Emerging 2D Material Prototype Devices Toward Energy-Efficient and Sustainable Optoelectronics

Abstract

Driven by global sustainable development goals and the rapid advancement of artificial intelligence (AI), low energy consumption, high integration density, and sustainability have emerged as core imperatives for optoelectronic device development. Conventional complementary metal-oxide-semiconductor (CMOS) architectures, featuring discrete sensing-memory-computing functions, are constrained by the von Neumann bottleneck, which is marked by excessive energy consumption in data transmission, and fail to meet the energy-saving demands of scenarios like the internet of things (IoT) and neuromorphic computing. In contrast, two-dimensional (2D) materials, with attributes including atomic-scale thickness, efficient optoelectronic coupling, and low fabrication energy consumption, serve as pivotal carriers to overcome this bottleneck. Prototype 2D material-based optoelectronic devices are evolving from single-function units to sensing-memory-computing integrated systems, reducing energy redundancy in traditional architectures via material-structure synergetic adaptation while combining low energy consumption, high integration, and environmental compatibility. With breakthroughs in key technologies, All-in-One 2D material devices will most likely reshape the optoelectronic industry landscape, providing hardware support for the synergy between AI and green development.

Keywords

optoelectronic devices / sustainable / two-dimensional (2D) material

References

[1] C. Liu, Y. Jiang, B. Shen, et al., “A Full-Featured 2D Flash Chip Enabled by System Integration,” Nature 646 (2025): 1081-1088.

[2] C. Liu, H. Chen, S. Wang, et al., “Two-Dimensional Materials for Next-Generation Computing Technologies,” Nature Nanotechnology 15 (2020): 545-557.

[3] Z. Sun, J. Liu, N. Zhang, et al., “Enhanced in-Plane Polarization in Two-Dimensional GaInS₃ via Strain Engineering for Self-Powered Photodetector,” Transactions of Materials Research 1 (2025): 100009.

[4] M. S. Ram, K. M. Persson, A. Irish, et al., “High-Density Logic-in-Memory Devices Using Vertical Indium Arsenide Nanowires on Silicon,” Nature Electronics 4 (2021): 914-920.

[5] Z. Zhang, S. Wang, C. Liu, et al., “All-in-One Two-Dimensional Retinomorphic Hardware Device for Motion Detection and Recognition,” Nature Nanotechnology 17 (2022): 27-32.

[6] M. Ao, X. Zhou, X. Kong, et al., “A RISC-V 32-Bit Microprocessor Based on Two-Dimensional Semiconductors,” Nature 640 (2025): 654-661.

[7] Y. Liu, X. Duan, H. J. Shin, et al., “Promises and Prospects of Two-Dimensional Transistors,” Nature 591 (2021): 43-53.

[8] J. Yu, J. Fu, H. Ruan, et al., “Tailoring Lithium Intercalation Pathway in 2D van der Waals Heterostructure for High-Speed Edge-Contacted Floating-Gate Transistor and Artificial Synapses,” InfoMat 6 (2024): e12599.

[9] D. Muoi and L. Van Tan, “Quantum Capacitance in Two-Dimensional TMDC Semiconductors: Effects of Temperature, Electric Field, and Spin-Valley Zeeman Field,” European Physical Journal B 98 (2025): 168.

[10] T. Li, W. Guo, L. Ma, et al., “Epitaxial Growth of Wafer-Scale Molybdenum Disulfide Semiconductor Single Crystals on Sapphire,” Nature Nanotechnology 16 (2021): 1201-1207.

[11] J. Tang, Q. Wang, J. Tian, et al., “Low Power Flexible Monolayer MoS₂ Integrated Circuits,” Nature Communications 14 (2023): 3633.

[12] X. Gao, L. Zheng, F. Luo, et al., “Integrated Wafer-Scale Ultra-Flat Graphene by Gradient Surface Energy Modulation,” Nature Communications 13 (2022): 5410.

[13] O. Lopez-Sanchez, D. Lembke, M. Kayci, et al., “Ultrasensitive Photodetectors Based on Monolayer MoS₂,” Nature Nanotechnology 8 (2013): 497-501.

[14] Q. Qiu and Z. Huang, “Photodetectors of 2D Materials From Ultraviolet to Terahertz Waves,” Advanced Materials 33 (2021): 2008126.

[15] L. Pi, P. Wang, S. J. Liang, et al., “Broadband Convolutional Processing Using Band-Alignment-Tunable Heterostructures,” Nature Electronics 5 (2022): 248-254.

[16] X. Song, X. Zhong, C. Li, et al., “Multifunctional Logic Gates via Coexistent Positive and Negative Photoconductivity of a Single Bi₂Se₃ Photodetector,” Advanced Materials 37 (2025): 2416934.

[17] Z. Yang, Z. Zhang, S. Huo, et al., “Emerging 2D Material-Based Synaptic Devices: Principles, Mechanisms, Improvements, and Applications,” SmartMat 6 (2025): e70005.

[18] Z. Yang, S. Huo, Z. Zhang, et al., “High-Precision Multibit Opto-Electronic Synapses Based on ReS₂/h-BN/Graphene Heterostructure for Energy-Efficient and High-Accuracy Neuromorphic Computing,” Advanced Functional Materials 48 (2025): 2509119.

[19] J. Wang, N. Ilyas, Y. Ren, et al., “Technology and Integration Roadmap for Optoelectronic Memristor,” Advanced Materials 36 (2024): 2307393.

[20] B. Tossoun, D. Liang, S. Cheung, et al., “High-Speed and Energy-Efficient Non-Volatile Silicon Photonic Memory Based on Heterogeneously Integrated Memresonator,” Nature Communications 15 (2024): 551.

[21] Q. Zhang, Q. Li, R. Chen, et al., “Large-Area Self-Assembled Hexagonal Boron Nitride Nanosheet Films for Ultralow Dark Current Vacuum-Ultraviolet Photodetectors,” Advanced Functional Materials 34 (2024): 2315149.

[22] N. Huo and G. Konstantatos, “Recent Progress and Future Prospects of 2D-Based Photodetectors,” Advanced Materials 30 (2018): 1801164.

[23] L. Jia, J. Wu, Y. Zhang, et al., “Fabrication Technologies for the On-Chip Integration of 2D Materials,” Small Methods 6 (2022): 2101435.

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2026 The Author(s). SusMat published by Sichuan University and John Wiley & Sons Australia, Ltd.