arXiv subjects

Nafise Rezaei

Publications and source records attributed to Nafise Rezaei.

11 recordsLinked to original sources

arXiv2026

Pressure-Tunable Electronic and Magnonic Transport in Altermagnet La$_2$O$_3$Mn$_2$Se$_2$

Hydrostatic pressure provides a symmetry-preserving route to engineer electronic and magnonic transport in the correlated insulating altermagnet La$_2$O$_3$Mn$_2$Se$_2$. Using first-principles calculations combined with spin-Hamiltonian modeling, we show that compression from 0 to 40 GPa markedly enhances the inequivalence between the competing second-neighbor exchange interactions, increasing $|J_{2a}-J_{2b}|$ from 1.97 to 9.38 meV while preserving the compensated antiferromagnetic ground state. The resulting exchange anisotropy amplifies the momentum-dependent splitting between the two chiral magnon branches, yielding a nearly fourfold enhancement of the longitudinal magnon-driven spin Seebeck response at 100 K, from $3.68\times10^{-1}$ to $1.36$ meV/K. In contrast, hydrostatic pressure preserves the magnetic-symmetry selection rules governing the anomalous Hall effect while redistributing the electronic Berry curvature, producing pronounced energy-dependent sign reversals in the anomalous Hall conductivity. These results identify exchange anisotropy as the microscopic mechanism underlying the pressure-enhanced magnon response and establish hydrostatic pressure as an effective means of simultaneously controlling electronic and magnonic transport in insulating altermagnets.

cond-mat.mtrl-sci↗

arXiv2026

Complex Magnetic Behavior in RuO$_2$ Thin Films Driven by Strain and Substrate Effects

Ruthenium dioxide (RuO$_2$) has been proposed as a prototypical metallic $d$-wave altermagnet, a Néel-ordered compensated antiferromagnetic state exhibiting nonrelativistic momentum-dependent spin splitting; yet, its magnetic ground state remains controversial both theoretically and experimentally. Using comprehensive first-principles calculations, we investigate RuO$_2$ thin films with (110), (100), and (001) orientations, both (un)strained freestanding and supported on a TiO$_2$ substrate. We show that emergent magnetic moments in RuO$_2$ thin films are highly fragile, strongly influenced by strain, surface orientation, and atomic relaxation, while also being highly sensitive to the choice of the Brillouin-zone integration scheme. We find that none of the thin film structures considered can stabilize a compensated antiferromagnetic order; therefore, an altermagnetic ground state cannot be realized. Instead, substrate-supported RuO$_2$ films on TiO$_2$ exhibit pronounced layer- and site-dependent magnetic moment variations and incomplete compensation between the two antiferromagnetically coupled Ru moments, yielding a \emph{ferrimagnetic-like} behavior. On the other hand, freestanding RuO$_2$ films display complex magnetic structures depending on their orientation and applied strain, with distinct behavior at the surfaces and in the inner layers. Our results reconcile conflicting theoretical and experimental reports and underscore the sensitivity of RuO$_2$ magnetism to structural and methodological details.

cond-mat.mtrl-sci↗

arXiv2025

Benchmarking First-Principles Approaches for Extracting Magnetic Exchange Interactions

Magnetic exchange interactions govern the macroscopic magnetic behavior of solids and underpin both fundamental spin phenomena and emerging technologies. The accurate and efficient determination of these interactions is therefore critical for predictive modeling of magnetic materials. Here we present a systematic first-principles comparison of three widely used approaches-the Least-Squares Total Energy (LSTE), the Four-State Total Energy (FSTE), and the Green's function-based Liechtenstein \textit{et al.} (LKAG) methods-applied to thirteen antiferromagnetic compounds. We introduce an framework for identifying the minimal supercells required for an accurate exchange parameter extraction in the FSTE method, significantly reducing computational cost while preserving precision. Our results show that LSTE and FSTE yield nearly identical exchange parameters, whereas the LKAG method reproduces the dominant exchange interactions but exhibits quantitative deviations. A detailed analysis of computational efficiency versus accuracy reveals that the LSTE scheme offers the most favorable balance, establishing a general, reproducible, and scalable workflow for Heisenberg mapping, while the FSTE approach remains the most straightforward for extracting specific exchange interactions.

cond-mat.mtrl-sci↗

arXiv2025

Experimental Exchange Interaction Dataset for Magnetic Materials: Spin Waves to MC Simulations

Inelastic neutron scattering (INS) provides direct insights into microscopic magnetic interactions in crystalline materials, making it a valuable experimental technique in condensed matter physics and materials science. These interactions can be extracted by fitting spin wave dispersions to Heisenberg Hamiltonians using spin wave theory. However, such datasets are scattered across the literature and lack a standardized format, which limits their accessibility, reproducibility, and utility. In this work, we compile and standardize exchange interaction data obtained from INS experiments on nearly 100 magnetic materials. The resulting dataset includes exchange parameters expressed in a unified Heisenberg model format, visualizations of crystal structures with annotated exchange pathways, and Monte Carlo simulation files generated using the ESpinS code. We use these experimentally derived exchange interactions to compute magnetic transition temperatures ($T_c$) via classical Monte Carlo simulations. Furthermore, we examine the impact of the $(S+1)/S$ correction in the simulations and find it improves agreement with experimental $T_c$ values in most cases. All data and related resources are openly available through a public GitHub repository.

cond-mat.mtrl-sci↗

arXiv2025

Origin of $A$-type antiferromagnetism and chiral split magnons in altermagnetic $α$-MnTe

The origin of the $A$-type antiferromagnetic ordering, characterized by ferromagnetic layers coupling antiferromagnetically, in the prototype semiconductor altermagnet $α$-MnTe has been a topic of ongoing debate. Experimentally, $α$-MnTe exhibits an in-plane ferromagnetic exchange interaction, whereas previous \emph{ab initio} calculations predicted an antiferromagnetic interaction. In this paper, we resolve this discrepancy by considering an expanded set of magnetic configurations, which reveals a ferromagnetic in-plane exchange interaction in agreement with experimental findings. Additionally, we demonstrate that the 10th nearest-neighbor exchange interaction is directionally dependent, inducing a nonrelativistic chiral splitting in the magnon bands, as recently observed experimentally. We further show that applying a compressive strain may significantly enhance both nonrelativistic spin and chiral magnon splittings. The strain can also change the sign of the in-plane exchange interaction. Computing magnetic susceptibility, we show that strain enhances the N{é}el temperature, significantly. Our results highlight the critical importance of convergence in the number of magnetic configurations for spin interactions in antiferromagnetic materials.

cond-mat.mtrl-sci↗

arXiv2025

Evaluating SCAN and r$^2$SCAN meta-GGA functionals for predicting transition temperatures in antiferromagnetic materials

Recent advancements in exchange-correlation functionals within density functional theory highlight the need for rigorous validation across diverse types of materials properties. In this study, we assess the performance of the newly developed meta-GGA r$^2$SCAN and its predecessor, SCAN, in predicting the Néel transition temperature of antiferromagnetic materials. Our analysis includes 48 magnetic materials, spanning both simple and complex systems. Using DFT, we compute the energies of various magnetic configurations and extract exchange interaction parameters through a least-squares fitting approach. These parameters are then used in classical Monte Carlo simulations to estimate the transition temperatures. Our results demonstrate that both SCAN and r$^2$SCAN greatly outperform standard GGA and GGA+$U$ methods, yielding predictions that closely align with experimental values. The Pearson correlation coefficients for SCAN and r$^2$SCAN are 0.97 and 0.98, respectively, when compared to experimental transition temperatures. Additionally, we calculate the energy differences between antiferromagnetic and ferromagnetic configurations to assess the performance of the hybrid HSE06 functional. We found that the HSE06 functional underestimates transition temperatures compared to the meta-GGA functionals and experimental values.

cond-mat.mtrl-sci↗

arXiv2024

Strain-tunable magnetic and magnonic states in Ni-dihalide monolayers

Monolayer NiI$_2$ garners large research interest due to its multiferroic behavior stemming from the interplay between its non-collinear magnetic order and the spin-orbit coupling. This prompts an investigation into the stability of the magnetic order in NiI$_2$ and similar materials under external stimuli. In this work, we report the effect of biaxial and uniaxial strain on the magnetic ground state, the critical temperature, and the magnonic properties of the NiX$_2$ (X = I, Br, Cl) monolayers. For all three materials, we reveal intricate strain-dependent phase diagrams, including ferromagnetic, helimagnetic, and skyrmionic phases. Moreover, we discuss the necessity of considering the biquadratic exchange interaction in the latter analysis. We reveal that the biquadratic exchange significantly alters both the magnetic ground state and the critical temperature of the magnetic order, and we demonstrate that its importance becomes even more explicit when monolayer Ni-dihalides are strained. Finally, we calculate the magnonic dispersion for the predicted magnetic states, showing that the skyrmionic phase functions as a magnonic crystal, and demonstrate the presence of strain-tunable soft magnon modes at finite wavevectors in the helimagnetic phase.

cond-mat.mes-hall↗

arXiv2024

Discovery of Novel Silicon Allotropes with Optimized Band Gaps to Enhance Solar Cell Efficiency through Evolutionary Algorithms and Machine Learning

In the pursuit of advancing solar energy technologies, this study presents 20 direct and quasi-direct band gap silicon crystalline semiconductors that satisfy the Shockley-Queisser limit, a benchmark for solar cell efficiency. Employing two evolutionary algorithm-based searches, we optimize structures and calculate fitness function using the DFTB method and Gaussian approximation potential. Following the preselection of structures based on energy considerations, we further optimize them using PBEsol DFT. Subsequently, we screen the structures based on their band gap, employing a DFTB method tailored for band gap calculation of silicon crystals. To ensure accurate band gap determination, we employ HSE and GW methods. To validate the structural stability, we employ phonon analysis via linear regression algorithm applied to PBEsol DFT data. Significantly, the structures unveiled in this study are of great importance due to their proven stability from both mechanical and dynamic perspectives. Furthermore, the ductility and low density of certain structures enhance their potential application. We examine the optical properties by studying the imaginary part of the dielectric function by solving the Bethe-Salpeter Equation on top of GW approximation. By calculating the SLME, we achieve an efficiency of 32.7% for Si$_{22}$ at a thickness of 500 nm. Moreover, the study harnesses various machine learning algorithms to develop a predictive model for the band gap energy of these silicon structures. Input data for machine learning models are derived from structural MBTR and SOAP descriptors, as well as DFT outputs. Notably, the results reveal that features extracted from DFT outperform the MBTR and SOAP descriptors.

cond-mat.mtrl-sci↗

arXiv2022

Electricity Price Forecasting Model based on Gated Recurrent Units

The participation of consumers and producers in demand response programs has increased in smart grids, which reduces investment and operation costs of power systems. Also, with the advent of renewable energy sources, the electricity market is becoming more complex and unpredictable. To effectively implement demand response programs, forecasting the future price of electricity is very crucial for producers in the electricity market. Electricity prices are very volatile and change under the influence of various factors such as temperature, wind speed, rainfall, intensity of commercial and daily activities, etc. Therefore, considering the influencing factors as dependent variables can increase the accuracy of the forecast. In this paper, a model for electricity price forecasting is presented based on Gated Recurrent Units. The electrical load consumption is considered as an input variable in this model. Noise in electricity price seriously reduces the efficiency and effectiveness of analysis. Therefore, an adaptive noise reducer is integrated into the model for noise reduction. The SAEs are then used to extract features from the de-noised electricity price. Finally, the de-noised features are fed into the GRU to train predictor. Results on real dataset shows that the proposed methodology can perform effectively in prediction of electricity price.

cs.LG↗

arXiv2021

ESpinS: A program for classical Monte-Carlo simulations of spin systems

We present \texttt{ESpinS} (Esfahan Spin Simulation) package to evaluate the thermodynamic properties of spin systems described by a spin model Hamiltonian. In addition to the Heisenberg exchange term, the spin Hamiltonian can contain interactions such as bi-quadratic, Dzyaloshinskii-Moriya, and single-ion anisotropy. By applying the classical Monte-Carlo simulation, \texttt{ESpinS} simulates the behavior of spin systems versus temperature. \texttt{ESpinS} ables to calculate the specific heat, susceptibility, staggered magnetization, energy histogram, fourth-order Binder cumulants, and the neutron scattering structure factor. Further, it can compute the user-defined magnetic order parameter i.e. summation of projection of spins on the user-defined directions and the physical quantities based on it. \texttt{ESpinS} works by either local update algorithm or parallel tempering algorithm. The latter feature is an appropriate option for considering the frustrated and spin glass magnetic systems. \texttt{ESpinS} is written in Fortran 90 and can be run in single or parallel mode. The package is freely available under the GPL license (see https://github.com/nafiserb/ESpinS ).

physics.comp-ph↗

arXiv2019

Ab initio investigation of magnetic ordering in the double perovskite Sr$_{2}$NiWO$_{6}$

{\it Ab initio} calculations, GGA/GGA+$U$, are used to propose a spin Hamiltonian for the B-site ordered double perovskite, Sr$_{2}$NiWO$_{6}$. Our results show that the exchange interaction constants between the next nearest neighbors in both intra- and inter- $ab$ plane ($J_2$ and $J_{2c}$) are an order of magnitude larger than the ones between the nearest neighbors ($J_1$ and $J_{1c}$). Employing the Monte Carlo simulation, we show that the obtained Hamiltonian properly describes the finite temperature properties of Sr$_{2}$NiWO$_{6}$. Our {\it ab initio} calculations also reveal a small magnetic anisotropy and non-trivial bi-quadratic interaction between the nearest inter-$ab$ plane neighbors, which play essential roles in stabilizing the type-II anti-ferromagnetic ground state of Sr$_{2}$NiWO$_{6}$.

cond-mat.str-el↗