Effect of rare-earth substitution at La-site on structural, electrical and thermoelectric properties of La0.7−xRExSr0.3MnO3 compounds (x = 0, 0.2, 0.3; RE = Eu, Gd, Y)

Choudhary, Y.R.S.; Mangavati, Suraj; Patil, Siddanagouda; Rao, Ashok; Nagaraja, B.S.; Thomas, Riya; Okram, G. S.; Kini, Savitha G

doi:10.1016/j.jmmm.2017.11.007

Cited by 27 publications

(7 citation statements)

References 33 publications

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“…The proposed models in this work were developed using one hundred experimentally measured MMEC of different manganite-based compounds extracted from the literature [7,8,11,15,18,[52][53][54][55][56][57][58][59][60][61][62][63][64]. The descriptors to the model are two sets of data.…”

Section: Dataset Description and Chemical Formula Of The Doped Manganmentioning

confidence: 99%

Modeling the Maximum Magnetic Entropy Change of Doped Manganite Using a Grid Search-Based Extreme Learning Machine and Hybrid Gravitational Search-Based Support Vector Regression

Shamsah

Owolabi

2020

Crystals

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The thermal response of a magnetic solid to an applied magnetic field constitutes magnetocaloric effect. The maximum magnetic entropy change (MMEC) is one of the quantitative parameters characterizing this effect, while the magnetic solids exhibiting magnetocaloric effect have great potential in magnetic refrigeration technology as they offer a green solution to the known pollutant-based refrigerants. In order to determine the MMEC of doped manganite and the influence of dopants on the magnetocaloric effect of doped manganite compounds, this work developed a grid search (GS)-based extreme learning machine (ELM) and hybrid gravitational search algorithm (GSA)-based support vector regression (SVR) for estimating the MMEC of doped manganite compounds using ionic radii and crystal lattice parameters as descriptors. Based on the root-mean-square error (RMSE), the developed GSA-SVR-radii model performs better than the existing genetic algorithm (GA)-SVR-ionic model in the literature by 27.09%, while the developed GSA-SVR-crystal model performs better than the existing GA-SVR-lattice model in the literature by 38.34%. Similarly, the developed ELM-GS-crystal model performs better than the existing GA-SVR-ionic model with a performance enhancement of 14.39% and 20.65% using the mean absolute error (MAE) and RMSE, respectively, as performance measuring parameters. The developed models also perform better than the existing models using correlation coefficient as the performance measuring parameter when validated with experimentally measured MMEC. The superior performance of the present models coupled with easy accessibility of the descriptors definitely will facilitate the synthesis of doped manganite compounds with a high magnetocaloric effect without experimental stress.

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Section: Dataset Description and Chemical Formula Of The Doped Manganmentioning

confidence: 99%

Modeling the Maximum Magnetic Entropy Change of Doped Manganite Using a Grid Search-Based Extreme Learning Machine and Hybrid Gravitational Search-Based Support Vector Regression

Shamsah

Owolabi

2020

Crystals

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“…Room temperature Hall effect measurement was performed using Ecopia HMS-5500 with 0.5T magnetic field to estimate the room temperature carrier concentration and mobility [15]. Thermopower is measured by adopting differential dc method [16].…”

Section: Methodsmentioning

confidence: 99%

“…The room temperature carrier concentration, and mobility, are given in Table 1. To understand the conduction mechanism, we adopted the Small Poloron Hopping (SPH) model which is given by [16],…”

Section: Structural Studies (X-ray Diffraction)mentioning

confidence: 99%

Investigation of Electrical and Thermoelectric Properties of ZnO/rGO Composites Prepared by Conventional Solid-state Reaction Method

Mangavati¹,

Rao

Devadiga³

et al. 2021

J. Nano- Electron. Phys.

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ZnO/rGO composites are prepared by the conventional solid-state reaction method. Structural properties of prepared compounds were studied using XRD technique and it is observed that all the samples are crystallized in wurtzite structure. Electrical resistivity measurements were carried out using four probe method employing a closed cycle refrigerator. With addition of rGO, colossal reduction in the resistivity is observed which is about three orders of magnitude smaller than that of the pure sample of ZnO. Room temperature Hall measurements were performed to estimate the bulk concentration and results show that addition of rGO into ZnO matrix enhances the number of charge carriers. Thermopower measurements were carried out using differential dc method and a large reduction in Seebeck coefficient is observed.

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“…The best fitting can be seen in figure 6. dependence of resistivity in a disordered system [40]. To better understand the source of the low-temperature increase in resistivity, the experimental data were analyzed with the inclusion of Kondo-like scattering, electron-electron interaction, and electron-phonon interaction.…”

Section: Electrical Transport Propertiesmentioning

confidence: 99%

Regulating the Electron Transport Mechanism and Increasing Magnetoresistance: The Role of CuO Filler in La0.7Sr0.2Ca0.1MnO3 Grain Boundary

Zulkarnain

Imaduddin²,

Munazat

et al. 2023

Preprint

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Magnetoresistance in perovskite materials has been extensively studied due to their great potential in spintronics technology. Perovskite samples composite with metal oxides can modify electrical properties, which can subsequently improve LFMR under low magnetic fields. In this study, we investigate changes in electrical properties at different temperatures of polycrystalline (1-x)La0.7Sr0.2Ca0.1MnO3/xCuO (LC) composites, where x = 0, 0.05, 0.10, 0.15, and 0.20. Polycrystalline La0.7Sr0.2Ca0.1MnO3 (LSCMO) was synthesized using the sol-gel method and CuO powder as a filler was mixed with LSCMO using wet. The LC composite was then oven-dried to remove moisture, compacted at 10 MPa, and sintered at 1200°C for 12 hours. All samples in the LSCMO phase have a rhombohedral structure with space group R3c. The crystal structure parameters were studied using Rietveld refinement through GSAS II software. SEM results show that CuO is in the LSCMO grain boundary and confirmed by EDS. As the CuO composition increased, the magnetization decreased, as observed by VSM at room temperature. The electrical transport properties of pure LSCMO and LC composites were studied from 5 to 300 K characterized by a cryogenic magnetometer. LC resistivity is higher than LSCMO, and the more CuO content, the smaller the metal transition temperature. CuO present at the grain boundary can decrease the resistivity value as compared to LSCMO. Additionally, the CuO layer weakens spin polarized tunneling intergrain, ultimately impacting the magnetoresistance value. The highest magnetoresistance value is for the LC15 composite at a temperature of 5K with an external field of 2T at 28.5%.

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Effect of rare-earth substitution at La-site on structural, electrical and thermoelectric properties of La0.7−xRExSr0.3MnO3 compounds (x = 0, 0.2, 0.3; RE = Eu, Gd, Y)

Cited by 27 publications

References 33 publications

Modeling the Maximum Magnetic Entropy Change of Doped Manganite Using a Grid Search-Based Extreme Learning Machine and Hybrid Gravitational Search-Based Support Vector Regression

Modeling the Maximum Magnetic Entropy Change of Doped Manganite Using a Grid Search-Based Extreme Learning Machine and Hybrid Gravitational Search-Based Support Vector Regression

Investigation of Electrical and Thermoelectric Properties of ZnO/rGO Composites Prepared by Conventional Solid-state Reaction Method

Regulating the Electron Transport Mechanism and Increasing Magnetoresistance: The Role of CuO Filler in La0.7Sr0.2Ca0.1MnO3 Grain Boundary

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Effect of rare-earth substitution at La-site on structural, electrical and thermoelectric properties of La0.7−xRExSr0.3MnO3 compounds (x = 0, 0.2, 0.3; RE = Eu, Gd, Y)

Cited by 27 publications

References 33 publications

Modeling the Maximum Magnetic Entropy Change of Doped Manganite Using a Grid Search-Based Extreme Learning Machine and Hybrid Gravitational Search-Based Support Vector Regression

Modeling the Maximum Magnetic Entropy Change of Doped Manganite Using a Grid Search-Based Extreme Learning Machine and Hybrid Gravitational Search-Based Support Vector Regression

Investigation of Electrical and Thermoelectric Properties of ZnO/rGO Composites Prepared by Conventional Solid-state Reaction Method

Regulating the Electron Transport Mechanism and Increasing Magnetoresistance: The Role of CuO Filler in La0.7Sr0.2Ca0.1MnO3 Grain Boundary

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Effect of rare-earth substitution at La-site on structural, electrical and thermoelectric properties of La0.7−xRExSr0.3MnO3 compounds (x = 0, 0.2, 0.3; RE = Eu, Gd, Y)