Tailoring the transport coefficients and thermoelectric properties of Cs 2 NaYbCl 6 perovskite by doping and nanoengineering: A first-principles based theoretical approach

Accelerating the application of lead-free inorganic halide perovskites in solar cells necessitates the development of novel perovskite materials with suitable bandgap widths, high stability, and environmental friendliness. This represents a crucial pathway for driving photovoltaic technology innovation and reducing reliance on conventional fossil fuels. However, traditional material development paradigms heavily depend on trial-and error experimental screening or pure density functional theory (DFT) calculations, which incur significant time and material costs.<br>To address these challenges, this study innovatively proposes and implements an efficient screening strategy based on the synergy between deep learning and DFT calculations. By constructing a database containing 1181 inorganic halide double perovskite materials, we systematically trained and compared the performance of five mainstream machine learning models for the bandgap prediction task: Random Forest Regression (RFR), Gradient Boosting Regression (GBR), Support Vector Regression (SVR), eXtreme Gradient Boosting Regression (XGBR), and a Deep Neural Network (DNN) model. Results demonstrate that the DNN model, leveraging its powerful nonlinear mapping capability and advantage in automatic high-dimensional feature extraction, achieved exceptional prediction accuracy on the test set, with the Mean Absolute Error (MAE) significantly reduced to 0.264 eV and the coefficient of determination (R<sup>2</sup>) reaching 0.925. Its performance was markedly superior to other compared models, highlighting the immense potential of deep learning in predicting complex material properties.<br>Using this optimized DNN model, this study successfully screened four promising inorganic double perovskite candidates from 55 potential materials: Cs<sub>2</sub>GaAgCl<sub>6</sub>, Cs<sub>2</sub>AgIrF<sub>6</sub>, Cs<sub>2</sub>InAgCl<sub>6</sub>, and Cs<sub>2</sub>AlAgBr<sub>6</sub>. Among them, Cs<sub>2</sub>AgIrF<sub>6</sub> and Cs<sub>2</sub>AlAgBr<sub>6</sub> performed particularly well, with predicted bandgaps of 1.36 eV and 1.20 eV, respectively. This range ideally matches the requirement for efficient light absorption in solar cells. Further device performance simulations revealed that the solar cell based on Cs<sub>2</sub>AgIrF<sub>6</sub> achieved a simulated power conversion efficiency (PCE) of 23.71%, with an open-circuit voltage (<i>V<sub>OC</sub></i>) of 0.94 V, a short-circuit current density (<i>J<sub>SC</sub></i>) of 31.19 mA/cm<sup>2</sup>, and a fill factor (FF) of 80.81%. Cs<sub>2</sub>AlAgBr<sub>6</sub> also exhibited a simulated efficiency of 22.37%, corresponding to <i>V<sub>OC</sub></i>=0.78 V, <i>J<sub>SC</sub></i>=36.73 mA/cm<sup>2</sup>, and FF=77.66%. Notably, both materials demonstrated high open-circuit voltages and fill factors, clearly indicating excellent carrier separation efficiency and significantly reduced nonradiative recombination losses within these materials.<br>In summary, this study successfully validates the significant efficacy of the deep learning-DFT synergistic strategy in accelerating the discovery of novel lead-free perovskite materials. This method not only substantially enhances the efficiency of DFT data analysis and the depth of pattern mining, overcoming some bottlenecks associated with traditional highthroughput calculations, but more importantly, it provides a practical and highly innovative approach for the rational design of high-performance, stable, and environmentally friendly lead-free perovskite solar cells, holding positive implications for advancing green, low-carbon energy technologies.

Universal behaviour of thermal and electrical transport coefficients near the néel temperature of Cr 99.94Al 0.06

Theoretical investigations of double perovskites Rb2YCuX6 (X =Cl, F) for green energy applications: DFT study

Screening for lead-free inorganic double perovskites with suitable band gaps and high stability using combined machine learning and DFT calculation

External pressure can significantly alter the transport coefficients, power factor, and figure of merit because of its direct influence on the electronic structure, electron–phonon, and phonon–phonon couplings. This study delves into the electronic and thermal transport properties of at external pressures up to 30 GPa using first‐principles calculations and Boltzmann transport theory. The electron–phonon relaxation time is computed within the electron–phonon‐averaged (EPA) approximation, enabling exploration beyond the constant relaxation time approximation. The first‐principles calculations reveal an indirect bandgap of 1.76 (without pressure) and 0.12 eV (30 GPa). The density functional perturbation theory calculations confirm the dynamic stability of at external pressure up to 30 GPa. The electronic transport properties are improved by more than one order of magnitude at 30 GPa, consistent with experimental observations. The Peierls–Boltzmann transport calculations demonstrate the room temperature lattice thermal conductivity of 0.22 (without pressure) and 7.4 (at 30 GPa). The results emanate that exhibits of 0.71 at 900 K at a hole doping of 2 at zero pressure, which decreases with increasing pressure. The findings explore the effect of external pressure on both electronic and thermal transport properties of , warranting further experimental exploration of thermal transport properties at higher pressures.

The thermoelectric properties of indium nitride in the most stable wurtzite phase (w-InN) as a function of electron and hole concentrations and temperature were studied by solving the semiclassical Boltzmann transport equations in conjunction with ab initio electronic structure calculations, within Density Functional Theory. Based on maximally localized Wannier function basis set and the ab initio band energies, results for the Seebeck coefficient are presented and compared with available experimental data for n-type as well as p-type systems. Also, theoretical results for electric conductivity and power factor are presented. Most cases showed good agreement between the calculated properties and experimental data for w-InN unintentionally and p-type doped with magnesium. Our predictions for temperature and concentration dependences of electrical conductivity and power factor revealed a promising use of InN for intermediate and high temperature thermoelectric applications. The rigid band approach and constant scattering time approximation were utilized in the calculations.

Copper(I)-Based Highly Emissive All-Inorganic Rare-Earth Halide Clusters

Investigations of thermoelectric properties of ZnO monolayers from the first-principles approach

Structural stability, optoelectronic, thermoelectric, and elastic characteristics of X2ScBiO6 (X= Mg, Ca, and Ba) double perovskites for energy harvesting: First-principles analysis

Efficient white-light-emitting single-material sources are ideal for sustainable lighting applications. Though layered hybrid lead-halide perovskite materials have demonstrated attractive broad-band white-light emission properties, they pose a serious long-term environmental and health risk as they contain lead (Pb2+) and are readily soluble in water. Recently, lead-free halide double perovskite (HDP) materials with a generic formula A(I)2B'(III)B″(I)X6 (where A and B are cations and X is a halide ion) have demonstrated white-light emission with improved photoluminescence quantum yields (PLQYs). Here, we present a series of Bi3+/In3+ mixed-cationic Cs2Bi1-xInxAgCl6 HDP solid solutions that span the indirect to direct band-gap modification which exhibit tailorable optical properties. Density functional theory (DFT) calculations indicate an indirect-direct band-gap crossover composition when x > 0.50. These HDP materials emit over the entire visible light spectrum, centered at 600 ± 30 nm with full-width at half maxima of ca. 200 nm upon ultraviolet light excitation and a maximum PLQY of 34 ± 4% for Cs2Bi0.085In0.915AgCl6. Short-range structural insight for these materials is crucial to unravel the unique atomic-level structural properties which are difficult to distinguish by diffraction-based techniques. Hence, we demonstrate the advantage of using solid-state nuclear magnetic resonance (NMR) spectroscopy to deconvolute the local structural environments of these mixed-cationic HDPs. Using ultrahigh-field (21.14 T) NMR spectroscopy of quadrupolar nuclei (115In, 133Cs, and 209Bi), we show that there is a high degree of atomic-level B'(III)/B″(I) site ordering (i.e., no evidence of antisite defects). Furthermore, a combination of XRD, NMR, and DFT calculations was used to unravel the complete atomic-level random Bi3+/In3+ cationic mixing in Cs2Bi1-xInxAgCl6 HDPs. Briefly, this work provides an advance in understanding the photophysical properties that correlate long- to short-range structural elucidation of these newly developed solid-state white-light emitting HDP materials.

Investigation of structural, magneto-electronic, elastic, mechanical and thermoelectric properties of novel lead-free halide double perovskite Cs2AgFeCl6: First-principles calcuations

Study of promising lithium-based lead-free double perovskites Li2AuBiX6 (X = Cl, Br, and I) for optoelectronic and other renewable energy applications

K2Ag(Ga/In)Br6 lead-free HDPs: Investigation of the elastic, optoelectronic, optical coating, and thermal characteristics for thermoelectric and solar cells

Designing piezoresistive materials from first-principles: Dopant effects on 3C-SiC

We report an analysis of the structural, electronic, mechanical, and thermoelectric properties of oxide double perovskite structures, specifically the compounds Ba2MgReO6 and Ba2YMoO6. Our study employs first-principles density functional theory (DFT) as the investigative methodology. The electronic attributes of the examined compounds are explained by investigating their energy bands, as well as the total and partial density of states. The computational evaluation of the electronic band structure reveals that both compounds exhibit an indirect band gap semiconductor behavior in the spin-down channel, while demonstrating metallic properties in the spin-up channel. The magnetic attributes indicate a ferromagnetic nature, thus categorizing some double perovskite compounds as materials displaying half-metallic ferromagnetism (HM-FM) in addition to some other properties such as metallic and semiconductor in paramagnetic or antiferromagnetic states. The outcomes derived from the analysis of elastic constants confirm the mechanical robustness of the studied double perovskite compounds. Notably, the computed data for bulk modulus (B), shear modulus (G), and Young’s modulus (E) for Ba2MgReO6 surpass those of Ba2YMoO6. The calculated ratio of Bulk to shear modulus (B/G) indicates that both compounds possess ductile characteristics, rendering them suitable for device fabrication. Furthermore, both compounds display outstanding electronic and elastic properties, positioning them as promising contenders for integration within mechanical and spintronic devices. Finally, we investigate into the thermoelectric potential by evaluating parameters such as the Seebeck coefficient, electrical conductivity, thermal conductivity, figure of merit, and power factor. This assessment is conducted using the semiclassical Boltzmann theory and the constant relaxation time approximation, implemented through the BoltzTraP code. The results indicate that the investigated double perovskite oxides hold promise for utilization in thermoelectric applications.