N-type LaFe1-xMnxO3 prepared by sol-gel method for gas sensing

Li, Fēi; Wang, Zhenfa; Wang, An; Wu, Shumao; Zhang, Liangji

doi:10.1016/j.jallcom.2019.152647

Cited by 15 publications

(7 citation statements)

References 40 publications

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“…enhances the response and selectivity to different gases [33][34][35]. This is also the case when substituting Fe 3+ ions with Mg 2+ , Co 2+ , or Mn 3+ ones [31,[36][37][38]. Accordingly, in this paper, we synthesized the La 0.67 Ca 0.2 Ba 0.13 Fe 0.97 M 0.03 O 3 (M = Ti 4+ , Cr 3+ , and Mn 3+ ) compounds via the autocombustion method and described a comprehensive study for the 3% Ti 4+ , Mn 3+ , and Cr 3+ ion insertion effects on particle size and gas-sensing properties.…”

Section: Introductionmentioning

confidence: 85%

Particle Size Effect on Optical and Gas-Sensing Properties of La0.67Ca0.2Ba0.13Fe0.97M0.03O3 (M = Ti4+, Mn3+, and Cr3+) Compounds

Dhahri,

Saoudi,

Gavinho

et al. 2024

Crystals

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In the present work, the morphological, optical, and gas-sensing properties of La0.67Ca0.2Ba0.13Fe0.97M0.03O3 (M = Ti, Cr, and Mn) nano-powders prepared via the auto-combustion route, were investigated. TEM images prove the nanoscale particle size of all the samples. Optical studies confirm the semiconductor behavior of the studied materials. The response of the prepared nano-powders towards the presence of two gas-reducing agents (ethanol and acetone) was investigated. From the resistance ratio under air and gas, it was possible to determine the response to different gases and deduce that La0.67Ca0.2Ba0.13Fe0.97Ti0.03O3 presents the highest responses to ethanol and acetone. Likewise, we deduced that the prepared materials were able to detect low concentrations of ethanol and acetone gases.

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Section: Introductionmentioning

confidence: 85%

Particle Size Effect on Optical and Gas-Sensing Properties of La0.67Ca0.2Ba0.13Fe0.97M0.03O3 (M = Ti4+, Mn3+, and Cr3+) Compounds

Dhahri,

Saoudi,

Gavinho

et al. 2024

Crystals

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“…Li et al 79 reported n-type LaFe 1– x Mn x O 3 for ethanol sensing and explained transformation of a p-type LaFeO 3 to n-type LaFe 1– x Mn x O 3 semiconductor. Lanthanum nitrate, ferric nitrate, and citric acid were dissolved in 25 mL of distilled water, and subsequently, Mn-nitrate was added dropwise and stirred for 30 min.…”

Section: Lafeo 3 For Reducing Gases Sensingmentioning

confidence: 99%

La-Fe-O Perovskite Based Gas Sensors: Recent Advances and Future Challenges

Patil,

Babar,

Nadargi

et al. 2024

ACS Omega

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Interest in the importance of gas sensing devices has increased significantly due to their critical function in monitoring the environment and controlling pollution, resulting in an increased market demand. The present review explores perovskite La-Fe-O based gas sensors with a special focus on LaFeO 3 and evaluates their sensitivity to a diverse range of practical target gases that need to be monitored. An analysis has been conducted to assess different routes not only of synthesizing LaFeO 3 material but also of characterization with the targeted use for their gas sensing abilities. Additionally, a comprehensive analysis has been performed to explore the effect of introducing other elements through doping. In view of the LaFeO 3 sensing performance, more common gases like acetone, ethanol, methanol, formaldehyde, NO x , and CO 2 have been targeted. In addition, a discussion on uncommon gases such as CO, SO 2 , TEA, C 2 H 5 , C 6 H 6 , and others is also made to give a complete picture of LaFeO 3 -based gas sensors. The summary and conclusion section of the study addresses the primary obstacles in the synthesis process, the variables that restrict the sensing capabilities of LaFeO 3 , and its commercial fulfillment.

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“…The magnetocaloric material must have a Curie temperature (Tc) of close to room temperature and demonstrate a significant magnetic entropy change (𝛥𝑆𝑚) over considerable temperature fluctuations in order to be fabricated into an operable magnetic refrigerator at room temperature. Manganite alloys have been researched for various applications such as magnetic refrigerants [3], catalysts [4], sensor applications [5], solid oxide fuel cell electrodes [6],…”

Section: Introductionmentioning

confidence: 99%

Implementation of Backpropagation Neural Network for Prediction Magnetocaloric Effect of Manganite

Setiawan,

Simbolon,

Yunasfi

2024

JUITA

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In the field of magnetic cooling technology, there is still much to learn about the magnetocaloric properties of magnetic cooling materials. Research into magnetocaloric manganites exhibiting a significant maximum magnetic entropy change in the vicinity of ambient temperature yields encouraging outcomes for the advancement of magnetic refrigeration apparatus. Through a combination of chemical substitutions, changes in the amount of oxygen present, and different synthesis techniques, these manganites undergo lattice distortions that result in pseudocubic, orthorhombic, and rhombohedral structures instead of perovskite cubic structures. The present investigation used backpropagation neural networks (BPNNs) to investigate the correlations among maximum magnetic entropy change (MMEC), Curie temperature (Tc), lanthanum manganite compositions, lattice properties, and dopant ionic radii. Simbrain 3.07 was used to execute the BPNN model, and the suggested model accuracy was examined using coefficient determination. As a result, the model's predicted values for the mean absolute error, root mean square, and coefficient correlation for MMEC are 0.012, 0.022, and 0.9861, respectively. The model predicts that the Curie temperature mean absolute error, root mean square, and coefficient correlation will be 0.015, 0.021, and 0.9947, respectively. Based on these results, BPNN has the potential to be applied in predicting the MMEC and Tc of manganite as preliminary decision during experiments.

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N-type LaFe1-xMnxO3 prepared by sol-gel method for gas sensing

Cited by 15 publications

References 40 publications

Particle Size Effect on Optical and Gas-Sensing Properties of La0.67Ca0.2Ba0.13Fe0.97M0.03O3 (M = Ti4+, Mn3+, and Cr3+) Compounds

Particle Size Effect on Optical and Gas-Sensing Properties of La0.67Ca0.2Ba0.13Fe0.97M0.03O3 (M = Ti4+, Mn3+, and Cr3+) Compounds

La-Fe-O Perovskite Based Gas Sensors: Recent Advances and Future Challenges

Implementation of Backpropagation Neural Network for Prediction Magnetocaloric Effect of Manganite

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