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First-Principles Simulations of X-ray Transient Absorption for Probing Attosecond Electron Dynamics
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Investigation of Electrocatalytic CO 2 Reduction on MXene Materials via First-Principles Simulations
Computational studies of CO 2 reduction to yield various products were carried out on the basal plane and edges of different MXene materials. The impact of vacancies upon Mo 2 TiC 2 T x , W 2 TiC 2 T x , and Ti 3 C 2 T x (T x = O and OH) was also examined for both edge and basal sites. Initial calibrations were carried out to generate surfaces with optimal oxide/hydroxide ratios and proper termination sites upon which various vacancy sites were explored to ensure an accurate model of the surfaces’ resting states. From this work, Mo 2 TiC 2 O was determined to exhibit the lowest theoretical overpotential for methane as determined by volcano plot analyses. At a large enough vacancy concentration, the CO 2 reduction reaction (CO 2 RR) is predicted to outcompete the hydrogen evolution reaction (HER) as the predominant reaction on the surface. In conclusion, when examining the edge of Mo 2 TiC 2 O, stronger CO 2 binding was exhibited to such an extent that the reaction was predicted to terminate after the generation of formate on the edge.
Interactions of CO 2 Anion Radicals with Electrolyte Environments from First-Principles Simulations
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Investigation of local distortion effects on X-ray absorption of ferroelectric perovskites from first principles simulations
Understanding the role of ferroelectric polarization in modulating the electronic and structural properties of crystals is critical for advancing these materials for overcoming various technological and scientific challenges. However, due to difficulties in performing experimental methods with the required resolution, or in interpreting the results of methods therein, the nanoscale morphology and response of these surfaces to external electric fields has not been properly elaborated. Here, in this work, we investigate the effect of ferroelectric polarization and local distortions in a BaTiO 3 perovskite, using two widely used computational approaches which treat the many-body nature of X-ray excitations using different philosophies, namely the many-body, delta-self-consistent-field determinant (mb-ΔSCF) and the Bethe–Salpeter equation (BSE) approaches. We show that in agreement with our experiments, both approaches consistently predict higher excitations of the main peak in the O–K edge for the surface with upward polarization. However, the mb-ΔSCF approach mostly fails to capture the L 2,3 separations at the Ti–L edge, due to the absence of spin–orbit coupling in Kohn–Sham density functional theory (KS-DFT) at the generalized gradient approximation level. On the other hand, and most promising, we show that application of the GW/BSE approach successfully reproduces the experimental XAS, both the relative peak intensities as well as the L 2,3 separations at the Ti–L edges upon ferroelectric switching. Thus simulated XAS is shown to be a powerful method for capturing the nanoscale structure of complex materials, and we underscore the need for many-body perturbation approaches, with explicit consideration of core-hole and multiplet effects, for capturing the essential physics in these systems.
First principles simulations of MgO(100) surface hydration at ambient conditions
Developing a better understanding of water ordering and hydroxylation at oxide mineral surfaces is important across a breath of application spaces.
Prediction challenge: First principles simulation of the ultrafast electron diffraction spectrum of cyclobutanone
Computer simulation has long been an essential partner of ultrafast experiments, allowing the assignment of microscopic mechanistic detail to low-dimensional spectroscopic data. However, the ability of theory to make a priori predictions of ultrafast experimental results is relatively untested. Herein, as a part of a community challenge, we attempt to predict the signal of an upcoming ultrafast photochemical experiment using state-of-the-art theory in the context of preexisting experimental data. Specifically, we employ ab initio Ehrenfest with collapse to a block mixed quantum–classical simulations to describe the real-time evolution of the electrons and nuclei of cyclobutanone following excitation to the 3s Rydberg state. The gas-phase ultrafast electron diffraction (GUED) signal is simulated for direct comparison to an upcoming experiment at the Stanford Linear Accelerator Laboratory. Following initial ring-opening, dissociation via two distinct channels is observed: the C3 dissociation channel, producing cyclopropane and CO, and the C2 channel, producing CH2CO and C2H4. Direct calculations of the GUED signal indicate how the ring-opened intermediate, the C2 products, and the C3 products can be discriminated in the GUED signal. We also report an a priori analysis of anticipated errors in our predictions: without knowledge of the experimental result, which features of the spectrum do we feel confident we have predicted correctly, and which might we have wrong?
Transport in high-performance plasmas of the TJ-II stellarator: from first-principles simulations to experimental validation
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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.
First-principles simulation of a shocked H-He mixture along the principal Hugoniot
Recent laser-shock experiments on an H–He mixture containing 11% helium (atomic fraction) have suggested the presence of an immiscibility region inside Jupiter. Reflectivity measurements were used as the primary diagnostic of H–He demixing, with discontinuities in the optical reflectivity proposed as a signature of phase separation under conditions relevant to Jupiter's interior. Here, we investigate shock-compressed H–He using ab initio molecular dynamics simulations with optical properties evaluated within the Kubo–Greenwood formalism. The equation of state and ionic configurations were obtained using the thermal Tr 2 SCANL meta-GGA exchange–correlation (XC) functional, while optical properties were computed using the recently developed RS-KDT0 range-separated thermal hybrid XC, which provides state-of-the-art accuracy for band-gap predictions in the warm dense matter regime. The calculated reflectivity shows overall good agreement with experimental measurements; however, no discontinuity is observed at elevated temperatures. Moreover, the reflectivity predictions for the mixed system are consistent with the experimental measurements in the temperature range where the mixture is inferred to be demixed. Furthermore, these results suggest that reflectivity alone may not provide a unique or sensitive diagnostic of H–He demixing at low helium concentrations under these conditions.
Electronic structure of pristine and Ni-substituted La Fe O 3 from near edge x-ray absorption fine structure experiments and first-principles simulations
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First Principles Simulations of Electrified Interfaces in Electrochemistry
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Deep learning based surrogate models for first-principles global simulations of fusion plasmas
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Equation of state of hot, dense magnesium derived with first-principles computer simulations
Using two first-principles computer simulation techniques, path integral Monte Carlo and density functional theory molecular dynamics, we derive the equation of state of magnesium in the regime of warm dense matter, with densities ranging from 0.43 to 86.11 g cm –3 and temperatures from 20,000 K to 5×10 8 K. These conditions are relevant for the interiors of giant planets and stars as well as for shock compression measurements and inertial confinement fusion experiments. Here, we study ionization mechanisms and the electronic structure of magnesium as a function of density and temperature. We show that the L shell electrons, 2s and 2p energy bands, merge at high densities. This results in gradual ionization of the L-shell with increasing density and temperature. In this regard, Mg differs from MgO, which is also reflected in the shape of its principal shock Hugoniot curve. For Mg, we predict a single broad pressure-temperature region, where the shock compression ratio is approximately 4.9. Mg thus differs from Si and Al plasmas that exhibit two well-separated compression maxima on the Hugoniot curve for L and K shell ionizations. Finally, we study multiple shocks and effects of preheat and precompression.
First benchmarked electron cooling simulations from first principles
We present the first microscopic electron cooling simulations from first principles with accurate prediction of cooling time. These simulations were performed using our previously developed numerical method, PHAD, which is the first efficient large-scale collisional numerical method in beam physics. The simulation results are benchmarked with the experimental data of the low energy bunched electron cooling of ion beams at the storage ring CSRm at the IMP facility in China. Here, we have accurately considered the nonlinear dynamics in the whole accelerator system in addition to the electron cooling section. As a result, our simulations correctly reproduced cooling times of the experiments from first principles and without any tuning or fitting parameters in the code.
Elucidating the temperature and density dependence of silver chloride hydration numbers in high-temperature water vapor: A first-principles molecular simulation study
Hydration numbers of metal complexes in low-density aqueous solutions are required for developing geochemical models for ore-forming metals and for designing supercritical desalination processes. In this study, we investigate the temperature and density dependence of the hydration numbers of silver chloride at 623 K, 673 K, and 713 K and densities of 10–100 kg/m 3 . Experimental estimates of the hydration number in the literature for AgCl at these conditions are inconclusive and possibly contradictory as to the temperature and density dependence. First-principles molecular simulation presents an attractive alternative to experimental measurements. Specifically, recent work shows that machine-learning-accelerated nested Monte Carlo simulations provide reliable estimates for the hydration numbers of CuCl at 623 K from 10 to 100 kg/m 3 . Using the same technique, we find a monotonic temperature dependence, with the hydration number decreasing slightly with increasing temperature. In addition, the simulation-predicted hydration numbers steadily increase with increasing density. These temperature and density trends are in agreement with certain experimental data sets. Therefore, this work demonstrates how first-principles Monte Carlo simulations assist in resolving discrepancies between experimental data sets. Our simulation results also correctly predict that the hydration number, and thus also the solubility, of AgCl is lower than that of CuCl under the same conditions. Furthermore, the bond length and angle formed between the water complex and AgCl differ from those for CuCl, consistent with the lower solubility of AgCl.
Nonideal mixing effects in warm dense matter studied with first-principles computer simulations
Here, we study nonideal mixing effects in the regime of warm dense matter (WDM) by computing the shock Hugoniot curves of BN, MgO, and MgSiO 3 . First, we derive these curves from the equations of state (EOS) of the fully interacting systems, which were obtained using a combination of path integral Monte Carlo calculations at high temperature and density functional molecular dynamics simulations at lower temperatures. We then use the ideal mixing approximation at constant pressure and temperature to rederive these Hugoniot curves from the EOS tables of the individual elements. We find that the linear mixing approximation works remarkably well at temperatures above ~2 × 10 5 K, where the shock compression ratio exceeds ~3.2. The shape of the Hugoniot curve of each compound is well reproduced. Regions of increased shock compression, which emerge because of the ionization of L and K shell electrons, are well represented, and the maximum compression ratio of the Hugoniot curves is reproduced with high precision. Some deviations are seen near the onset of the L shell ionization regime, where ionization equilibrium in the fully interacting system cannot be well reproduced by the ideal mixing approximation. This approximation also breaks down at lower temperatures, where chemical bonds play an increasingly important role. However, the results imply that the equilibrium properties of binary and ternary mixtures in the regime of WDM can be derived from the EOS tables of the individual elements. This significantly simplifies the characterization of binary and ternary mixtures in the WDM and plasma phases, which otherwise requires large numbers of more computationally expensive first-principles computer simulations.