arXiv subjects

Ilya Grinberg

Publications and source records attributed to Ilya Grinberg.

At least 19 recordsLinked to original sources

arXiv2025

An atomistic approach for modeling of polarizability and Raman scattering of water clusters and liquid water

In this work, we develop a framework for atomistic modeling of electronic polarizability to predict the Raman spectra of hydrogen-bonded clusters and liquids from molecular dynamics (MD) simulations. The total polarizability of the system is assumed to arise from contributions of both the monomer unit and intermolecular interactions. The generalized bond-polarizability model (GBPM), inspired by the classic bond-polarizability model, effectively describes the electronic polarizability of a monomer. To account for the electronic polarizability arising from intermolecular interactions, we use a basis set of rapidly decaying functions of interatomic distances. We apply this model to calculate the electronic polarizability and Raman spectra of water clusters ((H2O)r, r = 2, 3, 4, 5, 6) and liquid water. The computational results are compared with the results of quantum-mechanical calculations for clusters and to experimental data for the liquid. It is demonstrated that this simple and physically motivated model, which relies on a small number of parameters, performs well for clusters at both low and high temperatures, capturing strong anharmonic effects. Moreover, its high transferability suggests its applicability to other water clusters. These results suggest that a hierarchical approach based on the Jacob's ladder of increasingly sophisticated and accurate atomistic polarizability models incorporating additional effects can be used for efficient modeling of Raman spectra from MD simulations of clusters, liquids and solids.

physics.chem-ph↗

arXiv2025

Generalized Bond Polarizability model for more accurate atomistic modeling of Raman spectra

Raman spectroscopy is an important tool for studies of molecules, liquids and solids. While Raman spectra can be obtained theoretically from molecular dynamics (MD) simulations, this requires the calculation of the electronic polarizability along the simulation trajectory. First-principles calculations of electronic polarizability are computationally expensive, motivating the development of atomistic models for the evaluation of the changes in the electronic polarizability with the changes in the atomic coordinates of the system. The bond polarizability model (BPM) is one of the oldest and simplest such atomistic models, but cannot reproduce the effects of angular vibrations, leading to inaccurate modeling of Raman spectra. Here, we demonstrate that the generalization of BPM through inclusion of terms for atom pairs that are traditionally considered to be not involved in bonding dramatically improves the accuracy of polarizability modeling and Raman spectra calculations. The generalized BPM (GBPM) reproduces the ab initio polarizability and Raman spectra for a range of tested molecules (SO2, H2S, H2O, NH3, CH4, CH3OH and CH3CH2OH) with high accuracy and also shows significantly improved agreement with ab initio results for the more complex ferroelectric BaTiO3 systems. For liquid water, the anisotropic Raman spectrum derived from atomistic MD simulations using GBPM evaluation of polarizability shows significantly improved agreement with the experimental spectrum compared to the spectrum derived using BPM. Thus, GBPM can be used for the modeling of Raman spectra using large-scale molecular dynamics and provides a good basis for the further development of atomistic polarizability models.

cond-mat.mtrl-sci↗

arXiv2024

Insights into Chemical and Structural Order at Planar Defects in a Functional Oxide Using Multislice Electron Ptychography

Switchable order parameters in ferroic materials are essential for functional electronic devices, yet disruptions of the ordering can take the form of planar boundaries or defects that exhibit distinct properties. Characterizing the structure of these boundaries is challenging due to their confined size and three-dimensional nature. Here, a chemical anti-phase boundary in the highly ordered double perovskite \ce{Pb2MgWO6} is investigated using multislice electron ptychography. The boundary is revealed to be inclined along the electron beam direction with a finite width of chemical intermixing. Additionally, regions at and near the boundary exhibit antiferroelectric-like displacements, contrasting with the predominantly paraelectric matrix. Spatial statistics and density functional theory calculations further indicate that despite their higher energy, chemical anti-phase boundaries form due to kinetic constraints during growth, with extended antiferroelectric-like distortions induced by the chemically frustrated environment in the proximity of the boundary. The three-dimensional imaging provides critical insights into the interplay between local chemistry and the polar environment, elucidating the role of anti-phase boundaries and their associated confined structural distortions and offering new opportunities for engineering ferroic thin films.

cond-mat.mtrl-sci↗

arXiv2024

Accuracy and limitations of the bond polarizability model in modeling of Raman scattering from molecular dynamics simulations

Calculation of Raman scattering from molecular dynamics (MD) simulations requires accurate modeling of the evolution of the electronic polarizability of the system along its MD trajectory. For large systems, this necessitates the use of atomistic models to represent the dependence of electronic polarizability on atomic coordinates. The bond polarizability model (BPM) is the simplest such model and has been used for modeling the Raman spectra of molecular systems but has not been applied to solid-state systems. Here, we systematically investigate the accuracy and limitations of the BPM parameterized from density functional theory (DFT) results for a series of simple molecules such as CO2, SO2, H2S, H2O, NH3, and CH4, the more complex CH2O, CH3OH and CH3CH2OH and thiophene molecules and the BaTiO3 and CsPbBr3 perovskite solids. We find that BPM can reliably reproduce the overall features of the Raman spectra such as shifts of peak positions. However, with the exception of highly symmetric systems, the assumption of non-interacting bonds limits the quantitative accuracy of the BPM; this assumption also leads to qualitatively inaccurate polarizability evolution and Raman spectra for systems where large deviations from the ground state structure are present.

cond-mat.mtrl-sci↗

arXiv2023

Bonding-aware Materials Representation for Deep Learning Atomistic Models

Deep potentials for molecular dynamics (MD) achieve first-principles accuracy at much lower computational cost. However, their use in large length- and time-scale simulations is limited by their lower speeds compared to analytical atomistic potentials, primarily due to network complexity and long embedding time. Here, based on the moments theorem, we develop a chemical-bonding-aware embedding for neural network potentials that achieve state-of-the-art accuracy in forces and local electronic density of states prediction with an ultrasmall 16x32 neural network resulting in significantly lower computational cost.

cond-mat.mtrl-sci↗

arXiv2023

An atomistic model of electronic polarizability for calculation of Raman scattering from large-scale MD simulations

The application of molecular dynamics (MD) simulations to the interpretation of Raman scattering spectra is hindered by inability of atomistic simulations to account for the dynamic evolution of electronic polarizability, requiring the use of either ab initio method or parameterization of machine learning models. More broadly, the dynamic evolution of electronic-structure-derived properties cannot be treated by the current atomistic models. Here, we report a simple, physically-based atomistic model with few (maximum 10 parameters for the systems considered here) adjustable parameters that can accurately represent the changes in the electronic polarizability tensor for molecules and solid-state systems. Due to its compactness, the model can be applied for simulations of Raman spectra of large (~ 1,000,000-atom) systems with modest computational cost. To demonstrate its accuracy, the model is applied to the CO2 molecule, water clusters, and BaTiO3 and CsPbBr3 perovskites and shows good agreement with ab-initio-derived and experimental polarizability tensor and Raman data. The atomistic nature of the model enables local analysis of the contributions to Raman spectra, paving the way for the application of MD simulations for the interpretation of Raman spectroscopy results. Furthermore, our successful atomistic representation of the evolution of electronic polarizability suggests that the evolution of electronic structure and its derivative properties can be represented by atomistic models, opening up the possibility of studies of electronic-structure-dependent properties using large-scale atomistic simulations.

cond-mat.mtrl-sci↗

arXiv2023

Identification of high-reliability regions of machine learning predictions in materials science using transparent conducting oxides and perovskites as examples

Progress in the application of machine learning (ML) methods to materials design is hindered by the lack of understanding of the reliability of ML predictions, in particular for the application of ML to small data sets often found in materials science. Using ML prediction for transparent conductor oxide formation energy and band gap, dilute solute diffusion, and perovskite formation energy, band gap and lattice parameter as examples, we demonstrate that 1) analysis of ML results by construction of a convex hull in feature space that encloses accurately predicted systems can be used to identify regions in feature space for which ML predictions are highly reliable 2) analysis of the systems enclosed by the convex hull can be used to extract physical understanding and 3) materials that satisfy all well-known chemical and physical principles that make a material physically reasonable are likely to be similar and show strong relationships between the properties of interest and the standard features used in ML. We also show that similar to the composition-structure-property relationships, inclusion in the ML training data set of materials from classes with different chemical properties will not be beneficial and will slightly decrease the accuracy of ML prediction and that reliable results likely will be obtained by ML model for narrow classes of similar materials even in the case where the ML model will show large errors on the dataset consisting of several classes of materials. Our work suggests that analysis of the error distributions of ML predictions will be beneficial for the further development of the application of ML methods in material science.

cond-mat.mtrl-sci↗

arXiv2023

Distance-based Analysis of Machine Learning Prediction Reliability for Datasets in Materials Science and Other Fields

Despite successful use in a wide variety of disciplines for data analysis and prediction, machine learning (ML) methods suffer from a lack of understanding of the reliability of predictions due to the lack of transparency and black-box nature of ML models. In materials science and other fields, typical ML model results include a significant number of low-quality predictions. This problem is known to be particularly acute for target systems which differ significantly from the data used for ML model training. However, to date, a general method for characterization of the difference between the predicted and training system has not been available. Here, we show that a simple metric based on Euclidean feature space distance and sampling density allows effective separation of the accurately predicted data points from data points with poor prediction accuracy. We show that the metric effectiveness is enhanced by the decorrelation of the features using Gram-Schmidt orthogonalization. To demonstrate the generality of the method, we apply it to support vector regression models for various small data sets in materials science and other fields. Our method is computationally simple, can be used with any ML learning method and enables analysis of the sources of the ML prediction errors. Therefore, it is suitable for use as a standard technique for the estimation of ML prediction reliability for small data sets and as a tool for data set design.

cond-mat.mtrl-sci↗

arXiv2022

Strong Bulk Photovoltaic Effect in Planar Barium Titanate Thin Films

The bulk photovoltaic effect (BPE) leads to the generation of a photocurrent from an asymmetric material. Despite drawing much attention due to its ability to generate photovoltages above the band gap ($E_g$), it is considered a weak effect due to the low generated photocurrents. Here, we show that a remarkably high photoresponse can be achieved by exploiting the BPE in simple planar BaTiO$_3$ (BTO) films, solely by tuning their fundamental ferroelectric properties via strain and growth orientation induced by epitaxial growth on different substrates. We find a non-monotonic dependence of the responsivity ($R_{\rm SC}$) on the ferroelectric polarization ($P$) and obtain a remarkably high BPE coefficient ($β$) of $\approx$10$^{-2}$ 1/V, which to the best of our knowledge is the highest reported to date for standard planar BTO thin films. We show that the standard first-principles-based descriptions of BPE in bulk materials cannot account for the photocurrent trends observed for our films and therefore propose a novel mechanism that elucidates the fundamental relationship between $P$ and responsivity in ferroelectric thin films. Our results suggest that practical applications of ferroelectric photovoltaics in standard planar film geometries can be achieved through careful joint optimization of the bulk structure, light absorption, and electrode-absorber interface properties.

cond-mat.mtrl-sci↗

arXiv2021

Advancing from phenomenological to predictive theory of ferroelectric oxide solution properties through consideration of domain walls

Prediction of properties from composition is a fundamental goal of materials science and can greatly accelerate development of functional materials. It is particularly relevant for ferroelectric perovskite solid solutions where compositional variation is a primary tool for materials design. To advance beyond the commonly used Landau-Ginzburg-Devonshire and density functional theory methods that despite their power are not predictive, we elucidate the key interactions that govern ferroelectrics using 5-atom bulk unit cells and non-ground-state defect-like ferroelectric domain walls as a simple as possible but not simpler model systems. We also develop a theory relating properties at several different length scales that provides a unified framework for the prediction of ferroelectric, antiferroelectric and ferroelectric phase stabilities and the key transition temperature, coercive field and polarization properties from composition. The elucidated physically meaningful relationships enable rapid identification of promising piezoelectric and dielectric materials.

cond-mat.mtrl-sci↗

arXiv2018

Graph-based Preconditioning Conjugate Gradient Algorithm for N-1 Contingency Analysis

Contingency analysis (CA) plays a critical role to guarantee operation security in the modern power systems. With the high penetration of renewable energy, a real-time and comprehensive N-1 CA is needed as a power system analysis tool to ensure system security. In this paper, a graph-based preconditioning conjugate gradient (GPCG) approach is proposed for the nodal parallel computing in N-1 CA. To pursue a higher performance in the practical application, the coefficient matrix of the base case is used as the incomplete LU (ILU) preconditioner for each N-1 scenario. Additionally, the re-dispatch strategy is employed to handle the islanding issues in CA. Finally, computation performance of the proposed GPCG approach is tested on a real provincial system in China.

cs.DC↗

arXiv2017

First-principles studies of the local structure and relaxor behavior of Pb(Mg$_{1/3}$Nb$_{2/3}$)O$_3$-PbTiO$_3$-derived ferroelectric perovskite solid solutions

We have investigated the effect of transition metal dopants on the local structure of the prototypical 0.75 Pb(Mg$_{1/3}$Nb$_{2/3}$)O$_3$-0.25 PbTiO$_3$ relaxor ferroelectric. We find that these dopants give rise to very different local structure and other physical properties. For example, when Mg is partially substituted by Cu or Zn, the displacement of Cu or Zn is much larger than that of Mg, and is even comparable to that of Nb. The polarization of these systems is also increased, especially for the Cu-doped solution, due to the large polarizability of Cu and Zn. As a result, the predicted maximum dielectric constant temperatures ($T_m$) are increased. On the other hand, the replacement of a Ti atom with a Mo or Tc dramatically decreases the displacements of the cations and the polarization, and thus, the $T_m$ values are also substantially decreased. The higher $T_m$ cannot be explained by the conventional argument based on the ionic radii of the cations. Furthermore, we find that Cu, Mo, or Tc doping increase the cations displacement disorder. The effect of the dopants on the temperature dispersion $ΔT_m$, which is the change of $T_m$ for different frequencies, is also discussed. Our findings lay the foundation for further investigations of unexplored dopants.

cond-mat.mtrl-sci↗

arXiv2016

Atomistic Description for Temperature-Driven Phase Transitions in BaTiO$_3$

Barium titanate (BaTiO$_3$) is a prototypical ferroelectric perovskite that undergoes the rhombohedral-orthorhombic-tetragonal-cubic phase transitions as the temperature increases. In this work, we develop a classical interatomic potential for BaTiO$_3$ within the framework of the bond-valence theory. The force field is parameterized from first-principles results, enabling accurate large-scale molecular dynamics (MD) simulations at finite temperatures. Our model potential for BaTiO$_3$ reproduces the temperature-driven phase transitions in isobaric-isothermal ensemble (NPT) MD simulations. This potential allows the analysis of BaTiO$_3$ structures with atomic resolution. By analyzing the local displacements of Ti atoms, we demonstrate that the phase transitions of BaTiO$_3$ exhibit a mix of order-disorder and displacive characters. Besides, from detailed observation of structural dynamics during phase transition, we discover that the global phase transition is associated with changes in the equilibrium value and fluctuations of each polarization component, including the ones already averaging to zero, Contrary to the conventional understanding that temperature increase generally causes bond-softening transition, the x polarization component exhibits a bond-hardening character during the orthorhombic to tetragonal transition. These results provide further insights about the temperature-driven phase transitions in BaTiO$_3$.

cond-mat.mtrl-sci↗

arXiv2015

Photoferroelectric and Photopiezoelectric Properties of Organometal Halide Perovskites

Piezoelectrics play a critical role in various applications. The permanent dipole associated with the molecular cations in organometal-halide perovskites (OMHPs) may lead to spontaneous polarization and thus piezoelectricity. Here, we explore the piezoelectric properties of OMHPs with density functional theory. We find that the piezoelectric coefficient depends sensitively on the molecular ordering, and that the experimentally observed light-enhanced piezoelectricity is due to to a non-polar to polar structural transition. By comparing OMHPs with different atomic substitutions in the $ABX_3$ architecture, we find that the displacement of the $B$-site cation contributes to nearly all the piezoelectric response, and that the competition between $A$-$X$ hydrogen bond and $B$-$X$ metal-halide bond in OMHPs controls the piezoelectric properties. These results highlight the potential of the OMHP architecture for designing new functional photoferroelectrics and photopiezoelectrics.

cond-mat.mtrl-sci↗

arXiv2015

Bulk photovoltaic effect enhancement via electrostatic control in layered ferroelectrics

The correlation between the shift current mechanism for the bulk photovoltaic effect (BPVE) and the structural and electronic properties of ferroelectric perovskite oxides is not well understood. Here, we study and engineer the shift current photovoltaic effect using a visible-light-absorbing ferroelectric Pb(Ni$_{x}$Ti$_{1-x}$)O$_{3-x}$ solid solution from first principles. We show that the covalent orbital character dicates the direction, magnitude, and onset energy of shift current in a predictable fashion. In particular, we find that the shift current response can be enhanced via electrostatic control in layered ferroelectrics, as bound charges face a stronger impetus to screen the electric field in a thicker material, delocalizing electron densities. This heterogeneous layered structure with alternative photocurrent generating and insulating layers is ideal for BPVE applications.

cond-mat.mtrl-sci↗

arXiv2014

The Structural Diversity of ABS3 Compounds with d0 Electronic Configuration for the B-cation

We use first-principles density functional theory (DFT) within the local density approx- imation (LDA) to ascertain the ground state structure of real and theoretical compounds with the formula ABS3 (A = K, Rb, Cs, Ca, Sr, Ba, Tl, Sn, Pb, and Bi; and B = Sc, Y, Ti, Zr, V, and Nb) under the constraint that B must have a d0 electronic configuration. Our findings indicate that none of these AB combinations prefer a perovskite ground state with corner-sharing BS6 octahedra, but that they prefer phases with either edge- or face-sharing motifs. Further, a simple two-dimensional structure field map created from A and B ionic radii provides a neat demarcation between combinations preferring face-sharing versus edge- sharing phases for most of these combinations. We then show that by modifying the common Goldschmidt tolerance factor with a multiplicative term based on the electronegativity dif- ference between A and S, the demarcation between predicted edge-sharing and face-sharing ground state phases is enhanced. We also demonstrate that, by calculating the free energy contribution of phonons, some of these compounds may assume multiple phases as synthesis temperatures are altered, or as ambient temperatures rise or fall.

cond-mat.mtrl-sci↗

arXiv2014

Density Functional Theory Study Of Hypothetical PbTiO3-Based Oxysulfides

Using density functional theory (DFT) within the local density approximation (LDA), we calculate the physical and electronic properties of PbTiO3 (PTO) and a series of hypothetical compounds PbTiO3-xSx x = 0.2, 0.25, 0.33, 0.5, 1, 2, and 3 arranged in the corner-sharing cubic perovskite structure. We determine that replacing the apical oxygen atom in the PTO tetragonal unit cell with a sulfur atom reduces the x = 0 LDA calculated band gap of 1.47 eV to 0.43 - 0.67 eV for x = 0.2 - 1 and increases the polarization. PBE0 and GW methods predict that the hypothetical compositions x = 0.2 to x = 2 will have band gaps in the visible range. For all values of x < 2, the oxysulfide perovskite retains the tetragonal phase of PbTiO3, and the a-lattice parameter remains within 2.5% of the oxide. Thermodynamic analysis indicates that chemical routes using high temperature gas, such as H2S and CS2, can be used to substitute O for S in PTO for the compositions x = 0.2 - 0.5.

cond-mat.mtrl-sci↗

arXiv2013

Exploration of the momentum of ferroelectric domain walls via molecular dynamics simulations

The motion of ferroelectric domain walls (DW) is critical for various technological applications of ferroelectric materials. One important question that is of interest both scientifically and technologically is whether the ferroelectric DW has momentum. To address this problem, we performed canonical ensemble molecular dynamics simulations of 180$^\circ$ and 90$^\circ$ DWs under applied electric field. Examination of the evolution of the polarization and local structure of DWs reveals that they stop moving after the removal of electric field. Thus, our computational study shows that ferroelectric domain walls do not have momentum.

cond-mat.mtrl-sci↗