Lithographic patterning, which utilizes the solubility switch of photoresists to convert optical signals into nanostructures on the substrate, is the primary top-down approach for nanoscale fabrication. However, the low light/electron-energy conversion efficiency severely limits the throughput of lithography. Thiol–ene reaction, as a photoinitiated radical addition reaction, is widely known as click reaction in the field of chemistry due to its extremely high efficiency. Here, we introduce a click lithography strategy utilizing the rapid thiol–ene click reaction to realize ultraefficient nanofabrication. This novel approach facilitated by the implementation of ultrahigh-functionality material designs enables high-contrast patterning of metal-containing nanoclusters under an extremely low deep-ultraviolet exposure dose, e.g., 7.5 mJ cm–2, which is 10–20 times lower than the dose used in the photoacid generator-based photoresist system. Meanwhile, 45 nm dense patterns were also achieved at a low dose using electron beam lithography, revealing the great potential of this approach in high-resolution patterning. Our results demonstrated the high-sensitivity and high-resolution features of click lithography, providing inspiration for future lithography design.

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Resolution, line edge/width roughness, and sensitivity (RLS) are critical indicators for evaluating the imaging performance of resists. As the technology node gradually shrinks, stricter indicator control is required for high-resolution imaging. However, current research can improve only part of the RLS indicators of resists for line patterns, and it is difficult to improve the overall imaging performance of resists in extreme ultraviolet lithography. Here, we report a lithographic process optimization system of line patterns, where RLS models are first established by adopting a machine learning method, and then these models are optimized using a simulated annealing algorithm. Finally, the process parameter combination with optimal imaging quality of line patterns can be obtained. This system can control resist RLS indicators, and it exhibits high optimization accuracy, which facilitates the reduction of process optimization time and cost and accelerates the development of the lithography process.

The line edge roughness (LER) is one of the most critical indicators of photoresist imaging performance, and its measurement using a reliable method is of great significance for lithography. However, most studies only investigate photoresist resolution and sensitivity because LER measurements require an expensive and not widely available critical dimension scanning electron microscopy (SEM) technology; thus, the imaging performance of photoresist has not been adequately evaluated. Here, we report an image processing software developed for offline calculation of LER that can analyze lithographic patterns with resolutions up to ∼15 nm. This software can effectively process all graphic files obtained from commonly used SEM machines by utilizing the adjustable double threshold. To realize the effective detection of high-resolution patterns in advanced lithography, we used SEM images generated from extreme ultraviolet and electron beam lithography to develop and validate the software's graphic recognition algorithm. This image processing software can process typical SEM images and produce reliable LER in an efficient and user-friendly manner, constituting a powerful tool for promoting the development of high-performance photoresist materials.

Metal–organic nanoclusters(MOCs) are being increasingly used as prospective photoresist candidates for advanced nanoscale lithography technologies. However, insight into the irradiation‐induced solubility switching process remains unclear. Hereby, the theoretical study employing density functional theory (DFT) calculations of the alkene‐containing zirconium oxide MOC photoresists is reported, which is rationally synthesized accordingly, to disclose the mechanism of the nanoscale patterning driven by the switch of solubility from the acid‐catalyzed or electron‐triggered ligand dissociation. By evaluating the dependence of MOCs’ imaging process on photoacid, lithographies of photoresists with and without photoacid generators after exposure to ultraviolet (UV), electron beam, and soft X‐ray, it is revealed that photoacid is essential in UV lithography, but it demonstrates little effect on exposure dose in high‐energy lithography. Furthermore, theoretical studies using DFT simulations to investigate the plausible photoacid‐catalyzed, electron‐triggered dissociation, and accompanying radical reaction are performed, and a mechanism is demonstrated that the nanoscale patterning of this type of MOCs is driven by the solubility switch resulting from dissociation‐induced strong electrostatic interaction and low‐energy barrier radical polymerization with other species. This study can give insights into the chemical mechanisms of patterning, and guide the rational design of photoresists to realize high resolution and high sensitivity.