Polydopamine-based composites have attracted much attention due to polydopamine (PDA) similarity to 3,4-dihydroxy-L-phenylalanine (DOPA), a key structure that produces superior adhesion stem from mussel foot silk protein. Considering that PDA is rich in highly active functional groups such as catechol groups and amine groups etc., it is desirable to provide a large number of active sites through various strong interactions just like hydrogen bonding, electrostatic interactions, π–π stacking interactions, coordination or chelation, thereby removing pollutants such as heavy metals or organic synthetic dyes from industrial waste water. In fact, the introduction of PDA into wastewater treatment materials will greatly improve the pH usage range, accuracy, and biocompatibility of adsorbent, which has generated the interest of water treatment materials researchers. In this review article, based on the two methods of adsorption and degradation commonly used in water treatment, which mainly refer to separation of heavy metal ions and degradation of organic pollutants, we describe the special role of PDA in the process of removing pollutants from industrial wastewater materials in recent years. A brief summary and some key issues in water treatment field and must be considered in future research is given in the finally. We hope to provide researchers with ideas based on the outstanding advantages of PDA composite materials in the treatment of pollutants in wastewater, so that the role of PDA can be better explored.

For yield measurement of an apple orchard or the mechanical harvesting of apples, there needs to be accurate identification of the target apple fruit. However, in a natural scene, affected by the apple’s growth posture and camera position, there are many kinds of apple images, such as overlapped apples; mutual shadows or leaves; stems; etc. It is a challenge to accurately locate overlapped apples. They will influence the positioning time and recognition efficiency and then affect the harvesting efficiency of apple-harvesting robots or the accuracy of orchard yield measurement. In response to this problem, an overlapped circle positioning method based on local maxima is proposed. First, the apple image is transformed into the Lab color space and segmented by the K-means algorithm. Second, some morphological processes, like erosion and dilation, are implemented to abstract the outline of the apples. Then image points are divided into central points; edge points; or outer points. Third, a fast algorithm is used to calculate every internal point’s minimum distance from the edge. Then, the centers of the apples are obtained by finding the maxima among these distances. Last, the radii are acquired by figuring out the minimum distance between the center and the edge. Thus, positioning is achieved. Experimental results showed that this method can locate overlapped apples accurately and quickly when the apple contour was complete; and this has certain practicability.

A self-switchable polymer reactor with a hyperbranched structure for controlled catalytic chemistry processes is reported. This polymer reactor was made of silver nanoparticles and a polymer carrier consisting of hyperbranched polyethylenimine and hydroxyethyl acrylate that behaved as thermally switchable domains. Below the transfer temperature, relatively strong catalytic reactivity was demonstrated due to the leading role of hydrophilic groups in the switchable domains, which opened access to the substrate for the packaged silver nanoparticles. In contrast, it showed weak catalysis at relatively high temperatures, reducing from the significantly increased hydrophobicity in the switchable domains. In this way, the polymer reactor displays controllable, tunable, catalytic activity based on this approach. This novel design opens up the opportunity to develop intelligent polymer reactors for controlled catalytic processes.