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CP2K: An Electronic Structure and Molecular Dynamics Software Package - Quickstep: Efficient and Accurate Electronic Structure Calculations

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular and biological systems. It is especially aimed at massively-parallel and linear-scaling electronic structure methods and state-of-the-art ab-initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension. TDK has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 716142). VRR has been supported by the Swiss National Science Foundation in the form of Ambizione grant No. PZ00P2 174227 and RZK by the Natural Sciences and Engineering Research Council of Canada (NSERC) through Discovery Grants (RGPIN-2016-0505). GKS and CJM are supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. UK based work was funded under the embedded CSE programme of the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk), grants eCSE03-011, eCSE06-6, eCSE08-9, eCSE13-17 and the EPSRC (EP/P022235/1) grant “Surface and Interface Toolkit for the Materials Chemistry Community". Computational resources were provided by the Swiss National Supercomputing Centre (CSCS) and Compute Canada. The generous allocation of computing time on the FPGA-based supercomputer “Noctua" at PC2 is kindly acknowledged.

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GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗

Nuclear Resonance Vibrational Spectroscopy Definition of O 2 Intermediates in an Extradiol Dioxygenase: Correlation to Crystallography and Reactivity

The extradiol dioxygenases are a large subclass of mononuclear nonheme Fe enzymes that catalyze the oxidative cleavage of catechols distal to their OH groups. These enzymes are important in bioremediation, and there has been significant interest in understanding how they activate O 2 . The extradiol dioxygenase homoprotocatechuate 2,3-dioxygenase (HPCD) provides an opportunity to study this process, as two O 2 intermediates have been trapped and crystallographically defined using the slow substrate 4-nitrocatechol (4NC): a side-on Fe–O 2 –4NC species and a Fe–O 2 –4NC peroxy bridged species. Also with 4NC, two solution intermediates have been trapped in the H200N variant, where H200 provides a second-sphere hydrogen bond in the wild-type enzyme. While the electronic structure of these solution intermediates has been defined previously as Fe III -superoxo-catecholate and Fe III -peroxy-semiquinone, their geometric structures are unknown. Nuclear resonance vibrational spectroscopy (NRVS) is an important tool for structural definition of nonheme Fe–O 2 intermediates, as all normal modes with Fe displacement have intensity in the NRVS spectrum. In this study, NRVS is used to define the geometric structure of the H200N–4NC solution intermediates in HPCD as an end-on Fe III -superoxo-catecholate and an end-on Fe III -hydroperoxo-semiquinone. Parallel calculations are performed to define the electronic structures and protonation states of the crystallographically defined wild-type HPCD–4NC intermediates, where the side-on intermediate is found to be a Fe III -hydroperoxo-semiquinone. The assignment of this crystallographic intermediate is validated by correlation to the NRVS data through computational removal of H200. While the side-on hydroperoxo semiquinone intermediate is computationally found to be nonreactive in peroxide bridge formation, it is isoenergetic with a superoxo catecholate species that is competent in performing this reaction. In conclusion, this study provides insight into the relative reactivities of Fe III -superoxo and Fe III -hydroperoxo intermediates in nonheme Fe enzymes and into the role H200 plays in facilitating extradiol catalysis.

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Optimization of Thermal Conductance at Interfaces Using Machine Learning Algorithms

We report optimization of thermal transport across the interface of two different materials is critical to micro-/nanoscale electronic, photonic, and phononic devices. Although several examples of compositional intermixing at the interfaces having a positive effect on interfacial thermal conductance (ITC) have been reported, an optimum arrangement has not yet been determined because of the large number of potential atomic configurations and the significant computational cost of evaluation. On the other hand, computation-driven materials design efforts are rising in popularity and importance. Yet, the scalability and transferability of machine learning models remain as challenges in creating a complete pipeline for the simulation and analysis of large molecular systems. In this work we present a scalable Bayesian optimization framework, which leverages dynamic spawning of jobs through the Message Passing Interface (MPI) to run multiple parallel molecular dynamics simulations within a parent MPI job to optimize heat transfer at the silicon and aluminum (Si/Al) interface. We found a maximum of 50% increase in the ITC when introducing a two-layer intermixed region that consists of a higher percentage of Si. Because of the random nature of the intermixing, the magnitude of increase in the ITC varies. We observed that both homogeneity/heterogeneity of the intermixing and the intrinsic stochastic nature of molecular dynamics simulations account for the variance in ITC.

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MBX V1.2: Accelerating Data-Driven Many-Body Molecular Dynamics Simulations

The MBX software provides an advanced platform for molecular dynamics simulations, leveraging state-of-the-art MB-pol and MB-nrg data-driven many-body potential energy functions. Developed over the past decade, these potential energy functions integrate physics-based and machine-learned many-body terms trained on electronic structure data calculated at the "gold standard" coupled-cluster level of theory. Recent advancements in MBX have focused on optimizing its performance, resulting in the release of MBX v1.2. While the inherently many-body nature of MB-pol and MB-nrg ensures high accuracy, it poses computational challenges. MBX v1.2 addresses these challenges with significant performance improvements, including enhanced parallelism that fully harnesses the power of modern multicore CPUs. In conclusion, these advancements enable simulations on nanosecond time scales for condensed-phase systems, significantly expanding the scope of high-accuracy, predictive simulations of complex molecular systems powered by data-driven many-body potential energy functions.

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Computational investigation on tunable optical band gap in armchair polyacenes

Polyacenes in their armchair geometry (phenacenes) have recently been found to possess appealing electronic and optical properties with higher chemical stability and comparatively larger band gap as compared to linear polyacenes. They also behave as high-temperature superconductors upon alkali metal doping. Moreover, the optical properties of crystalline picene can be finely tuned by applying external pressure. We investigated the variation of optical gap as a function of altering the interplanar distances between parallel cofacial phenacene dimers. We employed both time-dependent density functional theory and density matrix renormalization group (DMRG) technique to investigate the lowest singlet excitations in phenacene dimer. Our study showed that the lowest singlet excitation in these systems evolved as a function of interplanar separation. The optical excitation energy gap decreases as a function of inverse interplanar separation of the phenacene dimer. The distant dependent variation of optical absorption at the dimer level may be comparable with experimental observation in picene crystal under pressure. DMRG study also demonstrates that besides picene, electronic properties of higher phenacenes can also be tunable by altering interplanar separation.

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Boosting Photoelectric Conductivity in Porphyrin-Based MOFs Incorporating C 60

Electronic structure calculations show that guest C60 in the porphyrin-containing metal organic frameworks Zn 2 (TCPB)(DA-ZnP) (DA-MOF; H 4 TCPB = 1,2,4,5-tetrakis(4-carboxyphenyl)benzene, DA-ZnP = [5,15-bis[(4-pyridyl)ethynyl]-10,20-diphenylporphinato]zinc(II)) and Zn 2 (TCPB)(F-ZnP) (F-MOF; F-ZnP = [5,15-di(4-pyridyl)-10,20-bis(pentafluorophenyl)porphinato]zinc(II)) engenders high photoelectrical conductivity due to efficient donor–acceptor charge-transfer (CT) interactions. Structural modifications at the meso position of the porphyrin influence the preferred positions of C 60 within the frameworks, giving rise to host–guest interactions with different anisotropic structural, electronic, and optoelectronic properties. A preferred slipped-parallel π-stacked interaction of C 60 that is predicted for NH 2 -substituted DA-MOF and F-MOF fosters strong CT transitions and lowers band gaps by ~1.0 eV compared to the pristine DA-MOF and F-MOF. Hopping rates computed using Marcus theory are found to be anisotropic and accelerated by multiple orders of magnitude across π-stacked interfaces created by C 60 incorporation, a consequence of strong electronic coupling between initial and final diabatic states. Calculations indicate that photoinduced electron transfer, as well as direct CT from porphyrin to C 60 upon irradiation, triggers a charge separation process that leads to the formation of what should be long-lived electron-trapped states at the heterojunctions. Lastly, design principles revealed here for the control of photophysical and electron-transfer processes will be useful for constructing new MOF-derived visible- and infrared-based optoelectronics.

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GPU acceleration of rank-reduced coupled-cluster singles and doubles

Here, we have developed a graphical processing unit (GPU) accelerated implementation of our recently introduced rank-reduced coupled-cluster singles and doubles (RR-CCSD) method. RR-CCSD introduces a low-rank approximation of the doubles amplitudes. This is combined with a low-rank approximation of the electron repulsion integrals via Cholesky decomposition. The result of these two low-rank approximations is the replacement of the usual fourth-order CCSD tensors with products of second- and third-order tensors. In our implementation, only a single fourth-order tensor must be constructed as an intermediate during the solution of the amplitude equations. Owing in large part to the compression of the doubles amplitudes, the GPU-accelerated implementation shows excellent parallel efficiency (95% on eight GPUs). Our implementation can solve the RR-CCSD equations for up to 400 electrons and 1550 basis functions—roughly 50% larger than the largest canonical CCSD computations that have been performed on any hardware. In addition to increased scalability, the RR-CCSD computations are faster than the corresponding CCSD computations for all but the smallest molecules. We test the accuracy of RR-CCSD for a variety of chemical systems including up to 1000 basis functions and determine that accuracy to better than 0.1% error in the correlation energy can be achieved with roughly 95% compression of the ov space for the largest systems considered. We also demonstrate that conformational energies can be predicted to be within 0.1 kcal mol -1 with efficient compression applied to the wavefunction. Finally, we find that low-rank approximations of the CCSD doubles amplitudes used in the similarity transformation of the Hamiltonian prior to a conventional equation-of-motion CCSD computation will not introduce significant errors (on the order of a few hundredths of an electronvolt) into the resulting excitation energies.

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Multireference Ab Initio Studies of Magnetic Properties of Terbium-Based Single-Molecule Magnets

Here, we explore how different chemical environments influence magnetic properties of terbium(III) (Tb)-based single-molecule magnets (SMMs), using first-principles relativistic multireference methods. Recent experiments showed that Tb-based SMMs can have exceptionally large magnetic anisotropy and that they can be used for experimental realization of quantum information applications, with a judicious choice of chemical environment. Here, we perform complete active space self-consistent field calculations including relativistic spin–orbit interaction for representative Tb-based SMMs such as TbPc 2 and TbPcNc in three charge states. We calculate the low-energy electronic structure from which we compute the Tb crystal-field (CF) parameters and construct an effective pseudospin Hamiltonian. Our calculations show that the ligand type and fine points of molecular geometry do not affect the gap between the ground-state and first-excited doublets, whereas the latter varies weakly with oxidation number. On the other hand, higher-energy levels have a strong dependence on all these characteristics. For neutral TbPc 2 and TbPcNc molecules, the Tb magnetic moment and ligand spin are parallel to each other and the coupling strength between them does not depend much on the ligand type and details of the atomic structure. However, ligand distortion and molecular symmetry play a crucial role in transverse CF parameters which lead to tunnel splitting. The tunnel splitting induces quantum tunneling of magnetization by itself or by combining with other processes. Our results provide insights into the mechanisms of magnetization relaxation in the representative Tb-based SMMs.

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The benzene⋯naphthalene complex: A more challenging system than the benzene dimer for newly developed computational methods

High-level coupled cluster singles, doubles, and perturbative triples [CCSD(T)] computations with up to the aug-cc-pVQZ basis set (1924 basis functions) and various extrapolations toward the complete basis set (CBS) limit are presented for the sandwich, T-shaped, and parallel-displaced benzene⋯naphthalene complex. Using the CCSD(T)/CBS interaction energies as a benchmark, the performance of some newly developed wave function and density functional theory methods has been evaluated. The best performing methods were found to be the dispersion-corrected PBE0 functional (PBE0-D3) and spin-component scaled zeroth-order symmetry-adapted perturbation theory (SCS-SAPT0). The success of SCS-SAPT0 is very encouraging because it provides one method for energy component analysis of π-stacked complexes with 200 atoms or more. Most newly developed methods do, however, overestimate the interaction energies. The results of energy component analysis show that interaction energies are overestimated mainly due to the overestimation of dispersion energy.

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Oxygen Vacancies Alter Methanol Oxidation Pathways on NiOOH

A thorough comprehension of the mechanism underlying the methanol oxidation reaction (MOR) on Ni-based catalysts is critical for future electrocatalytic design and development. However, the mechanism of MOR on these materials remains a matter of controversy. Herein, we combine in situ surface-enhanced infrared absorption spectroscopy (SEIRAS) and density functional theory (DFT) calculations to identify the active sites and determine the mechanism of MOR on monometallic Ni-based catalysts in alkaline media. The SEIRAS results show that formate and (bi)carbonate are formed after the commencement of the MOR with potential-dependent relative distributions. These spectroscopic results are in good agreement with the DFT-computed reaction profiles over an oxygen vacancy, suggesting that the MOR mainly proceeds through the formate-involving pathway, in which the early consumption of methanol yields formate as the major product, while increasing potential drives further oxidation of formate to (bi)carbonate. We also find a parallel pathway for the generation of (bi)carbonate at high potentials that bypasses the formation of formate. The two main pathways are thermodynamically more feasible than the one predominantly reported in the literature for MOR on NiOOH that involves CHO and/or CO as key intermediates. These DFT results are supported by spectroscopic evidence showing that no band associated with CHO or CO can be detected by SEIRAS, which is attributed to the nature of the oxygen vacancies as the active sites, suppressing deep dehydrogenation of CH 2 O to CHO. Furthermore, this work thus shows the promising role of defect engineering in promoting the electrocatalytic MOR activity and selectivity.

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Assessing MP2 frozen natural orbitals in relativistic correlated electronic structure calculations

The high computational scaling with the basis set size and the number of correlated electrons is a bottleneck limiting applications of coupled cluster algorithms, in particular for calculations based on two- or four-component relativistic Hamiltonians, which often employ uncontracted basis sets. This problem may be alleviated by replacing canonical Hartree–Fock virtual orbitals by natural orbitals (NOs). Here, in this paper, we describe the implementation of a module for generating NOs for correlated wavefunctions and, in particular, second order Møller–Plesset perturbation frozen natural orbitals (MP2FNOs) as a component of our novel implementation of relativistic coupled cluster theory for massively parallel architectures [Pototschnig et al. J. Chem. Theory Comput. 17, 5509, (2021)]. Our implementation can manipulate complex or quaternion density matrices, thus allowing for the generation of both Kramers-restricted and Kramers-unrestricted MP2FNOs. Furthermore, NOs are re-expressed in the parent atomic orbital (AO) basis, allowing for generating coupled cluster singles and doubles NOs in the AO basis for further analysis. By investigating the truncation errors of MP2FNOs for both the correlation energy and molecular properties—electric field gradients at the nuclei, electric dipole and quadrupole moments for hydrogen halides HX (X = F–Ts), and parity-violating energy differences for H 2 Z 2 (Z = O–Se)—we find MP2FNOs accelerate the convergence of the correlation energy in a roughly uniform manner across the Periodic Table. It is possible to obtain reliable estimates for both energies and the molecular properties considered with virtual molecular orbital spaces truncated to about half the size of the full spaces.

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Self-Assembly and Critical Aggregation Concentration Measurements of ABA Triblock Copolymers with Varying B Block Types: Model Development, Prediction, and Validation

The dissipative particle dynamics (DPD) simulation technique is a coarse-grained (CG) molecular dynamics-based approach that can effectively capture the hydrodynamics of complex systems while retaining essential information about the structural properties of the molecular species. An advantageous feature of DPD is that it utilizes soft repulsive interactions between the beads, which are CG representation of groups of atoms or molecules. In this study, we used the DPD simulation technique to study the aggregation characteristics of ABA triblock copolymers in aqueous medium. Pluronic polymers (PEG-PPO-PEG) were modeled as two segments of hydrophilic beads and one segment of hydrophobic beads. Tyrosine-derived PEG 5K -b-oligo(desaminotyrosyl tyrosine octyl ester-suberate)-b-PEG 5K (PEG5K-oligo(DTO-SA)-PEG 5K ) block copolymers possess alternate rigid and flexible components along the hydrophobic oligo(DTO-SA) chain, and were modeled as two segments of hydrophilic beads and one segment of hydrophobic, alternate soft and hard beads. The formation, structure, and morphology of the initial aggregation of the polymer molecules in aqueous medium were investigated by following the aggregation dynamics. The dimensions of the aggregates predicted by the computational approach were in good agreement with corresponding results from experiments, for the Pluronic and PEG 5K -oligo(DTO-SA)-PEG 5K block copolymers. In addition, DPD simulations were utilized to determine the critical aggregation concentration (CAC), which was compared with corresponding results from an experimental approach. For Pluronic polymers F68, F88, F108, and F127, the computational results agreed well with experimental measurements of the CAC measurements. For PEG 5K -b-oligo(DTO-SA)-b-PEG 5K block polymers, the complexity in polymer structure made it difficult to directly determine their CAC values via the CG scheme. Therefore, we determined CAC values of a series of triblock copolymers with 3–8 DTO-SA units using DPD simulations, and used these results to predict the CAC values of triblock copolymers with higher molecular weights by extrapolation. In parallel, a PEG 5K -b-oligo(DTO-SA)-b-PEG 5K block copolymer was synthesized, and the CAC value was determined experimentally using the pyrene method. The experimental CAC value agreed well with the CAC value predicted by simulation. Furthermore, these results validate our CG models, and demonstrate an avenue to simulate and predict aggregation characteristics of ABA amphiphilic triblock copolymers with complex structures.

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Experiments and computations of microfluidic liquid–liquid flow patterns

We study two-phase liquid–liquid flow patterns in a 500 μm capillary microchannel for four biphasic systems: ethyl acetate/water, 2-pentanol/water, methyl isobutyl ketone/water, and heptane/water. Flow visualization experiments using laser induced fluorescence (LIF) reveal a total of 7 different flow patterns for all solvent pairs, namely slug flow, droplet flow, slug-droplet flow, parallel, annular, dispersed, and irregular flow. A map of different flow patterns was built to delineate the origin of their formation. We find conventional dimensionless groups are insufficient to uniquely identify the flow patterns. Computational fluid dynamics (CFD) modeling in OpenFOAM shows agreement with the experimental flow patterns for most of the two-phase flows. Principal component analysis reduces the dimensionality of potential descriptors of flow patterns and, unlike prior work using two dimensionless numbers, determines six important features that describe >95% of the variance of the experimental flow patterns. These include the total flow rate, the flow rate ratio between the two phases, the capillary and Ohnesorge numbers of the aqueous phase, and the Weber number and velocity of the organic phase. Lastly, we build a decision-tree model to further regress the data and identify the critical features and demonstrate an accuracy in predicting the flow patterns of up to 93%.

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Theoretical study of the CO 2 –O 2 van der Waals complex: potential energy surface and applications

A four-dimensional-potential energy surface (4D-PES) of the atmospherically relevant carbon dioxide–oxygen molecule (CO 2 –O 2 ) van der Waals complex is mapped using the ab initio explicitly correlated coupled cluster method with single, double, and perturbative triple excitations (UCCSD(T)-F12b), and extrapolation to the complete basis set (CBS) limit using the cc-pVTZ-F12/cc-pVQZ-F12 bases and the l –3 formula. An analytic representation of the 4D-PES was fitted using the method of interpolating moving least squares (IMLS). These calculations predict that the most stable configuration of CO 2 –O 2 complex corresponds to a planar slipped-parallel structure with a binding energy of V ~ –243 cm –1 . Another isomer is found on the PES, corresponding to a non-planar cross-shaped structure, with V ~ –218 cm –1 . The transition structure connecting the two minima is found at V ~ –211 cm –1 . We also performed comparisons with some CO 2 –X van der Waals complexes. Moreover, we provide a SAPT analysis of this molecular system. Then, we discuss the complexation induced shifts of CO 2 and O 2 . Afterwards, this new 4D-PES is employed to compute the second virial coefficient including temperature dependence. A comparison between quantities obtained in our calculations and those from experiments found close agreement attesting to the high quality of the PES and to the importance of considering a full description of the anisotropic potential for the derivation of thermophysical properties of CO 2 –O 2 mixtures.

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Dissociative chemisorption of methane on metal surfaces: Tests of dynamical assumptions using quantum models and ab initio molecular dynamics

The dissociative chemisorption of methane on metal surfaces is of great practical and fundamental importance. Not only is it the rate-limiting step in the steam reforming of natural gas, the reaction exhibits interesting mode-selective behavior and a strong dependence on the temperature of the metal. We present a quantum model for this reaction on Ni(100) and Ni(111) surfaces based on the reaction path Hamiltonian. The dissociative sticking probabilities computed using this model agree well with available experimental data with regard to variation with incident energy, substrate temperature, and the vibrational state of the incident molecule. We significantly expand the vibrational basis set relative to earlier studies, which allows reaction probabilities to be calculated for doubly excited initial vibrational states, though it does not lead to appreciable changes in the reaction probabilities for singly excited initial states. Sudden models used to treat the center of mass motion parallel to the surface are compared with results from ab initio molecular dynamics and found to be reasonable. Similar comparisons for molecular rotation suggest that our rotationally adiabatic model is incorrect, and that sudden behavior is closer to reality. Such a model is proposed and tested. A model for predicting mode-selective behavior is tested, with mixed results, though we find it is consistent with experimental studies of normal vs. total (kinetic) energy scaling. Models for energy transfer into lattice vibrations are also examined.

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Zr 6 O 8 Node-Catalyzed Butene Hydrogenation and Isomerization in the Metal–Organic Framework NU-1000

Zirconium-based metal–organic frameworks (Zr-MOFs) have been increasingly studied over the past two decades as heterogeneous catalysts due to their synthetic tunability, well-defined nature, and chemical stability. In contrast to traditional zirconia-based heterogeneous catalysts, the community has assumed that Zr-MOFs are inert catalyst supports that do not participate directly in hydrocarbon transformations, such as olefin hydrogenation and isomerization. Here, we report that the Zr-MOF NU-1000 is capable of catalyzing olefin hydrogenation and isomerization, without any postsynthetic modifications, under a hydrogen atmosphere. We probe H 2 activation over the nodes of NU-1000 via spectroscopic and computational techniques revealing that H 2 dissociation can occur heterolytically across coordinatively unsaturated Zr sites and proximal hydroxide and μ3-oxo ligands. These results, along with catalytic experiments, suggest that H 2 activation results in node-supported zirconium hydrides capable of the hydrogenation and isomerization of 1-butene. When examining rate dependence on the partial pressure of H 2 , we observe first-order dependence for hydrogenation and half-order dependence for isomerization. Half-order H 2 rate dependence is consistent with a mechanism where both fragments of cleaved H 2 are active for 1-butene isomerization, suggesting that heterolytic cleavage generates acidic protons resulting in parallel, acid-, and hydride-catalyzed isomerization pathways. In conclusion, this work shows that Zr-MOFs have more diverse reactivity than the current literature may suggest and opens possibilities for ways in which Zr-MOFs can be used as heterogeneous catalysts and supports.

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