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In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.

The textile sector is moving towards new technologies, where the application of nanotechnology is offering fabrics with multifunctional properties making fabric odourless, hydrophobic, durable and self-cleaning. This aim of this research is to investigate self-cleaning ability of denim fabric with the application of zinc oxide nanoparticles (ZnO NPs) synthesized naturally. The primary focus of this investigation is achieving sustainability mark through green synthesis of ZnO NPs.

In this analysis, ZnO NPs being one of the metal oxides exhibiting self-cleaning, UV-protective and anti-microbial properties were synthesized naturally using Azadirachta Indica leaves. The prepared NPs were characterized by using X-ray diffraction and scanning electron microscopy analyses confirming their size and crystalline structure. Different formulations were investigated with varying concentration of zinc oxide and auxiliaries onto the denim fabric using pad-dry-cure application technique.

XRD analysis confirmed the successful green synthesis of ZnO NPs. SEM analysis revealed the homogeneous and hexagonal wurtzite NPs deposition on the denim fabric. It was ascertained that with 5% ZnO NPs and 7% Binder concentrations, the formulation resulted in a smooth and even layer on the denim fabric maintaining the appearance and feel at the same time offers appreciable grading (Grade 4) against the stringent stains of Ketchup, Coffee, Grape and Orange Juice with insignificant change in tensile strength.

In this study, self-cleaning attributes of denim fabric with zinc oxide nano formulations of different composition was studied to achieve promising functional properties in a single step not studied earlier.

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 shift in consumer focus towards green marketing mix elements is not a unique thing. Especially in recent times, most organizations are trying to implement green marketing strategies in order to influence customers as well as to reduce the negative impacts of environmental footprints. However, in recent times service marketing requires thorough implementation of a Green Marketing Mix as evidenced by Asian countries. However, research also claims that the use of a traditional green marketing mix is not a guarantee of success in the long run and therefore has been criticized by several researchers and scholars. Hence, there is a need to follow the Green-SIVA (Solution, Information, Access, and Value) concept in order to create a long-lasting impact on consumer buying and to discuss the application of tools in a more comprehensive manner. Although the linkage of Green-SIVA marketing might provide a new way to develop an effective marketing mix strategy for services. Hence, this chapter has been written purposely to discuss GMM elements with reference to the service industry of Pakistan and tries to develop an association with green-SIVA marketing practices in order to optimize service marketing practices.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

This study aims to address a comprehensive and integrated investigations pertaining to the preparation of AgNPs with well-defined nano-sized scale using the aforementioned poly (meth acrylic acid [MAA])–chitosan graft copolymer, which is cheap, nontoxic, biodegradable and biocompatible agent as a substitute for the traditionally used toxic reducing agents.

AgNPs are prepared under a range of conditions, containing silver nitrate and poly (MAA)–chitosan graft copolymer concentrations, time, temperature and pH of the preparation medium. To classify AgNPs obtained under the various conditions, ultraviolet–visible spectroscopy spectra and transmission electron microscopy images are used for characterization of AgNPs instrumentally in addition to the visual color change throughout the work. The work was further extended to study the application of the so prepared AgNPs on cotton fabric to see their suitability as antibacterial agent as well as their durability after certain washing cycles.

According to the current investigation, the optimal conditions for AgNPs formation of nearly 3–15 nm in size are 5 g/l, poly (MAA)–chitosan graft copolymer and 300 ppm AgNO₃ in addition to carrying out the reaction at 60°C for 30 min at pH 12. Besides, the application of the so prepared AgNPs on cotton fabric displayed a substantial reduction in antibacterial efficiency against gram-positive and gram-negative bacteria estimated even after 10 washing cycles in comparison with untreated one.

To the best of the authors’ information, no comprehensive study of the synthesis of AgNPs using poly (MAA)–chitosan graft copolymer with a graft yield of 48% has been identified in the literature.

This paper aims to fabricate a polymer-based polyethylene glycol (PEG) coating with acrylic resin as a binder that can show antiviral activity against the feline coronavirus (FCov) on the glass substrate.

The PEG/acrylic coating systems of different weight percentages were coated on the glass substrates using the spray-coating method and cured at room temperature for 24 h.

The coating system containing 20 Wt.% of PEG exhibits the highest antiviral activities as high as 99.9% against FCov compared with other samples.

Findings will be useful in the development of antiviral coating for PPE fabrics by using the simple synthesis method.

Application of PEG as an antiviral agent in the antiviral coating system with high antiviral activities about 99.9%.

This study’s aim is to introduce a high-performance sorbent for the removal of both anionic (Congo red; CR) and cationic (methylene blue; MB) dyes from aqueous solutions.

Sodium silicate is adopted as a substrate for GO and AgNPs with positive charge are used as modifiers. The synthesized nanocomposite is characterized by FTIR, FESEM, EDS, BET and XRD techniques. Then, some of the most effective parameters on the removal of CR and MB dyes such as solution pH, sorbent dose, adsorption equilibrium time, primary dye concentration and salt effect are optimized using the spectrophotometry technique.

The authors successfully achieved notable maximum adsorption capacities (Qmax) of CR and MB, which were 41.15 and 37.04 mg g⁻¹, respectively. The required equilibrium times for maximum efficiency of the developed sorbent were 10 and 15 min for CR and MB dyes, respectively. Adsorption equilibrium data present a good correlation with Langmuir isotherm, with a correlation coefficient of R2 = 0.9924 for CR and R2 = 0.9904 for MB, and kinetic studies prove that the dye adsorption process follows pseudo second-order models (CR R2 = 0.9986 and MB R2 = 0.9967).

The results showed that the proposed mechanism for the function of the developed sorbent in dye adsorption was based on physical and multilayer adsorption for both dyes onto the active sites of non-homogeneous sorbent.

The as-prepared nano-adsorbent has a high ability to remove both cationic and anionic dyes; moreover, to the high efficiency of the adsorbent, it has been tried to make its synthesis steps as simple as possible using inexpensive and available materials.

The purpose of this paper is to examine the purchase behavior of consumers towards green products by adapting and extending the theory of planned behavior with the inclusion of three pertinent environmental factors posited to reflect environmental consciousness in the form of environmental concern, environmental knowledge and environmental values.

The data was collected from 410 consumers at shopping malls with retail stores selling green and non-green products in a developing country using cluster sampling and analyzed using covariance-based structural equation modeling.

The findings of this study indicate that environmental factors reflecting environmental consciousness positively influence consumers’ attitude towards purchasing green products, wherein consumers’ environmental values have a stronger influence than their environmental concern and environmental knowledge. The findings also reveal that subjective norm, attitude and perceived behavioral control toward purchasing green products positively shape green purchase intention. The same positive effect is also witnessed between green purchase intention and behavior. However, perceived behavioral control towards purchasing green products had no significant influence on green purchase behavior.

This study suggests that green marketers should promote environmental consciousness among consumers to influence and shape their planned behavior towards green purchases. This could be done by prioritizing efforts and investments in inculcating environmental values, followed by enhancing environmental knowledge and finally inducing environmental concern among consumers. Green marketers can also leverage subjective norm and perceptions of behavioral control toward purchasing green products to reinforce green purchase intention, which, in turn, strengthens green purchase behavior. This green marketing strategy should also be useful to address the intention–behavior gap as seen through the null effect of perceived behavioral control on purchase behavior toward green products when this strategy is present.

This study contributes to theoretical generalizability by reaffirming the continued relevance of the theory of planned behavior in settings concerning the environment (e.g. green purchases), and theoretical extension by augmenting environmental concern, environmental knowledge and environmental values with the theory of planned behavior, resulting in an environmentally conscious theory of planned behavior. The latter is significant and noteworthy, as this study broadens the conceptualization and operationalization of environmental consciousness from a unidimensional to a multidimensional construct.

The problem of environmental pollution is becoming increasingly severe, and international consensus confirms the need for eco-friendly consumption. Worldwide, the eco-friendly food market is booming, so understanding consumers’ motivations to purchase these foods is crucial. This paper aimed to construct a model explaining consumers’ intentions to purchase eco-friendly food by combining stimuli-organism-response (SOR) and signalling theories and exploring the mechanisms by which macro- and micro-signals impact perceptions of value and consumers’ subsequent willingness to purchase eco-friendly food.

An online questionnaire was distributed through the Qualtrics platform, and the completed questionnaires were collected in March and April 2023. The study used partial least squares structural equation modelling (PLS-SEM) to analyse the 331 valid responses received.

The results indicated that trustworthy eco-labels for high-quality and health-promoting products, as conveyed in macro signals, significantly enhanced consumers’ perceptions of functional value. The peer effect and a moderate level of food anthropomorphism conveyed in micro-signals substantially improved their perceptions of social value, whilst the perceived value of products significantly and positively influenced their purchase intentions.

This study explains consumers’ motivations to purchase eco-friendly products. This provides an explanation for the effect of macro- and micro-signals on value perceptions. By integrating the different dimensions of these signals to create a unified research perspective, the paper provides an integrated model, thereby filling a research gap concerning the influence of two-dimensional signals on purchase intention. By supporting eco-friendly food use, the paper contributes to environmental protection and sustainable development.