Non-monotonic growth of MoS<sub>2</sub> quantum dots observed through fractal analysis: role of precursor concentration on the overall growth dynamics

Abstract The article discusses the time evolution and growth mechanics of MoS 2 quantum dots (QD) with variable precursor concentration during a bottom-up process for a hydrothermal reaction. At a constant reaction time (14 hours taken as reference), we observe a special value of concentration C * that generates the highest average QD size, which interestingly produces smaller QDs on either side of C * . These observations have been supported by morphological and photophysical studies, indicating that the compactness of the systems is impacted. This prompts us to investigate the entire growth dynamics using a statistical method like fractal analysis. We also observe a non-monotonic behaviour of bandgap with a minimum value (4.69 eV) as well as a distinct peak (≈450 nm) for the photoluminescence (PL) spectra, both occurring at the same concentration C * . Subsequently, the spatial correlation in the QD sheets that formed through aggregation during the process has been been explored through fractal analysis, yielding the highest fractal dimension, d f = 1.97 at C * . The non-monotonic behaviour of d f around C * has been attributed to an interplay of aggregation and fragmentation of the sheets combined with Ostwald ripening. As it appears that the growth dynamics of the system may be viewed in a statistical manner we further apply numerical simulations based on random walk on a 2D lattice to understand the formation of the QD sheets. The results are found to be in good agreement with the experimental results, both with increasing reaction time and for different precursor concentrations.

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Publication Details

Journal
Physica Scripta
Published
2025-03-26
DOI
https://doi.org/10.1088/1402-4896/adc5b2
Primary Topic
Machine Learning in Materials Science
Type
article
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article

Non-monotonic growth of MoS2 quantum dots observed through fractal analysis: role of precursor concentration on the overall growth dynamics

Chanchal Chakraborty, Subhadeep Roy, G K Sahu, Souri Banerjee
Physica Scripta
Machine Learning in Materials Science
article

Non-monotonic growth of MoS2 quantum dots observed through fractal analysis: role of precursor concentration on the overall growth dynamics

Chanchal Chakraborty, Subhadeep Roy, G K Sahu, Souri Banerjee
article en

Abstract

Abstract The article discusses the time evolution and growth mechanics of MoS 2 quantum dots (QD) with variable precursor concentration during a bottom-up process for a hydrothermal reaction. At a constant reaction time (14 hours taken as reference), we observe a special value of concentration C * that generates the highest average QD size, which interestingly produces smaller QDs on either side of C * . These observations have been supported by morphological and photophysical studies, indicating that the compactness of the systems is impacted. This prompts us to investigate the entire growth dynamics using a statistical method like fractal analysis. We also observe a non-monotonic behaviour of bandgap with a minimum value (4.69 eV) as well as a distinct peak (≈450 nm) for the photoluminescence (PL) spectra, both occurring at the same concentration C * . Subsequently, the spatial correlation in the QD sheets that formed through aggregation during the process has been been explored through fractal analysis, yielding the highest fractal dimension, d f = 1.97 at C * . The non-monotonic behaviour of d f around C * has been attributed to an interplay of aggregation and fragmentation of the sheets combined with Ostwald ripening. As it appears that the growth dynamics of the system may be viewed in a statistical manner we further apply numerical simulations based on random walk on a 2D lattice to understand the formation of the QD sheets. The results are found to be in good agreement with the experimental results, both with increasing reaction time and for different precursor concentrations.

Physica ScriptaVol. 100(5)
Synergy University Dubai (AE), Birla Institute of Technology and Science - Hyderabad Campus (IN), Birla Institute of Technology and Science, Pilani - Dubai Campus (AE)
Openalex Percentile: Top 96%
Machine Learning in Materials Science
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