This paper reports the manipulation of surface plasmon polaritons (SPPs) in a liquid plasmonic metal by changing its physical phase. Dynamic properties were controlled by solid-to-liquid phase transitions in 1D Ga gratings that were fabricated using a simple molding process. Solid and liquid phases were found to exhibit different plasmonic properties, where light coupled to SPPs more efficiently in the liquid phase. We exploited the supercooling characteristics of Ga to access plasmonic properties associated with the liquid phase over a wider temperature range (up to 30 °C below the melting point of bulk Ga). Ab initio density functional theory-molecular dynamic calculations showed that the broadening of the solid-state electronic band structure was responsible for the superior plasmonic properties of the liquid metal.

This paper describes a new nanofabrication method, moiré nanolithography, that can fabricate subwavelength lattices with high-rotational symmetries. By exposing elastomeric photomasks sequentially at multiple offset angles, we created arrays with rotational symmetries as high as 36-fold, which is three times higher than quasiperiodic lattices (≤12-fold) and six times higher than two-dimensional periodic lattices (≤6-fold). Because these moiré nanopatterns can be generated over wafer-scale areas, they are promising for a range of photonic applications, especially those that require broadband, omnidirectional absorption of visible light.

This paper describes the properties of silver plasmonic crystals with quasiperiodic rotational symmetries. Compared to periodic plasmonic crystals, quasiperiodic moiré structures exhibited an increased number of surface plasmon polariton modes, especially at high angles of excitation. In addition, plasmonic band gaps were often formed at the intersections of these new modes. To identify the origin and predict the location of the band gaps, we developed a Bragg-based indexing system using the reciprocal lattice vectors of the moiré plasmonic crystals. We showed that even more complicated quasiperiodic geometries could also be described by this indexing model. We anticipate that these quasiperiodic lattices will be useful for applications that require the concentration and manipulation of light over a broadband spectrum.

We report a method based on density functional theory molecular dynamics that allows us to calculate the plasmonic properties of liquid metals and metal alloys from first principles with no a priori knowledge of the system. We show exceptional agreement between the simulated and measured optical constants of liquid Ga and the room temperature liquid In-Ga eutectic alloy (T(m) = 289 K). We then use this method to analyze the plasmonic properties of various alloy concentrations in the In-Ga system. The plasmonic performance of the In-Ga system decreases with increasing In concentration. However, the benefits of a room-temperature plasmonic liquid are likely to outweigh the minor reduction in plasmonic performance when moving from pure Ga to the eutectic composition. Our results show that density functional theory molecular dynamics can be used as a predictive tool for studying the optical properties of liquid metal systems amenable to plasmonics.

Modern semiconductor fabrication pushes the limits of chemistry and physics while simultaneously employing largescale, cutting-edge processing techniques. While fab expansion and capital expenditures continue to grow, the human element has become ever more demanding and prone to error. To assist with this issue, computer-aided process engineering, process control, and tool monitoring will continue to rise in the coming years. In this paper, we present an APC-integrated, customizable solution to an in-fab processing segment. Through machine learning, we combine information from design-specific extracted features with processing and metrology data to predict oxide deposition thickness. The result is a design-aware augmentation for current metrology that can recommend accurate process recipe conditions for new layouts. We also present experimental results highlighting the benefits of adding design-aware features with in-fab data to anchor and support each other across layouts and technologies. This result paves the way to decouple, isolate, and quantify the individual influences each processing step imposes on different designs at various stages of the fabrication flow.