The dye extract of Curcuma longa (turmeric), which is very rich in curcumin, was chemically modified by complexation reaction with Zn2+, Cu2+, and Fe3+ ions to enhance its stability, electron transfer and photovoltaic performance. The dye and complexes were characterized by Ultraviolet-Visible (UV-Vis) absorption and Fourier Transform Infra-Red (FTIR) spectroscopy of potential chromophores and functional groups. The spectral data obtained indicated that the curcuminoid ligands were successfully coordinated with the metal centers, resulting in red-shifted absorption bands from beyond 460 nm and C=O vibrational frequency decreasing below 1650 cm−1. Complexation reaction resulted in improved photochemical response and enhanced light-harvesting potential. When compared, the solar cells fabricated with titanium dioxide (TiO2) photoanodes sensitized by the complexes afforded improvement in the magnitude of short-circuit current density as well as power conversion efficiency compared to the devices sensitized with the crude extract. Among the three complexes, the Zn-complex afforded the highest efficiency (1.20%), attributed to favourable electronic coupling and reduced recombination losses. Computational studies conducted through quantum chemical calculations based on the curcumin structure supported the experimental findings. The findings from this study demonstrate that metal ions-natural dye complexes have potential for application as low-cost, eco-friendly and sustainable sensitizers, thereby opening a novel horizon in green photovoltaic technologies.
Lignin, a highly complex and abundant biopolymer, forms an integral part of plant cell walls and represents a promising resource for sustainable industrial applications. Lignin has recently gained attention due to its potential use in biofuels, bioplastics, adhesives, and antioxidant formulations. This paper focuses on lignin extraction from Neolamarckia cadamba bark by deep eutectic solvent (DES) composed of thymol and menthol. Extracted lignin and starch (extracted from Colocasia esculenta roots) were used for the synthesis of bioplastic. The extracted lignin was characterized through multiple analytical techniques, including UV-V is spectroscopy, FTIR, and visual staining with safranin. Bioplastic was characterized for thermal resistance, absorbance, and solubility. The moisture content was obtained as 29.59%, water solubility as 72.61% with almost completely (98%) biodegradable. The work contributes to valorising environmental biomass and enhancing the industrial relevance of lignin. Furthermore, it aligns with the sustainable development goals by transforming bio-waste into valuable bioproducts, such as bioplastics, biochemicals, bioadsorbents, etc. The outcomes of this research may serve as a foundation for future studies in lignin-based material innovation and biorefinery integration.
Driven by the global goal of carbon neutrality, offshore floating photovoltaic (OFPV) technology has become a primary focus of photovoltaic research. In particular, flexible thin-film structures have become a central focus of research in sustainable energy development. It offers numerous advantages, including light weight, low cost, and strong adaptability to the marine environment. However, traditional experimental methods still face challenges in accurately capturing the motion response of flexible thin films. To address this issue, this study proposes a motion measurement and monitoring framework based on binocular vision. The framework is validated using gyroscope data, and the results demonstrate its high accuracy and real-time performance. The research team conducted experiments on a flexible floating photovoltaic structure in a wave flume, applying the proposed framework to monitor its motion response under wave excitation. The experimental results show that wave height and wave period have significant effects on the acceleration response of the thin film: higher wave heights lead to notably greater accelerations, whereas longer wave periods result in a gradual decrease in acceleration. Overall, the proposed framework provides reliable technical support for the design optimization and safety assessment of flexible thin-film FPV structures.
Unmanned Aerial Vehicles (UAVs) equipped with RGB cameras are increasingly used as low-cost tools for crop monitoring, offering a range of vegetation indexes in the visible spectral range. These indexes have often been reported to correlate with other multispectral indexes such as the Normalized Difference Vegetation Index (NDVI) during active growth stages. However, still efforts should be done about their performance under conditions of canopy degradation. In this study, UAV flights were conducted over a cereal field immediately after harvest, when the canopy consisted mostly of bare soil and dry residues. RGB-based indexes were calculated from the orthomosaic, normalized to a [0–1] scale, and compared to NDVI derived from a multispectral sensor. Data preprocessing included ground control point (GCP) georeferencing, removal of NoData pixels, and raster alignment. Results revealed very weak correlations between RGB indexes and NDVI (Pearson r < 0.15), with Visible Atmospherically Resistant Index (VARI) showing almost no variability across the field. Although the Leaf Index (GLI), yielded the lowest error values, all RGB indexes failed to reproduce the variability of NDVI under post-harvest conditions. These findings highlight a critical methodological limitation: RGB indexes are unsuitable for vegetation monitoring when canopy cover is severely reduced. While they remain useful during active growth, their reliability diminishes in degraded or post-harvest scenarios, thereby limiting their application in assessing abiotic stress in cereals.
The alveolar units, composed of alveolar epithelial type II cells (AT2) and type I cells (AT1), are essential for efficient gas exchange. While AT2 cells are known to play critical roles in alveolar homeostasis and regeneration, the contribution of heterogeneous AT2 cells to lung repair remains poorly understood. Here, we identified a distinct AT2 subpopulation that exclusively expressed Lysozyme 1 (Lyz1) through single-cell RNA sequencing (scRNA-seq) analyses. Cell fate mapping revealed that the Lyz1CreERT2 mouse strain specifically labeled Lyz1-expressing AT2 cells in vivo at homeostasis. Following lung injury, Lyz1+ AT2 cells expanded and contributed to alveolar regeneration by generating both self-renewing AT2 cells and differentiating AT1 cells. We further observed the emergence of de novo Lyz1-expressing cells in the airways after lung injury. Additionally, Lyz1+ AT2 cells displayed significantly enhanced proliferative capacity compared with general bulk AT2 cells in 3D organoid cultures. These findings define Lyz1+ AT2 cells as a previously unrecognized progenitor population, expanding the paradigm of alveolar regeneration and providing insight into how epithelial diversity supports lung regeneration.
