Machine learning-enabled optimization of melt electro-writing three-dimensional printing

Melt electrowriting(MEW)is a solvent-free(i.e.,no volatile chemicals),a high-resolution three-dimensional(3D)printing method that enables the fabrication of semi-flexible structures with rigid polymers.Despite its advantages,the MEW pro-cess is sensitive to changes in printing parameters(e.g.,voltage,printing pressure,and temperature),which can causefluid column breakage,jet lag,and/orfiber pulsing,ultimately deteriorating the resolution and printing quality.In spite of the commonly used error-and-trial method to determine the most suitable parameters,here,we present a machine learning(ML)-enabled image analysis-based method for determining the optimum MEW printing parameters through an easy-to-use graph-ical user interface(GUI).We trainedfive different ML algorithms using 168 MEW 3D print samples,among which the Gaussian process regression ML model yielded 93%accuracy of the variability in the dependent variable,0.12329 on root mean square error for the validation set and 0.015201 mean square error in predicting line thickness.Integration of ML with a control feedback loop and MEW can reduce the error-and-trial steps prior to the 3D printing process,decreasing the printing time(i.e.,increasing the overall throughput of MEW)and material waste(i.e.,improving the cost-effectiveness of MEW).Moreover,embedding a trained ML model with the feedback control system in a GUI facilitates a more straightforward use of ML-based optimization techniques in the industrial section(i.e.,for users with no ML skills).

3D bioprinted organ-on-chips

Organ-on-a-chip(OOC)platforms recapitulate human in vivo-like conditions more realistically compared to many animal models and conventional two-dimensional cell cultures.OOC setups benefit from continuous perfusion of cell cultures through microfluidic channels,which promotes cell viability and activities.Moreover,microfluidic chips allow the integration of biosensors for real-time monitoring and analysis of cell interactions and responses to administered drugs.Three-dimensional(3D)bioprinting enables the fabrication of multicell OOC platforms with sophis-ticated 3D structures that more closely mimic human tissues.3D-bioprinted OOC platforms are promising tools for understanding the functions of organs,disruptive influences of diseases on organ functionality,and screening the efficacy as well as toxicity of drugs on organs.Here,common 3D bioprinting techniques,advantages,and limitations of each method are reviewed.Additionally,recent advances,applica-tions,and potentials of 3D-bioprinted OOC platforms for emulating various human organs are presented.Last,current challenges and future perspectives of OOC plat-forms are discussed.