The rapid increase in both the quantity and complexity of data that are being generated daily in the field of environmental science and engineering (ESE) demands accompanied advancement in data analytics. Advanced data analysis approaches, such as machine learning (ML), have become indispensable tools for revealing hidden patterns or deducing correlations for which conventional analytical methods face limitations or challenges. However, ML concepts and practices have not been widely utilized by researchers in ESE. This feature explores the potential of ML to revolutionize data analysis and modeling in the ESE field, and covers the essential knowledge needed for such applications. First, we use five examples to illustrate how ML addresses complex ESE problems. We then summarize four major types of applications of ML in ESE: making predictions; extracting feature importance; detecting anomalies; and discovering new materials or chemicals. Next, we introduce the essential knowledge required and current shortcomings in ML applications in ESE, with a focus on three important but often overlooked components when applying ML: correct model development, proper model interpretation, and sound applicability analysis. Finally, we discuss challenges and future opportunities in the application of ML tools in ESE to highlight the potential of ML in this field.

Quantum dots (QDs) have been facilitating the development of sensitive fluorescence biosensors over the past two decades due to their high quantum yield, narrow and tunable emission spectrum and good photostability. The new emerging QDs with improved biocompatibility further promote their biological applications. In this review, we first briefly introduce the prevalently used QDs and their preparation and bioconjugation approaches. Then we summarize QDs-based fluorescent biosensing for proteins and nucleic acids, and QDs-based applications in cellular and in vivo targeting and imaging. Last but not the least, we envision the potential QDs-based applications in future perspectives.

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A novel label-free immunosensor for the detection of C-reactive protein (CRP) was developed based on a three-dimensional ordered macroporous (3DOM) gold film modified electrode by using the electrochemical impedance spectroscopy (EIS) technique. The electrode was electrochemically fabricated with an inverted opal template, making the surface area of the 3DOM gold film up to 14.4 times higher than that of a classical bare flat one, characterized by the cyclic voltammetric (CV) technique. The 3DOM gold film which was composed of interconnected gold nanoparticles not only has a good biocompatible microenvironment but also promotes the increase of conductivity and stability. The CRP immunosensor was developed by covalently conjugating CRP antibodies with 3-mercaptopropionic acid (MPA) on the 3DOM gold film electrode. The CRP concentration was measured through the increase of impedance values in the corresponding specific binding of CRP antigen and CRP antibody. The increased electron-transfer resistance (R(et)) values were proportional to the logarithmic value of CRP concentrations in the range of 0.1 to 20 ng mL(-1). The detection of CRP levels in three sera obtained from hospital showed acceptable accuracy.

Regular BiPO4 nanorods, for the first time, and BiOCl lamellae have been successfully synthesized via a facile sonochemical method in a surfactant/ligand-free system under ambient air. The as-prepared products are characterized by XRD, TEM, SAED, FE-SEM, HRTEM, and Raman spectroscopy. The effects of pH and ultrasound irradiation on the phase and morphology of the products are studied and the sonochemical formation mechanisms of 1D and 2D structures are discussed. TEM data from samples made after different reaction times suggest an ultrasound-induced nucleation and an oriented-attachment growth mechanism.

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A green strategy for the facile preparation and effective stabilization of Pd nanoparticles has been developed by using D-glucose as the reducing and stabilizing agents. The UV/vis absorption spectroscopy, transmission electron microscopy (TEM), x-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR) and zeta potential measurements were used to characterize the as-prepared Pd nanoparticles. It was found that the D-glucose concentration and pH value had an important effect on the size distribution and stability of the nanoparticles. Further, the Pd nanoparticles exhibited good catalytic properties in the degradation of azo dyes.

A novel hydrogen peroxide biosensor has been constructed based on the characteristics of the carbon nanotube. The multiwall carbon nanotube (MWNT) was used as a coimmobilization matrix to incorporate horseradish peroxidase (HRP) and electron transfer mediator methylene blue (MB) onto a glassy carbon electrode surface. Cyclic voltammetry and amperometric measurements were employed to demonstrate the feasibility of methylene blue as an electron carrier between the immobilized peroxidase and the surface of glassy carbon electrode. The amperometric response of this resulting biosensor to H 2 O 2 shows a linear relation in the range from 4 mM to 2 mM. The detection limit was 1 mM when the signal to noise ratio is 3. The presence of dopamine and ascorbic acid hardly affects the sensitive determination of H 2 O 2 . This biosensor also possesses very good stability and reproducibility.