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Article source: Gaochao Research Group? Research background Aerogel is the lightest type of substance in the world.
It is named because it has many pores and is full of air
.
Graphene aerogel (also known as graphene foam, graphene sponge, etc.
) is an ultra-light porous material assembled from two-dimensional graphene sheets.
It is used in smart sensing, energy storage, adsorption, heat insulation and sound insulation, etc.
Various fields have shown great application potential
.
? At present, whether it is the template method or the "sol-gel" method, the obtained graphene aerogel is derived from the dilute solution of the graphene precursor, and the assembly structure has poor mechanical stability and is difficult to withstand complex deformation; at the same time, The complex freeze-drying process limits its large-scale continuous and high-precision miniaturization preparation, which is not conducive to its large-scale application
.
? In contrast, the common polymer foam technology in life is simple and can be directly obtained from solid polymer through thermoplastic foaming, and the prepared foam has excellent mechanical stability, among which thermoplasticity is the polymer foaming and maintaining excellent A prerequisite for mechanical stability
.
However, for graphene, its melting temperature is high and it is difficult to meet the requirements of thermoplasticity.
Therefore, how to achieve solid-state foaming of graphene materials is still a huge challenge
.
? The team of Professor Chao Chao (Common Communication), Researcher Xu Zhen (Common Communication), and Associate Researcher Liu Yingjun (Common Communication) of the Department of Polymer Science of Zhejiang University revealed the lyoplasticity of two-dimensional graphene oxide sheets and proposed the "lyoplasticization" The "foaming" method realizes the large-scale continuous and high-precision miniaturized preparation of graphene aerogels, which is comparable to the "thermoplastic foaming" preparation method of polymer foam
.
At the same time, the "melt foamed" graphene aerogel has the same excellent mechanical stability as the polymer foam
.
The team cooperated with researcher Peng Yuxin of the Department of Physical Education of Zhejiang University (joint communication) to develop an ultra-sensitive graphene aerogel microarray tactile sensor.
Through artificial intelligence algorithms, the graphene aerogel finger sensor exhibits tactile sensitivity beyond human hands.
.
Related results were published in Science Advances (Sci.
Adv.
2020; 6: eabd4045) under the title "Hydroplastic foaming of graphene aerogels and artificially intelligent tactile sensors"
.
The first author of the paper is Pang Kai, a PhD student from a superb team
.
This paper was funded by the National Key Research and Development Program, the National Natural Science Foundation of China, and the Hundred Talents Program of Zhejiang University
.
? Work highlights (1) proposed the method of lyoplastic foaming
.
Reveal the lyoplasticity of two-dimensional graphene oxide, realize the continuous and large-scale foaming of solid graphene oxide film to prepare aerogels, and provide new principles and new methods for the preparation of other nano-material aerogels; and Through the classical bubble nucleation and growth law, precise control of the aerogel wall thickness and pore size can be achieved, laying a foundation for the industrial application of aerogels
.
? (2) The resulting graphene aerogel has excellent mechanical stability
.
Benefit from the joint effect of lyotropic plasticization and bubble tension, it greatly eliminates the lap defects in the aerogel, realizes the tight bonding of graphene, and gives the aerogel excellent mechanical stability, which can withstand the actual environment The complex deformation
.
? (3) Developed an ultra-sensitive graphene aerogel microarray tactile sensor
.
The printed microarray sensor can reach the smallest micron level, combined with deep machine learning, to achieve accurate recognition of material types and surface letters, with an accuracy rate of more than 80%, which is far beyond the tactile sensitivity of human hands (human hands accuracy rate ~ 30%)
.
? Graphical guide Figure 1.
Preparation and mechanism of lyoplastic foamed graphene aerogel
.
(A) The process of lyotropic plasticization and foaming
.
(B) The insertion of water molecules in graphene oxide realizes lamellar plasticization
.
(C) With the nucleation and growth of bubbles, the graphene oxide sheet slowly undergoes plasticization and slippage deformation until it is stable
.
(D) Form tightly overlapping hyperboloid graphene aerogel
.
(E) Scanning topography and bubble structure model of graphene aerogel
.
? Video 1.
The foaming process of graphene oxide film
.
? Figure 2.
Bubble nucleation and growth and structure control
.
(A) Observed in situ by an optical microscope the changes in bubble size with bubble nucleation density (foaming agent concentration) and bubble growth time during the lyoplastic foaming process
.
(B) The topography and schematic diagram of the bubble during the nucleation and growth process
.
(C) The relationship between bubble nucleation density (Nn) and graphene aerogel wall thickness (T) accords with the relationship T=33Nn-1.
0
.
(D) A schematic diagram of the wall thickness decreasing as the bubble nucleation density increases
.
(E) The bubble growth time (t) and the density (ρ) of the obtained aerogel conform to the relationship between ρ=13.
3t-0.
2, and the density is mainly determined by the aerogel pore size
.
? Video 2.
Use the ultra-thin graphene oxide film to observe the in-situ foaming process under an optical microscope
.
? Figure 3.
Mechanical stability of lyoplastic foamed graphene aerogel
.
(A) The large graphene aerogel was repeatedly folded and compressed into a slender elbow.
The aerogel structure was not damaged and no obvious debris fell off
.
(B) Compressive stress-strain curve of graphene aerogel after 105 cycles under 90% strain
.
(C) Literature comparison of graphene aerogel compression cycle performance
.
(DG) Comparison of mechanical curves of stretching, shearing, bending and tearing processes
.
? Video 3.
Graphene aerogel repeatedly folds through thin tubes
.
? Figure 4.
High-sensitivity graphene aerogel
.
(A) The structure and scanning diagram of the graphene aerogel sensor prepared by direct writing and foaming
.
(B) The piezoresistance change curve of the sensor
.
(C) Piezoresistive fatigue stability of the sensor
.
(D) Comparison of prepared sensor with literature
.
(E) Fix the sensor on the manipulator to identify different carbon aerogel densities
.
(F) Using the compression distance of the manipulator relative to the carbon aerogel and the change in resistance as the signal input, combined with the Gaussian kernel algorithm, the density determination is realized
.
? Figure 5.
Artificial intelligence microarray sensor for graphene aerogel
.
(A) Cover the palm of the hand on a 10x10 graphene aerogel array sensor (single size 0.
5x0.
7mm), and get the pressure distribution of (B) the palm
.
(C) An 8x8 microarray sensor, where a single size is about 300 microns
.
(D) Fix the robot arm with the microarray sensor on the robot arm and touch the letter pattern continuously to recognize the letter
.
(E) Artificial intelligence recognition mainly includes: data collection, image conversion and deep machine learning
.
The training data set in the machine learning process is a public data set
.
(F) The collected letter signal diagram
.
(G) Comparison of the recognition accuracy of letters between artificial intelligence fingers and human fingers
.
(H) Using the collected letter signals for training and learning, a 100% letter recognition rate can be achieved
.
This article provides a rapid and efficient method for preparing ultra-light and mechanically stable graphene aerogels by lyoplastic foaming.
The mechanism has been studied in depth, and the design and microstructure of aerogels have been solved.
The control problem has realized the large-scale preparation of graphene aerogels and the demonstration of AI applications, and at the same time provides a new universal solution for aerogel assembly of other nanomaterials (such as nanocellulose, etc.
)
.
This work was completed on the basis of the previous accumulation of the team of super professors and previous experience summaries (Advanced Materials 2013, 25, 2554; 2017, 29, 1701482; Nature Communications 2018, 9, 881)
.
It is named because it has many pores and is full of air
.
Graphene aerogel (also known as graphene foam, graphene sponge, etc.
) is an ultra-light porous material assembled from two-dimensional graphene sheets.
It is used in smart sensing, energy storage, adsorption, heat insulation and sound insulation, etc.
Various fields have shown great application potential
.
? At present, whether it is the template method or the "sol-gel" method, the obtained graphene aerogel is derived from the dilute solution of the graphene precursor, and the assembly structure has poor mechanical stability and is difficult to withstand complex deformation; at the same time, The complex freeze-drying process limits its large-scale continuous and high-precision miniaturization preparation, which is not conducive to its large-scale application
.
? In contrast, the common polymer foam technology in life is simple and can be directly obtained from solid polymer through thermoplastic foaming, and the prepared foam has excellent mechanical stability, among which thermoplasticity is the polymer foaming and maintaining excellent A prerequisite for mechanical stability
.
However, for graphene, its melting temperature is high and it is difficult to meet the requirements of thermoplasticity.
Therefore, how to achieve solid-state foaming of graphene materials is still a huge challenge
.
? The team of Professor Chao Chao (Common Communication), Researcher Xu Zhen (Common Communication), and Associate Researcher Liu Yingjun (Common Communication) of the Department of Polymer Science of Zhejiang University revealed the lyoplasticity of two-dimensional graphene oxide sheets and proposed the "lyoplasticization" The "foaming" method realizes the large-scale continuous and high-precision miniaturized preparation of graphene aerogels, which is comparable to the "thermoplastic foaming" preparation method of polymer foam
.
At the same time, the "melt foamed" graphene aerogel has the same excellent mechanical stability as the polymer foam
.
The team cooperated with researcher Peng Yuxin of the Department of Physical Education of Zhejiang University (joint communication) to develop an ultra-sensitive graphene aerogel microarray tactile sensor.
Through artificial intelligence algorithms, the graphene aerogel finger sensor exhibits tactile sensitivity beyond human hands.
.
Related results were published in Science Advances (Sci.
Adv.
2020; 6: eabd4045) under the title "Hydroplastic foaming of graphene aerogels and artificially intelligent tactile sensors"
.
The first author of the paper is Pang Kai, a PhD student from a superb team
.
This paper was funded by the National Key Research and Development Program, the National Natural Science Foundation of China, and the Hundred Talents Program of Zhejiang University
.
? Work highlights (1) proposed the method of lyoplastic foaming
.
Reveal the lyoplasticity of two-dimensional graphene oxide, realize the continuous and large-scale foaming of solid graphene oxide film to prepare aerogels, and provide new principles and new methods for the preparation of other nano-material aerogels; and Through the classical bubble nucleation and growth law, precise control of the aerogel wall thickness and pore size can be achieved, laying a foundation for the industrial application of aerogels
.
? (2) The resulting graphene aerogel has excellent mechanical stability
.
Benefit from the joint effect of lyotropic plasticization and bubble tension, it greatly eliminates the lap defects in the aerogel, realizes the tight bonding of graphene, and gives the aerogel excellent mechanical stability, which can withstand the actual environment The complex deformation
.
? (3) Developed an ultra-sensitive graphene aerogel microarray tactile sensor
.
The printed microarray sensor can reach the smallest micron level, combined with deep machine learning, to achieve accurate recognition of material types and surface letters, with an accuracy rate of more than 80%, which is far beyond the tactile sensitivity of human hands (human hands accuracy rate ~ 30%)
.
? Graphical guide Figure 1.
Preparation and mechanism of lyoplastic foamed graphene aerogel
.
(A) The process of lyotropic plasticization and foaming
.
(B) The insertion of water molecules in graphene oxide realizes lamellar plasticization
.
(C) With the nucleation and growth of bubbles, the graphene oxide sheet slowly undergoes plasticization and slippage deformation until it is stable
.
(D) Form tightly overlapping hyperboloid graphene aerogel
.
(E) Scanning topography and bubble structure model of graphene aerogel
.
? Video 1.
The foaming process of graphene oxide film
.
? Figure 2.
Bubble nucleation and growth and structure control
.
(A) Observed in situ by an optical microscope the changes in bubble size with bubble nucleation density (foaming agent concentration) and bubble growth time during the lyoplastic foaming process
.
(B) The topography and schematic diagram of the bubble during the nucleation and growth process
.
(C) The relationship between bubble nucleation density (Nn) and graphene aerogel wall thickness (T) accords with the relationship T=33Nn-1.
0
.
(D) A schematic diagram of the wall thickness decreasing as the bubble nucleation density increases
.
(E) The bubble growth time (t) and the density (ρ) of the obtained aerogel conform to the relationship between ρ=13.
3t-0.
2, and the density is mainly determined by the aerogel pore size
.
? Video 2.
Use the ultra-thin graphene oxide film to observe the in-situ foaming process under an optical microscope
.
? Figure 3.
Mechanical stability of lyoplastic foamed graphene aerogel
.
(A) The large graphene aerogel was repeatedly folded and compressed into a slender elbow.
The aerogel structure was not damaged and no obvious debris fell off
.
(B) Compressive stress-strain curve of graphene aerogel after 105 cycles under 90% strain
.
(C) Literature comparison of graphene aerogel compression cycle performance
.
(DG) Comparison of mechanical curves of stretching, shearing, bending and tearing processes
.
? Video 3.
Graphene aerogel repeatedly folds through thin tubes
.
? Figure 4.
High-sensitivity graphene aerogel
.
(A) The structure and scanning diagram of the graphene aerogel sensor prepared by direct writing and foaming
.
(B) The piezoresistance change curve of the sensor
.
(C) Piezoresistive fatigue stability of the sensor
.
(D) Comparison of prepared sensor with literature
.
(E) Fix the sensor on the manipulator to identify different carbon aerogel densities
.
(F) Using the compression distance of the manipulator relative to the carbon aerogel and the change in resistance as the signal input, combined with the Gaussian kernel algorithm, the density determination is realized
.
? Figure 5.
Artificial intelligence microarray sensor for graphene aerogel
.
(A) Cover the palm of the hand on a 10x10 graphene aerogel array sensor (single size 0.
5x0.
7mm), and get the pressure distribution of (B) the palm
.
(C) An 8x8 microarray sensor, where a single size is about 300 microns
.
(D) Fix the robot arm with the microarray sensor on the robot arm and touch the letter pattern continuously to recognize the letter
.
(E) Artificial intelligence recognition mainly includes: data collection, image conversion and deep machine learning
.
The training data set in the machine learning process is a public data set
.
(F) The collected letter signal diagram
.
(G) Comparison of the recognition accuracy of letters between artificial intelligence fingers and human fingers
.
(H) Using the collected letter signals for training and learning, a 100% letter recognition rate can be achieved
.
This article provides a rapid and efficient method for preparing ultra-light and mechanically stable graphene aerogels by lyoplastic foaming.
The mechanism has been studied in depth, and the design and microstructure of aerogels have been solved.
The control problem has realized the large-scale preparation of graphene aerogels and the demonstration of AI applications, and at the same time provides a new universal solution for aerogel assembly of other nanomaterials (such as nanocellulose, etc.
)
.
This work was completed on the basis of the previous accumulation of the team of super professors and previous experience summaries (Advanced Materials 2013, 25, 2554; 2017, 29, 1701482; Nature Communications 2018, 9, 881)
.
