Vinyl acetate

For evaluating the flame retardancy performance of polymers, one may need to visualize the hidden phenomena behind fire scenarios. For example, THR has a unit of energy, but TTI is the time scale that demonstrates the resistance of the system against the appearance of flame at the initial stage of a fire. Therefore, they are inherently of a different nature and cannot be considered alone or in combination as a good criterion for evaluating the flame retardancy of thermoplastic composites. The other difficulty with measuring fire retardancy performance is that the situation of interaction of additives with polymers is always unknown. Hirschler [6 (link)] defined “Fire Performance Index”, FPI, in brief, as the ratio of the TTI to the pHRR having the unit of sm²/kW. The FPI appeared as a first-order indicator of tendency to flashover. The higher FPI values could principally specify a higher fire retardancy performance when a higher numerator, a lower denominator, or both moving in the aforementioned directions could be observed. A lower pHRR was simultaneously required for achieving higher performance levels. A wide variety of systems have been studied and concluded that such an approach would be a good measure for flame retardancy assessment. Nevertheless, one may need a simpler way to evaluate the function of flame retardants used in thermoplastic composites, such as a dimensionless criterion which could eliminate the need for simultaneous evaluation of two different measures with their own dimensions each reflecting a complexity of explanation. The new criterion had to be simple, universal, including three main parameters (pHRR, THR and TTI), and critically dimensionless to image the fingerprint of fire in a given thermoplastic composite.
To develop the idea that a universal dimensionless index is necessary, there is a perquisite to distinguish one thermoplastic composite from the other in terms of flame retardancy performance. Following the first steps taken in the aforementioned study, the plot of THR (MJ/m²) (Y-axis) versus pHRR/TTI (kW/m².s) (X-axis) could be considered as a new pattern of fire retardancy performance. The lower X and Y axes were looked for when expecting a higher performance from a thermoplastic composite. In this sense, a huge body of literature was searched to find thermoplastic composites in which only one kind of additive was used. To give the research a versatile character, four types of polymer matrices were selected among different families of thermoplastic: polypropylene (PP) as a commodity highly flammable polymer, poly(methyl methacrylate) (PMMA) as an engineering polymer, poly(lactic acid) (PLA) as a biopolymer, and poly(ethylene-co-vinyl acetate) (EVA) as an emerging polymer widely used in the cable industry. Table 1 summarizes the whole data extracted from the literature on cone calorimetry features of selected systems.
The variations of THR versus pHRR/TTI for the composites based on PP, PMMA, EVA, and PLA are then presented in Figure 2. This figure visualizes the actions of additives of different types and families in the aforementioned thermoplastic matrixes for evaluating the flame retardancy behavior of composites. Two points should be cared when using these plots. First, since data are picked out from different sources considering the limited access to reports in which the desired cone calorimetry data could be extracted from, each plot for the assigned thermoplastic contains several symbols denoting the mentioned neat polymer. The diversity of flame retardancy levels of neat polymers in each plot is an indication of the difference in flame retardancy of the selected polymer matrix in terms of molecular weight and viscosity obviously controlled over flame retardancy behavior of the specified thermoplastic. Second, the distribution pattern of flame retardancy of thermoplastic composites featured by THR (MJ/m²) and pHRR/TTI (kW/m².s) in any specified case can be detected with symbols of spread positions in the area of the plot that can be noticed as a signature of complexity of the behavior of system against fire. The mauve arrows in the plots represent the direction toward which a desired flame retardancy improvement was likely to ensue. When THR and pHRR/TTI together take a low value, the desired flame retardancy will be recognized. However, the comparison is qualitative and there is no measure for quantifying the performance of systems. In other words, the unanswered question remaining with such a qualitative plot is: “Which polymer matrix or flame retardant additive would be the best choice?” The main complexity of providing an answer to the above question is that the very broad distribution of symbols (assigned to additives marked in each plot) gives a complex nature to the performance of flame retardant additives, each with its own hidden effect on the fire behavior of the system, and they cannot explicitly be held responsible for their actions.
Here, we define and put into practice the "Flame Retardancy Index”, FRI, as a simple yet universal dimensionless index in terms of pHRR, THR, and TTI. The FRI was defined as the ratio of $\mathrm{THR}*\left(\frac{\mathrm{pHRR}}{\mathrm{TTI}}\right)$ between the neat polymer and the corresponding thermoplastic composite containing only one flame retardant additive: $Flame Retardancy Index \left(FRI\right)=\frac{{\left[\mathrm{THR}*\left(\frac{\mathrm{pHRR}}{\mathrm{TTI}}\right)\right]}_{\mathrm{Neat}\mathrm{Polymer}}}{{\left[\mathrm{THR}*\left(\frac{\mathrm{pHRR}}{\mathrm{TTI}}\right)\right]}_{\mathrm{Composite}}}$
In principal, it is expected that by introducing the flame retardant additive and dividing the term calculated for the neat polymer to that of the thermoplastic composite, a dimensionless quantity greater than 1 is obtained. This operation and incorporation of a neat polymer value in the FRI formula lets us compare the different systems regardless of the nature of the used polymer in terms of molecular weight or viscosity. Having this in mind and by calculating FRI for reliable data on thermoplastic systems given in Table 1, we defined “Poor”, “Good”, and “Excellent” fire retardancy features assigned to well-classified ranges of FRI quantities colored in red, blue, and green, respectively (Figure 3). Classically saying, the quality of the flame retardancy performance can be assigned to the quantitative levels defined below in terms of ranges in FRI values (Figure 3). It is expected to see the value of 10⁰ from Equation (1) as the low limit for flame retardancy performance below which the addition of a flame retardant additive is not reasonable. This is representative of a system in which the addition of a flame retardant additive inversely affects performance. Therefore, FRI < 1 is taken as the lowest level of flame retardancy symbolized as “Poor” performance. Since data are gathered from a variety of reports in which different polymers (PP, PLA, PMMA, and EVA) filled with different amounts of various additives are included, the trend in the variation pattern of FRI can be considered as a snapshot of the behavior of thermoplastic composites when subjected to fire. From Figure 3A it can be observed that FRI values up to 10¹ (1 ˂ FRI ˂ 10) are the most probable case, which are nominated as the “Good” zone colored in blue. A closer view of “Poor” and “Good” situations is provided in Figure 3B. The majority of FRI values calculated by Equation (1) are located in between 1 and 10. Moreover, in contrast to our initial expectation, some FRI values took quantities below 10⁰. This suggests that flame retardants can also contribute to combustion and, therefore, even in the presence of a flame retardant, the flame retardancy of a polymer can be worsened. The FRI values between 10¹ and below 10² (10 ˂ FRI ˂ 100) are labeled “Excellent” and are distinguished by a green background in Figure 3A. Three points are located in the excellent flame retardancy zone. These systems contain EVA and expanded graphite [12 (link)] or zinc borate [11 (link)]. Expanded graphite is well known as a conventional flame retardant that acts on the barrier effect of a formed char, in terms of quality and quantity, during the combustion. It can also change the thermal conductivity of a polymer. Its incorporation into polymer leads to the increase of thermal conductivity and, therefore, to the dissipation of heat at the surface of the polymer. It is worth mentioning that the loading percentage of expanded graphite is unusually and extremely high for this type of flame retardant in the aforementioned study [12 (link)]. Zinc borate is a char promoter and during the degradation, forms compact char, which protects the underlying polymer from fire. Once again, in this study, the incorporation percentage of zinc borate is higher than the usual quantity [24 (link)].
The dimensionless index nominated as FRI is useful for the comparative evaluation of the flame retardancy performance of thermoplastic systems regardless of the types of polymers and additives used. However, for now, this index is only adapted to simple fire scenarios where one peak of HRR appears during combustion. More complex fire scenarios can happen when two or more pHRR are compared to a second curve. In that case, one may need a high flame resistance rather than flame retardancy and, therefore, the char quantity and quality should be meticulously considered as well.

Body temperature was recorded during three winter seasons (2009/10, 2012/13, 2013/14) using temperature data loggers (iButtons, DS1922L-F5#, range: −40 to +85 °C, accuracy: ±0.5 °C, Maxim Integrated Products International, Dublin, Ireland). The iButtons (coated in Elvax ethylene vinyl acetate resins, DuPont, and paraffin, gas-sterilised; potted mass: ~4.5 g) were implanted subcutaneously in the neck region (dorsal, between the scapulae). This method has proved successful in this species due to the absence of pronounced prehibernation fattening (Hufnagl et al. 2011 ; Lebl and Millesi 2008 ). Individuals were trapped in the early morning hours and transported (~20 min) to a veterinary clinic where the implantation was done under isoflurane anaesthesia. When the animals had recovered from anaesthesia, they were returned to the field site and released at their burrows, i.e., about 1–2 h after trapping and still within their daily morning activity period (Schmelzer and Millesi 2005 ). In total, we implanted 36 hamsters with iButtons. The burrows of the implanted individuals were monitored weekly during winter (open/closed) to detect potential activity. None of the individuals showed signs of above-ground activity until mid-March. Starting in early March, burrows of implanted individuals were checked at daily intervals, active hamsters were recaptured, and the data loggers were removed using the above-mentioned techniques. We were able to recover iButtons of 28 individuals (recovery rate: 78 %). None of the recaptured animals lost the data logger during winter, but two iButtons failed (one of an adult male and one of an adult female). Thus, temperature data of five adult males, seven adult females, eight juvenile males, and six juvenile females were analyzed in this study. Body mass and overwinter survival rates of implanted individuals did not differ from untreated ones of the same age and sex (Siutz et al. unpublished data). Emergence date was defined as the date when an individual was observed above ground or trapped for the first time (this was also the day when an individual removed its burrow plug). Emergence body mass was used for analysis when measured within 1 week after the individual’s vernal emergence date. Mass changes over winter were calculated as percentage of differences between immergence and emergence body mass.
Body temperature was recorded at 90-min intervals from autumn until recapture of individuals in spring. Torpor bouts were defined as multiday periods of reduced body temperature between two arousals, from the sampling interval when body temperature started to continuously decrease from 30 °C to at least 15 °C until it had reached 30 °C again. To analyze hibernation patterns, we defined the following parameters: hibernation onset (date of the first torpor bout), duration of post-immergence euthermy (days spent euthermic after immergence until hibernation onset), number of torpor bouts, mean torpor bout duration (calculated in hours, expressed as days), time spent in torpor (total duration of all torpor bouts, calculated in hours, expressed as days), mean arousal bout duration (calculated in hours, expressed as days), hibernation end (date of the last torpor bout), hibernation duration (days from the onset of the first and termination of the last torpor bout), and duration of preemergence euthermy (days spent euthermic after termination of the last torpor bout until vernal emergence).

Copper sulfate pentahydrate was obtained from El-Goumhouria Co., Cairo, Egypt. Ascorbic acid was obtained from Merck Chemical Co., Germany. Tween 80 surfactant (T80) was obtained from MP Biomedical Co., India. Low density polyethylene pellets were obtained from El Sewedy Plastic Manufacturing (SEDPLAST), Tenth of Ramadan City, Cairo, Egypt. Ethylene vinyl acetate containing 18% of vinyl acetate was obtained from Arkema Inc., North America. Bidistalled water was utilized throughout the preparation steps.

All chemicals in this study were obtained from commercial sources and did not require further purification. Lipase TL IM form Thermomyces lanuginosus was purchased from Novo Nordisk. Adenosine was purchased from Macklin (Shanghai, China), inosine was purchased from Accela (Shanghai, China), 6-chloropurine nucleoside was purchased from Aladdin (Shanghai, China). Vinyl acetate was purchased from SCRC (Shanghai, China), vinyl laurate from Aladdin (Shanghai, China), vinyl palmitate and divinyl adipate from TCI (Tokyo, Japan). Harvard Instrument PHD 2000 syringe pump was purchased from Harvard University (Holliston, MA, USA). The flow reactor and Y-mixer were purchased from Beijing Haigui Medical Engineering Design Co., Ltd. (Beijing China). A 400 MHz NMR spectrometer (Billerica, MA, USA) were also used in this study.