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At least 307 records · Page 17

Study of self-interaction-errors in barrier heights using locally scaled and Perdew-Zunger self-interaction methods

We study the effect of self-interaction errors on the barrier heights of chemical reactions. For this purpose we use the well-known Perdew-Zunger [J. P. Perdew and A. Zunger, Phys. Rev. B,23, 5048 (1981)] self-interaction-correction(PZSIC), as well two variations of the recently developed, locally scaled self-interaction correction (LSIC) [Zope et al.,J. Chem. Phys.151, 214108 (2019)] to study the barrier heights of the BH76 benchmark dataset. Our results show that both PZSIC and especially the LSIC methods improve the barrier heights relative to the local density approximation(LDA). The version of LSIC that uses the iso-orbital indicator z as a scaling factor gives a more consistent improvement than an alternative version that uses an orbital-dependent factor based on the ratio of orbital densities to the total electron density. We show that LDA energies evaluated using the self-consistent and self-interaction-free PZSIC densities can be used to assess density-driven errors. Furthermore, the LDA reaction barrier errors for the BH76 set are found to contain significant density-driven errors for all types of reactions contained in the set, but the corrections due to adding SIC to the functional are much larger than those stemming from the density for the hydrogen transfer reactions and of roughy equal size for the non-hydrogen transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface Energies of LaMnO 3 High-Index Surfaces Obtained from Density-Functional Theory

Here, the first six cubic LaMnO 3 high-index surfaces, (210), (211), (221), (310), (311), and (320), are examined for the first time. The unrelaxed and relaxed surface energies of the surfaces are computed as a function of surface model thickness using unrelaxed and relaxed surface models, respectively. The (210), (320), (211), and (221) surfaces are found to be more stable than the low-index (011) and (111) surfaces. Helping to explain this result, the surface terminations of the (210), (320), (211), or (221) surface are seen to exhibit a rotational relaxation of the MnO 6 or oxygen octahedra extending from the surface into the bulk. By contrast, the relaxed surface energies of the (310) and (311) surfaces are concluded to be difficult to determine due to a structural transformation or phase change in the surface models of the surfaces away from cubic LaMnO 3 . The finding of a phase change is important. It indicates that a phase change in the surface models of a surface for another material could occur if the surface is relatively open and a different phase of the material is stable at low temperature. When modeling such a surface, two steps are suggested to be taken.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Density Matrix Implementation of the Fermi–Löwdin Orbital Self-Interaction Correction Method

The Fermi–Löwdin orbital self-interaction correction (FLOSIC) method effectively provides a transformation from canonical orbitals to localized Fermi–Löwdin orbitals which are used to remove the self-interaction error in the Perdew–Zunger (PZ) framework. This transformation is solely determined by a set of points in space, called Fermi–Löwdin descriptors (FODs), and the occupied canonical orbitals or the density matrix. In this work, we provide a detailed workflow for the implementation of the FLOSIC method for removal of self-interaction error in DFT calculations in an orbital-by-orbital basis that takes advantage of the unitary invariant nature of the FLOSIC method. In this way, it is possible to cast the self-consistent energy minimization at fixed FODs in the same manner than standard Kohn–Sham with one additional term in the Kohn–Sham Hamiltonian that introduces the PZ self-interaction correction. Each energy minimization iteration is divided in two substeps, one for the density matrix and one for the FODs. Expressions for the effective Kohn–Sham matrix and FOD gradients are provided such that its implementation is suitable for most electronic structure codes. Here, we analyze the convergence characteristics of the algorithm and present applications for the evaluation of NMR shielding constants and real-time time-dependent DFT simulations based on the Liouville–von Neumann equation to calculate excitation energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Investigation of a CO 2 Conversion Strategy via Diels–Alder Reaction in a Carbon Capture Solvent

Molecular-level insights into reactive separations are crucial for the design of new conversion pathways of carbon dioxide (CO 2 ). This work explores a postulated pathway that directs CO 2 to undergo inverse-electron-demand Diels–Alder reactions to produce heterocycles using the CO 2 chemically fixed on water-lean solvent molecules. Density functional theory calculations are applied to evaluate the lowest unoccupied molecular orbital (LUMO) energies of three types of reactants (1,3-butadiene, 1,3-cyclohexadiene, and 1,2,4,5-tetrazine) with various functional substituents. These calculations also provide a data set (5.8k data) for developing a machine learning model to efficiently predict LUMO energies. A computational screening of LUMO energies for an additional 47k diene and tetrazine candidates is performed, and a list of candidates with lowered LUMO energies by electron-withdrawing substituents is provided. These candidates are further examined by their reaction energy barriers computed from the interatomic potential or density functional theory. Two major energy barriers are identified, one for the proton transfer within the water-lean solvent and the other for the CO 2 transfer from the solvent molecule to the reactant candidate (diene or tetrazine). The functional substituents have a more significant impact on the second barrier but a very slight one on the first barrier. This exploratory work demonstrates a new possibility for guiding experimental efforts toward the chemical conversion of fixated CO 2 to value-added compounds.

Chemical reactions↗

Self-interaction-corrected Kohn–Sham effective potentials using the density-consistent effective potential method

Density functional theory (DFT) and beyond-DFT methods are often used in combination with photoelectron spectroscopy to obtain physical insights into the electronic structure of molecules and solids. The Kohn–Sham eigenvalues are not electron removal energies except for the highest occupied orbital. The eigenvalues of the highest occupied molecular orbitals often underestimate the electron removal or ionization energies due to the self-interaction (SI) errors in approximate density functionals. Here, we adapt and implement the density-consistent effective potential method of Kohut, Ryabinkin, and Staroverov (2014) to obtain SI-corrected local effective potentials from the SI-corrected Fermi–Löwdin orbitals and density in the Fermi–Löwdin orbital self-interaction correction scheme. The implementation is used to obtain the density of states (photoelectron spectra) and HOMO–LUMO gaps for a set of molecules and polyacenes. Good agreement with experimental values is obtained compared to a range of SI uncorrected density functional approximations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vibrational Entropy Contribution to Mixing Free Energy of Ni-Rich LiNi 1- y Co y O 2

First principles density-functional-theory calculations are performed of the mixing free energy of the layered oxide LiNi 1-y Co y O 2 , a model Li-ion-battery cathode material, at 1000 K. Analysis of internal energy, LN exchange, configurational entropy and vibrational entropy are combined to obtain the net mixing free energy. The vibrational entropy requires a more indirect treatment than the other terms; analysis based on heat capacity is presented here, to show that the vibrational entropy is of comparable magnitude to the configurational entropy, and it tends to promote solid-solution behavior in LiNi 1-y Co y O 2 .

25 ENERGY STORAGE↗

Analyzing barium titanate TiO2 surface interactions with tert-butylphosphonic acid using density functional theory

Abstract Barium titanate (BTO) is a widely researched ferroelectric useful for energy storage. While BTO’s surface chemistry is commonly studied using density functional theory, little has been published on the TiO2 surface. Here, we determined that BTO’s surface response can be decoupled from the ferroelectric response by using a pre-optimized ferroelectric slab and allowing only the top three atomic z-layers to respond to ligand binding. Multiple favorable binding modes were identified for hydrogen, hydroxyl, water, and tert-butyl phosphonic acid on BTO’s TiO 2 surface. Of these ligands, tBuPA dominates surface binding with binding energies as low as − 2.61 eV for its nine configurations. Graphical abstract

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parallelized Screening of Characterized and DFT-Modeled Bimetallic Colloidal Cocatalysts for Photocatalytic Hydrogen Evolution

Using a newly designed and developed parallelized photoreactor and colorimetric detection method, a large sampling of bimetallic co-catalysts (Pd/Sn, Pd/Mo, Pd/Ru, Pd/Pb, Pd/Ni, Ni/Sn, Mo/Sn and Pt/Sn) for photocatalytic water reduction have been tested in this work. Of these co-catalysts, the combination of palladium and tin showed the highest synergistic behavior and peak hydrogen gas production at a low relative fraction of palladium. The resulting Pd/Sn bimetallic co-catalysts were characterized using high-angle annular dark-field (HAADF) and scanning transmission electron microscopy energy dispersive X-ray spectroscopy (STEM-EDS), and specifically, investigation of the palladium/tin mixture indicated that palladium and tin elements reside within the same particle. The experimental catalytic activity for the palladium/tin mixture was compared to density functional theory-derived energy values associated with the adsorption of hydrogen onto a surface. This comparison demonstrated that the typical peak found in electrochemical Sabatier volcano plots at ΔG H* = ~0 eV was replicated in the experimental photocatalytic system with a peak activity observed at ΔG H* = -0.036 eV. Computational confirmation of the results expressed here demonstrates the efficacy of colorimetric detection of hydrogen in parallel and presents a model for increasingly rapid catalyst screening.

08 HYDROGEN↗

Understanding Hydrogenation Chemistry at MgB 2 Reactive Edges from Ab Initio Molecular Dynamics

Solid-state hydrogen storage materials often operate via transient, multistep chemical reactions at complex interfaces that are difficult to capture. Here, we use direct ab initio molecular dynamics simulations at accelerated temperatures and hydrogen pressures to probe the hydrogenation chemistry of the candidate material MgB 2 without a priori assumption of reaction pathways. Focusing on highly reactive ($10\overline{1}0$) edge planes where initial hydrogen attack is likely to occur, we track mechanistic steps toward the formation of hydrogen-saturated BH 4 – units and key chemical intermediates, involving H 2 dissociation, generation of functionalities and molecular complexes containing BH 2 and BH 3 motifs, and B–B bond breaking. Further, the genesis of higher-order boron clustering is also observed. Different charge states and chemical environments at the B-rich and Mg-rich edge planes are found to produce different chemical pathways and preferred speciation, with implications for overall hydrogenation kinetics. The reaction processes rely on B–H bond polarization and fluctuations between ionic and covalent character, which are critically enabled by the presence of Mg 2+ cations in the nearby interphase region. Our results provide guidance for devising kinetic improvement strategies for MgB 2 -based hydrogen storage materials, while also providing a template for exploring chemical pathways in other solid-state energy storage reactions.

08 HYDROGEN↗

Electronic structure factors and the importance of adsorbate effects in chemisorption on surface alloys

The chemisorption energy is an integral aspect of surface chemistry, central to numerous fields such as catalysis, corrosion, and nanotechnology. Electronic-structure-based methods such as the Newns-Anderson model are therefore of great importance in guiding the engineering of material surfaces with optimal properties. However, existing methods are inadequate for interpreting complex, multi-metallic systems. Herein, we introduce a physics-based chemisorption model for alloyed transition metal surfaces employing primarily metal d-band properties that accounts for perturbations in both the substrate and adsorbate electronic states upon interaction. Importantly, we show that adsorbate-induced changes in the adsorption site interact with its chemical environment leading to a second-order response in chemisorption energy with the d-filling of the neighboring atoms. We demonstrate the robustness of the model on a wide range of transition metal alloys with O, N, CH, and Li adsorbates yielding a mean absolute error of 0.13 eV versus density functional theory reference chemisorption energies.

36 MATERIALS SCIENCE↗

Modeling antiphase boundary energies of Ni 3 Al-based alloys using automated density functional theory and machine learning

Antiphase boundaries (APBs) are planar defects that play a critical role in strengthening Ni-based superalloys, and their sensitivity to alloy composition offers a flexible tuning parameter for alloy design. Here, we report a computational workflow to enable the development of sufficient data to train machine-learning (ML) models to automate the study of the effect of composition on the (111) APB energy in Ni 3 Al-based alloys. We employ ML to leverage this wealth of data and identify several physical properties that are used to build predictive models for the APB energy that achieve a cross-validation error of 0.033 J m –2 . We demonstrate the transferability of these models by predicting APB energies in commercial superalloys. Moreover, our use of physically motivated features such as the ordering energy and stoichiometry-based features opens the way to using existing materials properties databases to guide superalloy design strategies to maximize the APB energy.

36 MATERIALS SCIENCE↗

Interfacial Engineering Using Covalent Organic Frameworks in Polymer Composites for High‐Temperature Electrostatic Energy Storage

Abstract The use of inorganic nanofillers has been an effective method to improve high‐temperature capacitive performance of dielectric polymers, though there are unmet challenges such as undesirable organic–inorganic compatibility, and low efficiencies and energy densities. Herein, a surface functionalization strategy using covalent organic frameworks (COFs) is employed to address such challenges in realizing high‐performing polymer composites. Specifically, core–shell structured nanoparticles, where ZrO 2 nanoparticles act as the core and a COF material forms the shell, are constructed and composited with the polyetherimide (PEI) matrix. The design leverages the high electron affinity ( E A ) of the outer COF shell to create energy traps, thereby capturing free charges and limiting electrical conduction. Concurrently, the low E A and wide bandgap of the ZrO 2 core introduce energy barriers to impede charge injection and migration. This orchestrated “energy level cascade” results in a marked reduction of leakage current and energy loss. The resulting polymer composite showcases an impressive discharged energy density of 6.21 J cm −3 at an efficiency above 90%, with a maximum discharged energy density reaching 7.43 J cm −3 at 150 °C. These performance metrics position the PEI/ZrO 2 @COF polymer composite to surpass or be on par with state‐of‐the‐art high‐temperature PEI composites and other advanced polymer dielectrics.

Xie, Zongliang↗

Deep level defects and cation sublattice disorder in ZnGeN 2

The III-nitrides have revolutionized lighting technology and power electronics. Expanding the nitride semiconductor family to include the heterovalent ternary nitrides opens up new and exciting opportunities for device design that may help overcome some of the limitations of the binary nitrides as well as new applications. However, the more complex cation sublattice also gives rise to new complexities with both native and extrinsic defects, such as disorder on the cation sublattice. Here, depth-resolved cathodoluminescence spectroscopy and surface photovoltage spectroscopy measurements of defect energy levels in ZnGeN 2 combined with transmission microscopy and crystal lattice diffraction reveal optical signatures of mid-gap states that can be associated with cation sublattice disorder. The energies of these characteristic optical signatures in ZnGeN 2 thin films grown by metal-organic chemical vapor deposition are in good agreement with energy levels predicted by density functional theory for specific thermodynamically stable native point defects. To test the dependence of these defect signatures on crystal atomic composition, we correlated spatially-resolved optical and atomic composition measurements using spatially resolved x-ray photoelectron spectroscopy with systematically varied growth conditions on the same ZnGeN 2 films. The resultant elemental maps versus defect spectral energies and intensities suggest that cation antisite complexes (Zn Ge -Ge Zn ) versus isolated native point defects form preferentially and introduce mid-gap states that dominate electron-hole pair recombination. Complexing of Zn Ge and Ge Zn antisites manifests as disorder in the cation sub-lattice and leads to the formation of wurtzitic ZnGeN 2 as indicated by transmission electron microscopy diffraction patterns and x-ray diffraction (XRD) reciprocal space maps. Furthermore, these findings emphasize the importance of growth conditions to control cation place exchange.

42 ENGINEERING↗

Task Sharing of Proton Incorporation in Vertically Aligned Nanocomposite Triple Conductors: Growth, Structure, and Surface Exchange Kinetics

As protonic ceramic electrolysis cells emerge for efficient H 2 production, there is a need to develop air electrode materials enabling fast, durable steam splitting and proton incorporation. Single-phase triple conductors may fail to satisfy the myriad performance/stability requirements, and their critical charge-carriers (holes, oxygen vacancies, and protons) are in competition, limiting their concentrations. Instead, we propose task-sharing, vertically aligned nanocomposites (VANs), comprising a proton conductor (BaZr 0.9 Y 0.1 O 3-δ ) and a redox-active mixed ionic electronic conductor (Ce 0.9 Pr 0.1 O 2-δ ), that may enable rapid proton surface exchange at the solid–gas interface and transport along the solid–solid heterointerfaces. We grew VANs by pulsed laser deposition and investigated the interplay between their processing conditions, structure, and proton and oxygen surface exchange kinetics. We varied the substrate temperature, laser repetition rate, laser fluence, and processing oxygen pressure. The crystallinity and phases were characterized by grazing-incidence X-ray diffraction, and the strain and structural order as a function of depth were evaluated by angle-dependent synchrotron X-ray pair distribution function analysis. To evaluate the potential for interdiffusion, the formation energies of substitutional defects were simulated with density functional theory. Corresponding structural analysis and elemental mapping were performed by scanning/transmission electron microscopy, energy-dispersive X-ray spectroscopy, and electron energy-loss spectroscopy, indicating distinct nanoscale compositional regions with a hierarchical structure embedded in individual VANs columns and minimal interdiffusion across a bilayer film. Proton and oxygen surface exchange coefficients (k H , k O ) and polarization resistances were evaluated by electrical and optical relaxations and impedance spectroscopy of VAN-incorporated protonic ceramic electrochemical cells, respectively, at 400–500 °C, demonstrating values comparable to some of the best-known triple and mixed conductors.

36 MATERIALS SCIENCE↗

First-Principles Study on the Role of Cu and Cl-Based Dopants in NiO

Utilization of wide band gap oxide-based materials in thin-film solar energy technologies has increased in recent years. Among the numerous candidate oxide materials, NiO has shown many desirable optoelectronic properties that are applicable to thin-film PV technologies such as cadmium telluride PV. However, one critical factor requiring further investigation is the p-type doping behavior of NiO, specifically when the cadmium telluride solar cell undergoes conventional processes such as copper doping and chlorine-based activation treatment. The previous literature has shown a large degree of variability in hole concentrations in NiO when copper is used as the primary dopant. This study uses first-principles computational modeling based on density functional theory coupled with defect equilibria calculations to quantitatively explore the role of copper and chlorine-based extrinsic dopants in the p-type doping activity of NiO. The study reveals the importance of extrinsic dopants and their binding interactions with nickel vacancies to effectively p-dope NiO. It is suggested that both the formation of V Ni + Cu Ni and V Ni + Cl O defect pairs under a supersaturated state of NiO are potential mechanisms for increasing hole densities. On the other hand, the production of 2Cu Ni severely limits the effectiveness of p-doping in NiO, even in the presence of the aforementioned defect pairs. Furthermore, the study provides a guideline for experimentalists interested in using copper or chlorine species to understand how to controllably p-dope NiO during thin-film synthesis.

chlorine↗

DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials

Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods, such as density functional theory (DFT) at the meta-GGA level and/or with exact exchange, quantum Monte Carlo, etc., generating a sufficient amount of data for training an ML potential has remained computationally challenging due to their high cost. In this work, we demonstrate that this issue can be largely alleviated with Deep Kohn–Sham (DeePKS), an ML-based DFT model. DeePKS employs a computationally efficient neural network-based functional model to construct a correction term added upon a cheap DFT model. Upon training, DeePKS offers closely matched energies and forces compared with high-level QM method, but the number of training data required is orders of magnitude less than that required for training a reliable ML potential. As such, DeePKS can serve as a bridge between expensive QM models and ML potentials: one can generate a decent amount of high-accuracy QM data to train a DeePKS model and then use the DeePKS model to label a much larger amount of configurations to train an ML potential. Further, this scheme for periodic systems is implemented in a DFT package ABACUS, which is open source and ready for use in various applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗