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At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Defect modeling in semiconductors: the role of first principles simulations and machine learning

Abstract Point defects in semiconductors dictate their electronic and optical properties. Vacancies, interstitials, substitutional defects, and defect complexes can form in the semiconductor lattice and significantly impact its performance in applications such as solar absorption, light emission, electronics, and catalysis. Understanding the nature and energetics of point defects is essential for the design and optimization of next-generation semiconductor technologies. Here, we provide a comprehensive overview of the current state of research on point defects in semiconductors, focusing on the application of density functional theory (DFT) and machine learning (ML) in accelerating the prediction and understanding of defect properties. DFT has been instrumental in accurately calculating defect formation energies, charge transition levels, and other defect-related properties such as carrier recombination rates and lifetimes, and ion migration barriers. ML techniques, particularly neural networks, have emerged as powerful tools for enabling rapid prediction of defect properties at DFT-accuracy in order to overcome the expense of using large supercells and advanced functionals. We begin this article with a discussion of different types of point defects and complexes, their impact on semiconductor properties, and the experimental and DFT approaches typically used for their characterization. Through multiple case studies, we explore how DFT has been successfully applied to understand defect behavior across a variety of semiconductors, and how ML approaches integrated with DFT can efficiently predict defect properties and facilitate the discovery of new materials with tailored defect behavior. Overall, the advent of ‘DFT+ML’ promises to drive advancements in semiconductor technology, catalysis, and renewable energy applications, paving the way for the development of high-performance semiconductors which are defect-tolerant or have desirable dopability.

Rahman, Md Habibur (ORCID:000000027705984X)↗
DOE OSTI2022

Monte-Carlo modeling of phonon thermal transport using DFT-based anisotropic dispersion relations over the full Brillouin zone

In this work, we present a Monte Carlo (MC) approach to solve the phonon Boltzmann transport equation (BTE) in which the anisotropic phonon dispersion relations over the full Brillouin zone (BZ) are used. In this approach, the discretization of the BZ used to compute the phonon relaxation time places constraints on the direction of scattered phonons in the real-space simulation domain. The phonon dispersion and phonon relaxation times are calculated using the density functional theory (DFT) approach. The modified MC approach is validated by a close examination of its ability to simulate phonon transport in both the ballistic and diffusive regimes for multiple materials including GaAs, InAs, ThO 2 , and α-U. In doing so, the phonon thermal conductivities from 100 K to 1000 K are calculated and compared with traditional non-transport solution of the phonon BTE. It is found that the phonon thermal conductivities of α-U and ThO 2 obtained from MC simulations using isotropic dispersion are larger than the values obtained using anisotropic phonon dispersion relations over the full BZ. The effect of phonon-defect scattering on the thermal conductivity of ThO 2 is also studied as an application of the current MC approach and found to agree with previously computed values in the literature. The MC solver developed here has been parallelized as a step to demonstrate its potential to solving computationally intensive phonon thermal transport problems at the mesoscale.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ab-initio vibrational properties of WTe2 and Li0.5WTe2

We present ab-initio calculations of the Td and 1T’ phases of WTe2 and the Td’ phase of Li 0.5 WTe 2 using density functional theory (DFT). These include lattice relaxations, total energy calculations, phonon calculations, and calculations of elastic constants. We also provide a detailed view of the transformation from Td to Td’ using a non-primitive representation of the Td lattice that more closely resembles the Td’ structure. The details presented here are intended as a supplement to a forthcoming experimental-computational paper on lithiated WTe 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

First-principles study on the mechanical and thermodynamic properties of MoNbTaTiW

Refractory high-entropy alloys (RHEAs) are emerging as new materials for high temperature structural applications because of their stable mechanical and thermal properties at temperatures higher than 2273 K. In this study, the mechanical properties of MoNbTaTiW REDEA are examined by applying calculations based on first-principles density functional theory (DFT) and using a large unit cell with 100 randomized atoms. The phase calculation of MoNbTaTiW with CALPHAD method shows the existence of a stable body-centered cubic structure at a high temperature and a hexagonal closely packed phase at a low temperature. The predicted phase, shear modulus, Young’s modulus, Poisson’s ratio, and hardness values are consistent with available experimental results. The linear thermal expansion coefficient, vibrational entropy, and vibrational heat capacity of MoNbTaTiW RHEA are investigated in accordance with Debye-Grüneisen theory. These results may provide a basis for future research related to the application of RHEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Density-functional theory of material design: fundamentals and applications-I

This article is part-I of a review of density-functional theory (DFT) that is the most widely used method for calculating electronic structure of materials. The accuracy and ease of numerical implementation of DFT methods has resulted in its extensive use for materials design and discovery and has thus ushered in the new field of computational material science. In this article, we start with an introduction to Schrödinger equation and methods of its solutions. After presenting exact results for some well-known systems, difficulties encountered in solving the equation for interacting electrons are described. How these difficulties are handled using the variational principle for the energy to obtain approximate solutions of the Schrödinger equation is discussed. The resulting Hartree and Hartree–Fock theories are presented along with results they give for atomic and solid-state systems. We then describe Thomas–Fermi theory and its extensions which were the initial attempts to formulate many-electron problem in terms of electronic density of a system. Having described these theories, we introduce modern DFT by discussing Hohenberg–Kohn theorems that form its foundations. We then go on to discuss Kohn–Sham (KS) formulation of DFT in its exact form. Next, local density approximation (LDA) is introduced and solutions of KS equation for some representative systems, obtained using the LDA, are presented. We end part-I of the review describing the contents of part-II.

36 MATERIALS SCIENCE↗
DOE OSTI2024

First-principles calculation of Hubbard U for Terbium metal under high pressure

Abstract Using density functional theory (DFT) and linear response approaches, we compute the on-site Hubbard interaction U of elemental Terbium (Tb) metal in the pressure range ∼ 0–65 GPa. The resulting first-principles U values with experimental crystal structures enable us to examine the magnetic properties of Tb using a DFT+U method. The lowest-energy magnetic states in our calculations for different high-pressure Tb phases—including hcp, α -Sm, and dhcp—are found to be compatible with the corresponding magnetic ordering vectors reported in experiments. The result shows that the inclusion of Hubbard U substantially improves the accuracy and efficiency in modeling correlated rare-earth materials. Our study also provides the necessary U information for other quantum many-body techniques to study Tb under extreme pressure conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

DFT-based mesoscopic interactions of N adatoms on Cu(100)

The first-principles density functional theory (DFT) method is used to directly calculate the interactions of N atoms of various configurations on Cu(100) surfaces. This allows us to derive a mesoscopic substratemediated interaction model. We find that, for these Cu(100)-supported two-dimensional N clusters, oscillating substrate-mediated interactions obtained from an elastic eigenvector approach including a mesoscopic interacting range (called the mesoscopic model) have reasonable agreement with the DFT results. The DFT periodic boundary conditions are properly mapped into the mesoscopic model. The model is used to analyze the energies of c(2×2) square islands independent of their sizes. Previous experimental studies have shown that, in the low coverage region, N atoms agglomerate to isolated square islands of about 5 nm × 5 nm in size with a c(2×2) structure. With increasing coverage, those islands form regular patterns but do not touch below about 0.4 monolayers. From previous experiments and calculations, the square island pattern shows significant elastic effects which are now confirmed.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Intrinsic Defect-Induced Local Semiconducting-to-Metallic Regions Within Monolayer 1T-TiS2 Displayed by First-Principles Calculations and Scanning Tunneling Microscopy

Using density functional theory (DFT) and scanning tunneling microscopy (STM), the intrinsic point defects, formation energy, and electronic structure of 1T-TiS2 were investigated. Defect systems include single-atom vacancies, interstitial and adatom additions, and direct atomic substitution. Using a collective approach for analyzing realistic systems for point defect investigation, we provide a more straightforward comparison to the experimental measurements, reproducing more realistic environmental conditions related to thin film growth. STM images are compared to computationally simulated electron density images to identify specific geometries that result from favorable point defects. DFT suggests that titanium interstitials are the most energetically favorable intrinsic defect, and sulfur vacancies are more likely to form than titanium vacancies within this realistic analysis, which is in agreement with STM data. A pristine, stoichiometric monolayer system is calculated to have a direct band gap of 0.422 eV, which varies based on local point defects. Local semiconducting-to-metallic electronic transitions are predicted to occur based on the presence of Ti interstitials.

Keeney, P. J.↗
DOE OSTI2024

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, the development of new coating systems is hindered by the large design space and difficulty in predicting the properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate the thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict the phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate the accurate prediction of the anisotropy of the CTE in good agreement with the diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Analysis and prediction of reaction kinetics using the degree of rate control

“Degree of rate control” (DRC) analysis provides a quantitative approach for analysing the kinetics of multi-step reaction mechanisms that has been widely applied to both heterogeneous and homogeneous catalysis research, as well as electrocatalysis. The DRC of any given transition state or intermediate is defined as a partial derivative such that it approximately equals the fractional increase in net rate to the product of interest per differential decrease in its standard-state free energy for that species (÷RT), holding constant the standard-state free energies of all other transition states and intermediates. Even very complex mechanisms usually have only a few species with non-zero DRCs and are thus the species whose interactions with the catalyst most strongly affect the net rate. These key DRC values thus offer a simple and intuitive route to optimize catalyst materials, especially with the assistance of computational methods like density functional theory (DFT). These high-DRC species are also the species whose energetics must be most accurately measured or calculated to achieve an accurate kinetic model for any reaction mechanism. In simple cases with a single “rate-determining step”, the DRC for its transition state (TS) is + 1. Catalyst-bound intermediates, on the other hand, often have negative DRCs equal to a small integer times their fractional occupancy of catalyst sites. The apparent activation energy equals a weighted average of the standard-state enthalpies (relative to reactants) of all the species (intermediates, transition states and products) in the reaction mechanism, each weighted by its DRC (+RT). It has been shown that the apparent transfer coefficient in electrocatalysis, an inverted form of the Tafel slope, is a weighted average of the number of electrons transferred to generate each intermediate or product species in the mechanism, weighted again by the DRC. Quantitative analysis of kinetic isotope effects (KIEs, or the ratio of net rates for different reactant isotopes) in complex mechanisms has shown that the logarithm of the KIE equals the weighted average over all species in the mechanism of the difference between the two isotopes in their standard-state free energies (÷RT), again weighted by the DRC. The reaction orders with respect to fluid-phase concentrations of reactants, products and intermediates have also been proven to be directly related to DRCs. Thus, there are numerous experimental observables which equate to short linear combinations of DRCs, so that combinations of experimental measurements might provide access to DRC values. Since its invention for transition states in 1994 and its generalization to include intermediates in 2009, the DRC has thus far mainly been calculated for microkinetic models based either entirely on DFT or on DFT with the key energies (i.e., those for high-DRC species) being fine-tuned to match experiments. The relationships summarized in this work provide new opportunities for using experiments earlier in the development and optimization of microkinetic models that require input from computational catalysis.

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

Search for active and inactive ion insertion sites in organic crystalline materials

The position of mobile active and inactive ions, specifically ion insertion sites, within organic crystals, significantly affects the properties of organic materials used for energy storage and ionic transport. Identifying the positions of these atomic (and ionic) sites in an organic crystal is challenging, especially when the element has low X-ray scattering power, such as lithium (Li) and hydrogen, which are difficult to detect by powder X-ray diffraction. First-principles calculations, exemplified by density functional theory (DFT), are very practical for confirming the relative stability of ion positions in materials. However, the lack of effective strategies to identify ion sites in these organic crystalline frameworks renders this task extremely challenging. This work presents two algorithms: the (i) efficient location of ion insertion sites from extrema in electrostatic local potential and charge density (ELIISE), and the (ii) ElectRostatic InsertioN (ERIN), which leverage charge density and electrostatic potential fields accessed from first-principles calculations, combined with the Simultaneous Ion Insertion and Evaluation (SIIE) workflow. SIIE inserts all ions simultaneously—to determine ion positions in organic crystals. We demonstrate that these methods accurately reproduce known ion positions in 16 organic materials and identify previously overlooked low-energy sites in tetralithium 2,6-naphthalenedicarboxylate (Li4NDC), an organic electrode material, highlighting the importance of inserting all ions simultaneously, as in the SIIE workflow. These algorithms are also integrated with off-the-shelf machine learning potentials, yielding promising results comparable to first-principles findings.

Gopidi, Harshan Reddy [Argonne National Laboratory↗
DOE OSTI2022

Computational insights into the lattice dynamics of Pu(IV) oxalates

Despite its use in PuO 2 production, the structure of anhydrous Pu(C 2 O 4 ) 2 is still not completely understood. Recently, two candidate structures for Pu(C 2 O 4 ) 2 were proposed via density functional theory (DFT), after which the first experimental optical vibrational spectra were reported. Here, in this study, we calculated the lattice dynamics of the candidate structures using DFT and found that the primary difference between them is the presence of a vibrational mode near 1380 cm -1 in one structure. The frequency and optical activity of this mode agree well with the published experimental results, providing strong support for this calculated structure as that of anhydrous Pu(C 2 O 4 ) 2 .

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Growth of Cd 0.9 Zn 0.1 Te 1-y Se y Single Crystals for Room Temperature Gamma-Ray Detection

Quaternary Cd 0.9 Zn 0.1 Te 1-y Sey (CZTS) single crystals, a novel room-temperature nuclear radiation detector semiconductor material, have been grown using a modified vertical Bridgman method (VBM) and a travelling heater method (THM). The percentage concentration of selenium in the VBM-grown crystal was 3% and that in the THM-grown crystal was 2%. While the THM Frisch collar detector (4.4 × 4.4 × 10.7 mm 3 ) produced a highly resolved pulse height spectra (PHS) with a resolution of ~1.06% for 662-keV gamma rays without any correction, the VBM-grown detector (10 × 10 × 2 mm 3 ) offered a high energy resolution of ~2% after application of a digital biparametric correction. The high-resolution performance of these detectors has been attributed to the addition of Se in the Cd 0.9 Zn 0.1 Te (CZT) matrix. Ab-initio calculations based on density functional theory (DFT) also confirmed that the addition of Se in the CZT matrix helps to reduce the formation of TeCd and the TeZn anti-sites. The VBM-grown crystals were characterized using powder x-ray diffraction (XRD) and energy dispersive x-ray spectroscopy (EDS). While XRD results revealed sharp diffraction peaks confirming the crystalline nature of the grown crystal, the EDS results confirmed the targeted stoichiometry of the elemental composition. The bulk resistivity of the grown crystal was calculated to be ~3 × 10 10 Ω-cm from current-voltage characteristics recorded at room temperature in a planar configuration, ensuring that the grown CZTS crystals have low dark current as required for detector-grade crystals.

42 ENGINEERING↗
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 OSTI2022

CO 2 Hydrogenation to Methanol over Inverse ZrO 2 /Cu(111) Catalysts: The Fate of Methoxy under Dry and Wet Conditions

Understanding the surface chemistry of CH 3 O species is essential for the production of methanol by CO 2 hydrogenation over Cu-based heterogeneous catalysts, as it facilitates the rational design of more efficient conversion processes. Recent research has identified inverse ZrO 2 /Cu catalysts as highly active and selective systems for the transformation of CO 2 to methanol with a performance that can be better than that of commercial Cu/ZnO catalysts. Here, we employed synchrotron-based ambient pressure X-ray photoelectron spectroscopy (AP-XPS) and calculations based on density functional theory (DFT) to understand the fate of CH 3 O groups under dry and wet environments. AP-XPS spectra revealed that under CO 2 hydrogenation conditions, formate and methoxy are two key intermediates to produce methanol. Furthermore, there are three different types of reactive sites on the surface: One is active for methoxy adsorption, which is stable and responsible for the methanol synthesis; Another one transforms CO 2 into CO; and a third one is active for CO 2 and methoxy dissociation, leading to C and methane formation. The theoretical calculations indicate that CH 3 OH readily dissociates to CH 3 O species following a highly exothermic (ΔE = -20.99 kcal/mol) and barrierless process. The water produced by the reverse water-gas shift reaction (CO 2 + H 2 → H 2 O + CO) can prevent the decomposition of CH 3 O species. We discovered that by introducing a tiny amount of water vapor (2 × 10 -6 Torr) into the reaction chamber, the energy barrier for the reaction CH 3 O(ads) + H(ads) → CH 3 OH(gas) is dramatically reduced. AP-XPS and computational modelling showed that water is quite capable of extracting adsorbed methoxy to form gaseous methanol. With this in mind, one could boost the methanol selectivity by adding appropriate amounts of water or steam, which is an inexpensive and feasible solution for industrial operations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Implications of the fractional charge of hydroxide at the electrochemical interface

Rational design of materials that efficiently convert electrical energy into chemical bonds will ultimately depend on a thorough understanding of the electrochemical interface at the atomic level. Towards this goal, the use of density functional theory (DFT) at the generalized gradient approximation (GGA) level has been applied widely in the past 15 years. In the calculation of electrochemical reaction energetics using GGA-DFT, it is frequently implicitly assumed that ions in the Helmholtz plane have unit charge. However, the ion charge is observed to be fractional near the interface through both a capacitor model and through Bader charge partitioning. In this work, we show that this spurious charge transfer can be effectively mitigated by continuum charging of the electrolyte. Finally, we show that, similar to hydronium, the observed fractional charge of hydroxide is not due to a GGA level self-interaction error, as the partial charge is observed even when using hybrid level exchange–correlation functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Defect Diffusion Graph Neural Networks for Materials Discovery in High-Temperature Energy Applications

Here, the migration of crystallographic defects dictates material properties and performance for a plethora of technological applications. Density functional theory (DFT)-based nudged elastic band (NEB) calculations are a powerful computational technique for predicting defect migration activation energy barriers, yet they become prohibitively expensive for high-throughput screening of defect diffusivities. Without introducing hand-crafted (i.e., chemistry- or structure-specific) descriptors, we propose a generalized deep learning approach to train surrogate models for NEB energies of vacancy migration by hybridizing graph neural networks with transformer encoders and simply using pristine host structures as input. With sufficient training data, computationally efficient and simultaneous inference of vacancy defect thermodynamics and migration activation energies can be obtained to compute temperature-dependent vacancy diffusivities and to down-select candidates for more thorough DFT analysis or experiments. Thus, as we specifically demonstrate for potential water-splitting materials, candidates with desired defect thermodynamics, kinetics, and host stability properties can be more rapidly targeted from open-source databases of experimentally validated or hypothetical materials.

14 SOLAR ENERGY↗
DOE OSTI2022

Samarium: from a distorted-fcc phase to melting under dynamic compression using in-situ x-ray diffraction

Abstract Lattice and electronic structure interactions for f -electrons are fundamental challenges for lanthanide equation of state development. Difficulties in first-principles calculations, such as density functional theory (DFT), emphasize the need for well-characterized experimental data. Here, we measure in-situ x-ray diffraction of shocked samarium (Sm) and temperature along the Hugoniot for the first time, providing direct evidence for phase transitions. We report direct evidence of a distorted fcc (dfcc) phase at 23 GPa. Shocked samarium melts from the dfcc phase starting at 33 GPa (1333 K), with complete melt at 40 GPa (1468 K). Previous work indicated shock melt at 27 GPa (1200 K), underscoring the significance of x-ray measurements for detecting phase transitions. Interestingly, our observed melting is in sharp contrast with the melting reported by a diamond anvil cell study. These experimental data can tightly constrain first principles calculations and serve as key touchstones for equation of state modeling.

36 MATERIALS SCIENCE↗