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At least 145 records · Page 8

Understanding the Effect of Single Atom Cationic Defect Sites in an Al 2 O 3 (012) Surface on Altering Selenate and Sulfate Adsorption: An Ab Initio Study

Adsorption is a promising under-the-sink selenate remediation technique for distributed water systems. Recently it was shown that adsorption induced water network rearrangement control adsorption energetics on the α-Al 2 O 3 (012) surface. Here, we aim to elucidate the relative importance of the water network effects and surface cation identity on controlling selenate and sulfate adsorption energy using density functional theory calculations. Density functional theory (DFT) calculations predicted the adsorption energies of selenate and sulfate on nine transition metal cations (Sc–Cu) and two alkali metal cations (Ga and In) in the α-Al 2 O 3 (012) surface under simulated acidic and neutral pH conditions. We find that the water network effects had a larger impact on the adsorption energy than the cationic identity. However, cation identity secondarily controlled adsorption. Most cations decreased the adsorption energy, weakening the overall performance, the larger Sc and In cations enabled inner-sphere adsorption in acidic conditions because they relaxed outward from the surface, providing more space for adsorption. Additionally, only Ti induced Se selectivity over S by reducing the adsorbing selenate to selenite but not reducing the sulfate. Altogether, this study indicates that tuning water network structure will likely have a larger impact than tuning cation–selenate interactions for increasing adsorbate effectiveness.

Adsorption↗

Spectral-partitioned Kohn-Sham density functional theory

Here we introduce a general, variational scheme for systematic approximation of a given Kohn-Sham free-energy functional by partitioning the density matrix into distinct spectral domains, each of which may be spanned by an independent diagonal representation without requirement of mutual orthogonality. It is shown that by generalizing the entropic contribution to the free energy to allow for independent representations in each spectral domain, the free energy becomes an upper bound to the exact (unpartitioned) Kohn-Sham free energy, attaining this limit as the representations approach Kohn-Sham eigenfunctions. A numerical procedure is devised for calculation of the generalized entropy associated with spectral partitioning of the density matrix. The result is a powerful framework for Kohn-Sham calculations of systems whose occupied subspaces span multiple energy regimes. As a case in point, we apply the proposed framework to warm- and hot-dense matter described by finite-temperature density functional theory, where at high energies the density matrix is represented by that of the free-electron gas, while at low energies it is variationally optimized. We derive expressions for the spectral-partitioned Kohn-Sham Hamiltonian, atomic forces, and macroscopic stresses within the projector-augmented wave (PAW) and the norm-conserving pseudopotential methods. It is demonstrated that at high temperatures, spectral partitioning facilitates accurate calculations at dramatically reduced computational cost. Moreover, as temperature is increased, fewer exact Kohn-Sham states are required for a given accuracy, leading to further reductions in computational cost. Finally, it is shown that standard multiprojector expansions of electronic orbitals within atomic spheres in the PAW method lack sufficient completeness at high temperatures. Spectral partitioning provides a systematic solution for this fundamental problem.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multiconfiguration Pair-Density Functional Theory for Vertical Excitation Energies in Actinide Molecules

Modeling actinides with electronic structure theories is challenging because these systems present a strong ligand field and metal–ligand covalency. Here, we systematically investigate the effectiveness of pair-density functional theory (PDFT) for the calculation of vertical excitation energies in An(III), [An III Cl 6 ] 3– , and [An VI O 2 ] 2+ (An = U, Np, Pu, and Am). We compare the performance of PDFT, hybrid PDFT, and multistate PDFT with traditional active-space methods followed by perturbation theory, like multistate CASPT2, and with experimental data. Overall, multistate PDFT gives quantitative agreement with multistate CASPT2 at a significantly reduced computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atom Equivalent Energies for the Rapid Estimation of the Heat of Formation of Explosive Molecules from Density Functional Tight Binding Theory

Atom equivalent energies have been derived from which the gas-phase heat of formation of explosive molecules can be estimated from fast, semiempirical density functional tight binding total energy calculations. The root-mean-square deviation and maximum deviation of the heats of formation from the experimental values for the set of 45 energetic molecules compiled by Byrd and Rice [ J. Phys. Chem. A, 2006, 110, 1005–1013] are 10.4 and 25.5 kcal/mol, respectively, using 4 atom equivalent energies and 7.4 and 15.0 kcal/mol, respectively, using 7 atom equivalent energies. These errors are around a factor of 2–3 larger than those obtained from density functional theory calculations but are smaller than those obtained from other semiempirical electronic structure methods. Heats of formation calculated with density functional tight binding theory using the 4 and 7 atom equivalent energies, the Byrd and Rice scheme, and the atom pair contribution method for a new set of 531 energetic molecules that contain only carbon, hydrogen, nitrogen, and oxygen are provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Formation energy puzzle in intermetallic alloys: Random phase approximation fails to predict accurate formation energies

We performed density functional calculations to estimate the formation energies of intermetallic alloys. We used two semilocal approximations, the generalized gradient approximation (GGA) by Perdew-Burke- Ernzerhof (PBE) and the strongly constrained and appropriately normed (SCAN) meta-GGA. In addition, we utilized two nonlocal DFT functionals, the hybrid HSE06, and the state-of-the-art random phase approximation (RPA). The nonlocal functionals such as HSE06 and RPA yield accurate formation energies of binary alloys with completely-filled d-band metals, where semilocal functionals underperform. The accuracy at the nonlocal functionals is greatly reduced when a partially-filled d-band metal is present in an alloy, while PBE-GGA outperforms in these cases. We show that the accurate prediction of formation energies by any DFT method depends on its ability to predict the accurate electronic properties, e.g., valence d-band contribution to the density of states (DOS). The SCAN meta-GGA often corrects the PBE-DOS, however, it does not provide accurate formation energies compared to PBE. This is assumed to be due to the lack of proper error cancellation that should be expected due to the similar bulk nature of both alloys and their constituents, which may improve with the modification of meta-GGA ingredients. RPA yields too negative formation energies of alloys with partially-filled d-band metals. RPA results can be corrected by restoring the exchange-correlation kernel, thereby improving the short-range electron-electron correlation in metallic densities.

36 MATERIALS SCIENCE↗

Toward Quantum Chemical Free Energy Simulations of Platinum Nanoparticles on Titania Support

Platinum nanoparticles (Pt-NPs) supported on titania surfaces are costly but indispensable heterogeneous catalysts because of their highly effective and selective catalytic properties. Therefore, it is vital to understand their physicochemical processes during catalysis to optimize their use and to further develop better catalysts. However, simulating these dynamic processes is challenging due to the need for a reliable quantum chemical method to describe chemical bond breaking and bond formation during the processes but, at the same time, fast enough to sample a large number of configurations required to compute the corresponding free energy surfaces. Density functional theory (DFT) is often used to explore Pt-NPs; nonetheless, it is usually limited to some minimum-energy reaction pathways on static potential energy surfaces because of its high computational cost. In this work, we report a combination of the density functional tight binding (DFTB) method as a fast but reliable approximation to DFT, the steered molecular dynamics (SMD) technique, and the Jarzynski equality to construct free energy surfaces of the temperature-dependent diffusion and growth of platinum particles on a titania surface. In particular, we present the parametrization for Pt-X (X = Pt, Ti, or O) interactions in the framework of the second-order DFTB method, using a previous parametrization for titania as a basis. The optimized parameter set was used to simulate the surface diffusion of a single platinum atom (Pt 1 ) and the growth of Pt 6 from Pt 5 and Pt 1 on the rutile (110) surface at three different temperatures (T = 400, 600, 800 K). The free energy profile was constructed by using over a hundred SMD trajectories for each process. We found that increasing the temperature has a minimal effect on the formation free energy; nevertheless, it significantly reduces the free energy barrier of Pt atom migration on the TiO 2 surface and the transition state (TS) of its deposition. In a concluding remark, the methodology opens the pathway to quantum chemical free energy simulations of Pt-NPs’ temperature-dependent growth and other transformation processes on the titania support.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis and visualization of energy densities. II. Insights from linear-response time-dependent density functional theory calculations

Inspired by the analysis of Kohn–Sham energy densities by Nakai and coworkers, we extended the energy density analysis to linear-response time-dependent density functional theory (LR-TDDFT) calculations. Using ethylene–tetrafluoroethylene and oxyluciferin–water complexes as examples, distinctive distribution patterns were demonstrated for the excitation energy densities of local excitations (within a molecular fragment) and charge-transfer excitations (between molecular fragments). It also provided a simple way to compute the effective energy of both hot carriers (particle and hole) from charge-transfer excitations via an integration of the excitation energy density over the donor and acceptor grid points.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Development of Density Functional Tight-Binding Parameters Using Relative Energy Fitting and Particle Swarm Optimization

We provide a strategy to optimize density functional tight-binding (DFTB) parameterization for the calculation of the structures and properties of organic molecules consisting of hydrogen, carbon, nitrogen, and oxygen. We utilize an objective function based on similarity measurements and the Particle Swarm Optimization (PSO) method to find an optimal set of parameters. This objective function considers not only the common DFTB descriptors of binding energies and atomic forces but also incorporates relative energies of isomers into the fitting procedure for more chemistry-driven results. The quality in the description of the binding energies and atomic forces is measured based on the Ballester similarity index and relative energies through a similarity index induced by the Levenshtein edit distance to quantify the correct energetic order of isomers. Training and testing datasets were created to include all relevant chemical functional groups. Finally, the accuracy of this strategy is assessed, and its range of applicability is discussed by comparison against our previous parameterization. The improved performance of the new DFTB parameterization is validated with respect to the density functional theory large datasets QM-9 and ANI-1, where excellent agreement is found between the structures and properties available in these datasets, and the ones obtained with DFTB.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fast Emulation of Expensive Simulations using Approximate Gaussian Processes [Slides]

Nuclear Computational Low-Energy Initiative (NUCLEI) collaboration uses Density Functional Theory (DFT) simulations to predict the structure and binding energies of nuclei over a wide range of proton (Z) and neutron (N) numbers. The DFT simulations utilize a particular parameterization of a Skyrme energy density functional called UNEDF1 which depends on 12 free parameters that must be fit to data (M Kortelainen et al 2014). Fitting involves comparing (e.g.) predicted binding energies of nuclei to experimentally measured values. We use only binding energies as observables, but DFT with UNEDF1 will predict structure (shape) observables as well. In this work, assessing the capability of approximate GP emulators to balance emulator accuracy with computational speed to facilitate improved UNEDF1 calibration. Sparse GPs are straightforward to train and accurate. Calibration is not straightforward with MCMC (using MH or HMC/NUTS). We produced reusable software for continuing and building on this work as well as accessing and using Darwin cluster compute resources

97 MATHEMATICS AND COMPUTING↗

Polymorphous nature of cubic halide perovskites

Many common crystal structures can be described by a single (or very few) repeated structural motif (“monomorphous structures”) such as octahedron in cubic halide perovskites. Interestingly, recent accumulated evidence suggests that electronic structure calculations based on such macroscopically averaged monomorphous cubic ($\textit{Pm} – 3m$) halide perovskites obtained from x-ray diffraction, show intriguing deviations from experiment. These include systematically too small band gaps, dielectric constants dominated by the electronic, negative mixing enthalpy of alloys, and significant deviations from the measured pair distribution function. We show here that a minimization of the systems $\textit{T}$ = 0 internal energy via density functional theory reveals a distribution of different low-symmetry local motifs, including tilting, rotations, and B-atom displacements (“polymorphous networks”). This is found only if one allows for larger-than-minimal cell size that does not geometrically exclude low symmetry motifs. As the (super) cell size increases, the energy is lowered relative to the monomorphous cell, and stabilizes after ~32 formula units (≥160 atoms) are included. Being a result of nonthermal energy minimization in the internal energy without entropy, this correlated set of displacements must represent the intrinsic geometry preferred by the underlying chemical bonding (lone pair bonding), and as such has a different origin than the normal, dynamic thermal disorder modeled by molecular dynamics. Indeed, the polymorphous network, not the monomorphous ansatz, is the kernel structure from which high temperature thermal agitation develops. The emerging physical picture is that the polymorphous network has an average structure with high symmetry, yet the local structural motifs have low symmetries. In this work we find that, compared with monomorphous counterparts, the polymorphous networks have significantly lower predicted total energies, larger band gaps, and ionic dominated dielectric constants, and agree much more closely with the observed pair distribution functions. An analogous polymorphous situation is found in the paraelectric phase of a few cubic oxide perovskites where local polarization takes the role of local displacements in halide perovskites, and in the paramagnetic phases of a few 3 d oxides where the local spin configuration takes that role.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Machine Learning Accelerated First-Principles Study of the Hydrodeoxygenation of Propanoic Acid

The complex reaction network of catalytic biomass conversions often involves hundreds of surface intermediates and thousands of reaction steps, greatly hindering the rational design of metal catalysts for these conversions. Here, we present a framework of machine learning (ML)-accelerated first-principles studies for the hydrodeoxygenation (HDO) of propanoic acid over transition metal surfaces. The microkinetic model (MKM) is initially parametrized by ML-predicted energies and iteratively improved by identifying the rate-determining species and steps (RDS), computing their energies by density functional theory (DFT), and reparameterizing the MKM until all the RDS are computed by DFT. The Gaussian process (GP) model performs significantly better than the linear ridge regression model for predicting both the adsorption free energies and transition state free energies. Parameterized with energies from the GP model, only 5–20% of the full reaction network has to be computed by DFT for the MKM to possess DFT-level accuracy for the TOF and dominant reaction pathway. While the linear ridge regression model performs worse than the GP model, its performance is greatly improved when only transition states are predicted by the regression model and adsorption energies are computed by DFT. Overall, we find that a high accuracy in adsorption free energies is more important for a reliable MKM than a high accuracy in TS free energies. Lastly, based on the GP model with GOH and GCHCHCO as catalyst descriptors, we build two-dimensional volcano plots in activity and selectivity that can help design promising alloy catalysts for HDO reactions of organic acids.

adsorption↗

Helical Organic and Inorganic Polymers

Despite being a staple of synthetic plastics and biomolecules, helical polymers are scarcely studied with Gaussian-basis-set ab initio electron-correlated methods on an equal footing with molecules. This article introduces an ab initio second-order many-body Green’s-function [MBGF(2)] method with nondiagonal, frequency-dependent Dyson self-energy for infinite helical polymers using screw-axis-symmetry-adapted Gaussian-spherical-harmonics basis functions. Together with the Gaussian-basis-set density-functional theory for energies, analytical atomic forces, translational-period force, and helical-angle force, it can compute correlated energy, quasiparticle energy bands, structures, and vibrational frequencies of an infinite helical polymer, which smoothly converge at the corresponding oligomer results. These methods can handle incommensurable structures, which have an infinite translational period and are hard to characterize by any other method, just as efficiently as commensurable structures. We apply them to polyethylene (2/1 helix), polyacetylene (Peierls’ system), and polytetrafluoroethylene (13/6 helix) to establish the quantitative accuracy of MBGF(2)/cc-pVDZ in simulating their (angle-resolved) ultraviolet photoelectron spectra, and of B3LYP/cc-pVDZ or 6-31G** in reproducing their structures, infrared and Raman band positions, phonon dispersions, and (coherent and incoherent) inelastic neutron scattering spectra. We then predict the same properties for infinitely catenated chains of nitrogen or oxygen and discuss their possible metastable existence under ambient conditions. They include planar zigzag polyazene (N2)x (Peierls’ system), 11/3-helical isotactic polyazane (NH)x, 9/4-helical isotactic polyfluoroazane (NF)x, and 7/2-helical polyoxane (O)x as potential high-energy-density materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unconventional Error Cancellation Explains the Success of Hartree–Fock Density Functional Theory for Barrier Heights

Energy barriers, which control the rates of chemical reactions, are seriously underestimated by computationally efficient semilocal approximations for the exchange-correlation energy. The accuracy of a semilocal density functional approximation is strongly boosted for reaction barrier heights by evaluating that approximation non-self-consistently on Hartree–Fock electron densities, which has been known for ~30 years. Here, the conventional explanation is that the Hartree–Fock theory yields the more accurate density. This work presents a benchmark Kohn–Sham inversion of accurate coupled-cluster densities for the reaction H 2 + F → HHF → H + HF and finds a strong, understandable cancellation between positive (excessively overcorrected) density-driven and large negative functional-driven errors (expected from stretched radical bonds in the transition state) within this Hartree–Fock density functional theory. This confirms earlier conclusions (Kaplan, A. D., et al. J. Chem. Theory Comput. 2023, 19, 532–543) based on 76 barrier heights and three less reliable, but less expensive, fully nonlocal density functional proxies for the exact density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Density functional thermodynamic description of spin, phonon and displacement degrees of freedom in antiferromagnetic-to-paramagnetic phase transition in YNiO 3

This work herein demonstrates a direct density functional description of the finite-temperature thermodynamic properties of solids exhibiting phase transitions through positional and spin symmetry breaking degrees of freedom. A classic example addressed here is the rare-earth (R) nickelates RNiO 3 where the ground state is characterized by crystallographic and magnetic (e.g., antiferromagnetic) long-range order (LRO), whereas the higher temperature paramagnetic phase manifests a range of local spin and positional symmetry breaking motifs with short-range order (SRO). Unlike time-dependent simulations of spin and positional degrees of freedom, in the present work, phases are described via a superposition of static configurations constructed by populating a periodic base lattice supercell allowing for the formation of energy lowing distribution of positional and spin local motifs. The thermal populations of the configurations in such a superposition phase are obtained from the energy-minimized Density Functional Theory (DFT)-calculated partition functions at different temperatures. This approach offers flexible inclusion of different physical contributions to the free energy, such as elastic, electronic and phonon free energies, all obtained from the same underlying DFT total energy calculations of periodic structures. The thermodynamic and magnetic properties of both LRO and SRO crystallographic and spin phases, including antiferromagnetic (AFM) to paramagnetic (PM) Néel phase transition in YNiO3 are studied. Including spin and phonon contributions, we find a DFT-calculated Néel temperature to be 144 K in satisfactory agreement with the experimental value of 145 K; whereas omitting the phonon contribution, one obtains a Néel temperature of 81 K. We present phonon contributions to the DFT-calculated temperature-dependent SRO, heat capacities, and the polymorphous distribution of nonzero local magnetic moments in the PM phase. This approach thus extends to finite temperatures the symmetry-broken DFT description of both the AFM and PM phases, demonstrating that a thermodynamic superposition approach based on symmetry broken configurations evaluated by a mean-field like DFT is sufficient to obtain a consistent description of the thermal physics of the AFM, PM phases and their interconversion in 3d oxides illustrated by YNiO 3 .

36 MATERIALS SCIENCE↗

Imposing correct jellium response is key to predict the density response by orbital-free DFT

Orbital-free density functional theory constitutes a computationally highly effective tool for modeling electronic structures of systems ranging from room-temperature materials to warm dense matter. Its accuracy critically depends on the employed kinetic energy (KE) density functional, which has to be supplied as an external input. In this work we consider several nonlocal and Laplacian-level KE functionals and use an external harmonic perturbation to compute the static density response at T = 0 K in the linear and beyond-linear response regimes. We test for the satisfaction of exact conditions in the limit of uniform densities and for how approximate KE functionals reproduce the density response of realistic materials (e.g., Al and Si) against the Kohn-Sham DFT reference, which employs the exact KE. The results illustrate that several functionals violate exact conditions in the uniform electron gas (UEG) limit. We find a strong correlation between the accuracy of the KE functionals in the UEG limit and in the strongly inhomogeneous case. This empirically demonstrates the importance of imposing the limit of UEG response for uniform densities and validates the use of the Lindhard function in the formulation of kernels for nonlocal functionals. This conclusion is substantiated by additional calculations for bulk aluminum (Al) with a face-centered cubic (fcc) lattice and silicon (Si) with an fcc lattice, body-centered cubic (bcc) lattice, and semiconducting crystal diamond state. The analysis of fcc Al, and fcc as well as bcc Si data follows closely the conclusions drawn for the UEG, allowing us to extend our conclusions to realistic systems that are subject to density inhomogeneities induced by ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enhancing high-fidelity neural network potentials through low-fidelity sampling

The efficacy of neural network potentials (NNPs) critically depends on the quality of the configurational datasets used for training. Prior research using empirical potentials has shown that well-selected liquid–solid transitional configurations of a metallic system can be translated to other metallic systems. This study demonstrates that such validated configurations can be relabeled using density functional theory (DFT) calculations, thereby enhancing the development of high-fidelity NNPs. Training strategies and sampling approaches are efficiently assessed using empirical potentials and subsequently relabeled via DFT in a highly parallelized fashion for high-fidelity NNP training. Our results reveal that relying solely on energy and force for NNP training is inadequate to prevent overfitting, highlighting the necessity of incorporating stress terms into the loss functions. To optimize training involving force and stress terms, we propose employing transfer learning to fine-tune the weights, ensuring that the potential surface is smooth for these quantities composed of energy derivatives. This approach markedly improves the accuracy of elastic constants derived from simulations in both empirical potential-based NNPs and relabeled DFT-based NNPs. Overall, this study offers significant insights into leveraging empirical potentials to expedite the development of reliable and robust NNPs at the DFT level.

97 MATHEMATICS AND COMPUTING↗

Enhanced Sulfur Dioxide Adsorption in UiO-66 Through Crystal Engineering and Chalcogen Bonding

Adsorption of corrosive SO 2 gas occurs in metal–organic frameworks (MOFs) including UiO-66. Improvements in SO 2 capacity is obtained through the incorporation of residual modulators in the UiO-66 framework by introducing new binding sites in the material, through residual modulators. Four residual modulators were investigated (acetic acid, trifluoroacetic acid, 3-DMAP acid, cyanoacetic acid), and the UiO-66 framework modulated with cyanoacetic acid exhibited nearly twice the SO 2 uptake for the 18:1 modulator/linker synthesis ratio compared with other modulated UiO-66 structures. Density functional theory investigations confirmed that targeted host–guest interactions were maintained after the modulator was incorporated into the framework. The strongest binding energy was between SO 2 and cyanoacetic acid, consistent with dynamic SO 2 adsorption data, and identified contributions from both the SO 2 reacting with the residual modulator and the coordinating linkers. The successful increase in dynamic SO 2 capacity illustrates how often-overlooked non-covalent interactions can be used in targeted adsorption applications. Further investigation into weak electrostatic interactions for adsorption properties is also needed to advance the potential selectivity and capacity in the adsorption sphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing the Performance of Exchange‐Correlation Density Functionals in Describing the Iron‐Catalyzed Ammonia Synthesis System

Density functional theory (DFT) has been widely employed for elucidating mechanistic aspects of heterogeneous catalysis. However, the accuracy of DFT calculations relies heavily on selecting an exchange-correlation (XC) functional that correctly describes the electronic structure of materials involved in the reactions. This study assesses the accuracy of several XC density functionals for modeling the iron-catalyzed ammonia synthesis system. In the assessment of functional accuracy, experimental references are compared to DFT-calculated values for the formation energy of gas-phase ammonia and nitrogen, bulk Fe/Fe-nitride (γ′-Fe 4 N) lattice constants and cohesive/formation energies, and nitrogen and ammonia binding energies on Fe(100), Fe(111), Fe(110), and γ′-Fe 4 N(111). It is observed that the experimental value for each of these descriptors is accurately modeled by at least one functional. RPBE alone provides reliable estimates for both the lattice constant and cohesive energy of Fe and γ′-Fe 4 N. Temperature-programmed desorption experiments led to estimates for N and NH 3 adsorption across several Fe-based facets that are best captured by RPBE. These results highlight the importance of choosing an appropriate XC functional that accurately describes experimental systems and offer insights into effectively modeling the interactions between nitrogen and ammonia on Fe-based surfaces.

adsorption↗