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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Benchmarking Density Functional Theory Methods for Efficient Calculations of a Strongly Correlated Li 1– x Ni 1– y O 2−δ System

Transition metal oxides (TMOs), such as LiNiO 2 , are promising candidates for energy storage and electronic devices due to their unique electronic properties, exceptional physical and chemical characteristics, and ability to adopt multiple oxidation states. However, accurately predicting their properties using mean-field density functional theory (DFT) is challenging due to the presence of strongly correlated d-electrons and the complex interplay between their structural, electronic, and magnetic responses. These challenges are further exacerbated by the need to model defects, surfaces, and interfaces, which require computationally efficient, large-scale simulations. To address these issues, we carry out a benchmark study on the Li 1–x NiO 2 system, evaluating the performance of several popular functionals. Our findings demonstrate that combining SCAN functional relaxation with single-step HSE calculations provides a practical and scalable computational strategy. This approach balances accuracy and efficiency, enabling high-throughput simulations of strongly correlated TMOs and improved predictive modeling capability of TMOs for practical applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Overdestabilization vs Overstabilization in the Theoretical Analysis of f-Orbital Covalency

The complex nature of the f-orbital electronic structures and their interaction with the chemical environment pose significant computational challenges. Advanced computational techniques that variationally include scalar relativities and spin–orbit coupling directly at the molecular orbital level have been developed to address this complexity. Among these, variational relativistic multiconfigurational multireference methods stand out for their high accuracy and systematic improvement in studies of f-block complexes. Additionally, these advanced methods offer the potential for calibrating low-scaling electronic structure methods such as density functional theory. However, studies on the Cl K-edge X-ray absorption spectra of the [Ce(III)Cl 6 ] 3– and [Ce(IV)Cl 6 ] 2– complexes show that time-dependent density functional theory with approximate exchange–correlation kernels can lead to inaccuracies, resulting in an overstabilization of 4f orbitals and incorrect assessments of covalency. In contrast, approaches utilizing small active space wave function methods may understate the stability of these orbitals. The results herein demonstrate the need for large active space, multireference, and variational relativistic methods in studying f-block complexes.

chemical calculations↗
DOE OSTI2026

MnRhBi3: A Cleavable Antiferromagnetic Metal

This dataset contains DFT input and output files supporting the theoretical modeling in the associated publication (Chem. Mater. 2024, 36, 11306-11316). The calculations characterize MnRhBi3, an orthorhombic (Cmmm) van der Waals-layered intermetallic compound that cleaves easily between neighboring Bi layers. The dataset is organized into three calculation types: (i) Bulk: Structural relaxations of the periodic MnRhBi3 crystal in antiferromagnetic (AFM) and ferromagnetic (FM) configurations, using the vdW-DF-optB86b functional. These provide the equilibrium lattice constants, magnetic energy differences (AFM is 0.5 meV/f.u. lower than FM), and magnetic moments (4.4 µB/Mn, 0.17 µB/Rh, 0.18 µB/Bi) reported in Table 1 of the main text. (ii) Slab: Same magnetic configurations computed with an 18 Ang vacuum layer introduced between Bi layers, used to calculate the cleavage energy Ec = 0.56 J/m2 (AFM) and 0.57 J/m2 (FM), establishing MnRhBi3 as a van der Waals-layered material comparable to graphite, MoS2, and CrI3. (iii) ELF: Single-point calculation on the relaxed bulk AFM geometry with LELF=.TRUE., producing the ELFCAR file used to generate electron localization function isosurfaces and contour maps (Fig. 2, main text) showing Bi lone pairs directed into the van der Waals gaps. All folders contain CONTCAR, INCAR, KPOINTS, OUTCAR, and POSCAR. The ELF/ folder additionally contains ELFCAR. Calculations were performed using VASP 6.3.2 with PBE + vdW-DF-optB86b, PAW potentials, and an energy cutoff of 800 eV.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Local Electronic Structure of Supercritical CO 2 from X-ray Raman Spectroscopy and Atomistic-Scale Modeling

Supercritical CO 2 is encountered in several technical and natural systems related to biology, geophysics, and engineering. While the structure of gaseous CO 2 has been studied extensively, the properties of supercritical CO 2 , particularly close to the critical point, are not well-known. Here, in this work, we combine X-ray Raman spectroscopy, molecular dynamics simulations, and first-principles density functional theory (DFT) calculations to characterize the local electronic structure of supercritical CO 2 at conditions around the critical point. The X-ray Raman oxygen K-edge spectra manifest systematic trends associated with the phase change of CO 2 and the intermolecular distance. Extensive first-principles DFT calculations rationalize these observations on the basis of the 4sσ Rydberg state hybridization. X-ray Raman spectroscopy is found to be a sensitive tool for characterizing electronic properties of CO 2 under challenging experimental conditions and is demonstrated to be a unique probe for studying the electronic structure of supercritical fluids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Dopant levels in large nanocrystals using stochastic optimally tuned range-separated hybrid density functional theory

In this work, we apply a stochastic version of an optimally tuned range-separated hybrid functional to provide insight on the electronic properties of P- and B- doped Si nanocrystals of experimentally relevant sizes. We show that we can use the range-separation parameter for undoped systems to calculate accurate results for dopant activation energies. We apply this strategy for tuning functionals to study doped nanocrystals up to 2.5 nm in diameter at the hybrid functional level. In this confinement regime, the P- and B- dopants have large activation energies and have strongly localized states that lie deep within the energy gaps. Structural relaxation plays a greater role for B-substituted dopants and contributes to the increase in activation energy when the B dopant is near the nanocrystal surface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Spectroscopic signature of negative electronic compressibility from the Ti core-level of titanium carbonitride MXene

Two-dimensional transition metal carbides, carbonitrides, and nitrides called MXenes exhibit high metallic conductivity, ion intercalation capability and reversible redox activity, prompting their applications in energy storage and conversion, electromagnetic interference (EMI) shielding, and electronics, among many other fields. It has been shown that replacement of about 50% of carbon atoms in the most popular MXene family member, titanium carbide (Ti 3 C 2 T x ), by nitrogen atoms, forming titanium carbonitride (Ti 3 CNT x ), leads to drastically different properties, such as very high negative charge in solution and extreme EMI shielding effectiveness, exceeding all known materials, even metals at comparable thicknesses. Here, by using ultraviolet photoemission spectroscopy (UPS), the electronic structures of Ti 3 CNT x and Ti 3 C 2 T x are systematically investigated and compared as a function of charge carrier density. We observe that, in contrast to Ti 3 C 2 T x , the Ti 3p core-level of Ti 3 CNT x exhibits a counterintuitive shift to a lower binding energy of up to approximately 250 meV upon increasing the electron density, which is a spectroscopic signature of negative electronic compressibility (NEC). These experimentally measured chemical potential shifts are well-captured by the density functional theory (DFT) calculation. The DFT results also further suggest that the hybridization of titanium-nitrogen bonding in Ti 3 CNT x helps promoting the available states of Ti atoms for receiving more electron above the Fermi level and leads to the observed NEC. Furthermore, our findings explain the differences in electronic properties between the two very important and widely studied MXenes and also suggest a new strategy to apply the NEC effect of Ti 3 CNT x in energy and charge storage applications.

2D materials↗
DOE OSTI2020

Rationalizing Calcium Electrodeposition Behavior by Quantifying Ethereal Solvation Effects on Ca 2+ Coordination in Well-Dissociated Electrolytes

Ca-ion electrochemical systems have been pushed to the forefront of recent multivalent energy storage advances due to their use of earth-abundant redox materials and their high theoretical specific densities in relation to monovalent or even other more widely explored multivalent-charge carriers. However, significant pitfalls in metal plating and stripping arise from electrolyte decomposition and can be related to the coordination environment around Ca 2+ with both the negatively charged anion and the organic–aprotic solvent. Here, we apply multiple spectroscopic techniques in conjunction with density functional theory to evaluate the coordination environment of Ca 2+ across a class of ethereal solvents. Through the combination of X-ray absorption fine structure and time-dependent density functional theory, descriptive measures of the local geometry, coordination, and electronic structure of Ca–ethereal complexes provide distinct structural trends depending on the extent of the Ca 2+ –solvent interaction. Finally, we correlate these findings with electrochemical measurements of calcium tetrakis(hexafluoroisopropoxy)borate (CaBHFIP 2 ) salts dissolved within this class of solvents to provide insight into the preferred structural configuration of Ca 2+ electrolytic solutions for optimized electrochemical plating and stripping.

25 ENERGY STORAGE↗
DOE OSTI2021

Reactions of U + with H 2 , D 2 , and HD Studied by Guided Ion Beam Tandem Mass Spectrometry and Theory

The kinetic energy-dependent reactions of the atomic actinide uranium cation (U + ) with H 2 , D 2 , and HD were examined by guided ion beam tandem mass spectrometry. An average 0 K bond dissociation energy of D 0 (U + – H) = 2.48 ± 0.06 eV is obtained by analysis of the endothermic product ion cross sections. Quantum chemistry calculations were performed for comparison with experimental thermochemistry, including high-level CASSCF–CASPT2–RASSI calculations of the spin–orbit corrections. CCSD(T) and the CASSCF levels show excellent agreement with experiment, whereas B3LYP and PBE0 slightly overestimate and the M06 approach badly underestimates the bond energy for UH + . Theory was also used to investigate the electronic structures of the reaction intermediates and potential energy surfaces. The experimental product branching ratio for the reaction of U + with HD indicates that these reactions occur primarily via a direct reaction mechanism, despite the presence of a deep-well for UH 2 + formation according to theory. The reactivity and hydride bond energy for U + are compared with those for transition metal, lanthanide, and actinide cations, and periodic trends are discussed. Furthermore, these comparisons suggest that the 5f electrons on uranium are largely core and uninvolved in the reactive chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

First-principles study of an S = 1 quasi one-dimensional quantum molecular magnetic material

We use density functional theory to study the structural, magnetic, and electronic structures of the organometallic quantum magnet NiCl 2-4 SC (NH 2 ) 2 (DTN). Recent work has demonstrated the quasi one-dimensional nature of the molecular crystal and studied its quantum phase transitions at low temperatures. The system includes a magnetoelectric (ME) coupling and, when doped with Br, the presence of an exotic Bose-glass state. Using the generalized gradient approximation with inclusion of a van der Waals term to account for weak intermolecular forces and by introducing a Hubbard U term to the total energy, we systematically show that our calculations reproduce the magnetic anisotropy, the intermolecular exchange coupling strength, and the magnetoelectric effect in DTN, which have been observed in previous experiments. Further analysis of the electronic structure gives insight into the underlying magnetic interactions, including what mechanisms may be causing the ME effect. Using this computationally efficient model, we predict what effect applying an electric field might have on the magnetic properties of this quantum magnet.

1-dimensional spin chains↗
DOE OSTI2023

A closer look at how symmetry constraints and the spin–orbit coupling shape the electronic structure of Bi(111)

Abstract Fully relativistic density-functional-theory calculations of Bi(111) thin films are analyzed to revisit their two metallic surface-states branches. We first contrast these metallic branches with surface states arising at gaps in the valence band opened by the spin–orbit coupling (SOC). We find that the two metallic branches along Γ M ‾ do not overlap with the bulk band at the zone boundary,M. We show that the spin texture observed in such states cannot be traced to the lifting of Kramers’ degeneracy. Instead, we track them to the m j = ± 1 / 2 – m j = ± 3 / 2 SOC splitting, the potential anisotropy for in-plane and out-of-plane states, and the coupling between the opposite surfaces of a slab occurring nearM, which is driven by a spatial redistribution of the four metallic states composing the two metallic branches. Each of these branches appears to be non-degenerate at the tested surface, yet each is degenerate with another state of opposite spin at the other surface. Nevertheless, the four metallic states bear some contribution on both surfaces of the film because of their spatial redistribution nearM. The overlapping among these states nearM, afforded by their spatial redistribution on both surfaces, causes a hybridization that perpetuates the splitting between the two branches, makes the film’s electronic structure thickness dependent nearM, extinguishes the magnetic moment of the metallic states avoiding the magnetic-moment discontinuity atM, and denies the need or expectancy of the metallic branches becoming degenerate atM. We propose that theoppositespin polarization observed for the two metallic branches occurs because the surface atoms retain their covalent bonds and thus cannot afford magnetic polarization. We show that the Rashba-splitting of the metallic states for inversion-asymmetric films does not have a fixed magnitude but can be tuned by changing the perturbation breaking inversion symmetry.

Physics↗
DOE OSTI2021

Coordination and activation of nitrous oxide by iron zeolites

Iron-containing zeolites are heterogeneous catalysts that exhibit remarkable activity in the selective oxidation of inert hydrocarbons and catalytic decomposition of nitrous oxide (N 2 O). The reduction of N 2 O is critical to both these functions, but experimental data tracking the iron active sites during N 2 O binding and activation are limited. Here, the N 2 O-ligated Fe(ii) active site in iron-exchanged zeolite beta is isolated and characterized by variable-temperature Mössbauer, diffuse reflectance UV-vis-NIR and Fourier transform infrared spectroscopy. N 2 O binds through the terminal nitrogen atom with substantial backbonding from the Fe(ii) centre at low temperature. At higher temperatures, the Fe–N 2 O interaction is weakened, facilitating isomerization to the O-bound form, which is competent in O-atom transfer. Density functional theory calculations show the geometric and electronic structure requirements for N 2 O binding and activation. A geometric distortion imposed by the zeolite lattice plays an important role in activating N 2 O. As a result, this highlights a mechanism for structural control over function in Fe-zeolite catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Featureless adaptive optimization accelerates functional electronic materials design

Electronic materials that exhibit phase transitions between metastable states (e.g., metal-insulator transition materials with abrupt electrical resistivity transformations) are challenging to decode. For these materials, conventional machine learning methods display limited predictive capability due to data scarcity and the absence of features that impede model training. In this article, we demonstrate a discovery strategy based on multi-objective Bayesian optimization to directly circumvent these bottlenecks by utilizing latent variable Gaussian processes combined with high-fidelity electronic structure calculations for validation in the chalcogenide lacunar spinel family. We directly and simultaneously learn phase stability and bandgap tunability from chemical composition alone to efficiently discover all superior compositions on the design Pareto front. Previously unidentified electronic transitions also emerge from our featureless adaptive optimization engine. Our methodology readily generalizes to optimization of multiple properties, enabling co-design of complex multifunctional materials, especially where prior data is sparse.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electronic properties of corundum-like Ir 2 O 3 and Ir 2 O 3 -Ga 2 O 3 alloys

In the hexagonal, corundum-like structure, α-Ga 2 O 3 has a bandgap of ~5.1 eV, which, combined with its relatively small electron effective mass, high Baliga's figure of merit, and high breakdown field, makes it a promising candidate for power electronics. Ga 2 O 3 is easy to dope n-type, but impossible to dope p-type, impeding the realization of some electronic device designs. Developing a lattice-matched p-type material that forms a high-quality heterojunction with n-type Ga 2 O 3 would open new opportunities in electronics and perhaps optoelectronic devices. In this work, we studied Ir 2 O 3 as a candidate for that purpose. Using hybrid density functional theory calculations we predict the electronic band structure of α-Ir 2 O 3 and compare that to α-Ga 2 O 3 , and study the stability and electronic properties of α-(Ir x Ga 1–x ) 2 O 3 alloys. We discuss the band offset between the two materials and compare it with recently available experimental data. We find that the Ir d bands that compose the top of the valence band in α-Ir 2 O 3 are much higher in energy than O p bands in α-Ga 2 O 3 , possibly enabling effective p-type doping. Finally, our results provide an insight into using the Ir 2 O 3 or Ir 2 O 3 -Ga 2 O 3 alloys as p-type material lattice-matched to α-Ga 2 O 3 for the realization of p–n heterojunctions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

MnRhBi 3 : A Cleavable Antiferromagnetic Metal

Cleavable metallic antiferromagnets may be of use for low-dissipation spintronic devices; however, few are currently known. Here, in this study, we present orthorhombic MnRhBi 3 as one such compound and present a thorough study of its physical properties. Exfoliation is demonstrated experimentally, and the cleavage energy and electronic structure are examined by density functional theory calculations. It is concluded that MnRhBi 3 is a van der Waals-layered material that cleaves easily between neighboring Bi layers and that the Bi atoms have lone pairs extending into the van der Waals gaps. A series of four phase transitions are observed below room temperature, and neutron diffraction shows that at least two of the transitions involve the formation of antiferromagnetic order. Anomalous thermal expansion points to a crystallographic phase transition and/or strong magnetoelastic coupling. This work reveals a complex phase evolution in MnRhBi 3 and establishes this cleavable antiferromagnetic metal as an interesting material for studying the interplay of structure, magnetism, and transport in the bulk and ultrathin limits, as well as the role of lone pair electrons in interface chemistry and proximity effects in van der Waals heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Machine learning for accuracy in density functional approximations

Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally efficient electronic structure methods, such as density functional theory, to chemical accuracy and to correct for fundamental errors in density functional approaches. In this paper, recent progress in applying machine learning to improve the accuracy of density functional and related approximations is reviewed. Promises and challenges in devising machine learning models transferable between different chemistries and materials classes are discussed with the help of examples applying promising models to systems far outside their training sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

From Oxo to Oxyl to Biradical: Systematic Multireference Calculations of Methane Activation at MOF Nodes

Methane C–H activation at transition-metal sites often involves electronic structures that challenge conventional single-reference electronic structure descriptions. Although Kohn–Sham density functional theory (DFT) is widely used to study catalytic trends, its reliability for reactions involving strongly correlated species remains uncertain. Here we present a systematic multireference investigation of methane activation at metal–organic framework (MOF) node catalysts across the 3d transition-metal series. We introduce an automated workflow for active space selection to enable consistent application of multireference methods, including multiconfiguration pair-density functional theory and n-electron valence state perturbation theory, to these catalytic systems. These calculations show substantial static correlation in the C–H activation reaction step and predict activation barriers that differ from DFT by 30–70 kJ mol–1, with DFT often qualitatively disagreeing in barrier height trends across transition metals. Analysis of multireference wave functions shows that reactivity is governed by the electronic structure of the M–O moiety along a continuum from metal–oxo to oxyl radical and O biradical character. Increased oxygen-centered spin density and weakened M–O bonding are identified as descriptors of catalytic activity which correlate with lower activation barriers.

Wardzala, Jacob↗
DOE OSTI2024

Hybrid programming-model strategies for GPU offloading of electronic structure calculation kernels

To address the challenge of performance portability and facilitate the implementation of electronic structure solvers, we developed the basic matrix library (BML) and Parallel, Rapid O(N), and Graph-based Recursive Electronic Structure Solver (PROGRESS) library. The BML implements linear algebra operations necessary for electronic structure kernels using a unified user interface for various matrix formats (dense and sparse) and architectures (CPUs and GPUs). Focusing on density functional theory and tight-binding models, PROGRESS implements several solvers for computing the single-particle density matrix and relies on BML. In this paper, we describe the general strategies used for these implementations on various computer architectures, using OpenMP target functionalities on GPUs, in conjunction with third-party libraries to handle performance critical numerical kernels. In this study, we demonstrate the portability of this approach and its performance in benchmark problems.

36 MATERIALS SCIENCE↗