Thermal optofluidics is an emerging field that promises to create numerous research and application opportunities in biophysics, biochemistry, and clinical biology. Innovation in plasmonic optics has led to the development of various invaluable tools in the fields of biosensing and microfluidic manipulation. The optothermal effect originates from light–matter interactions during photon–phonon conversion, which can lead to micro‐ or nanoscale inhomogeneities in the thermal distribution. This further induces a series of hydrodynamic phenomena such as natural convection, Marangoni convection, thermophoresis, the electrolyte Seebeck effect, depletion forces, and interfacial effects in colloidal particles. Light–matter interactions are particularly important for three aspects of microfluidics, namely the motion of colloidal particles, fluidic actuation, and biochemical reactions. This review first systematically elucidates the role of both nanoscale plasmonic thermal generation and heat‐induced fluidic motion in optofluidic microsystems. Then, recent state‐of‐the‐art thermal optofluidic applications of the above‐listed three aspects are presented. The paper aims to provide an insightful reference for future research in optofluidic biochemical systems.

Optothermal nanotweezers have emerged as an innovative optical manipulation technique in the past decade, which revolutionized classical optical manipulation by efficiently capturing a broader range of nanoparticles. However, the optothermal temperature field was merely employed for in-situ manipulation of nanoparticles, its potential for identifying bio-nanoparticles remains largely untapped. Hence, based on the synergistic effect of optothermal manipulation and CRIPSR-based bio-detection, we developed CRISPR-powered optothermal nanotweezers (CRONT). Specifically, by harnessing diffusiophoresis and thermo-osmotic flows near the substrate upon optothermal excitation, we successfully trapped and enriched DNA functionalized gold nanoparticles, CRISPR-associated proteins, as well as DNA strands. Remarkably, we built an optothermal scheme for enhancing CRISPR-based single-nucleotide polymorphism (SNP) detection at single molecule level, while also introducing a novel CRISPR methodology for observing nucleotide cleavage. Therefore, this innovative approach has endowed optical tweezers with DNA identification ability in aqueous solution which was unattainable before. With its high specificity and feasibility for in-situ bio-nanoparticle manipulation and identification, CRONT will become a universal tool in point-of-care diagnosis, biophotonics, and bio-nanotechnology.

The aero-engine system is complex, and the working environment is harsh. As the fundamental component of the aero-engine control system, the sensor must monitor its health status. Traditional sensor fault detection algorithms often have many parameters, complex architecture, and low detection accuracy. Aiming at this problem, a convolutional neural network (CNN) whose basic unit is an inception block composed of convolution kernels of different sizes in parallel is proposed. The network fully extracts redundant analytical information between sensors through different size convolution kernels and uses it for aero-engine sensor fault detection. On the sensor failure dataset generated by the Monte Carlo simulation method, the detection accuracy of Inception-CNN is 95.41%, which improves the prediction accuracy by 17.27% and 12.69% compared with the best-performing non-neural network algorithm and simple BP neural networks tested in the paper, respectively. In addition, the method simplifies the traditional fault detection unit composed of multiple fusion algorithms into one detection algorithm, which reduces the complexity of the algorithm. Finally, the effectiveness and feasibility of the method are verified in two aspects of the typical sensor fault detection effect and fault detection and isolation process.