Multidimensional heterogeneous integration of two-dimensional materials and artificial visual systems: Frontier innovations and paradigm-shifting advancements

WEN Yu; HAN Suting; ZHOU Ye

doi:10.7498/aps.74.20250703

Abstract

Artificial visual system (AVS) has received increasing attention for their transformative potential in fields such as medical diagnostics, intelligent robotics, and machine vision. Traditional silicon-based imaging technologies, however, face significant limitations, including high energy consumption, limited dynamic range, and integration challenges. Two-dimensional (2D) semiconductor materials, such as MoS₂, WSe₂, and black phosphorus have emerged as promising alternatives due to their atomically thin structure, tunable bandgaps, high carrier mobility, and superior optoelectronic properties. In this work, recent breakthroughs in the integration of 2D materials with AVS are investigated. Highlighted is the development of a reconfigurable four-terminal phototransistor array based on WSe₂ and IGZO heterostructures, which enables monocular 3D disparity reconstruction without the need for multiple cameras or active light sources. The system demonstrates a dynamic imaging rate exceeding 33 frames per second and supports real-time sensing, memory storage, and ambipolar mode switching with ultralow power consumption (as low as 142 pW). Key innovations include multifunctional device architectures that simulate the retinal photoreceptors, bipolar cells, and even neural synapses, achieving functions such as image sensing, real-time adaptation, color recognition, motion tracking, and multimodal perception. Furthermore, by simulating the human neurovisual pathways, these 2D material-based devices can potentially realize in-sensor computing and neuromorphic processing, which substantially reduce data transfer bottlenecks and energy overhead. Nonetheless, the field is still in its formative stage. Here, several critical bottlenecks are emphasized: the lack of scalable, defect-controlled synthesis of 2D heterostructures; the limited spectral bandwidth and color fidelity of current photonic components; the immature state of neuromorphic elements, which often lacks stability, long-term memory, and bio-realistic plasticity. Moreover, the practical integration with real-world applications requires compatibility with high-density manufacturing and dynamic, multi-modal environments. In the future, artificial vision platforms, empowered by engineered 2D materials and heterostructures, will develop into highly compact, intelligent, and context-aware agents capable of autonomous perception and interaction in complex real-world settings.

Keywords:

Authors and contacts

1.
Institute for Advanced Study, Shenzhen University, Shenzhen 518060, China
2.
Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Kowloon, Hong Kong 999077, China

Corresponding author: ZHOU Ye, yezhou@szu.edu.cn

Funds: Project supported by the National Natural Science Foundation of China (Grant No. 62304137), the Natural Science Foundation of Guangdong Province, China (Grant Nos. 2023A1515012479, 2024B1515040002), and the Graduate Education Innovation Plan Project of Guangdong Province, China (Grant No. 2025JGXM_151).

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References

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Cited By

图 1 可重构PCHT架构^[1]　(a) PCHT结构示意图; (b) PCHT阵列的光学图像; (c) 三维视差可重构原理. 引用图片已获相关授权

Figure 1. Reconfigurable PCHT architecture^[1]: (a) Schematic diagram of reconfigurable PCHT, array and chip; (b) optical image of our monolithic integrated reconfigurable PCHT array; (c) 3D parallax reconstruction principle. Reproduced with permission from Springer Nature.

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图 2 PCHT模型光电特性^[1]　(a) 动态成像模式工作机制模型; (b) 静态成像模式工作机制模型; (c) 双极型模式工作机制模型; (d) PCHT等效电路图; (e)—(g) 动态模式响应; (h)—(j) 静态模式响应. 引用图片已获相关授权

Figure 2. PCHT mode-dependent optoelectronic performance^[1]: (a) Model of the operation mechanism of the dynamic imaging mode with temporal-dependent storage; (b) model of the operating mechanism of the constant perception mode for static imaging; (c) model of the operation mechanism of the ambipolar mode; (d) equivalent functional circuit of the reconfigurable PCHT; (e)–(g) dynamic mode response; (h)–(j) static mode response. Reproduced with permission from Springer Nature.

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图 3 三维视差重建演示^[1]　(a) 可重构PCHT阵列硬件架构示意图; (b) 可重构PCHT阵列算法示意图; (c) 三维形态重构; (d) 二维深度场重构; (e) 多角度耦合重构; (f) 眼球形态的感知与重构. 引用图片已获相关授权

Figure 3. 3-dimensional (3D) parallax reconstruction demonstration^[1]: (a) Schematic of the reconfigurable PCHT array hardware architecture; (b) algorithmic methodology of the 3D parallax reconstruction; (c) stereo morphology reconstruction of a complex object assembly. Scale bars, 10, 5 and 5 pixels in x, y, z, respectively; (d) 2D depth field mapping of two spatial configurations; (e) demonstration of multi-viewing coupling; (f) surface reconstruction of the bulbus oculi of a normal (top) and myopic eye (bottom). Reproduced with permission from Springer Nature.

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图 4 三种不同AVS 器件结构图对比　(a) Gr/h-BN/MoTe₂/MoS₂结构^[8]; (b) WSe₂/BN结构^[23]; (c) IGZO/WSe₂ 结构^[1]

Figure 4. Comparison of three different AVS device structures: (a) Gr/h-BN/MoTe₂/MoS₂ structure^[8]; (b) WSe₂/BN structure^[23]; (c) IGZO/WSe₂ structure^[1].

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表 1 三种AVS关键参数对比表

Table 1. Comparison of key parameters of three AVS devices.

器件结构	帧率	功耗/nW	响应时间/ms	光谱响应范围	参考文献
Gr/h-BN /MoTe₂ /MoS₂	无	无	1.5	集中在635 nm	[8]
WSe₂/BN	无	10	<8	可见光全范围	[23]
IGZO/WSe₂	>3 frames/s	0.14	<10	450—880 nm	[1]

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[2]	Liao F Y, Zhou Z, Kim B J, Chen J W, Wang J L, Wan T Q, Zhou Y, Hoang A T, Wang C, Kang J F, Ahn J H, Chai Y 2022 Nat. Electron. 5 84 Google Scholar
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[5]	沈柳枫, 胡令祥, 康逢文, 叶羽敏, 诸葛飞 2022 物理学报 71 148505 Google Scholar Shen L F, Hu L X, Kang F W, Ye Y M, Zhu G F 2022 Acta Phys. Sin. 71 148505 Google Scholar
[6]	Dodda A, Jayachandran D, Radhakrishnan S S, Pannone A, Zhang Y K, Trainor N, Redwing J M, Das S 2022 ACS Nano 16 20010 Google Scholar
[7]	廖付友, 柴扬 2021 物理 50 378 Google Scholar Liao F Y, Cai Y, 2021 PHYSICS 50 378 Google Scholar
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[10]	Tan D C, Zhang Z R, Shi H H, Sun N, Li Q K, Bi S, Huang J J, Liu Y H, Guo Q L, Jiang C M 2024 Adv. Mater. 36 2407751
[11]	Han Z, Zhang Y C, Mi Q, You J, Zhang N N, Zhong Z Y, Jiang Z M, Guo H, Hu H Y, Wang L M, Zhu Z M 2024 ACS Nano 18 29968 Google Scholar
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