Open Access Article
Robert D.
Nedoluha
,
Majed N.
Saadawi
and
Christopher W.
Barney
*
School of Polymer Science and Polymer Engineering, 250 S Forge St, Akron, OH 44325, USA. E-mail: barneyc@uakron.edu; Tel: +1(330)972-4297
First published on 4th August 2025
Poisson's ratio (ν) is a materials property that quantifies the compressibility of a material. Measurements of this property become important for soft elastomers which display nearly incompressible behavior (ν > 0.495). Small differences in this property can lead to large differences in the stresses that develop during hydrostatic loadings such as those observed in gaskets, o-rings, and thin films. While there are multiple methods that can be used to quantify ν, many methods were developed for compressible materials which require less precision than nearly incompressible materials. Here an experimental survey of three methods of characterizing ν of a nearly incompressible elastomer is performed. These methods include direct measurement via digital image correlation, indirect measurement from the bulk modulus and Young's modulus, and a recently proposed method of indirect measurement from the shear modulus and Young's modulus. Particular care is paid towards understanding how experimental errors impact both the precision and accuracy of each method. It is found that indirectly measuring ν from the bulk modulus and Young's modulus is the most appropriate method for distinguishing nearly incompressible behavior from the incompressible limit (ν = 0.5).
While measuring the Poisson's ratio of nearly incompressible materials is important, it is also challenging. One challenge is that as a material approaches the incompressible limit, an increase in the precision of the measurement technique is needed to meaningfully characterize this property. In the infinitesimal strain limit, Poisson's ratio can be defined as the negative of the ratio between the transverse and axial strains during uniaxial extension.5 Using this definition and assuming stretching is applied in the 1 direction gives,
| εvol = ε1 + ε2 + ε3 = ε1(1 − 2ν), | (1) |
![]() | (2) |
which is only distinguishable from the 0.5 limit with a measurement error of 0.0001 or less. For compressible materials (ν < 0.495), resolving ν to the fourth decimal point is unnecessary and measurements with lower precision can be performed. This implies that nearly incompressible materials need to be matched with measurement techniques that provide sufficient resolution to characterize Poisson's ratio as it approaches the limiting value of 0.5.
Methods developed to characterize ν largely fall into two categories. Direct methods include techniques where ν is directly quantified from the deformation of a material during loading. This category includes techniques such as digital image correlation (DIC),9–13 strain gauge analysis,14–16 and dilatometry.17,18 Indirect methods include techniques that infer the value of ν from the measurement of at least two elastic moduli. This category includes techniques such as pressurization19–22 to measure K combined with separate measurements of either E or the shear modulus μ,23–25 radially confined compression (RCC)2,8,24–27 to measure K combined with a separate measurement of E, and an emerging trend28,29 of combining measurements of E and μ to infer ν. The methods used in this work measure low strain values of Poisson's ratio and have varied sensitivity to experimental errors.
Reported values of the error for each of these methods is displayed in Fig. 1 where 0.5 − Δν is plotted against the measurement error Δν. This compiled literature data is summarized in the SI. Note that these literature values are gathered on materials with varied chemical compositions and should thus have different values of ν. The black line on which this data falls represents the maximum value of ν that is distinguishable from the incompressible limit of 0.5 as a function of measurement error. As is apparent in Fig. 1, RCC and pressurization offer the highest levels of resolution. The next most precise method is dilatometry which occupies a large range of 2–4 decimal points of resolution. DIC follows this method with the ability to resolve 2–3 decimal points of ν. Strain gauge analysis appears to measure ν out to 2 decimal points. Finally, the emerging trend of inferring ν from measurements of E and μ can resolve 1–2 decimal points. Notably, the reported values for inferring ν from E and μ have all been generated from measurements in different setups (e.g. combining data from tensile tests and rheology28 or tensile tests and lap shear tests29) and have not been attempted in a single setup. Based on this, we aim to infer ν from measurements of E and μ on a single sample and compare this to the resolution of other methods for quantifying ν of nearly incompressible elastomers.
![]() | ||
| Fig. 1 Plot showing 0.5 − Δν vs. Δν from literature data for RCC,7,8,24,25 pressurization,23–25 DIC,9,11,12 strain gauge analysis,30 dilatometry,17,30 and inferred from E and μ.28,29 | ||
Achieving this aim will require selecting several different methods to characterize ν. The first method presented is DIC during uniaxial extension as it is a highly accessible method that is similar to strain gauge analysis. The second method presented is to infer ν from measurements of K and E. In this work, RCC is used to measure K as previous works24,25 have concluded that pressurization and RCC offer similar resolutions while RCC requires less specialized instrumentation. Dilatometry will not be performed in this work as it requires specialized instrumentation and spans a range of precision already covered by RCC and DIC. The final measurement method will exploit a combined tension and torsion tester to measure E in tension and μ in torsion on a single sample. All three methods are performed on the same commercially available rubbery crosslinked silicone elastomer that neither flows at long time scales nor exchanges mass with the surrounding environment. Such materials are known to be nearly incompressible (ν > 0.495)8 and are a reasonable model for this analysis. A comparison of all three of these methods including a discussion of the observed error associated with each technique is presented at the end. Note that these methods characterize the low strain elastic behavior of materials. These findings have strong implications for characterizing the mechanical response of gaskets, o-rings, and thin coatings.2,26,31
:
1 prepolymer
:
curing agent. Samples were manually mixed and then degassed under vacuum before being poured into either 4 inch square Petri dishes for the DIC, indentation, and RCC samples or 3 mL disposable plastic syringe barrels with torch sealed tips for the tension/torsion samples. The samples were subsequently cured at 70 °C for 21 hours after which they were removed and allowed to cool at room temperature for 5 days before any tests were performed. Cylinder samples were removed from the syringe barrel by first scoring the barrels with a Micro-Mark WonderCutter S and then pulling apart the barrel until it split in half. No visual indication of damage was observed on the cylinder surfaces. Samples for indentation were prepared by cutting out a square inch sample from the cured film. After indentation, RCC samples were prepared by punching out disks with a 5 mm diameter punch from this square inch film. A disk from this film was used to perform the compressional DMA described in the SI. Rectangular samples for uniaxial extension were cut from the same film source as the indentation sample.
was used to calculate E from,34![]() | (3) |
RCC was performed by compressing disks in a 5 mm diameter pellet die sourced from MSE Supplies and used as received. Samples were punched out with a 5 mm diameter punch (exact dimensions in SI) and loaded into the pellet die before the pellet die was loaded onto an Instron 5567 universal testing machine. The Instron was equipped with 100 kN capacity compression platens and a 30 kN force capacity load cell. Samples were tested by indenting at a rate of 1 μm s−1 (0.0005 s−1) to a turnaround force of 4000 N, which translates to a max pressure of ∼0.2 GPa. An instrument stiffness of 31.6 MN m−1 was measured in a run without a sample loaded into the die and this value was used to correct the observed displacement.
![]() | ||
Fig. 2 (a) Images showing the stretching of rectangular strip with DIC overlay. (b) Plot of vs. ε1 used in the DIC ratio method. (c) Log–log plot of (λ2)−1vs. λ1 used in the DIC scaling method. | ||
ν can be estimated from the DIC data through one of two different methods. The first method takes advantage of the small strain definition of ν where,
![]() | (4) |
is plotted against ε1. This ratio was directly calculated and averaged across all grid points with the error bars being calculated as the standard deviation of this distribution as has been done by others.9 Notably the error bars are large in the low strain regime where the displacements are similar in scale to the errors from DIC. The inset plot shows that, consistent with prior observations,29
decreases as ε1 increases. This reduction results from a failure of the small strain definition of ν, not from an increase in the compressibility of the material. As shown in the SI,
should decrease at large strains for an incompressible material. Given the large errors that occur below ε = 0.05, the value of ν was calculated as the intercept from a linear extrapolation of the larger strain data. This fitting protocol from the direct ratio definition gives ν = 0.48 ± 0.02 when averaged across five samples.
A second method for measuring ν from DIC data uses a larger strain definition30 where,
![]() | (5) |
Notably, the direct ratio method results in an uncertainty value of Δν = 0.02 which is larger than the uncertainty value Δν = 0.005 observed with the scaling method. These uncertainty values set the number of significant figures with which ν should be reported. As is apparent from these values, the direct ratio method can quantify ν to two significant figures while the scaling method can report ν to three significant figures. This is consistent with the literature data in Fig. 1 which showed that reported DIC values of ν for nearly incompressible elastomers span a range of 2–3 significant figures. Ultimately, the difference in resolution between the two methods suggests that the scaling method is better at quantifying ν of nearly incompressible elastomers.
![]() | (6) |
Indentation was used to measure E as described in Section 1.3 and gave an estimate of E = 2.27 ± 0.08 MPa. Note that E can be measured in different ways and indentation was selected here, instead of another method such as uniaxial extension, as it is non-destructive and can be performed on the film used to punch out RCC disks. RCC was used to measure K and an image of the pellet die loaded into the compression setup is shown in Fig. 3a. A plot of the imposed displacement vs. time is shown in Fig. 3b. Note that the raw data reported by the Instron has been corrected for the deflection of the instrument by measuring the stiffness of the setup without a sample loaded into the pellet die. This stiffness was found to be 31.6 MN m−1 and the displacement was corrected by taking the raw displacement and subtracting the force divided by the instrument stiffness.
An example plot of force vs. displacement is shown in Fig. 3c for both the raw data and corrected data. Positive forces on this graph are compressive. Note that hydrostatic compression does not occur until full compaction of the material in the die. Once full compaction occurs K can be calculated as,7,8
![]() | (7) |
![]() | (8) |
is the slope of the stress vs. strain curve. This measurement gave K = 4.2 ± 0.3 GPa averaged across five samples. When combined with E, the measurements of K give ν = 0.49991 ± 0.00001 averaged across five samples. This value shows that, consistent with the literature data in Fig. 1, RCC can provide an incredibly precise measurement of ν out to five significant figures.
The error associated with inferring ν from E and K can be understood by propagating the uncertainty from the moduli measurements. Derived fully in the SI, doing this yields,39
![]() | (9) |
. Since E and K have different physical origins and are orders of magnitude apart, very precise measurements of ν can be inferred from this method. For example, eqn (9) predicts that the measurements in this work result in Δν = 0.00002 which is in good agreement with the value calculated directly from the distribution of ν values. Based on this, it is clear that inferring ν from E and K provides a much more precise measurement than either of the DIC methods presented previously.
![]() | (10) |
In this work, inferring ν from E and μ is given its best chance of working by performing both moduli measurements on the same sample instead of combining measurements from different setups as was done in previous works.28,29 Here that is accomplished by using a combined tension and torsion tester to first stretch the samples and then twist the samples. Note that the uniaxial extension measurements used here to characterize E are distinct from the indentation measurements used in the previous section. Images of this testing protocol can be seen in Fig. 4a. Plots showing displacement vs. time and angle vs. time are shown in Fig. 4b and d, respectively. These plots show that first the sample is subjected to uniaxial extension before unloading. E is measured as the low strain slope on the loading curve as can be seen on a plot of stress vs. stretch in Fig. 4d. These measurements give E = 2.47 ± 0.14 MPa across five samples. This E value shows reasonable agreement with the value of E = 2.27 ± 0.08 MPa measured via indentation.
After the tension is removed from the sample it is twisted to apply torsion. μ is measured as,40
![]() | (11) |
is measured from a plot of torque vs. angle as shown in Fig. 4e and gives μ = 0.79 ± 0.07 MPa measured across five samples.
Note that the values of ν were not calculated from the averaged moduli values. Instead each sample's measurement of E and μ was used to directly calculate an estimate of ν as can only be done when both measurements are performed on the same sample. Doing this, gives ν = 0.56 ± 0.09 when ν is then averaged across five samples. The observation that Δν = 0.09 is consistent with the literature reported values shown in Fig. 1.
Table 1 contains a summary of the observed values of ν for all of the methods presented in this work. This data is plotted in the SI. This data suggests that inferring ν from μ and E is the worst possible method while inferring it from K and E is the best possible method. This difference in precision between the two methods can be understood by propagating the error,39 as shown fully in the SI, from the moduli measurements to get,
![]() | (12) |
. Given that
when ν = 0.5, the error that propagates from the measurement of μ and E will increase by a factor of 1.5 through this method. This in stark contrast to the previous section where the propagated error was reduced by orders of magnitude. This implies that reasonable measurements of μ and E can result in large errors for ν. For example, plugging the values in this section into eqn (12) gives Δν = 0.16. While there appears to be less error when Δν is directly calculated from a distribution of ν this is only possible when performing measurements on a single sample as is done in this work. Regardless, the fact that this method only gives one decimal point of resolution means that the value of Poisson's ratio for nearly incompressible elastomers cannot be meaningfully inferred from measurements of μ and E.
| Method | ν |
|---|---|
| DIC (ratio) | 0.48 ± 0.02 |
| DIC (scaling) | 0.493 ± 0.005 |
| Inferred from K and E | 0.49991 ± 0.00001 |
| Inferred from μ and E | 0.56 ± 0.09 |
The first step towards addressing this question comes in remarking on the fact that every experimental measurement is associated with some amount of error. This variability results in a distribution of values that are measured. While replicates are typically run in lab, measurements only sample a subset of this distribution of values. The hope is that the reported mean and standard deviation of this sampling is representative of the “true” value of the measured property. This means that the sensitivity of a measured value of ν to experimental errors can be quantified by assuming a “true” value of ν. For example, assuming the “true” value of ν is the incompressible value of 0.5 gives,
![]() | (13) |
term quantifies how far the observed value of ν is from the “true” value of 0.5 for a given error level. C represents the cumulative error that results from combining the individual errors of the measured values of ε1 and ε2. A similar analysis can be performed for the scaling DIC method and gives,![]() | (14) |
This analysis can be further extended to the indirect calculation methods. If a true value of ν = 0.5 is assumed then
which gives,
![]() | (15) |
![]() | (16) |
Both of these equations are plotted in Fig. 6. This plot shows that the observed value of ν = 0.56 for inferring from μ and E would only require C ≈ 4%. Further, it can be seen on this plot that this method is the most susceptible method to cumulative error. Notably, it only takes a cumulative error of 10% to see an apparent value of ν = 0.35 which likely explains some of the more extreme values reported in the literature.28 On the other hand, a cumulative error of 100% only decreases the apparent value of ν to 0.49965 when inferring it from measurements of K and E. This demonstrates that inferring ν from measurements of K and E is a superior method for nearly incompressible materials that demand both high accuracy and high precision. All other methods presented in this work lack the precision and accuracy to meaningfully distinguish values of ν in the nearly incompressible regime (ν > 0.495) from the incompressible limit of ν = 0.5. Further, future researchers attempting to measure ν for nearly incompressible materials need to carefully consider the impact that cumulative errors have on their measurement of Poisson's ratio.
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| Fig. 6 Plot showing how cumulative error can shift the apparent value of ν when inferring it from moduli measurements. | ||
SI videos, compiled literature data, derivations of equations, and further experimental details. See DOI: https://doi.org/10.1039/d5sm00535c
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