@Article{icces.2022.08829,
AUTHOR = {Jingyu Wang, Yongrou Zhang, Zuyue Lei, Junqi Wang, Yangming Zhao, Taolin Sun, Zhenyu Jiang, Licheng Zhou, Zejia Liu, Yiping Liu, Bao Yang, Liqun Tang},
TITLE = {Hydrogels with Brain	Tissue-Like Mechanical	Properties	in	Complex	 Environments},
JOURNAL = {The International Conference on Computational \& Experimental Engineering and Sciences},
VOLUME = {25},
YEAR = {2023},
NUMBER = {4},
PAGES = {1--1},
URL = {http://www.techscience.com/icces/v25n4/53864},
ISSN = {1933-2815},
ABSTRACT = {In	surgical	training	applications	and	experimental	research,	brain	tissues	immersed	in	cerebrospinal	fluid	
often	involve	very	complex	deformation	and	strain	rate	effects,	which	affects	their	reliability	and	stability.	
Thus,	 it	 is	 indispensable	 to	 develop	 a	 high-fidelity	 human	 brain	 tissue	 simulant	 material	 as	 a	 physical	
surrogate	model	to	understand	their	mechanical	behavior,	such	as	traumatic	brain	injury	(TBI).	However,	
the	reported	simulant	materials	have	not	yet	been	able	to	compare	and	satisfy	the	above	two	mechanical	
properties.	Here,	we	developed	a	novel	composite	hydrogel	with	brain	tissue-like	mechanical	properties	and	
investigated	 their	 mechanical	 behavior	 in	 a	 solution	 environment.	 The	 results	 demonstrate	 that	 this	
composite	 hydrogel	 shows	 some	 common	 features	 with	 fresh	 porcine	 brain	 tissue,	 such	 as	 nonlinear	
mechanical	behavior	and	a	good	similarity	under	various	external	environments	(artificial	cerebrospinal	
fluid,	saline	solution,	deionized	water,	and	air	environments)	and	strain	rates	(0.001s-1,900s-1,1700s-1).	
Furthermore,	using	a	life-sized	brain	tissue	mold,	we	successfully	constructed	a	3D brain-like tissue	model	
based	on	this	composite	hydrogel,	which	validates	the	feasibility	of	surgical	training	on	this	model.	Since	the	
properties	of	human	brain	tissue	are	similar	to	those	of	porcine	brain	tissue,	our	work	will	have	important	
reference	value	for	the	realization	of	surgical	training	and	related	research	in	biomedical	engineering.},
DOI = {10.32604/icces.2022.08829}
}