Plasmonic gold nanoparticle incorporated MgO-coated SnO2 photoanode for efficiency enhancement in dye-sensitized solar cells

SnO2 is an attractive semiconducting material suitable for application as the photoanode in dye sensitized solar cells (DSSCs) due to its wide energy band gap and notable photo stability. However, improved solar cell performance can be achieved only by using composites of SnO2 with other materials like MgO, ZnO, Al2O3 and CaCO3. In this study, plasmonic DSSCs were fabricated using MgO coated SnO2 (SnO2:MgO) based photoanodes incorporating gold nanoparticles (Au NP) having the size in the 30 – 35 nm range and sensitized with ruthernium N719 dye. Photoanodes were characterized by UV–VIS spectroscopy and the DSSCs were characterized by current–voltage (J–V) measurements, incident photon-to-electron conversion efficiency (IPCE) measurements and electrochemical impedance spectroscopy (EIS). Under the illumination of 100 mW cm−2 (AM 1.5), the efficiency (η) of the reference DSSC with pristine SnO2 photoanode was 1.52%, where as the efficiency of the optimized plasmonic DSSC with Au NP incorporated SnO2:MgO photoanode (Au: SnO2:MgO) was an impressive 4.69%. This efficiency enhancement of about 208% compared to the reference DSSC appears to be due to the increased open-circuit voltage (VOC) of 725.6 and increased short-circuit photocurrent density (JSC) of 9.06 mA cm−2 respectively evidently caused by the reduced electron recombination by ultra-thin MgO barrier layer and the enhanced light harvesting caused by the local surface plasmon resonance (LSPR) effect due to Au nanopraticles. EIS analysis showed that the incorporation of plasmonic Au metal nanoparticles leads to a decrease in the series resistance (RS) and the interfacial charge-transfer resistance (RCT) at the SnO2/electrolyte interface.</p

Characterization of poly (vinylidene fluoride-co-hexafluoropropylene) (PVdF-HFP) nanofiber membrane based quasi solid electrolytes and their application in a dye sensitized solar cell

The electrolyte plays a major role in dye sensitized solar cells (DSSCs). In this work a quasi-solid state (gel) electrolyte has been formed by incorporating a liquid electrolyte made with KI dissolved in ethylene carbonate (EC) and propylene carbonate (PC) co-solvent in poly (vinylidene fluoride-hexafluoropropylene) (PVdF-HFP) co-polymer nanofiber membrane prepared by electrospinning. SEM images of the electrolyte membrane showed the formation of a three-dimensional network of polymer nanofibers with diameters between 100 and 300 nm and an average membrane thickness of 14 μm. The electrolyte was characterized by FTIR and differential scanning calorimetry (DSC) measurements. The DSSCs fabricated with this electrolyte were characterized by current-voltage and Electrochemical Impedance Spectroscopy (EIS) measurements. DSC thermograms revealed that the crystallinity of the PVdF-HFP nanofiber is 14% lower than that of the pure PVdF-HFP polymer while the FTIR spectra showed a reduced polymer-polymer interaction in the nano fiber based gel electrolyte. The DSSCs fabricated with nanofiber based gel electrolyte showed an energy conversion efficiency of 5.36% under 1.5 a.m. solar irradiation, whereas the efficiency of the DSSC made with the liquid electrolyte based cell was 6.01%. This shows the possibility of replacing the liquid electrolyte in DSSCs by electro-spun polymer nanofiber based gel electrolyte and thereby minimizing some major drawbacks associated with liquid electrolyte based solar cells while maintaining a reasonably high efficiency

Efficiency enhancement in dye-sensitized solar cells with co-sensitized, triple layered photoanode by enhanced light scattering and spectral responses

Abstract: A method for impressive efficiency enhancement in TiO2-based nanoparticle (NP) dye-sensitized solar cells (DSSCs) is demonstrated by using a co-sensitized triple layered photoanode, comprising a nanofibre (NF) layer of TiO2 sandwiched between two TiO2 P25 NP layers. Rose Bengal (RB) and Eosin-Y (EY) dyes are used for the co-sensitization. DSSCs with conventional TiO2 (P25) NP bi-layer photoanode (NP/NP), sensitized with EY, showed an overall power conversion efficiency (η) of 0.89% under the illumination of 100 mW cm–2 (AM 1.5) with iodide-based liquid electrolyte. Whereas DSSCs fabricated with triple layered photoanode (NP/NF/NP) with the same total thickness and sensitized with EY yielded 1.77% efficiency under the same illumination conditions, showing an impressive ~99% enhancement in the overall power conversion efficiency. The DSSCs fabricated with RB-sensitized NP/NP and NP/NF/NP photoanodes showed 0.25 and 0.73% efficiencies, respectively. Upon optimization, DSSCs fabricated with co-sensitized NP/NP bi-layer and NP/NF/NP triple layer photoanodes showed 1.04 and 2.09% efficiencies, respectively, showing again an impressive ~100% enhancement in η due to the co-sensitized triple layer photoanode structure. Increase in the short circuit photocurrent density, UV–visible absorptions measurements, incident photon to current efficiency and electrochemical impedance spectroscopic measurements confirmed that this enhancement is very likely due to the enhanced light harvesting and reduction of recombination of photoelectrons combined with the enhanced spectral responses of the co-sensitized triple layered photoanode.</p

AusTraits: a curated plant trait database for the Australian flora

INTRODUCTION AusTraits is a transformative database, containing measurements on the traits of Australia’s plant taxa, standardised from hundreds of disconnected primary sources. So far, data have been assembled from &gt; 250 distinct sources, describing &gt; 400 plant traits and &gt; 26,000 taxa. To handle the harmonising of diverse data sources, we use a reproducible workflow to implement the various changes required for each source to reformat it suitable for incorporation in AusTraits. Such changes include restructuring datasets, renaming variables, changing variable units, changing taxon names. While this repository contains the harmonised data, the raw data and code used to build the resource are also available on the project’s GitHub repository, http://traitecoevo.github.io/austraits.build/. Further information on the project is available in the associated publication and at the project website austraits.org. Falster, Gallagher et al (2021) AusTraits, a curated plant trait database for the Australian flora. Scientific Data 8: 254, https://doi.org/10.1038/s41597-021-01006-6 CONTRIBUTORS The project is jointly led by Dr Daniel Falster (UNSW Sydney), Dr Rachael Gallagher (Western Sydney University), Dr Elizabeth Wenk (UNSW Sydney), and Dr Hervé Sauquet (Royal Botanic Gardens and Domain Trust Sydney), with input from &gt; 300 contributors from over &gt; 100 institutions (see full list above). The project was initiated by Dr Rachael Gallagher and Prof Ian Wright while at Macquarie University. We are grateful to the following institutions for contributing data Australian National Botanic Garden, Brisbane Rainforest Action and Information Network, Kew Botanic Gardens, National Herbarium of NSW, Northern Territory Herbarium, Queensland Herbarium, Western Australian Herbarium, South Australian Herbarium, State Herbarium of South Australia, Tasmanian Herbarium, Department of Environment, Land, Water and Planning, Victoria. AusTraits has been supported by investment from the Australian Research Data Commons (ARDC), via their “Transformative data collections” (https://doi.org/10.47486/TD044) and “Data Partnerships” (https://doi.org/10.47486/DP720) programs; fellowship grants from Australian Research Council to Falster (FT160100113), Gallagher (DE170100208) and Wright (FT100100910), a grant from Macquarie University to Gallagher. The ARDC is enabled by National Collaborative Research Investment Strategy (NCRIS). ACCESSING AND USE OF DATA The compiled AusTraits database is released under an open source licence (CC-BY), enabling re-use by the community. A requirement of use is that users cite the AusTraits resource paper, which includes all contributors as co-authors: Falster, Gallagher et al (2021) AusTraits, a curated plant trait database for the Australian flora. Scientific Data 8: 254, https://doi.org/10.1038/s41597-021-01006-6 In addition, we encourage users you to cite the original data sources, wherever possible. Note that under the license data may be redistributed, provided the attribution is maintained. The downloads below provide the data in two formats: austraits-3.0.2.zip: data in plain text format (.csv, .bib, .yml files). Suitable for anyone, including those using Python. austraits-3.0.2.rds: data as compressed R object. Suitable for users of R (see below). Both objects contain all the data and relevant meta-data. AUSTRAITS R PACKAGE For R users, access and manipulation of data is assisted with the austraits R package. The package can both download data and provides examples and functions for running queries. STRUCTURE OF AUSTRAITS The compiled AusTraits database has the following main components: austraits ├── traits ├── sites ├── contexts ├── methods ├── excluded_data ├── taxanomic_updates ├── taxa ├── definitions ├── contributors ├── sources └── build_info These elements include all the data and contextual information submitted with each contributed datasets. A schema and definitions for the database are given in the file/component definitions, available within the download. The file dictionary.html provides the same information in textual format. Full details on each of these components and columns are contained within the definition. Similar information is available at http://traitecoevo.github.io/austraits.build/articles/Trait_definitions.html and http://traitecoevo.github.io/austraits.build/articles/austraits_database_structure.html. CONTRIBUTING We envision AusTraits as an on-going collaborative community resource that: Increases our collective understanding the Australian flora; and Facilitates accumulation and sharing of trait data; Builds a sense of community among contributors and users; and Aspires to fully transparent and reproducible research of the highest standard. As a community resource, we are very keen for people to contribute. Assembly of the database is managed on GitHub at traitecoevo/austraits.build. Here are some of the ways you can contribute: Reporting Errors: If you notice a possible error in AusTraits, please post an issue on GitHub. Refining documentation: We welcome additions and edits that make using the existing data or adding new data easier for the community. Contributing new data: We gladly accept new data contributions to AusTraits. See full instructions on how to contribute at http://traitecoevo.github.io/austraits.build/articles/contributing_data.html

AusTraits, a curated plant trait database for the Australian flora

International audienceWe introduce the austraits database-a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual-and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge