MXene-Nanoflakes-Enabled All-Optical Nonlinear Activation Function for On-Chip Photonic Deep Neural Networks

Hazan, Adir and Ratzker, Barak and Zhang, Danzhen and Katiyi, Aviad and Sokol, Maxim and Gogotsi, Yury and Karabchevsky, Alina (2023) MXene-Nanoflakes-Enabled All-Optical Nonlinear Activation Function for On-Chip Photonic Deep Neural Networks. Advanced Materials, 35 (11): 2210216. ISSN 0935-9648

Abstract

2D metal carbides and nitrides (MXene) are promising material platforms for on-chip neural networks owing to their nonlinear saturable absorption effect. The localized surface plasmon resonances in metallic MXene nanoflakes may play an important role in enhancing the electromagnetic absorption; however, their contribution is not determined due to the lack of a precise understanding of its localized surface plasmon behavior. Here, a saturable absorber made of MXene thin film and a silicon waveguide with MXene flakes overlayer are developed to perform neuromorphic tasks. The proposed configurations are reconfigurable and can therefore be adjusted for various applications without the need to modify the physical structure of the proposed MXene-based activator configurations via tuning the wavelength of operation. The capability and feasibility of the obtained results of machine-learning applications are confirmed via handwritten digit classification task, with near 99% accuracy. These findings can guide the design of advanced ultrathin saturable absorption materials on a chip for a broad range of applications.