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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Crystalline phase transitions and water-soluble complexes of copper(Ⅰ) 2-hydroxyethanethiolate

We report the coordination polymer copper(I) 2-hydroxyethanethiolate, (CuSCH 2 CH 2 OH) n , though insoluble in all common solvents, dissolved readily in basic aqueous solutions of the thiolate anion (HOCH 2 CH 2 S – ) of 2-mercaptoethanol to form a single species: the tetranuclear cluster [Cu 4 (μ-SCH 2 CH 2 OH) 6 ] 2– . From this solution were grown X-ray quality single crystals of copper(I) 2-hydroxyethanethiolate. This compound underwent a hitherto unknown crystal phase transition at ca. 6 °C, from point group P2 1 2 1 2 1 to Pna2 1 , with noticeable changes in the geometry of the Cu-S layer and in the orientation of the alkylthiolate side chains. When the bulky base tetrabutylammonium hydroxide was employed in the aqueous thiolate solution used to dissolve (CuSCH 2 CH 2 OH) n , the water-soluble polynuclear copper(I) complex bis(tetrabutylammonium) hexakis(μ-2-hydroxyethanethiolato) tetracuprate(I), [(C 4 H 9 ) 4 N] 2 [Cu 4 (μ-SCH 2 CH 2 OH) 6 ], could be isolated as X-ray quality crystals. Structural characterization of this complex revealed a tetrahedral arrangement of copper(I) centers with thiolates bridging the edges of the tetrahedra. On standing, this complex degraded to a larger polynuclear Cu(I) sulfide cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Adversarial Ensemble Modeling of Multi-modal Mechanical Properties for Iron-Based Alloys

Mechanical properties of alloys are controlled by their microstructure; and microstructure evolution is controlled by internal and external stressors. Chemical complexity during the alloy processing may result in heterogeneity and observation of multimodal performance patterns. Thus, to ensure the desired performance of stressed components it is important to understand the origin and mechanisms of such behavior. Adversarial ensemble modeling was introduced here to explain multimodal mechanical properties of the iron-based alloys. The modeling results showed that the areas of a single mechanism predominance were contiguous across the alloy compositions clustered by similarity, with sharp and persistent boundaries separating the single-mechanism domains. The marginal compositions resulted in increased competition between the adversarial models but only led to the multimodal behavior when the competing models diverged. Transparency of the clustering method allowed explicit interpretation of the chemistries leading to such competition. The adversarial ensemble was interpreted through transition from ductile to brittle microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Uranyl-Tc( vii )/Tc( v ) hybrid clusters

Pertechnetate ( 99 Tc VII O 4 − ) and autoreduced 99 Tc(v), species coordinate to UO 2 2+ to form hybrid clusters. These clusters have important implications to understanding technetium chemistry in spent nuclear fuel and legacy wastes.

Chemistry↗
DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1979

A meteor ablation-cluster ion atmospheric sodium theory

Neutral and ionic forms of sodium form narrow, well-defined layers which peak in the 90-95 km altitude region at midlatitudes. A new theory for the sodium layer is presented, which is found to be in good agreement with existing atmospheric observations as well as available laboratory measurements of rate constants. The layer is believed to result naturally from a meteor ablation source over a chemical sink with vertical transport of Na(+) playing an important role in the layer shape and variation. While the neutral chemistry is believed to consist of chemical equilibrium between Na and NaO, the ion chemistry departs from earlier studies and considers a cluster ion scheme. It is possible that higher-order cluster ions of sodium play a role in the formation of aerosols, through attachment or ion-induced nucleation processes.

Richter, E. S.↗
DOE OSTI2019

Diuranium(IV) Carbide Cluster U 2 C 2 Stabilized Inside Fullerene Cages

>Novel actinide cluster fullerenes, U 2 C 2 @ I h (7)-C 80 and U 2 C 2 @ D 3 h (5)-C 78 , were synthesized and fully characterized by mass spectrometry, single-crystal X-ray crystallography, UV–vis–NIR, nuclear magnetic resonance spectroscopy (NMR), X-ray absorption spectroscopy (XAS), Raman spectroscopy, IR spectroscopy, as well as density functional and multireference wave function calculations. The encapsulated U 2 C 2 is a novel example of a uranium carbide cluster featuring two U centers bridged by a C≡C unit. The U–C bond distances in these U 2 C 2 clusters are in the range between 2.130 and 2.421 Å. While the U 2 C 2 cluster in U 2 C 2 @C 80 adopts a butterfly-shaped geometry with a U–C 2 –U dihedral angle of 112.7° and a U–U distance of 3.855 Å, the U–U distance in U 2 C 2 @C 78 is 4.164 Å and the resulting U–C 2 –U dihedral angle is increased to 149.1°. The combined experimental and quantum-chemical results suggest that the formal U oxidation state is +4 in the U 2 C 2 cluster, and each U center transfers three electrons to the C 2 n cage and one electron to C 2 . Different from the strong U ＝ C covalent bonding reported for U 2 C 2 @ C 80 , the U–C bonds in U 2 C 2 are less covalent and predominantly ionic. The C–C triple bond is somewhat weaker than in HCCH, and the C–C π bonds undergo donation bonding with the U centers. This work shows that the combination of the unique encapsulation effect of fullerene cages and the variable oxidation states of actinide elements can lead to the stabilization of novel actinide clusters, which are not accessible by conventional synthetic methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Efficient Modeling of Structural, Electronic, and Optical Properties of Silver and Gold Metal Nanoclusters and Alloys Using Optimized SCC-DFTB Parameters

Computation of optical properties using conventional time-dependent density functional theory (TD-DFT) is time-consuming and memory-intensive. In this study, we investigate the accuracy and efficiency of the density functional tight binding (DFTB) framework with newly optimized Slater–Koster (SK) parameters for modeling the structural, electronic properties, and absorption spectra of silver and gold nanoclusters and their alloys. Our investigation of the ground state (GS) properties demonstrates that the newly developed GS-SK parameters enable DFTB to closely approximate DFT-calculated bond lengths for octahedron, tetrahedron, icosahedra, and truncated octahedron with sizes Ag n /Au n (n = 19, 20, 38, 55), nanoclusters and Ag 20 /Au 20 nanoalloys, with a maximum deviation of approximately 0.15 Å. Formation energy results indicate that the GS-SK parameters can closely estimate changes in formation energies with alloy composition, and the comparison of electronic structures for Ag 20 , Au 20 , and AgAu alloy nanoclusters using the DFTB approximation reveals good agreement in the projected density of states (DOS) profiles and energy levels. A second set of SK parameters, ES-SK, has been developed to describe excited state (ES) properties, including the absorption spectra of silver octahedron Ag 19 , tetrahedral Ag n (n = 20, 56, 84), truncated octahedron Ag 38 , and icosahedra Ag 55 closed-shell clusters and their gold and alloy counterparts over a broad range of alloy compositions. This parametrization uses TD-DFTB calculations and fine-tunes the d and p eigenvalues by comparing them to reference absorption spectra from first-principles TD-DFT. This enables the generation of absorption spectra that closely match the reference spectra when plasmon excitation is dominant, as demonstrated by studying the plasmonic properties of icosahedral Ag n and Au n (n = 309 and 561) nanoparticles. This includes the rapid loss in plasmon quality when Au partially replaces Ag in alloy clusters. Furthermore, these results provide a foundation for addressing computational bottlenecks in plasmonics and with new prospects for applications in the quantum plasmonics for bimetallic alloys.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Accelerating the Global Arrays ComEx Runtime using Multiple Progress Ranks

Partitioned Global Address Space (PGAS) models are part of system software that are being designed to support communication runtime for exascale applications. Suitability of using MPI as a scalable PGAS communication subsystem has been shown as a viable option due to its standardization and higher performance. We used MPI two-sided semantics with a combination of automatic and user defined splitting of MPI communicators to achieve asynchronous progress. Our implementation can make use of multiple asynchronous progress ranks (PR) per node that can be mapped to the computing architecture of a node in a distributed cluster. We are able to show significant speed up of over 2.0X and scaling of communication bound computational chemistry application over 1024 nodes of state- of-the-art HPC clusters. Our results show that while running a communication bound application workload on a certain number of cluster nodes, a use of optimum number of ranks dedicated for communication may be used to achieve asynchronous communication progress and obtain highest performance.

PGAS, global-arrays, NWCHEM, NWChemEx, HPC, GPGPU↗
NASA NTRS2019

Accelerated Simulation of Air Pollution Using NVIDIA RAPIDS

Atmospheric chemistry models are a central tool to study and forecast the impact of air pollution on the environment, vegetation, and human health. However, the numerical simulation of chemical kinetics is computationally expensive due to the stiffness of the system of ordinary differential equations that describes atmospheric chemistry. Here we present an alternative approach to the computation of atmospheric chemistry based on machine learning. Our training data set is produced using the NASA Goddard Earth Observing System (GEOS) model with GEOS-Chem chemistry, run on the NASA Center for Climate Simulation (NCCS) Discover supercomputing cluster on 384 Intel Xeon Haswell cores. This model spends more than 50% of total run time on solving atmospheric chemistry. The data set contains as input features the air pollution concentrations before solving the differential equations, together with some key physical parameters such as temperature and sun intensity. As target variables we define the air pollution concentrations after solving the differential equations. Using Dask-cuDF and Dask-XGBoost on the NVIDIA RAPIDS platform on 8 Tesla V100 GPUs, we generate from this training set gradient boosted decision tree models that can reproduce the simulation of chemical kinetics. We do this on the NCCS Advanced Data Analytics Platform (ADAPT) science cloud environment. Our application takes full advantage of recent advances in Dask-XGBoost, such as multi-node and multi-GPU scaling for distributed training with large data sets. The increase in training data size enabled by this is critical to capture the full range of chemical environments encountered across the globe and all annual seasons.The boosted tree models offer good predictability and show many of the features of the full chemistry reference simulation. Further improvements can be achieved through mass balance considerations and by accounting for error correlations. We incorporate the boosted tree models into the GEOS reference model using XGBoost's C API. This enables a seamless integration of the GPU trained models into GEOS-Chem, which is written in Fortran and optimized for use in a massively parallel CPU environment. We show the benefits of this approach and discuss the potential speedup of this machine learning accelerated atmospheric chemistry model.

Keller, Christoph A.↗
DOE OSTI2023

Navier: Dataflow Architecture for Computation Chemistry

Navier’s objectives were two evaluate the use of emerging technologies, especially dataflow accelerators, for high-performance computing (HPC) applications, specifically in the domain of chemistry, and to develop a prototype software stack to support such applications. Navier builds on capabilities previously developed by synergistic projects, such as PNNL Data Model Convergence (DMC) LDRD Hardware Advanced Workflows (HAW) and DuOMO, as well as DOE ARIAA. Throughout its 18 months, the Navier team developed new capabilities and artifacts at all levels of the HW/SW stack, provided a seamless way to integrate novel computing architectures (Sambanova SN10 and Xilinx Versal AI) into an existing software stack, developed chemistry workflows, data analytics tools, and HPC molecular dynamics workflows that leverage the developed stack and PNNL institutional investments in emerging architectures. Navier also explored the use of active learning to accelerate a computational chemistry workflow for organic molecules on PNNL Junction cluster (in collaboration with AMD/Xilinx). Navier developed tools, methodologies, and studies for hardware software co-design and (sparse) dataflow accelerators that are composable and can be used together or separately. These methodologies are now used in other projects, such as DOE AMAIS and HPDA. This report describes Navier’s achievement, the developed tools and methodologies, and the research findings and conclusions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Iron-sulfur clusters: the road to room temperature

Abstract Iron-sulfur proteins perform a wide variety of reactions central to the metabolisms of all living organisms. Foundational to their reaction chemistry are the rich electronic structures of their constituent Fe-S clusters, which differ in important ways from the active sites of mononuclear Fe enzymes. In this perspective, we summarize the essential electronic structure features that make Fe-S clusters unique, and point to the need for studies aimed at understanding the electronic basis for their reactivity under physiological conditions. Specifically, at ambient temperature, both the ground state and a large number of excited states are thermally populated, and thus a complete understanding of Fe-S cluster reactivity must take into account the properties, energies, and reactivity patterns of these excited states. We highlight prior research toward characterizing the low-energy excited states of Fe-S clusters that has established what is now a consensus model of these excited state manifolds and the bonding interactions that give rise to them. In particular, we discuss the low-energy alternate spin states and valence electron configurations that occur in Fe-S clusters of varying nuclearities, and finally suggest that there may be unrecognized functional roles for these states. Graphical abstract

Skeel, Brighton A. (ORCID:000000018458088X)↗
DOE OSTI2022

Computational studies of structural, energetic, and electronic properties of pure Pt and Mo and mixed Pt/Mo clusters: Comparative analysis of characteristics and trends

The added technological potential of bimetallic clusters and nanoparticles, as compared to their pure (i.e., one-component) counterparts, stems from the ability to further fine-tune their properties and, consequently, functionalities through a simultaneous use of the “knobs” of size and composition. The practical realization of this potential can be greatly advanced by the knowledge of the correlations and relationships between the various characteristics of bimetallic nanosystems on the one hand and those of their pure counterparts as well as pure constituent components on the other hand. Here, in this study, we present results of a density functional theory based study of pure Pt n and Mo n clusters aimed at revisiting and exploring further their structural, electronic, and energetic properties. These are then used as a basis for analysis and characterization of the results of calculations on two-component Pt n-m Mo m clusters. The analysis also includes establishing relationships between the properties of the Pt n-m Mo m clusters and those of their Pt n-m and Mo m components. One of the particularly intriguing findings suggested by the calculated data is a linear dependence of the average binding energy per atom in sets of Pt n-m Mo m clusters that have the same fixed number m of Mo atoms and different number n-m of Pt atoms on the fractional content (n-m)/n of Pt atoms. We derive an analytical model that establishes the fundamental basis for this linearity and expresses its parameters—the m-dependent slope and intercept—in terms of characteristic properties of the constituent components, such as the average binding energy per atom of Mo m and the average per-atom adsorption energy of the Pt atoms on Mo m . The conditions of validity and degree of robustness of this model and of the linear relationship predicted by it are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Lewis Acid Supported Nickel Nitrenoids

Metalation of the polynucleating ligand F,tbs LH 6 (1,3,5-C 6 H 9 (NC 6 H 3 −4-F−2-NSiMe 2 t Bu) 3 ) with two equivalents of Zn(N(SiMe 3 ) 2 ) 2 affords the dinuclear product ( F,tbs LH 2 )Zn 2 (1), which can be further deprotonated to yield ( F,tbs L)Zn 2 Li 2 (OEt 2 ) 4 (2). Transmetalation of 2 with NiCl 2 (py) 2 yields the heterometallic, trinuclear cluster ( F,tbs L)Zn 2 Ni(py) (3). Reduction of 3 with KC 8 affords [KC 222 ][( F,tbs L)Zn 2 Ni] (4) which features a monovalent Ni centre. Addition of 1-adamantyl azide to 4 generates the bridging μ 3 -nitrenoid adduct [K(THF) 3 ][( F,tbs L)Zn 2 Ni(μ 3 -NAd)] (5). EPR spectroscopy reveals that the anionic cluster possesses a doublet ground state (S = 1/2). Cyclic voltammetry of 5 reveals two fully reversible redox events. The dianionic nitrenoid [K 2 (THF) 9 ][( F,tbs L)Zn 2 Ni(μ 3 -NAd)] (6) was isolated and characterized while the neutral redox isomer was observed to undergo both intra- and intermolecular H-atom abstraction processes. Here, Ni K-edge XAS studies suggest a divalent oxidation state for the Ni centres in both the monoanionic and dianionic [Zn 2 Ni] nitrenoid complexes. However, DFT analysis suggests Ni-borne oxidation for 5.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Spatiotemporal Studies of Soluble Inorganic Nanostructures with X‐rays and Neutrons

This Review addresses the use of X-ray and neutron scattering as well as X-ray absorption to describe how inorganic nanostructured materials assemble, evolve, and function in solution. We first provide an overview of techniques and instrumentation (both large user facilities and benchtop). We review recent studies of soluble inorganic nanostructure assembly, covering the disciplines of materials synthesis, processes in nature, nuclear materials, and the widely applicable fundamental processes of hydrophobic interactions and ion pairing. Reviewed studies cover size regimes and length scales ranging from sub-Ångström (coordination chemistry and ion pairing) to several nanometers (molecular clusters, i.e. polyoxometalates, polyoxocations, and metal-organic polyhedra), to the mesoscale (supramolecular assembly processes). Reviewed studies predominantly exploit 1) SAXS/WAXS/SANS (small- and wide-angle X-ray or neutron scattering), 2) PDF (pair-distribution function analysis of X-ray total scattering), and 3) XANES and EXAFS (X-ray absorption near-edge structure and extended X-ray absorption fine structure, respectively). While the scattering techniques provide structural information, X-ray absorption yields the oxidation state in addition to the local coordination. Our goal for this Review is to provide information and inspiration for the inorganic/materials science communities that may benefit from elucidating the role of solution speciation in natural and synthetic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Rank-reduced coupled-cluster. III. Tensor hypercontraction of the doubles amplitudes

In this work, we develop a quartic-scaling implementation of coupled-cluster singles and doubles (CCSD) based on low-rank tensor hypercontraction (THC) factorizations of both the electron repulsion integrals (ERIs) and the doubles amplitudes. This extends our rank-reduced (RR) coupled-cluster method to incorporate higher-order tensor factorizations. The THC factorization of the doubles amplitudes accounts for most of the gain in computational efficiency as it is sufficient, in conjunction with a Cholesky decomposition of the ERIs, to reduce the computational complexity of most contributions to the CCSD amplitude equations. Further THC factorization of the ERIs reduces the complexity of certain terms arising from nested commutators between the doubles excitation operator and the two-electron operator. We implement this new algorithm using graphical processing units and demonstrate that it enables CCSD calculations for molecules with 250 atoms and 2500 basis functions using a single computer node. Furthermore, we show that the new method computes correlation energies with comparable accuracy to the underlying RR-CCSD method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Kinetics of Carbon Condensation in Detonation of High Explosives: First-Order Phase Transition Theory Perspective

We report the kinetics of carbon condensation, or carbon clustering, in detonation of carbon-rich high explosives is modeled by solving a system of rate equations for concentrations of carbon particles. Unlike previous efforts, the rate equations account not only for the aggregation of particles but also for their fragmentation in a thermodynamically consistent manner. Numerical simulations are performed, yielding the distribution of particle concentrations as a function of time. In addition to that, analytical expressions are obtained for all the distinct steps and regimes of the condensation kinetics, which facilitates the analysis of the numerical results and allows one to study the sensitivity of the kinetic behavior to the variation of system parameters. The latter is important because the numerical values of many parameters are not reliably known at present. The theory of the kinetics of first-order phase transitions is found adequate to describe the general kinetic trends of carbon condensation, as described by the rate equations. Such physical phenomena and processes as the coagulation, nucleation, growth, and Ostwald ripening are observed, and their dependence on various system parameters is studied and reported. It is believed that the present work will become useful when analyzing the present and future results for the kinetics of carbon condensation, obtained from experiments or atomistic simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Reversible CO 2 Hydrogenation, Neutron Crystallography, and Hydride Reactivity of a Triiridium Heptahydride Complex

Here, the authors report the structure, reactivity, and catalytic utility of a triiridium complex, [Ir 3 H 6 (μ 3 -H)(PN) 3 ] 2+ (2-H, PN = (2-pyridyl)CH 2 PBu t 2 ). Despite its unusual stability to unsaturated organics, electrophiles, and even CF 3 SO 3 D, they find that complex 2-H catalyzes hydrogenation of CO 2 to formate (TON Ir = 9600) and reverse formic acid dehydrogenation (TON Ir = 54 400). The hydrogenation operates via a reactive intermediate [Ir 3 H 4 (μ-H) 4 (PN) 3 ] + (5). Neutron crystallography and DFT-supported neutron vibrational spectroscopy of 2-H reveal Ir─H bond lengths and elucidate the vibration modes within the Ir 3 H 7 core. Stoichiometric oxidation of 2-H produces four classes of iridium complexes of varied nuclearity and hydride structure: tetra- and pentanuclear clusters [Ir 3 H 6 (μ 3 -AuPPh 3 )(PN) 3 ] 2+ (2-Au) and [Ag{Ir 2 H 4 (μ-OAc)(PN) 2 } 2 ] 3+ (6) are generated using AuPPh 3 + and AgOAc, respectively. Further oxidation to class [Ir 2 H 3 (μ-X) 2 (PN) 2 ] + is possible with AgOAc, Hg(OAc) 2 , or I 2 . Finally, a TEMPO/HCl system completely oxidizes the hydrides and gives [Ir 2 Cl 4 (μ-Cl) 2 (PN) 2 ] (11).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗