Issue

Vol. 17 (2025)

A Multifunctional Hydrogel with Multimodal Self-Powered Sensing Capability and Stable Direct Current Output for Outdoor Plant Monitoring Systems

https://doi.org/10.1007/s40820-024-01587-y
Xinge Guo
Department of Electrical & Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117576, Singapore
Luwei Wang
Department of Electrical & Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117576, Singapore
Zhenyang Jin
Department of Electrical & Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117576, Singapore
Chengkuo Lee
Department of Electrical & Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117576, Singapore

Corresponding Author: Chengkuo Lee

elelc@nus.edu.sg

Nano-Micro Letters, Vol. 17 (2025), Article Number: 76

Abstract

Smart farming with outdoor monitoring systems is critical to address food shortages and sustainability challenges. These systems facilitate informed decisions that enhance efficiency in broader environmental management. Existing outdoor systems equipped with energy harvesters and self-powered sensors often struggle with fluctuating energy sources, low durability under harsh conditions, non-transparent or non-biocompatible materials, and complex structures. Herein, a multifunctional hydrogel is developed, which can fulfill all the above requirements and build self-sustainable outdoor monitoring systems solely by it. It can serve as a stable energy harvester that continuously generates direct current output with an average power density of 1.9 W m−3 for nearly 60 days of operation in normal environments (24 °C, 60% RH), with an energy density of around 1.36 × 107 J m−3. It also shows good self-recoverability in severe environments (45 °C, 30% RH) in nearly 40 days of continuous operation. Moreover, this hydrogel enables noninvasive and self-powered monitoring of leaf relative water content, providing critical data on evaluating plant health, previously obtainable only through invasive or high-power consumption methods. Its potential extends to acting as other self-powered environmental sensors. This multifunctional hydrogel enables self-sustainable outdoor systems with scalable and low-cost production, paving the way for future agriculture.


Highlights:
1 A simple and scalable fabricated hydrogel with multiple functionalities to realize self-sustainable outdoor monitoring solely by it for large-scale applications in precision agriculture.
2 Stable direct-current output without requirement on stochastic or temporal environmental energies, achieving an energy density of 1.36 × 107 J m–3 with continuous operation of 56.25 days in normal outdoor environment.
3 Self-powered noninvasive leaf relative water content monitoring and environmental sensing to evaluate plant health status with high durability and self-recoverability in severe environments.

Keywords

Self-powered sensor Hydrogel Energy harvester Outdoor farming Self-sustainable IoT
Guo, Xinge, Luwei Wang, Zhenyang Jin, and Chengkuo Lee. 2024. “A Multifunctional Hydrogel With Multimodal Self-Powered Sensing Capability and Stable Direct Current Output for Outdoor Plant Monitoring Systems”. Nano-Micro Letters 17 (November):76. https://doi.org/10.1007/s40820-024-01587-y.
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References
  1. K. Fuglie, Climate change upsets agriculture. Nat. Clim. Change 11, 294–295 (2021). https://doi.org/10.1038/s41558-021-01017-6
  2. P. Zhu, J. Burney, J. Chang, Z. Jin, N.D. Mueller et al., Warming reduces global agricultural production by decreasing cropping frequency and yields. Nat. Clim. Change 12, 1016–1023 (2022). https://doi.org/10.1038/s41558-022-01492-5
  3. United Nations. World Population Prospects 2022: Summary of Results [Internet]. United Nation. pp. 1–52. (2022).
  4. A. Piancharoenwong, Y.F. Badir, IoT smart farming adoption intention under climate change: the gain and loss perspective. Technol. Forecast. Soc. Change 200, 123192 (2024). https://doi.org/10.1016/j.techfore.2023.123192
  5. E.M.B.M. Karunathilake, A.T. Le, S. Heo, Y.S. Chung, S. Mansoor, The path to smart farming: innovations and opportunities in precision agriculture. Agriculture (Switzerland) 13, 1593 (2023). https://doi.org/10.3390/agriculture13081593
  6. F. Zabel, R. Delzeit, J.M. Schneider, R. Seppelt, W. Mauser et al., Global impacts of future cropland expansion and intensification on agricultural markets and biodiversity. Nat. Commun. 10, 2844 (2019). https://doi.org/10.1038/s41467-019-10775-z
  7. A. Balmford, T. Amano, H. Bartlett, D. Chadwick, A. Collins et al., Author Correction: The environmental costs and benefits of high-yield farming. Nat. Sustain. 2, 339–341 (2019). https://doi.org/10.1038/s41893-018-0138-5
  8. V. Piñeiro, J. Arias, J. Dürr, P. Elverdin, A.M. Ibáñez et al., A scoping review on incentives for adoption of sustainable agricultural practices and their outcomes. Nat. Sustain. 3, 809–820 (2020). https://doi.org/10.1038/s41893-020-00617-y
  9. B. Basso, J. Antle, Digital agriculture to design sustainable agricultural systems. Nat. Sustain. 3, 254–256 (2020). https://doi.org/10.1038/s41893-020-0510-0
  10. Editorials (2018) Sustainable agriculture. Nat. Sustain. 1, 531 https://doi.org/10.1038/s41893-018-0163-4
  11. D. Li, H. Zhou, Z. Ren, C. Xu, C. Lee, Tailoring light–matter interactions in overcoupled resonator for biomolecule recognition and detection. Nano-Micro Lett. 17, 10 (2024). https://doi.org/10.1007/s40820-024-01520-3
  12. X. Chen, T. Wang, J. Shi, W. Lv, Y. Han et al., A novel artificial neuron-like gas sensor constructed from CuS quantum dots/Bi2S3 nanosheets. Nano-Micro Lett. 14, 8 (2022). https://doi.org/10.1007/s40820-021-00740-1
  13. M. Raj, S. Gupta, V. Chamola, A. Elhence, T. Garg et al., A survey on the role of Internet of Things for adopting and promoting Agriculture 4.0. J. Network Computer Appl. 187, 103107 (2021). https://doi.org/10.1016/j.jnca.2021.103107
  14. H. Khalid, S.J. Hashim, S.M.S. Ahmad, F. Hashim, M.A. Chaudhary, Robust multi-gateway authentication scheme for agriculture wireless sensor network in society 5.0 smart communities. Agriculture (Switzerland) 11, 1020 (2021). https://doi.org/10.3390/agriculture11101020
  15. Y. Sun, J. Cui, S. Feng, J. Cui, Y. Guo et al., Projection stereolithography 3D printing high-conductive hydrogel for flexible passive wireless sensing. Adv. Mater. 36, 2400103 (2024). https://doi.org/10.1002/adma.202400103
  16. L. Kong, W. Li, T. Zhang, H. Ma, Y. Cao et al., Wireless technologies in flexible and wearable sensing: from materials design, system integration to applications. Adv. Mater. 36, 2400333 (2024). https://doi.org/10.1002/adma.202400333
  17. V.K. Quy, N. Van Hau, D. Van Anh, N.M. Quy, N.T. Ban et al., IoT-enabled smart agriculture: architecture, applications, and challenges. Appl. Sci. (Switzerland) 12, 3396 (2022). https://doi.org/10.3390/app12073396
  18. E.M. Ouafiq, R. Saadane, A. Chehri, S. Jeon, AI-based modeling and data-driven evaluation for smart farming-oriented big data architecture using IoT with energy harvesting capabilities. Sustain. Energy Technol. Assessments 52, 102093 (2022). https://doi.org/10.1016/j.seta.2022.102093
  19. G. Reggio, M. Leotta, M. Cerioli, R. Spalazzese, F. Alkhabbas, What are IoT systems for real? an experts’ survey on software engineering aspects. Internet of Things (Netherlands) 12, 100313 (2020). https://doi.org/10.1016/j.iot.2020.100313
  20. S. El khediri, A. Benfradj, A. Thaljaoui, T. Moulahi, K. Ullah Khan et al., Integration of artificial intelligence (AI) with sensor networks: trends, challenges, and future directions. J King Saud Univ. – Comput. Inform. Sci. 36, 101892 (2024). https://doi.org/10.1016/j.jksuci.2023.101892
  21. O. Friha, M.A. Ferrag, L. Shu, L. Maglaras, X. Wang, Internet of Things for the future of smart agriculture: a comprehensive survey of emerging technologies. IEEE/CAA J. Automatica Sinica 8, 718–752 (2021). https://doi.org/10.1109/JAS.2021.1003925
  22. R.K. Singh, P.P. Puluckul, R. Berkvens, M. Weyn, Energy consumption analysis of LPWAN technologies and lifetime estimation for IoT application. Sensors (Basel) 20, 4794 (2020). https://doi.org/10.3390/s20174794
  23. T. He, C. Lee, Evolving flexible sensors, wearable and implantable technologies towards bodynet for advanced healthcare and reinforced life quality. IEEE Open J. Circuits Syst. 2, 702–720 (2021). https://doi.org/10.1109/OJCAS.2021.3123272
  24. T. He, F. Wen, Y. Yang, X. Le, W. Liu et al., Emerging wearable chemical sensors enabling advanced integrated systems toward personalized and preventive medicine. Anal. Chem. 95, 490–514 (2023). https://doi.org/10.1021/acs.analchem.2c04527
  25. Y. Luo, M.R. Abidian, J.H. Ahn, D. Akinwande, A.M. Andrews et al., Technology roadmap for flexible sensors. ACS Nano 17, 5211–5295 (2023). https://doi.org/10.1021/acsnano.2c12606
  26. Q. Shi, B. Dong, T. He, Z. Sun, J. Zhu et al., Progress in wearable electronics/photonics—moving toward the era of artificial intelligence and Internet of Things. InfoMat 2, 1131–1162 (2020). https://doi.org/10.1002/inf2.12122
  27. Y. Li, Q. Lin, T. Sun, M. Qin, W. Yue et al., A perceptual and interactive integration strategy toward telemedicine healthcare based on electroluminescent display and triboelectric sensing 3D stacked device. Adv. Funct. Mater. (2024). https://doi.org/10.1002/adfm.202402356
  28. Y. Li, Z. Qiu, H. Kan, Y. Yang, J. Liu et al., A human-computer interaction strategy for an FPGA platform boosted integrated “perception-memory” system based on electronic tattoos and memristors. Adv. Sci. 11, 2470237 (2024). https://doi.org/10.1002/advs.202470237
  29. Z. Liu, T. Zhu, J. Wang, Z. Zheng, Y. Li et al., Functionalized fiber-based strain sensors: pathway to next-generation wearable electronics. Nano-Micro Lett. 14, 61 (2022). https://doi.org/10.1007/s40820-022-00806-8
  30. T. Sun, B. Feng, J. Huo, Y. Xiao, W. Wang et al., Artificial intelligence meets flexible sensors: emerging smart flexible sensing systems driven by machine learning and artificial synapses. Nano-Micro Lett. 16, 14 (2023). https://doi.org/10.1007/s40820-023-01235-x
  31. D. Lu, T. Liu, X. Meng, B. Luo, J. Yuan et al., Wearable triboelectric visual sensors for tactile perception. Adv. Mater. 35, 2209117 (2023). https://doi.org/10.1002/adma.202209117
  32. X. Cao, Y. Xiong, J. Sun, X. Xie, Q. Sun et al., Multidiscipline applications of triboelectric nanogenerators for the intelligent era of Internet of Things. Nano-Micro Lett. 15, 14 (2022). https://doi.org/10.1007/s40820-022-00981-8
  33. B. Zhou, J. Liu, X. Huang, X. Qiu, X. Yang et al., Mechanoluminescent-triboelectric bimodal sensors for self-powered sensing and intelligent control. Nano-Micro Lett. 15, 72 (2023). https://doi.org/10.1007/s40820-023-01054-0
  34. X. Meng, C. Cai, B. Luo, T. Liu, Y. Shao et al., Rational design of cellulosic triboelectric materials for self-powered wearable electronics. Nano-Micro Lett. 15, 124 (2023). https://doi.org/10.1007/s40820-023-01094-6
  35. X. Lv, Y. Liu, J. Yu, Z. Li, B. Ding, Smart fibers for self-powered electronic skins. Adv. Fiber Mater. 5, 401–428 (2023). https://doi.org/10.1007/s42765-022-00236-6
  36. F. Wen, T. He, H. Liu, H.Y. Chen, T. Zhang et al., Advances in chemical sensing technology for enabling the next-generation self-sustainable integrated wearable system in the IoT era. Nano Energy 78, 105155 (2020). https://doi.org/10.1016/j.nanoen.2020.105155
  37. M. Huang, M. Zhu, X. Feng, Z. Zhang, T. Tang et al., Intelligent cubic-designed piezoelectric node (iCUPE) with simultaneous sensing and energy harvesting ability toward self-sustained artificial intelligence of things (AIoT). ACS Nano 17, 6435–6451 (2023). https://doi.org/10.1021/acsnano.2c11366
  38. L. Chen, M. Ren, J. Zhou, X. Zhou, F. Liu et al., Bioinspired iontronic synapse fibers for ultralow-power multiplexing neuromorphic sensorimotor textiles. Proc. Natl. Acad. Sci. U.S.A. 121, e2407971121 (2024). https://doi.org/10.1073/pnas.2407971121
  39. H. Zhang, H. Li, Y. Li, Biomimetic electronic skin for robots aiming at superior dynamic-static perception and material cognition based on triboelectric-piezoresistive effects. Nano Lett. 24, 4002–4011 (2024). https://doi.org/10.1021/acs.nanolett.4c00623
  40. H. Liu, J. Zhang, Q. Shi, T. He, T. Chen et al., Development of a thermoelectric and electromagnetic hybrid energy harvester from water flow in an irrigation system. Micromachines 9, 395 (2018). https://doi.org/10.3390/mi9080395
  41. X. Pu, W. Hu, Z.L. Wang, Toward wearable self-charging power systems: the integration of energy-harvesting and storage devices. Small 14, 1702817 (2018). https://doi.org/10.1002/smll.201702817
  42. T. He, H. Wang, J. Wang, X. Tian, F. Wen et al., Self-sustainable wearable textile nano-energy nano-system (NENS) for next-generation healthcare applications. Adv. Sci. 6, 1901437 (2019). https://doi.org/10.1002/advs.201901437
  43. Z.L. Wang, Self-powered nanosensors and nanosystems. Adv. Mater. 24, 280–285 (2012). https://doi.org/10.1002/adma.201102958
  44. Z. Chai, N. Zhang, P. Sun, Y. Huang, C. Zhao et al., Tailorable and wearable textile devices for solar energy harvesting and simultaneous storage. ACS Nano 10, 9201–9207 (2016). https://doi.org/10.1021/acsnano.6b05293
  45. X. Pu, L. Li, H. Song, C. Du, Z. Zhao et al., A self-charging power unit by integration of a textile triboelectric nanogenerator and a flexible lithium-ion battery for wearable electronics. Adv. Mater. 27, 2472–2478 (2015). https://doi.org/10.1002/adma.201500311
  46. F.R. Fan, W. Tang, Z.L. Wang, Flexible nanogenerators for energy harvesting and self-powered electronics. Adv. Mater. 28, 4283–4305 (2016). https://doi.org/10.1002/adma.201504299
  47. Y. Pang, X. Zhu, T. He, S. Liu, Z. Zhang et al., AI-assisted self-powered vehicle-road integrated electronics for intelligent transportation collaborative perception. Adv. Mater. (2024). https://doi.org/10.1002/adma.202404763
  48. X. Zhao, Z. Sun, C. Lee, Augmented tactile perception of robotic fingers enabled by AI-enhanced triboelectric multimodal sensors. Adv. Funct. Mater (2024). https://doi.org/10.1002/adfm.202409558
  49. B. Kim, J.Y. Song, D.Y. Kim, M.W. Cho, J.G. Park et al., Environmentally robust triboelectric tire monitoring system for self-powered driving information recognition via hybrid deep learning in time-frequency representation. Small 20, 2400484 (2024). https://doi.org/10.1002/smll.202400484
  50. S. Khernane, S. Bouam, C. Arar, Renewable energy harvesting for wireless sensor networks in precision agriculture. Int. J. Networked Distributed Computing 12, 8–16 (2024). https://doi.org/10.1007/s44227-023-00017-6
  51. X. Guo, L. Liu, Z. Zhang, S. Gao, T. He et al., Technology evolution from micro-scale energy harvesters to nanogenerators. J. Micromech. Microeng. 31, 093002 (2021). https://doi.org/10.1088/1361-6439/ac168e
  52. Q. Shi, Z. Sun, Z. Zhang, C. Lee, Triboelectric nanogenerators and hybridized systems for enabling next-generation IoT applications. Research 2021, 6849171 (2021). https://doi.org/10.34133/2021/6849171
  53. P. Maharjan, T. Bhatta, H. Cho, X. Hui, C. Park et al., A fully functional universal self-chargeable power module for portable/wearable electronics and self-powered IoT applications. Adv. Energy Mater. 10, 1–15 (2020). https://doi.org/10.1002/aenm.202002782
  54. Y. Yang, X. Guo, M. Zhu, Z. Sun, Z. Zhang et al., Triboelectric nanogenerator enabled wearable sensors and electronics for sustainable Internet of Things integrated green earth. Adv. Energy Mater. 13, 2203040 (2023). https://doi.org/10.1002/aenm.202203040
  55. A. Luo, S. Gu, X. Guo, W. Xu, Y. Wang et al., AI-enhanced backpack with double frequency-up conversion vibration energy converter for motion recognition and extended battery life. Nano Energy 131, 110302 (2024). https://doi.org/10.1016/j.nanoen.2024.110302
  56. Q. Zhang, Q. Liang, D.K. Nandakumar, H. Qu, Q. Shi et al., Shadow enhanced self-charging power system for wave and solar energy harvesting from the ocean. Nat. Commun. 12, 616 (2021). https://doi.org/10.1038/s41467-021-20919-9
  57. L. Wang, T. He, Z. Zhang, L. Zhao, C. Lee et al., Self-sustained autonomous wireless sensing based on a hybridized TENG and PEG vibration mechanism. Nano Energy 80, 105555 (2021). https://doi.org/10.1016/j.nanoen.2020.105555
  58. C. Ma, Y.-W. Choi, D. Kang, B. Kim, S.-G. Choi et al., Moisturized 2-dimensional halide perovskite generates a power density of 30 mW cm–3. Energy Environ. Sci. 16, 5982–5991 (2023). https://doi.org/10.1039/d3ee01765f
  59. Q. Li, L. Zhang, C. Zhang, Y. Tian, Y. Fan et al., Compact, robust, and regulated-output hybrid generators for magnetic energy harvesting and self-powered sensing applications in power transmission lines. Energy Environ. Sci. 17, 2787–2799 (2024). https://doi.org/10.1039/d3ee04563c
  60. R. Li, Y. Shi, M. Wu, S. Hong, P. Wang, Photovoltaic panel cooling by atmospheric water sorption–evaporation cycle. Nat. Sustain. 3, 636–643 (2020). https://doi.org/10.1038/s41893-020-0535-4
  61. X. Li, J. Luo, K. Han, X. Shi, Z. Ren et al., Stimulation of ambient energy generated electric field on crop plant growth. Nat. Food 3, 133–142 (2022). https://doi.org/10.1038/s43016-021-00449-9
  62. Z. Wang, Q. Tang, C. Shan, Y. Du, W. He et al., Giant performance improvement of triboelectric nanogenerator systems achieved by matched in ductor design. Energy Environ. Sci. 14, 6627–6637 (2021). https://doi.org/10.1039/D1EE02852A
  63. G. Xu, X. Li, J. Fu, Y. Zhou, X. Xia et al., Environmental lifecycle assessment of CO2-filled triboelectric nanogenerators to help achieve carbon neutrality. Energy Environ. Sci. 16, 2112–2119 (2023). https://doi.org/10.1039/d2ee04119g
  64. S. Panda, S. Hajra, Y. Oh, W. Oh, J. Lee et al., Hybrid nanogenerators for ocean energy harvesting: mechanisms, designs, and applications. Small 19, 2300847 (2023). https://doi.org/10.1002/smll.202300847
  65. X. Guo, T. He, Z. Zhang, A. Luo, F. Wang et al., Artificial intelligence-enabled caregiving walking stick powered by ultra-low-frequency human motion. ACS Nano 15, 19054–19069 (2021). https://doi.org/10.1021/acsnano.1c04464
  66. S. Dai, X. Li, C. Jiang, Y. Shao, J. Luo et al., A water-driven and low-damping triboelectric nanogenerator based on agricultural debris for smart agriculture. Small 18, 2204949 (2022). https://doi.org/10.1002/smll.202204949
  67. H. Ryu, J.H. Lee, U. Khan, S.S. Kwak, R. Hinchet et al., Sustainable direct current powering a triboelectric nanogenerator via a novel asymmetrical design. Energy Environ. Sci. 11, 2057–2063 (2018). https://doi.org/10.1039/c8ee00188j
  68. H. Liu, Y. Qian, N. Wang, C. Lee, An in-plane approximated nonlinear MEMS electromagnetic energy harvester. J. Microelectromech. Syst. 23, 740–749 (2014). https://doi.org/10.1109/jmems.2013.2281736
  69. H. Liu, T. Chen, L. Sun, C. Lee, An electromagnetic MEMS energy harvester array with multiple vibration modes. Micromachines 6, 984–992 (2015). https://doi.org/10.3390/mi6080984
  70. L. Liu, Q. Shi, X. Guo, Z. Zhang, C. Lee, A facile frequency tuning strategy to realize vibration-based hybridized piezoelectric-triboelectric nanogenerators. EcoMat 5, e12279 (2023). https://doi.org/10.1002/eom2.12279
  71. S.D. Mahapatra, P.C. Mohapatra, A.I. Aria, G. Christie, Y.K. Mishra et al., Piezoelectric materials for energy harvesting and sensing applications: roadmap for future smart materials. Adv. Sci. 8, e2100864 (2021). https://doi.org/10.1002/advs.202100864
  72. L.C. Zhao, H.X. Zou, K.X. Wei, S.X. Zhou, G. Meng et al., Mechanical intelligent energy harvesting: from methodology to applications. Adv. Energy Mater. 13, 2300557 (2023). https://doi.org/10.1002/aenm.202300557
  73. H. Liu, H. Fu, L. Sun, C. Lee, E.M. Yeatman, Hybrid energy harvesting technology: from materials, structural design, system integration to applications. Renew. Sustain. Energy Rev. 137, 110473 (2021). https://doi.org/10.1016/j.rser.2020.110473
  74. L. Xu, L. Xu, J. Luo, Y. Yan, B.-E. Jia et al., Hybrid all-in-one power source based on high-performance spherical triboelectric nanogenerators for harvesting environmental energy. Adv. Energy Mater. 10, 2001669 (2020). https://doi.org/10.1002/aenm.202001669
  75. L. Dong, J. Zhu, H. Li, J. Zhang, D. Zhao et al., Bionic dragonfly staggered flapping hydrofoils triboelectric-electromagnetic hybrid generator for low-speed water flow energy harvesting. Nano Energy 127, 109783 (2024). https://doi.org/10.1016/j.nanoen.2024.109783
  76. L. Liu, X. Guo, C. Lee, Promoting smart cities into the 5G era with multi-field Internet of Things (IoT) applications powered with advanced mechanical energy harvesters. Nano Energy 88, 106304 (2021). https://doi.org/10.1016/j.nanoen.2021.106304
  77. L. Liu, X. Guo, W. Liu, C. Lee, Recent progress in the energy harvesting technology-from self-powered sensors to self-sustained IoT, and new applications. Nanomaterials (Basel) 11, 2975 (2021). https://doi.org/10.3390/nano11112975
  78. Y. Chai, C. Chen, X. Luo, S. Zhan, J. Kim et al., Cohabiting plant-wearable sensor in situ monitors water transport in plant. Adv. Sci. 8, 2003642 (2021). https://doi.org/10.1002/advs.202003642
  79. Q. Zhang, Y. Ying, J. Ping, Recent advances in plant nanoscience. Adv. Sci. 9, 2103414 (2022). https://doi.org/10.1002/advs.202103414
  80. G. Lee, Q. Wei, Y. Zhu, Emerging wearable sensors for plant health monitoring. Adv. Funct. Mater. 31, 2106475 (2021). https://doi.org/10.1002/adfm.202106475
  81. H. Yin, Y. Cao, B. Marelli, X. Zeng, A.J. Mason et al., Soil sensors and plant wearables for smart and precision agriculture. Adv. Mater. 33, 1–24 (2021). https://doi.org/10.1002/adma.202007764
  82. K. Lee, J. Park, M.S. Lee, J. Kim, B.G. Hyun et al., In-situ synthesis of carbon nanotube-graphite electronic devices and their integrations onto surfaces of live plants and insects. Nano Lett. 14, 2647–2654 (2014). https://doi.org/10.1021/nl500513n
  83. A. Bukhamsin, K. Moussi, R. Tao, G. Lubineau, I. Blilou et al., Robust, long-term, and exceptionally sensitive microneedle-based bioimpedance sensor for precision farming. Adv. Sci. 8, 1–13 (2021). https://doi.org/10.1002/advs.202101261
  84. F. Zhao, J. He, X. Li, Y. Bai, Y. Ying et al., Smart plant-wearable biosensor for in situ pesticide analysis. Biosens. Bioelectron. 170, 112636 (2020). https://doi.org/10.1016/j.bios.2020.112636
  85. G. Khandelwal, R. Dahiya, Self-powered active sensing based on triboelectric generators. Adv. Mater. 34, 2200724 (2022). https://doi.org/10.1002/adma.202200724
  86. C.C. Qu, X.Y. Sun, W.X. Sun, L.X. Cao, X.Q. Wang et al., Flexible wearables for plants. Small 17, 1–25 (2021). https://doi.org/10.1002/smll.202104482
  87. Q. Zhou, J. Pan, S. Deng, F. Xia, T. Kim, Triboelectric nanogenerator-based sensor systems for chemical or biological detection. Adv. Mater. 33, 2008276 (2021). https://doi.org/10.1002/adma.202008276
  88. Z. Li, T. Yu, R. Paul, J. Fan, Y. Yang et al., Agricultural nanodiagnostics for plant diseases: recent advances and challenges. Nanoscale Adv. 2, 3083–3094 (2020). https://doi.org/10.1039/c9na00724e
  89. J.P. Giraldo, H. Wu, G.M. Newkirk, S. Kruss, Nanobiotechnology approaches for engineering smart plant sensors. Nat. Nanotechnol. 14, 541–553 (2019). https://doi.org/10.1038/s41565-019-0470-6
  90. B. Ying, X. Liu, Skin-like hydrogel devices for wearable sensing, soft robotics and beyond. IScience 24, 103174 (2021). https://doi.org/10.1016/j.isci.2021.103174
  91. K. Yao, J. Zhou, Q. Huang, M. Wu, C.K. Yiu et al., Encoding of tactile information in hand via skin-integrated wireless haptic interface. Nat. Machine Intelligence 4, 893–903 (2022). https://doi.org/10.1038/s42256-022-00543-y
  92. X. Wu, J. Zhu, J.W. Evans, A.C. Arias, A single-mode, self-adapting, and self-powered mechanoreceptor based on a potentiometric–triboelectric hybridized sensing mechanism for resolving complex stimuli. Adv. Mater. 32, 2005970 (2020). https://doi.org/10.1002/adma.202005970
  93. X. Guo, Z. Sun, Y. Zhu, C. Lee, Zero-biased bionic fingertip E-skin with multimodal tactile perception and artificial intelligence for augmented touch awareness. Adv. Mater. 36, e2406778 (2024). https://doi.org/10.1002/adma.202406778
  94. H. Liu, H. Chu, H. Yuan, D. Li, W. Deng et al., Bioinspired multifunctional self-sensing actuated gradient hydrogel for soft-hard robot remote interaction. Nano-Micro Lett. 16, 69 (2024). https://doi.org/10.1007/s40820-023-01287-z
  95. Y. Yang, T. He, P. Ravindran, F. Wen, P. Krishnamurthy et al., All-organic transparent plant e-skin for noninvasive phenotyping. Sci. Adv. 10, 7488 (2024). https://doi.org/10.1126/sciadv.adk7488
  96. R. Ajdary, B.L. Tardy, B.D. Mattos, L. Bai, O.J. Rojas, Plant nanomaterials and inspiration from nature: water interactions and hierarchically structured hydrogels. Adv. Mater. 33, e2001085 (2021). https://doi.org/10.1002/adma.202001085
  97. Y. Zhu, C. Romain, C.K. Williams, Sustainable polymers from renewable resources. Nature 540, 354–362 (2016). https://doi.org/10.1038/nature21001
  98. K. He, P. Cai, S. Ji, Z. Tang, Z. Fang et al., An antidehydration hydrogel based on zwitterionic oligomers for bioelectronic interfacing. Adv. Mater. 36, 2311255 (2024). https://doi.org/10.1002/adma.202311255
  99. X. Yan, Y. Ma, Y. Lu, C. Su, X. Liu et al., Zeolitic imidazolate-framework-engineered heterointerface catalysis for the construction of plant-wearable sensors. Adv. Mater. 36, 2311144 (2024). https://doi.org/10.1002/adma.202311144
  100. X. Wu, Y. Pan, X. Li, Y. Shao, B. Peng et al., Rapid and in-field sensing of hydrogen peroxide in plant by hydrogel microneedle patch. Small 20, 2402024 (2024). https://doi.org/10.1002/smll.202402024
  101. N. Shakoor, S. Lee, T.C. Mockler, High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field. Curr. Opin. Plant Biol. 38, 184–192 (2017). https://doi.org/10.1016/j.pbi.2017.05.006
  102. C.H. Bock, G.H. Poole, P.E. Parker, T.R. Gottwald, Plant disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging. Crit. Rev. Plant Sci. 29, 59–107 (2010). https://doi.org/10.1080/07352681003617285
  103. M.D. Fariñas, D. Jimenez-Carretero, D. Sancho-Knapik, J.J. Peguero-Pina, E. Gil-Pelegrín et al., Instantaneous and non-destructive relative water content estimation from deep learning applied to resonant ultrasonic spectra of plant leaves. Plant Methods 15, 1–10 (2019). https://doi.org/10.1186/s13007-019-0511-z
  104. H.S. Magar, R.Y.A. Hassan, A. Mulchandani, Electrochemical impedance spectroscopy (EIS): principles, construction, and biosensing applications. Sensors (Basel) 21, 6578 (2021). https://doi.org/10.3390/s21196578
  105. J.J. Kim, L.K. Allison, T.L. Andrew, Vapor-printed polymer electrodes for long-term, on-demand health monitoring. Sci. Adv. 5, 0463 (2019). https://doi.org/10.1126/sciadv.aaw0463ith advanced multi-layer nanofiber-reinforced 3D scaffolds for acellular tendon complexes. Mater. Today Bio 26, 101099 (2024). https://doi.org/10.1016/j.mtbio.2024.101099
  106. W. Wei, H. Dai, Articular cartilage and osteochondral tissue engineering techniques: recent advances and challenges. Bioact. Mater. 6, 4830–4855 (2021). https://doi.org/10.1016/j.bioactmat.2021.05.011
  107. M. Qasim, D.S. Chae, N.Y. Lee, Bioengineering strategies for bone and cartilage tissue regeneration using growth factors and stem cells. J. Biomed. Mater. Res. A 108, 394–411 (2020). https://doi.org/10.1002/jbm.a.36817
  108. S. Camarero-Espinosa, I. Beeren, H. Liu, D.B. Gomes, J. Zonderland et al., 3D niche-inspired scaffolds as a stem cell delivery system for the regeneration of the osteochondral interface. Adv. Mater. 36, e2310258 (2024). https://doi.org/10.1002/adma.202310258
  109. A.J. Boys, H. Zhou, J.B. Harrod, M.C. McCorry, L.A. Estroff et al., Top-down fabrication of spatially controlled mineral-gradient scaffolds for interfacial tissue engineering. ACS Biomater. Sci. Eng. 5, 2988–2997 (2019). https://doi.org/10.1021/acsbiomaterials.9b00176
  110. S.M. Bittner, B.T. Smith, L. Diaz-Gomez, C.D. Hudgins, A.J. Melchiorri et al., Fabrication and mechanical characterization of 3D printed vertical uniform and gradient scaffolds for bone and osteochondral tissue engineering. Acta Biomater. 90, 37–48 (2019). https://doi.org/10.1016/j.actbio.2019.03.041
  111. C. Wang, W. Huang, Y. Zhou, L. He, Z. He et al., 3D printing of bone tissue engineering scaffolds. Bioact. Mater. 5, 82–91 (2020). https://doi.org/10.1016/j.bioactmat.2020.01.004
  112. T.D. Ngo, A. Kashani, G. Imbalzano, K.T.Q. Nguyen, D. Hui, Additive manufacturing (3D printing): a review of materials, methods, applications and challenges. Compos. Part B Eng. 143, 172–196 (2018). https://doi.org/10.1016/j.compositesb.2018.02.012
  113. B. Liao, R.F. Xia, W. Li, D. Lu, Z.M. Jin, 3D-printed Ti6Al4V scaffolds with graded triply periodic minimal surface structure for bone tissue engineering. J. Mater. Eng. Perform. 30, 4993–5004 (2021). https://doi.org/10.1007/s11665-021-05580-z
  114. A. Bagheri, J. Jin, Photopolymerization in 3D printing. ACS Appl. Polym. Mater. 1, 593–611 (2019). https://doi.org/10.1021/acsapm.8b00165
  115. L. Li, R. Hao, J. Qin, J. Song, X. Chen et al., Electrospun fibers control drug delivery for tissue regeneration and cancer therapy. Adv. Fiber Mater. 4, 1375–1413 (2022). https://doi.org/10.1007/s42765-022-00198-9
  116. L. Wang, T. Zhu, Y. Kang, J. Zhang, J. Du et al., Crimped nanofiber scaffold mimicking tendon-to-bone interface for fatty-infiltrated massive rotator cuff repair. Bioact. Mater. 16, 149–161 (2022). https://doi.org/10.1016/j.bioactmat.2022.01.031
  117. Z. Chen, H. Xiao, H. Zhang, Q. Xin, H. Zhang et al., Heterogenous hydrogel mimicking the osteochondral ECM applied to tissue regeneration. J. Mater. Chem. B 9, 8646–8658 (2021). https://doi.org/10.1039/D1TB00518A
  118. H. Zhang, S. Wu, W. Chen, Y. Hu, Z. Geng et al., Bone/cartilage targeted hydrogel: strategies and applications. Bioact. Mater. 23, 156–169 (2022). https://doi.org/10.1016/j.bioactmat.2022.10.028
  119. L. Chen, L. Wei, X. Su, L. Qin, Z. Xu et al., Preparation and characterization of biomimetic functional scaffold with gradient structure for osteochondral defect repair. Bioengineering 10, 213 (2023). https://doi.org/10.3390/bioengineering10020213
  120. Z. Zhao, R. Li, H. Ruan, Z. Cai, Y. Zhuang et al., Biological signal integrated microfluidic hydrogel microspheres for promoting bone regeneration. Chem. Eng. J. 436, 135176 (2022). https://doi.org/10.1016/j.cej.2022.135176
  121. M.K. Kim, K. Paek, S.M. Woo, J.A. Kim, Bone-on-a-chip: biomimetic models based on microfluidic technologies for biomedical applications. ACS Biomater. Sci. Eng. 9, 3058–3073 (2023). https://doi.org/10.1021/acsbiomaterials.3c00066
  122. P. Pan, X. Chen, K. Metavarayuth, J. Su, Q. Wang, Self-assembled supramolecular systems for bone engineering applications. Curr. Opin. Colloid Interface Sci. 35, 104–111 (2018). https://doi.org/10.1016/j.cocis.2018.01.015
  123. X. Lin, Q. Wang, C. Gu, M. Li, K. Chen et al., Smart nanosacrificial layer on the bone surface prevents osteoporosis through acid-base neutralization regulated biocascade effects. J. Am. Chem. Soc. 142, 17543–17556 (2020). https://doi.org/10.1021/jacs.0c07309
  124. K. Maji, K. Pramanik, Electrospun scaffold for bone regeneration. Int. J. Polym. Mater. Polym. Biomater. 71, 842–857 (2022). https://doi.org/10.1080/00914037.2021.1915784
  125. Z. Wang, Y. Wang, J. Yan, K. Zhang, F. Lin et al., Pharmaceutical electrospinning and 3D printing scaffold design for bone regeneration. Adv. Drug Deliv. Rev. 174, 504–534 (2021). https://doi.org/10.1016/j.addr.2021.05.007
  126. J. Xue, T. Wu, Y. Xia, Perspective: Aligned arrays of electrospun nanofibers for directing cell migration. APL Mater. 6, 120902 (2018). https://doi.org/10.1063/1.5058083
  127. Z. Fan, H. Liu, Z. Ding, L. Xiao, Q. Lu et al., Simulation of cortical and cancellous bone to accelerate tissue regeneration. Adv. Funct. Mater. 33, 2301839 (2023). https://doi.org/10.1002/adfm.202301839
  128. W. Liu, J. Lipner, J. Xie, C.N. Manning, S. Thomopoulos et al., Nanofiber scaffolds with gradients in mineral content for spatial control of osteogenesis. ACS Appl. Mater. Interfaces 6, 2842–2849 (2014). https://doi.org/10.1021/am405418g
  129. W. Liu, Q. Sun, Z.-L. Zheng, Y.-T. Gao, G.-Y. Zhu et al., Topographic cues guiding cell polarization via distinct cellular mechanosensing pathways. Small 18, e2104328 (2022). https://doi.org/10.1002/smll.202104328
  130. S.K. Perikamana, J. Lee, T. Ahmad, Y. Jeong, D.G. Kim et al., Effects of immobilized BMP-2 and nanofiber morphology on in vitro osteogenic differentiation of hMSCs and in vivo collagen assembly of regenerated bone. ACS Appl. Mater. Interfaces 7, 8798–8808 (2015). https://doi.org/10.1021/acsami.5b01340
  131. Q. Chen, C. Wang, X. Zhang, G. Chen, Q. Hu et al., In situ sprayed bioresponsive immunotherapeutic gel for post-surgical cancer treatment. Nat. Nanotechnol. 14, 89–97 (2019). https://doi.org/10.1038/s41565-018-0319-4
  132. R.K. Tindell, L.P. Busselle, J.L. Holloway, Magnetic fields enable precise spatial control over electrospun fiber alignment for fabricating complex gradient materials. J. Biomed. Mater. Res. A 111, 778–789 (2023). https://doi.org/10.1002/jbm.a.37492
  133. M.L. Tanes, J. Xue, Y. Xia, A general strategy for generating gradients of bioactive proteins on electrospun nanofiber mats by masking with bovine serum albumin. J. Mater. Chem. B 5, 5580–5587 (2017). https://doi.org/10.1039/C7TB00974G
  134. T. Wu, J. Xue, H. Li, C. Zhu, X. Mo et al., General method for generating circular gradients of active proteins on nanofiber scaffolds sought for wound closure and related applications. ACS Appl. Mater. Interfaces 10, 8536–8545 (2018). https://doi.org/10.1021/acsami.8b00129
  135. Z. Qiao, M. Lian, Y. Han, B. Sun, X. Zhang et al., Bioinspired stratified electrowritten fiber-reinforced hydrogel constructs with layer-specific induction capacity for functional osteochondral regeneration. Biomaterials 266, 120385 (2021). https://doi.org/10.1016/j.biomaterials.2020.120385
  136. I. Calejo, R. Costa-Almeida, R.L. Reis, M.E. Gomes, A textile platform using continuous aligned and textured composite microfibers to engineer tendon-to-bone interface gradient scaffolds. Adv. Healthc. Mater. 8, e1900200 (2019). https://doi.org/10.1002/adhm.201900200
  137. G. Narayanan, L.S. Nair, C.T. Laurencin, Regenerative engineering of the rotator cuff of the shoulder. ACS Biomater. Sci. Eng. 4, 751–786 (2018). https://doi.org/10.1021/acsbiomaterials.7b00631
  138. J. Cai, J. Wang, K. Ye, D. Li, C. Ai et al., Dual-layer aligned-random nanofibrous scaffolds for improving gradient microstructure of tendon-to-bone healing in a rabbit extra-articular model. Int. J. Nanomedicine 13, 3481–3492 (2018). https://doi.org/10.2147/IJN.S165633
  139. X. Wang, K. Xu, L. Mu, X. Zhang, G. Huang et al., Mussel-derived bioadaptive artificial tendon facilitates the cell proliferation and tenogenesis to promote tendon functional reconstruction. Adv. Healthc. Mater. 12, e2203400 (2023). https://doi.org/10.1002/adhm.202203400
  140. C. Yu, T. Wang, H. Diao, N. Liu, Y. Zhang et al., Photothermal-triggered structural change of nanofiber scaffold integrating with graded mineralization to promote tendon–bone healing. Adv. Fiber Mater. 4, 908–922 (2022). https://doi.org/10.1007/s42765-022-00154-7
  141. I. Roppolo, M. Caprioli, C.F. Pirri, S. Magdassi, 3D printing of self-healing materials. Adv. Mater. 36, 2305537 (2024). https://doi.org/10.1002/adma.202305537
  142. M.K. Joshi, H.R. Pant, A.P. Tiwari, H.J. Kim, C.H. Park et al., Multi-layered macroporous three-dimensional nanofibrous scaffold via a novel gas foaming technique. Chem. Eng. J. 275, 79–88 (2015). https://doi.org/10.1016/j.cej.2015.03.121
  143. L. Wang, Y. Qiu, Y. Guo, Y. Si, L. Liu et al., Smart, elastic, and nanofiber-based 3D scaffolds with self-deploying capability for osteoporotic bone regeneration. Nano Lett. 19, 9112–9120 (2019). https://doi.org/10.1021/acs.nanolett.9b04313
  144. G. Turnbull, J. Clarke, F. Picard, P. Riches, L. Jia et al., 3D bioactive composite scaffolds for bone tissue engineering. Bioact. Mater. 3, 278–314 (2018). https://doi.org/10.1016/j.bioactmat.2017.10.001
  145. L. Wu, X. Pei, B. Zhang, Z. Su, X. Gui et al., 3D-printed HAp bone regeneration scaffolds enable nano-scale manipulation of cellular mechanotransduction signals. Chem. Eng. J. 455, 140699 (2023). https://doi.org/10.1016/j.cej.2022.140699
  146. K. Garg, N.A. Pullen, C.A. Oskeritzian, J.J. Ryan, G.L. Bowlin, Macrophage functional polarization (M1/M2) in response to varying fiber and pore dimensions of electrospun scaffolds. Biomaterials 34, 4439–4451 (2013). https://doi.org/10.1016/j.biomaterials.2013.02.065
  147. S. Jiang, C. Lyu, P. Zhao, W. Li, W. Kong et al., Cryoprotectant enables structural control of porous scaffolds for exploration of cellular mechano-responsiveness in 3D. Nat. Commun. 10, 3491 (2019). https://doi.org/10.1038/s41467-019-11397-1
  148. M. Lafuente-Merchan, S. Ruiz-Alonso, F. García-Villén, I. Gallego, P. Gálvez-Martín et al., Progress in 3D bioprinting technology for osteochondral regeneration. Pharmaceutics 14, 1578 (2022). https://doi.org/10.3390/pharmaceutics14081578
  149. J. Zhang, D. Tong, H. Song, R. Ruan, Y. Sun et al., Osteoimmunity-regulating biomimetically hierarchical scaffold for augmented bone regeneration. Adv. Mater. 34, e2202044 (2022). https://doi.org/10.1002/adma.202202044
  150. J. Zhang, W. Hu, C. Ding, G. Yao, H. Zhao et al., Deferoxamine inhibits iron-uptake stimulated osteoclast differentiation by suppressing electron transport chain and MAPKs signaling. Toxicol. Lett. 313, 50–59 (2019). https://doi.org/10.1016/j.toxlet.2019.06.007
  151. C. Li, W. Zhang, Y. Nie, D. Jiang, J. Jia et al., Integrated and bifunctional bilayer 3D printing scaffold for osteochondral defect repair. Adv. Funct. Mater. 33, 2214158 (2023). https://doi.org/10.1002/adfm.202214158
  152. Y. Liu, L. Peng, L. Li, C. Huang, K. Shi et al., 3D-bioprinted BMSC-laden biomimetic Multiphasic scaffolds for efficient repair of osteochondral defects in an osteoarthritic rat model. Biomaterials 279, 121216 (2021). https://doi.org/10.1016/j.biomaterials.2021.121216
  153. X. Zhang, W. Song, K. Han, Z. Fang, E. Cho et al., Three-dimensional bioprinting of a structure-, composition-, and mechanics-graded biomimetic scaffold coated with specific decellularized extracellular matrix to improve the tendon-to-bone healing. ACS Appl. Mater. Interfaces 15, 28964–28980 (2023). https://doi.org/10.1021/acsami.3c03793
  154. R. Sinha, M. Cámara-Torres, P. Scopece, E. Verga Falzacappa, A. Patelli et al., A hybrid additive manufacturing platform to create bulk and surface composition gradients on scaffolds for tissue regeneration. Nat. Commun. 12, 500 (2021). https://doi.org/10.1038/s41467-020-20865-y
  155. I.A.O. Beeren, P.J. Dijkstra, A.F.H. Lourenço, R. Sinha, D.B. Gomes et al., Installation of click-type functional groups enable the creation of an additive manufactured construct for the osteochondral interface. Biofabrication (2022). https://doi.org/10.1088/1758-5090/aca3d4
  156. Y. Cai, S.Y. Chang, S.W. Gan, S. Ma, W.F. Lu et al., Nanocomposite bioinks for 3D bioprinting. Acta Biomater. 151, 45–69 (2022). https://doi.org/10.1016/j.actbio.2022.08.014
  157. S. Pouraghaei Sevari, J.K. Kim, C. Chen, A. Nasajpour, C.Y. Wang et al., Whitlockite-enabled hydrogel for craniofacial bone regeneration. ACS Appl. Mater. Interfaces 13, 35342–35355 (2021). https://doi.org/10.1021/acsami.1c07453
  158. A. Mokhtarzade, R. Imani, P. Shokrollahi, A gradient four-layered gelatin methacrylate/agarose construct as an injectable scaffold for mimicking osteochondral tissue. J. Mater. Sci. 58, 5735–5755 (2023). https://doi.org/10.1007/s10853-023-08374-x
  159. X. Hao, S. Miao, Z. Li, T. Wang, B. Xue et al., 3D printed structured porous hydrogel promotes osteogenic differentiation of BMSCs. Mater. Des. 227, 111729 (2023). https://doi.org/10.1016/j.matdes.2023.111729
  160. W. Wei, W. Liu, H. Kang, X. Zhang, R. Yu et al., A one-stone-two-birds strategy for osteochondral regeneration based on a 3D printable biomimetic scaffold with kartogenin biochemical stimuli gradient. Adv. Healthc. Mater. 12, 2300108 (2023). https://doi.org/10.1002/adhm.202300108
  161. D. Gan, Z. Wang, C. Xie, X. Wang, W. Xing et al., Mussel-inspired tough hydrogel with in situ nanohydroxyapatite mineralization for osteochondral defect repair. Adv. Healthc. Mater. 8, e1901103 (2019). https://doi.org/10.1002/adhm.201901103
  162. C. Parisi, L. Salvatore, L. Veschini, M.P. Serra, C. Hobbs et al., Biomimetic gradient scaffold of collagen-hydroxyapatite for osteochondral regeneration. J. Tissue Eng. 11, 2041731419896068 (2020). https://doi.org/10.1177/2041731419896068
  163. P. Mou, H. Peng, L. Zhou, L. Li, H. Li et al., A novel composite scaffold of Cu-doped nano calcium-deficient hydroxyapatite/multi-(amino acid) copolymer for bone tissue regeneration. Int. J. Nanomedicine 14, 3331–3343 (2019). https://doi.org/10.2147/IJN.S195316
  164. S. Stein, L. Kruck, D. Warnecke, A. Seitz et al., Osseointegration of titanium implants with a novel silver coating under dynamic loading. Eur. Cells Mater. 39, 249–259 (2020). https://doi.org/10.22203/ecm.v039a16
  165. C. Gao, W. Dai, X. Wang, L. Zhang, Y. Wang et al., Magnesium gradient-based hierarchical scaffold for dual-lineage regeneration of osteochondral defect. Adv. Funct. Mater. 33, 2304829 (2023). https://doi.org/10.1002/adfm.202304829
  166. R. Yang, G. Li, C. Zhuang, P. Yu, T. Ye et al., Gradient bimetallic ion-based hydrogels for tissue microstructure reconstruction of tendon-to-bone insertion. Sci. Adv. 7, eabg3816 (2021). https://doi.org/10.1126/sciadv.abg3816
  167. C. Li, L. Ouyang, I.J. Pence, A.C. Moore, Y. Lin et al., Buoyancy-driven gradients for biomaterial fabrication and tissue engineering. Adv. Mater. 31, e1900291 (2019). https://doi.org/10.1002/adma.201900291
  168. C. Li, J.P. Armstrong, I.J. Pence, W. Kit-Anan, J.L. Puetzer et al., Glycosylated superparamagnetic nanop gradients for osteochondral tissue engineering. Biomaterials 176, 24–33 (2018). https://doi.org/10.1016/j.biomaterials.2018.05.029
  169. L. Xiao, M. Wu, F. Yan, Y. Xie, Z. Liu et al., A radial 3D polycaprolactone nanofiber scaffold modified by biomineralization and silk fibroin coating promote bone regeneration in vivo. Int. J. Biol. Macromol. 172, 19–29 (2021). https://doi.org/10.1016/j.ijbiomac.2021.01.036
  170. S. Chen, H. Wang, V.L. Mainardi, G. Talò, A. McCarthy et al., Biomaterials with structural hierarchy and controlled 3D nanotopography guide endogenous bone regeneration. Sci. Adv. 7, eabg3089 (2021). https://doi.org/10.1126/sciadv.abg3089
  171. P. Kazimierczak, A. Benko, K. Palka, C. Canal, D. Kolodynska et al., Novel synthesis method combining a foaming agent with freeze-drying to obtain hybrid highly macroporous bone scaffolds. J. Mater. Sci. Technol. 43, 52–63 (2020). https://doi.org/10.1016/j.jmst.2020.01.006
  172. Z. Zhao, G. Li, H. Ruan, K. Chen, Z. Cai et al., Capturing magnesium ions via microfluidic hydrogel microspheres for promoting cancellous bone regeneration. ACS Nano 15, 13041–13054 (2021). https://doi.org/10.1021/acsnano.1c02147
  173. J.J. Paredes, N. Andarawis-Puri, Therapeutics for tendon regeneration: a multidisciplinary review of tendon research for improved healing. Ann. N. Y. Acad. Sci. 1383, 125–138 (2016). https://doi.org/10.1111/nyas.13228
  174. C. Zhu, S. Pongkitwitoon, J. Qiu, S. Thomopoulos, Y. Xia, Design and fabrication of a hierarchically structured scaffold for tendon-to-bone repair. Adv. Mater. 30, e1707306 (2018). https://doi.org/10.1002/adma.201707306
  175. W. Su, J. Guo, J. Xu, K. Huang, J. Chen et al., Gradient composite film with calcium phosphate silicate for improved tendon-to-Bone intergration. Chem. Eng. J. 404, 126473 (2021). https://doi.org/10.1016/j.cej.2020.126473
  176. H. Zhang, H. Huang, G. Hao, Y. Zhang, H. Ding et al., 3D printing hydrogel scaffolds with nanohydroxyapatite gradient to effectively repair osteochondral defects in rats. Adv. Funct. Mater. 31, 2006697 (2021). https://doi.org/10.1002/adfm.202006697
  177. Q. Wang, Y. Feng, M. He, W. Zhao, L. Qiu et al., A hierarchical Janus nanofibrous membrane combining direct osteogenesis and osteoimmunomodulatory functions for advanced bone regeneration. Adv. Funct. Mater. 31, 2008906 (2021). https://doi.org/10.1002/adfm.202008906
  178. C. Deng, J. Yang, H. He, Z. Ma, W. Wang et al., 3D bio-printed biphasic scaffolds with dual modification of silk fibroin for the integrated repair of osteochondral defects. Biomater. Sci. 9, 4891–4903 (2021). https://doi.org/10.1039/d1bm00535a
  179. D. Shi, J. Shen, Z. Zhang, C. Shi, M. Chen et al., Preparation and properties of dopamine-modified alginate/chitosan-hydroxyapatite scaffolds with gradient structure for bone tissue engineering. J. Biomed. Mater. Res. A 107, 1615–1627 (2019). https://doi.org/10.1002/jbm.a.36678
  180. Y. Wang, C. Ling, J. Chen, H. Liu, Q. Mo et al., 3D-printed composite scaffold with gradient structure and programmed biomolecule delivery to guide stem cell behavior for osteochondral regeneration. Biomater. Adv. 140, 213067 (2022). https://doi.org/10.1016/j.bioadv.2022.213067
  181. N. Zhang, Y. Wang, J. Zhang, J. Guo, J. He, Controlled domain gels with a biomimetic gradient environment for osteochondral tissue regeneration. Acta Biomater. 135, 304–317 (2021). https://doi.org/10.1016/j.actbio.2021.08.029
  182. A.-M. Wu, C. Bisignano, S. James, G.G. Abady, A. Abedi et al., Global, regional, and national burden of bone fractures in 204 countries and territories, 1990–2019: a systematic analysis from the global burden of disease study 2019. Lancet Healthy Longev. 2, e580–e592 (2021). https://doi.org/10.1016/S2666-7568(21)00172-0
  183. Y. Li, X. Wei, J. Zhou, L. Wei, The age-related changes in cartilage and osteoarthritis. Biomed. Res. Int. 2013, 916530 (2013). https://doi.org/10.1155/2013/916530
  184. H. Minagawa, N. Yamamoto, H. Abe, M. Fukuda, N. Seki et al., Prevalence of symptomatic and asymptomatic rotator cuff tears in the general population: from mass-screening in one village. J. Orthop. 10, 8–12 (2013). https://doi.org/10.1016/j.jor.2013.01.008
  185. L. Mancinelli, G. Intini, Age-associated declining of the regeneration potential of skeletal stem/progenitor cells. Front. Physiol. 14, 1087254 (2023). https://doi.org/10.3389/fphys.2023.1087254
  186. S. Ghouse, N. Reznikov, O.R. Boughton, S. Babu, K.C.G. Ng et al., The design and in vivo testing of a locally stiffness-matched porous scaffold. Appl. Mater. Today 15, 377–388 (2019). https://doi.org/10.1016/j.apmt.2019.02.017
  187. P. Diloksumpan, R.V. Bolaños, S. Cokelaere, B. Pouran, J. de Grauw et al., Orthotopic bone regeneration within 3D printed bioceramic scaffolds with region-dependent porosity gradients in an equine model. Adv. Healthc. Mater. 9, e1901807 (2020). https://doi.org/10.1002/adhm.201901807
  188. G. Li, L. Wang, W. Pan, F. Yang, W. Jiang et al., In vitro and in vivo study of additive manufactured porous Ti6Al4V scaffolds for repairing bone defects. Sci. Rep. 6, 34072 (2016). https://doi.org/10.1038/srep34072
  189. S. Jia, J. Wang, T. Zhang, W. Pan, Z. Li et al., Multilayered scaffold with a compact interfacial layer enhances osteochondral defect repair. ACS Appl. Mater. Interfaces 10, 20296–20305 (2018). https://doi.org/10.1021/acsami.8b03445
  190. Y. Zhang, D. Li, Y. Liu, L. Peng, D. Lu et al., 3D-bioprinted anisotropic bicellular living hydrogels boost osteochondral regeneration via reconstruction of cartilage-bone interface. Innovation 5, 100542 (2023). https://doi.org/10.1016/j.xinn.2023.100542
  191. Y.S. Zhang, G. Haghiashtiani, T. Hübscher, D.J. Kelly, J.M. Lee et al., 3D extrusion bioprinting. Nat. Rev. Methods Primers 1, 75 (2021). https://doi.org/10.1038/s43586-021-00073-8
  192. L. Wang, Z. Wang, Immune responses to silk proteins in vitro and in vivo: lessons learnt. Silk-based biomaterials for tissue engineering, regenerative and precision medicine (Elsevier, Amsterdam, 2024), pp.385–413. https://doi.org/10.1016/b978-0-323-96017-5.00006-6
  193. S. Tajvar, A. Hadjizadeh, S.S. Samandari, Scaffold degradation in bone tissue engineering: an overview. Int. Biodeterior. Biodegrad. 180, 105599 (2023). https://doi.org/10.1016/j.ibiod.2023.105599
  194. Q. Zhang, Y. Jiang, Y. Zhang, Z. Ye, W. Tan et al., Effect of porosity on long-term degradation of poly (ε-caprolactone) scaffolds and their cellular response. Polym. Degrad. Stab. 98, 209–218 (2013). https://doi.org/10.1016/j.polymdegradstab.2012.10.008
  195. J. Ye, N. Liu, Z. Li, L. Liu, M. Zheng et al., Injectable, hierarchically degraded bioactive scaffold for bone regeneration. ACS Appl. Mater. Interfaces 15, 11458–11473 (2023). https://doi.org/10.1021/acsami.2c18824
  196. J. Xue, T. Wu, J. Qiu, S. Rutledge, M.L. Tanes et al., Promoting cell migration and neurite extension along uniaxially aligned nanofibers with biomacromolecular ps in a density gradient. Adv. Funct. Mater. 30, 2002031 (2020). https://doi.org/10.1002/adfm.202002031
  197. X. Zhang, L. Li, J. Ouyang, L. Zhang, J. Xue et al., Electroactive electrospun nanofibers for tissue engineering. Nano Today 39, 101196 (2021). https://doi.org/10.1016/j.nantod.2021.101196
  198. C. Xie, J. Ye, R. Liang, X. Yao, X. Wu et al., Advanced strategies of biomimetic tissue-engineered grafts for bone regeneration. Adv. Healthc. Mater. 10, e2100408 (2021). https://doi.org/10.1002/adhm.202100408
  199. P. Zhang, Z. Teng, M. Zhou, X. Yu, H. Wen et al., Upconversion 3D bioprinting for noninvasive in vivo molding. Adv. Mater. 36, e2310617 (2024). https://doi.org/10.1002/adma.202310617
  200. P. Pei, H. Hu, Y. Chen, S. Wang, J. Chen et al., NIR-II ratiometric lanthanide-dye hybrid nanoprobes doped bioscaffolds for in situ bone repair monitoring. Nano Lett. 22, 783–791 (2022). https://doi.org/10.1021/acs.nanolett.1c04356
  201. L.B. Jiang, S.L. Ding, W. Ding, D.H. Su, F.X. Zhang et al., Injectable sericin based nanocomposite hydrogel for multi-modal imaging-guided immunomodulatory bone regeneration. Chem. Eng. J. 418, 129323 (2021). https://doi.org/10.1016/j.cej.2021.129323
  202. B. Li, M. Zhao, L. Feng, C. Dou, S. Ding et al., Organic NIR-II molecule with long blood half-life for in vivo dynamic vascular imaging. Nat. Commun. 11, 3102 (2020). https://doi.org/10.1038/s41467-020-16924-z
  203. P. Pei, Y. Chen, C. Sun, Y. Fan, Y. Yang et al., X-ray-activated persistent luminescence nanomaterials for NIR-II imaging. Nat. Nanotechnol. 16, 1011–1018 (2021). https://doi.org/10.1038/s41565-021-00922-3
  204. L. Zelaya-Lainez, H. Kariem, W. Nischkauer, A. Limbeck, C. Hellmich, “Variances” and “in-variances” in hierarchical porosity and composition, across femoral tissues from cow, horse, ostrich, emu, pig, rabbit, and frog. Mater. Sci. Eng. C 117, 111234 (2020). https://doi.org/10.1016/j.msec.2020.111234
  205. H. Zhang, L. Yang, X.G. Yang, F. Wang, J.T. Feng et al., Demineralized bone matrix carriers and their clinical applications: an overview. Orthop. Surg. 11, 725–737 (2019). https://doi.org/10.1111/os.12509
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