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At least 145 records · Page 8

Introducing LibXC into GAMESS (US)

The interface between LibXC and GAMESS (US), which enables the latter to perform calculations with >200 popular density functional approximations, including recently proposed r 2 SCAN, M06-SX and CAM-QTP00, is presented. The LibXC-GAMESS interface allows users to specify custom functionals as linear combinations of the present ones, exact exchange (producing hybrids) and MP2-correlation (producing double-hybrids).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Communication: xDH double hybrid functionals can be qualitatively incorrect for non-equilibrium geometries: Dipole moment inversion and barriers to radical-radical association using XYG3 and XYGJ-OS

Here, double hybrid (DH) density functionals are amongst the most accurate density functional approximations developed so far, largely due to the incorporation of correlation effects from unoccupied orbitals via second order perturbation theory (PT2). The xDH family of DH functionals calculate energy directly from orbitals optimized by a lower level approach like B3LYP, without self-consistent optimization. XYG3 and XYGJ-OS are two widely used xDH functionals that are known to be quite accurate at equilibrium geometries. Here, we show that the XYG3 and XYGJ-OS functionals can be ill behaved for stretched bonds well beyond the Coulson-Fischer point, predicting unphysical dipole moments and humps in potential energy curves for some simple systems like the hydrogen fluoride molecule. Numerical experiments and analysis show that these failures are not due to PT2. Instead, a large mismatch at stretched bond-lengths between the reference B3LYP orbitals and the optimized orbitals associated with the non-PT2 part of XYG3 leads to an unphysically large non-Hellman-Feynman contribution to first order properties like forces and electron densities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of self-interaction errors in density functional predictions of dipole polarizabilities and ionization energies of water clusters using Perdew-Zunger and locally scaled self-interaction corrected methods

Here, we studied the effects of self-interaction error (SIE) on the static dipole polarizabilities of water clusters modelled with three increasingly sophisticated, non-empirical density functional approximations (DFAs), viz. the local spin density approximation (LDA), the Perdew-Burke-Ernzherof (PBE) generalized-gradient approximation (GGA), and the strongly constrained and appropriately normed (SCAN) meta-GGA, using the Perdew-Zunger self-interaction-correction (PZ-SIC) energy functional in the Fermi-Lowdin orbital SIC (FLO-SIC) framework. Our results show that while all three DFAs overestimate the cluster polarizabilities, the description systematically improves from LDA to PBE to SCAN. The self-correlation free SCAN predicts polarizabilities quite accurately with a mean absolute error (MAE) of 0.58 Bohr 3 with respect to coupled cluster singles and doubles (CCSD) values. Removing SIE using PZ-SIC correctly reduces the DFA polarizabilities, but over-corrects, resulting in underestimated polarizabilities in SIC-LDA, -PBE, and -SCAN. Finally, we applied a recently proposed local-scaling SIC (LSIC) method using a quasi self-consistent scheme and using the kinetic energy density ratio as an iso-orbital indicator. The results show that the LSIC polarizabilities are in excellent agreement with mean absolute error of 0.08 Bohr 3 for LSIC-LDA and 0.06 Bohr 3 for LSIC-PBE with most recent CCSD polarizabilities. Likewise, the ionization energy estimates as an absolute of highest occupied energy eigenvalue predicted by LSIC are also in excellent agreement with CCSD(T) ionization energies with MAE of 0.4 eV for LSIC-LDA and 0.04 eV for LSIC-PBE. The LSIC-LDA predictions of ionization energies are comparable to the reported GW ionization energies while the LSIC-PBE ionization energies are more accurate than reported GW results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bridging the Homogeneous-Heterogeneous Divide: Modeling Spin for Reactivity in Single Atom Catalysis

Single atom catalysts (SACs) are emergent catalytic materials that have the promise of merging the scalability of heterogeneous catalysts with the high activity and atom economy of homogeneous catalysts. Computational, first-principles modeling can provide essential insight into SAC mechanism and active site configuration, where the sub-nm-scale environment can challenge even the highest-resolution experimental spectroscopic techniques. Nevertheless, the very properties that make SACs attractive in catalysis, such as localized d electrons of the isolated transition metal center, make them challenging to study with conventional computational modeling using density functional theory (DFT). For example, Fe/N-doped graphitic SACs have exhibited spin-state dependent reactivity that remains poorly understood. However, spin-state ordering in DFT is very sensitive to the nature of the functional approximation chosen. In this work, we develop accurate benchmarks from correlated wavefunction theory (WFT) for relevant octahedral complexes. We use those benchmarks to evaluate optimal DFT functional choice for predicting spin state ordering in small octahedral complexes as well as models of pyridinic and pyrrolic nitrogen environments expected in larger SACs. Using these guidelines, we determine Fe/N-doped graphene SAC model properties and reactivity as well as their sensitivities to DFT functional choice. Finally, we conclude with broad recommendations for computational modeling of open-shell transition metal single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Use of FLOSIC for understanding anion-solvent interactions

An Achille’s heel of lower-rung density-functional approximations is that the highest-occupied-molecular-orbital energy levels of anions, known to be stable or metastable in nature, are often found to be positive in the worst case or above the lowest-unoccupied-molecular-orbital levels on neighboring complexes that are not expected to accept charge. A trianionic example, [Cr(C2O4)3]3−, is of interest for constraining models linking Cr isotope ratios in rock samples to oxygen levels in Earth’s atmosphere over geological timescales. Here we describe how crowd sourcing can be used to carry out self-consistent Fermi–Löwdin–Orbital-Self-Interaction corrected calculations (FLOSIC) on this trianion in solution. The calculations give a physically correct description of the electronic structure of the trianion and water. In contrast, uncorrected local density approximation (LDA) calculations result in approximately half of the anion charge being transferred to the water bath due to the effects of self-interaction error. Use of group-theory and the intrinsic sparsity of the theory enables calculations roughly 125 times faster than our initial implementation in the large N limit reached here. By integrating charge density densities and Coulomb potentials over regions of space and analyzing core-level shifts of the Cr and O atoms as a function of position and functional, we unambiguously show that FLOSIC, relative to LDA, reverses incorrect solute-solvent charge transfer in the trianion-water complex. In comparison to other functionals investigated herein, including Hartree–Fock and the local density approximation, the FLOSIC Cr 1s eigenvalues provide the best agreement with experimental core ionization energies.

Chemistry↗

Structural and dynamic properties of solvated hydroxide and hydronium ions in water from ab initio modeling

Predicting the asymmetric structure and dynamics of solvated hydroxide and hydronium in water from ab initio molecular dynamics (AIMD) has been a challenging task. The difficulty mainly comes from a lack of accurate and efficient exchange–correlation functional in elucidating the amphiphilic nature and the ubiquitous proton transfer behaviors of the two ions. By adopting the strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation functional in AIMD simulations, we systematically examine the amphiphilic properties, the solvation structures, the electronic structures, and the dynamic properties of the two water ions. In particular, we compare these results to those predicted by the PBE0-TS functional, which is an accurate yet computationally more expensive exchange–correlation functional. We demonstrate that the general-purpose SCAN functional provides a reliable choice for describing the two water ions. Specifically, in the SCAN picture of water ions, the appearance of the fourth and fifth hydrogen bonds near hydroxide stabilizes the pot-like shape solvation structure and suppresses the structural diffusion, while the hydronium stably donates three hydrogen bonds to its neighbors. We apply a detailed analysis of the proton transfer mechanism of the two ions and find the two ions exhibit substantially different proton transfer patterns. In conclusion, our AIMD simulations indicate that hydroxide diffuses more slowly than hydronium in water, which is consistent with the experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Logical Activation Functions v.1.1

SAND2024-01501O Logical Activation Functions software is a PyTorch implementation from the paper, "Logical Activation Functions for Training Arbitrary Probabilistic Boolean Logic." The activation functions approximate logit-space marginalization of probabilistic truth tables from probabilistic interpretations of inputs. They also provide a general methodology to approximate logical relationships between abstract antecedents and consequents for machine learning architectures. They do not target any specific application or use-case. By training probabilistic truth tables, these activation functions can capture more expressive relationships in a neural network than typical elementwise activation functions. This code is only designed for a single compute node with a GPU and is limited to machine learning architectures than can fit within the memory of a single GPU. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Duersch, Jed↗

The effect of self-interaction error on electrostatic dipoles calculated using density functional theory

Spurious electron self-interaction in density functional approximations (DFAs) can lead to inaccurate predictions of charge transfer in heteronuclear molecules that manifest as errors in calculated electrostatic dipoles. Here we show the magnitude of these errors on dipoles computed for a diverse set of 47 molecules taken from the recent benchmark study of Hait and Head-Gordon. We compare results of Perdew-Wang local spin density approximation (PW92), Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA), and strongly constrained and appropriatedly normed (SCAN) meta-GGA dipole calculations, along with those of their respective self-interaction-corrected (SIC) counterparts, to reference values from accurate wave function-based methods. The SIC calculations were carried out using the Fermi-Löwdin orbital (FLO-SIC) approach. We find that correcting for self-interaction generally increases the degree of charge transfer, thereby increasing the size of calculated dipole moments. The FLO-SIC-PW92 and FLO-SIC-PBE dipoles are in better agreement with reference values than their uncorrected DFA counterparts, particularly for strongly ionic molecules where significant improvement is seen. Applying FLO-SIC to SCAN does not improve dipole values overall. In addition, we show that removing self-interaction improves the description of the dipole for stretched-bond geometries and recovers the physically correct separated atom limit of zero dipole. Finally, we find that the best agreement between the FLO-SIC-DFA and reference dipoles occurs when the molecular geometries are optimized using the FLO-SIC-DFA.

74 ATOMIC AND MOLECULAR PHYSICS↗

hp -VPINNs: Variational physics-informed neural networks with domain decomposition

We formulate a general framework for hp-variational physics-informed neural networks (hp-VPINNs) based on the nonlinear approximation of shallow and deep neural networks and hp-refinement via domain decomposition and projection onto the space of high-order polynomials. The trial space is the space of neural network, which is defined globally over the entire computational domain, while the test space contains piecewise polynomials. Specifically in this study, the hp-refinement corresponds to a global approximation with a local learning algorithm that can efficiently localize the network parameter optimization. Here, we demonstrate the advantages of hp-VPINNs in both accuracy and training cost for several numerical examples of function approximation and in solving differential equations.

42 ENGINEERING↗

Polarizable Frozen Density Embedding with External Orthogonalization

In this work, we report a polarizable subsystem density functional theory to describe electronic properties of molecules embedded on a metal cluster. Interaction between the molecule and metal cluster is described using frozen density embedding (FDE). Substituting the nonadditive kinetic potential (NAKP) by approximate functionals is circumvented by enforcing external orthogonality (EO) through a projection operator. The computationally expensive freeze/thaw (FT) cycles are bypassed by including a polarization term in the embedding operator. Furthermore, the combination of polarization and EO permits supermolecular basis set calculations, which was not possible for strongly interacting systems with existing kinetic energy functionals. To test the method, we described the ground state density of pyridine, water, and benzene on a silver cluster. Performing FT on top of EO results in exact density embedding for this category of systems and is thus used for benchmarking the method. We find that the density is reproduced to within 0.15e, and the dipole and quadrupole moments are within 18% of the reference points for subsystem separations ranging from bonding to noninteracting distances. Additionally, our formalism allows the flexibility of incorporating different density functionals to the molecular and the metallic subsystems reducing the overall computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Symmetry breaking and self-interaction correction in the chromium atom and dimer

Density functional approximations to the exchange–correlation energy can often identify strongly correlated systems and estimate their energetics through energy-minimizing symmetry-breaking. In particular, the binding energy curve of the strongly correlated chromium dimer is described qualitatively by the local spin density approximation (LSDA) and almost quantitatively by the Perdew–Burke–Ernzerhof generalized gradient approximation (PBE-GGA), where the symmetry breaking is antiferromagnetic for both. Here, we show that a full Perdew–Zunger self-interaction-correction (SIC) to LSDA seems to go too far by creating an unphysical symmetry-broken state, with effectively zero magnetic moment but non-zero spin density on each atom, which lies ~4 eV below the antiferromagnetic solution. A similar symmetry-breaking, observed in the atom, better corresponds to the 3d↑↑4s↑3d↓↓4s↓ configuration than to the standard 3d↑↑↑↑↑4s↑. For this new solution, the total energy of the dimer at its observed bond length is higher than that of the separated atoms. In conclusion, these results can be regarded as qualitative evidence that the SIC needs to be scaled down in many-electron regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data–driven and constrained optimization of semi–local exchange and nonlocal correlation functionals for materials and surface chemistry

Reliable predictions of surface chemical reaction energetics require an accurate description of both chemisorption and physisorption. Herein, we present an empirical approach to simultaneously optimize semi-local exchange and nonlocal correlation of a density functional approximation to improve these energetics. A combination of reference data for solid bulk, surface, and gas-phase chemistry and physical exchange-correlation model constraints leads to the VCML-rVV10 exchange-correlation functional. Owing to the variety of training data, the applicability of VCML-rVV10 extends beyond surface chemistry simulations. It provides optimized gas phase reaction energetics and an accurate description of bulk lattice constants and elastic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Weak Galerkin Method for the Reissner–Mindlin Plate in Primary Form

We developed a new finite element method for the Reissner–Mindlin equations in its primary form by using the weak Galerkin approach. Like other weak Galerkin finite element methods, this one is highly flexible and robust by allowing the use of discontinuous approximating functions on arbitrary shape of polygons and, at the same time, is parameter independent on its stability and convergence. Furthermore, error estimates of optimal order in mesh size h are established for the corresponding weak Galerkin approximations. Numerical experiments are conducted for verifying the convergence theory, as well as suggesting some superconvergence and a uniform convergence of the method with respect to the plate thickness.

97 MATHEMATICS AND COMPUTING↗

Study of the Thermal Neutron Spectrum of the W-Be Photoneutron Source of the INR RAS

The possibility of reconstructing the neutron flux density of a W-Be photoneutron source using neutron activation analysis of Ag, Mn, Fe, Mn, and Ti samples is considered. The use of simple functions as AE{sup –B}, describing particular regions of the spectrum, as a reconstruction option is discussed. The dependence of the deviation of the measured reaction rates on those calculated in this study on the parameters of approximating functions is investigated. The convergence of the reconstruction results is obtained by increasing the amount of experimental data. This reconstruction method can be used for the operational measurement of the thermal neutron flux density of the photoneutron source and for the optimization of the source parameters.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Construction of meta-GGA functionals through restoration of exact constraint adherence to regularized SCAN functionals

The strongly constrained and appropriately normed (SCAN) meta-GGA exchange–correlation functional is constructed as a chemical environment-determined interpolation between two separate energy densities: one describes single-orbital electron densities accurately and another describes slowly varying densities accurately. To conserve constraints known for the exact exchange–correlation functional, the derivatives of this interpolation vanish in the slowly varying limit. While theoretically convenient, this choice introduces numerical challenges that degrade the functional’s efficiency. We have recently reported a modification to the SCAN meta-GGA, termed restored-regularized-SCAN (r 2 SCAN) , that introduces two regularizations into SCAN, which improve its numerical performance at the expense of not recovering the fourth order term of the slowly varying density gradient expansion for exchange. Here, we show the derivation of a progression of density functional approximations [regularized SCAN (rSCAN), r++SCAN, r 2 SCAN, and r 4 SCAN] with increasing adherence to exact conditions while maintaining a smooth interpolation. The greater smoothness of r 2 SCAN seems to lead to better general accuracy than the additional exact constraint of SCAN or r 4 SCAN does.

, correlation energy↗

Adsorption and Recovery of Polyphenolic Flavonoids Using TiO 2 -Functionalized Mesoporous Silica Nanoparticles

Exploiting specific interactions with titania (TiO 2 ) has been proposed for the separation and recovery of a broad range of biomolecules and natural products, including therapeutic polyphenolic flavonoids which are susceptible to degradation, such as quercetin. Functionalizing mesoporous silica with TiO 2 has many potential advantages over bulk and mesoporous TiO 2 as an adsorbent for natural products, including robust synthetic approaches leading to high surface area, stable separation platforms. Here, TiO 2 surface functionalized mesoporous silica nanoparticles (MSNPs) are synthesized and characterized as a function of TiO 2 content (up to 636 mg TiO2/g). The adsorption isotherms of two polyphenolic flavonoids, quercetin and rutin, were determined (0.05-10 mg/ml in ethanol), and a 100-fold increase in the adsorption capacity was observed relative to functionalized nonporous particles with similar TiO 2 surface coverage. An optimum extent of functionalization (approximately 440 mg TiO 2 /g particles) is interpreted from characterization techniques including grazing incidence x-ray scattering (GIXS), high resolution transmission electron microscopy (HRTEM) and nitrogen adsorption, which examined the interplay between the extent of TiO 2 functionalization and the accessibility of the porous structures. The recovery of flavonoids is demonstrated using ligand displacement in ethanolic citric acid solution (20% w/v), in which greater than 90% recovery can be achieved in a multistep extraction process. The radical scavenging activity (RSA) of the recovered and particle-bound quercetin as measured by 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay demonstrates greater than 80% retention of antioxidant activity by both particle-bound and recovered quercetin. In conclusion, these mesoporous titanosilicate materials can serve as a synthetic platform to isolate, recover, and potentially deliver degradation-sensitive natural products to biological systems.

36 MATERIALS SCIENCE↗

Improvements in the orbitalwise scaling down of Perdew–Zunger self-interaction correction in many-electron regions

The Perdew-Zunger (PZ) method offers a way to remove the self-interaction (SI) error from density functional approximations on an orbital by orbital basis. The PZ method provides significant improvements for the properties such as barrier heights or dissociation energies but results in over-correcting the properties well described by SI-uncorrected semi-local functional. One cure to rectify the over-correcting tendency is to scale down the magnitude of SI-correction of each orbital in the many electron region. We have implemented the orbitalwise scaled down SI-correction (OSIC) scheme of Vydrov et al. [J. Chem. Phys. 124, 094108 (2006)] using the Fermi-L owdin SI-correction method. After validating the OSIC implementation with previously reported OSICLSDA results, we examine its performance with the most successful non-empirical SCAN meta-GGA functional. Using different forms of scaling factors to identify one-electron regions, we assess the performance of OSIC-SCAN for a wide range of properties: total energies, ionization potentials and electron affinities for atoms, atomization energies, dissociation and reaction energies, and reaction barrier heights of molecules. Our results show that OSIC-SCAN provides superior results than the previously reported OSIC-LSDA, -PBE, and -TPSS results. Furthermore, we propose selective scaling of OSIC (SOSIC) to remove its major shortcoming that destroys the -1/r asymptotic behavior of the potentials. The SOSIC method gives the highest occupied orbital eigenvalues practically identical to those in PZSIC and unlike OSIC provides bound atomic anions even with larger powers of scaling factors. Furthermore, SOSIC compared to PZSIC or OSIC provides more balanced description of total energies and barrier heights.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental Validation of Approximate Dynamic Programming Based Optimization and Convergence on Microgrid Applications

Stochastic optimization can better address uncertainties in power system problems. However, when state space and action space become large, many existing approaches become computationally expensive and even infeasible. Approximate dynamic programming (ADP) attracts researchers’ attention as a powerful tool for solving power system optimization problems with reduced computational cost. In this paper, in light of the existing literature, we investigate how the ADP approach with post-decision value function approximation converges to the nearly optimal solution with improved computational speed and experimentally validate the performance of the approach for a microgrid energy optimization problem. The approximation error versus the number of iteration is studied for convergence analysis of the post-decision ADP. A flowchart is provided to illustrate the proposed ADP algorithm for a microgrid energy optimization problem. The performance of ADP and dynamic programming (DP) is compared in terms of optimization error and computational time. It has found that the post-decision ADP approach can achieve competitive optimality with improved computational speed compared to the traditional DP.

Das, Avijit↗