In this review, recent advances regarding the integration of machine learning into electrochemical analysis are overviewed, focusing on the strategies to increase the analytical context of electrochemical data for enhanced machine learning applications. While information-rich electrochemical data offer great potential for machine learning applications, limitations arise when sensors struggle to identify or quantitatively detect target substances in a complex matrix of non-target substances. Advanced machine learning techniques are crucial, but equally important is the development of methods to ensure that electrochemical systems can generate data with reasonable variations across different targets or the different concentrations of a single target. We discuss five strategies developed for building such electrochemical systems, employed in the steps of preparing sensing electrodes, recording signals, and analyzing data. In addition, we explore approaches for acquiring and augmenting the datasets used to train and validate machine learning models. Through these insights, we aim to inspire researchers to fully leverage the potential of machine learning in electroanalytical science.

Natural fiber has become one of the most widely used alternative materials for chemical sensor fabrication due to its advantages, such as biocompatibility, flexibility, and self-microfluidic properties. Enhanced natural fiber surface has been used as a substrate in colorimetric and electrochemical sensors. This review focuses on improving the natural fiber properties for preparation as a substrate for chemical sensors. Various methods for natural fiber extraction are discussed and compared. Bleaching and decolorization is important for preparation of colorimetric sensors, while carbonization and nanoparticle doping are favorable for increasing their electrical conductivity for electrochemical sensor fabrication. Also, example fabrications and applications of natural fiber-based chemical sensors for chemical and biomarker detection are discussed. The selectivity of the sensors can be introduced and improved by surface modification of natural fiber, such as enzyme immobilization and biorecognition element functionalization, illustrating the adaptability of natural fiber as a smart sensing device, e.g., wearable and portable sensors. Ultimately, the high performances of natural fiber-based chemical sensors indicate the potential uses of natural fiber as a renewable and eco-friendly substrate material in the field of chemical sensors and biosensors for clinical diagnosis and environmental monitoring.

In recent years, numerous emerging contaminants have been identified in surface water, groundwater, and drinking water. Developing novel sensing methods for detecting diverse emerging pollutants in water is urgently needed, as even at low concentrations, these pollutants can pose a serious threat to human health and environmental safety. Traditional testing methods are based on laboratory equipment, which is highly sensitive but complex to operate, costly, and not suitable for on-site monitoring. Microfluidic sensors offer several benefits, including rapid evaluation, minimal sample usage, accurate liquid manipulation, compact size, automation, and in-situ detection capabilities. They provide promising and efficient analytical tools for high-performance sensing platforms in monitoring emerging contaminants in water. In this paper, recent research advances in microfluidic sensors for the detection of emerging contaminants in water are reviewed. Initially, a concise overview is provided about the various substrate materials, corresponding microfabrication techniques, different driving forces, and commonly used detection techniques for microfluidic devices. Subsequently, a comprehensive analysis is conducted on microfluidic detection methods for endocrine-disrupting chemicals, pharmaceuticals and personal care products, microplastics, and perfluorinated compounds. Finally, the prospects and future challenges of microfluidic sensors in this field are discussed.

Cancer is a common illness with a high mortality. Compared with traditional technologies, biomarker detection, with its low cost and simple operation, has a higher sensitivity and faster speed in the early screening and prognosis of cancer. Therefore, extensive research has focused on the development of biosensors and the construction of sensing interfaces. Molybdenum disulfide (MoS2) is a promising two-dimensional (2D) nanomaterial, whose unique adjustable bandgap shows excellent electronic and optical properties in the construction of biosensor interfaces. It not only has the advantages of a high catalytic activity and low manufacturing costs, but it can also further expand the application of hybrid structures through different functionalization, and it is widely used in various biosensors fields. Herein, we provide a detailed introduction to the structure and synthesis methods of MoS2, and explore the unique properties and advantages/disadvantages exhibited by different structures. Specifically, we focus on the excellent properties and application performance of MoS2 and its composite structures, and discuss the widespread application of MoS2 in cancer biomarkers detection from both electrochemical and optical dimensions. Additionally, with the cross development of emerging technologies, we have also expanded the application of other emerging sensors based on MoS2 for early cancer diagnosis. Finally, we summarized the challenges and prospects of MoS2 in the synthesis, functionalization of composite groups, and applications, and provided some insights into the potential applications of these emerging nanomaterials in a wider range of fields.

Metal-organic frameworks (MOFs) are porous materials with huge specific surface area and abundant active sites, which are composed of metal ions or clusters and organic ligands in the form of coordination bonds. In recent years, MOFs have been successfully applied in many fields due to their excellent physical, chemical, and biological properties. Electrochemical sensors have advantages such as economy, portability, and sensitivity, making them increasingly valued in the field of sensors. Many studies have shown that the electrode materials will affect the performance of electrochemical sensors. Therefore, the research on electrode materials is still one of the hotspots. MOFs are also commonly used to construct electrochemical sensors. However, electrochemical sensors prepared from single MOFs have shortcomings such as insufficient conductivity, low sensitivity, and poor electrochemical catalytic ability. In order to compensate for these defects, a new type of nanocomposite material with very ideal conductivity was formed by adding metal nanoparticles (MNPs) to MOFs. The combination of the two is expected to be widely applied in the field of sensors. This review summarizes the applications of various MNPs/MOFs composites in the field of electrochemical sensors and provides some references for the development of MNPs/MOFs composites-based electrochemical sensors in the future.

Our brain is an intricate neuromodulatory network, and various neurochemicals, including neurotransmitters, neuromodulators, gases, ions, and energy metabolites, play important roles in regulating normal brain function. Abnormal release or imbalance of these substances will lead to various diseases such as Parkinson\'s and Alzheimer\'s diseases, therefore, in situ and real-time analysis of neurochemical interactions in pathophysiological conditions is beneficial to facilitate our understanding of brain function. Implantable electrochemical biosensors are capable of monitoring neurochemical signals in real time in extracellular fluid of specific brain regions because they can provide excellent temporal and spatial resolution. However, in vivo electrochemical biosensing analysis mainly faces the following challenges: First, foreign body reactions induced by microelectrode implantation, non-specific adsorption of proteins and redox products, and aggregation of glial cells, which will cause irreversible degradation of performance such as stability and sensitivity of the microsensor and eventually lead to signal loss; Second, various neurochemicals coexist in the complex brain environment, and electroactive substances with similar formal potentials interfere with each other. Therefore, it is a great challenge to design recognition molecules and tailor functional surfaces to develop in vivo electrochemical biosensors with high selectivity. Here, we take the above challenges as a starting point and detail the basic design principles for improving in vivo stability, selectivity and sensitivity of microsensors through some specific functionalized surface strategies as case studies. At the same time, we summarize surface modification strategies for in vivo electrochemical biosensing analysis of some important neurochemicals for researchers\' reference. In addition, we also focus on the electrochemical detection of low basal concentrations of neurochemicals in vivo via amperometric waveform techniques, as well as the stability and biocompatibility of reference electrodes during long-term sensing, and provide an outlook on the future direction of in vivo electrochemical neurosensing.

Since cells are the basic structural and functional units of organisms, the detection or quantitation of cells is one of the most common basic problems in life science research. The established cell detection techniques mainly include fluorescent dye labeling, colorimetric assay, and lateral flow assay, all of which employ antibodies as cell recognition elements. However, the widespread application of the established methods generally dependent on antibodies is limited, because the preparation of antibodies is complicated and time-consuming, and unrecoverable denaturation is prone to occur with antibodies. By contrast, aptamers that are generally selected through the systematic evolution of ligands by exponential enrichment can avoid the disadvantages of antibodies due to their controllable synthesis, thermostability, and long shelf life, etc. Accordingly, aptamers may serve as novel molecular recognition elements like antibodies in combination with various techniques for cell detection. This paper reviews the developed aptamer-based cell detection methods, mainly including aptamer-fluorescent labeling, aptamer-isothermal amplification assay, electrochemical aptamer sensor, aptamer-based lateral flow analysis, and aptamer-colorimetric assay. The principles, advantages, progress of application in cell detection and future development trend of these methods were specially discussed. Overall, different assays are suitable for different detection purposes, and the development of more accurate, economical, efficient, and rapid aptamer-based cell detection methods is always on the road in the future. This review is expected to provide a reference for achieving efficient and accurate detection of cells as well as improving the usefulness of aptamers in the field of analytical applications.

Nitrous oxide (N2O), also known as laughing gas, is arguably one of the most detrimental greenhouse gases while concurrently being overlooked by the public. Specifically, N2O is ∼300 times more damaging than its better-known counterpart carbon dioxide (CO2) and has a longer-lived lifetime in the atmosphere than CO2. There exist both natural and anthropogenic sources of N2O, and thus, for a better understanding of sources, capture, and decomposition, it is pivotal to identify N2O within the nitrogen biosphere. This review covers the past and current low-cost N2O gas-sensing technologies, focusing specifically on low-cost metal oxide semiconductors (MOSs), chemiresistive and electrochemical sensors that can provide spatial and temporal monitoring of N2O emissions from various sources. Additionally, compositional modifications to MOsS using metal-organic frameworks (MOFs) are discussed, potentially facilitating new awareness and efforts for increased sensing performance and functionality in N2O detection.

Bionic skin has shown great potential in the fields of multifunctional robots and medical care. The tactile sensor, an important part of bionic skin, is used to measure the temperature, humidity, pressure, vibration, and other physical quantities including the external environment, object shape, and structure size. As a result, tactile sensors can be applied as epidermal sensors amounted on human skin to monitor the health and motion of users, and applied on soft robotics to help robots sense the environment information around. This paper analyzes and discusses the research progress of tactile sensing technology applied in bionic skin in recent years, including capacitive tactile sensors, piezoresistive tactile sensors, piezoelectric tactile sensors, photoelectric tactile sensors, magnetic tactile sensors, electrochemical sensors, and multi-component tactile sensors. In addition, the principle of each tactile sensor, advantages and disadvantages of various tactile sensors, and their practical applications in various fields are summarized. Finally, the future research direction of bionic skin sensing technology is outlooked.

Vanillin is an organic compound that not only acts as a flavoring and fragrance enhancer in some foods, but also can have antioxidant, anti-inflammatory, anti-cancer and anti-depressant effects. Nevertheless, its excessive use can be associated with side effects on human health. Consequently, there is a need to achieve a rapid vanillin determination approach to enhance food safety. The diversity and high sensitivity of analytical approaches has led researchers to use more advanced and efficient methods providing quantitative and qualitative outcomes in complex matrices. Among these, prominent attention has been drawn to electrochemical sensors for reasons such as reliability, simplicity, cost-effectiveness, portability, selectivity, and ease of operation, especially for the determination of vanillin. Nanomaterials are a good candidate for sensor construction due to their commendable physicochemical attributes. Some advanced nanostructures with promising platforms for high-sensitivity, highly selective, and long-lasting electrochemical sensors include graphene (Gr) and its derivatives, graphite carbon nitride (g-C3N4), carbon nanotubes (CNTs), metal nanoparticles, metal organic frameworks, carbon nanofibers (CNFs) and quantum dots. Study about sizes, dimensions, and morphologies of nanomaterials makes strong candidates for improving sensitivity or selectivity according to electrocatalytic abilities. The low LOD and wide linear range of samples demonstrated an excellent catalytic performance towards the vanillin oxidation. Some investigations have reported the synergistic effects like great conductivity of carbon nanomaterials which improved the electrocatalytic performance of nanocomposites which demonstrated the estimable sensitivity of nanomaterial-supported electrochemical sensors for determination of vanillin concentrations. The sensors which have reported have a commendable response to practical potential and evaluated in biscuit, pudding powder, chocolate, custard specimens and etc. sensitivity, stability, reproducibility and repeatability of suggested sensor were investigated. The present review article scrutinizes recent advances in the fabrication of nanomaterial-based electrochemical sensors to detect vanillin in various food matrices.