Silicon nanowire field-effect transistors are promising devices used to detect minute amounts of different biological species. We introduce the theoretical and computational aspects of forward and backward modeling of biosensitive sensors. Firstly, w...
Thermal actuation is a common actuation method for soft robots. However, a major limitation is the relatively slow actuation speed. Here we report significant increase in the actuation speed of a bimorph thermal actuator by harnessing the snap-throug...
Soft grippers that incorporate functional materials are important in the development of mechanically compliant and multifunctional interfaces for both sensing and stimulating soft objects and organisms. In particular, the capability for firm and deli...
Neuromorphic computing aims at the realization of intelligent systems able to process information similarly to our brain. Brain-inspired computing paradigms have been implemented in crossbar arrays of memristive devices; however, this approach does n...
Liquid-crystal elastomer (LCE)-based soft robots and devices via an electrothermal effect under a low driving voltage have attracted a great deal of attention for their ability on generating larger stress, reversible deformation, and versatile actuat...
Establishing standardized methods for a consistent analysis of spectral data remains a largely underexplored aspect in surface-enhanced Raman spectroscopy (SERS), particularly applied to biological and biomedical research. Here we propose an effectiv...
A neuromorphic network composed of silver nanowires coated with TiO is found to show certain parallels with neural networks in nature such as biological brains. Owing to the memristive properties emerging at nanowire-to-nanowire contacts, where the A...
To improve performance of thermopneumatic soft actuators, which have recently been developed for various industrial applications, we embedded different nanoscale materials into their elastomer bodies. This yields a significant enhancement in the actu...
The journal of physical chemistry letters
May 29, 2020
Neural networks, trained on data generated by a microkinetic model and finite-element simulations, expand explorable parameter space by significantly accelerating the predictions of electrocatalytic performance. In addition to modeling electrode reac...
The ability for artificially reproducing human brain type signals' processing is one of the main challenges in modern information technology, being one of the milestones for developing global communicating networks and artificial intelligence. Electr...
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