**1. Introduction**

Plastics are a versatile class of materials which can be found in products ranging from single-use packaging to components used in automotive and durable goods. Unfortunately, plastics are also identified as an environmental pollutant due to poor recycling rates and poor end-of-life waste management [1, 2]. This has led to many organizations, such as the Ellen MacArthur Foundation, to promote a circular economy for plastic [3].

The circular economy for plastic is based on three tenets: reducing the use of plastics, reusing a product multiple times and recycling at end of life. The first two components are directed more toward plastic packaging but recycling at end of life can be applied to all types of products and industries. Post-consumer recycled (PCR) resin is the recycled product of waste created by consumers and is defined by ISO 14021 [4]. It is commercially available from multiple suppliers, but not all grades are created equal. However, there needs to be a demand for recycled plastics for the circular economy to work properly. Regrettably, there is a misperception that recycled plastics are always inferior to virgin plastics and therefore can only be used in "down-cycled" applications. As engineers and scientists interested in both the production of high-quality products and environmental sustainability, we questioned the validity of this misperception and initiated this study to answer the following questions:


Although there are many factors associated with completely answering the questions above, the factor which we will be evaluating in this paper is strength. Strength of plastics can be quantified by measuring tensile, bending, shear, compression, flexural, and impact properties, among others. Each molded plastic resin's mechanical properties can vary depending on molecular weight, crystallinity, molding parameters, and additives/fillers. The mechanical properties can be defined by testing specimens in compliance with ASTM [5, 6] or ISO [7] testing standards. The advantages of mechanical property testing following ASTM or ISO testing standards are

A. Standard specimens can be obtained from material supplier


Since a plastic's strength degrades over time as it ages in the environment, it is crucial to take this degradation into account when designing parts. Therefore, the aging behavior of plastics needs to be understood thoroughly. As real-time aging can take a significant time (i.e., years), most aging studies are performed using accelerated aging tests utilizing temperature, temperature and humidity, temperature cycling, UV exposure, and/or chemical exposure [8]. The Arrhenius-based accelerated life model is the most popular model to understand the acceleration of aging due to temperature. The rate of reaction, *R,* based on the Arrhenius model can be explained by

$$R(T) = A e^{-\frac{E\_a}{kT}} \tag{1}$$

where *A* is a material constant; *Ea* is the activation energy (eV), *K* is the Boltzmann's constant (eV/K), and *T* (K) is the absolute temperature. Based on this model, the acceleration factor (AF) can be calculated as

$$AF = \exp\left[\frac{E\_a}{K}\left(\frac{1}{T\_u} - \frac{1}{T\_t}\right)\right] \tag{2}$$

where,

Tu is unit localized temperature during field usage (K).

Tt is unit localized temperature in the test (K).

*Effect of Environmental Aging on Tensile Properties of Post-Consumer Recycled (PCR)… DOI: http://dx.doi.org/10.5772/intechopen.99528*

Ea is activation energy.

K is Boltzmann's constant (8.617385 x10–5 eV/K).

The acceleration factor for temperature and humidity-based acceleration is derived from Peck's Model:

$$AF = \left(\frac{RH\_u}{RH\_t}\right)^{-n} \exp\left[\frac{Ea}{k}\left(\frac{1}{T\_u} - \frac{1}{T\_t}\right)\right] \tag{3}$$

where,

RHu is relative humidity in field (%).

RHt is relative humidity in the test (%).

n is a constant.

Finally, the acceleration factor for aging due to thermal cycling comes from the modified Coffin-Manson model:

$$AF = \left(\frac{\Delta T\_{test}}{\Delta T\_{field}}\right)^m \tag{4}$$

where,

ΔTtest = temperature difference in TC test (°C);

ΔTfield = temperature difference in field usage (°C);

m = Coffin-Manson exponent.

Any acceleration-based model depends on the distribution of the data that best fits. The life of a consumer product follows a bathtub curve under variable stress and can be explained better by the Weibull distribution, for which the probability density function can be explained as

$$f(t) = \frac{\beta}{a} \left(\frac{t-\gamma}{a}\right)^{\beta-1} e^{-\left(\frac{t-\gamma}{a}\right)^{\beta}}\tag{5}$$

where β is the shape parameter or slope of the curve, α is the characteristic orWeibull life, and α is the location parameter. This is true for 3 parameter Weibull distribution. Typically, γ is considered to be zero and hence the equation can be derived as

$$f(t) = \frac{\beta}{a} \left(\frac{t}{a}\right)^{\beta - 1} e^{-\left(\frac{t}{a}\right)^{\beta}} \tag{6}$$

In this chapter, the scope of the research is to focus on the performance variation of different grades of PCR compared to conventional or virgin PC after thermal cycling and high temperature & high humidity aging. The reason behind picking thermal cycling and high temperature & high humidity aging is because these two are the most common environmental exposures for consumer hardware. The effects of chemical, UV and solar aging will be reported at a later date.
