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The aim of this study was to investigate the activity of 4-((4-((2-hydroxyethyl)(methyl)amino)benzylidene) amino)-1,5-dimethyl-2-phenyl-1,2-dihydro-3H-pyrazol-3-one (HEMAP), a Schiff base synthesized and characterized for the first time, to the authors’ knowledge, as a novel inhibitor against corrosion of mild steel (MS) in hydrochloric acid solution.

HEMAP was characterized by some spectroscopic methods including High-Resolution Mass Spectrometry (HRMS), Proton Nuclear Magnetic Resonance (1H NMR), Carbon-13 (C13) nuclear magnetic resonance (13C NMR) and Fourier Transform Infrared Spectroscopy (FT-IR). Then, the inhibition efficiency of HEMAP on MS in a hydrochloric acid solution was investigated by potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). To explain the inhibition mechanism, the surface charge, adsorption isotherms and thermodynamic parameters of MS in the inhibitor solution were studied.

EIS tests displayed that the highest inhibition efficiency was calculated approximately as 99.5% for 5 × 10⁻² M HEMAP in 1 M HCl solution. The adsorption of HEMAP on the MS surface was found to be compatible with the Langmuir model isotherm. The thermodynamic parameter results showed that the standard free energy of adsorption of HEMAP on the MS surface was found to be more chemical than physical.

This study is important in terms of demonstrating the performance of the first synthesized HEMAP molecule as an inhibitor against the corrosion of MS in acidic media. EIS tests displayed that the highest inhibition efficiency was calculated approximately as 99.5% for 5 × 10⁻² M HEMAP in 1 M HCl solution.

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 main purpose of this study was to prepare the cotton fibers and cellulose powder by a layer of nano-crystalline-titanium dioxide (TiO₂) using the sol-gel sono-synthesis method to clean the wastewater containing reactive dye. Moreover, TiO₂ nano-materials are remarkable due to their photoactive properties and valuable applications in wastewater treatment.

In this research, TiO₂ was synthesized and deposited effectively on cotton fibers and cellulose powder using ultrasound-assisted coating. Further, tetra butyl titanate was used as a precursor to the synthesis of TiO₂ nanoparticles. Reactive dye (red 195) was used in this study. X-ray Diffraction, scanning electron microscopy and Fourier transform infrared spectroscopy were performed to prove the aptitude for the formation of crystal TiO2 on the cotton fibers and cellulose powder along with TiO₂ nanoparticles as well as to analyze the chemical structure. Decoloration of the wastewater was investigated through ultraviolet (UV-Visible) light at 30 min.

The experimental results revealed that the decolorization was completed at 2.0 min with the cellulose nano TiO₂ treatment whereas cotton nano TiO₂ treated solution contained reactive dyestuffs even after the treatment of 2 min. This was the fastest method up to now than all reported methods for sustainable decolorization of wastewater by absorption. Furthermore, this study explored that the cellulose TiO₂ nano-composite was more effective than the cotton TiO₂ nano-composite of decoloration wastewater for the eco-friendly remedy.

Cotton fibers and cellulose powder with nano-TiO₂, and only reactive dye (red 195) were tested.

With reactive dye-containing wastewater, it seems to be easier to get rid of the dye than to retain it, especially from dyeing of yarn, fabric, apparel, and as well as other sectors where dyestuffs are used.

This research would help to reduce pollution in the environment as well as save energy and cost.

Decoloration of wastewater treatment is an essential new track with nano-crystalline TiO2 to fast and efficient cleaning of reactive dyes containing wastewater used as a raw material.

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.

Current methods for the preparation of composite powder feedstock for selective laser melting (SLM) rely on costly nanoparticles or yield inconsistent powder morphology. This study aims to develop a cost-effective Ti6Al4V-carbon feedstock, which preserves the parent Ti6Al4V particle’s flowability, and produces in situ TiC-reinforced Ti6Al4V composites with superior traits.

Ti6Al4V particles were directly mixed with graphite flakes in a planetary ball mill. This composite powder feedstock was used to manufacture in situ TiC-Ti6Al4V composites using various energy densities. Relative porosity, microstructure and hardness of the composites were evaluated for different SLM processing parameters.

Homogeneously carbon-coated Ti6Al4V particles were produced by direct mixing. After SLM processing, in situ grown 100–500 nm size TiC nanoparticles were distributed within the α-martensite Ti6Al4V matrix. The formation of TiC particles refines the Ti6Al4V β grain size. Relative density varied between 96.4% and 99.5% depending on the processing parameters. Hatch distance, exposure time and point distance were all effective on relative porosity change, whereas only exposure time and point distance were effective on hardness change.

This work introduces a novel, cost-effective powder feedstock preparation method for SLM manufacture of Ti6Al4V-TiC composites. The in situ SLM composites achieved in this study have high relative density values, well-dispersed TiC nanoparticles and increased hardness. In addition, the feedstock preparation method can be readily adapted for various matrix and reinforcement materials in future studies.

The purpose of this paper is to investigate the process of fused filament fabrication (FFF) of a compliant gripper (CG) using thermoplastic polyurethane (TPU) material. The paper studies the applicability of different CG designs and the efficiency of some design parameters.

After reviewing a number of different papers, two designs were selected for a number of exploratory experiments. Using design of experiments (DOE) techniques to identify important design parameters. Finally, the efficiency of the parts was investigated.

The research finds that a simpler design sacrifices some effectiveness in exchange for a remarkable decrease in production cost. Decreasing infill percentage of previous designs and 3D printing them, out of TPU, experimenting with different parameters yields functional products. Moreover, the paper identified some key parameters for further optimization attempts of such prototypes.

The cost of conducting FFF experiments for TPU increases dramatically with product size, number of parameters studied and the number of experiments. Therefore, all three of these factors had to be kept at a minimum. Further confirmatory experiments encouraged.

This paper addresses an identified need to investigate applications of FFF and TPU in manufacturing functional efficient flexible mechanisms, grippers specifically. While most research focused on designing for increased performance, some research lacks discussion on design philosophy, as well as manufacturing issues. As the needs for flexible grippers vary from high-performance grippers to lower performance grippers created for specific functions/conditions, some effectiveness can be sacrificed to reduce cost, reduce complexity and improve applicability in different robotic assemblies and environments.

This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.

In industrial applications, formaldehyde-based wood adhesives have been used extensively because of their low costs and high reactivity. However, their real-world applications are hindered by some main bottlenecks, especially the formaldehyde emission and usage of nonrenewable raw materials. The purpose of this study is the development of sustainable and formaldehyde-free wood adhesive formulation.

In this study, starch and tannin-based wood adhesive were synthesized. Chemical structures and thermal properties of the prepared bio-based resin formulations were elucidated by using Fourier transform infrared and differential scanning calorimetry analysis, respectively. Laboratory scale particleboard production was carried out to determine the performance of the developed resin formulations. Obtained results were evaluated in dry medium (P2) according to European norms EN 312 (2010). Furthermore, the board formaldehyde content was determined by using the perforator method according to the European Norm EN 12460-5.

The results show that the improved starch and tannin-based wood adhesives were successful in their adhesive capacity, and the formaldehyde content of the final product was obtained as low as 0.75 mg/100 g. This paper highlights that the presented adhesive formulations could be a potential eco-friendly and cost-effective alternative to the formaldehyde-based wood adhesives for interior particleboard production.

Starch-based resins in the liquid form needed to be continuously mixed throughout their shelf life to prevent the starch from settling because it was not possible to dissolve the precipitated starch again after a while. For this reason, starch was given to the chips in powder form while preparing the particleboard.

In conclusion, this study shows that the developed bio-based resin formulations have a high potential to be used for producing interior-grade particleboards instead of commercial formaldehyde-based wood adhesives because the obtained results generally satisfied the interior grade particleboard requirements according to European norms EN 312, P2 class (2010). In addition, it was determined that the produced boards had significantly low formaldehyde content. The low formaldehyde content of the final boards was not because of the resin but because of the natural structure of the wood raw material, press parameters and environmental factors.

The developed bio-based resin system made it possible to obtain boards with significantly low formaldehyde content compared to commercial resins.

The developed bio-based resin formulation made it possible to produce laboratory-scale board prototypes at lower press factors and board densities compared to their counterparts.

This study aims to use the voice of the customer (VoC) strategy to collect user-generated content (UGC) compare customer expectations with reality, make the necessary improvements for the business and create personalized strategies for each customer to maximize revenue, focus on hospitality industry in Vietnam market.

This study proposes a synthesis of techniques for a deep understanding of the VoC based on online reviews in the hospitality industry. First, 409,054 comments were collected from websites in the hospitality sector. Second, the data will be organized, stored, cleaned, analyzed and evaluated. Next, research using business intelligence (BI) solutions integrating three models, including net promoter score (NPS), graph model and latent Dirichlet allocation (LDA), based on natural language processing (NLP) technique, experiment on Vietnamese and English data to explore the multidimensional voice of customer’s row. Finally, a dashboard system will be implemented to visualize analysis results and recommendations on marketing strategies to improve product and service quality.

Experimental results allow analysts and managers to “listen to the customer’s voice” accurately and effectively, identify relationships between entities, topics of discussion in favor of positive and negative trends.

The novelty in this study is the integration of three models, including NPS, graph model and LDA. These models are combined based on the BI solution and NLP technique. The study also conducted experiments on both Vietnamese and English languages, which ensures more effective practical application.

Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.

As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.

Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.

It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.