Interactions between light and metal nanostructures are mediated by collective excitations of free electrons called surface plasmons, which depend primarily on geometry and dielectric environment. Excitation with ultrafast pulses can excite optomechanical modes that modulate the volume and shape of nanostructures at gigahertz frequencies. Plasmons serve as an optical handle to study the ultrafast electronic dynamics of nanoscale systems. We describe a method to synthesize core–shell Ag@TiO2 nanocubeswhile successfully maintaining the size and shape of the nanocube. Transient absorbance spectroscopy (TAS) is used to track photophysical processes on multiple time scales: from the ultrafast creation of hot carriers to their decay into phonons and the formation of optomechanical modes. Surprisingly, the TiO2 shell surrounding the Ag nanocubes caused no appreciable change in the frequency of the optomechanical mode, indicating that mechanical coupling between the core and shell is weak. However, the optomechanical mode was strongly attenuated by the TiO2 shell and TAS decay at ultrafast time scales (0–5 ps) was much faster. This observation suggests that up to ∼36% of the energy coupled into the plasmon resonance is being lost to the TiO2 as hot carriers instead of coupling to the optomechanical mode. Analysis of both ultrafast decay and characterization of optomechanical modes provides a dual accounting method to track energy dissipation in hybrid metal–semiconductor nanosystems for plasmon-enhanced solar energy conversion and chemical fuel generation.

Patterning of diamond-like carbon (DLC) and DLC:metal nanocomposites is of interest for an increasing number of applications. We demonstrate a nanoimprint lithography process based on silicon containing thermoplastic resist combined with plasma etching for straightforward patterning of such films. A variety of different structures with few hundred nanometer feature size and moderate aspect ratios were successfully realized. The quality of produced patterns was directly investigated by the means of optical and scanning electron microscopy (SEM). Such structures were further assessed by employing them in the development of gratings for guided mode resonance (GMR) effect. Optical characterization of such leaky waveguide was compared with numerical simulations based on rigorous coupled wave analysis method with good agreement. The use of such structures as refractive index variation sensors is demonstrated with sensitivity up to 319 nm/RIU, achieving an improvement close to 450% in sensitivity compared to previously reported similar sensors. This pronounced GMR signal fully validates the employed DLC material, the technology to pattern it and the possibility to develop DLC based gratings as corrosion and wear resistant refractometry sensors that are able to operate under harsh conditions providing great value and versatility.

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Due to the fast pace of life and online communications and the prevalence of English and the QWERTY keyboard, people tend to forgo using diacritics, make typographical errors (typos) when typing in other languages. Restoring diacritics and correcting spelling is important for proper language use and the disambiguation of texts for both humans and downstream algorithms. However, both of these problems are typically addressed separately: the state-of-the-art diacritics restoration methods do not tolerate other typos, but classical spellcheckers also cannot deal adequately with all the diacritics missing.In this work, we tackle both problems at once by employing the newly-developed universal ByT5 byte-level seq2seq transformer model that requires no language-specific model structures. For a comparison, we perform diacritics restoration on benchmark datasets of 12 languages, with the addition of Lithuanian. The experimental investigation proves that our approach is able to achieve results (>98%) comparable to the previous state-of-the-art, despite being trained less and on fewer data. Our approach is also able to restore diacritics in words not seen during training with >76% accuracy. Our simultaneous diacritics restoration and typos correction approach reaches >94% alpha-word accuracy on the 13 languages. It has no direct competitors and strongly outperforms classical spell-checking or dictionary-based approaches. We also demonstrate all the accuracies to further improve with more training. Taken together, this shows the great real-world application potential of our suggested methods to more data, languages, and error classes.

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