Search results

Using microwave low-pressure discharge, we synthesised magnetic iron-oxide nanopowder from the iron pentacarbonyl precursor. We were able to vary the size and chemical composition (especially the ratio between various iron oxides) by careful control of the process parameters. The nanoparticulate product was analysed by X-ray diffraction (XRD) and Raman spectroscopy. However, the XRD cannot reliably distinguish between the size-broadened peaks of γ-Fe₂O₃ (maghemite) and Fe₃O₄ (magnetite) due to their nearly identical crystalline structure. Hence we used a chemical method to determine the presence of Fe(II) and Fe(III) ions in the nanopowder samples. The results agree with those from the Raman spectroscopy.

This review aims to focus on recent reported research work on the construction and function of different electrochemical DNA biosensors. It also describes different sensing materials, chemistries of immobilization probes, conditions of hybridization and principles of transducing and amplification strategies.

The human disease-related mutated genes or DNA sequence detection at low cost can be verified by the electrochemical-based biosensor. A range of different chemistries is used by the DNA-based electrochemical biosensors, out of which the interactions of nanoscale material with recognition layer and a solid electrode surface are most interesting. A diversity of advancements has been made in the field of electrochemical detection.

Some important aspects are also highlighted in this review, which can contribute in the creation of successful biosensing devices in the future.

This paper provides an updated review of construction and sensing technologies in the field of biosensing.

This paper is aimed at analyzing the inter-contextual relationships among the factors that led to inadequate management of electronic and electrical waste (WEEE) during COVID-19 using a subjective perspective.

Grey sets and a Decision-Making Trial and Evaluation Laboratory (DEMATEL)-based approach has been employed to identify the causal association of intertwined WEEE management barriers.

Results reveal the lack of implementation of the legislative framework, extended producer responsibility and lesser corporate initiatives are some of the most challenging WEEE management challenges during the current pandemic.

The findings of the study would enable stakeholders of WEEE management toward building resilient policies and effective implementation plans during as well as post-crisis situations.

COVID-19 led challenges related to healthcare waste have attracted a significant amount of scholarly attention, but there has been lesser attention toward e-waste management challenges during the pandemic. Negligence toward e-waste management can pose threats to the environment as well as human well-being.

Waste classification plays an important role in reducing pollution, promoting waste recycling and resource utilization. This paper aims to explore the multiple reasons that affect the performance of waste classification governance.

Content analysis of the existing waste classification policies is conducted using the Latent Dirichlet Allocation (LDA) model. Based on this analysis, influencing factors are identified through the technology-organization-environment (TOE) research framework. The condition configurations and action paths that cause differences in governance performance are derived using the fuzzy-set qualitative comparative analysis method (fsQCA).

The results show that there are spatial and temporal disparities in waste classification policies among different provinces/cities. In most situations, the implementation effect of policy combinations is better than that of a single type of policy, with mandatory policies playing a key role. Additionally, a single influencing factor cannot constitute the bottleneck of high governance performance. Policy topics coordinate with environmental and technical factors to influence governance performance. Finally, in light of China's actual governance situation, several targeted implications are proposed for the practical optimization of local government waste classification governance.

This paper presents a novel approach by integrating multiple heterogeneous data sources from both online and offline channels, adopting a public-government perspective and applying the fsQCA method to investigate the combined effects of technical, organizational and environmental factors on waste classification governance performance across 31 provinces and cities in China.