Particle defects are important contributors to yield loss in semi-conductor manufacturing. Particles need to be detected and characterized in order to determine and eliminate their root cause. We have conceived a process flow for advanced defect classification (ADC) that distinguishes three consecutive steps; detection, review and classification. For defect detection, TNO has developed the Rapid Nano (RN3) particle scanner, which illuminates the sample from nine azimuth angles. The RN3 is capable of detecting 42 nm Latex Sphere Equivalent (LSE) particles on XXX-flat Silicon wafers. For each sample, the lower detection limit (LDL) can be verified by an analysis of the speckle signal, which originates from the surface roughness of the substrate. In detection-mode (RN3.1), the signal from all illumination angles is added. In review-mode (RN3.9), the signals from all nine arms are recorded individually and analyzed in order to retrieve additional information on the shape and size of deep sub-wavelength defects. This paper presents experimental and modelling results on the extraction of shape information from the RN3.9 multi-azimuth signal such as aspect ratio, skewness, and orientation of test defects. Both modeling and experimental work confirm that the RN3.9 signal contains detailed defect shape information. After review by RN3.9, defects are coarsely classified, yielding a purified Defect-of-Interest (DoI) list for further analysis on slower metrology tools, such as SEM, AFM or HIM, that provide more detailed review data and further classification. Purifying the DoI list via optical metrology with RN3.9 will make inspection time on slower review tools more efficient.

We report the etching of and electronic transport in nanoribbons of graphene sandwiched between atomically flat hexagonal boron nitride (h-BN). The etching of ribbons of varying width was achieved with a focused beam of 30 keV He⁺ ions. Using in-situ electrical measurements, we established a critical dose of 7000 ions nm⁻² for creating a 10 nm wide insulating barrier between a nanoribbon and the rest of the encapsulated graphene. Subsequently, we measured the transport properties of the ion-beam etched graphene nanoribbons. Conductance measurements at 4 K show an energy gap, that increases with decreasing ribbon width. The narrowest ribbons show a weak dependence of the conductance on the Fermi energy. Furthermore, we observed power-law scaling in the measured current-voltage (I-V) curves, indicating that the conductance in the helium-ion-beam etched encapsulated graphene nanoribbons is governed by Coulomb blockade.

The current-phase relation (CPR) of a Josephson junction (JJ) determines how the supercurrent evolves with the superconducting phase difference across the junction. Knowledge of the CPR is essential in order to understand the response of a JJ to various external parameters. Despite the rising interest in ultraclean encapsulated graphene JJs, the CPR of such junctions remains unknown. Here, we use a fully gate-tunable graphene superconducting quantum intereference device (SQUID) to determine the CPR of ballistic graphene JJs. Each of the two JJs in the SQUID is made with graphene encapsulated in hexagonal boron nitride. By independently controlling the critical current of the JJs, we can operate the SQUID either in a symmetric or asymmetric configuration. The highly asymmetric SQUID allows us to phase-bias one of the JJs and thereby directly obtain its CPR. The CPR is found to be skewed, deviating significantly from a sinusoidal form. The skewness can be tuned with the gate voltage and oscillates in antiphase with Fabry-Pérot resistance oscillations of the ballistic graphene cavity. We compare our experiments with tight-binding calculations that include realistic graphene-superconductor interfaces and find a good qualitative agreement.