Conventional photodetectors dominated by a single physical effect are strictly constrained by the Shockley-Queisser limit, accompanied by intrinsic performance saturation, inadequate operational flexibility, and a complete absence of functions and secure functionalities. Here, we present large-area integrable Te/GaN heterostructure array devices fabricated from high-quality Te films via glancing-incidence physical vapor deposition. Benefiting from the intrinsic synergy between photovoltaic and photothermoelectric effects, these devices offer bias-free, position-programmable bipolar photoresponse. Under 365 nm illumination, the Te/GaN devices exhibit competitive figures of merit among similar devices, with positive/negative responsivity up to 308.4 mA/W and 54.5 mA/W, specific detectivity exceeding 1.09×10¹³ Jones and 7.52×10¹² Jones, respectively, at zero bias. By using illumination position and response polarity as dual physical keys, the developed wafer-scale 20×20-pixel Te/GaN heteroarrays successfully implement reconfigurable image processing and encrypted image transmission, demonstrating unprecedented intelligent and physically secure functionalities for next-generation optoelectronic chips. This work overcomes the performance bottlenecks and limited operational degrees of freedom in single-effect devices, and achieves reliable, scalable array applications without external components, establishing a universal paradigm for high-performance, intelligent and secure integrated optoelectronics systems.

Based on the three major contexts of the popularization of higher education, the third wave of artificial intelligence, and the fourth paradigm shift in engineering education, this paper explores the future construction ideas of general physics courses in engineering colleges to support the “four futures” tasks of smart education. The popularization of higher education requires three major transformations in curriculum construction: from knowledge imparting to ability development, from standardized teaching to autonomous learning, and from classroom-led to industry-education integration. In this context, artificial intelligence has driven education into an era of human-machine collaboration where carbon-based life and silicon-based intelligence are deeply integrated, and has prompted the future teaching objective of physics courses to shift from knowledge-centered to ability and thinking centered, and the teaching model to upgrade to the trinity of “teacher, student and life”. At the same time, the fourth paradigm shift in engineering education is centered on new engineering disciplines, highlighting innovation-driven and cross-integration. The future construction of engineering physics courses will focus on replacing traditional teaching with project-based instruction, deeply integrating AI to achieve human-machine collaboration, and creating borderless classrooms that integrate online and offline. Ultimately, with a student-centered approach, practice and innovation are used to develop their engineering capabilities for the future.