Griffiths Phase and Disorder in Perovskite Manganite Oxides La1−x Ca x MnO3 and La0.7Sr0.3MnO3

Zhang, Hongguang; Chen, Lingshan; Li, Yongtao; Liu, Hao; Chen, Yuanyuan; Chen, Kai; Xiao, Dong; Yang, Hao; Gao, Tianyou; Li, Qi

doi:10.1007/s10948-010-1081-5

Cited by 17 publications

(11 citation statements)

References 28 publications

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“…It is observed that the E ρ initially decreases with increasing Bi 3+ content up to x=0.025, however, with further increase in x, E ρ increases with increase in x value. The increase in E ρ is due to the fact that increase in bismuth concentration lowers the possibility of conduction electron to hop to the neighboring sites and promotes the formation of lattice polarons [11]. The fitting observed between the experimental and theoretical data validates the applicability of SPH model in the paramagnetic insulating region.…”

Section: Electrical Transport and Magneto-resistancesupporting

confidence: 65%

“…The S data in the PM insulating region is analyzed within the framework of Mott's polaron hopping model [38] which is given by the well-known equation S(T) = k B /e((E S /k B T)+α) (11) where E S is the activation energy for Seebeck coefficient and α a constant related to the kinetic energy of the polarons, respectively. The experimental data of S for all the samples in the PM region were fitted using Eq.…”

Section: Thermoelectric Powermentioning

confidence: 99%

“…In particular, La 1-x Ca x MnO 3 (LCMO) compounds are of immense significance because of the fact that these are intermediate bandwidth systems which are well-known to display the largest colossal magneto-resistance (CMR) which is related with the presence of charge ordering tendencies [7]. The existence of Griffiths Phase (GP) in several manganites has renewed attention in these systems over the last few decades [8][9][10][11]. The Griffiths phase essentially means the existence of nano-scale magnetic inhomogeneties seen in the paramagnetic regions [8,9].…”

Section: Introductionmentioning

confidence: 99%

“…The Griffiths phase essentially means the existence of nano-scale magnetic inhomogeneties seen in the paramagnetic regions [8,9]. Griffiths phase has its origin from various factors viz., structural disorders caused by doping ions at various sites [8,10,11], Jahn-Teller distortion [8,12] and grain sizes [9]. GP in the case of La 1-x Ca x MnO 3 is believed to arise from the disorders arising from the tilting of MnO 6 octahedron [8,13] where as the static Jahn-Teller distortion leads to GP in La 1-x Sr x MnO 3 system [12].…”

Section: Introductionmentioning

confidence: 99%

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Investigation on magnetic, electrical and thermoelectric power of Bi-substituted La0.8Ca0.2MnO3 manganites

Manjunatha

Rao

Awana³

et al. 2015

Journal of Magnetism and Magnetic Materials

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Section: Electrical Transport and Magneto-resistancesupporting

confidence: 65%

Section: Thermoelectric Powermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Investigation on magnetic, electrical and thermoelectric power of Bi-substituted La0.8Ca0.2MnO3 manganites

Manjunatha

Rao

Awana³

et al. 2015

Journal of Magnetism and Magnetic Materials

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“…Recently, focus on ECG rhythm (ECGr) classification has similarly been on the increase. ECGr classification can be grouped into areas that focus on finding effective extraction methods, [13,14] improving classification outcomes, [15][16][17][18][19] and utilization of deep learning methods to enhance the performance of classification [20][21][22][23][24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

A Multitier Deep Learning Model for Arrhythmia Detection

Hammad

Iliyasu

Subaşı

et al. 2021

IEEE Trans. Instrum. Meas.

165

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Electrocardiograph (ECG) is employed as a primary tool for diagnosing cardiovascular diseases (CVD) in the hospital, which often helps in the early detection of such ailments. ECG signals provide a framework to probe the underlying properties and enhance the initial diagnosis obtained via traditional tools and patient-doctor dialogues. It provides cardiologists with inferences regarding more serious cases. Notwithstanding its proven utility, deciphering large datasets to determine appropriate information remains a challenge in ECGbased CVD diagnosis and treatment. Our study presents a deep neural network (DNN) strategy to ameliorate the aforementioned difficulties. Our strategy consists of a learning stage where classification accuracy is improved via a robust feature extraction. This is followed using a genetic algorithm (GA) process to aggregate the best combination of feature extraction and classification. The MIT-BIH Arrhythmia was employed in the validation to identify five arrhythmia categories based on the association for the advancement of medical instrumentation (AAMI) standard. The performance of the proposed technique alongside state-of-the-art in the area shows an increase of 0.94 and 0.953 in terms of average accuracy and F1 score, respectively. The proposed model could serve as an analytic module to alert users and/or medical experts when anomalies are detected in the acquired ECG data in a smart healthcare framework.

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A review on the performance of concrete filled tubular columns under axial compression: Emphasis on geometrical parameters and various concrete infills and encasings

Rohilla,

Gupta

2023

Structural Design Tall Build

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SummaryThis paper summarizes the literature available on the behavior of concrete‐filled steel tubular (CFST) columns to evaluate the effect of geometrical properties such as shape of cross‐section, diameter‐to‐thickness ratio, and length‐to‐diameter ratio of CFST columns under axial loading. Then, the impact of different material composition for core concrete and encasing material is concluded for columns under axial loading. The performance of CFST is evaluated in terms of failure modes, ductility, stiffness, and axial compressive strength. For encasing tube, carbon steel, stainless steel, and aluminum are studied while for core, various concretes such as Normal (NSC) and high strength concrete (HSC), light weight concrete (LWC), recycled aggregate concrete (RAC), expansive concrete (EC), rubber crumb concrete(RuCC), and steel slag concrete (SSC) are covered for review in this paper. Material limitations as provided by various codes for design of composite structures is also mentioned for both tube and core concrete. Failure modes of concrete‐filled tubular(CFT) columns are most affected by geometric properties columns while materials used for concrete and encasing tube do not cause much difference. Though, ductility, axial compressive strength, and stiffness are affected by both geometric and material properties.

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Griffiths Phase and Disorder in Perovskite Manganite Oxides La1−x Ca x MnO3 and La0.7Sr0.3MnO3

Cited by 17 publications

References 28 publications

Investigation on magnetic, electrical and thermoelectric power of Bi-substituted La0.8Ca0.2MnO3 manganites

Investigation on magnetic, electrical and thermoelectric power of Bi-substituted La0.8Ca0.2MnO3 manganites

A Multitier Deep Learning Model for Arrhythmia Detection

A review on the performance of concrete filled tubular columns under axial compression: Emphasis on geometrical parameters and various concrete infills and encasings

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