Shalini Thakkar

Bio: Shalini Thakkar is an academic researcher from Deakin University. The author has contributed to research in topics: Arsenic & Colloidal gold. The author has an hindex of 1, co-authored 1 publications receiving 12 citations. Previous affiliations of Shalini Thakkar include The Energy and Resources Institute.

Arsenic ion assisted core–satellites nano-assembly of gold nanoparticles for its colorimetric determination in water

Abstract: Arsenic contamination in water has threatened lives globally. The capability of arsenic to interact with the sulfhydryl group of amino acids in human body is considered as one of the factors leading to its increased toxicity and there is the dire need for development of better detection platforms. In this study, advantage of natural biomimetic interaction between thiol rich ligands and arsenic ions along with the effect of nanoarchitecture was evaluated by fabricating a heterostructural bioreceptor probe which interacts with arsenic based on affinity interaction to bring about a visual colorimetric response via plasmon coupling. As (III) ions can bind to these selective ligands and self-assemble to form gold nanoparticle networks. The mesh-like nanoarchitecture enhances the available surface area for interaction between selective bioreceptor heads and As (III) ions. The developed chemoprobe was validated by assessing the spiked real water samples with recoveries of 95–103%. The results indicate that the chemical nanoprobe was responsive over a wide linear range of 1 to 200 μg L −1 , offering the detection limit of 0.22 μg L −1 and selective for As (III) ions in a presence of 10 times more concentrated solution of the competing ions which indicates at the potential of nano-architecture in improving current detection systems. • Arsenic ion triggered core–satellite assembly of gold nanoparticles • Colorimetric determination of arsenic ions in water • Heterogeneous gold nanoparticles as nanoprobes for enhanced detection sensitivity • Amino acid functionalized smart nanoprobes for heavy metal detection • Feasibility of colorimetric assay in food and agro industries

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review.

Abstract: With the arrival of new technologies in modern smart factories, automated predictive maintenance is also related to production robotisation. Intelligent sensors make it possible to obtain an ever-increasing amount of data, which must be analysed efficiently and effectively to support increasingly complex systems' decision-making and management. The paper aims to review the current literature concerning predictive maintenance and intelligent sensors in smart factories. We focused on contemporary trends to provide an overview of future research challenges and classification. The paper used burst analysis, systematic review methodology, co-occurrence analysis of keywords, and cluster analysis. The results show the increasing number of papers related to key researched concepts. The importance of predictive maintenance is growing over time in relation to Industry 4.0 technologies. We proposed Smart and Intelligent Predictive Maintenance (SIPM) based on the full-text analysis of relevant papers. The paper's main contribution is the summary and overview of current trends in intelligent sensors used for predictive maintenance in smart factories.

Recent advances in the application of nanomaterials for the remediation of arsenic-contaminated water and soil

Abstract: This review specifically deals with the latest advances in the application of nanotechnologies and nanocomposites for remediation of arsenic (As)-contaminated water and soil. Remediation mechanisms generally include physicochemical adsorption and (photo)chemical redox reactions and filtration. Recently, various types of engineered organic/inorganic nanocomposites have been designed in membrane forms, embedded structures, or composites with extraordinary physical-chemical properties, and outstanding capacity for removal or immobilization of As in contaminated sites. In the present article, we give an overview of engineered nanomaterials developed recently (2017–2021) and their interaction mechanisms with As in contaminated water and soil. Emerging approaches include the development of bio-nanocomposites and nanomaterials that show both oxidative and adsorptive capacities. For the first time, we set out to perform a comprehensive assessment of the advantages of nanomaterials in As-contaminated soils with the focus on the mechanisms of decreasing bioavailability and leaching of As. Although great researches have been developed, serious study gaps and a new direction to future researches have been identified.

In-situ polymerization of dendritic polyaniline nanofibers network embedded with Ag@SiO2 core-shell nanoparticles for electrochemical determination of trace arsenic(III)

Abstract: Arsenic(III) is a highly toxic pollutant in the environment, and the development of nanomaterials with high electrochemical activity for As(III) detection is a research focus at present. Herein, an electrochemical sensing platform based on polyaniline nanofibers embedded with [email protected]2 nanoparticles ([email protected]2/PANI NFs) was successfully constructed for trace As(III) determination. Owing to an in-situ chemical oxidation polymerization strategy, the polyaniline nanofibers loaded with [email protected]2 core-shell nanoparticles blossomed into the dendritic three-dimensional network. The unique structure with a huge specific surface area greatly enhanced the adsorption efficiency of As(III). Combined with the outstanding conductivity of polyaniline and the electrocatalytic ability of uniformly dispersed AgNPs, the stripping current signal of As(III) was further amplified. Based on the optimized conditions, the sensitivity of 0.83 μA μg−1 L was obtained in the linear range of 0.1 ~ 100 μg L−1 with a low detection limit of 0.013 μg L−1. And the selectivity, reproducibility, and long-term stability of this sensor were excellent. Additionally, satisfactory results were achieved by the recovery experiment of real samples, and the accuracy of this method was verified by comparison with ICP-MS. The above results demonstrated the promising application of the as-fabricated sensor in As(III) detection.