Journal of Zhejiang University

Bio-Design and Manufacturing 2026 Vol.9 No.4 P.782 - 795

Bayesian optimization-enabled efficient embedded ink writing of human tissue analogs

Author(s): Shanti Quinto,Haoran Cui,Lily Raymond,Eric Shen,Hopson Tan,Liam Bond,Yue Yuan,Bin Duan,Yan Wang,Guangrui Chai,Yifei Jin
Affiliation(s): 1. Department of Mechanical Engineering, University of Nevada, Reno, Reno, Nevada 89557, USA more
Corresponding email(s): yanwang@unr.edu, chaigr@sj-hospital.org, yifeij@unr.edu
Key Words: Bayesian optimization, Embedded ink writing, Support bath design, Three-dimensional (3D) printing parameter prediction, Biomedical applications

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Shanti Quinto, Haoran Cui, Lily Raymond, Eric Shen, Hopson Tan, Liam Bond, Yue Yuan, Bin Duan, Yan Wang, Guangrui Chai, Yifei Jin. Bayesian optimization-enabled efficient embedded ink writing of human tissue analogs[J]. Journal of Zhejiang University Science D, 2026, 9(4): 782 - 795.

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author="Shanti Quinto, Haoran Cui, Lily Raymond, Eric Shen, Hopson Tan, Liam Bond, Yue Yuan, Bin Duan, Yan Wang, Guangrui Chai, Yifei Jin",
journal="Journal of Zhejiang University Science D",
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pages="782 - 795",
year="2026",
publisher="Zhejiang University Press & Springer",
doi="10.1631/bdm.2600114"
}

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Abstract
Chinese Summary
Academic Network
Reviewer Comment

Abstract: Embedded ink writing has been extensively applied in recent years for various biomedical applications. Despite its outstanding ability to create complex structures, the challenge of optimizing multiple factors has hampered further utilization of this three-dimensional bioprinting strategy. In this work, we experimentally summarized the coupling effects of ink viscosity, support bath rheological properties, and key printing parameters on filament formation. Based on the gathered data, Bayesian optimization is used to establish a filament prediction platform, which can accurately estimate the rheology of support baths for printing alginate-based ink under the given conditions. Additionally, the platform is used to predict the optimal parameters for printing with chitosan ink. Two representative eye-relevant tissues are successfully fabricated using the predictions of the platform. The insights from this study lay the foundation for embedded ink writing strategies that can guide support bath design and identify optimal printing parameters, aiding efficient reconstruction of human tissues and organs in the future.

基于贝叶斯优化的仿生人体组织高效嵌入式墨水书写技术

近年来，嵌入式墨水书写技术已广泛应用于各种生物医学领域。尽管其在创建复杂结构方面具有出色的能力，但需同时优化多个因素的挑战阻碍了这种三维生物打印策略的进一步利用。在本研究中，我们通过实验总结了墨水粘度、支撑浴流变特性和关键打印参数对细丝形成机理的耦合影响。基于所收集的数据，利用贝叶斯优化建立了一个细丝结构预测平台。该平台可以准确估算在给定条件下打印藻酸盐基墨水所需的支撑浴流变特性。此外，该平台还被用于预测使用壳聚糖墨水打印的最佳参数。利用该平台的预测，我们成功制造了两种具有代表性的眼部相关组织。本研究为嵌入式墨水书写策略奠定了基础，可指导支撑浴的设计并确定最佳打印参数，从而有助于未来人体组织和器官的高效重建。
关键词：贝叶斯优化；嵌入式墨水书写；支撑浴设计；三维（3D）打印参数预测；生物医学应用