Stabilizing the dopability of chalcogens in BaZrO3 through TiZr co-doping and its impact on the opto-electronic and photocatalytic properties: A meta-GGA level DFT study

Zulfiqar, Waqas; Javed, Farrukh; Abbas, Ghulam; Larsson, J. Andreas; Alay-e-Abbas, Syed Muhammad

doi:10.1016/j.ijhydene.2024.01.202

Cited by 3 publications

(2 citation statements)

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“…ABO 3 -type perovskites are highly promising semiconductor photocatalysts, drawing increasing interest from researchers [ 43 , 44 ]. This study focused on rapidly screening promising ABO 3 -type perovskites for photocatalytic applications and accelerating the design of perovskite-oxide-based photocatalysts.…”

Section: Introductionmentioning

confidence: 99%

“…The method involved several steps, including data collection, feature engineering, model construction, web-service development, virtual screening, and mechanism elucidation. ABO 3 -type perovskites are highly promising semiconductor photocatalysts, drawing increasing interest from researchers [43,44]. This study focused on rapidly screening promising ABO 3 -type perovskites for photocatalytic applications and accelerating the design of perovskite-oxide-based photocatalysts.…”

Section: Introductionmentioning

confidence: 99%

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Accelerated Design for Perovskite-Oxide-Based Photocatalysts Using Machine Learning Techniques

Zhai,

Chen

2024

Materials

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The rapid discovery of photocatalysts with desired performance among tens of thousands of potential perovskites represents a significant advancement. To expedite the design of perovskite-oxide-based photocatalysts, we developed a model of ABO3-type perovskites using machine learning methods based on atomic and experimental parameters. This model can be used to predict specific surface area (SSA), a key parameter closely associated with photocatalytic activity. The model construction involved several steps, including data collection, feature selection, model construction, web-service development, virtual screening and mechanism elucidation. Statistical analysis revealed that the support vector regression model achieved a correlation coefficient of 0.9462 for the training set and 0.8786 for the leave-one-out cross-validation. The potential perovskites with higher SSA than the highest SSA observed in the existing dataset were identified using the model and our computation platform. We also developed a webserver of the model, freely accessible to users. The methodologies outlined in this study not only facilitate the discovery of new perovskites but also enable exploration of the correlations between the perovskite properties and the physicochemical features. These findings provide valuable insights for further research and applications of perovskites using machine learning techniques.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Accelerated Design for Perovskite-Oxide-Based Photocatalysts Using Machine Learning Techniques

Zhai,

Chen

2024

Materials

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First Principle Investigations of Cesium Based Cubic CsSiX₃ (X = Cl and F) Perovskites for Solar Conversion Applications: A DFT Study

Shahzad,

Hussain,

Ashraf

et al. 2024

Int J of Quantum Chemistry

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The use of solar water‐splitting technology is anticipated to reduce the disparity between demand and consumption of energy. Herein, CASTEP software is used to investigate the perovskite CsSiX3 (X = Cl and F) materials by applying GGA‐PBE exchange–correlation functional. According to structure properties, compounds possess a cubic structure of “pm3m” by using space group 221. The direct band gaps in the CsSiX3 (X = Cl and F) compounds are 1.04 and 1.07 eV, respectively. Measures of the density of states and the partial density of states (PDOS) are being utilized to determine the degree of electron localization in several bands. The compounds' optical characteristics are examined by altering their relation between the dielectric function (DF) scales and the pertinent peak. According to our results, the mechanical properties show that CsSiCl3 is brittle (0.13, 045) and CsSiF3 is ductile (0.32, 2.52) and stable with covalent bonds. Compounds CsSiCl3 and CsSiF3 modulus and elastic constants are {B (8.259, 52.375), E (8.110, 55.082), and G (18.331, 20.790)} and {C11 (13.766, 73.566), C12 (5.506, 41.780), and C44 (10.763, 24.052)} are found, according to mechanical properties. Therefore, such materials can be used for photovoltaic light absorption in the visible spectrum. These materials offer a wide range of possible uses in sensing and solar conversion because compounds combine effectively.

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Spectral scheme for atomic structure calculations in density functional theory

Bhowmik,

Pask,

Medford

et al. 2025

Computer Physics Communications

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Stabilizing the dopability of chalcogens in BaZrO3 through TiZr co-doping and its impact on the opto-electronic and photocatalytic properties: A meta-GGA level DFT study

Cited by 3 publications

References 49 publications

Accelerated Design for Perovskite-Oxide-Based Photocatalysts Using Machine Learning Techniques

Accelerated Design for Perovskite-Oxide-Based Photocatalysts Using Machine Learning Techniques

First Principle Investigations of Cesium Based Cubic CsSiX₃ (X = Cl and F) Perovskites for Solar Conversion Applications: A DFT Study

Spectral scheme for atomic structure calculations in density functional theory

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Stabilizing the dopability of chalcogens in BaZrO3 through TiZr co-doping and its impact on the opto-electronic and photocatalytic properties: A meta-GGA level DFT study

Cited by 3 publications

References 49 publications

Accelerated Design for Perovskite-Oxide-Based Photocatalysts Using Machine Learning Techniques

Accelerated Design for Perovskite-Oxide-Based Photocatalysts Using Machine Learning Techniques

First Principle Investigations of Cesium Based Cubic CsSiX3 (X = Cl and F) Perovskites for Solar Conversion Applications: A DFT Study

Spectral scheme for atomic structure calculations in density functional theory

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Product

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First Principle Investigations of Cesium Based Cubic CsSiX₃ (X = Cl and F) Perovskites for Solar Conversion Applications: A DFT Study