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International Journal of Bioprinting AI for sustainable bioprinting

Figure 1. Overview of the structure of this review, which explores how artificial intelligence (AI) supports sustainable bioprinting across four key domains:
material discovery, bioink screening, process optimization, and intelligent system integration. These AI-driven strategies contribute to the development of
eco-friendly hydrogels, the reduction of material waste, improved energy efficiency, and experimental productivity.

Figure 2. Schematic representation of the four main bioprinting methods. (A) Inkjet bioprinting utilizes piezoelectric or thermal actuators to eject precise,
small droplets of bioinks containing hydrogels and cells. (B) Microextrusion bioprinting deposits filaments of viscous bioinks continuously through a
nozzle, driven by pneumatic or mechanical (piston or screw-based) force. This technique excels in fabricating constructs with high cell densities and
structural integrity. (C) Laser-assisted bioprinting uses a focused laser pulse to vaporize a thin donor layer (typically metallic or energy-absorbing material),
generating high-pressure bubbles that propel droplets of bioink onto the substrate. (D) Stereolithography bioprinting employs ultraviolet (UV) or visible
light to selectively polymerize photoreactive bioink layer-by-layer, creating a three-dimensional construct. Reprinted from Foyt et al. 21

Volume 11 Issue 4 (2025) 135 doi: 10.36922/IJB025170164