Material Coupling in Hybrid Neuromorphic Devices: From Fundamentals to System‐Level Applications

ABSTRACT

Neuromorphic devices aim to integrate sensing, memory, and processing by emulating adaptive biological functions. Emerging semiconductor materials, including organic semiconductors, metal oxides, two‐dimensional materials, and metal halide perovskites, provide complementary physical properties, but each platform also faces intrinsic limitations in stability, charge transport, optical response, ionic/defect control, or scalable integration. Hybrid materials coupling effectively addresses these challenges by creating heterogeneous interfaces where charge transfer and storage, energy‐level alignment, defect modulation, photogating, and ion migration can be deliberately combined. In this review, we discuss recent progress in hybrid neuromorphic devices based on emerging semiconductor materials from a material–interface–device–system perspective. We first outline the material characteristics that enable neuromorphic operation in each platform. Hybrid neuromorphic devices were then classified into intra‐family and inter‐family hybridization strategies, highlighting how heterointerface design governs charge transport, charge storage, optical response, and ion‐ or defect‐mediated dynamics, thereby shaping synaptic plasticity and learning while enabling adaptive sensing, optoelectronic memory, and in‐sensor computing. We also discuss remaining challenges in process compatibility, interface stability and reproducibility, coupled interfacial mechanism analysis, and array‐level reliability.