The availability of metrology solutions, one of the key factors to drive leading edge semiconductor devices and processes, can be confronted with difficulties in the advanced node. For developing new metrology solutions, high quality test structures fabricated at specific sizes are needed. Conventional resist-based lithography have been utilized to manufacture such samples. However, it can encounter significant resolution difficulties or requiring complicated optimization process for advanced technology node. In this work, potential of helium ion beam direct milling (HIBDM) for fabricating metrology test structures with programmed imperfection is investigated. Features down to 5 nm are resolvable without implementing any optimization method. Preliminary results have demonstrated that HIBDM can be a promising alternative to fabricate metrology test structures for advanced metrology solutions in sub 10 nm node.
KEYWORDS: Electron beam lithography, Monte Carlo methods, Line edge roughness, Computer simulations, Critical dimension metrology, Transistors, Optical simulations, Diffusion, Optimization (mathematics), Point spread functions
Low-energy electron beam lithography is one of the promising next-generation lithography technology solutions for the 21-nm half-pitch node and beyond because of fewer proximity effects, higher resist sensitivity, and less substrate damage compared with high-energy electron beam lithography. To achieve high-throughput manufacturing, low-energy electron beam lithography systems with writing parameters of larger beam size, larger grid size, and lower dosage are preferred. However, electron shot noise can significantly increase critical dimension deviation and line edge roughness. Its influence on patterning prediction accuracy becomes nonnegligible. To effectively maximize throughput while meeting patterning fidelity requirements according to the International Technology Roadmap for Semiconductors, a new method is proposed in this work that utilizes a new patterning prediction algorithm to rigorously characterize the patterning variability caused by the shot noise and a mathematical optimization algorithm to determine optimal writing parameters. The new patterning prediction algorithm can achieve a proper trade-off between computational effort and patterning prediction accuracy. Effectiveness of the new method is demonstrated on a static random-access memory circuit. The corresponding electrical performance is analyzed by using a gate-slicing technique and publicly available transistor models. Numerical results show that a significant improvement in the static noise margin can be achieved.
KEYWORDS: Sensors, Monte Carlo methods, Electron beams, Signal detection, Lithography, Electron beam lithography, Detector arrays, Optical simulations, Semiconducting wafers, Silicon
Multiple-electron-beam-direct-write lithography is one of the promising candidates for next-generation lithography
because of its high resolution and ability of maskless operation. In order to achieve the throughput requirement for highvolume
manufacturing, miniaturized electro-optics elements are utilized in order to drive massively parallel beams
simultaneously. Electron beam drift problems can become quite serious in multiple-beam systems. Periodic recalibration
with reference markers on the wafer has been utilized in single-beam systems to achieve beam placement accuracy. This
technique becomes impractical with multiple beams. In this work, architecture of a two dimensional beam position
monitor system for multiple-electron-beam lithography is proposed. It consists of an array of miniaturized electron
detectors placed above the wafer to detect backscattered electrons. The relation between beam drift and distribution of
backscattered-electron trajectories is simulated by an in-house Monte Carlo electron-scattering simulator. Simulation
results indicate that electron beam drift may be effectively estimated from output signals of detector array with some
array signal processing to account for cross-coupling effects between beams.
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