Nanoparticles are used in chemical mechanical planarization for semiconductor manufacturing as well as in other precision manufacturing operations. Particles used in processing need to be removed from surfaces in order to enhance yields. Nanoparticles are difficult to remove from surfaces during cleaning due to the high van der Waals attractive forces between particles and surfaces relative to the low fluid drag forces that are used for typical removal methods. Ionic surfactant molecules can adsorb on particles and surfaces to create an electrostatic repulsion between particles and surfaces as well as provide a steric barrier to mitigate adsorption and adhesion. The effectiveness of the surfactant in enhancing particle removal is related to surfactant properties, and it can be correlated with and modeled relative to the critical micelle concentration of the surfactant. The general approach for modeling will be discussed, and the model will be compared with particle removal data.

Cleanliness is a prerequisite for obtaining economically feasible yield levels in the semiconductor industry. For the next generation of lithographic equipment, EUV lithography, the size of yield-loss inducing particles for the masks will be smaller than 20 nm. Consequently, equipment for handling EUV masks should not add particles larger than 20 nm. Detection methods for 20 nm particles on large area surfaces are needed to qualify the equipment for cleanliness. Detection of 20 nm particles is extremely challenging, not only because of the particle size, but also because of the large surface area and limited available time.

In 2002 TNO developed the RapidNano, a platform that is capable of detecting nanoparticles on flat substrates. Over the last decade, the smallest detectable particle size was decreased while the inspection rate was increased. This effort has led to a stable and affordable detection platform that is capable of inspecting the full surface of a mask blank.

The core of RapidNano is a dark-field imaging technique. Every substrate type has a typical background characteristic, which strongly affects the size of the smallest detectable particle. The noise level is induced by the speckle generated by the surface roughness of the mask. The signal-to-noise ratio can be improved by illuminating the inspection area from nine different angles. This improvement was first shown on test bench level and then applied in the RapidNano3. The RapidNano3 is capable of detecting 42nm latex sphere equivalents (and larger) on silicon surfaces. RapidNano4, the next generation, will use 193 nm light and the same nine angle illumination mode. Camera sensitivity and available laser power determine the achievable throughput. Therefore, special care was given to the optical design, particularly the optical path. With RapidNano4, TNO will push the detection limit of defects on EUV blanks to below 20nm.

Understanding particle adhesion is vital to any industry where particulate systems are involved. There are multiple factors that affect the strength of the adhesion force, including the physical properties of the interacting materials and the system conditions. Surface roughness on the particles and the surfaces to which they adhere, including roughness at the nanoscale, is critically important to the adhesion force. The focus of this work is on the capillary force that dominates the adhesion whenever condensed moisture is present. Theoretical capillary forces were calculated for smooth particles adhered to smooth and rough surfaces. Simulations of the classical centrifuge technique used to describe particle adhesion to surfaces were performed based on these forces. A model was developed to describe the adhesion of the particles to the rough surface in terms of the adhesion to a smooth surface and an ‘effective’ contact angle distribution.

Sonication is a commonly used method for particle removal from various surfaces. There has been a growing interest in the use of combination of two or more acoustic frequencies for cleaning as it is expected to achieve better particle removal efficiency and lower feature damage compared to a single frequency acoustic system. In this study, stable and transient cavitation characteristics in de-ionized water subjected to dual-frequency irradiation have been illustrated using experimentally obtained absolute values of cavitation pressures and pressure-frequency spectra. Comparison of the calculated ratio of stable cavitation pressure to transient cavitation pressure suggests that dual-frequency mode has the potential to reduce feature damage while maintaining the particle removal efficiency compared to low frequency ultrasonic field. These observations are further confirmed from the results of damage studies conducted on aluminum coated glass samples.

Surfactants are commonly used as additives in cleaning formulations during acoustic cleaning of semiconductor surfaces. Since surfactants are surface active, they can affect cavitation characteristics and, therefore, influence cleaning efficiency and damage to the surface. In this work, stable and transient cavitation pressures were characterized in Triton® X-100 containing aqueous solutions subjected to single frequency and dual-frequency sound fields using acoustic emission measurements. The hydrophone based technique allowed quantitative measurements of the absolute pressure values from stable and transient cavitation fields. The ratio of stable cavitation pressure to transient cavitation pressure under different conditions indicated that surfactants can play an important role in reducing feature damage while maintaining particle removal efficiency. Damage studies conducted on aluminum coated glass samples further confirmed these results.

To achieve the goal of biocompatibility in nano-based materials we must first obtain a fundamental understanding of the physical and chemical behavior of biomolecules at the interfaces of nanomaterials. A first step towards understanding protein interactions with nanomaterials is to understand how individual amino acids interact at the interfaces. In this paper, we investigated the lysine adsorption behavior on fumed silica nanoparticles by solid-state NMR spectroscopy. We use 1H, 13C and 15N solid-state magic angle spinning (MAS) NMR techniques to elucidate how lysine is adsorbed on silica nanoparticles surfaces via strong hydrogen-bonding interaction between the protonated side-chain amine group and silanol group on silica nanoparticles surfaces.*