*2.1. Plant Material and Sample Preparation*

"Italia" table grapes were grown in Foggia (Puglia, Italy, 41◦28 39.2 N), in 2 contiguous vineyards of the same grower, but with plants of 2 different ages, 4 and 14 years. The vegetative system consisted of the "tendone" which was covered with a plastic net and a plastic film of LDPE. Grapes were harvested randomly from 12 marked plants in October, when according to the grower procedure, the commercial maturity was reached. Grapes were rapidly transported to the Postharvest Laboratory of the University of Foggia where clusters were divided into smaller clusters. Three replicates of 400 g were used for initial quality determinations while 18 samples of the same size were prepared for storage in air in macroperforated bags (AIR) or in modified-atmosphere packaging (MAP). For MAP, 9 samples were packaged in polypropylene (PP) trays sealed with a PP/PA film (polypropylene/polyamide, 30 μm, with CO2 transmission rate of 48 mL·m−2 day and O2 transmission rate of 135 mL·m−2 day) in active modified-atmosphere (20% CO2 in air) using a semi-automatic tabletop tray sealer (ILPRA termosaldatrici, FoodPack, Vigevano, PV, Italy). For AIR treatment the trays were wrapped in macroperforated bags containing wet paper pads to keep a high-RH environment around the product. Three replicate trays were prepared for each treatment and sampling time, with a total of 18 trays. All samples were stored at 0 ◦C for 28 days. After 8, 21, and 28 days of storage, 3 trays for each treatment (MAP and AIR) were used for quality determinations together with samples freshly harvested from the 12 marked plants (PLANT).


**4. Conclusions**

Extinctions driven by deterministic factors are present in the ecosystems globally as a result of direct and indirect human effects. Both terrestrial and marine habitats are overexploited under the ever-growing human pressure. Considering environmental factors, species living at low elevations, low and high latitudes and/or in suboptimal habitats (e.g. at the peripheries of historical species ranges) are under greater threat than rest of the world. At the species level, K-selected species, especially large-bodied species, specifically large herbivores, carnivores are becoming rare mainly due to extensive hunting. Species adapted to a narrow range of temperature will probably collapse quickly, especially if they are not mobile, because of rapid climatic change. Seasonal changes in precipitation and temperature affect several ecosystems all around the world. Both grasslands and forests are suffering experiencing biodiversity and/ or biomass loss and collapses [91]. Hidden failures, which are revealed only during significant changes in environmental conditions, will enhance collapses. Endemic, rare and weak dispersing species in regions with the largest and quickest climatic changes will probably die out. At the community level, positive species interactions are already melting because of the high number of species loss. Species interactions and functions are disappearing. The abundance of predators has decreased dramatically because of overhunting. Small mammal population cycles are collapsing as a result of climate change. Populations experiencing Allee effect will probably have a tendency to collapse under climate change. Common species are becoming rare, which decreases resilience and increases the vulnerability to collapse. Studies show that abundant species are one of the most persistent, except in case of specialization. The extinction of abundant species can be followed by co-extinction and rapid collapse. Literature suggests that many keystone species have deterministic species traits, which can lead ecosystems to a sudden collapse. Further consequences of human activities in the ecosystems are genetic changes, hybridization, invasion, pathogens, shorter food chains, altered trophic structure, disrupted species interactions and general homogenization.

[3] The IUCN Red List of Threatened Species. n.d. Available from: http://www.iucnredlist.

Characteristics of Collapsing Ecosystems and Main Factors of Collapses

http://dx.doi.org/10.5772/intechopen.75124

31

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[5] Burgess SD, Bowring S, Shen S. High-precision timeline for Earth most severe extinction. Proceedings of the National Academy of Sciences. Mar 2014;**111**(9):3316-3321. DOI:

[6] Gill JL, Williams JW, Jackson ST, Lininger KB, Robinson GS. Pleistocene megafaunal collapse, novel plant communities, and enhanced fire regimes in North America. Science.

[7] United Nations. Department of Economic and Social Affairs, Population Division (2017). World Population Prospects: The 2017 Revision, Key Findings and Advance Tables. Working Paper No. ESA/P/WP/248. United Nations, New York. 2017. 19 p. https://esa. un.org/unpd/wpp/publications/Files/WPP2017\_KeyFindings.pdf [Accessed: Dec 10, 2017]

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Sudden collapses have a high priority in the literature. Frequently mentioned triggers of rapid collapses are, among others, nestedness in mutualistic communities, adaptation to a narrow range of environmental factor, keystone species with deterministic species traits. The extinction of abundant species can be followed by rapid and extensive collapse. It must be noted that deterministic factors tend to converge, which increases the probability of collapses. An ecosystem which is burdened with several deterministic extinction factors and belongs to a high-velocity region is under the greatest threat. That is why it is important to identify the early warning signals of collapses. Deterministic factors of extinctions and other factors which trigger sudden collapses are likely to be good indicators. Specialization at species level seems to be one of the most vulnerable extinction traits. According to the literature, carnivores, forest structure, phenology and vertebrate community altogether can be used as indicators of forest collapses. The collapse of mutualistic plant-animal relationships could be detected with reduced seed dispersal distances. Short-lived specialists respond to perturbation quickly, thus they can be considered as good early warning indicators, as well.

Mainly direct human effects dominate the first stage of recent mass extinction and it can be characterized by deterministic extinction factors which undermine the biodiversity and thus the resilience of ecosystems. In the next stage, which probably has already started, an increased number of stochastic events can be expected because of climate change. Stochastic events bring about the sudden collapses of the weakened ecosystems. Positive feedback loops both in climate (e.g. Arctic sea ice melting) and in ecosystems (e.g. forest collapses) are present. They are likely to indicate the onset of the middle stage of mass extinction, which may be irreversible [92].


**6. Conclusion**

In this study, an effective GWO algorithm is united with quasi-oppositional based learning (QOGWO) has been effectively implemented to solve a hydrothermal test system with quadratic nonlinear cost functions. Progressive improvement of the computational efficiency and better convergence characteristics are attained by quasioppositional based learning introduced in the conventional GWO algorithm. It is observed that the simulation time for the same number of iterations and the net cost of generation got by the presented QOGWO for the day is lower than others in all the

*Swarm Intelligence - Recent Advances and Current Applications*

**Table 3.**

*Hourly hydro discharges ( 104 m3) of the test system in case-3.*


**Chapter 3**

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*Inverse Heat Conduction and Heat Exchangers*

**46**


4.2.2. VHE Observations and Results

The H.E.S.S. telescopes followed-up the event for ∼2 h starting from 10.1 h, revealing the presence of a source with a 5.3*σ* pre-trial significance (5.0*σ* post-trial6 ). The observation was performed in standard dark and good weather conditions with a mean zenith angle of 31.5◦ . Another observation was performed under similar conditions 18 days after the previous one with results consistent with background events. The inferred flux at ∼11 h and the flux upper limit at 18 d are shown in Figure 14 (red symbols).

The observed spectrum in the 0.1–0.44 TeV energy band has been fitted both with a power-law (panel on the left in Figure 15) and with a power-law with a cutoff *Fint* = *F*0,*int E E*0 −*γint* , to describe an intrinsic power-law spectrum affected by the EBL attenuation *e* −*τ*(*E*,*z*) (see Figure 15, panel on the right). With reference to the second fit, the analysis returns a photon index *γint* = 1.6 ± 1.2 (statistical) ±0.4 (systematic) and a flux normalization *F*0,*int* = (7.52 ± 2.03 (statistical) +4.53 −3.84) (systematic) ×10−10 TeV−1 cm−2 s −1 , evaluated at an energy *E*0,*int* = 0.154 TeV.

**Figure 14.** GRB 180720B: broad-band light curves and photon index evolution including optical, X-ray and VHE data. For the late time H.E.S.S. observation (18 days after the trigger) an UL has been derived. A flux temporal decay with index 1.2 (similar to what observed in optical and X-ray) is also shown in black dashed line. From [4].

**Figure 15.** GRB 180720B: spectral fit to the observed emission in the 0.1–0.44 TeV energy range. In the left panel (**a**), the observed spectrum is assumed to be described by a power-law model, while in the panel on the right (**b**), the spectrum is an power-law attenuated by EBL. Statistical and systematic uncertainties at a 1*σ* confidence level are shown with shaded areas. From [4].


**1. Introduction**

Among the myriad anthropogenic impacts on the world's oceans, perhaps the most significant is the increase in temperature associated with production of greenhouse gases [1]. This warming is responsible for large-scale changes in circulation and storm activity through melting of glaciers, warming of air masses, and increased evaporation and salinity [1], and as such, warming may have an indirect effect on marine organisms. However, the majority of marine organisms are ectothermic, and are therefore dependent on environmental temperature to gain adequate energy for their own biological functions. The relationship between the performance of an ectotherm and temperature is non-linear, where performance gradually increases with temperature until it reaches

a thermal optimum after which it rapidly declines (Thermal Performance Curve: [2]). Hence, the effect of increasing temperature on marine ectotherms may be more direct, affecting physiology and metabolism [3–7], which may have implications for growth, motor function, development, reproduction and behaviour [6–15], which in turn may impact species' abundance and distribution [16]. Therefore, increasing temperatures may be the most pervasive climate change factor influencing marine organisms [7,17,18]. Warming can subsequently impact entire ecological communities and ecosystems by differentially impacting individuals and functional traits [19–21].

Coral reefs are one of the most biodiverse ecosystems in the world [22,23]. Even though the rate of increase in sea surface temperature (SST) is 30% less in tropical oceans than the global average [24], coral reefs are also among the most sensitive ecosystems to changes in environmental conditions [22,25,26], and thus, are particularly at risk of thermal stress. Tropical ectotherms have a narrow thermal tolerance range, and their thermal optimum is close to their thermal maximum, as they have evolved under relatively stable thermal conditions [27,28]. As SSTs rise, corals and coral reef associated organisms are being subjected to higher temperatures (29–31 ◦C) for increasing periods of time [24]. As a consequence many tropical organisms are thought to be living at or close to their thermal limits [29]. SSTs are predicted to continue to rise over the coming years [1] and extreme warming events, resulting in global scale coral bleaching, are occurring with increasing regularity and severity [30–34], causing degradation of coral reef habitats [22,30,31,35,36].

In addition to the corals themselves, research on the effects of marine heatwaves has also focused heavily on fishes [37–48], which are also typically included in coral reef monitoring efforts. However, studies have almost completely ignored the myriad of small, cryptic, species, which make up a disproportionate amount of coral reef biodiversity [49–51]. One such group are parasites, which make up the largest consumer strategy globally [52] and comprise an estimated 40% of global biodiversity [53–56]. In addition to host behavior, physiology, and population dynamics, parasitic organisms have been shown to have impacts on interspecific interactions, energy flow, and the structure, ecology, and biodiversity of communities [55,57–60]. Parasites are particularly diverse on coral reefs [61] with an estimate of over 20,000 species on the Great Barrier Reef (GBR) alone [62]. However even with such a large presence in coral reef communities, they are significantly underrepresented in ecological studies [10,55,63]. Coral reef parasites are also ectothermic, and as such, may be affected by changes to their environmental temperature [10,11,64–67]. Some parasites are ectoparasitic and would be highly vulnerable to increased temperatures. Ectoparasites are also likely to be directly impacted by the temperature itself, in addition to being indirectly affected through changes in community structure due to temperature impacts on hosts [68] and other organisms. For example, the life cycle of a monogenean ectoparasite (*Neobenedinia*) was faster and the life span of their larvae (oncomiracidia) decreased as temperatures increased from 22 ◦C to 34 ◦C [69].

Gnathiid isopods are one of the most common ectoparasites in coral reef habitats [70–72]. They are small crustaceans, typically 1–3 mm long, that do not permanently live on their fish hosts [73,74]. In fact, with few exceptions, they associate only long enough to extract a blood meal and may therefore also be referred to as "micropredators" [75,76]. After feeding on tissue and blood from their fish host they return to the benthos to molt and progress to the next developmental stage [73,74]. They are only parasitic during their three juvenile stages, and no longer feed once they metamorphose into an adult. Gnathiids can have significant impacts on their hosts [66]. Direct effects include influencing behavior [77–83], physiology [84], and mortality [85]. Indeed, as few as one gnathiid can kill a young juvenile fish [83,86–90]. Indirect effects include transmission of blood-borne parasites [91] and wounds that can facilitate infection [92]. Gnathiids are also the most common items in the diet of many cleaner fishes, including *Labroides dimidiatus* [93,94], a species with far-reaching ecosystem effects [95–97]. Indeed, environmental perturbations, including a coral bleaching event with water temperatures reaching up to 30 ◦C, resulted in an 80% decline in *L. dimidiatus* at Lizard Island, GBR [48]. However, the processes leading to this decline remain unknown.

A long-term monitoring study of gnathiid isopods off Lizard Island, GBR, revealed a significant decrease in gnathiid abundance during extreme warm-water periods associated with bleaching events, compared with cooler periods in the same year or during non-bleaching years [65]. However, the cause of this decline was unclear. Sikkel et al. (2019) [65] hypothesized that the direct effects of temperature on gnathiid mortality may have partly contributed to the decline in gnathiid abundance. The aim of this study therefore, was to assess the direct effect of a rapid increase in seawater temperatures on mortality of shallow-reef gnathiid isopods. By conducting laboratory experiments on gnathiids in two coral reef regions subject to bleaching, GBR, Australia [31,32,98], and Philippines [99–101], we show that a rapid increase in temperature causes significant increases in mortality.


**Example 3**

For priorities *Y CRP X age Z body weight* we determine the contents of *B* as

1 3 1 1 3 5 1 3 315 1 *XYZ X B Y Z*

The largest eigenvalue ( = 3.033) of *B* has the associated eigenvector *V* = (0.37, 0.92, 0.15). *V* is composed of coordinates that are interpreted as the importance weights *w*1, *w*2, *w*3 sought for *X*, *Y*, *Z*.

Let us rearrange the form of function *f* by adding the weights of importance to the vector code values. The new pattern of *f* is designed as *f*(*x y z*) = *w*1*x* + *w*2*y* + *w*3*z*. The function value yields the patient's characteristics given by a combination of codes stated for different symptoms.

#### **Example 4**

The patient vector *v* = (3, 1, 2) has the characteristics *f* (312) 0.37 3 0.92 1 0.15 2 2.33 .

Due to the physician's expertise we assume that we can operate patients who are characterized by codes of age equal to 1, 2 and 3, codes of *CRP* recognized as 0, 1 and 2 and codes of body weight determined as 1, 2 and 3. The minimal patient characteristics to be operated is thus *f* (101) 0.37 1 0.92 0 0.15 1 0.52 , whereas the maximal data characteristics, classifying the patient for the operation is given by *f* (323) 0.37 3 0.92 2 0.15 3 3.4 . We conclude that the patient who is capable to be operated should have the characteristics *f*(*x y z*) included in the interval [0.52, 3.4]. It is worth emphasizing that the decisions are made with respect to the decisive power of biological markers *age*, *CRP* and *body weight*.

#### **Example 5**

We test *v* = (4, 2, 4). As *f* (4 2 4) 0.37 4 0.92 2 0.15 4 3.92 , which lies beyond the boundaries of the "operate" interval, then the patient with data *v* = (4, 2, 4) should not be operated. For vectors *v*1 = (3, 2, 2), *v*2 = (2, 0, 2), *v*3 = (3, 1, 3), *v*4 = (3, 1, 2) the decision will be made as "operate".

The flow chart, sketched in Fig. 3, will show the selection of vectors typical of the decision "operate".

The vectors *v*1, *v*2, *v*3 and *v*4 will be included in the experimental population of representative data strings for the positive decision of the operation. We intend to use them in the next part of the chapter, when discussing the action of the NS algorithm adapted to the operation model.


**1. Introduction**

Research processes for most of today's young learners include online searches. However, the ability to conduct online searches and discern online information is a challenge for children and adolescents [1–4], and children struggle with basic skills [5,6]. This struggle is in part due to the unique features of what we call the "wild wide web" [4], which contains unvetted content, fake news, ads, and other features that distract from desired information and make internet searches complicated [2,7]. The term "fake news" has been used to describe fabricated news, with no factual basis, that is presented to the public as a credible report [8,9]. Loos, Ivan, and Leu [10] (2018) as well as other researchers [11–14] suggest that fake news threatens information access, which is a basic right of all citizens. In addition, the threat of "fake news" on the internet complicates instruction related to the internet as an information source. To discern credible information and news, readers must apply critical thinking to develop what we call "reliability reasoning" [5] (pp. 85–86), or the ability to determine the credibility of online information. The development of such critical thinking requires instruction and practice; yet many teachers are reluctant to allow children to search the wild wide web due to safety concerns [4]. A 2019 study found that most teacher-recommended websites designed for elementary students operate in neat, tidy, and safe walled gardens; students navigate pre-vetted websites, avoiding the "wild wide web" [4] (p. 97). In a walled garden environment, searches are restricted to content within the host's website [15], which limits authentic experiences and does not pose the same "messy" (p. 112) challenges of discerning between relevant content and ads and other distractors.

**Citation:** Pilgrim, J.; Vasinda, S. Fake News and the "Wild Wide Web": A Study of Elementary Students' Reliability Reasoning. *Societies* **2021**, *11*, 121. https://doi.org/10.3390/ soc11040121

Academic Editors: Eugène Loos and Loredana Ivan

Received: 20 August 2021 Accepted: 25 September 2021 Published: 1 October 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

How can students discern information on the internet without authentic practice? Children will use the internet as an information source, with or without instruction on how to do so. As educators, we have a responsibility to keep our young readers safe, and we also have a responsibility to equip them to handle the discoveries and distractions of wild online reading. Therefore, over the past five years we have continued our work with elementary students in grades 1–5 to understand the skills students exhibit when it comes to searching for and evaluating information on the internet. We recently revisited a 2006 University of Connecticut study in which seventh graders lacked the skills needed to determine the credibility of a website about a tree octopus. Using the same website twelve years later, we re-examined how 68 first- through fifth-grade students evaluated the source and shared rationales about its authenticity. Although the students in our study were more critical of the tree octopus article, 65% of students trusted the information. Only at the fifth-grade level did more students question the accuracy of the website information than those who trusted it [6]. Many students believed the tree octopus article to be credible because it had "real" pictures. If young learners trust "real" photos, then other issues present with fake news, in which articles hide behind a "mask of legitimacy" [3], may be problematic. Since this study, we have extended our work with students in grades 1–5 to evaluate concepts of online text and concepts of online research. For the purpose of this article, we discuss findings related to internet searches on the "wild wide web," using two tasks that require the narrowing and evaluation of websites and their content. The guiding question for this study was: What search and evaluation skills do students in grades 1–5 demonstrate during an internet query?


**7. Strain measurement**

The measurement of strain is the most challenging part of the tensile testing of thin film specimens. Due to the small size of thin films, none of the current macro-scale methods of strain measurement are applicable to tensile testing of thin films. Thin film specimens are at the same size scale of resistive strain gages and are too small for LVDT-based extensometers. Technically, any method of strain measurement that is used in contact with the specimen is not useful. Therefore, many researchers have developed or adapted non-contact strain measurement techniques to measure the strain during tensile testing. These techniques can be categorized into four different groups, including cross-head displacement; optical imaging; interferometry-based methods; and advanced microscopy techniques like AFM, SEM, and TEM for *in situ* strain measurement. In what follows, these methods are discussed in detail.

Having prepared the samples and mounted them in grippers, they had to be loaded to the required load level and the load value has to be measured. With the availability of different types of commercial actuators and load cells, this part of a tensile testing setup is not as challenging as the other parts. Piezo driven actuators were among the popular tools for loading. These actuators provide the capability of loading the specimen with different waveforms and frequencies. If they are fitted with any type of displacement sensor, e.g. strain gage, LVDT, or capacitive sensors, they can be controlled in a close-loop system in order to compensate for hysteresis and drift. On the other hand, this displacement feedback can be recorded as the cross-head displacement and be used for the measurement of strain. Many of the research works discussed earlier in this chapter are equipped with this type of actuators (Read & Dally, 1993; Cornella, 1999; Sharpe et al., 1997; Zupan & Hemker, 2001; Allameh et al., 2004). Inchworm (Chasiotis & Knauss, 2002) and motor-driven micrometer (Ruud et al., 1993) actuators are also among the type of actuators that were used for specimen loading. Sharpe & Bagdahn, 2004 used a loud-speaker operating at 20 kHz in their early fatigue tests on polysilicon to dynamically load their specimens at high frequencies. Almost all research groups used strain gage-based load cells to measure the applied load and hence the stress. Tajik, 2008 also used piezoelectric actuators along with precision strain gage load cells that can provide static and dynamic loading capabilities to test thin film

A specific group of tensile test setups are those that have integrated the load-actuation and measurement with the specimen itself on a MEMS-based tensile testing device. These devices provide much higher resolution for load actuation and load measurement, making them a versatile tool to study the mechanical properties of nano-scale structures like carbon nanotubes and nano-wires (Zhu et al., 2007), and films that are substantially thin or have very small gage section areas. (Haque & Saif, 2004) On the other hand, because of their small size, they can be used for *in situ* study of deformation in Scanning Electron Microscope (SEM) or Transmission Electron Microscope (TEM). (Zhu et al., 2003; Haque & Saif, 2003, 2004; Samuel & Haque, 2006; Rajagopalan et al., 2007) However, these devices are not so applicable at the length scale where most of the thin films are usually fabricated and used in

The measurement of strain is the most challenging part of the tensile testing of thin film specimens. Due to the small size of thin films, none of the current macro-scale methods of strain measurement are applicable to tensile testing of thin films. Thin film specimens are at the same size scale of resistive strain gages and are too small for LVDT-based extensometers. Technically, any method of strain measurement that is used in contact with the specimen is not useful. Therefore, many researchers have developed or adapted non-contact strain measurement techniques to measure the strain during tensile testing. These techniques can be categorized into four different groups, including cross-head displacement; optical imaging; interferometry-based methods; and advanced microscopy techniques like AFM, SEM, and TEM for *in situ* strain measurement. In what follows, these methods are discussed

**6. Load actuation and measurement**

specimens as thin as 300 nm.

MEMS and microelectronics applications.

**7. Strain measurement**

in detail.

Read & Dally, 1993 monitored the cross-head displacement and used it as a measure for strain. There are many sources of error involved in this technique. Specimen may slip at the gripper. On the other hand, the gripper itself may have clearances that cause backlash during the changes in load direction. Compliance of the test setup is the other source that deteriorates the accuracy of the method. The cross-head displacement is a combination of all of the deformations in the load train, i.e. the deformations in load-cell, load actuator, the test rig, grippers and albeit in the specimen itself. Therefore, this measurement will not provide an accurate measure of stain in the gage section of the sample.

Cornella, 1999 measured the compliance of the test setup by compressing the load actuator to the load cell in the absence of specimen and subtracted this compliance from the actual measurements to find the deformation in the specimen. They reported that 76% of the measured displacement accounts for the actual deformation in the specimen (Zhang et al., 2006). In order to validate the strain relaxation measurements and to show that the drop in the stress level over time is the actual behavior of the specimen itself and not the test setup, they used iridium specimens. Iridium, due to its high melting point, has a very low relaxation at room temperature. Since these tests revealed no relaxation, they argued that their test setup is stiff enough and that the relaxation behavior that they monitored during the tensile testing of Al films is the actual material behavior.

Chasiotis et al., 2007 used the cross-head displacement to study the relaxation in gold thin films. They measured the deformation of the load-cell and the apparatus compliance and subtract it from the results. Due to the high compliance of their specimens compared to the setup, 99% of the cross-head displacement was due to the deformation in the specimen. They verified the accuracy of the crosshead displacement method by testing brittle materials with known elastic modulus.

Greek & Johnson, 1997 cancelled out the effect of the compliance of the test setup by testing specimens with identical gages section areas and different gage lengths. Assuming that the compliance of the test setup is constant for any test, they calculated the deformations caused by test setup and subtract it from the test results. This method is only applicable to the cases that the compliance of the specimens are sufficiently different at different gage lengths.

Emry & Povirk, 2003a also measured the displacement in grippers by monitoring the displacement of two markers using a video camera. They argued that their method has the limitation that the measured strain is not the actual strain in the gage section. They also reported a non-linearity in the stress-strain curve in low loads. Figure 6 shows this nonlinearity which is technically an experimental error. They extrapolated the linear portion of the results to find the zero point of stress-strain curve. Due to this non-linearity in the curve, calculating the yield stress using the 0.2% offset rule was erroneous. Therefore they found the yield point by defining it as the point where the slope of the stress-strain curve drops to one tenth of the elastic modulus.

Due to the uncertainties involved in the application of cross-head displacement for strain measurements, a number of techniques have been introduced to measure the strain directly on the gage section. An inexpensive way of measuring strain is to put markers on the specimen's gage section and monitor their displacement using a camera. Allameh et al., 2004 used a video camera and monitored the deformation of two markers milled by Focused Ion Beam (FIB) on LIGA Ni specimens. Markers were 300μm apart and were located by block matching in a series of images captured by a camera during tensile testing. They have not

Standalone Tensile Testing of Thin Film Materials for MEMS/NEMS Applications 447

optical lever for magnification. They reported that the resolution of the system is limited by

The main advantage of this technique is that since axial and lateral strains can be measured simultaneously, not only Young's modulus but also the Poisson's ratio can be calculated. Since the modulus of the photoresist islands is sufficiently lower than that of the film's, their presence has very negligible effect on the mechanical behavior of the specimen material. The aforementioned techniques were all based on optical imaging. The main issue with imaging techniques is that their resolution is limited by the optical setup, and more specifically by the magnification and the CCD resolution. An advanced method of improving the resolution of optical devices is to use light interference. This approach which is the basis of interferometry techniques has been used by a few researchers for strain

Fig. 7. Double field of view microscope setup for strain measurement (Ogawa et al., 1997) Sharpe et al., 1997 used Interferometric Strain/Displacement Gage (ISDG) method to measure axial and lateral strains in thin film specimens. ISDG was originally proposed by Sharpe (Sharpe, 1968, 1982, 1986, 1989) in the late 1980s to measure strains in macrospecimens in non-contact mode. The principle of this technique is based on the diffraction and interference of light from two slits, i.e. Young's two slit interference. In this method, two markers are put on the specimen. They can be fabricated either by nano-indentation or by FIB-assisted deposition. When the laser beam is illuminated on them the beam is diffracted. The diffracted beams interfere to form interference fringes. The frequency of the fringes is directly proportional to the distance between the two markers. When the specimen is elongated under the applied load, the distance between the two markers varies, resulting in a change in the fringe frequency. By monitoring this frequency the strains can be directly calculated on the specimen. Since the fringe frequency is also affected by the rigid-body motion of the specimen, two separate detectors have to be used to cancel out the effect of

the signal-to-noise ratio of the detector and provides strain resolution of 50μstrains.

measurement in thin film materials.

discussed the accuracy of their setup; however, they reported that the strains that were measured as such were only used in the plastic deformation regime. In this method, one way to achieve higher displacement measurement resolution is to use higher optical magnification. However, at high magnifications, the field of view (FOV) of the objective is so small that the two markers cannot be fit in a single image, simultaneously. To overcome this issue, two different approaches have been used. Cheng et al., 2005 used a low magnification (350X) to fit 180μm-apart markers in a single image. Utilizing the digital image correlation (DIC) method, they post-processed the data to the resolution of 0.02 pixel. For their optical setup, this resolution is the equivalent of 0.01μm displacement on the specimen which translates to 55μstrain resolution for a 180μm gage length. Since compared to other techniques, usually less or no preparation is required on the surface of the specimen and inexpensive optical imaging equipment can be used for this purpose, this method is becoming more popular among researchers. The only disadvantage of DIC is that this method is computationally expensive and therefore cannot be used in real-time and straincontrolled measurements.

In another attempt to tackle the small FOV issue in high magnifications, Ogawa et al., 1997 proposed a double field of view approach. As shown in Figure 7, a low magnification objective is used to view the two markers which were 1-1.4mm apart. Image of each marker position was then magnified on a separate CCD and their displacement was monitored. In their technique, they could measure displacements to better than 1μm corresponding to 0.1% strain for a 1mm gage length.

Fig. 6. Stress-strain curve of gold thin films, showing non-linearity at low loads. The dashed line is fitted to the curve to find the zero point. (Emry & Povirk, 2003a)

Ruud et al., 1993 patterned a two-dimensional area of photoresist islands on the specimen and monitored the displacement of the diffracted spots from these islands to directly measure the strain on the gage section. As shown in Figure 8, presence of the photoresist islands results in diffraction patterns when a laser beam is illuminated on the surface of the sample. Diffracted spots are then detected using a two-dimensional position sensor. By monitoring the displacement of these spots, the relative displacement of the islands and hence the specimen deformation can be measured. In this setup, system works in the third diffraction order and the distance between the sample and position detector serves as an

discussed the accuracy of their setup; however, they reported that the strains that were measured as such were only used in the plastic deformation regime. In this method, one way to achieve higher displacement measurement resolution is to use higher optical magnification. However, at high magnifications, the field of view (FOV) of the objective is so small that the two markers cannot be fit in a single image, simultaneously. To overcome this issue, two different approaches have been used. Cheng et al., 2005 used a low magnification (350X) to fit 180μm-apart markers in a single image. Utilizing the digital image correlation (DIC) method, they post-processed the data to the resolution of 0.02 pixel. For their optical setup, this resolution is the equivalent of 0.01μm displacement on the specimen which translates to 55μstrain resolution for a 180μm gage length. Since compared to other techniques, usually less or no preparation is required on the surface of the specimen and inexpensive optical imaging equipment can be used for this purpose, this method is becoming more popular among researchers. The only disadvantage of DIC is that this method is computationally expensive and therefore cannot be used in real-time and strain-

In another attempt to tackle the small FOV issue in high magnifications, Ogawa et al., 1997 proposed a double field of view approach. As shown in Figure 7, a low magnification objective is used to view the two markers which were 1-1.4mm apart. Image of each marker position was then magnified on a separate CCD and their displacement was monitored. In their technique, they could measure displacements to better than 1μm corresponding to

Fig. 6. Stress-strain curve of gold thin films, showing non-linearity at low loads. The dashed

Ruud et al., 1993 patterned a two-dimensional area of photoresist islands on the specimen and monitored the displacement of the diffracted spots from these islands to directly measure the strain on the gage section. As shown in Figure 8, presence of the photoresist islands results in diffraction patterns when a laser beam is illuminated on the surface of the sample. Diffracted spots are then detected using a two-dimensional position sensor. By monitoring the displacement of these spots, the relative displacement of the islands and hence the specimen deformation can be measured. In this setup, system works in the third diffraction order and the distance between the sample and position detector serves as an

line is fitted to the curve to find the zero point. (Emry & Povirk, 2003a)

controlled measurements.

0.1% strain for a 1mm gage length.

optical lever for magnification. They reported that the resolution of the system is limited by the signal-to-noise ratio of the detector and provides strain resolution of 50μstrains.

The main advantage of this technique is that since axial and lateral strains can be measured simultaneously, not only Young's modulus but also the Poisson's ratio can be calculated. Since the modulus of the photoresist islands is sufficiently lower than that of the film's, their presence has very negligible effect on the mechanical behavior of the specimen material.

The aforementioned techniques were all based on optical imaging. The main issue with imaging techniques is that their resolution is limited by the optical setup, and more specifically by the magnification and the CCD resolution. An advanced method of improving the resolution of optical devices is to use light interference. This approach which is the basis of interferometry techniques has been used by a few researchers for strain measurement in thin film materials.

Fig. 7. Double field of view microscope setup for strain measurement (Ogawa et al., 1997)

Sharpe et al., 1997 used Interferometric Strain/Displacement Gage (ISDG) method to measure axial and lateral strains in thin film specimens. ISDG was originally proposed by Sharpe (Sharpe, 1968, 1982, 1986, 1989) in the late 1980s to measure strains in macrospecimens in non-contact mode. The principle of this technique is based on the diffraction and interference of light from two slits, i.e. Young's two slit interference. In this method, two markers are put on the specimen. They can be fabricated either by nano-indentation or by FIB-assisted deposition. When the laser beam is illuminated on them the beam is diffracted. The diffracted beams interfere to form interference fringes. The frequency of the fringes is directly proportional to the distance between the two markers. When the specimen is elongated under the applied load, the distance between the two markers varies, resulting in a change in the fringe frequency. By monitoring this frequency the strains can be directly calculated on the specimen. Since the fringe frequency is also affected by the rigid-body motion of the specimen, two separate detectors have to be used to cancel out the effect of

Standalone Tensile Testing of Thin Film Materials for MEMS/NEMS Applications 449

In another effort to use interferometric measurement techniques, Read, 1998 used speckle interferometry to measure in-plane strains in thin film specimens. The main advantage of speckle interferometry is that since it uses the speckles caused by the surface topography, no surface preparation or marker fabrication is required. However, it is usually computationally expensive and has low signal-to-noise ratio. In this technique, instead of the strain, the strain rate was measured in the elastic deformation regime and was used to calculate the modulus of elasticity. The uncertainty of the calculated modulus was reported

Tajik, 2008 used another interferometric technique to measure the strain fields in a thin film specimen. This method is schematically represented in Figure 10-a. Diffraction gratings are milled on the freestanding thin film specimen using Focused Ion Beam (FIB). (Figure 10-b and c) Gratings are then illuminated by two laser beams and the interferogram thus formed is captured via a CCD camera. Deformation of the specimen and hence the gratings will result in changes in the interferogram. Intensity of the interferogram can be correlated to the

> 0 ( , ) ( , ) ( , )cos(2 (2 ) ( , )) *s Ixy I xy xy f Uxy*

intensity and fringe visibility, respectively. In this equation, *sf* is the spatial frequency of

As shown in Equation (1), displacement field is essentially the phase of the interferogram. Therefore, in order to measure displacement field, one needs to calculate the phase value from the interferogram data. For this purpose, continuous wavelet transformation (CWT) has been used in this study. In brief, it has been shown that the spatial derivative of the displacement field, which in fact corresponds to strains, correlates with the value of the

> 1 ( ) 2 () *c xx*

where ( ) *r a x* is the scale value on the ridge of the wavelet for any coordinate *x* and *cf* is the center frequency of the Morlet wavelet. This method is then used to extract uniform and non-uniform strain fields. It is shown that wavelet transformations have exceptional capabilities in denoising the experimental interferogram, given appropriate wavelet parameters are chosen in the analysis. Figure 11 demonstrates the capabilities of this method to reconstruct the non-uniform strain field around a hole in a plate under axial tension. The last group of strain measurement methods are those that used advanced microscopy techniques to measure the strain in thin films. The challenges involved in using optical microscopy led researchers to use other microscopy techniques like AFM, SEM, and TEM to measure the deformation of thin films specimens. These techniques, on the other hand, can provide an insight into the microstructural deformation of thin film materials during

Chasiotis & Knauss, 2002 monitored the surface topography changes during loading using Atomic Force Microscopy (AFM). Correlating the AFM images of the deformed and undeformed surface using Digital Image Correlation (DIC), they calculated the strain field.

*s r f x f a x*

where *Ixy* (,) is the interferogram intensity, and 0*I x*(,) *y* and

scaling parameter at the ridge of the transformation,

the gratings and *U x*(,) *y* represents in the axial displacement field.

(1)

(,) *x y* are the background

(2)

to be 5%.

loading.

displacement field, such that

this motion. A schematic of this setup is shown in Figure 9. In the original setup, in order to measure the strains from the fringe data, the location of the fringe minimum was isolated at the beginning of the test and was followed through a complex algorithm. In this algorithm only a small part of the optical signal was used and most of it which contained a lot of information was omitted in calculations. With this algorithm, the strain resolution was 5μstains with uncertainty of ±30μstrains. Zupan & Hemker, 2002 used Fourier Transforms on the whole optical signal and improved the uncertainty of the technique to ±15μstrains. An advantage of ISDG is that if markers are placed along the width of the specimen, the lateral strains and hence the Poisson's ratio can also be measured with this technique. However, since the markers have to be at least 300μm apart, (Hemker & Sharpe, 2007) wide specimens have to be utilized.

Fig. 8. Schematic diagram of the setup to use diffraction spots for strain measurement (Ruud et al., 1993)

Fig. 9. Schematic representation of ISDG technique. (Sharpe et al., 1997)

this motion. A schematic of this setup is shown in Figure 9. In the original setup, in order to measure the strains from the fringe data, the location of the fringe minimum was isolated at the beginning of the test and was followed through a complex algorithm. In this algorithm only a small part of the optical signal was used and most of it which contained a lot of information was omitted in calculations. With this algorithm, the strain resolution was 5μstains with uncertainty of ±30μstrains. Zupan & Hemker, 2002 used Fourier Transforms on the whole optical signal and improved the uncertainty of the technique to ±15μstrains. An advantage of ISDG is that if markers are placed along the width of the specimen, the lateral strains and hence the Poisson's ratio can also be measured with this technique. However, since the markers have to be at least 300μm apart, (Hemker & Sharpe, 2007) wide

Fig. 8. Schematic diagram of the setup to use diffraction spots for strain measurement

Fig. 9. Schematic representation of ISDG technique. (Sharpe et al., 1997)

specimens have to be utilized.

(Ruud et al., 1993)

In another effort to use interferometric measurement techniques, Read, 1998 used speckle interferometry to measure in-plane strains in thin film specimens. The main advantage of speckle interferometry is that since it uses the speckles caused by the surface topography, no surface preparation or marker fabrication is required. However, it is usually computationally expensive and has low signal-to-noise ratio. In this technique, instead of the strain, the strain rate was measured in the elastic deformation regime and was used to calculate the modulus of elasticity. The uncertainty of the calculated modulus was reported to be 5%.

Tajik, 2008 used another interferometric technique to measure the strain fields in a thin film specimen. This method is schematically represented in Figure 10-a. Diffraction gratings are milled on the freestanding thin film specimen using Focused Ion Beam (FIB). (Figure 10-b and c) Gratings are then illuminated by two laser beams and the interferogram thus formed is captured via a CCD camera. Deformation of the specimen and hence the gratings will result in changes in the interferogram. Intensity of the interferogram can be correlated to the displacement field, such that

$$I(\mathbf{x}, y) = I\_0(\mathbf{x}, y) + \varphi(\mathbf{x}, y) \cos(2\pi(2f\_s) \mathcal{U}(\mathbf{x}, y)) \tag{1}$$

where *Ixy* (,) is the interferogram intensity, and 0*I x*(,) *y* and (,) *x y* are the background intensity and fringe visibility, respectively. In this equation, *sf* is the spatial frequency of the gratings and *U x*(,) *y* represents in the axial displacement field.

As shown in Equation (1), displacement field is essentially the phase of the interferogram. Therefore, in order to measure displacement field, one needs to calculate the phase value from the interferogram data. For this purpose, continuous wavelet transformation (CWT) has been used in this study. In brief, it has been shown that the spatial derivative of the displacement field, which in fact corresponds to strains, correlates with the value of the scaling parameter at the ridge of the transformation,

$$
\varepsilon\_{\rm xx}(\mathbf{x}) = \frac{1}{2f\_s} \frac{f\_c}{a\_r(\mathbf{x})} \tag{2}
$$

where ( ) *r a x* is the scale value on the ridge of the wavelet for any coordinate *x* and *cf* is the center frequency of the Morlet wavelet. This method is then used to extract uniform and non-uniform strain fields. It is shown that wavelet transformations have exceptional capabilities in denoising the experimental interferogram, given appropriate wavelet parameters are chosen in the analysis. Figure 11 demonstrates the capabilities of this method to reconstruct the non-uniform strain field around a hole in a plate under axial tension.

The last group of strain measurement methods are those that used advanced microscopy techniques to measure the strain in thin films. The challenges involved in using optical microscopy led researchers to use other microscopy techniques like AFM, SEM, and TEM to measure the deformation of thin films specimens. These techniques, on the other hand, can provide an insight into the microstructural deformation of thin film materials during loading.

Chasiotis & Knauss, 2002 monitored the surface topography changes during loading using Atomic Force Microscopy (AFM). Correlating the AFM images of the deformed and undeformed surface using Digital Image Correlation (DIC), they calculated the strain field.

Standalone Tensile Testing of Thin Film Materials for MEMS/NEMS Applications 451

nanostructures rather than common thin film materials. A stress-strain curve along with respective microstructural observations produced by this method is shown in Figure 13.

(a) (b)

0 0.5 1 1.5 2 2.5 3 x 10-3

0 0.2 0.4 0.6 0.8 1 1.2 1.4 x 10-4

xx (Strains)

xx (Strains)

(c)

Original Reconstructed

x (m)

Original Reconstructed

x (m)

Fig. 11. (a) Reconstructed (top) and original (bottom) strain field using continuous wavelet transformations, (b) reconstructed strains at top of the hole (y=12μm), (c) through the hole

Fig. 12. Displacement field in the vicinity of a crack in polysilicon film measured by

(y=0). (Tajik, 2008)

AFM/DIC. (Chasiotis, 2004)

The process of imaging is very time intensive and usually takes about 10 minutes for each scan and is confined to an area of a few microns long. In addition to the time required for each AFM scan, there is also the post-processing time added for DIC. They reported 400 μstrains resolution in their strain measurements for a 512×512 pixel image and 1/8 pixel DIC resolution. However, the main advantage of this technique is that it provides a wholefield strain data which helped the analysis of the strain field around geometry inclusions and notches (Chasiotis & Knauss, 2003), as well as cracks. (Chasiotis et al., 2006; Cho et al., 2007). A typical displacement field at the vicinity of a crack in polysilicon that has been measured using AFM/DIC is shown in Figure 12.

Fig. 10. (a) Schematic representation of the optical setup for moiré interferometry, (b) diffraction gratings fabricated using FIB milling on the test specimen, and (c) high magnification image of the gratings on the specimen. (Tajik, 2008)

A few researchers used MEMS based devices to study the mechanical properties of thin films in electron microscopes. If the thin film samples are electron transparent, i.e. have nanometer thickness, *in situ* studies in TEM are also possible which provides more information on the microstructural deformations during loading. Haque & Saif, 2003, 2004 used the technique to study the mechanical behavior of Al and Au thin film specimens under SEM and TEM. The resolution of the measured strain and stress depends on the magnification of the microscope and the size of the specimen. At 100nm microscope resolution, the strain resolution was 0.05% for 200nm thick and 185μm long Al films and was 0.03% for 100nm thick and 275μm long specimens. Rajagopalan et al., 2007 reported lower strain resolutions of 0.005% and 0.01% for Al and Au films, respectively. Although this method of strain measurement has a high resolution and provides extra information on the microstructural deformations, its force and displacement scales are within the limits of

The process of imaging is very time intensive and usually takes about 10 minutes for each scan and is confined to an area of a few microns long. In addition to the time required for each AFM scan, there is also the post-processing time added for DIC. They reported 400 μstrains resolution in their strain measurements for a 512×512 pixel image and 1/8 pixel DIC resolution. However, the main advantage of this technique is that it provides a wholefield strain data which helped the analysis of the strain field around geometry inclusions and notches (Chasiotis & Knauss, 2003), as well as cracks. (Chasiotis et al., 2006; Cho et al., 2007). A typical displacement field at the vicinity of a crack in polysilicon that has been

Fig. 10. (a) Schematic representation of the optical setup for moiré interferometry, (b) diffraction gratings fabricated using FIB milling on the test specimen, and (c) high magnification image of the gratings on the specimen. (Tajik, 2008)

A few researchers used MEMS based devices to study the mechanical properties of thin films in electron microscopes. If the thin film samples are electron transparent, i.e. have nanometer thickness, *in situ* studies in TEM are also possible which provides more information on the microstructural deformations during loading. Haque & Saif, 2003, 2004 used the technique to study the mechanical behavior of Al and Au thin film specimens under SEM and TEM. The resolution of the measured strain and stress depends on the magnification of the microscope and the size of the specimen. At 100nm microscope resolution, the strain resolution was 0.05% for 200nm thick and 185μm long Al films and was 0.03% for 100nm thick and 275μm long specimens. Rajagopalan et al., 2007 reported lower strain resolutions of 0.005% and 0.01% for Al and Au films, respectively. Although this method of strain measurement has a high resolution and provides extra information on the microstructural deformations, its force and displacement scales are within the limits of

(c)

measured using AFM/DIC is shown in Figure 12.

(a) (b)

nanostructures rather than common thin film materials. A stress-strain curve along with respective microstructural observations produced by this method is shown in Figure 13.

Fig. 11. (a) Reconstructed (top) and original (bottom) strain field using continuous wavelet transformations, (b) reconstructed strains at top of the hole (y=12μm), (c) through the hole (y=0). (Tajik, 2008)

Fig. 12. Displacement field in the vicinity of a crack in polysilicon film measured by AFM/DIC. (Chasiotis, 2004)

Standalone Tensile Testing of Thin Film Materials for MEMS/NEMS Applications 453

interferometry have much higher resolution and can be used to extract strain values as well as strain fields. However, their main disadvantage is the hardware complexity and cost. On the other hand, optical imaging methods in combination with Digital Image Correlation (DIC) can provide about the same resolution; however, they are computationally expensive and cannot be used in real-time and strain-controlled experiments. Therefore, depending on the specific type of application, one needs to

The information obtain through this review provide a detailed understanding of the challenges involved in tensile testing of thin film materials and different approaches that were used to tackled these issues. The results will help design and implement a device that can meet these challenges toward a reliable and precise study of the mechanical

The financial support from the Natural Sciences and Engineering Council of Canada (NSERC) is appreciated. Center for Integrated RF Engineering (CIRFE) and WatLabs of the University of Waterloo, Nanofabrication Laboratory of the University of Western Ontario and the Canadian Centre for Electron Microscopy in McMaster University are acknowledged for providing research facilities. A great portion of this research is conducted in Laboratory for the Mechanical Properties of Thin Film Materials at the University of

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Fig. 13. *In situ* TEM test results for Al thin film specimens. Microstructural deformations corresponding to the tensile test is also presented. (Haque & Saif, 2004)