CN114280030B - Soft material viscoelasticity characterization method based on laser-induced breakdown spectroscopy - Google Patents
Soft material viscoelasticity characterization method based on laser-induced breakdown spectroscopy Download PDFInfo
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Abstract
The invention discloses a method for rapidly characterizing the viscoelasticity of a soft substance based on a laser-induced breakdown spectroscopy technology. After the calibration curve of the viscoelasticity parameter and the selected spectrum parameter of the soft substance is established, the invention can carry out in-situ on-line rapid detection on the soft substance to be detected, and the operation is convenient and rapid, and does not depend on the motion characteristics of particles in the soft substance to be detected. The defects of complex design, time consumption and direct contact with a substance to be measured of the traditional mechanical rheological measurement method are overcome.
Description
Technical Field
The invention relates to the field of soft material testing, in particular to a method for rapidly characterizing the viscoelasticity of a soft material based on a laser-induced breakdown spectroscopy technology.
Background
Soft substances are a special class of substances between solids and ideal fluids, which have wide application in modern production and life of humans. Soft materials are generally composed of macromolecules or groups such as polymers, colloids, foams, particulate materials, living system materials, etc. that are common in everyday life. The viscoelasticity is an important mechanical property of the soft material, and the development of the soft material viscoelasticity characterization method is convenient and quick, so that not only can the preparation and application problems of the soft material be solved in a boosting way, but also the progress of the basic research field of the soft material can be boosted.
Currently, conventional means for measuring the viscoelasticity of soft substances are based on mechanical rheometry methods, such as the wide variety of rheometers available on the market, the principle of which is to realize the characterization of the viscoelasticity by measuring the stresses externally applied to the medium and the deformations of the medium. The main disadvantages of the conventional mechanical rheometry method are the complex design, time-consuming, and the need for direct contact with the sample to be measured.
As an emerging substance component analysis technology, the Laser-induced breakdown spectroscopy (Laser-induced breakdown spectroscopy, LIBS for short) has the characteristics of no need of sample pretreatment, simultaneous multi-element analysis, rapid real-time and remote online analysis, and has wide application prospects in the fields of industrial process monitoring, geological exploration, food safety detection, environmental pollution monitoring and the like. LIBS analysis technology is to ablate the surface of a substance by using high-energy pulse laser to generate plasma, and quantitative analysis of chemical components of the substance is realized by measuring the emission spectrum of the plasma. However, the application of the laser-induced breakdown spectroscopy technology in the viscoelastic characterization of soft materials has not been reported.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a method for representing the viscoelasticity of a soft substance based on LIBS technology. The method can rapidly characterize the viscoelasticity of the soft substance in situ on line, does not need sampling and sample processing, does not directly contact the substance to be detected, and has no requirement on the internal movement of the substance.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the soft matter viscoelasticity characterization method based on the LIBS technology provided by the invention comprises the following steps:
first, preparing n soft matter sample groups with different viscoelasticity parameters, respectively marked as S 1 ,S 2 ,S 3 ……S n Forming a standard sample group;
secondly, irradiating the surface of each soft substance sample by adopting pulse laser in an LIBS system to generate plasma, and collecting a plasma emission spectrum of the corresponding sample;
thirdly, analyzing the acquired spectrum, and selecting a certain spectrum parameter as a calibration probe of the viscoelasticity corresponding to the group of samples, wherein the selected spectrum parameter has a one-to-one correspondence with the viscoelasticity;
fourth, constructing a viscoelastic parameter calibration curve corresponding to the group of soft substance samples based on the selected spectral parameters;
fifthly, collecting a laser plasma emission spectrum corresponding to the soft substance to be detected, and obtaining the spectrum parameter corresponding to the substance to be detected;
sixth, comparing the spectrum parameter corresponding to the substance to be measured with the calibration curve obtained in the fourth step to obtain the viscoelasticity parameter of the soft substance to be measured,
in the third step of the method, the spectrum parameter is defined as any parameter which is obtained by analysis from the acquired spectrum and can characterize the LIBS emission spectrum, such as the characteristic spectral line intensity or spectral line width corresponding to a certain element in the soft material, the intensity ratio of certain two characteristic spectral lines, the plasma temperature, the electron density and the like.
The soft matter viscoelastic characterization method based on the LIBS technology specifically comprises the following steps:
1) Preparing a group of n standard soft matter samples with different viscoelasticity, namely standard samples, wherein each standard sample is respectively marked as S 1 ,S 2 ,S 3 ……S n ；
2) Sequentially radiating the surface of each standard sample by LIBS equipment to generate plasmas, collecting and detecting the emitted light of the plasmas, and finally obtaining corresponding emission spectrums;
3) Selecting proper spectrum parameters from the spectrum corresponding to each standard sample, wherein the selected standard is that the spectrum parameters and the viscoelastic parameters corresponding to the standard samples have a one-to-one correspondence;
4) Drawing a calibration curve by taking the viscoelastic parameter value corresponding to each standard sample as a horizontal axis and the selected spectrum parameter value corresponding to each standard sample as a vertical axis;
5) Measuring the plasma emission spectrum of the soft substance to be measured based on the parameters of the equipment in the step 2), and further obtaining the spectrum parameter value corresponding to the step 3);
6) And (3) comparing the spectrum parameter value obtained in the step (5) with the calibration curve obtained in the step (4), and rapidly and quantitatively representing the viscoelastic parameter value corresponding to the soft substance to be detected.
In the above method step 1), the standard meaning is that, except for the viscoelastic properties, the two are different;
the soft matter may be a moving, stationary or quasi-stationary soft matter, which refers to a soft matter in which particles in the surface of the material do not have significant brownian motion, such as a stationary particulate packing material;
in step 2), the parameter settings of the device, including the laser parameters, the collection of emission spectrum and the detection parameters, are optimized and kept constant when detecting the substance to be detected;
in the step 3), the spectrum parameter is defined as any parameter which is obtained by analysis from the acquired spectrum and can characterize the LIBS emission spectrum, such as the characteristic spectral line intensity or spectral line width corresponding to the element contained in the soft material, the intensity ratio of two characteristic spectral lines, the plasma temperature, the electron density and the like;
taking the ratio of the intensities of two characteristic spectral lines of the same element and different upper energy levels as an example of the selected spectral parameters for illustration: firstly, extracting integral intensity of two selected characteristic spectral lines from the acquired spectrum, and then obtaining a two-spectral line intensity ratio R corresponding to each standard sample 1 ，R 2 ，R 3 ……R n The formula is as follows:
wherein R is n Represents the integral intensity ratio corresponding to the nth standard sample, I 1 And I 2 The emission intensities of the two characteristic spectral lines, C being constant (the magnitude of C being dependent on the wavelength corresponding to the selected spectral line, the probability of transition and the degeneracy of the corresponding energy level), K B Is Boltzmann constant, E 1 And E is 2 Respectively represent the upper energy level energy of two characteristic spectral lines, T exc Is the plasma temperature;
in step 4), the calibration curve constructs a one-to-one correspondence of the viscoelastic parameters and the spectral parameters of the set of soft matter standards.
The beneficial effects of the invention are as follows: the invention provides a soft substance viscoelasticity characterization method based on LIBS technology, which solves the defects of complex design, time consumption and direct contact with a substance to be measured in the traditional mechanical rheological measurement method. After the calibration curve of the viscoelasticity parameter and the selected spectrum parameter of the soft substance is established, the invention can carry out in-situ on-line rapid detection on the soft substance to be detected, and the operation is convenient and rapid, and does not depend on the motion characteristics of particles in the soft substance to be detected.
Drawings
FIG. 1 is a calibration curve of the void fraction (viscoelasticity) of particulate matter constructed with the intensity ratio of the two characteristic lines as spectral parameters in example 1, and the predictive effect on "unknown" samples.
FIG. 2 is a calibration curve of the porosity (viscoelasticity) of the particulate material constructed with the emission intensity of the characteristic spectral lines as spectral parameter in example 2, and the predictive effect on "unknown" samples.
FIG. 3 is a calibration curve of the porosity (viscoelasticity) of the particulate material constructed with the line width of the characteristic lines as spectral parameters in example 3, and the predictive effect on "unknown" samples.
Detailed Description
The following detailed description of the invention is provided in connection with the accompanying drawings that are presented to illustrate the invention and not to limit the scope thereof. The examples provided below are intended as guidelines for further modifications by one of ordinary skill in the art and are not to be construed as limiting the invention in any way.
The experimental methods in the following examples, unless otherwise specified, are conventional methods, and are carried out according to techniques or conditions described in the literature in the field or according to the product specifications. Materials, reagents and the like used in the examples described below are commercially available unless otherwise specified.
In an embodiment of the present invention, a method for in situ rapid characterization of soft matter viscoelasticity based on LIBS technology is provided. The method uses the emission spectral characteristics of a plasma generated by laser ablation of particulate matter to characterize the magnitude of the soft matter viscoelastic parameter. The method comprises the following steps:
first, preparing n soft matter samples with different viscoelastic parameters, respectively labeled S 1 ,S 2 ,S 3 ……S n Forming a standard sample group;
secondly, irradiating the surfaces of each group of soft substance samples by adopting pulse laser in an LIBS system to generate plasmas, and collecting plasma emission spectrums of the corresponding samples;
thirdly, analyzing the acquired spectrum, selecting a certain spectrum parameter as a calibration probe of the viscoelasticity corresponding to the group of samples, wherein the selected spectrum parameter has a one-to-one correspondence with the viscoelasticity. It should be emphasized that, the spectral parameters herein are defined as any parameter that can characterize the spectral characteristics of the LIBS emission obtained by analysis from the collected spectrum, such as the characteristic spectral line intensity or spectral line width corresponding to a certain element, the intensity ratio of certain two characteristic spectral lines, the plasma temperature or electron density, etc.;
fourth, constructing a viscoelastic parameter calibration curve corresponding to the group of soft substance samples based on the selected spectral parameters;
fifthly, collecting a laser plasma emission spectrum corresponding to the soft substance to be detected, and obtaining the spectrum parameter corresponding to the substance to be detected;
and sixthly, comparing the spectral parameters corresponding to the substance to be detected with the calibration curve obtained in the fourth step to obtain the viscoelasticity parameters of the soft substance to be detected.
The method specifically comprises the following steps:
1) Preparing a group of n standard soft matter samples with different viscoelasticity, namely standard samples, wherein each standard sample is respectively marked as S 1 ,S 2 ,S 3 ……S n The method comprises the steps of carrying out a first treatment on the surface of the The standard means that the chemical and physical properties of the samples are consistent, except for the difference in viscoelasticity;
2) Sequentially radiating the surface of each standard sample by LIBS equipment to generate plasmas, collecting and detecting the emitted light of the plasmas, and finally obtaining corresponding emission spectrums;
the parameter setting of the equipment in the step 2) comprises the laser parameter, the collection of the emission spectrum and the detection parameter, which are optimized and kept constant when detecting the substance to be detected;
3) Selecting proper spectrum parameters from the spectrum corresponding to each standard sample, wherein the selected standard is a one-to-one correspondence between the spectrum parameters and the viscoelastic parameters corresponding to the standard samples; taking the ratio of two characteristic spectral line intensities of different upper energy levels of the same element as an example of the selected spectral parameters, the following is exemplified: firstly, extracting integral intensity of two selected characteristic spectral lines from the acquired spectrum, and then obtaining two spectral line intensities corresponding to each standard sampleRatio R 1 ，R 2 ，R 3 ……R n The formula is as follows:
wherein R is n Represents the integral intensity ratio corresponding to the nth standard sample, I 1 And I 2 The emission intensity of two characteristic spectral lines respectively, C is a constant, K B Is Boltzmann constant, E 1 And E is 2 Respectively represent the upper energy level energy of two characteristic spectral lines, T exc Is the plasma temperature;
4) Drawing a calibration curve by taking the viscoelastic parameter value corresponding to each standard sample as a horizontal axis and the selected spectrum parameter value corresponding to each standard sample as a vertical axis;
the calibration curve constructs a one-to-one correspondence between the viscoelastic parameters and the spectral parameters of the set of soft material standard samples;
5) Measuring the plasma emission spectrum of the soft substance to be measured based on the parameters of the equipment in the step 2), and further obtaining the spectrum parameter value corresponding to the step 3);
6) And (3) comparing the spectrum parameter value obtained in the step (5) with the calibration curve obtained in the step (4), and rapidly and quantitatively representing the viscoelastic parameter value corresponding to the soft substance to be detected.
Example 1:
the present embodiments are merely exemplary and are not intended to limit the scope of the invention and its application. The viscoelastic characterization method of the soft substance is described by taking a soft substance formed by stacking copper ball microparticles as an example. This example uses the well-known knowledge that there is a one-to-one correspondence between the viscosity coefficient and elastic modulus of particulate matter and the porosity of particulate matter (see textbook, physical and mechanical of particulate matter, by Sun Jicheng et al 2011). Therefore, for simplicity of description, the void fraction of the particulate matter is employed in the present example to directly express the viscoelasticity of the particulate matter. The embodiment specifically comprises the following steps:
1) Diameter information of adopted copper ball microparticlesRest is d 50 ＝72μm,d 10 ＝59μm,d 90 =92 μm. Copper ball particles were naturally filled into 5 sample cartridges, respectively, with an initial filling height higher than the upper surface of the cartridge, and the internal dimensions of the cartridge were 70mm (length) ×70mm (width) ×9mm (height). Applying different vibration times to each sample, removing copper particles above the surface of the sample box by using a scraper to level the surface of the sample to obtain 5 standard soft material samples with different void ratios (namely different viscoelasticity), and recording as S 1 ,S 2 ,S 3 ,S 4 ,S 5 ；
2) Weighing each sample using a balance with a net mass M 1 ＝251.52g,M 2 ＝246.16g,M 3 ＝242.10g,M 4 ＝238.56g,M 5 = 234.59g; calculating the void ratio of each standard sample to be P 1 '＝36.3％,P 2 '＝37.7％,P 3 '＝38.7％,P 4 '＝39.6％,P 5 '＝40.6％。
3) Each standard sample was placed in sequence on a sample stage of the LIBS apparatus, the sample stage movement speed was set to 8mm/s, the laser pulse energy was set to 30mJ, the frequency was set to 1Hz, and the laser beam was focused onto the sample surface through a lens. The sample surface is placed at a position 10mm above the laser beam waist after focusing, the start time of an acquisition time gate of the plasma emission spectrum is 1 mu s relative to the laser pulse delay, and the gate width is set to be 2 mu s. Each group of samples collect LIBS spectra corresponding to 400 single laser pulses;
4) The 400 spectra corresponding to each sample are equally divided into eight groups (i.e., each group contains LIBS spectra corresponding to 50 single laser pulses); superposing and then averaging each group of LIBS spectra; selecting two characteristic spectral lines CuI 515.3nm and CuI 510.6nm emitted by neutral Cu atoms from the superimposed and averaged LIBS spectrum, and calculating the intensity ratio R of the two spectral lines and the corresponding standard deviation to obtain the corresponding ratio R of each group of samples 1 ＝1.99±,R 2 ＝1.95±,R 3 ＝1.91±,R 4 ＝1.87±,R 5 ＝1.75±；
5) In sample S n The corresponding void fraction P' of (n=1, 2,4, 5) is the abscissa, and the corresponding spectral line intensity ratio R n The calibration curves for both are established on the ordinate as shown in fig. 1. In the figure, single exponential fitting is used, and in different embodiments, multiple regression, single variable fitting, partial least square method, neural network or other methods can be used to establish the calibration curve.
6) Sample S 3 As an "unknown" sample, its corresponding porosity reference value P 3 ' 38.7% and line intensity ratio R 3 Also plotted in figure 1 is =1.91±. As can be seen by comparison, the result of the prediction of the void fraction of the "unknown" sample by using the calibration curve obtained in 5) matches the true value thereof within the error range.
Example 2:
in this embodiment, a calibration curve of void fraction is established by taking a certain characteristic spectral line intensity as a spectral parameter. On the basis of example 1, the ratio of the intensities of the two characteristic lines in step 4) is replaced by the intensity I of a certain characteristic line. The spectral line intensity corresponding to CuI 515.3nm is exemplified here as the selected spectral parameter. Firstly, the integrated intensity I of the CuI 515.3nm line corresponding to 5 groups of samples is extracted respectively 1 ，I 2 ，I 3 ，I 4 ，I 5 The method comprises the steps of carrying out a first treatment on the surface of the In sample S n The corresponding void fraction P' of (n=1, 2,4, 5) is the abscissa, and the corresponding line intensity ratio I n For the ordinate, a calibration curve was established for both, as shown in fig. 2. In the figure, single exponential fitting is used, and in different embodiments, multiple regression, single variable fitting, partial least square method, neural network or other methods can be used to establish the calibration curve. Sample S 3 As an "unknown" sample, its corresponding porosity reference value P 3 ' sum line intensity I 3 The values are also plotted in figure 2. By comparison, the predicted result of the void fraction of the "unknown" sample by using the calibration curve is matched with the true value thereof in the error range.
Example 3:
in the embodiment, a calibration curve of void fraction is established by taking the line width of a certain characteristic spectral line as a spectral parameter. On the basis of example 1, the ratio of the intensities of the two characteristic lines in step 4) is replaced by the line width W of a certain characteristic line. The line width corresponding to CuI 521.8nm is selectedThe specified spectral parameters are exemplified. Firstly, the full width at half maximum W of line width CuI of 521.8nm corresponding to 5 groups of samples is extracted respectively 1 ，W 2 ，W 3 ，W 4 ，W 5 The method comprises the steps of carrying out a first treatment on the surface of the In sample S n The corresponding void fraction P' of (n=1, 2,4, 5) is the abscissa, corresponding line width value W n For the ordinate, a calibration curve was established for both, as shown in fig. 3. In the figure, single exponential fitting is used, and in different embodiments, a calibration curve can be established by using methods such as multiple regression, single variable fitting, partial least square method or neural network; sample S 3 As an "unknown" sample, its corresponding porosity reference value P 3 ' sum spectral line width W 3 The values are also plotted in figure 3. By comparison, the predicted result of the void fraction of the "unknown" sample by using the calibration curve is matched with the true value thereof in the error range.
The spectral parameters shown in the above examples are all able to establish a calibration curve of void fraction (i.e. soft material viscoelastic parameter), and some other defined spectral parameters are also able to establish a one-to-one correspondence therewith, which is not shown here by way of example. It should be noted that any case that uses the emission spectrum characteristics of the plasma generated by the LIBS technology to characterize the viscoelasticity of the soft material is included in the scope of the patent claims.
The present invention is described in detail above. It will be apparent to those skilled in the art that the present invention can be practiced in a wide range of equivalent parameters, concentrations, and conditions without departing from the spirit and scope of the invention and without undue experimentation. While the invention has been described with respect to specific embodiments, it will be appreciated that the invention may be further modified. In general, this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. The application of some of the basic features may be done in accordance with the scope of the claims that follow.
Claims (8)
1. A soft matter viscoelasticity characterization method based on LIBS technology comprises the following steps:
first, preparing n soft matter samples with different viscoelastic parameters, respectively labeled S 1 ,S 2 ,S 3 ……S n Forming a standard sample group;
secondly, irradiating the surface of each soft substance sample by adopting pulse laser in an LIBS system to generate plasma, and collecting a plasma emission spectrum of the corresponding sample;
thirdly, analyzing the acquired spectrum, and selecting a certain spectrum parameter as a calibration probe of the viscoelasticity corresponding to the group of samples, wherein the selected spectrum parameter has a one-to-one correspondence with the viscoelasticity;
fourth, constructing a viscoelastic parameter calibration curve corresponding to the group of soft substance samples based on the selected spectral parameters;
fifthly, collecting a laser plasma emission spectrum corresponding to the soft substance to be detected, and obtaining the spectrum parameter corresponding to the substance to be detected;
and sixthly, comparing the spectral parameters corresponding to the substance to be detected with the calibration curve obtained in the fourth step to obtain the viscoelasticity parameters of the soft substance to be detected.
2. The method according to claim 1, characterized in that: in the third step, the spectral parameter is any parameter which is obtained by analysis from the acquired spectrum and can characterize the LIBS emission spectrum.
3. The method according to claim 2, characterized in that: the spectral parameters are parameters which are extracted from LIBS emission spectra corresponding to the elements contained in the collected soft substances and can characterize spectral features.
4. A method according to any one of claims 1-3, characterized in that: the method comprises the following steps:
1) Preparing a group of n standard soft matter samples with different viscoelasticity, namely standard samples, wherein each standard sample is respectively marked as S 1 ,S 2 ,S 3 ……S n ；
2) Sequentially irradiating the surface of each standard sample by LIBS equipment to generate plasmas, collecting and detecting the emitted light of the plasmas, and finally obtaining corresponding emission spectrums;
3) Selecting proper spectrum parameters from the spectrum corresponding to each standard sample, wherein the selected standard is that the spectrum parameters and the viscoelastic parameters corresponding to the standard samples have a one-to-one correspondence;
4) Drawing a calibration curve by taking the viscoelastic parameter value corresponding to each standard sample as a horizontal axis and the selected spectrum parameter value corresponding to each standard sample as a vertical axis;
5) Measuring the plasma emission spectrum of the soft substance to be measured based on the parameters of the equipment in the step 2), and further obtaining the spectrum parameter value corresponding to the step 3);
6) And (3) comparing the spectrum parameter value obtained in the step (5) with the calibration curve obtained in the step (4), and rapidly and quantitatively representing the viscoelasticity parameter value of the soft substance to be detected.
5. The method according to claim 4, wherein: in step 2), the parameter settings of the device, including the laser parameters, the collection of the emission spectrum and the detection parameters, are optimized and kept constant when detecting the substance to be detected.
6. The method according to claim 4 or 5, characterized in that: in step 3), the spectral parameter is any one of parameters which can be characterized by spectral characteristics and are analyzed from the acquired LIBS spectrum.
7. The method according to any one of claims 4-6, wherein: in step 3), taking the ratio of the intensities of two characteristic spectral lines of the same element and different upper energy levels as the selected spectral parameter as an example: firstly, extracting the intensity of two selected characteristic spectral lines from the acquired spectrum, and then obtaining the corresponding two-spectral-line intensity ratio R of each standard sample 1 ，R 2 ，R 3 ……R n The formula is as follows:
wherein R is n Represents the integral intensity ratio corresponding to the nth standard sample, I 1 And I 2 The emission intensity of two characteristic spectral lines respectively, C is a constant, K B Is Boltzmann constant, E 1 And E is 2 Respectively represent the upper energy level energy of two characteristic spectral lines, T exc Is the plasma temperature.
8. The method according to any one of claims 4-7, characterized in that: in step 4), the calibration curve constructs a one-to-one correspondence of the viscoelastic parameters and the spectral parameters of the set of soft matter standards.
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| JPH05256754A (en) * | 1992-03-13 | 1993-10-05 | Res Dev Corp Of Japan | Apparatus for measuring viscoelasticity of liquid crystal |
| JP2005098893A (en) * | 2003-09-25 | 2005-04-14 | Kajima Corp | Method and apparatus for measuring strength of cured object |
| WO2006110963A1 (en) * | 2005-04-21 | 2006-10-26 | K.U.Leuven Research And Development | Monitoring of the v1sco-elastic properties of gels and liquids |
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| US9494475B2 (en) * | 2010-09-26 | 2016-11-15 | Val-Chum, Limited Partnership | Apparatus, system and method for dynamically measuring material viscoelasticity using shear wave induced resonance |
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| JPH05256754A (en) * | 1992-03-13 | 1993-10-05 | Res Dev Corp Of Japan | Apparatus for measuring viscoelasticity of liquid crystal |
| JP2005098893A (en) * | 2003-09-25 | 2005-04-14 | Kajima Corp | Method and apparatus for measuring strength of cured object |
| WO2006110963A1 (en) * | 2005-04-21 | 2006-10-26 | K.U.Leuven Research And Development | Monitoring of the v1sco-elastic properties of gels and liquids |
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