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Exploiting stretchable solar cells that can accommodate large strain and feature high cyclic mechanical endurance is challenging for wearable and skin-interfaced electronics application. In this work, we demonstrated such solar cells using the kirigami design. Experiments and mechanical simulations showed that the kirigami structure effectively imparted stretchability to perovskite solar cells (PSCs) through out-of-plane deformation, which significantly reduced the stress in devices. The kirigami-based PSCs with optimal geometric parameters exhibited high mechanical deformability, including stretchability (strain up to 200%), twistability (angle up to 450°), and bendability (radius down to 0.5 mm). More importantly, the kirigami PSCs revealed high mechanical endurance with almost unchanged performance even after 1000 repetitive stretching, twisting, and bending cycles. This kirigami design for stretchable PSCs presented here provides a promising strategy to achieve high deformability for solar cells as well as other optoelectronic devices.

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Singing voice conversion is converting the timbre in the source singing to the target speaker's voice while keeping singing content the same. However, singing data for target speaker is much more difficult to collect compared with normal speech data. In this paper, we introduce a singing voice conversion algorithm that is capable of generating high quality target speaker's singing using only his/her normal speech data. First, we manage to integrate the training and conversion process of speech and singing into one framework by unifying the features used in standard speech synthesis system and singing synthesis system. In this way, normal speech data can also contribute to singing voice conversion training, making the singing voice conversion system more robust especially when the singing database is small. Moreover, in order to achieve one-shot singing voice conversion, a speaker embedding module is developed using both speech and singing data, which provides target speaker identify information during conversion. Experiments indicate proposed sing conversion system can convert source singing to target speaker's high-quality singing with only 20 seconds of target speaker's enrollment speech data.