Hybrid photonic integration exploits complementary strengths of different material platforms, thereby offering superior performance and design flexibility in comparison to monolithic approaches. This applies in particular to multi-chip concepts, where components can be individually optimized and tested on separate dies before integration into more complex systems. The assembly of such systems, however, still represents a major challenge, requiring complex and expensive processes for high-precision alignment as well as careful adaptation of optical mode profiles. Here we show that these challenges can be overcome by in-situ nano-printing of freeform beam-shaping elements to facets of optical components. The approach is applicable to a wide variety of devices and assembly concepts and allows adaptation of vastly dissimilar mode profiles while considerably relaxing alignment tolerances to the extent that scalable, cost-effective passive assembly techniques can be used. We experimentally prove the viability of the concept by fabricating and testing a selection of beam-shaping elements at chip and fiber facets, achieving coupling efficiencies of up to 88 % between an InP laser and an optical fiber. We also demonstrate printed freeform mirrors for simultaneously adapting beam shape and propagation direction, and we explore multi-lens systems for beam expansion. The concept paves the way to automated fabrication of photonic multi-chip assemblies with unprecedented performance and versatility.

No abstract

Three-dimensional (3D) nano-printing of freeform optical waveguides, also referred to as photonic wire bonding, allows for efficient coupling between photonic chips and can greatly simplify optical system assembly. As a key advantage, the shape and the trajectory of photonic wire bonds can be adapted to the mode-field profiles and the positions of the chips, thereby offering an attractive alternative to conventional optical assembly techniques that rely on technically complex and costly high-precision alignment. However, while the fundamental advantages of the photonic wire bonding concept have been shown in proof-of-concept experiments, it has so far been unclear whether the technique can also be leveraged for practically relevant use cases with stringent reproducibility and reliability requirements. In this paper, we demonstrate optical communication engines that rely on photonic wire bonding for connecting arrays of silicon photonic modulators to InP lasers and single-mode fibres. In a first experiment, we show an eight-channel transmitter offering an aggregate line rate of 448 Gbit/s by low-complexity intensity modulation. A second experiment is dedicated to a four-channel coherent transmitter, operating at a net data rate of 732.7 Gbit/sa record for coherent silicon photonic transmitters with co-packaged lasers. Using dedicated test chips, we further demonstrate automated mass production of photonic wire bonds with insertion losses of (0.7 ± 0.15) dB, and we show their resilience in environmental-stability tests and at high optical power. These results might form the basis for simplified assembly of advanced photonic multi-chip systems that combine the distinct advantages of different integration platforms.

Profiles of inventors' technological competence are a valuable source of information for decision‐making in research and development (R&D) management, e.g. concerning inventor assessment, human resource development and R&D team‐building. In the following exposition, a new method of inventor profiling will be put forward, which is based in particular on semantic patent analysis and multidimensional scaling. First, in the course of semantic patent analysis, specialized software, equipped with a natural language processor, reads the patent text transferring the contents into a subject–action–object–format (SAO). The extracted SAO structures are then used to create similarity matrices for patents or patent sets, respectively, according to a specific similarity value. Subsequently, an inventor competence map can be produced by means of multidimensional scaling. The benefits of this method for R&D‐related issues in human resource management will be illustrated by the example of a German mechanical engineering company. Two distinct types of profiles were generated and tested: (i) the profile of a single key inventor and (ii) a profile of key inventor sets. The single key inventor profile gives information on the range of competence, i.e. the homogeneity or heterogeneity of a certain inventor's competences, providing far more detailed insights than resorting to bibliographic data like international patent classification (IPC) classes or citations, whereas the latter kind of profile establishes the position of a certain key inventor in relation to others, helping to highlight specific groups of inventors and their domains. These results are clearly apt to support human resource management.

No abstract