Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
  • G01N15/08—Investigating permeability, pore-volume, or surface area of porous materials
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
  • G01N15/08—Investigating permeability, pore-volume, or surface area of porous materials
  • G01N15/082—Investigating permeability by forcing a fluid through a sample
  • G01N15/0826—Investigating permeability by forcing a fluid through a sample and measuring fluid flow rate, i.e. permeation rate or pressure change
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
  • G01N15/08—Investigating permeability, pore-volume, or surface area of porous materials
  • G01N2015/0846—Investigating permeability, pore-volume, or surface area of porous materials by use of radiation, e.g. transmitted or reflected light

Definitions

• the invention relates to an arrangement for determining the permeation rate of a sample for a permeate.
• the permeate should in particular be water vapor.
• samples can be formed from barrier materials for the respective permeates.
• the arrangement according to the invention for determining the permeation rate of a sample has a plurality of detectors which are designed for the spatially resolved spectral analysis of electromagnetic radiation within a wavelength interval. These detectors are arranged in a series or a row and column arrangement. The detectors are connected to an electronic evaluation unit and are arranged such that electromagnetic radiation emitted by a broadband radiation source occurs either after reflection at the surface of the sample or from a layer formed on the sample and / or after passing through a sample transparent to the electromagnetic radiation the detectors hits. In this case, the irradiation takes place in such a way that a homogeneous intensity of the electromagnetic radiation is maintained on a surface from which the electromagnetic radiation is reflected or transmitted through the surface. The area to be detected simultaneously should therefore be irradiated with homogeneous intensity. In the case of broadband irradiation electromagnetic waves, which are within a wavelength interval, directed to the respective surface of the sample to be examined.
• the electronic evaluation unit is designed in such a way that the measurement signals detected spatially and wavelength-resolved by the detectors within a wavelength interval can be assigned to a specific wavelength range and within a predefinable partial area of the sample surface to a single location point.
• the totality of the wavelengths resolved at all local points of the respective sample surface forms a three-dimensional data structure consisting of one wavelength-resolved and two spatially resolved dimensions (hypercube).
• a data reduction is to be carried out for all measurement signals of the subarea detected with wavelength resolution, in which meaningful features are selected and the resulting feature set is determined using a regression model stored in an electronic memory, which was determined using feature sets which were previously determined on samples, their permeation rates in particular the
• a sample investigated by the method according to the invention should belong to the same class of sample, which should have a comparable structure or composition, as have been previously investigated with another measuring method with higher measuring accuracy.
• the functional relationship between adequately selected feature sets of samples and their permeation rates, which were determined using a different measurement method, can be determined, for example, by means of linear or nonlinear regression, a partial least squares algorithm (PLS), a neural network, a combination of at least two of these procedures or other regression methods (regression model).
• PLS partial least squares algorithm
• neural network a combination of at least two of these procedures or other regression methods (regression model).
• the electronic memory should therefore contain the regression model, which was created on the basis of the data records of the inventive arrangement of samples which were subjected to data reduction and feature extraction and whose permeation rates were determined using another measurement method. Based on a regression model stored in the electronic memory, the permeation rate of a comparably examined sample of the same sample class with a comparable structure can be determined from the data sets determined using the inventive arrangement.
• the electronic evaluation unit undertakes the data reduction and feature extraction of the data sets determined with the arrangement according to the invention. In this case, an evaluation of the spectral information and then the location information can first take place. Also possible is a reverse order or any combination of more than two individual steps for data reduction and feature extraction.
• the data reduction and feature extraction can be done by principal component analysis (PCA), texture information parameterization, averaging and / or standard deviation determination and combinations thereof.
• PCA principal component analysis
• the n intensities of the wavelengths (spectra) of all the loci are transformed by a coordinate transformation into a new orthogonal coordinate system - the principal component space - in which the original data have maximum variance, and where n represents the number of wavelengths measured.
• the coordinate transformation is calculated by determining the n eigenvectors (main components) and the corresponding n eigenvalues of the covariance matrix of the data set of the measured subarea.
• nents the original variance, ie the eigenvector with the largest eigenvalue is the first major component of the dataset and describes most of the original variance of the dataset.
• the eigenvector with the lowest eigenvalue is the nth major component of the dataset and does not describe any relevant properties of the dataset.
• the coordinates of the spectra in the newly spanned principal component space are the so-called score values (score), which sufficiently characterize the corresponding location point.
• the data reduction and feature extraction can be carried out with the electronic evaluation unit such that the data recorded according to the invention are evaluated in the same way as the data of the samples, on the basis of which known permeation rates the regression model was created.
• the permeation rate of the sample is then determined on the basis of the data record acquired according to the invention, the intensities of the electromagnetic radiation detected at location and wavelength resolution, using the regression model.
• the first six main components are preferably determined. Since the data acquired according to the invention represent all location points of a surface under investigation, the areal distribution of the scores per main component can be specified. The quantification of the different areal distribution of the scores is carried out by various statistical parameters, which are based on all scores of a main component of the respective sub-area be determined. In particular, these are the variance, the interquantile distance or the mean absolute deviation. This procedure can be used for all main components.
• the permeation rate is determined by the electronic evaluation unit on the basis of a regression model, such as a partial least squares regression model (PLS), the parameters being subjected to a further previous feature extraction, preferably via a further principal component analysis (PCA) ,
• a regression model such as a partial least squares regression model (PLS)
• PLS partial least squares regression model
• PCA principal component analysis
• Variant b) One or more principal component (s), in particular the score values of the location points per main component, which can be given over the sample distributed over the sample, are calculated by means of a principal component analysis of the spectral information of all detected location points of the respective examined subarea.
• the location points can be different
• Parameters of the scores are described, in addition to the actual value in particular by the threefold standard deviation of the average of all scores of the respective sub-area. If, at a location point, these parameters deviate by more than three times the standard deviation from the mean value of this parameter of all location points, it is classified as a defect. If such a location point lies next to a location point already classified as defective, then groups of location points (defect areas) classified as defective can be determined in this way.
• the defect regions are divided into different groups, whereby the group division of the defect regions determined according to the invention can be carried out by determining parameters which provide spatial information of the defect region, in particular the surface, expansion in the direction both location coordinates, center, eccentricity, equivalent diameter, circumferential length, filling of the enveloping polygon area, ratio of
• the parameter sets describing the defects can be assigned to specific types of defects, with a breakdown into four types of defects having proven advantageous.
• the permeation rate of the partial area can be determined on the basis of a regression model, in particular of a linear regression model.
• the regression model used was previously determined on the basis of samples of the same sample class with a comparable structure whose permeation rates, in particular the water vapor permeabilities, were determined using a different measurement method which has a higher accuracy of measurement, with all the steps of feature extraction being carried out analogously to the method described above.
• An examined subarea should have a size in the range 500 ⁇ x 500 ⁇ to 1500 ⁇ x 1500 ⁇ . It should be a detection with a spatial resolution in the range of 0.5 ⁇ to 1.5 ⁇ , preferably at 1 ⁇ feasible.
• At least 30, preferably at least 100 detectors should be arranged.
• At least one, preferably at least 50 detectors should be arranged.
• An arrangement according to the invention can be an HSI camera with suitable radiation forms the optical elements and an electronic evaluation electronics are used.
• the irradiation of the surface should be done with at least an angle in the range 0 ° to ⁇ 90 ° with respect to the normal of the surface of the sample.
• the angle of at least approximately 0 ° to the sample normal should advantageously be observed, ie the radiation should be directed as perpendicularly as possible to the surface of the sample in order to keep the reflected portion as small as possible.
• the irradiation and detection can also be carried out with variable angle of incidence of the electromagnetic radiation. As already stated, angles of incidence in the range of 0 ° can occur up to a maximum of 89 °.
• Detection may also be limited to linearly polarized electromagnetic radiation.
• an advantageous orientation of one or more polarization plane (s) before and / or after the sample can be selected.
• the detectors and the sample along at least one axis can be relatively and thereby preferably moved at an advantageous distance from each other.
• a sample can be moved along an axis. This can be achieved with a correspondingly movable table, on which a sample is arranged, which can be moved in an x direction and possibly also in a y direction. But it is also the settlement of roll to roll possible if the sample is made of a flexible deformable material, for example in the form of a film.
• the electromagnetic radiation forming elements may be present.
• the radiation source can be combined with a microscope.
• a radiation source it is also possible for a radiation source to be arranged in a hollow body from which the electromagnetic radiation emerges diffusely and can be directed onto the surface to be irradiated.
• the hollow body may be a ball or cylinder. It should be possible to homogeneously irradiate a surface to be detected simultaneously.
• the wavelength range used should be taken into account in the selection of the respectively used optical elements which serve for beam shaping.
• a diaphragm avoiding the incidence of scattered electromagnetic radiation can be arranged in front of the detectors.
• the radiation source can emit electromagnetic radiation whose wavelength range begins in the UV range and ends in the IR range. Radiation from the wavelength range of visible light up to the NIR range is therefore particularly preferred from 250 nm to 1000 nm. th in a wavelength range used for the irradiation as possible all wavelengths within the respective interval can be used. The limits should be limited only by the sensitivity range of the detectors used with respect to their sensitivity / accuracy of the detectable intensities for the respective wavelengths and the optical
• a sample may also be a multi-layer structure, several layers preferably formed of different materials or materials.
• the base material of the sample may be a polymer film or a thin metal or glass foil to which further thin polymer, ceramic or metal layers may be applied in various combinations.
• the detectors used and the electronic evaluation unit and optionally also the radiation source can represent a so-called hyperspectral image system, which can be used in the arrangement according to the invention. As a result, it is possible to obtain, in addition to the spectral information, location information for the respectively detected subarea of the sample.
• Permeation rate relevant information to be separated from the non-relevant which also significantly reduces the electronic computational effort and thus the required time is also reduced.
• the use of highly complex, cost-intensive electronic computing is not required.
• a statistical model can be created on the basis of which the permeation rate of the examined sample system in the corresponding underlying subarea can be predicted.
• the data record which is possible with one of a plurality of preferably in series arranged optical detectors with which a Weilenofficen- and spatially resolved detection of intensities is possible to be detected.
• the value of the permeation rate is influenced by deviations from the ideal state of the sample. These deviations may be defects, particles, layer thickness variations, material changes, etc. Likewise, these artifacts cause light that interacts with the sample to be reflected, scattered, or transmitted differently (spectrally, intensity). The totality of a sufficient number of individual wavelength-resolved detected intensities (spectra) of different location points of a detected partial area of a sample can thus represent the information about the permeation rate in the considered sample area.
• the permeation rate can be determined on the basis of a measured feature set using a regression model set up in advance with samples of the same sample class with a comparable design with known permeation rates.
• the measured feature sets are to undergo a data reduction and thus a feature extraction. So can the individual
• the parameters used in the regression model can therefore be the number and distribution of the clusters, the scores of the main components or their distribution.
• image compression methods for texture evaluation can be used for texture evaluation, in which the intensities of individual wavelengths detected at all local points of the respective subarea or those of the sum or the averaged sum of the intensities of several wavelengths Wavelengths or the parameters determined by a spectral feature reduction and / or their combinations are subjected to image compression.
• at least one parameter should be transmitted via a wavelet transformation or a different image compression method, such as Taylor polynomials, for example.
• the permeation rate of partial surfaces can be predicted, with the respective measured data records being used for calibration and prediction identical steps of feature reduction are treated.
• a multiple linear regression analysis MLRA
• PCR principal component regression
• PLS partial least square regression
• neural network a neural network
• Prerequisites for a sufficient accuracy of determination are a homogeneous illumination of the area used for detection, so that a
• Working distances and magnifications are adapted to the respective surface of the sample to be detected.
• Permeationseigenschaften of high barrier materials are used. These are used in particular in the packaging industry, the coating of LCD panels / TFTs, the enclosure / encapsulation of thin-film solar cells or for reliable OLED encapsulation.
• n number of eigenvalues of the image

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• 2015
  • 2015-07-23 DE DE102015213974.3A patent/DE102015213974B4/de not_active Expired - Fee Related
• 2016
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  • 2016-07-18 PL PL16744338T patent/PL3325941T3/pl unknown
  • 2016-07-18 EP EP16744338.1A patent/EP3325941B1/de active Active
  • 2016-07-18 JP JP2018503249A patent/JP6612423B2/ja active Active
  • 2016-07-18 WO PCT/EP2016/067019 patent/WO2017013050A1/de not_active Ceased
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