Nanomaterials for advanced photovoltaic cells

Kumar, Neeraj; Phani, M. Kalyan; Chamoli, Pankaj; Manoj, Manoranjan Kumar; Sharma, Ashutosh; Ahmed, Waqar; Srivastava, Ashok; Kumar, S. Phani

doi:10.1016/b978-0-12-821346-9.00006-7

Cited by 3 publications

(11 citation statements)

References 67 publications

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“…Within the context of video colorization, the majority of techniques are based on GAN-based methods [15], [16], as well as the utilization of transformer-based approaches [17] such as those featured in [7], [18], [19]. Notably, Saharia et al [20] propose leveraging diffusion models for various image-to-image tasks, including colorization.…”

Section: Research Contributionmentioning

confidence: 99%

“…Kumar et al have introduced ColTran [18], a transformerbased image colorization model that operates through a threestep process. Initially, it colorizes a low-resolution version of the image, as it leverages self-attention, which is computationally demanding for high-resolution photos.…”

Section: Related Work a Conventional Deep Learning Approachesmentioning

confidence: 99%

“…The qualitative results in Figure 7 visually compare the colorization performance of different methods, including DeOldify [6], ColTran [18], DeepRemaster [42], GCP [31], VCGAN [41], LatentColorization without temporal consistency enabled, LatentColorization, and the ground truth. These comparisons are based on image sequences from the GRID [58] and Lombard Grid [59] datasets.…”

Section: A Qualitative Analysismentioning

confidence: 99%

“…Table 2 provides a quantitative evaluation of the colorization methods, considering various image metrics. It is a useful way to compare the performance of DeOldify [6], DeepRemaster [42], ColTran [18], GCP [31], VCGAN [41] , LatentColorization without temporal consistency mechanism, LatentColorization, and human colorization. By assessing metrics such as PSNR, SSIM, FID, FVD, NIQE, and BRISQUE, you can analyze the quality, similarity, and naturalness of the colorized images.…”

Section: B Quantitative Analysismentioning

confidence: 99%

“…The comparison between LatentColorization and nonautoregressive models like ColTran [18] provides insights into the importance of the autoregressive nature of the system in the context of video colorization. Fig 7 demonstrates the difference in consistency between the two approaches.…”

Section: A Model Comparisonsmentioning

confidence: 99%

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LatentColorization: Latent Diffusion-Based Speaker Video Colorization

Ward,

Bigioi,

Basak

et al. 2024

IEEE Access

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While current research predominantly focuses on image-based colorization, the domain of video-based colorization remains relatively unexplored. Most existing video colorization techniques operate on a frameby-frame basis, often overlooking the critical aspect of temporal coherence between successive frames. This approach can result in inconsistencies across frames, leading to undesirable effects like flickering or abrupt color transitions between frames. To address these challenges, we harness the generative capabilities of a fine-tuned latent diffusion model designed specifically for video colorization, introducing a novel solution for achieving temporal consistency in video colorization, as well as demonstrating strong improvements on established image quality metrics compared to other existing methods. Furthermore, we perform a subjective study, where users preferred our approach to the existing state of the art. Our dataset encompasses a combination of conventional datasets and videos from television/movies. In short, by leveraging the power of a fine-tuned latent diffusion-based colorization system with a temporal consistency mechanism, we can improve the performance of automatic video colorization by addressing the challenges of temporal inconsistency. A short demonstration of our results can be seen in some example videos available at https://youtu.be/vDbzsZdFuxM.

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Section: Research Contributionmentioning

confidence: 99%

Section: Related Work a Conventional Deep Learning Approachesmentioning

confidence: 99%

Section: A Qualitative Analysismentioning

confidence: 99%

Section: B Quantitative Analysismentioning

confidence: 99%

Section: A Model Comparisonsmentioning

confidence: 99%

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LatentColorization: Latent Diffusion-Based Speaker Video Colorization

Ward,

Bigioi,

Basak

et al. 2024

IEEE Access

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Comparative investigation of magnetic, di-electric, optical, and electrical properties of mono-BaFe2O4 and hexa-BaFe12O19 nano-ferrites for photovoltaic (PV) applications

Khan

Gul

2022

Appl. Phys. A

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A Review of the Technological Advances in the Design of Highly Efficient Perovskite Solar Cells

Njema,

Kibet

2023

International Journal of Photoenergy

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The search for renewable and sustainable energy for energy security and better environmental protection against hazardous emissions from petro-based fuels has gained significant momentum in the last decade. Towards this end, energy from the sun has proven to be reliable and inexhaustible. Therefore, better light harvesting technologies have to be sought. Herein, the current trends in the development of perovskite solar cells with a focus on device engineering, band alignment, device fabrication with superior light harvesting properties, and numerical simulation of solar cell architectures are critically reviewed. This work will form the basis for future scientist to have a better scientific background on the design of highly efficient solar cell devices, which are cost-effective to fabricate, highly stable, and eco-friendly. This review presents thorough essential information on perovskite solar cell technology and tracks methodically their technological performance overtime. The photovoltaic (PV) technology can help to reduce pollution related to greenhouse gas emissions, criterion pollutant emissions, and emissions from heavy metals and radioactive species by nearly 90%. Following the introduction of highly efficient perovskite solar cell (PSC) technologies, the problems associated with stability, short life-time and lead-based perovskite solar cell configurations have significantly been minimized. The fabrication and simulation of perovskite solar cells has been made possible with advanced technologies and state-of-the-art computational codes. Furthermore, device simulation strategies have lately been used to understand, select appropriate materials, and gain insights into solar cell devices’ physical behavior in order to improve their performances. Numerical simulation softwares such as the 1-dimenional solar cell capacitance simulator (SCAPS-1D), Silvaco ATLAS, and wx-analysis of microelectronic and photonic structures (wxAMPS) used to understand the device engineering of solar cells are critically discussed. Because of the need to produce charge collection selectivity, hole transport materials (HTMs) as well as electron transport materials (ETMs) constitute essential PSC components. In this work, the synthesis of inorganic HTMs, as well as their characteristics and uses in various PSCs comprising mesoporous and planar designs, are explored in detail. It is anticipated that the performance of inorganic HTLs on PSCs would encourage further research which will have a significant influence on the future designs and fabrication of highly efficient solar cells.

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Nanomaterials for advanced photovoltaic cells

Cited by 3 publications

References 67 publications

LatentColorization: Latent Diffusion-Based Speaker Video Colorization

LatentColorization: Latent Diffusion-Based Speaker Video Colorization

Comparative investigation of magnetic, di-electric, optical, and electrical properties of mono-BaFe2O4 and hexa-BaFe12O19 nano-ferrites for photovoltaic (PV) applications

A Review of the Technological Advances in the Design of Highly Efficient Perovskite Solar Cells

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