CN114235774A - SF-AAO-Au plasma sensor performance evaluation method - Google Patents
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Abstract
The invention discloses a performance evaluation method of an SF-AAO-Au plasma sensor, which comprises the steps of firstly, SERS activity and flexibility testing, secondly, judging the uniformity by using a Raman mapping test result, thirdly, calculating the relative standard deviation and comparing by using a characteristic peak in the Raman test result, and fourthly, calculating and evaluating the standard uncertainty on-line performance; the method for uniformly testing and evaluating the sensitivity, flexibility, reproducibility and uniformity of the plasma sensor by using the probe molecule R6G has the capability of being applied to field detection of the plasma sensor, can be used for trace and quantitative detection, and is worthy of popularization as a uniform detection and evaluation standard of the performance of a novel plasma sensor.
Description
Technical Field
The invention relates to the technical field of sensor performance evaluation, in particular to a SF-AAO-Au plasma sensor performance evaluation method.
Background
The flexible substrate can wrap a complex surface to carry out SERS detection, has good mechanical tolerance and can be randomly cut into any size and shape, and the SERS has high sensitivity, so that the molecules of a monomolecular layer and a submonomolecular layer adsorbed on the metal surface can be detected, and the structural information of the surface molecules can be provided, so that the flexible substrate is considered to be a good surface research technology;
the performance of the produced novel plasma sensor cannot be uniformly detected and evaluated in the field of plasma sensor preparation due to the fact that the existing method for detecting and evaluating the performance of the plasma sensor is not uniform, and a uniform evaluation standard is lacked, so that the invention provides the method for evaluating the performance of the SF-AAO-Au plasma sensor to solve the problems in the prior art.
Disclosure of Invention
In view of the above problems, the present invention is directed to a method for evaluating performance of an SF-AAO-Au plasma sensor, in which probe molecules R6G are used to perform a unified test and evaluation on sensitivity, flexibility, reproducibility, and uniformity of a plasma sensor device, and the method has the capability of being applied to on-site detection of the plasma sensor device, can perform trace and quantitative detection, and is worth popularizing as a unified detection and evaluation standard for performance of a novel plasma sensor device.
In order to realize the purpose of the invention, the invention is realized by the following technical scheme: a SF-AAO-Au plasma sensor performance evaluation method comprises the following steps:
firstly, testing SERS activity and flexibility, namely dripping probe molecules R6G on the surface of a plasma sensor device for pretreatment, and then taking the treated plasma sensor device to test SERS enhanced signals under different curvatures and different rotation modes;
step two, uniformity testing, namely performing Raman mapping testing on the plasma sensing device processed in the step one, and selecting three characteristic peaks of probe molecules R6G to judge the uniformity of the plasma sensing device;
step three, reproducibility test, namely taking one characteristic peak in the Raman mapping test result in the step two, calculating the relative standard deviation of the intensity of the characteristic peak by using the following formula, and comparing the intensity with an international specified value
Wherein RSD is relative standard deviation, SD is standard deviation,
represents the mean value of the measurements;
and fourthly, performing on-line performance calculation and evaluation on the standard uncertainty, predicting the time sequence output by the plasma sensor in the ith period based on wavelet filtering and a neural network, and calculating the standard uncertainty by using a maximum error method.
The further improvement lies in that: the specific pretreatment method in the step one is to take probe molecules 10-5M R6G liquid transfer gun is used to make the liquid drop size of 0.5 × 0.5cm2The dropping amount of the surface of the plasma sensing device is 10 mu L/time, and the dropping is carried out for three times, wherein after the probe molecules are dropped each time, the next dropping can be carried out only after the surface of the plasma sensing device is completely dried.
The further improvement lies in that: when SERS enhanced signals under different bending angles are tested in the first step, the plasma sensing device is bent by 10 degrees, 45 degrees and 80 degrees respectively, and 5 different points are selected under each bending angle for carrying out Raman testing.
The further improvement lies in that: respectively stretching and twisting the plasma sensing device when SERS enhanced signals in different rotation modes are tested in the first step, and selecting 5 different points to perform Raman test under the condition of 120% stretching; the raman test was performed by selecting 5 different points with a 90 ° twist.
The further improvement lies in that: in the second step, Raman mapping is carried outTest at 20X 20 μm2And in the third step, 50 points in one characteristic peak in the three characteristic peaks in the second step are selected for calculating the relative standard deviation.
The further improvement lies in that: the specific steps of the step four middle prediction are
1) Filtering, wherein a plurality of data points are collected in the ith period to form a sampling data sequence, then wavelet transformation and filtering are carried out on the data sequence, and the average value of the middle 4 digits of the reconstructed signal is taken as filtering output;
2) and (3) neural network online prediction, wherein the first m sampling values obtained by filtering the actual output of the plasma sensing device are used as the output prediction of the network in the ith period.
The further improvement lies in that: the standard uncertainty calculation method in the fourth step comprises the steps of taking the predicted value of the time sequence in the ith period as a true value, comparing the true value with the actual output value of the plasma sensing device to obtain a residual error, and calculating the standard uncertainty s value measured once in the (i + 1) th period by using the following formula
Wherein deltaiIn order to be the value of the residual error,
is a coefficient related to the number of times of measurement, n is 1 when in online measurement,
the invention has the beneficial effects that: the method for uniformly testing and evaluating the sensitivity, flexibility, reproducibility and uniformity of the plasma sensor by using the probe molecule R6G has the capability of being applied to field detection of the plasma sensor, can be used for trace and quantitative detection, and is worthy of popularization as a uniform detection and evaluation standard of the performance of a novel plasma sensor.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of the evaluation of the present invention.
FIG. 2 is a graph showing the calculation results of relative standard deviations in example 2 of the present invention.
FIG. 3 is a schematic diagram of the AAO template structure and the flexible AAO preparation process of the present invention.
FIG. 4 shows the SEM images of SF, SF-AAO, and SF-AAO-Au according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," "third," "fourth," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Example 1
According to fig. 1, 3 and 4, the embodiment provides a method for evaluating the performance of an SF-AAO-Au plasma sensor, which comprises the following steps:
step one, SERS activity and flexibility test, taking probe molecules 10 firstly-5M R6G liquid transfer gun is used to make the liquid drop size of 0.5 × 0.5cm2The dropping amount of the surface of the plasma sensor is 10 mu L/time, the surface of the plasma sensor is pretreated by dropping for three times, wherein after probe molecules are dropped each time, the next dropping can be carried out only after the surface of the plasma sensor is completely dried, then when the treated plasma sensor is used for testing SERS enhanced signals under different curvatures, the plasma sensor is respectively bent at 10 degrees, 45 degrees and 80 degrees, 5 different points are selected at the bending surface of each bending angle for carrying out Raman testing, when the SERS enhanced signals under different rotation modes are tested, the plasma sensor is respectively stretched and twisted, and when the SERS enhanced signals under the condition of stretching 120 percent, 5 different points are selected for carrying out Raman testing; selecting 5 different points to perform Raman test under the condition of 90-degree torsion, wherein the Raman laser in the Raman test is 633nm, and the test result chart is shown in the figure;
step two, uniformity test, namely performing Raman mapping test on the plasma sensing device processed in the step one, wherein the test is performed at 20 multiplied by 20 mu m2The method is carried out within the range, and three characteristic peaks of the probe molecule R6G are selected to judge the uniformity of the plasma sensing device;
step three, reproducibility test, namely taking 50 points in one characteristic peak in the Raman mapping test result in the step two, calculating the relative standard deviation of the intensity of the characteristic peak by using the following formula, and comparing the intensity with an international specified value
Wherein RSD is relative standard deviation, SD is standard deviation,
represents the mean value of the measurements;
fourthly, standard uncertainty online performance calculation and evaluation, and predicting the time sequence in the ith period output by the plasma sensor based on wavelet filtering and a neural network, wherein the specific step of prediction is
1) Filtering, wherein a plurality of data points are collected in the ith period to form a sampling data sequence, then wavelet transformation and filtering are carried out on the data sequence, and the average value of the middle 4 digits of the reconstructed signal is taken as filtering output;
2) and (3) neural network online prediction, wherein the first m sampling values obtained by filtering the actual output of the plasma sensing device are used as the output prediction of the network in the ith period.
Calculating by using a maximum error method, taking a predicted value of the time sequence in the ith period as a true value, comparing the true value with an actual output value of the plasma sensing device to obtain a residual error, and calculating a standard uncertainty s value of single measurement in the (i + 1) th period by using the following formula
Wherein deltaiIn order to be the value of the residual error,
is a coefficient related to the number of times of measurement, n is 1 when in online measurement,
example 2
According to fig. 1, 2, 3 and 4, the embodiment provides a method for evaluating the performance of an SF-AAO-Au plasma sensor, which comprises the following steps:
step one, SERS activity and flexibility test, taking probe molecules 10 firstly-5M R6G liquid transfer gun is used to make the liquid drop size of 0.5 × 0.5cm2The dropping amount of the surface of the plasma sensing device is 10 mu L/time, the surface of the plasma sensing device is pretreated by dropping for three times, wherein after the probe molecules are dropped each time, the next dropping can be carried out until the surface of the plasma sensing device is completely dried, and then the treated plasma sensing device is takenWhen the sensor device tests SERS enhanced signals under different curvatures, the plasma sensor device is respectively bent by 10 degrees, 45 degrees and 80 degrees, 5 different points are selected at the bending surface of each bending angle for carrying out Raman test, when the SERS enhanced signals under different rotation modes are tested, the plasma sensor device is respectively stretched and twisted, and 5 different points are selected for carrying out Raman test under the condition of stretching by 120%; selecting 5 different points to carry out Raman test under the condition of 90-degree torsion;
step two, uniformity test, namely performing Raman mapping test on the plasma sensing device processed in the step one, wherein the test is performed within the range of 20 multiplied by 20 microns 2 and 121 points in total, and 774cm of probe molecules R6G are selected-1、1358cm-1And 1504cm-1The three characteristic peaks judge the uniformity of the plasma sensor;
step three, repeatability testing, namely 1358cm in the Raman mapping test result in the step two-150 points in 121 characteristic peaks have high overlapping degree of Raman spectra and show higher reproducibility, and 1358cm of the 50 points is determined by the following formula-1Calculating relative standard deviation of intensity at characteristic peak, and comparing with international specified value
Wherein RSD is relative standard deviation, SD is standard deviation,
the precision of the result which can be analyzed in the checking and detecting work of the relative standard deviation is shown as the measurement average value, and the calculation result is 7.6 percent after the relevant mathematical calculation<12% is internationally specified with reproducibility), as shown in the drawings of the specification;
fourthly, standard uncertainty online performance calculation and evaluation, and predicting the time sequence in the ith period output by the plasma sensor based on wavelet filtering and a neural network, wherein the specific step of prediction is
1) Filtering, wherein a plurality of data points are collected in the ith period to form a sampling data sequence, then wavelet transformation and filtering are carried out on the data sequence, and the average value of the middle 4 digits of the reconstructed signal is taken as filtering output;
2) and (3) neural network online prediction, wherein the first m sampling values obtained by filtering the actual output of the plasma sensing device are used as the output prediction of the network in the ith period.
Calculating by using a maximum error method, taking a predicted value of the time sequence in the ith period as a true value, comparing the true value with an actual output value of the plasma sensing device to obtain a residual error, and calculating a standard uncertainty s value of single measurement in the (i + 1) th period by using the following formula
Wherein deltaiIn order to be the value of the residual error,
is a coefficient related to the number of times of measurement, n is 1 when in online measurement,
the foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (7)
1. A SF-AAO-Au plasma sensor performance evaluation method is characterized by comprising the following steps:
firstly, testing SERS activity and flexibility, namely dripping probe molecules R6G on the surface of a plasma sensor device for pretreatment, and then taking the treated plasma sensor device to test SERS enhanced signals under different curvatures and different rotation modes;
step two, uniformity testing, namely performing Raman mapping testing on the plasma sensing device processed in the step one, and selecting three characteristic peaks of probe molecules R6G to judge the uniformity of the plasma sensing device;
step three, reproducibility test, namely taking one characteristic peak in the Raman mapping test result in the step two, calculating the relative standard deviation of the intensity of the characteristic peak by using the following formula, and comparing the intensity with an international specified value
Wherein RSD is relative standard deviation, SD is standard deviation,
represents the mean value of the measurements;
and fourthly, performing on-line performance calculation and evaluation on the standard uncertainty, predicting the time sequence output by the plasma sensor in the ith period based on wavelet filtering and a neural network, and calculating the standard uncertainty by using a maximum error method.
2. The SF-AAO-Au plasma sensor performance evaluation method of claim 1, wherein: the specific pretreatment method in the step one is to take probe molecules 10-5MR6G was applied by pipette at a size of 0.5X 0.5cm2The dropping amount of the surface of the plasma sensing device is 10 mu L/time, and the dropping is carried out for three times, wherein after the probe molecules are dropped each time, the next dropping can be carried out only after the surface of the plasma sensing device is completely dried.
3. The SF-AAO-Au plasma sensor performance evaluation method of claim 1, wherein: when SERS enhanced signals under different bending angles are tested in the first step, the plasma sensing device is bent by 10 degrees, 45 degrees and 80 degrees respectively, and 5 different points are selected under each bending angle for carrying out Raman testing.
4. The SF-AAO-Au plasma sensor performance evaluation method of claim 1, wherein: respectively stretching and twisting the plasma sensing device when SERS enhanced signals in different rotation modes are tested in the first step, and selecting 5 different points to perform Raman test under the condition of 120% stretching; the raman test was performed by selecting 5 different points with a 90 ° twist.
5. The SF-AAO-Au plasma sensor performance evaluation method of claim 1, wherein: in the second step, the Raman mapping test is carried out at 20 x 20 mu m2And in the third step, 50 points in one characteristic peak in the three characteristic peaks in the second step are selected for calculating the relative standard deviation.
6. The SF-AAO-Au plasma sensor performance evaluation method of claim 1, wherein: the specific steps of the step four middle prediction are
1) Filtering, wherein a plurality of data points are collected in the ith period to form a sampling data sequence, then wavelet transformation and filtering are carried out on the data sequence, and the average value of the middle 4 digits of the reconstructed signal is taken as filtering output;
2) and (3) neural network online prediction, wherein the first m sampling values obtained by filtering the actual output of the plasma sensing device are used as the output prediction of the network in the ith period.
7. The SF-AAO-Au plasma sensor performance evaluation method of claim 1, wherein: the standard uncertainty calculation method in the fourth step comprises the steps of taking the predicted value of the time sequence in the ith period as a true value, comparing the true value with the actual output value of the plasma sensing device to obtain a residual error, and calculating the standard uncertainty s value measured once in the (i + 1) th period by using the following formula
Wherein deltaiIn order to be the value of the residual error,
is a coefficient related to the number of times of measurement, n is 1 when in online measurement,
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