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Nanosensors have a wide range of applications because of their high sensitivity, selectivity and specificity. In the past decade, extensive and pervasive research related to nanosensors has led to significant progress in diverse fields, such as biomedicine, environmental monitoring and industrial process control. This led to better and more efficient detection and monitoring of physical and chemical properties at better resolution, opening new horizons in the development of novel technologies and applications for improved human health, environment protection, enhanced industrial processes, etc.

In this paper, the authors discuss the application of citation network analysis in the field of nanosensor research and development. Cluster analysis was carried out using papers published in the field of nanomaterial-based sensor research, and an in-depth analysis was carried out to identify significant clusters. The purpose of this study is to provide researchers to identify a pathway to the emerging areas in the field of nanosensor research. The authors have illustrated the knowledge base, knowledge domain and knowledge progression of nanosensor research using the citation analysis based on 3,636 Science Citation Index papers published during the period 2011 to 2021.

Among these papers, the bibliographic study identified 809 significant research publications, 11 clusters, 556 research sector keywords, 1,296 main authors, 139 referenced authors, 63 nations, 206 organizations and 42 journals. The authors have identified single quantum dot (QD)-based nanosensor for biological applications, carbon dot-based nanosensors, self-powered triboelectric nanogenerator-based nanosensor and genetically encoded nanosensor as the significant research hotspots that came to the fore in recent years. The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

This is a novel bibliometric analysis in the area of “nanomaterial based sensor,” which is carried out in CiteSpace software.

The purpose of this study is to investigate the predictive influence of transactional leadership on employee green creative behaviour (GCB) and the mediating role of workplace learning and green knowledge management (GKM) in this relationship. Based on the leader–member exchange (LMX) theory. This study also uses moderated mediation analysis to investigate social networking sites (SNS) use as a moderator to better understand the indirect relationship between transactional leadership and employee GCB.

The data for this quantitative study were collected using a time-lag technique, with two time waves apart by two months. The final sample for the study included 294 employee–supervisor dyads from small and medium-sized tourism enterprises in the north eastern part of China.

Findings supported the study's proposed hypotheses, indicating that transactional leadership has a significant impact on workplace learning and GKM, as well as a significant role of mediators (workplace learning and GKM) in the relationship between transactional leadership and employee GCB. Furthermore, SNS use significantly moderated the impact of both mediators in establishing a link between transactional leadership and employee GCB.

This study offers new perspectives and insights for entrepreneurs, decision-makers, academics and tourism sector experts by identifying and putting into practise the predictive role of transactional leadership in innovative behaviours. This study also suggests that small and mid-sized travel agencies should focus on workplace learning, GKM and SNS use to promote environment-friendly creative employee behaviour.

This study aims to examine the moderating effect of cultural conditions on the relationship between environmental performance and environmental disclosure.

The authors used meta-analysis technique to examine 100 effect sizes from 43 studies published between 1982 and 2023 to integrate the existing results and to detect causes contributing to variability of results across studies.

There is a significant positive relationship between environmental performance and environmental disclosure. Further, the authors found that cultures with long-term orientation positively moderated the relationship, whereas cultures with high uncertainty avoidance and indulgence negatively moderated it.

This study did not account for the problem of endogeneity between environmental performance and environmental disclosure because most of the already published studies included in the authors’ meta-analysis did not address this issue.

This research provides regulators and policymakers insights on the influence of cultural factors on environmental disclosure and performance, critical information to consider when adopting, or revising social and environmental policy and regulations within a country.

To the best of the authors’ knowledge, this is the first meta-analysis study examining different cultural dimensions influencing the relationship between environmental performance and environmental disclosure and contributes new knowledge to the literature on determinants of environmental disclosure.

The purpose of this study is to experimentally investigate the large deformation compression characteristics of fused deposition modelling (FDM)-printed poly lactic acid (PLA), considering the combined effect of infill density and strain rate, and to develop a constitutive viscoplastic model that can incorporate the infill density to predict the experimental result.

The experimental approach focuses on strain rate-dependent (2.1 × 10⁻⁴, 2.1 × 10⁻³, and 2.1 × 10⁻² s⁻¹) compression testing for varied infill densities. Scanning electron microscopy (SEM) imaging of compressed materials is used to investigate deformation processes. A hyperelastic-viscoplastic constitutive model is constructed that can predict mechanical deformations at different strain rates and infill densities.

The yield stress of PLA increased with increase in strain rate and infill density. However, higher degree of strain-softening response was witnessed for the strain rate corresponding to 2.1 × 10⁻² s⁻¹. While filament splitting and twisting were identified as the damage mechanisms at higher strain rates, matrix crazing was observed as the primary deformation mechanism for higher infill density (95%). The developed constitutive model captured yield stress and post-yield softening behaviour of FDM build PLA samples with a high R² value of 0.99.

This paper addresses the need to analyse and predict the mechanical response of FDM print polymers (PLA) undergoing extensive strain-compressive loading through a hyperelastic-viscoplastic constitutive model. This study links combined effects of the printing parameter (infill density) with the experimental parameter (strain rate).