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March 19, 2026Nature Communications4 citationsOpen Access

All-optical logic processing unit using Kerr nonlinearity of MXene

YGYanqi GeWWWenkai WangMWMengdi Wang

Key Points

  • The aim is to develop a reconfigurable all-optical logic processing unit using Kerr nonlinearities in MXene materials.
  • Utilized Kerr nonlinear effects from high-entropy MXenes for optical logic operations.
  • Developed a platform for executing seven Boolean operations: AND, OR, NOT, NOR, NAND, XOR, XNOR.
  • Conducted handwritten digit recognition on the MNIST dataset, assessing performance and accuracy.
  • Achieved a classification accuracy of 97.7% for digit recognition on the MNIST dataset.
  • Demonstrated the capability of dynamic switching among seven Boolean operations.
  • Established the potential for increased throughput and energy efficiency for AI workloads.

Abstract

Optical logic computing harnesses the speed of light and the high bandwidth of optical signals to achieve ultrafast, highly parallel and energy-efficient operations. In particular, all-optical logic gates can perform Boolean functions using only photons, acting as core elements of future optical computing and communication systems. However, the multifunctional integration and flexible reconfiguration of optical devices remain challenging. Here, we present an electrically reconfigurable all-optical logic processing unit that leverages the Kerr nonlinear effect in conjunction with modulation of high-entropy MXene surface terminations. This architecture enables dynamic switching among seven fundamental Boolean operations — including AND, OR, NOT, NOR, NAND, XOR and XNOR — within a single optical configuration. With our platform we demonstrate handwritten digit recognition on the MNIST dataset, achieving a classification accuracy of 97.7%. By combining reconfigurable nonlinear optics with multifunctional two-dimensional materials, our approach establishes an alternative logic architecture pathway with the potential to enhance throughput and energy efficiency in response to AI workloads. The rapid rise of artificial intelligence pushes the need for more efficient computing. Here, authors propose an electrically reconfigurable, all-optical logic processing unit based on the combination of Kerr nonlinearities and high-entropy MXene surface terminations. They achieve an accuracy of 97.7% for digit recognition on the MNIST dataset.

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Cite This Study

Ge et al. (2026) studied this question.

synapsesocial.com/papers/69bb9279496e729e6297fde2https://doi.org/10.1038/s41467-026-70834-0
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