we developed a two-step (i.e., Co ion doping and adsorption) Co-N-C catalyst with increased CoN 4 site density and optimized porosity for mass transport, and demonstrated its outstanding fuel cell performance and durability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of stoichiometry and hydration level on water domain size and transport in poly(aryl piperidinium) alkaline anion-exchange membranes

Alkaline water electrolysis holds promise in decarbonizing the global economy by enabling renewable hydrogen production with non-precious group metal catalysts. Anion exchange membranes are an important component of alkaline water electrolyzers and would ideally be durable while allowing for high hydroxide conductivity. The poly(aryl piperidinium) (PAP) class of polymers has attracted recent interest due to their good mechanical robustness and high ionic conductivity. Here, in this work, we perform atomistic molecular dynamics (MD) simulations of several PAP polymers at experimentally relevant hydration levels and polymer ion exchange capacities (IECs) to gain nanoscale insight into their properties and to help elucidate the trade-offs that result from tuning the IECs through the polymer stoichiometry. Our MD-predicted macroscopic polymer properties were found to be in good agreement with experimentally available polymer swelling ratios, water-occupied volumes, X-ray scattering, and ionic conductivities. The models show that for hydration levels greater than 8H 2 O per cation a single water cluster will form that percolates through the system. The growth in water cluster size results in large polymer swelling, the creation of larger channels with widths of 7 Å or larger, and nanophase separation between the hydrophilic domains and the polymer with characteristic length scales of approximately 20–30 Å. The experimentally observed lack of a strong X-ray scattering peak at low wavevectors can be explained by a cancellation between the polymer-polymer/water-water and polymer-water correlations and not a loss in nanophase separation. The overlap in coordination environments of the hydroxide oxygen and polymer nitrogen atoms implies that vehicular diffusion between cationic groups could play a role in hydroxide transport. The polymers' hydroxide and water diffusion constants increase by approximately an order of magnitude between hydration levels of 8 and 20H 2 O per cation. However, there are diminishing returns in hydroxide diffusion constant once the IEC exceeds 2.4 meq/g.

08 HYDROGEN↗

Ni Nanoparticles on CeO 2 (111): Energetics, Electron Transfer, and Structure by Ni Adsorption Calorimetry, Spectroscopies, and Density Functional Theory

The morphology, interfacial bonding energetics and charge transfer of Ni clusters and nanoparticles on slightly-reduced CeO 2-x (111) surfaces at 100 to 300 K have been studied using single crystal adsorption calorimetry (SCAC), low-energy ion scattering spectroscopy (LEIS), Xray photoelectron spectroscopy (XPS), low energy electron diffraction (LEED) and density functional theory (DFT). The initial heat of adsorption of Ni vapor decreased with the extent of pre-reduction (x) of the CeO 2-x (111), showing that stoichiometric ceria adsorbs Ni more strongly than oxygen vacancies. On CeO 1.95 (111) at 300 K, the heat dropped quickly with coverage in the first 0.1 ML, attributed to nucleation of Ni clusters on stoichiometric steps, followed by the Ni particles spreading onto less favorable terrace sites. At 100 K, the clusters nucleate on terraces due to slower diffusion. Adsorbed Ni monomers are in the +2 oxidation state, and they bind by ~45 kJ/mol more strongly to step sites than terraces. The measured heat of adsorption versus average particle size on terraces is favorably compared to DFT calculations. The Ce 3d XPS lineshape showed an increase in Ce 3+ /Ce 4+ ratio with Ni coverage, providing the number of electrons donated to the ceria per Ni atom. The charge transferred per Ni is initially large but strongly decreases with increasing cluster size for both experiments and DFT, and shows large differences between clusters at steps versus terraces. This charge is localized on the interfacial Ni and Ce atoms in their atomic layers closest to the interface. This knowledge is crucial to understanding the nature of the active sites on the surface of Ni-CeO 2 catalysts for which metal-oxide interactions play a very important role in the activation of O-H and C-H bonds. In conclusion, the changes in these interactions with Ni particle size (metal loading) and the extent of reduction of the ceria help to explain how previously reported catalytic activity and selectivity change with these same structural details.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ligation of Single-Site Ruthenium within Perovskite Oxides for Efficient Conversion of Thermodynamically Stable Molecules

Ru cation ligation in SrTiO 3 perovskite and their migration to the surface through exsolution are investigated for the dry reforming of methane (DRM), a chemistry that requires activation of two thermodynamically stable molecules, CH 4 and CO 2 . Compared to a supported 1 wt % Ru/SrTiO 3 benchmark, doped and exsolved Ru-SrTiO 3 demonstrate ≥3× higher CH 4 turnover rates (873 K), with isolated, ligated Ru exhibiting higher reactivity. Reactor studies assert that CH 4 and CO 2 activation are both kinetically relevant for CH 4 turnover rates on exsolved Ru-SrTiO 3 , unlike for supported Ru systems, where H-abstraction from CH 4 is the sole kinetically relevant step. As such, exsolved and doped Ru architectures are responsive toward co-reactant activation strategies, with their consequent reaction networks showing marked departures from those established for supported Ru catalysts. In situ spectroscopy and kinetic analyses propose distinct sensitivity toward CO 2 on Ru-SrTiO 3 systems, where higher CH4 turnover rates result from O-assisted C─H bond activation pathways. These pathways occur on paired Ru-oxygen vacancy sites that are inherent to the perovskite structure and are not readily accessible on supported Ru catalysts. Here, CO 2 is activated on oxygen vacancies directly adjacent to Ru active sites, which facilitates CH 4 C─H bond activation through a surface methoxy intermediate. The high reactivity of Ru-SrTiO 3 systems enables stable CH 4 turnover rates at milder reaction temperatures (673 K), conditions under which the supported counterpart, Ru/SrTiO 3 , is inactive. Overall, this work demonstrates that ligation of catalytically active cations in perovskite oxides facilitates site engineering toward atom-efficient activation of thermodynamically stable feedstocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

P‐Doping Modulated RuIr Nanoparticles Anchored on Co/N/C Catalysts with Improved Alkaline Hydrogen Evolution Activity and Stability

Achieving efficient and stable hydrogen evolution reactions in alkaline conditions is crucial for hydrogen production. In this study, a RuIr/Co (SA) NC-P catalyst featuring RuIr alloys alongside P-doping and CoNx sites is developed. RuIr alloying optimizes the electronic structure between Ru and Ir, promoting electron transfer from Ru to Ir. P-doping further modulates the electronic properties of RuIr alloys, optimizing hydrogen binding energy and weakening Ru─OH binding energy, facilitating rapid H 2 generation and OH ad transfer. Meanwhile, CoNx promotes water dissociation, providing a fast proton delivery path for RuIr alloys. The catalyst exhibits enhanced HER activity with a low overpotential of 20 mV at 10 mA cm −2 , a Tafel slope of 20.4 mV dec −1 , and a turnover frequency of 19.5 H 2 s −1 at 150 mV overpotential. Moreover, catalyst stability is improved 8 times by mitigating RuIr alloy dissolution/agglomeration via P-doping. In conclusion, this work introduces a promising approach for developing efficient and stable HER electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic Layer Deposition for Materials-Based H2 Storage: Opportunities and Limitations

The transportation demands in our growing hydrogen (H2) economy requires robust storage systems. The current commercially implemented technology in fuel cell cars relies on the well-established technology of hydrogen gas compressed to 350-700 bar, depending on the application. The compressed gas tanks in use today are bulky and cost intensive. To address this challenge, material-based storage is one of the long-term alternatives considered and constitutes the focus of this talk. Material-based storage is broadly defined as hydrogen bound to solid materials, with its binding strength varying from physisorption to porous materials, such as zeolites and metal organic frameworks, to chemisorption in (complex) metal hydrides. The ultimate targets set by the U.S. Department of Energy for this technology include a system gravimetric capacity of 6.5 wt% and volumetric capacity of 40 g/L at 100 bar, operating temperatures ranging between -40 C and +40 C and adsorption/desorption timescales of < 5 min. Storage in the form of physisorbed or chemisorbed hydrogen has guided the materials research, which metal- organic framework and (complex) metal hydrides being the most promising materials classes. A variety of these materials have met one or more of the targets, but it has remained elusive for a single material system to meet all these stringent requirements. Nano-encapsulation and low-concentration chemical additives have previously been employed separately to overcome such challenges. Functionalization via atomic layer deposition (ALD), however, offers unique characteristics that make it suitable for both, nano-encapsulation and "doping" with low-concentration additives. This deposition technique has sub-monolayer thickness control, is highly conformal in high-surface area materials and is self-limiting, i.e., once the gas-phase precursor reacts with the available surface sites, the surface reactions stop. In this presentation, we will showcase examples where ALD, more generally vapor-phase functionalization, on (complex) metal hydrides and organic frameworks has improved the material properties for H2 storage. In our first study, Al2O3 was deposited on magnesium borohydride, Mg(BH4)2, at room temperature using trimethylaluminum (TMA) and water. From our findings, encouraging initial results were obtained: the H2 desorption temperature was lowered by 60-120 degrees C, the desorbed gravimetric H2 capacity at temperatures < 250 degrees C was doubled, and the desorption kinetics increased by a factor of ~6 compared to uncoated Mg(BH4)2. However, hydrolysis reactions caused by residual surface -OH groups from the ALD water-pulse degraded the sample substantially. Through this study, the use of TMA was observed to be highly reactive with the Mg(BH4)2 surface species, leading to the strategy of exposing the sample only to TMA. The relative mole fraction of the vapor-phase additive can be precisely controlled with the number of TMA pulses and pulse duration. By tuning these parameters, we show in our second study that 10 pulses of TMA at ambient conditions were able to decrease the H2 desorption temperature by ~100 degrees C while retaining <95 % of its H2 capacity. We applied this approach with other additives such as BBr3, TiCl4 and tetrahydrofuran, and demonstrate that this unique approach opens the door to a new class of molecular additives and catalysts which cannot easily be introduced with conventional mechano-chemical or solvent-based techniques for (complex) metal-hydrides. In the case of metal organic frameworks, ALD is a promising technique to functionalize the pores with metal atoms or functional groups able to tune the gas selectivity and binding energy, for which ~15 kJ/mol has been established as the optimal value for H2 storage in sorbent materials. Vapor-phase techniques such as ALD have numerous benefits over other functionalization tools for H2 storage materials opening innumerable opportunities to the field. To exploit these opportunities, the current limitations on room temperature and water-less ALD processes needs to be overcome which will greatly expand the possibilities of encapsulation and incorporation of additives for organic frameworks and (complex) metal hydrides.

atomic layer deposition↗

Intermetallic Nanocatalysts from Heterobimetallic Group 10–14 Pyridine-2-thiolate Precursors

Intermetallic compounds are atomically ordered inorganic materials containing two or more transition metals and main-group elements in unique crystal structures. Intermetallics based on group 10 and group 14 metals have shown enhanced activity, selectivity, and durability in comparison to simple metals and alloys in many catalytic reactions. While high-temperature solid-state methods to prepare intermetallic compounds exist, softer synthetic methods can provide key advantages, such as enabling the preparation of metastable phases or of smaller particles with increased surface areas for catalysis. In this work, we study a generalized family of heterobimetallic precursors to binary intermetallics, each containing a group 10 metal and a group 14 tetrel bonded together and supported by pincer-like pyridine-2-thiolate ligands. Upon thermal decomposition, these heterobimetallic complexes form 10–14 binary intermetallic nanocrystals. Experiments and density functional theory (DFT) computations help in better understanding the reactivity of these precursors toward the synthesis of specific intermetallic binary phases. Using Pd 2 Sn as an example, we demonstrate that nanoparticles made in this way can act as uniquely selective catalysts for the reduction of nitroarenes to azoxyarenes, which highlights the utility of the intermetallics made by our method. Employing heterobimetallic pincer complexes as precursors toward binary nanocrystals and other metal-rich intermetallics provides opportunities to explore the fundamental chemistry and applications of these materials.

10-14 intermetallics↗

Selective activation of methane C–H bond in the presence of methanol

Direct methane to methanol (MTM) conversion over heterogeneous catalysts is a promising route for valorization of methane. The methane C-H bond activation is considered as the key step of the MTM and is the focus of considerable research activity. However, the formed methanol typically suffers from overoxidation largely due to the cleavage of a methanol C-H bond, whose bond dissociation energy is ca. 0.5 eV lower than that of the methane C-H bond, which usually translates to a transition state energy of the methanol C-H bond cleavage that is ca. 0.55 eV lower than that of methane whenever the reactions proceed through a radical mechanism. Furthermore, we propose a general approach for decreasing the transition state energy difference between the CH 4 and CH 3 OH C-H bond dissociation. When a metal-oxide supported cationic transition metal atom and a neighboring oxygen on the oxide surface serve as the active site, the transition state energy difference through a surface-stabilized pathway can be noticeably narrowed as compared with that of a radical pathway. For Ir, Pt and Rh-doped anatase TiO 2 (101), the CH 4 C-H bond activation can be preferred over that of CH 3 OH at significant methanol mole fraction. Also, for PdAu alloys containing adsorbed oxygen and positively charged Pd, calculations suggest in agreement with recent experiments (Science 367 (6474), 193-197) that the CH 4 C-H bond can be selectively activated in the presence of CH 3 OH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scalable Nano-Scaffold SOFC Anode Architecture Enabling Direct Hydrocarbon Utilization

This project is based on WVU’s pending patents, technology and aims to design and modify the internal surfaces of the Ni/YSZ anode from currently commercially viable Solid Oxide Fuel Cells (SOFCs) using the additive manufacturing process of Atomic Layer Deposition (ALD). The surface architecture/scaffold added onto the internal surface of the anode possesses an engineered nanostructure but it features only commonly-used oxide conductors and electro-catalyst materials. The surface layer possesses a minimum thickness of ~2-40 nm and is solely designed to control the surface reforming reactions and to increase catalytic activity. Three-dimensional (3D) nano scaffold architectures with the noble metal nano-catalyst, low-cost bimetallic catalytic alloys, and nano-scale ionic conducting oxide fully compatible with the state-of-the-art Ni/YSZ anode, were applied to the internal surface of the entire porous SOFC anode using ALD. In the present work, the surface scaffold architecture is essentially multi-functional at the nano-scale, facilitated by the multiple heterostructured interfaces. It will significantly enhance the power density and cell durability for direct hydrocarbon utilization by (1) increasing the number of electrochemical reaction sites to enhance the hydrogen/hydrocarbon oxidation reactions; (2) reducing carbon formation; (3) mitigating the coarsening of backbone Ni phase and the oxidation attack of Ni from oxidants (e.g., H2O, CO2); and (4) promoting the internal reforming capabilities, especially for natural gas applications. ALD is employed to generate stable anode surface architectures that are uniform, precisely controllable at the atomic scale, and accurately repeatable for processing. The engineered anode surface nano-scaffold architecture was cataloged and analyzed using High-resolution Transmission Electron Microscopy (TEM), and cell power/durability performance assessed via comprehensive electrochemical performance testing with commercial specimens and relevant environments using hydrocarbon fuels. To the best of our knowledge, this project is the First Report on ALD of Ni/YSZ. The actual achievement of this Project includes (1). Successful demonstration of 7 types of ALD layers on Ni/YSZ anode, including Co, Ni, Mn, Pt, Ru, ZrOx and multi-functional nano-composite. (1). Conformal coating and subsequently spontaneously pinning the discrete nano-catalyst, including the precious metal nano-catalyst and the Ni and Co catalysts, on the YSZ surface upon the electrochemical operation in the reduced atmosphere. Those nano-catalysts on the ionic-conducting YSZ provided excellent sites for promoting internal reforming; (2). Demonstrated ALD coating increased both catalytic activity and conductivity of Ni/YSZ. Conformal coating provided dopants and introduced additional electrical conducting pathways on the YSZ ionic conductor. The doped surface layer of YSZ with mixed conductivity thus further introduces the active triple phase boundaries adjacent to the ALD-coated nano-catalysts such as Pt, Co, and Ni that are pinned on the YSZ surface. The nano-composite ALD coating on Ni/YSZ anode has significantly increased cell durability; and (3). ALD coating of Ni/YSZ anode increased the power density of the entire cell by 300%. For a long time, the SOFC performance, such as the power density, was deemed hindered by the cathode. The sluggish oxygen reduction reaction (ORR) in the cathode was deemed as hindering the power density of the SOFCs. For the anode-supported commercial SOFCs, the cell performance is considered to be limited by the cathode's performance. For the first time in the field of SOFC, this project has demonstrated that (1). the performance of commercial SOFCs can be further increased by the ALD coating on Ni/YSZ anode backbone. (2). ALD coating on Ni/YSZ fuel electrodes results in the enhancement of power density, and increased reliability, robustness, and endurance of SOFCs, for their application using both hydrogen and hydrocarbon fuels over the entire operating temperature range of 650-800ºC for the inherently functional commercial cells. (3). ALD coating provides alternative approaches of exsolutions for introducing the stable catalyst onto the internal surface of the Ni/YSZ electrode. ALD coating could be much more versatile than exsolution in employing the catalysts with various chemistries onto the various backbones. (4). Due to the negligible amount of ALD materials coated onto the internal surface of the porous cathode of the as-fabricated cells, a peak power density increase up to 300 % induced by ALD coating was simultaneously achieved in terms of both power density and specific power. (5). The ALD coating developed through this project was applied to both the SOFC and Solid Oxide Electrolysis Cells (SOEC). SOEC’s face a similar but more demanding need to improve the fuel electrode's performance. It opens further research directions for electrocatalytic surface nanoionics with a wide range of chemistry. It will revolutionize our ability to render the formation of a nanostructured electrode that has been constantly pursued yet barely achieved for practical SOFC/SOEC applications. The research is also immediately transformative since both the preliminary data and the proposed work are on the direct implantation of nanoionics into the state-of-the-art inherently functional SOCs. It represents an immediate impact on the commercial sectors in SOC technology since the applied ALD processing is computer-controlled ALD coating using the commercial ALD systems, and it is scalable to both the single cells and SOC stacks.

36 MATERIALS SCIENCE↗

HydraGNN_Predictive_GFM_2026 - Ensemble of predictive graph foundation models for atomistic materials modeling

This release contains data and parameters of HydraGNN-based graph foundation models trained as a result of the work published in the pre-print "Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic Data" by M. Lupo Pasini et al. (https://arxiv.org/abs/2604.15380). We jointly train on 16 open first-principles datasets (544+ million structures covering 85+ elements) using a multi-task architecture with per-dataset heads and a scalable ADIOS2/DDStore data pipeline. On Frontier, we execute six large-scale DeepHyper hyperparameter optimization campaigns in FP64 and promote the top-performing message-passing models to sustained 2,048-node training, yielding a PaiNN-based lead model. The version of HydraGNN used to generate the outputs provided in this release is HydraGNN v5.0 (https://github.com/ORNL/HydraGNN/releases/tag/v5.0) The list of datasets used for the training of the graph foundation model is the following: 1) Alexandria [1] 2) ANI1x [2] 3) MPTrj [3] 4) Open Catalyst 2020 (OC20) [4] 5) Open Catalyst 2022 (OC22) [5] 6) Open Catalyst 2025 (OC25) [6] 7) Open Direct ir Capture 2023 (ODAC23) [7] 8) Open Materials 2024 (OMat24) [8] 9) Open Molecules 2025 (OMol25) [9] 10) OMol25-neutral (subset of OMol25 that contains only molecules with zero total charge) 11) OMol25-non-neutral (subset of OMol25 that contains only molecules with non-zero total charge) 12) Open Polymers 2026 (OPoly2026) [10] 13) Nabla2DFT [11] 14) QCML [12] 15) QM7X [reference 13] 16) transition1x [14] Dataset references: [1] J. Schmidt et al., “A dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals,” Scientific Data, vol. 9, p. 64, 2022. [2] J. S. Smith et al., “The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules,” Scientific Data, vol. 7, p. 134, 2020. [Online]. Available: https: //www.nature.com/articles/s41597-020-0473-z [3] A. Jain et al., “Commentary: The Materials Project: A materials genome approach to accelerating materials innovation,” APL Materials, vol. 1, no. 1, p. 011002, 07 2013. [Online]. Available: https://doi.org/10.1063/1.4812323 [4] L. Chanussot et al., “Open catalyst 2020 (oc20) dataset and community challenges,” ACS Catalysis, vol. 11, no. 10, pp. 6059–6072, 2021. [Online]. Available: https://doi.org/10.1021/acscatal.0c04525 [5] K. Tran et al., “Open catalyst 2022 (oc22) dataset and challenges for oxidation electrocatalysts,” ACS Catalysis, vol. 13, no. 5, pp. 3066–3084, 2023. [Online]. Available: https://doi.org/10.1021/acscatal.2c05426 [6] S. J. Sahoo et al., “The open catalyst 2025 (oc25) dataset and models for solid-liquid interfaces,” arXiv preprint arXiv:2509.17862, 2025. [Online]. Available: https://arxiv.org/abs/2509.17862 [7] A. Sriram et al., “The open DAC 2023 dataset and challenges for sorbent discovery in direct air capture,” ACS Central Science, vol. 10, no. 5, pp. 923–941, 2024. [8] L. Barroso-Luque et al., “Open materials 2024 (omat24) inorganic materials dataset and models,” 2024. [Online]. Available: https://arxiv.org/abs/2410.12771 [9] D. S. Levine et al., “The open molecules 2025 (OMol25) dataset, evaluations, and models,” 2025. [Online]. Available: https://arxiv.org/abs/2505.08762 [10] D. S. Levine et al., The open polymers 2026 (OPoly26) dataset and evaluations,” arXiv preprint arXiv:2512.23117, 2025. [Online]. Available: https://arxiv.org/abs/2512.23117 [11] K. Khrabrov et al., “Nabla2dft: A universal quantum chemistry dataset of drug-like molecules and a benchmark for neural network potentials,” in NeurIPS 2024 Datasets and Benchmarks Track, 2024. [Online]. Available: https://openreview.net/forum?id=ElUrNM9U8c [12] S. Ganscha et al., “The QCML dataset, quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations,” Scientific Data, vol. 12, p. 406, 2025. [13] J. Hoja et al., “QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules,” Scientific Data, vol. 8, p. 43, 2021. [Online]. Available: https://www.nature.com/articles/s41597-021-00812-2 [14] M. Schreiner et al., “Transition1x - a dataset for building generalizable reactive machine learning potentials,” Scientific Data, vol. 9, p. 779, 2022. The folder "datasets_ADIOS2_format" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "datasets_ADIOS2_format" directory contains 2 sub-directories, one for the version "v1" of the datasets and one for the version "v2" of the datasets. The version "v1" of the datasets provides values of the total energy as they are extracted from the original data as it was released by the respective institutions. The version "v2" of the datasets provides values of the energy that have been realigned. The realignment was performed by training a linear regression model that predicts the total energy as a function of the chemical composition of the atomistic structure, and then subtract such prediction from the original value of the total energy. Both folders "v1" and "v2" contain 16 sub-directories, each corresponding to an ADIOS2-formatted dataset The folder "DeepHyper-results" contains the configurational files and model's parameters for all the 186 HPO trials that were successfully completed by the scalable hyperparameter optimization (HPO) runs on Frontier. The content of the folder "DeepHyper-results" I structured as follows: 1) task-list.txt: list of mpnn name, jobid, and deephyper task id 2) gfm_${MPNN}_${JOBID}_0.${TASKID}: run directory with checkpoint files 3) gfm_${MPNN}: deephyper summary directory (*.csv) for each specific MPNN type 4) deephyper-experiment-${JOBID}: output and error logs for each job The file "deephyper-sorted.csv" contains the details of each HydraGNN model built and tested by HPO, obtained by merging the (*.csv) filed from each HPO run executed. Out of all the HPO trials, we selected 10 to continue the training of the respective HydraGNN models. Due to limited computational budget available in the LRN070 allocation we could not complete the training till convergence for all these 10 selected models. The folder "models" contains multiple sub-folders, one per each HydraGNN model trained. Each model sub-folder contains the parameters of each HydraGNN model, with multiple checkpoint-restarts. The list of sub-folders are as follows: 1) multidataset_hpo-BEST1-fp64 2) multidataset_hpo-BEST2-fp64 3) multidataset_hpo-BEST3-fp64 4) multidataset_hpo-BEST4-fp64 5) multidataset_hpo-BEST5-fp64 6) multidataset_hpo-BEST6-fp64 7) multidataset_hpo-BEST7-fp64 8) multidataset_hpo-BEST8-fp64 9) multidataset_hpo-BEST9-fp64 10) multidataset_hpo-BEST10-fp64 Within each one of these folders, additional auxiliary log files are provided with descriptions about how the training proceeded. The lead PaiNN-model is contained inside "multidataset_hpo-BEST6-fp64". The file "mlp_branch_weights" contains the parameters of the multi-layer perceptron (MLP) used to reconcile the predictions of the 16 output decoding heads of the HydragNN architectures. The MLP takes in input the chemical composition of the atomistic structure and predicts averaging weights to linearly mix the predictions of each output decoding head toward consolidating them into a single one. The folder "1.1billion-structure-inference" contains 1.1 billion atomistic structures randomly generated. Each structures is associated with energy and forces predicted with the lead-PaiNN model combined with the MLP model for reconciliation of the multi-branch predictions generated by the 16 output decoding heads. The folder "1.1billion-structure-inference" contains 9,300 (*.tar.gz) subdirectories, one per Frontier compute node used to execute the inference at exascale. Once uncompressed, each (*.tar.gz) subdirectory contains an ADIOS2 (*.bp) file container, where each atomistic structure is stored as a PyTorch-Geometric Data object. The file "export_dataset_environment_variables.sh" contains the environment variables that need to be set before running the HydraGNN code to reproduce the results provided in this dataset release. The code that can be used to load the ADIOS2 files, load HydraGNN models, and run inference is available at: https://github.com/ORNL/HydraGNN/releases/tag/v5.0

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