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At least 1,297 records · Page 72

MoS 2 -supported Au 31 for CO hydrogenation: A first-principle study

While the basal plane of single-layer molybdenum disulphide (MoS 2 ) is inert, attempts have been made to functionalize it chemically through the creation of defects and/or addition of dopants. With nanoparticles as dopants, the authors present density functional theory-based calculations of the hydrogenation of CO on a 31-atom, bilayer Au cluster supported on single-layer MoS 2 (Au31/MoS 2 ). Not surprisingly, the adsorption and reaction of all species involved in the hydrogenation occur at the edges of the cluster—the regions at which the interaction between MoS 2 and the Au cluster is tracked to be the strongest. The authors find two possible mechanisms that lead to the formation of methanol: (1) CO* → CHO* → CH 2 O* → CH 3 O* → CH 3 OH* and (2) CO* → CHO* → HCOH* → CH2OH* → CH3OH*, where * indicates the adsorbed species. Detailed analysis of the reaction pathways, however, does not result in favoring one mechanism over the other. Rather, both mechanisms are facile. In addition, the rate-limiting step in each mechanism is found to be the formation of the formyl radical group (CO* + H* → CHO*).

2D materials↗

Determining reference standard strength for neutron-irradiated reduced activation ferritic/martensitic steel F82H by Bayesian method

The deterministic approach widely adopted in the design of structural components relies on systematically defined design limits using empirically determined safety factors. However, this approach is not always appropriate because structures are subjected to a variety of loads in the practical environment, which may result in excessively conservative design limits. In recent years, a more rigorous probabilistic approach that incorporates material strength distributions has become an important solution. In the probabilistic approach, the probability density functions of material strength properties underpin the design criteria. Here, the objective of this study is to identify the density distribution functions that best describe tensile properties of irradiated F82H to define a reference strength for DEMO design. Due to the limited number of existing data, this study specifically employs a Bayesian prediction method based on Monte Carlo simulations to determine a material reference value with statistical reliability and to investigate its effectiveness. For example, the dependence of tensile properties of 300 °C irradiated materials on irradiation damage and the range predicted by 95% Bayesian estimation was evaluated. As a statistical model for the dose dependence of statistical parameters, the normal distribution exhibited a better fit for 0.2% proof strength and tensile strength, whereas the distribution of total elongation data gave comparable reference values for both the normal and Weibull distribution models. Both models gave comparable criteria for the distribution of total elongation data. The Weibull model also gave better results for uniform elongation. The function best describing the model was a logarithmic law for both 0.2% proof strength and tensile strength, while a power law for both total and uniform elongation, which allowed for more comprehensive data prediction of irradiation data with statistical accuracy for DEMO reactor design.

36 MATERIALS SCIENCE↗

Demonstration of an x-ray Raman spectroscopy setup to study warm dense carbon at the high energy density instrument of European XFEL

We present a proof-of-principle study demonstrating x-ray Raman Spectroscopy (XRS) from carbon samples at ambient conditions in conjunction with other common diagnostics to study warm dense matter, performed at the high energy density scientific instrument of the European x-ray Free Electron Laser (European XFEL). We obtain sufficient spectral resolution to identify the local structure and chemical bonding of diamond and graphite samples, using highly annealed pyrolytic graphite spectrometers. Due to the high crystal reflectivity and XFEL brightness, we obtain signal strengths that will enable accurate XRS measurements in upcoming pump–probe experiments with a high repetition-rate, where the samples will be pumped with high-power lasers. Molecular dynamics simulations based on density functional theory together with XRS simulations demonstrate the potential of this technique and show predictions for high-energy-density conditions. Our setup allows simultaneous implementation of several different diagnostic methods to reduce ambiguities in the analysis of the experimental results, which, for warm dense matter, often relies on simplifying model assumptions. The promising capabilities demonstrated here provide unprecedented insights into chemical and structural dynamics in warm dense matter states of light elements, including conditions similar to the interiors of planets, low-mass stars, and other celestial bodies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Early Career: First-Principles Tools for Nonadiabatic Attosecond Dynamics in Materials

The overarching goal of this project was to develop computer tools for predicting how electrons move in molecules and solids at the attosecond (billionth-of-a-billionth of a second) time scale, during and after interaction with intense and/or high energy laser light. An associated goal was to also determine how X-ray spectroscopy could be used as a probe of these dynamics. The project resulted in multiple methodology developments that allow for these processes to be simulated from first-principles, most notably the use of small bulk-mimicking clusters to model solids and fixes for a deficiency in a commonly used method (time-dependent density functional theory). Additionally, the simulations showed that X-ray absorption peaks can be directly related to the electron density above the absorbing atom, and can thus be used as an intuitive probe of "where the electrons are" at a given time in the system. Collectively, these tools and results expected to be valuable for predicting and interpreting future attosecond experiments, especially for X-ray pump/probe studies at free-electron laser facilities.

74 ATOMIC AND MOLECULAR PHYSICS↗

Plasma-catalyst modeling for materials selection: challenges and opportunities in nitrogen oxidation

Reliable kinetic models are essential to rationalize observations and to guide the selection of appropriate plasma-catalyst combinations. Kinetic models coupling plasma- and heterogeneous-catalytic-chemistries, however, are primitive. Here, we combine reduced plasma chemistries and density functional theory parameterized surface reactions to model NO formation from N2 oxidation, an alternative nitrogen fixation process. We first show plasma excited species can enhance turnover frequencies of both Pt and Au. The enhancing potential is a function of plasma species and their densities. We then compare NO production between plasma/Pt and plasma/Au with an integral reactor model and explore the dependence of NO production as a function of plasma conditions, reactor configurations and chemical compositions. Plasma/Pt generates more NO than plasma/Au under most thermal and plasma parametric conditions. Plasma/Au outperforms plasma/Pt under high plasma excitations at low temperatures. Furthermore, these results highlight that selection of plasma-catalyst combinations should consider the properties of plasmas, materials and the coupling of the two.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Assessment of DFT functionals for a minimal nitrogenase [Fe(SH) 4 H]- model employing state-of-the-art ab initio methods

We have designed a [Fe(SH)4H]- model with the fifth proton binding either to Fe or S. We show that the energy difference between these two isomers (ΔE) is hard to estimate with quantum-mechanical (QM) methods. For example, different density functional theory (DFT) methods give ΔE estimates that vary by almost 140 kJ/mol, mainly depending on the amount of exact Hartree–Fock included (0%–54%). The model is so small that it can be treated by many high-level QM methods, including coupled-cluster (CC) and multiconfigurational perturbation theory approaches. With extrapolated CC series (up to fully connected coupled-cluster calculations with singles, doubles, and triples) and semistochastic heat-bath configuration interaction methods, we obtain results that seem to be converged to full configuration interaction results within 5 kJ/mol. Our best result for ΔE is 101 kJ/mol. With this reference, we show that M06 and B3LYP-D3 give the best results among 35 DFT methods tested for this system. Brueckner doubles coupled cluster with perturbaitve triples seems to be the most accurate coupled-cluster approach with approximate triples. CCSD(T) with Kohn–Sham orbitals gives results within 4–11 kJ/mol of the extrapolated CC results, depending on the DFT method. Single-reference CC calculations seem to be reasonably accurate (giving an error of ~5 kJ/mol compared to multireference methods), even if the D1 diagnostic is quite high (0.25) for one of the two isomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DFT and microkinetic comparison of Pt, Pd and Rh-catalyzed ammonia oxidation

Ammonia oxidation is the heart of the Ostwald process and is important in emissions control. Catalytic behaviors are a function of conditions and are observed to vary across the platinum group metals (PGMs) Pt, Pd, Rh. Here, we combine density functional theory computations and microkinetic modeling to rationalize these dependencies. We compute reactions over model (2 1 1) and (1 1 1) surfaces of PGMs. Binding energies are similar on Pd and Pt and generally greater on Rh, while activation energies vary across all metals. Rates on (2 1 1) surfaces are greater than (1 1 1) surfaces. Additionally, the stepped Pt is most active and stepped Rh most selective to N 2 at ammonia slip conditions, while at Ostwald process conditions, stepped Pd is most active and stepped Pt most selective to NO. Degree of rate and selectivity control analysis provides insights into the reactions limiting performance of PGMs. Both activation barriers and surface coverages influence rates and selectivities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing the stability of Pd-exchanged sites in zeolites with the aid of a high throughput quantum chemistry workflow

Abstract Cation exchanged-zeolites are functional materials with a wide range of applications from catalysis to sorbents. They present a challenge for computational studies using density functional theory due to the numerous possible active sites. From Al configuration, to placement of extra framework cation(s), to potentially different oxidation states of the cation, accounting for all these possibilities is not trivial. To make the number of calculations more tractable, most studies focus on a few active sites. We attempt to go beyond these limitations by implementing a workflow for a high throughput screening, designed to systematize the problem and exhaustively search for feasible active sites. We use Pd-exchanged CHA and BEA to illustrate the approach. After conducting thousands of explicit DFT calculations, we identify the sites most favorable for the Pd cation and discuss the results in detail. The high throughput screening identifies many energetically favorable sites that are non-trivial. Lastly, we employ these results to examine NO adsorption in Pd-exchanged CHA, which is a promising passive NO x adsorbent (PNA) during the cold start of automobiles. The results shed light on critical active sites for NO x capture that were not previously studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coexistence of Dirac fermion and charge density wave in the square-net-based semimetal LaAuSb 2

Here, we report a comprehensive study of magnetotransport properties, angle-resolved photoemission spectroscopy (ARPES), and density functional theory (DFT) calculations on self-flux grown LaAuSb 2 single crystals. Resistivity and Hall measurements reveal a charge density wave (CDW) transition at 77 K. MR and de Haas-Van Alphen (dHvA) measurements indicate that the transport properties of LaAuSb 2 are dominated by Dirac fermions that arise from Sb square nets. ARPES measurements and DFT calculations reveal an electronic structure with a common feature of the square-net-based topological semimetals, which is in good agreement with the magnetotransport properties. Our results indicate the coexistence of CDW and Dirac fermion in LaAuSb 2 , both of which are linked to the bands arising from the Sb-square net, suggesting that the square net could serve as a structural motif to explore various electronic orders.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

How Does HF-DFT Achieve Chemical Accuracy for Water Clusters?

Bolstered by recent calculations of exact functional-driven errors (FEs) and density-driven errors (DEs) of semilocal density functionals in the water dimer binding energy , we investigate approximate FEs and DEs in neutral water clusters containing up to 20 monomers, charged water clusters, and alkali- and halide-water clusters. Our proxy for the exact density is r 2 SCAN 50, a 50% global hybrid of exact exchange with r 2 SCAN, which may be less correct than r 2 SCAN for the compact water monomer but importantly more correct for long-range electron transfers in the noncompact water clusters. We show that SCAN makes substantially larger FEs for neutral water clusters than r 2 SCAN, while both make essentially the same DEs. Unlike the case for barrier heights, these FEs are small in a relative sense and become large in an absolute sense only due to an increase in cluster size. SCAN@HF, short for SCAN evaluated on the Hartree–Fock (HF) density, produces a cancellation of errors that makes it chemically accurate for predicting the absolute binding energies of water clusters. Likewise, adding a long-range dispersion correction to r 2 SCAN@HF, as in the composite method HF-r 2 SCAN-DC4, makes its FE more negative than in r 2 SCAN@HF, permitting a near-perfect cancellation of FE and DE. r 2 SCAN by itself (and even more so, r 2 SCAN evaluated on the r 2 SCAN 50 density), is almost perfect for the energy differences between water hexamers, and thus probably also for liquid water away from the boiling point. Thus, the accuracy of composite methods like SCAN@HF and HF-r 2 SCAN-DC4 is not due to the HF density being closer to the exact density, but to a compensation of errors from its greater degree of localization. We also give an argument for the approximate reliability of this unconventional error cancellation for diverse molecular properties. Lastly, we confirm this unconventional error cancellation for the SCAN description of the water trimer via Kohn–Sham inversion of the CCSD(T) density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tailoring the Electronic Structures and Spectral Properties of ZnO with Irradiation Defects Generated Under Intense Electronic Excitation: A Combined Experimental and DFT Approach

Here, the relationship between the composition of the internal defect states, spectral properties, and correlated electronic structures of wurtzite zinc oxide (ZnO) crystals under 645 MeV Xe 35+ irradiation is systematically investigated, employing experimental characterizations combined with first-principle calculations. Based on the ion irradiation-induced thermal expansion and relaxation processes, the high concentration of vacancy/interstitial defects produced from the transient disordered phase in molten track states trigger photoelectric changes, as follows: i) the generation of internal defect states effectively reduces the intrinsic bandgap (3.25 eV → 2.66 eV); ii) a large number of defective active sites inhibits the recombination between electron–hole pairs, causing dark conductance and photoconductance to increase with increasing damage levels until optimal fluence is achieved. Based on the density functional theory (DFT) with the GGA + U (GGA = generalized gradient approximation) method, the defective models associated with the different electronic structures, density of states, formation energy, and the nature of the chemical bonding are established. The narrowing of the bandgap observed experimentally and the enhancement of carrier concentration originating from the internal electron defect states are qualitatively verified, therefore laying the foundation for designing future nanoscale photoelectronic devices and microelectronics applications.

36 MATERIALS SCIENCE↗

P SI4 1.4: Open-source software for high-throughput quantum chemistry

PSI4 is a free and open-source ab initio electronic structure program providing implementations of Hartree–Fock, density functional theory, many-body perturbation theory, configuration interaction, density cumulant theory, symmetry-adapted perturbation theory, and coupled-cluster theory. Most of the methods are quite efficient, thanks to density fitting and multi-core parallelism. The program is a hybrid of C++ and Python, and calculations may be run with very simple text files or using the Python API, facilitating post-processing and complex workflows; method developers also have access to most of PSI4 's core functionalities via Python. Job specification may be passed using The Molecular Sciences Software Institute (MolSSI) QCSCHEMA data format, facilitating interoperability. We announce a rewrite of our top-level computation driver, and concomitant adoption of the MolSSI QCARCHIVE INFRASTRUCTURE project, makes the latest version of PSI4 well suited to distributed computation of large numbers of independent tasks. The project has fostered the development of independent software components that may be reused in other quantum chemistry programs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Semi-classical approximation description of static properties of nuclei

In this report, we present recent development in semi-classical description of static properties of nuclei. By employing the Wigner transform, we derive simple semiclassical approximations for evaluating properties of nuclear system. We present results of calculations of static properties, using the energy density functional associated with Skyrme effective nucleon–nucleon interaction. In particular, we consider properties of the Wigner distribution function, line of beta stability, Coulomb and symmetry energies, deformation energies, equation of state, nuclear radii, and single-particle level density.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nonparametric maximum likelihood estimation of probability densities by penalty function methods

When it is known a priori exactly to which finite dimensional manifold the probability density function gives rise to a set of samples, the parametric maximum likelihood estimation procedure leads to poor estimates and is unstable; while the nonparametric maximum likelihood procedure is undefined. A very general theory of maximum penalized likelihood estimation which should avoid many of these difficulties is presented. It is demonstrated that each reproducing kernel Hilbert space leads, in a very natural way, to a maximum penalized likelihood estimator and that a well-known class of reproducing kernel Hilbert spaces gives polynomial splines as the nonparametric maximum penalized likelihood estimates.

Demontricher, G. F.↗

Accurate Prediction of Adiabatic Ionization Potentials of Organic Molecules using Quantum Chemistry Assisted Machine Learning

In previous work (Dandu et al., J. Phys. Chem. A, 2022, 126, 4528–4536), we were successful in predicting accurate atomization energies of organic molecules using machine learning (ML) models, obtaining an accuracy as low as 0.1 kcal/mol compared to the G4MP2 method. In this work, we extend the use of these ML models to adiabatic ionization potentials on data sets of energies generated using quantum chemical calculations. Atomic specific corrections that were found to improve atomization energies from quantum chemical calculations have also been used in this study to improve ionization potentials. Here, the quantum chemical calculations were performed on 3405 molecules containing eight or fewer non-hydrogen atoms derived from the QM9 data set, using the B3LYP functional with the 6–31G(2df,p) basis set for optimization. Low-fidelity IPs for these structures were obtained using two density functional methods: B3LYP/6–31+G(2df,p) and ωB97XD/6–311+G(3df,2p). Highly accurate G4MP2 calculations were performed on these optimized structures to obtain high-fidelity IPs to use in ML models based on the low-fidelity IPs. Our best performing ML methods gave IPs of organic molecules within a mean absolute deviation of 0.035 eV from the G4MP2 IPs for the whole data set. This work demonstrates that ML predictions assisted by quantum chemical calculations can be used to successfully predict IPs of organic molecules for use in high throughput screening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion quantum Monte Carlo

We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility. The auxiliary field QMC (AFQMC) implementation has been greatly expanded to include k-point symmetries, tensor-hypercontraction, and accelerated graphical processing unit (GPU) support. These scaling and memory reductions greatly increase the number of orbitals that can practically be included in AFQMC calculations, increasing the accuracy. Advances in real space methods include techniques for accurate computation of bandgaps and for systematically improving the nodal surface of ground state wavefunctions. Results of these calculations can be used to validate application of more approximate electronic structure methods, including GW and density functional based techniques. To provide an improved foundation for these calculations, we utilize a new set of correlation-consistent effective core potentials (pseudopotentials) that are more accurate than previous sets; these can also be applied in quantum-chemical and other many-body applications, not only QMC. These advances increase the efficiency, accuracy, and range of properties that can be studied in both molecules and materials with QMC and QMCPACK.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Atomically Precise PdSe 2 Pentagonal Nanoribbons

We report atomically precise pentagonal PdSe 2 nanoribbons (PNRs) fabricated on a pristine PdSe 2 substrate with a hybrid method of top-down and bottom-up processes. The PNRs form a uniform array of dimer structure with a width of 2.4 nm and length of more than 200 nm. In situ four-probe scanning tunneling microscopy (STM) reveals metallic behavior of PNRs with ballistic transport for at least 20 nm in length. Density functional theory calculations produce a semiconducting density of states of isolated PNRs and find that the band gap narrows and disappears quickly once considering coupling between PNR stacking layers or interaction with the PdSe 2 substrate. The coupling of PNRs is further corroborated by Raman spectroscopy and field-effect transistor measurements. The facile method of fabricating atomically precise PNRs offers an air-stable functional material for dimensional control.

36 MATERIALS SCIENCE↗

Exploring the Structural, Dynamic, and Functional Properties of Metal–Organic Frameworks through Molecular Modeling

This review spotlights the role of atomic-level modeling in research on metal-organic frameworks (MOFs), especially the key methodologies of density functional theory (DFT), Monte Carlo (MC) simulations, and molecular dynamics (MD) simulations. The discussion focuses on how periodic and cluster-based DFT calculations can provide novel insights into MOF properties, with a focus on predicting structural transformations, understanding thermodynamic properties and catalysis, and providing information or properties that are fed into classical simulations such as force field parameters or partial charges. Classical simulation methods, highlighting force field selection, databases of MOFs for high-throughput screening, and the synergistic nature of MC and MD simulations, are described. By predicting equilibrium thermodynamic and dynamic properties, these methods offer a wide perspective on MOF behavior and mechanisms. Additionally, the incorporation of machine learning (ML) techniques into quantum and classical simulations is discussed. These methods can enhance accuracy, expedite simulation setup, reduce computational costs, as well as predict key parameters, optimize geometries, and estimate MOF stability. By charting the growth and promise of computational research in the MOF field, the aim is to provide insights and recommendations to facilitate the incorporation of computational modeling more broadly into MOF research.

36 MATERIALS SCIENCE↗