Chromium-doped α-alumina is naturally photo-luminescent with spectral properties that are characterized by R-lines with two distinct peaks known as R1 and R2. When the material is subjected to stress, shifts in the R-lines occur, which is known as the piezospectroscopic (PS) effect. Recent work has shown that improved sensitivity of the technique can be achieved through a configuration of nanoparticles within a polymer matrix, which can be applied to a structure as a stress-sensing coating. This study demonstrates the capability of PS coatings in mechanical tests and investigates the effect of nanoparticle volume fraction on sensing performance. Here, measurements of spectral shifts that capture variation in stress of the coating during mechanical testing and in the region of substrate damage showed that stress contours are more noticeable on a soft laminate than hard laminate. It was found that the 20 % volume fraction PS coating showed the most distinct features of all the coatings tested with the highest signal-to-noise ratio and volume fraction of α-alumina. Post failure assessment of the PS coatings verified that the coatings were intact and peak shifts observed during mechanical testing were due to the stress in the substrate. The results suggest the ability to design and tailor the “sensing” capability of these nanoparticles and correlate the measured stress variations with the presence of stress and damage in underlying structures. This study is relevant to nondestructive evaluation in the aerospace industry, where monitoring signs of damage is of significance for testing of new materials, quality control in manufacturing and inspections during maintenance.

The aerospace industry relies on nondestructive evaluation (NDE) methods to determine mechanical properties of new materials through standardized tests and quality inspection during manufacturing and maintenance.1 One of the significant concerns is monitoring the health of aerospace structures. Metallic components tend to degrade due to factors such as fatigue damage, hidden cracks and corrosion.2 The increasing use of composite materials in aerospace structures is due to their high strength-to-weight ratios and corrosion resistance. Structures made from these composite materials are susceptible to failure due to delamination, matrix cracking, fiber-matrix debonding and fiber breakage.3 Failure prediction and detection is critical for aircraft structural integrity. NDE methods must be sensitive enough to detect these flaws and provide reliable results.4 Due to the increasing interest in structural health monitoring,5 the aerospace industry seeks new and improved NDE methods. In this study, the sensitivity of a stress-sensing nanoparticle smart coating concept, using piezospectroscopy, is investigated specifically for the effect of nanoparticle volume fraction on sensing performance.

Photoluminescence (PL) spectroscopy of chromium-doped α-alumina, a naturally photo-luminescent material, characterizes two distinct R-line peaks, R1 and R2, from the material6 shown in Figure 1. Intensities of R-lines have been used in our previous work to study dispersion of α-alumina nanoparticles in hybrid carbon fiber reinforced polymers (HCFRPs). HCFRPs utilize nanoparticles of α-alumina embedded into carbon fiber reinforced polymers to improve fracture toughness properties.7 While embedding nanoparticles into carbon fiber enhances mechanical properties, achieving uniform dispersion is a challenge since agglomerations and sedimentation can occur.7 Dispersion studies using PL spectroscopy enables the identification of regions of increased agglomeration8 and demonstrates capability of characterizing particle dispersion9 for applications in assessing manufacturing quality.

FIG. 1.

A schematic showing PS data collection.

FIG. 1.

A schematic showing PS data collection.

Close modal

Piezospectroscopy (PS) correlates changes in the peak position of laser-induced spectral emission of photo-luminescent materials when they undergo stress. Historically, this method was applied to diamond-anvil pressure cells to visually observe pressure effects on materials using the R-line fluorescence in ruby.10 It is also applicable to stress measurements of thermally grown oxide (TGO) layers in thermal barrier coatings (TBCs) in turbine engines.11,12 Through photoluminescence piezospectroscopy, the stress state of TBCs can be analyzed from the TGO, which is a chromium-doped α-alumina layer.13,14 The fundamental method is demonstrated when stress is applied to the material, where a shift in the R-lines can be observed. This phenomenon is known as the piezospectroscopic effect and can be expressed in the relationship shown in Equation 1.15,24

Δν=Πijσij
(1)

Here Πij represents the effective piezospectroscopic coefficients, and Δν represents the change in wavenumber from the peak shift while σij is the stress tensor. Past work on PS on α-alumina first introduced by Grabner24 has shown that the peak shifts can be calibrated to correlate with stress on the α-alumina. He and Clarke25 expanded on this work by relating the peak shifts to the first invariant of the stress tensor. Thus, present work on PS focuses on qualitatively assessing stress on α-alumina nanoparticles based on peak shifts.

Our work focuses on the investigation of a stress-sensing material based on the piezospectroscopic effect and comprises a polymer matrix with embedded α-alumina nanoparticles, which can be applied on a substrate. Here, the nanoparticles can be configured to improve the sensitivity of the measurements. In our previous study on the effect of nanoparticle volume fraction on stress sensing, mechanical tests were performed on epoxy material with variations in volume fractions of nanoparticles.17 The peak shifts (or frequency shifts) were plotted with respect to the applied compressive stress for each nanoparticle volume fraction tested, which showed a linear trend. The PS coefficient, which is an empirical value, was determined by taking the slope of the peak shift against the applied stress.24,25 It was found that the PS coefficient, which correlates with stress sensitivity, increases with increasing nanoparticle volume fraction. Analytical models were shown to underpredict the stress in the particles compared to what was experimentally observed for high volume fractions (20%). The effect of microstructural features and contact stresses present at higher volume fractions could potentially contribute to this difference.16 However, higher volume fraction of α-alumina nanoparticles will result in a more brittle and stiff material, which will lead to undesirable attributes for an efficient PS coating.

When implementing α-alumina nanoparticles as piezospectroscopic coatings for the study of aerospace materials, the ability to sense stress variations when the materials are subjected to loading has been successfully demonstrated.18,19 In the study by Freihofer et al.19 an open-hole tension (OHT) carbon fiber reinforced polymer (CFRP) was coated with epoxy that consisted of 20 % volume fraction of α-alumina nanoparticles and tested in accordance with ASTM D5766.20 It was found that the coating detected signs of internal ply damage at 77 % failure load19 well before it surfaced and was visually detected at 92 % of the failure load. In addition to having the ability to sense stress variations on a material (or substrate) subjected to load, another essential requirement needed for an efficient PS coating is that, during load, the coating should remain adhered to the substrate to ensure accurate readings.

This study demonstrates the sensitivity of stress and damage detection with piezospectroscopic (PS) coatings as a function of the volume fraction of nanoparticles within the coating. The study is an initial effort to answer the need to define optimal parameters for an ideal working configuration of this piezospectropic coating in order to enable the implementation and technique to complement other NDE methods that are currently being used. Specifically, the volume fraction of α-alumina nanoparticles in these PS coatings for stress sensing was investigated in this study. Based on a study by Stevenson et al17 it is expected that the coating’s sensitivity to changes in stress, which correlates with the PS coefficient (Equation 1), increases as the particle volume fraction increases. To validate this trend, the PS coatings tested were assessed for their sensitivity based on the SNR and luminosity, and the peak shift contour plots showing the qualitative stress distribution of the loaded specimens. Here, spectral data from the three specimens with 5 % and 10 % volume fraction of α-alumina within a PS coating on hard laminate and 20 % volume fraction of α-alumina on soft laminate tested in a previous study19 are compared for their sensitivity in stress and damage detection. In addition, the damaged OHT CFRP test specimens were assessed for post failure investigation using the piezospectroscopic coating.

The PS nanocoating investigated was manufactured by Elantas PDG Inc. by mixing 150 nm α-alumina nanoparticles (Inframat Corp.) with 99.8 % purity in epoxy to achieve 5 %, 10 % and 20 % volume fraction of particles. The coating was applied to an open-hole tension composite substrate consisting of laminated IM7-8552 unidirectional tape. Two OHT CFRP hard laminate specimens were coated with 5 % and 10 % volume fraction PS coatings. These composite substrates had an elastic modulus of 91 GPa. An OHT CFRP soft laminate specimen was coated with 20 % volume fraction PS coating. This composite substrate had an elastic modulus of 38.6 GPa. It is assumed that, in comparison to the substrate, the thickness and stiffness of the coating are small and have a negligible effect on the substrate characteristics during loading. The laminates and corresponding coating configurations are shown in Table I. The test specimens were loaded at a rate of 0.02 mm/sec and held at discrete increments using displacement control, so that substrate strain is kept constant during testing. The hard laminate specimens were loaded up to 88,964 N, while the soft laminate specimen was loaded up to 44,482 N. These were the maximum loads in which the specimens failed. PS data were collected using a 60 × 60 grid in a snake scan pattern, a measurement area of 25.4 mm2, and a spatial resolution of 0.4 mm. The portable photoluminescence piezospectroscopy system collects data in a snake scan pattern by taking point scans of a defined area on the specimen with a laser probe, as shown in Figure 1. The system continues this pattern until it scans the entire defined area. To gain sufficient intensity with respect to the amount of particles in the coating, the maps for each PS coating were collected at various times. Table I shows the total collection time for each PS coating. More information on the snake scan pattern and experimental setup are available in previous publications.17,19

TABLE I.

Coating properties and experimental parameters for each PS coating.

LaminatePS CoatingCollection TimeTotal CollectionMedian CoatingMedian
TypeVolume Fractionper PointTimeLuminositySNR
Hard 5 % 500 ms 32 minutes 8,529 counts/sec 42.85 
Hard 10 % 200 ms 14 minutes 25,013 counts/sec 58.05 
Soft 20 % 100 ms 8 minutes 104,698 counts/sec 94.27 
LaminatePS CoatingCollection TimeTotal CollectionMedian CoatingMedian
TypeVolume Fractionper PointTimeLuminositySNR
Hard 5 % 500 ms 32 minutes 8,529 counts/sec 42.85 
Hard 10 % 200 ms 14 minutes 25,013 counts/sec 58.05 
Soft 20 % 100 ms 8 minutes 104,698 counts/sec 94.27 

After the specimens were loaded to failure, a map scan of each specimen was taken without applying load to assess the post failure residual stress. The PL data for each specimen was collected using a 200 × 200 grid in a snake scan pattern with an area of 40 mm2 and a spatial resolution of 0.2 mm.

The analysis of this data was conducted using a set of in-house, non-linear, least squares codes that allow for the processing of large data sets in a relatively short amount of processing time. This consists of a set of curve-fitting algorithms that process the unique R-line doublet that makes up the photo-luminescent response of α-alumina using two pseudo-Voigt functions. The details of curve fitting of experimental data using two pseudo-Voigt functions are further described in a previous publication.21 

The sensing capability of the three coating configurations is analyzed in this section. First, the signal response coming from the PS coatings was investigated for each volume fraction. Then, comparisons of the peak shift maps during the tensile tests for each specimen were made to determine the differences in damage sensing capabilities for the hard and soft laminate and varying volume fraction. Lastly, peak shift maps of the three specimens after tensile failure were analyzed.

To verify the signal response coming from the PS coatings, the representative R-lines for each coating configuration were analyzed, as shown in Figure 2. The experimental parameters and corresponding signal properties are shown in Table I. The median signal-to-noise ratios (SNRs) were taken from the median of the spectra from one surface map, which consists of R-lines from 3600 point locations. The median coating luminosity was determined by taking the median intensity of one surface map divided by the collection time.

FIG. 2.

Representative R-lines for each PS coating with corresponding collection times. Laser power and beam diameter was kept consistent for each specimen.

FIG. 2.

Representative R-lines for each PS coating with corresponding collection times. Laser power and beam diameter was kept consistent for each specimen.

Close modal

The median SNRs measure the quality of the R-lines for each PS experimental parameter. The higher the median SNR and median coating luminosity, the lower the uncertainty in the peak position and the smoother the R-lines. It is shown that higher median SNR and median coating luminosity correlate with more distinctive peak shifts. With higher volume fractions of α-alumina nanoparticles in PS coating, higher median SNR and median luminosity can be obtained, which correlate with better signal quality. The differences in luminosity among the PS coatings tested are demonstrated in the dispersion maps as shown in Figure 3.

FIG. 3.

Contour maps showing α-alumina nanoparticle dispersion for (A) 5 %, (B) 10 % and (C) 20 % volume fraction PS coatings. Each map has dimensions of 25.4 mm × 25.4 mm. Also, note that “VF” is volume fraction.

FIG. 3.

Contour maps showing α-alumina nanoparticle dispersion for (A) 5 %, (B) 10 % and (C) 20 % volume fraction PS coatings. Each map has dimensions of 25.4 mm × 25.4 mm. Also, note that “VF” is volume fraction.

Close modal

The dispersion map for the 5 % volume fraction PS coating (Figure 3) showed that there was a small agglomerated spot at the top area. The dispersion map for the 10 % volume fraction PS coating showed the lowest presence of α-alumina nanoparticles and non-uniform dispersion around the hole of the OHT CFRP specimen. Although the dispersion map for the 10 % volume fraction PS coating suggests less uniformity in dispersion of α-alumina nanoparticles than the 5 % volume fraction PS coating, a fixed process was used to weigh the α-alumina nanoparticles to obtain the desired volume fraction for each coating. The non-uniformity in the presence of α-alumina nanoparticles in the 10 % volume fraction PS coating is most likely due to the application method of this coating, which may have led to a greater amount of agglomerations of nanoparticles. With the exception of a few agglomerated spots, the dispersion map for the 20 % volume fraction PS coating showed higher intensity readings in comparison to the dispersion maps for the 5 % and 10 % PS coatings.

The dispersion maps in Figure 3 further support that higher volume fractions of α-alumina correlate with higher SNR and luminosity. Thus, they correspond to higher intensities and lower uncertainty in the peak position. Although these dispersion maps indicate generally homogeneous dispersion, there were few areas in each PS coating with some variations in dispersion. It is expected that more agglomerations are present at higher volume fractions, which was clearly shown in the dispersion map for the 20 % volume fraction PS coating. However, these variations did not affect the PS coatings’ capability in sensing changes in stress in the substrates, which is demonstrated in Section III B.

Peak shift maps show shifts based on the type of stress that the specimens were experiencing. A positive shift indicates tensile stress, while a negative shift indicates compressive stress. Peak shift maps for the 5 % and 10 % volume fraction PS coatings were compared to observe differences in stress sensing capability on hard laminate as shown in Figure 4.

FIG. 4.

Stress sensing of two OHT CFRP specimens with 5 % and 10 % volume fraction PS coating with progressing loads. These specimens consist of composite substrates with hard laminate. Each map has dimensions of 25.4 mm × 25.4 mm.

FIG. 4.

Stress sensing of two OHT CFRP specimens with 5 % and 10 % volume fraction PS coating with progressing loads. These specimens consist of composite substrates with hard laminate. Each map has dimensions of 25.4 mm × 25.4 mm.

Close modal

Starting at 51,599 N, signs of tensile loading is clearly shown on the PS map for the 10 % volume fraction PS coating. At the same load, the PS map for the 5 % volume fraction PS coating showed only a slight change in stress. Based on this comparison, the 10 % volume fraction PS coating shows more sensitivity to changes in stress than the 5 % volume fraction PS coating. A higher PS coefficient for the 10 % volume fraction explains the higher stress sensitivity than the 5 % coating.17 The low SNR for the 5 % volume fraction PS coating may lead to “noisier” peak shift maps due to the increased uncertainty of the peak shift. The PS maps for both hard laminate specimens show strain release around the hole with increasing load. However, due to the high elastic modulus of this hard laminate substrate, there is not a significant change in the strain release compared to the soft laminate.

The peak shift maps for the 20 % volume fraction PS coating were observed for the coating’s stress sensing capability on soft laminate as shown in Figure 5. Intrinsic stress patterns are shown in the maps with progressive loading. Starting at 33,806 N, initiation of damage adjacent to the open-hole can be observed. This region was experiencing large tensile strains and was a likely location for damage to initiate.22 Work by Camanho23 supports this phenomenon in which a simulation using continuum damage mechanics of a transversely isotropic open-hole tension composite specimen predicted initial fiber failure in the 0° ply in the same region. At 39,144 N, the PS map shows large stress gradients adjacent to the open hole, which are likely caused by accumulating damage and redistribution of stresses.22 Significant variation of stresses on the soft laminate is distinctly shown in the PS maps, which indicates that the PS coating can easily sense the changes in stress on this type of laminate. Specifically, more ±45° fibers in the soft laminate make it more susceptible to damage compared to the hard laminate. The reduction in stress localized near the hole is due to interlaminar damage in that area, which begins at around 77% of the failure load. It is likely that higher stresses were redistributed throughout the larger area around the hole. As a result, these higher stresses over the larger area is less distinct, in terms of peak shift, than the localized reduction in stress near the hole. This phenomenon can be shown in previous work Freihofer et al.22 The high SNR makes it easier to see the stress distributions across the sample surface due to less uncertainty in peak shifts. The high-volume fraction also makes the nanocomposite PS coefficient higher. These combined effects made this sample the most optimal for demonstrating the sensing capability of PS coatings.19,22

FIG. 5.

Stress sensing the OHT CFRP specimen with 20 % volume fraction PS coating with progressing loads. This specimen consists of a composite substrate with soft laminate. Each map has dimensions of 25.4 mm × 25.4 mm.

FIG. 5.

Stress sensing the OHT CFRP specimen with 20 % volume fraction PS coating with progressing loads. This specimen consists of a composite substrate with soft laminate. Each map has dimensions of 25.4 mm × 25.4 mm.

Close modal

Map scans of the OHT CFRP specimens with 5 %, 10 % and 20 % volume fraction of α-alumina were taken after failure. Figure 6 shows the post failure peak shift maps for the specimens.

FIG. 6.

Contour maps with corresponding images of the OHT CFRP specimens showing peak shifts for (A) 5 %, (B) 10 % and (C) 20 % volume fraction PS coatings. Each map has dimensions of 40 mm × 40 mm. Also, note that “VF” is volume fraction.

FIG. 6.

Contour maps with corresponding images of the OHT CFRP specimens showing peak shifts for (A) 5 %, (B) 10 % and (C) 20 % volume fraction PS coatings. Each map has dimensions of 40 mm × 40 mm. Also, note that “VF” is volume fraction.

Close modal

The peak shift map for each PS coating configuration in Figure 6 shows mostly uniform residual stress after substrate failure in the unloaded condition. The peak shift maps from Figures 4 and 5 indicate a changing stress state around the hole for all three specimens. The peak shift maps for the 5% and 10% volume fractions in the post failure condition indicate that the relaxed stress state at the fractured surface is retained, which indicates that cracking has occurred in the composite at this location. The peak shifts from the 20% volume fraction are not clear in comparison due to sustained larger deformations and more significant damage around the hole and the coating from the load tests in comparison with the hard laminate specimens.

This study demonstrated that the sensing capability of the PS coatings can be designed and tailored. Notable differences in capturing the stress variations that correlate with the presence of crack initiation and propagation in each OHT CFRP specimen were observed in the PS maps. For the hard laminates, the 10 % volume fraction PS coating showed more sensitivity than the 5 % volume fraction PS coating due to it having higher SNR. Comparing the PS maps for the hard laminates and the soft laminate, the stress contours are more clearly observable for the PS coating on soft laminate with lower applied loads since it has more ±45° fibers than the hard laminate. The PS maps for the 20 % volume fraction PS coating show more features than the rest of the coatings due to it having the best median SNR and highest volume fraction of nanoparticles; and due to the soft laminate experiencing more progressive damage before failure than the hard laminate. However, it was observed that the 10 % volume fraction PS coating had a larger peak shift than the 20 % volume fraction PS coating, despite having a lower PS coefficient. Since the 10 % volume fraction PS coating retains the stress sensitive properties and has lower volume fraction of α-alumina, this configuration may be ideal for simplifying the manufacturing process. A novel conclusion is that very significant qualitative differences observed between the hard and soft laminates suggest that the PS coatings can detect different failure modes that are specific to the substrates’ laminate type. Other factors were considered when determining the necessary attributes for an effective PS coating. One factor is luminosity, which is independent of substrate type and one of the attributes that makes the 20 % volume fraction PS coating more appealing. Another factor that was considered is the feasibility of manufacturing the coating and creating a homogeneous particle dispersion. Peak shifts indicating that relaxed stress state at the fractured surface is retained was more distinctive on the post failure peak shift maps for the 5 % and 10 % volume fraction PS coating than for the 20 % volume fraction PS coating. Current work is focused on improving the optics and materials technology for better efficiency and sensitivity. Future work will focus on investigating coating degradation under various environmental conditions, studying the different substrate laminate types with a consistent volume fraction, and investigating ways to manufacture a PS coating with uniform particle dispersion while maintaining the desirable attributes for stress sensing. While visual inspection does not show any distinct sign of coating delamination in the areas where the fibers were still intact, further inspection of the coating can be done to determine whether damage was induced on it during and after load tests. Future efforts will relate the peak shifts to the substrate stress using multiscale modeling. To assess the effect of varying particle volume fractions on stress sensitivity, the PS coefficients will be determined empirically with additional calibration experiments. These coefficients, along with the SNRs, will be used to determine the stress uncertainty to further evaluate particle volume fraction effectiveness.

The Boeing Company is acknowledged for their assistance with experiments. This work was supported by the National Science Foundation under Grant Nos. IIP 1701983 and CMMI 1130837.

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