Lake ecosystems are critical slow-flow environments where silver nanoparticles (AgNPs) and bacterio-plankton interact. AgNPs, known for their strong antimicrobial activity and unique physicochemical properties, are widely used across industries but raise environmental concerns due to their size-depen dent distinct biochemical effects. Dissolved organic matter (DOM), primarily shaped by microbial activity, constitutes a key organic carbon component in lakes. Understanding DOM turnover under the influence of AgNPs is essential for gaining deeper insights into carbon cycling within lake ecosystems. This study investigated the effects of AgNPs on DOM properties using advanced spectroscopic techniques, highlighting the size-dependent impacts on bacterial community structures and DOM characteristics. Smaller AgNPs exhibited greater microbial toxicity, leading to higher concentrations of protein-associated C1 components within DOM. Furthermore, DOM influenced the transformation of silver between ionic and nanoparticle forms, modulating the toxicity of silver species. AgNPs also enhanced associations between specific bacterial taxa and environmental indicators. Size-dependent effects of AgNPs substantially altered microbial functions related to carbon and nitrogen cycling, affecting bacterial metabolism and the environmental behavior of functional genes. These findings underscore the pivotal role of nanomaterial size in shaping DOM turnover, bacterial community interactions, and biogeochemical processes. Overall, this study provides a foundational understanding of the ecological implications of AgNPs in lake ecosystems and informs future environmental risk assessments.

The inevitably formed residual stress in the Selective Laser Melting (SLM) process leads to distortion, crack and even delamination of the workpiece. Single laser is commonly applied during SLM processing. However, its productivity is much lower than multiple lasers. In addition, the research of residual stress with multi-laser condition currently is limited in the open documents. In this paper, a three-dimensional (3D) thermo-mechanical model, with considerations of temperature dependent properties of Ti-6Al-4V, phase change and convective flow, is developed at first. Then, the numerical results of maximum temperature and dimensions of the molten pool are validated by available experimental data. Furthermore, a parametric study in regards to a series of scan strategies is investigated. According to the simulation results, the residual stress increases significantly when the laser number reaches four. The “two-zone technique” scan strategy decreases the equivalent residual stress by 10.6% compared to the successive scan strategy. With a shortening scan length, the residual stress first increases slightly, then decreases dramatically and attains the minimum when it is a quarter. Furthermore, for the multi-laser SLM process, carefully planning the scanning sequence and the sweeping direction to decrease heat concentration is beneficial in controlling the residual stress.

As a result of the influence of surface characteristics, it is difficult to identify cracks on complex surfaces using the conventional processing of a single-frame image that misses important infrared thermal image sequences. In this paper, the red-green-blue normalisation method and the interframe difference method are used to make full use of the sequences and to characterise infrared thermal images of cracks on complex surfaces. An experiment to prove the effectiveness of the detection method was carried out on weld steel and carbon fibre-reinforced polymer (CFRP) steel plate. The selected infrared thermal image was divided into an objective area and a background area according to the relationship between three parameters for red-green-blue and objective temperature. The targeted and interfering information of the objective area were separated and processed based on the interframe difference method. The index of crack detection was extracted from the interframe difference matrix, which was constructed from two selected infrared thermal images. This method takes into account the local and global spatial information of the image and the maximum crack length measurement error was approximately 6%.