Modelling of electronic and optical properties of Cu<sub>2</sub>SnS<sub>3</sub> quantum dots for optoelectronics applications

Ahamed, Mansoor; Kumar, K. Sathish

doi:10.2478/msp-2018-0103

Cited by 16 publications

(13 citation statements)

References 32 publications

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“…These are also consistent with the band gap reported for bulk CTS crystals (0.94 eV) and CTS nanoparticles as well as CTS thin films (0.92–1.02 eV). ,,− In contrast, Dias et al . reported a larger band gap of 1.66 eV for CTS quantum dots with a very small size (∼3 nm), which is less than the exciton Bohr radius for CTS . From the predicted electronic band structures, the effective masses of electrons ( m e * ) and holes ( m h * ) for CTS, CdS, and ZnS were calculated by fitting the energy of the conduction band minimum and valence band maximum, respectively, to a quadratic polynomial in the reciprocal lattice vector k according to the relations: .…”

Section: Resultssupporting

confidence: 85%

“… 51 reported a larger band gap of 1.66 eV for CTS quantum dots with a very small size (∼3 nm), which is less than the exciton Bohr radius for CTS. 73 From the predicted electronic band structures, the effective masses of electrons ( m e * ) and holes ( m h * ) for CTS, CdS, and ZnS were calculated by fitting the energy of the conduction band minimum and valence band maximum, respectively, to a quadratic polynomial in the reciprocal lattice vector k according to the relations: . The calculated m e * and m h * for CTS are shown in Figure 7 d, whereas those for ZnS and CdS are provided in the Supporting Information ( Figures S3d and S4d ).…”

Section: Resultsmentioning

confidence: 99%

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Ternary Cu₂SnS₃: Synthesis, Structure, Photoelectrochemical Activity, and Heterojunction Band Offset and Alignment

et al. 2021

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Ternary Cu 2 SnS 3 (CTS) is an attractive nontoxic and earth-abundant absorber material with suitable optoelectronic properties for cost-effective photoelectrochemical applications. Herein, we report the synthesis of high-quality CTS nanoparticles (NPs) using a low-cost facile hot injection route, which is a very simple and nontoxic synthesis method. The structural, morphological, optoelectronic, and photoelectrochemical (PEC) properties and heterojunction band alignment of the as-synthesized CTS NPs have been systematically characterized using various state-of-the-art experimental techniques and atomistic first-principles density functional theory (DFT) calculations. The phase-pure CTS NPs confirmed by X-ray diffraction (XRD) and Raman spectroscopy analyses have an optical band gap of 1.1 eV and exhibit a random distribution of uniform spherical particles with size of approximately 15–25 nm as determined from high-resolution transmission electron microscopy (HR-TEM) images. The CTS photocathode exhibits excellent photoelectrochemical properties with PCE of 0.55% (fill factor (FF) = 0.26 and open circuit voltage (Voc) = 0.54 V) and photocurrent density of −3.95 mA/cm 2 under AM 1.5 illumination (100 mW/cm 2 ). Additionally, the PEC activities of CdS and ZnS NPs are investigated as possible photoanodes to create a heterojunction with CTS to enhance the PEC activity. CdS is demonstrated to exhibit a higher current density than ZnS, indicating that it is a better photoanode material to form a heterojunction with CTS. Consistently, we predict a staggered type-II band alignment at the CTS/CdS interface with a small conduction band offset (CBO) of 0.08 eV compared to a straddling type-I band alignment at the CTS/ZnS interface with a CBO of 0.29 eV. The observed small CBO at the type-II band aligned CTS/CdS interface points to efficient charge carrier separation and transport across the interface, which are necessary to achieve enhanced PEC activity. The facile CTS synthesis, PEC measurements, and heterojunction band alignment results provide a promising approach for fabricating next-generation Cu-based light-absorbing materials for efficient photoelectrochemical applications.

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confidence: 85%

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confidence: 99%

Ternary Cu₂SnS₃: Synthesis, Structure, Photoelectrochemical Activity, and Heterojunction Band Offset and Alignment

et al. 2021

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“…The energy level formation in semiconductor nanomaterials is unique due to the quantum confinement effect. The "Brus model" is one of the most familiar theoretical models that allows for a relatively simple analytical relationship between material size and energy bandgap [17,18].…”

Section: Brus Modelmentioning

confidence: 99%

Comparative energy bandgap analysis of zinc and tin based chalcogenide quantum dots

Ahamed

Kumar³

et al. 2022

Rev. Mex. Fís.

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Semiconductors with wide bandgap are crucial for optoelectronic devices and energy applications owing to their electron confinement, high optical transparency and tunable electrical conductivity. Therefore, in this study, the quantum confinement effect of the energy bandgap of chalcogenide semiconductor nanocrystals such as ZnS, ZnSe, ZnTe, SnS, SnSe and SnTe are studied based on the Brus model using the effective mass approximation, the hyperbolic band model and the cohesive energy model. The obtained results indicate that the value of energy bandgap differs from the bulk crystals related to the quantum confinement effect. These verdicts confirm the quantum confinement effects of materials and their potential applications in optoelectronic devices. Theoretical findings are compared with its valid experimental data.

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“…The dataset consist of user/patient information, personal details, symptoms and test results. The dataset contains history of information about patients with repository as storage medium [2] [3].…”

Section: Introductionmentioning

confidence: 99%

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2023

JISIS

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Machine learning is the subset of Artificial Intelligence and it is used for prediction various real time data analytics applications. Health care monitoring is the major area to analyse the result and make effective decisions. We need intelligent and automated process for predicting diseases using medical dataset. Machine learning methods are proposed to handle the dataset. Smart healthcare prediction is proposed to identify the user or patient information or symptoms as an input. Our system has forecasting accuracy index based on likelihood of the disease and health information. We use Naive bayes classifier algorithm for handling classification, prediction and accuracy index of dataset. Our algorithm measures the disease percentage and train the dataset. Once the prediction result will appears based on effective decision to be taken. In our work, we are taken 20000 train dataset and 7500 test data set for evaluation. TensorFlow simulator is used to simulate the system and measure accuracy. In this system achieves 95% accuracy and performance result compared with existing methods.

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Modelling of electronic and optical properties of Cu₂SnS₃ quantum dots for optoelectronics applications

Cited by 16 publications

References 32 publications

Ternary Cu₂SnS₃: Synthesis, Structure, Photoelectrochemical Activity, and Heterojunction Band Offset and Alignment

Ternary Cu₂SnS₃: Synthesis, Structure, Photoelectrochemical Activity, and Heterojunction Band Offset and Alignment

Comparative energy bandgap analysis of zinc and tin based chalcogenide quantum dots

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Modelling of electronic and optical properties of Cu2SnS3 quantum dots for optoelectronics applications

Cited by 16 publications

References 32 publications

Ternary Cu2SnS3: Synthesis, Structure, Photoelectrochemical Activity, and Heterojunction Band Offset and Alignment

Ternary Cu2SnS3: Synthesis, Structure, Photoelectrochemical Activity, and Heterojunction Band Offset and Alignment

Comparative energy bandgap analysis of zinc and tin based chalcogenide quantum dots

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Modelling of electronic and optical properties of Cu₂SnS₃ quantum dots for optoelectronics applications

Ternary Cu₂SnS₃: Synthesis, Structure, Photoelectrochemical Activity, and Heterojunction Band Offset and Alignment

Ternary Cu₂SnS₃: Synthesis, Structure, Photoelectrochemical Activity, and Heterojunction Band Offset and Alignment