Experimental Optimization of Antifoulant Impregnated Polymer Structures for Marine Applications

Trent Kelly, Tan GZ and Hunt EM

Published on: 2022-12-30

Abstract

Fabricated marine structures often suffer adverse effects from marine biofouling including structural failure due to the accumulated weight and surface profile of hard-shell fouling. While current techniques such as surface coatings can be somewhat effective, they are costly and have a relatively short lifespan. Additionally, there are updated regulations from the environmental agencies that prescribe allowable amounts of biocidal materials in the ocean in certain regions of the world. Antifoulant impregnation of polymers has been recently studied in marine fouling of offshore structures with promising results for microbial and cost efficacy. In this study, experiments were conducted to optimize a blend of antifoulant additives incorporated into a high-density polyethylene matrix during the manufacturing process. Samples were submerged in the Indian Ocean and data was collected over a period of seven months with the primary indicator of fouling being the growth of individual barnacles on the surface. Factors included for optimization include microbial efficacy, cost, and environmental regulations based on geographic location. Results show that for regulated waters, a blend of zinc oxide and ANA, a commercially available antifoulant, is the optimum formula for incorporation into high-density polyethylene. For unregulated waters, a blend of cuprous oxide and ANA provides the optimum formula for microbial and cost efficacy. Experimental data formed the basis for the optimization process used in this study. The methods used were time and cost intensive and dependent upon a variety of environmental factors such as temperature, salinity, and growth rate of individual barnacles. As the need for antifouling structures continues to grow in a variety of industries this experimental method becomes less feasible. Future work by the authors will examine a predictive machine learning approach to surface visualization and optimization of impregnated antifouling structures for use across industries.

Keywords

Biofouling; Antifoulant; Moulding

Introduction

Many manmade marine structures suffer adverse effects from marine biofouling, an occurrence in which microorganisms develop into a biofilm and subsequently marine macro-organisms adhere to a surface [1-3]. These biofilms form when microorganisms combine into a group and attach themselves to a variety of surfaces including piping and aquatic structures [4-6]. The absorption of the organisms which are a mixture of organic materials and bacteria is dependent on the substrate of the surface, the water temperature, salinity, and other environmental conditions [7]. For an underwater surface exposed to laminar flow conditions, there is a region known as the boundary layer. This region is defined when the water closest to the substrate is assumed to have the same velocity as the surface and this increases as the water becomes further from the surface. To reach the surface, bacteria need to cross this boundary layer which occurs as a result of van der Waals forces and Brownian motion [7-10]. Once the organisms pass through the boundary layer, they create a biological matrix or biofilm that acts as a scaffold on which other materials can attach. As this biofilm builds upon the surface of the substrate, it becomes stronger and healthier and provides nutrition to the microorganisms and eventually macro-organisms in the form of mussels and barnacles. These organisms cause stress cracking in both metallic and polymeric materials by forming colonies and eating away at the material surface. Biofouling has been well documented in substrates exposed to a variety of aqueous environments including seawater, freshwater, soils, and fuels [11-18]. Biofouling is documented as the root cause for up to 20% of all corrosion costs as marine life causes growths that develop on the hard surface and lead to mechanical and structural failures [19-20]. Biofouling increases cost of operations, increases drag and weight of marine vessels resulting in higher fuel costs, reduces power efficiencies, and requires frequent cleaning and build up removal causing billions of dollars of economic losses worldwide each year [21].

Biocidal paints or coatings are the traditionally accepted method for protecting an underwater surface. These coatings are considered to be antifouling because they contain materials that inhibit microbial growth which release at a controlled rate into the water and prevent the development of a biofilm on the surface to which they are applied [1-3], [22-24]. The most common biocides incorporated into the coatings are copper, cuprous oxide, zinc, zinc oxide, and zinc pyrithione.Dodge, et al. studied the incorporation of biocidal materials into the fabrication of polymer structures and examined their efficacies in high-fouling conditions [1].The rate of release of biocides is critical for efficacy; if it is too fast, the antifouling will fail prematurely, especially after a period of intense activity, while if it is too slow, the antifouling will be ineffective, particularly in areas with a high fouling challenge [1, 25]. The fouling organisms must be prevented from attaching and growing on the surface. Once this happens, growth is extremely rapid and the organisms are beyond the influence of antifouling paints, and can only be removed by scrubbing and scraping by underwater divers which is both costly and time consuming [25].

While current techniques for antifouling solutions can be effective, they are also thought to be outdated, costly, potentially unstable due to chipping, and environmentally problematic due to excessive leaching [26-31]. Copper-based coatings are the most widely used and oldest known antifoulants with ships dating back for centuries having copper plating utilized to prevent biofouling [26-27]. Zinc is the next most commonly used biocide and can be also be used in the form of zinc pyrithione. Previous research by the authors discusses the development of a nanoparticulate silver coating additive that is activated through combustion synthesis and forms a powder that can then be incorporated into traditional coating systems [3, 32-36]. The extraordinarily high surface areas these materials possess serve as an excellent platform for the neutralization of bacteria. These newly synthesized materials have been incorporated into coatings in the oil and gas industry, and are applied to metal, ceramic, plastic or composite surfaces. This type of coating system presents a novel approach to microbiological neutralization, or more specifically, microbiologically influenced corrosion protection. These coatings are currently being used in seawater applications off the Gulf of Mexico [37-39].

Recently, researchers have experimented with impregnating the antifoulant directly into the substrate that is needing protection [1-3]. While biocide impregnation of polymers in marine fouling and other relevant fields has been observed to be an effective means of preventing biofilm and biofouling growth, a comprehensive analysis has not been performed to understand which additives are best suited as polymer antifoulants and how to best impregnate them into polymers to provide a cost-effective and robust antifoulant solution [1]. Results from recent studies [1-4, 32-36, 40] fill an increasing void as biofouling and microbiologically influenced corrosion are being recognized as a major problem in a variety of industries including oil and gas, aviation, and healthcare. Expensive coatings and toxic chemicals are being used as a short term solution, but the ability to fabricate the substrate material with a ‘built-in’ or impregnated antimicrobial agents presents a creative long term solution.

The objective of this study is twofold:

  • Testing the antifouling efficacy of the impregnation with different biocidal materials,
  • Determine the most effective solution according to industry standards.

Testing was conducted with five biocidal materials in varying mixtures and percentages incorporated into a polymer-based matrix. Zinc oxide (ZnO), cuprous oxide (CuO), copper nickel (CuNi), zinc pyrithione, and silver are all currently used antibacterial agents. These materials may work in conjunction with one another in different ways to form a longer term antifouling solution.

Experimental

The experimental testing for this study was done through the lens of a current project for oil and gas majors. The industrial purpose is to determine potentially effective antifouling solutions to polymer wrapped pipes within marine environments. Current flow around a pipeline can result in vibration created by vortex shedding. The frequency of this vibration can become close to the natural frequency of the pipe, which can cause fatigue or damage the pipeline. A solution to this vibration is to wrap the pipe in a Vortex Induced Vibration (VIV) reducing strake. These strakes are a rotationally-moulded, high-density polyethylene wrap that completely encircle the pipe and change the trajectory of the flow around the pipeline. The materials and conditions in this study are based on the development of an antifouling HDPE VIV strake. The terms antimicrobial, antifouling, and biocidal all describe materials that resist microbial growth and will be used interchangeably throughout this study.

Antifoulant Materials

Antifouling testing was conducted utilizing eleven samples including a control sample. Each sample was produced using a combination of at least one the following antimicrobial powders: zinc oxide, cuprous oxide, copper nickel, zinc pyrithione, and a new, commercially available material called Antimicrobial Nano Alloy ANA) comprised of silver and aluminum oxide. Micron-scale zinc oxide powder was procured from Bulk Apothecary with a purity of 95%. Micron-scale cuprous oxide was procured from American Chemet Corporation with a purity of 95%. Copper nickel was procured from Richest Group and had a size of 10 micrometers and purity of 99%. Zinc pyrithione was procured from TCI and had a size of 5 microns and purity of 97%. ANA composed of a silver-aluminum alloy was procured from Buffalo Technology Group and had a size range of 0.5-10 micrometers and purity of 99%. Table 1 shows the blend of each substrate used in this project.

Table 1: Biocidal Material Matrix.

Active Ingredienta concentration % of antifoluant mixture

Sample ID

ANA

Zinc Oxide(Zno)

Cuprous Oxide (Cuo2)

Zinc Pyrithione

Antifoulant % of total sample

HDPE% of total sample

A

4

96

0

0

10%

90%

B

2

98

0

0

12%

88%

C

0

0

0

0

0

100%

D

17

83

0

0

0.20%

99.8%

E

0.5

99.5

0

0

12%

88%

F

0

0

0

100

10%

90%

G

1

49

50

0

12%

88%

H

0

0

0

0

0

100%

I

2

0

0

0

12%

88%

J

2

0

98

0

12%

88%

Moulding

HDPE powder and manufacturing specifications were provided by a rotational lining company. The HDPE samples were prepared using a lab-scale rotational molder and each sample contained 900 grams of HDPE dry powder. The testing substrates were manufactured using a rotational molding process to test the antimicrobial’s efficacy when dispersed throughout the thickness of the sample. The parts produced in this research modeled the rotational molding process designed to manufacture HDPE VIV strakes and thus temperatures and times were approximated based on those numbers. The rotational molding machine was rotated using a small direct current turkey rotisserie motor at a rotational velocity of approximately 16 rotations per minute.

Testing was done with this machine to determine the appropriate time spent in the oven to fully melt the HDPE but not deform the HDPE during the cooling process. Because a motor that can withstand the temperatures needed was difficult and expensive to procure, a setup was determined that would allow the motor to sit outside of the heating oven during the heating and melting phase and be insulated from the heat.

The aluminum mold for the samples was machined with a rectangular cavity with the dimensions of 13.5 inches by 6.75 inches by 1.25 inches. In order to ensure the HDPE would not stick to the mold silicone baking sheets were fastened to the inside of the mold. Figure 1 shows the rotational molding setup used to make the HDPE samples for testing.

Figure 1: Rotational molding setup.

Once the machine was fully tuned to form HDPE substrates with relatively even wall thicknesses, the mixing of antifoulant additives into the HDPE was performed. Each additive was weighed on a scale separately from the HDPE powder. Once the desired antimicrobial to HDPE ratio was determined the additive was poured into the HDPE powder in a container with a threaded cap. The cap was then closed and the container was shaken by hand for 5 minutes. In each case, after five minutes, the antifoulant and HDPE appeared visually to be homogeneously mixed. While the mixtures may not have been perfectly homogeneous, it is well established that these mixtures gain more homogeneity throughout the rotational moulding process as the powder is rotated and melted together [25].

The machine was turned on and set to rotate at 16 revolutions per minute. The rotating arm was then placed into a preheated oven set to 300o Celsius and left to rotate and melt for a duration of 3 hours. The oven was then turned off and the mould allowed to cool while continuing to rotate for approximately another hour or until the mold was cool to the touch. Samples were removed and cut into uniform rectangles using the largest sides.

Testing

Sacred Heart Marine Research Center (SHMRC) is a primary test facility for immersion and is located in Tuticorin Bay in south India. This facility is in close proximity to the floating test platforms in the protected bay area and enables SHMRC to expand its research and testing capabilities in marine coatings evaluation and marine research. Samples were sent to SHMRC to be submerged in a static immersion test per ASTM D3623-78a. Due to the high fouling rate and relatively uniform oceanic conditions throughout the year, Tuticorin Bay, India provided an excellent growth environment to evaluate these impregnated HDPE samples in as close to accelerated testing conditions as possible in actual oceanic conditions. The samples were shipped to Poseidon Sciences in Tuticorin Bay, India then secured by attaching wire through two holes previously drilled through the top of the sample. The samples were each submerged in a cage in the same location ensuring uniformity in testing conditions.

ASTM D3623 - 78a is a test is used to evaluate antifouling panels in shallow submergence. Static immersion remains a necessary step to validate the efficacy of coatings against fouling. The primary fouling organism is the barnacle, Balanus amphitrite amphitrite Darwin. This is also the most common fouling organism found in most parts around the world and likely distributed worldwide by seagoing vessels for many centuries. The seawater temperature remains above 200 degrees Celsius all year and reaches as high as 350 degrees Celsius. The 12x6 inch samples are placed two feet below the surface of the water and inspected once a month for growth both qualitatively and quantitatively. Once per month, an employee of Poseidon Sciences would remove each sample, lightly rinse it with salt water to remove any sand or non-attached sludge then take a picture of both sides of the sample.

The samples were secured in the cage and submerged until they were evaluated the following month. Rough counts were then made of each type of fouling present on the surface. Testing was conducted in four-month cycles of evaluation after which the testing team could determine whether to continue testing or terminate any samples. Samples that were fouled over roughly ninety-five percent of their surface or more were removed at the next four month evaluation stage.

Data Collection and Analysis

As previously addressed, Poseidon Science provided raw count data for each primary type of fouling present on the surfaces of the substrate. On a monthly basis, each sample was removed, rinsed with sea water to remove any non-adhering sludge from the surface, and photographed. The pictures were then later examined and the hard shell fouling organisms were identified as either barnacles or oysters. An approximate surface area of fouling on the sample was also provided using a visual estimation.

Fouling metrics for this test were determined by the raw count of the barnacle and oyster growth on each sample. This number was recorded in every observation until the sample became too oversaturated with growth to accurately hand count in which case a too numerous to count (TNTC) was indicated by Poseidon Science. The second factor was the percentage of surface area of the sample that was covered in fouling.

Results And Discussion

Each sample was evaluated for the number of barnacles on the surface during each of the six observation periods. SHMRC reports the number of barnacles on either side of the duplicated panels, maximum diameter of the barnacles on each side of the sample, and the number of oysters attached to the surface of the sample on a monthly basis. Figure 2 shows some of the samples and accumulated fouling over the testing period. Table 2 shows the counts of each sample graphed over the seven month period with the nomenclature TNTC used to indicate that the barnacles were too numerous to count.

Figure 2: Static submersion tests on marine growth and fouling for HDPE samples.

Table 2: Barnacle count on each sample over duration of testing.

Sample ID and exposure side

Month

1

2

3

4

5

6

A

0

0

8

31

42

295

296

B

0

6

34

39

185

320

350

C

0

287

TNTC

TNTC

TNTC

TNTC

TNTC

D

0

47

65

168

195

TNTC

TNTC

E

0

1

32

37

67

215

409

F

0

101

115

138

320

TNTC

TNTC

G

0

7

0

8

41

420

420

H

0

255

475

550

TNTC

TNTC

TNTC

I

0

14

13

17

21

25

34

J

0

2

8

15

21

28

61

Figure 3 was developed with the raw barnacle count provided by Poseidon Sciences over the seven month period. Trend lines were developed for each data set with a y intercept set at zero for each trendline due to each sample entering the water with no surface fouling. Samples with TNTC values were only plotted to the highest counted value.

Figure 3: Barnacle count on each sample over a 7-month period.

Using the data from Figure 3, the growth rate per month (slope of the trend line) and R2 value of each sample were determined. Table 3 shows the ranking of samples from lowest growth rate to highest growth rate. Figure 4 is the graphical representation of the rate of growth for each sample as developed from Table 3.

Table 3: Barnacle growth rate on each sample arranged from smallest to largest growth rate.

Sample ID

Growth Rate

R^2 value

I

5.4

0.9706

J

7.2

0.8946

A

38.8

0.7709

E

43.7

0.7871

B

50.9

0.9001

G

52.9

0.7185

D

48.7

0.9789

F

67.5

0.9435

H

203.9

0.9816

C

287

1

Figure 4: Graph of barnacle growth rate for each sample.

Figure 4 and Table 3 provide data for the growth rates of each sample over the 7 month testing period that can be used to make some observations. Samples C, D, F, and H reached a TNTC value over the testing period with the sample C and sample H experiencing the most accelerated growth to TNTC. Samples C and H are both control samples and are composed of 100% HDPE and no antimicrobial additives. Samples I and J observed the slowest rate of growth with slopes of 5.5 and 7.2 respectively. Both samples I and J contain copper which indicates efficacy for this as an antifoulant additive in rotationally moulded HDPE samples. Copper is traditionally accepted as an antifoulant and useful in marine environments as it does not corrode in seawater. However, Washington state and California are currently investigating the regulation of the amounts of copper that can be used in marine environments. Additionally, international waters have different allowances for copper deposits in the ocean water. Environmental regulations must be considered in the selection of the individual antifouling additives and should be separated as a basis for optimization.

Figure 5 shows the barnacle growth of each sample comparing the growth from the first to the sixth month of submersion allowing a visual representation of fouling that occurred over the substrate submersion time. Please note that samples C, D, F, and H were discontinued before the six month mark due to complete fouling so the image shown here is the last month of recorded data for these samples.

Figure 5: Pictures of each sample from the first to last month of testing.

An overall scoring was assigned to each sample consistent with two industry standards: efficacy and cost. After years of interactions with oil majors including Saudi Aramco, Shell, and Chevron, a scoring system was jointly developed weighing the efficacy at a 60% value and the cost with a 40% value. The cost score is a ratio of the cost per square foot for the sample to the cost per square foot to the highest cost sample (F).The efficacy score is a ratio of the growth rate (Figure 4) of the sample to the growth rate of the highest sample (C). Given this weighting system, Table 4 (Regulated Waters) and Table 5 (Unregulated Waters) show the total sore for each sample. The total score is using the weighting system developed with the oil and gas majors and applying it to the individual scores. For example, for sample A, the total score is 0.4 multiplied by the cost score (5.6) plus 0.6 multiplied by the efficacy score (7.40). These scores are developed in an effort to optimize the functionality and cost of each individual antimicrobial additive mixture.

Table 4: Weighted scores of each antifoulant mixture for Environmentally Regulated Waters.

Sample ID

 

Cost/Sqt

Efficacy(growth rate)

Cost score

Efficacy score

Total score

A

$

14.78

38.8

5.6

7.4

6.66

B

$

10.09

50.9

8.1

5.64

6.64

D

$

2.81

48.7

29.2

5.89

15.22

E

$

4.35

43.7

18.9

6.57

11.49

Table 5: Weighted scores of each antifoulant mixture for Unregulated Waters.

Sample ID

 

Cost/Sqt

Efficacy

(growth rate)

Cost score

Efficacy score

Total score

F

$

82.14

67.5

1

4.25

2.95

G

$

8.02

52.9

10.2

5.43

7.35

I

$

79.78

5.4

1

53.15

32.3

J

$

13.54

7.2

6.1

39.86

26.34

Each sample containing an antifoulant additive mixed into the rotationally molded HDPE performed remarkably better than the two control samples. For unregulated waters, samples I and J containing forms of copper had the lowest overall growth rate in this study. For regulated waters, sample D contained the highest percentage of the commercial additive ANA and had the third lowest growth rate followed by the other mixtures. The least effective of the doped samples was sample F containing 100% zinc pyrithione doped at a 10% concentration to the HDPE. Overall, the two control samples had a higher growth rate and lower total score than all other samples indicating that each of the antimicrobial mixtures were somewhat effective at reducing fouling.

Conclusion And Future Work

Results from this study fill an increasing void as biofouling is a major problem in a variety of industries including oil and gas and marine vehicles and structures. Short-term coatings and a variety of chemicals are being used as a current solution, but the ability to fabricate the substrate material with an impregnated antimicrobial presents a creative long term solution. Additionally, tailoring the additive mixture to suit the environmental regulations in certain waters creates an opportunity for a ground-up approach to solution development.

In this study, HDPE samples impregnated with bactericidal materials were submerged in the Indian Ocean natural water over a period of seven months.The growth of individual barnacles on the surface were quantitatively analyzed.The antimicrobial efficacy, cost, and environmental regulations based on geographic location were considered for the overall product evaluation. Results show that for regulated waters, a blend of zinc oxide and ANA, a commercially available antifoulant, is the optimal formula. For unregulated waters, a blend of cuprous oxide and ANA provides the optimual formula for antifouling efficacy and cost effectiveness. This study was time and cost intensive and dependent upon a variety of environmental factors such as temperature, salinity, and growth rate of individual barnacles. It provides a valuable foundation for future antifouling product development. Future work will focus on the predictive machine learning approach to surface visualization and optimization of impregnated antifouling structures. curing salt can be reused in pickling.

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