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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electronic structure analysis and DFT benchmarking of Rydberg-type alkali-metal-crown ether, -cryptand, and -adamanzane complexes

Density functional theory (DFT) and electron propagator theory (EPT) calculations were performed to study ground and excited electronic structures of alkali-metal (M) coordinated 9-crown-3, 24-crown-8, [2.1.1]cryptand, o-Me 2 -1.1.1, and 3 6 Adamanzane complexes. Each complex bears an expanded electron in the periphery and occupies diffuse 1p-, 1d-, 1f-type molecular orbitals (or superatomic 1P, 1D, 1F orbitals) in excited electronic states. The calculated superatomic shell model of the M(9-crown-3) 2 is 1S, 1P, 1D, 1F, 2S, 2P, 2D, 1G and it is held by all other complexes up to the studied 1F level. Due to the highly diffuse nature of the electron, the ionization energies of these complexes are significantly lower (1.6–2.0 eV) and hence these complexes belong to the superalkali category. Further, the ab initio EPT ionization energy and the excitation energies of the Li(9-crown-3) 2 were used to evaluate DFT errors associated with a series of exchange correlation functionals that span multiple rungs of Jacob's ladder (i.e., GGA, meta-GGA, global GGA hybrid, meta-GGA hybrid, range-separated hybrid, double-hybrid). Among these, the best performing functional is the range-separated hybrid CAM-B3LYP and the errors are within 6% of high-level ab initio EPT results. The accuracy of CAM-B3LYP is indeed transferable to similar complexes and hence the findings are expected to accelerate the progression of studies of Rydberg-type systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Subspace recursive Fermi-operator expansion strategies for large-scale DFT eigenvalue problems on HPC architectures

Quantum mechanical calculations for material modeling using Kohn–Sham density functional theory (DFT) involve the solution of a nonlinear eigenvalue problem for N smallest eigenvector-eigenvalue pairs, with N proportional to the number of electrons in the material system. Here, these calculations are computationally demanding and have asymptotic cubic scaling complexity with the number of electrons. Large-scale matrix eigenvalue problems arising from the discretization of the Kohn–Sham DFT equations employing a systematically convergent basis traditionally rely on iterative orthogonal projection methods, which are shown to be computationally efficient and scalable on massively parallel computing architectures. However, as the size of the material system increases, these methods are known to incur dominant computational costs through the Rayleigh–Ritz projection step of the discretized Kohn–Sham Hamiltonian matrix and the subsequent subspace diagonalization of the projected matrix. This work explores the potential of polynomial expansion approaches based on recursive Fermi-operator expansion as an alternative to the subspace diagonalization of the projected Hamiltonian matrix to reduce the computational cost. Subsequently, we perform a detailed comparison of various recursive polynomial expansion approaches to the traditional approach of explicit diagonalization on both multi-node central processing unit and graphics processing unit architectures and assess their relative performance in terms of accuracy, computational efficiency, scaling behavior, and energy efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

DFT Calculation of Thermal Expansion within Debye-Grüneisen Framework Made Simple and Accurate

The density functional theory (DFT) based Debye-Grüneisen approach is a computational method used to calculate the thermodynamic properties of materials by relating the volume dependence of the Debye frequency to the Grüneisen parameter. In this study, we propose a new model to describe the volume dependence of the Grüneisen parameter. This model offers a simple yet accurate approach to predict the thermal expansion of materials within the framework of the Debye-Grüneisen theory. Specifically, for pure elements or species used as a reference system, we calibrated the parameters to reproduce the experimental coefficient of thermal expansion, heat capacity, and entropy. For compounds with arbitrary compositions, the parameters are determined by taking the arithmetic or geometric average of those obtained from the pure elements or species based on their composition. We then compared the model prediction with experiments. This allowed for a comprehensive characterization of the thermal expansion behavior of various materials.

Wang, Yi↗
DOE OSTI2023

Electronic density response of warm dense matter

Matter at extreme temperatures and pressures—commonly known as warm dense matter (WDM)—is ubiquitous throughout our Universe and occurs in astrophysical objects such as giant planet interiors and brown dwarfs. Moreover, WDM is very important for technological applications such as inertial confinement fusion and is realized in the laboratory using different techniques. A particularly important property for the understanding of WDM is given by its electronic density response to an external perturbation. Such response properties are probed in x-ray Thomson scattering (XRTS) experiments and are central for the theoretical description of WDM. In this work, we give an overview of a number of recent developments in this field. To this end, we summarize the relevant theoretical background, covering the regime of linear response theory and nonlinear effects, the fully dynamic response and its static, time-independent limit, and the connection between density response properties and imaginary-time correlation functions (ITCF). In addition, we introduce the most important numerical simulation techniques, including path-integral Monte Carlo simulations and different thermal density functional theory (DFT) approaches. From a practical perspective, we present a variety of simulation results for different density response properties, covering the archetypal model of the uniform electron gas and realistic WDM systems such as hydrogen. Moreover, we show how the concept of ITCFs can be used to infer the temperature from XRTS measurements of arbitrary complex systems without the need for any models or approximations. Finally, we outline a strategy for future developments based on the close interplay between simulations and experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

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

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

36 MATERIALS SCIENCE↗
DOE OSTI2022

Feasibility of Prelithiation in LiFePO 4

Lithium iron phosphate (LiFePO 4 ) is widely applied as the cathode material for the energy storage Li-ion batteries due to its low cost and high cycling stability. However, the low theoretical specific capacity of LiFePO 4 makes its initial capacity loss more concerning. Therefore, lithium compensation by way of prelithiation and applications of sacrificial Li-rich additives in LiFePO 4 is imminent in elevating the energy density and/or prolonging the lifetime of the LiFePO 4 -based Li-ion batteries (LIBs). Prelithiation in LiFePO 4 is herein carried out by electrochemical and chemical methods and its feasibility is proved on the basis of the electrochemical evaluations such as the initial charge capacity and the cycling stability. In addition, the site of the pre-intercalated Li-ions is found via comprehensive physical characterizations and the density functional theory (DFT) calculations. Furthermore, these findings open a new avenue for elevating the energy density and/or prolonging the lifetime of the high-energy-density batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Vibrations and Phase Stability in Mixed Valence Antimony Oxide

α-Sb 2 O 4 (cervantite) and β-Sb 2 O 4 (clinocervantite) are mixed valence compounds with equal proportions of Sb III and Sb V as represented in the formula Sb III Sb V O 4 . Their structure and properties can be difficult to calculate owing to the Sb III lone-pair electrons. Here, we present a study of the lattice dynamics and vibrational properties using a combination of inelastic neutron scattering, Mössbauer spectroscopy, nuclear inelastic scattering, and density functional theory (DFT) calculations. DFT calculations that account for lone-pair electrons match the experimental densities of phonon states. Mössbauer spectroscopy reveals the β phase to be significantly harder than the α phase. Calculations with O vacancies reveal the possibility for nonstoichiometric proportions of Sb III and Sb V in both phases. An open question is what drives the stability of the α phase over the β phase, as the latter shows pronounced kinetic stability and lower symmetry despite being in the high-temperature phase. Since the vibrational entropy difference is small, it is unlikely to stabilize the α phase. In conclusion, our results suggest that the α phase is more stable only because the material is not fully stoichiometric.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Mapping the Complete Reaction Energy Landscape of a Metal–Organic Framework Phase Transformation

Crystalline materials undergo valuable phase transformations, and the energetic processes that underlie these transformations can be fully characterized through a combination of thermodynamic and kinetic studies. Here, we report the first complete reaction energy landscape of metal–organic framework (MOF) interpenetration, specifically in the phase transformation of NU-1200 to its doubly interpenetrated counterpart, STA-26. We characterized the thermodynamics of this phase transformation by pairing experiments with density functional theory (DFT) calculations. This analysis revealed that factors such as the increase in crystal density likely drive Zr- and Hf-NU-1200 to STA-26 interpenetration, while other chemical interactions such as steric repulsions prevent Th-NU-1200 from interpenetrating. Using time-resolved in situ X-ray diffraction, we monitored phase transformation reaction profiles and extracted quantitative kinetic information using the Avrami-Erofe’ev model. As a result, we obtained activation energies for the Zr- and Hf-NU-1200 transformations to Zr- and Hf-STA-26, respectively, revealing slower phase change kinetics for MOFs with stronger bonds. Finally, we paired the kinetic data with experimental observations to classify the mechanistic model of this phase transformation as partial dissolution. Here, we anticipate that this thermodynamic, kinetic, and mechanistic understanding will broadly inform further studies on the energetics of crystallization.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

All-electron, density-functional-based method for angle-resolved tunneling ionization in the adiabatic regime

Here we develop and test a method that integrates many-electron weak-field asymptotic theory (ME-WFAT) [O. I. Tolstikhin, L. B. Madsen, and T. Morishita, Phys. Rev. A 89, 013421 (2014)] in the integral representation (IR) into the density-functional-theory (DFT) framework. In particular, we present modifications of the integral formula in the IR ME-WFAT to incorporate the potential terms unique to DFT. By solving an adiabatic rate equation for the angle-resolved ionization yield in our DFT-based ME-WFAT method, we show that the results are in excellent agreement with those of real-time time-dependent density-functional-theory (TDDFT) simulations for NO, OCS, C⁢H 3 ⁢Br, and C⁢H 3 ⁢Cl interacting with one- and two-color laser fields with a fundamental wavelength of 800 nm. This agreement is significant because the WFAT calculations take only a small fraction of the time of full TDDFT calculations. These results suggest that in the wavelength region commonly used in strong-field experiments (800 nm and longer), our DFT-based WFAT treatment can be used to rapidly screen for the ionization properties of a large number of molecules as a function of alignment or orientation between the molecule and the strong field.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Accelerating Finite-temperature Kohn-Sham Density Functional Theory\ with Deep Neural Networks

We present a numerical modeling workflow based on machine learning (ML) which reproduces the the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible computational cost. Based on deep neural networks, our workflow yields the local density of states (LDOS) for a given atomic configuration. From the LDOS, spatially-resolved, energy-resolved, and integrated quantities can be calculated, including the DFT total free energy, which serves as the Born-Oppenheimer potential energy surface for the atoms. We demonstrate the efficacy of this approach for both solid and liquid metals and compare results between independent and unified machine-learning models for solid and liquid aluminum. Our machine-learning density functional theory framework opens up the path towards multiscale materials modeling for matter under ambient and extreme conditions at a computational scale and cost that is unattainable with current algorithms.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accelerating Finite-Temperature Kohn-Sham Density Functional Theory with Deep Neural Networks

We present a numerical modeling workflow based on machine learning (ML) which reproduces the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible computational cost. Based on deep neural networks, our workflow yields the local density of states (LDOS) for a given atomic configuration. From the LDOS, spatially-resolved, energy-resolved, and integrated quantities can be calculated, including the DFT total free energy, which serves as the Born-Oppenheimer potential energy surface for the atoms. We demonstrate the efficacy of this approach for both solid and liquid metals and compare results between independent and unified machine-learning models for solid and liquid aluminum. Our machine-learning density functional theory framework opens up the path towards multiscale materials modeling for matter under ambient and extreme conditions at a computational scale and cost that is unattainable with current algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Superconductivity enhancement in phase-engineered molybdenum carbide/disulfide vertical heterostructures

Stacking layers of atomically thin transition-metal carbides and two-dimensional (2D) semiconducting transition-metal dichalcogenides, could lead to nontrivial superconductivity and other unprecedented phenomena yet to be studied. In this work, superconducting α-phase thin molybdenum carbide flakes were first synthesized, and a subsequent sulfurization treatment induced the formation of vertical heterolayer systems consisting of different phases of molybdenum carbide—ranging from α to γ' and γ phases—in conjunction with molybdenum sulfide layers. These transition-metal carbide/disulfide heterostructures exhibited critical superconducting temperatures as high as 6 K, higher than that of the starting single-phased α-Mo 2 C (4 K). We analyzed possible interface configurations to explain the observed moiré patterns resulting from the vertical heterostacks. Our density-functional theory (DFT) calculations indicate that epitaxial strain and moiré patterns lead to a higher interfacial density of states, which favors superconductivity. Such engineered heterostructures might allow the coupling of superconductivity to the topologically nontrivial surface states featured by transition-metal carbide phases composing these heterostructures potentially leading to unconventional superconductivity. Moreover, we envisage that our approach could also be generalized to other metal carbide and nitride systems that could exhibit high-temperature superconductivity.

heterostructure↗
DOE OSTI2024

2D-EFICACY: Control of Metastable 2D Carbide[1]Chalcogenide Heterolayers: Strain and Moire Engineering

The experimental isolation of graphene led to the discovery of an entirely new world of two-dimensional (2D) materials in which the 2D nature often leads to emergent behaviors not seen in bulk systems. 2D transition metal dichalcogenides (TMDs) exhibit physico-chemical properties that depend on the transition metal, polymorph, thickness, and presence and type of defects. Recently, a group of thin (10-100nm) transition metal carbides (TMCs), such as Mo2C, has been synthesized that exhibit a thickness-dependent superconducting critical temperature (Tc). These thin TMCs are different from MXenes, another class of 2D materials consisting of few layers of nitrides or carbides (<5nm) produced by chemical etching and delamination. The goal of this renewal proposal is to combine experiment and computation to synthesize and elucidate the guiding principles that control the growth, orientation and strain of heterostacks of thin TMCs and TMDs composed with Nb, Ti and W. We expect to stabilize metastable hybrid phases of TMCs sandwiched between TMDs (H-TMD/Cs) with unprecedented physico-chemical properties. As part of previous DOE-funded work by the Terrones/Sinnott groups, thin (10-100 nm thick) Mo2C flakes were successfully synthesized by chemical vapor deposition (CVD). By subsequently exposing Mo2C to H2S, partial chalcogenization was achieved, resulting in heterostacks of MoCx phases and MoS2. The formation of MoS2 led to a deficiency of Mo atoms in the underlying Mo2C, resulting in an inhomogeneous phase change from α-Mo2C to γ’-MoCx and then to γ-MoC. The γ’-MoCx is a strained metastable phase and the heterostack of all three phases demonstrated an increased Tc relative to that of α-Mo2C, from 4 to 6K; its interleaved layered structure consisting of superconducting and semiconducting phases is ideal for future studies of Josephson junction series arrays. Moiré patterns in these heterostacked systems could result in new phenomena, as moiré patterns in bilayer graphene showed unconventional superconductivity and moiré excitons have been observed in twisted TMD heterobilayers. The scientific hypothesis of the proposed synergistic computational and experimental research is that orientation and strain control within confined thin metastable TMCs, sandwiched by stable phases of TMCs and layered TMDs, will depend on kinetic and thermodynamic “knobs” that include fast temperature changes, chalcogen diffusion through preferred crystallographic planes, reaction times, pressure, reactive atmosphere, precursors, and surfactants, which will also tailor properties such as superconductivity, magnetism, ferroelectricity, piezoelectricity, and catalytic performance. We will develop the guiding principles for the synthesis and stabilization of metastable H-TMD/Cs based on Nb, Ti and W. In order to validate the hypothesis, four tasks are proposed: The first task will synthesize ultra-thin TMCs based on Nb, W and Ti, by: 1) adapting the CVD method used for Mo2C, 2) plasma assisted CVD, 3) defect-mediated CVD processes, and 4) cryo-milling of carbide powders. The second task will accomplish the synthesis and basic physico-chemical characterizations of H-TMD/Cs by chalcogenization of the materials synthesized in task one, and by carbonization of TMDs. H-TMD/Cs will also be investigated for their suitability in energy conversion applications such as supercapacitors, Li and multivalent ion batteries, and electrocatalysts, topics of interest to DoE. These tasks will be carried out in close conjunction with density functional theory (DFT) calculations with insights into energetics, lattice parameters, stability, phase diagrams, band structures, and density of states of H-TMD/Cs. The third task will characterize and evaluate strain and moiré patterns at the interfaces of different H-TMD/Cs by high-resolution scanning transmission electron microscopy (HR-STEM), scanning tunneling microscopy (STM), and conductive tip atomic force microscopy. Nudged elastic band calculations with DFT will be performed to understand the chalcogen diffusion process, which will provide insights into the interfaces between different phases of TMCs and TMDs. The fourth task aims at quantifying the stability and dynamics of H-TMD/Cs by in-situ TEM and Raman studies under heating, strain, and electrical biasing. Phonon calculations using DFT will provide a basis for interpreting Raman spectra. This coherent framework involving synthesis, characterization, and computation will result in a broad scientific impact for energy related applications. The ability to develop new H-TMD/Cs will enhance a range of applications that include batteries, catalysts, switches, sensors, quantum computing components and smart coatings.

2-Dimensional materials↗
DOE OSTI2024

2D-EFICACY: Control of Metastable 2D Carbide Chalcogenide Heterolayers: Strain and Moire Engineering

The experimental isolation of graphene led to the discovery of an entirely new world of two-dimensional (2D) materials in which the 2D nature often leads to emergent behaviors not seen in bulk systems. 2D transition metal dichalcogenides (TMDs) exhibit physico-chemical properties that depend on the transition metal, polymorph, thickness, and presence and type of defects. Recently, a group of thin (10-100nm) transition metal carbides (TMCs), such as Mo 2 C, has been synthesized that exhibit a thickness-dependent superconducting critical temperature (Tc). These thin TMCs are different from MXenes, another class of 2D materials consisting of few layers of nitrides or carbides (<5nm) produced by chemical etching and delamination. The goal of this renewal proposal is to combine experiment and computation to synthesize and elucidate the guiding principles that control the growth, orientation and strain of heterostacks of thin TMCs and TMDs composed with Nb, Ti and W. We expect to stabilize metastable hybrid phases of TMCs sandwiched between TMDs (H-TMD/Cs) with unprecedented physico-chemical properties. As part of previous DOE-funded work by the Terrones/Sinnott groups, thin (10-100 nm thick) Mo 2 C flakes were successfully synthesized by chemical vapor deposition (CVD). By subsequently exposing Mo 2 C to H 2 S, partial chalcogenization was achieved, resulting in heterostacks of MoCx phases and MoS 2 . The formation of MoS 2 led to a deficiency of Mo atoms in the underlying Mo 2 C, resulting in an inhomogeneous phase change from α-Mo 2 C to γ’-MoCx and then to γ-MoC. The γ’-MoCx is a strained metastable phase and the heterostack of all three phases demonstrated an increased Tc relative to that of α-Mo 2 C, from 4 to 6K; its interleaved layered structure consisting of superconducting and semiconducting phases is ideal for future studies of Josephson junction series arrays. Moiré patterns in these heterostacked systems could result in new phenomena, as moiré patterns in bilayer graphene showed unconventional superconductivity and moiré excitons have been observed in twisted TMD heterobilayers. The scientific hypothesis of the proposed synergistic computational and experimental research is that orientation and strain control within confined thin metastable TMCs, sandwiched by stable phases of TMCs and layered TMDs, will depend on kinetic and thermodynamic “knobs” that include fast temperature changes, chalcogen diffusion through preferred crystallographic planes, reaction times, pressure, reactive atmosphere, precursors, and surfactants, which will also tailor properties such as superconductivity, magnetism, ferroelectricity, piezoelectricity, and catalytic performance. We will develop the guiding principles for the synthesis and stabilization of metastable H-TMD/Cs based on Nb, Ti and W. In order to validate the hypothesis, four tasks are proposed: The first task will synthesize ultra-thin TMCs based on Nb, W and Ti, by: 1) adapting the CVD method used for Mo 2 C, 2) plasma assisted CVD, 3) defect-mediated CVD processes, and 4) cryo-milling of carbide powders. The second task will accomplish the synthesis and basic physico-chemical characterizations of H-TMD/Cs by chalcogenization of the materials synthesized in task one, and by carbonization of TMDs. H-TMD/Cs will also be investigated for their suitability in energy conversion applications such as supercapacitors, Li and multivalent ion batteries, and electrocatalysts, topics of interest to DoE. These tasks will be carried out in close conjunction with density functional theory (DFT) calculations with insights into energetics, lattice parameters, stability, phase diagrams, band structures, and density of states of H-TMD/Cs. The third task will characterize and evaluate strain and moiré patterns at the interfaces of different H-TMD/Cs by high-resolution scanning transmission electron microscopy (HR-STEM), scanning tunneling microscopy (STM), and conductive tip atomic force microscopy. Nudged elastic band calculations with DFT will be performed to understand the chalcogen diffusion process, which will provide insights into the interfaces between different phases of TMCs and TMDs. The fourth task aims at quantifying the stability and dynamics of H-TMD/Cs by in-situ TEM and Raman studies under heating, strain, and electrical biasing. Phonon calculations using DFT will provide a basis for interpreting Raman spectra. This coherent framework involving synthesis, characterization, and computation will result in a broad scientific impact for energy related applications. The ability to develop new H-TMD/Cs will enhance a range of applications that include batteries, catalysts, switches, sensors, quantum computing components and smart coatings.

2-Dimensional Materials↗
DOE OSTI2020

Status and Challenges of Density Functional Theory

Here, we discuss some of the challenges facing density functional theory (DFT) and recent progress in DFT for both ground and excited electronic states. We discuss key aspects of the results we have been able to obtain with the strategy of designing density functionals to have various ingredients and functional forms that are then optimized to accurately predict various types of properties and systems with as much universality as possible. Finally, we make specific recommendations of approximate density functionals that are well suited for particular kinds of applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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

Unveiling the Role of Surface Ir-Oxo Species in O 2 Evolution at IrO 2 Electrocatalysts via Embedded Cluster Multireference Calculations

Understanding the mechanisms driving the oxygen evolution reaction (OER) on iridium oxide (IrO 2 )-based catalysts is essential to improving their performance and enabling an actual scale-up of water-splitting photoelectrochemical cells. The mechanistic pathways at IrO 2 interfaces have been extensively investigated computationally using density functional theory (DFT), which predicts a high-energy barrier for the last step of the OER of molecular oxygen detachment and release from the catalyst surface. Nevertheless, surface O 2 over- and under-binding results by standard generalized gradient approximation and hybrid density functionals, respectively, call for further analysis of this crucial step via multireference methods. Aiming at unveiling the nature of such a barrier, we hereby address the formation of O 2 from the most-stable IrO 2 (110) surface with both periodic DFT and an electrostatic embedded cluster approach at the n-electron valence-state perturbation theory. With this multireference approach, we find a value for the aforementioned energy barrier that is much closer to experimental indications than DFT ones. Here, an in-depth analysis of the involved molecular orbitals suggests that the origin of this barrier is related to the breaking of a π interaction between O 2 and Ir surface atom and to a significant additional O 2 interaction with adjacent electrophilic Ir-oxo species, which is present under experimental operating conditions. Besides shedding light on the mechanism of the OER on IrO 2 , these findings point out the importance of multireference methods for dissecting complex reactions at electrocatalytic interfaces and pave the route for further investigations with effective embedding approaches.

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

Atomic Manipulation of Single Erbium on GaAs(110): From Adatom Motion to Creation and Control of Bistable Substitutions

We demonstrate atomic-scale control over the position and configuration of single erbium (Er) atoms at the GaAs(110) surface using scanning tunneling microscopy (STM). By applying voltage pulses from the STM tip, we drive Er adatoms to move sequentially among three distinct adsorption sites and controllably substitute into Ga lattice sites. The resulting substitutional Er atoms exhibit two isoelectronic configurations that differ by less than one angstrom in lateral position and can be reversibly switched by additional voltage pulses. Differential conductance spectroscopy shows differences in the unoccupied local electronic states for the two substitutional configurations, and an absence of mid-gap states. Preliminary density functional theory (DFT) calculations support these findings, identifying the most stable adsorption and substitutional sites, their relative binding energies, charge states, and local density of states (LDOS) characteristics. Together, the experimental and theoretical results establish a method for precise, reversible manipulation of rare-earth dopants at semiconductor surfaces, opening a pathway to engineer atomic-scale quantum and optoelectronic functionalities.

Poche, Steven [Ohio State University]↗