Radiation Resilient Synthetic Antiferromagnets‐Based Neuromorphic Device for Sea Surface Temperature Reconstruction

ABSTRACT

Reconstruction of sea surface temperature is critical for marine monitoring, yet conventional edge devices based on complementary metal–oxide–semiconductor (CMOS) technology suffer from memory‐wall bottlenecks and radiation vulnerability in harsh marine environments. Here, we propose a neuromorphic computing framework based on radiation‐tolerant synthetic antiferromagnetic (SAF) synaptic devices through physical–algorithmic co‐design to achieve robust sea surface temperature reconstruction. The fabricated Ta/Ir/Fe _0.65 Tb _0.35 /Ru/Co/Pt/Ta‐based SAF devices enable field‐free magnetization switching via spin–orbit torque, exhibiting multilevel conductance states that naturally emulate synaptic and neuronal functions. Notably, these devices retain over 92% of their performance after 1 Mrad (Si) γ‐irradiation, demonstrating inherent radiation tolerance arising from strong antiferromagnetic exchange coupling. By mapping the nonlinear conductance response of SAF onto the cross‐attention mechanism of a Perceiver IO architecture, we achieve accurate reconstruction of sea surface temperature fields from sparse sensor inputs. On the National Oceanic and Atmospheric Administration dataset, our system attains a root‐mean‐square error below 2°C—competitive with deep learning baselines—while projections indicate a potential reduction in energy consumption by an order of magnitude. This work not only advances the application of neuromorphic computing in marine science, but also provides a promising pathway toward “environmentally adaptive intelligent computing”.