3D 프린터로 움직이는 세포 위에 센서 만들기.

https://techxplore.com/news/2020-06-discovery-d-sensors.html

The researchers started in the lab with a balloon-like surface and a specialized 3-D printer. They used motion capture tracking markers, much like those used in movies to create special effects, to help the 3-D printer adapt its printing path to the expansion and contraction movements on the surface. The researchers then moved on to an animal lung in the lab that was artificially inflated. They were able to successfully print a soft hydrogel-based sensor directly on the surface.

"The broader idea behind this research, is that this is a big step forward to the goal of combining 3-D printing technology with surgical robots,"

https://youtu.be/DTXqUrmr3FQ

 

논문을 읽어보니

 In medical applications, the target live biological surfaces are typically soft and undergo persistent motion and deformation. This time-varying geometry fundamentally limits the applications of existing 3D printing systems that were built upon an open-loop paradigm, in which a prescribed design is first manufactured offline on a calibrated planar substrate and then transferred to the target biological surface (1). This renders the fabrication “blinded” to the applied surface, leading to a Procrustean transfer. This is due to the mismatched interface between the as-fabricated sensors, with determinant form factors, and the target surfaces, with diverse, unique form factors that vary by user and with time. For instance, it may not be applicable to a nonplanar, dynamically morphing organ such as a lung. Moreover, fragile 3D constructs such as hydrogel materials can be disrupted during manual handling, transportation, and transplantation processes, which are susceptible to contamination. Also, manual transfer processes can result in operational inaccuracies and unpredictable human error. An alternative solution is in situ printing for seamlessly integrating the sensors on the target surface in an autonomous manner. To enable in situ printing, a new functionality is needed: a closed-loop artificial intelligence (AI) that can dynamically adapt the fabrication process by sensing the timevarying geometric states of the biological substrates in real time.

Here, we propose to model the space of deformation of the target surface using a shape basis model that can be learned from a dataset of 3D scans. With the learned shape model, accurate surface geometry can be recovered in 3D via a set of fiducial markers tracked by a stereo camera system.

Stretchable EIT sensors based on carbonelastomer composites as the conductive sensing materials have previously been developed to enable multidirectional strain mapping (3). Yet, the Young’s modulus of this composite is one order of magnitude larger than lung tissue (4).

EIT sensor (electrical impedance tomography)?

이런식으로 strain이 가해지면, 이런식으로 topological하게 나타나는 것이다. piezoelectrical한 뭔가가 있을거같다.

 

Procrustean transfer?

 

reference

1) Z. Zhu el al., "3D-printed deformable sensors," Science Advances (2020). DOI: 10.1126/sciadv.aba5575 , advances.sciencemag.org/content/6/25/eaba5575

2) Zhijie Zhu et al, 3D Printed Functional and Biological Materials on Moving Freeform Surfaces, Advanced Materials (2018). DOI: 10.1002/adma.201707495

3) H. Lee, D. Kwon, H. Cho, I. Park, J. Kim, Soft nanocomposite based multi-point, multi-directional strain mapping sensor using anisotropic electrical impedance tomography. Sci. Rep. 7, 39837 (2017).

4) S. R. Polio, A. N. Kundu, C. E. Dougan, N. P. Birch, D. E. Aurian-Blajeni, J. D. Schiffman, A. J. Crosby, S. R. Peyton, Cross-platform mechanical characterization of lung tissue. PLOS ONE 13, e0204765 (2018).