SOLVING ADHESIVE QUALITY ISSUES: A PROPOSED ROADMAP TO THE
ANSWER
Michael Bradshaw, Chemist, Chemsultants International, Mentor, OH
Troubleshooting adhesive failures can be overwhelming with the plethora of variables that are directly related to or at least contributing factors of failure. It can be easy to miss the forest for the trees and vice versa. This paper proposes a “roadmap” to aid the investigator in narrowing the window of potential variables to those most likely few (see Figure 1). At that stage, it is up to the investigator to perform experiments to exclude the non-contributing possibilities.
The first step in any problem-solving scenario is to verify that there is indeed a problem! This may seem nonsensical at first, but one has to be careful in knowing exactly why a product is deemed “bad”. Even with the advent of physical testing instruments, such as probe tack testers, tensile testers, etc., it still is rather common to see the “finger-stick” tack test or “hand-peel” adhesion test performed by end-users. While such crude tests can serve to distinguish between samples, the detection range is so vast for the test to have merit (i.e. a sample with tack and a sample with no tack). Anything in between requires actual numerical data to dispute a significant difference. We all know that there is no such thing as a calibrated hand or finger. One person’s observation of a “problem” may be another person’s observation of “within specification”.
Common physical testing methods available to the adhesives’ investigator include, but are not limited to: peel adhesion, probe tack, loop tack, shear, S.A.F.T., and the list goes on. When possible, all tests should be setup to emulate the actual use of the end product in the field in order to gather meaningful information. Otherwise, use of a standard substrate is warranted. Conditions such as the proper peel angle, proper substrate, and proper aging condition(s) must be adhered to whenever possible. For example, no meaningful information is gathered by aging a label under UV lamps (used to simulate outdoor sunlight) when the product is intended for indoor use. The same principle applies to peel angle. An end-user would be more likely to peel the release liner off a pest glue board at 180° as opposed to 90°, so why test at 90°? To arrive at potential root causes of failure, it is best to test a known “good” sample along side a “suspect”. It offers the investigator no help to have benchmarked the “suspect” sample and have no means of comparing the results. Once a statistically significant difference in physical properties is identified, the process of narrowing the variable window begins.
Once you’ve reached the end of the verification stage, the common benchmarking tests have already been completed. Samples were created and tested in a controlled laboratory setting thus eliminating application conditions as a source of deviation. The obvious next step is to determine what may be causing the differences seen. The most common and subsequently easiest-to-overlook issues may be how much adhesive is present on the “good” and “suspect” materials AND the continuity of the adhesive coating. Most investigators will check the adhesive coat weight only. It is possible to have two samples with similar adhesive coat weight but vastly different coverage or coat quality. If product were produced from a low coverage area, the physical properties would deviate from those of a nominal or higher coverage area. A quick and easy test to check for uniformity would be caliper (or thickness) provided the face stock caliper is uniform throughout or at the least, measurable. A quick test to check for gross inconsistencies in coverage would be a dye-stain test. Irregularities could be spotted based on visual inspection. If coating weight and/or uniformity are found to be the issue, only verification is needed. If not, then further investigations are warranted.
PROBLEM VERIFICATION
Peel adhesion, tack, shear, etc.
Y N
Check end-use conditions (i.e. application variables)
Physical Characterization:
• adhesive coat weight
• coating continuity (caliper)
• dye stain (silicone presence)
Y N
Verify
Analytical Characterization
Surface Phenomenon:
• ATR-FTIR
• X-Ray (XPS/ESCA or EDS)
Y N
Verify Bulk phenomenon:
• TGA, NMR,
or FTIR
Undetectable??
Once the physical benchmarking methods have substantiated a significant difference, the next step would be to analytically characterize the “good” and “suspect” products. The path to studying an adhesive analytically can be followed in one of two ways: (1) surface chemistry and (2) bulk chemistry. Proper selection of analytical methods is critical in obtaining the correct information. The primary job of an adhesive is to bond or adhere to substrates with some minimally acceptable level of strength for the application. . The action of the adhesive bonding to a substrate occurs with both surfaces. The benchmark testing, already performed, compared the adhesion of the “good” and “suspect” products under similar conditions to similar substrates. If a difference had been seen, the surface of the substrate is most likely not the contributor. The problem may lie on the surface of the adhesive. There are a wide variety of surface analytical testing methods to aid the investigator. The most common and most widely used is ATR-FTIR (acronym for Attenuated Total Reflectance Fourier
Transform InfraRed) spectroscopy. In general, this technique probes the surface of a sample (up to 2 microns deep) with infrared energy of varying wavelengths. To understand the technique we must consider a little theory.
Molecules are constantly in motion above absolute zero (-273.2 °C). These motions can vary in nature (i.e., vibration, rotation, stretching, wagging, etc.) and each molecule has a distinct frequency of motion determined by the masses of the atoms involved as well as the bonding of those atoms. Motions that result in a non-zero dipole moment in a molecule are said to be IR-active. What this means is that the motion can be excited with wavelengths of IR energy. It is by monitoring which wavelengths of IR energy are absorbed by a sample, that the investigator is able to determine which atoms are present and how they are bonded (grouped into a term called functionality). An example IR spectrum is shown below: 4000 3000 2000 1000 Wavenumber (cm-1) 0 50 100 % T ransm ittance 2962.65 2904.79 1446.61 1411.89 1261.44 1095.56 1022.27 864.11 798.53 702.09 686.66 663.51
Figure 2: Sample IR Spectrum [Silicone Fluid]
The y-axis indicates the amount of incident IR energy that passes through or reflects off the sample. The x-axis indicates the distinct frequencies of IR energy the sample is exposed to in wavenumbers (i.e. inverse wavelength). A decreasing transmission occurring at a distinct wave number correlates to absorption of that corresponding energy. Correlation charts are referred to determine functionality.
IR is usually performed on a bulk basis by passing IR energies through a solvated material or a solid IR-transparent pellet composed of, most likely, potassium bromide. Obvious drawbacks are analysis of insoluble products and the tedious sample preparation involved in producing a solid pellet. With the advancement of technology, the ability to perform IR analysis on the surface of a sample has been made possible. Crystals having favorable refractive indices (i.e. zinc selenide, diamond, etc.) can be employed to incident IR energy to multiple spots (ATR) or one spot (Single Reflectance ATR) on the surface of a sample. One of the conditions a sample must meet to use ATR-FTIR is that it must be flexible enough to make good contact with the crystal surface used. Pressure-sensitive-adhesive-coated materials fall under this criteria due to their natural ability to wet out a surface making the method readily useable. Another requirement of using ATR-FTIR is that the thickness of the adhesive should not be less than 2 microns (< 0.1 mils) because that is the penetration depth of the IR energy on the surface of the sample. Otherwise the information obtained would be more characteristic of the adhesive/face stock interaction surface or possibly the face stock alone. By the nature of the technique, ATR is a powerful tool is ascertaining IR-active surface impurities, like silicone. Silicone is an excellent example because of the strong extinction coefficients related to the motions of the silicon-oxygen/silicon-carbon bonds. Silicones are known to appear in the 1260 (± 5), 800 (± 10), and 1000 – 1200 cm-1 ranges.
Potential drawbacks of IR spectroscopy include the detection limit, the additive features of the spectrum, and the inability to absolutely distinguish between certain chemicals. The detection limit of IR has been noted to be between 2 and 3% by weight of the total analyzed sample. Therefore, any IR-active component in a sample at less than 2% by weight does not have a good chance of showing appreciable signals compared to the vastly more intense signals of the background. Secondly, IR is known to be an additive technique, which in it’s simplest terms means that the IR spectrum of a mixture composed of IR-active components A, B, and C will appear like an overlay of the IR spectra of components A, B, and C (provided they do not chemically react with each other). While this presents obvious advantages for a compounded PSA in determining what types of components are present, it can spell doom for a
spectroscopist trying to differentiate signals between various components. This is why IR is more widely used as a quality tool to compare “good” and “suspect” materials rather than ascertain absolute identification. There are cases where IR is not powerful enough alone to distinguish between two chemicals or components. For example, the spectra of the same polymer at different molecular weights can look the same. Also comparing n-heptane to n-nonane may prove difficult. More in-depth
analytical techniques coupled with IR spectroscopy can help alleviate these confusions.
A second surface-analysis technique involves the use of X-ray energy to identify various elements. This technique is referred to as X-ray Photoelectron Spectroscopy (XPS). X-rays of known energy displace inner-shell electrons of certain atoms (excluding hydrogen and helium). The kinetic energies of the expelled electrons are measured and coupled with the knowledge of the incident x-ray energy, binding energy of the expelled electrons are determined. This binding energy is used to identify what atoms are present on the surface. The resulting survey spectrum shows the elements present on the surface of a sample. XPS is limited to analysis depths of 20 – 50 angstroms due to the poor penetrating power of the electrons expelled.
If comparison of “good” and “suspect” sample surfaces does not show a chemical difference, the next logical step is to analytically study the bulk adhesive. A troublesome aspect of this type of analysis is how the “good” and “suspect” samples are supplied. More than likely, the samples will be finished constructions with adhesive coated onto a carrier or face stock and laminated to a release liner.
Therefore to analyze the bulk adhesive, the carrier or face stock needs to be removed from the assembly. Removal is commonly performed in one of two ways: (1) solvating the adhesive off of the carrier/face
stock or (2) microtoming the adhesive from the face stock. The preferred method would be microtoming of the adhesive since there may be coatings on the face side of the adhesive-coated material that could solvate leading to false identifications.
The starting point in any bulk analysis is to determine roughly how many components are present in the finished material. One of the quickest ways to accomplish this is with a thermal technique known as Thermal Gravimetric Analysis (TGA). A sample of known mass is heated at a specified rate under an inert atmosphere (nitrogen) from room temperature up to a maximum of 1000 °C. The mass of the sample is continually monitored as the temperature is raised. Under these conditions, decompositions of individual components in the sample occur as evidenced by decreasing mass at certain temperature ranges. What makes this technique so powerful is that is reveals both qualitative (how many
decomposable components are present) as well as quantitative information on your sample. Knowing the mass you started out with and the mass of the sample after a component degrades off, the
investigator can get a relative weight percentage of that component. Therefore, a simple analysis of both “good” and “suspect” samples can reveal relative compositional differences as long as the experimental conditions are similar. A sample TGA plot is shown below:
Figure 3: Sample TGA Thermogram
The plot shows the change in weight (y-axis) with respect to increase in temperature (x-axis). The obvious drawback of this technique is that it is destructive. Once the sample is analyzed, the sample has been irreversibly degraded. However, the sample mass needed to perform the test is in the 10’s of milligrams and thus can easily be spared.
Once you have a relative idea of how many components are present in the sample, the experimenter can devise a methodology for separation with various solvents or chromatographic methods. Once the components are solvated, techniques such as solvated FTIR can be performed. A more involved and powerful technique used to analyze solvated materials, called Fourier Transform Nuclear Magnetic Resonance (FTNMR), is a next step to FTIR to distinguish between chemicals with similar IR spectra. FTNMR gives information on the nuclear level for a select few atoms. The two most common nuclei studied are 1H (hydrogen) and 13C (carbon-13). The power of FTNMR lies in the ability to distinguish
between hydrogen or carbon nuclei bonded to different chemical types of atoms. Therefore, structural information can be obtained on a sample. Like FTIR, FTNMR is an additive technique leading to an
increased ability to ascertain differences. However, the complexity of the interpretations increases exponentially with the number of components in a sample.
FTNMR can be performed on only two types of samples: (1) solvated or liquid products or (2) solid powders. Thus FTNMR analysis of adhesives is only possible if the adhesive can be solvated. Choice of solvent is critical so that it does not cause spectral interference with the sample dissolved. To get around this, deuterated (2H) solvents are used in place of hydrocarbons. These solvents can be costly
based on the complexity of the structure. FTNMR involves placing a sample into a magnetic field and monitoring the absorption of radio frequencies. 1H and 13C nuclei, when exposed to a magnetic field,
possess split nuclear spin states. The splitting between those spin states depend on what chemical environment the nuclei are in (i.e. surrounded by electrons, other similar nuclei, etc.) and the magnitude of the external magnetic field. The position of the signal is normalized to a ppm value in order to factor out the effects of different magnetic field strength instruments leading to a direct correlation of signal position and chemical environment no matter what magnetic strength instrument is employed. Again, comparison between “good” and “suspect” solvated adhesives can show possible differences in the samples.
In addition to the aforementioned, other, more specialized analytical techniques are available to the investigator. The techniques presented in this paper offer a good foundation to build from to compare “good” and “suspect” samples. The correlation of the vast amount of analytical data to the physical benchmarking data can offer a complete picture on identification of a problem and possible sources of resolution. What follows is a step-by-step study of an adhesive issue making use of the “roadmap” discussed herein:
Case Study #1
End-user E has purchased pressure sensitive adhesive label stock from Vendor V for a 5-year period. Vendor V obtains the label stock from Manufacturer M. End-user E has seen tighter release
characteristics and label failures with their last lot of label stock.
Step #1: Problem Verification
The end-user is asked to submit samples of known “good” lot(s) of label stock along side the “suspect” lot(s). The label stocks are multi-purpose and therefore choice of a substrate is arbitrary. Stainless steel was chosen as a standard surface for testing. Release and subsequent adhesion (PSTC-4B) as well as probe tack (ASTM D 2979) were evaluated. The following results were obtained:
Table 1: Physical Comparative Testing of “Good” and “Suspect” Labels "Good" "Suspect" n 3 3 AVG 3.5 (± 0.7) 670.4 (± 98.0) MOF A A n 3 3 AVG 4.26 (± 0.09) 0.61 (± 0.04) MOF A A n 5 5 AVG 140 (± 8) 65 (± 7) MOF A A
Release (PSTC-4B): aged 24 hr @ 70 °C / 0.25 psi: g/in
180 ° Peel Adhesion (PSTC-4B): lbs/in
Probe Tack (ASTM D 2979): g/cm²
The data clearly indicates a discrepancy between the two lots of labels. Release is over 100 times greater in the case of the “suspect” material. Peel adhesion to stainless steel after aging of the label stocks for 24 hours at 70 °C under ¼ PSI shows an 85% decrease comparing the “good” to the “suspect”. Probe tack is 54% lower in the case of the “suspect” label stock compared to the “good” sample. Therefore physical testing has verified that a problem exists. However, there is not enough information from the data gathered to identify where the problem lies.
Step #2: Physical Characterization of Problem
Now that a statistically significant difference can be seen between “good” and “suspect” label stocks in a controlled laboratory environment, possible sources of the discrepancy can be investigated. Adhesive coat weight and caliper are determined for the two labels:
Table 2: Physical Comparative Characterization of “Good” and “Suspect” Labels "Good" "Suspect"
AVG 15.7 15.6
n 5 5
AVG 4.76 (± 0.04) 4.76 (± 0.07)
Adhesive Coat Weight (TLMI Coat Weight): g/m² Caliper (ASTM D 3652): mils
As can be seen from the data gathered, there was no statistically significant difference between the adhesive coating weight or adhesive caliper between the two label stocks.
Step # 3: Analytical Characterization of Problem
The “good” and “suspect” labels were shown to be different by physical testing and the difference was not seen to be due to adhesive coating weight and/or caliper. The first area of investigation for analytical work should be the adhesive surface. ATR-FTIR spectroscopy was performed on multiple
spots of each label adhesive surface. The individual stacked spectra of each spot analyzed are shown in Figures 4 and 5: 4000 3000 2000 1000 Wavenumber (cm-1) 0.5 1.0 1.5 Tr ans mi ttanc e
Figure 4: Stacked Overlay ATR-FTIR Spectra of Multiple Spots On Surface of “Good” Adhesive The spectra appear very similar to each other.
4000 3000 2000 1000 Wavenumber (cm-1) 0.5 1.0 1.5 T ransmit tance
Figure 5: Stacked Overlay ATR-FTIR Spectra of Multiple Spots On Surface of “Suspect” Adhesive The spectra appear similar to each other.
4000 3000 2000 1000 Wavenumber (cm-1) 0.65 0.70 0.75 0.80 0.85 0.90 0.95 1.00 1.05 1.10 Tr ans m ittanc e
Figure 6: Stacked Overlay Average ATR-FTIR Spectra of ‘Good’ and ‘Suspect’ Adhesive Surfaces Upon initial investigation, the spectra appear similar. A closer look at the spectra below 1700 cm-1 reveals differences: 1000 Wavenumber (cm-1) 0.85 0.90 0.95 1.00 Tr ans m ittanc e
Figure 7: Zoomed In Region of ‘Good’ and ‘Suspect’ Adhesive ATR-FTIR Spectra Overlay These differences are not readily seen unless a direct subtraction of the average ATR-FTIR spectrum of the adhesive surface from the ‘good’ label is made from the spectrum of the adhesive surface of the ‘suspect’ label:
4000 3000 2000 1000 Wavenumber (cm-1) 0.00 0.01 Tr ans m ittanc e 802. 24 1022. 09 1058. 73 1101. 15 1160. 94 1261. 22 1396. 21 1450. 21 1731. 76 2875. 34 2962. 13 2998. 77
Figure 8: ATR-FTIR Difference Spectrum Of ‘Good’ Label Adhesive From “Suspect” Label Adhesive The boxed regions are indicative of possible silicone presence.
Step #3-1: Verification
ATR-FTIR testing of the surfaces of the “good” and “suspect” labels showed possibly more silicone presence on the “suspect” label adhesive surface. XPS was used as a check for detection of quantitative differences in percentage of silicon atoms in the regions analyzed. Figures 9 and 10 represent the XPS elemental survey scans of a region of the adhesive surface of ‘good’ and ‘suspect’ labels respectively:
Figure 9: XPS Elemental Survey Scan of “Good” Label Adhesive Surface
Oxygen, carbon, and silicon atoms were detected on the surface of the “good” label adhesive denoted as O1s, C1s, Si2s, and Si2p respectively.
Figure 10: XPS Elemental Survey Scan of “Suspect” Label Adhesive Surface
The same three elements were detected on the surface of the “suspect” label adhesive denoted by the similar signals. To obtain an average surface percent atom composition, three spots were analyzed on the surface of the ‘good’ label adhesive:
Table 3: Percent Atom Composition of Adhesive Surface On “Good” and “Suspect” Labels
Carbon Oxygen Silicon
"Good" Label
Adhesive 77.0 (± 1.0) 21.3 (± 0.4) 1.8 (± 0.7)
"Suspect" Label
Adhesive 67.4 23.5 9.1
Atomic Percent
To confirm, fuchsin dye was used to wipe the surface of the liner after label removal on both “good” and “suspect” samples. Areas on the “suspect” label liner indicated removal of silicone by absorption of the dye into the base paper.
Conclusion
“Good” and “suspect” labels showed substantial differences in physical properties. Physical
characterization of the two products did not reveal a significant difference. Surface analytical testing showed possible presence of silicone on the adhesive surface through ATR-FTIR. XPS percent atomic survey showed a substantially higher level of silicon atoms on the surface of the “suspect” adhesive. Dye stain/anchorage testing of the liners showed that silicone was poorly anchored on the release liner to which the “suspect” labels had been laminated. Therefore, the silicone presence detected is
hypothesized to be due to silicone transfer from the liner to the adhesive surface in the “suspect” lot. Thus explaining the diminished adhesive properties in the “suspect” material.
Case Study #2
Manufacturer Y buys a water-based, high shear pressure-sensitive label adhesive from Company D to use in production of permanent labels. In mid-production, a switch in lots of adhesive was made. Sporadic failure complaints came in for poor adhesion and flagging of the labels.
Step #1: Problem Verification
Manufacturer Y submits failing and non-failing label products for testing. Stainless steel was chosen as a standard surface for testing. Peel adhesion (PSTC-101F) as well as probe tack (ASTM D 2979) were evaluated:
Table 4: Peel Adhesion and Probe Tack Data For Failing and Non-Failing Labels Non-Failing
Labels Failing Labels
n 3 3 AVG 2.74 (± 0.01) pk 1.16 (± 0.04) MOF FD A n 5 5 AVG 178 (± 21) 66 (± 7) MOF A A
Peel Adhesion (PSTC-101F): lbs/in
Probe Tack (ASTM D 2979): g/cm²
The data clearly shows a discrepancy between the two label products with face stock tearing bonds in one case and clean release peel in the other. There is also an approximate 3-fold difference in tack between the failing and non-failing products.
Step #2: Physical Characterization of Problem
Now that a statistically significant difference can be seen between the label stocks in a controlled laboratory environment, possible sources of the discrepancy can be investigated. Adhesive coat weight and caliper are determined for the two label stocks:
Table 2: Physical Comparative Characterization of “Good” and “Suspect” Labels
Non-Failing Labels Failing Labels
n 7 5
AVG 5.45 (± 0.07) 5.39 (± 0.04)
AVG 22.0 21.6
Total Caliper (ASTM D 3652 modified): mils
Adhesive Coatweight (TLMI Coat Weight Test modified): g/m²
Step # 3: Analytical Characterization of Problem
The failing and non-failing labels were shown to be different by physical testing and the difference was not seen to be due to adhesive coating weight and/or caliper. To investigate surface differences, ATR-FTIR spectroscopy was performed on multiple spots of each label adhesive surface. The individual stacked spectra are shown in Figures 11 and 12:
3000 2000 1000 Wavenumber (cm-1) 0.0 0.5 1.0 Tr ans mi ttanc e
Figure 11: Stacked ATR-FTIR Spectra of Non-Failing Label Adhesive Surface
There appears to be no significant differences between the three regions other than the signals at ~ 2300 cm-1 attributed to carbon dioxide presence from the atmosphere.
3000 2000 1000 Wavenumber (cm-1) 0.0 0.5 1.0 Tr ans mittanc e
Figure 12: Stacked ATR-FTIR Spectra of Failing Label Adhesive Surface Again, the spectra appear similar to each other. To directly compare the two samples, the average spectra were stacked together and presented in Figure 13:
3000 2000 1000 Wavenumber (cm-1) 0.0 0.5 1.0 Tr ans mittanc e N o n - f a i l i n g L a b e l F a i l i n g L a b e l
Figure 13: Stacked Average ATR-FTIR Spectra of Failing and Non-Failing Label Adhesives Some signal intensity differences can be seen between the two spectra that could be due to either contact pressure of the sample with the ATR crystal or concentration differences in the formulation. Signal location and structure seems to be similar between the two samples.
Step #4: Bulk Analysis
To help ascertain whether the intensity differences seen are due to quantitative formulation differences or the analysis procedure, TGA was performed on the two adhesives after removal from the face stock. The thermograms are presented in Figures 14 and 15 respectively:
Figure 14: TGA Thermogram of Non-Failing Label Adhesive Sample
The adhesive appears to have two major decomposable components. Relative quantification of the components leads to a ratio of approximately 70:30. The corresponding thermogram for the failing adhesive follows:
Figure 15: TGA Thermogram of Failing Label Adhesive Sample
There still appears to be two components with relatively similar decomposition rates and temperatures. However, the ratio between the two components seems to be shifted from approximately 70:30 to approximately 80:20. Therefore, the signal intensity differences seen with ATR-FTIR were indicative of a formulation difference between the two adhesives. Further analysis would be needed to determine the identity of the two components.
Conclusion
Physical comparative testing confirmed differences in the failing and non-failing label stocks in peel adhesion and tack properties. Caliper and adhesive coating weight were not seen to be statistically different between the two labels. ATR-FTIR showed similar signal location and structures with slight differences in some signal intensities. Possible causes were rationalized to be experimental error or formulation differences. TGA bulk adhesive analysis was performed on the failing and non-failing samples with differences seen in the ratio of two major components. Therefore the root cause of the problem is most likely related to the adhesive formulation differences between the two labels.
These examples are two of many quality issues that can likely be resolved by use of the troubleshooting “roadmap” presented. A thorough investigation of quality issues not only determines what the
differences are between “good” and “bad” product but also identifies potential root causes. By applying this “roadmap” design, one can accomplish both goals.
