Different effects of three soil microfloras on the corrosion of copper

Abstract

Many studies have indicated that microorganisms provide less protection or even detrimental effects to metals and alloys. In this study, surface analytical (SEM and EDS) and electrochemical techniques (polarization curves and EIS) were used to analyze the behaviour of copper corrosion by actinomyces, fungi and bacteria, which were isolated from the soil. Many pits and craters were presented on the copper surfaces after incubation with these three microfloras, and clear differences in the corrosion products and morphologies of the copper samples were observed in the fungi and bacteria groups compared with the control. The biofilm layer and the cumulated corrosion products are associated with an oxygen concentration cell, which may influence the corrosion susceptibility of copper. Our results suggest that the corrosion rate of copper samples increases more rapidly in the bacteria groups than in the actinomyces, while in the fungi groups it displays a volatile change with a large amplitude.

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Introduction

Microbiologically influenced corrosion (MIC) is one type of corrosion that can be very harmful to almost all engineering materials.^1,2 The loss due to MIC is so great that its impact on industry, the economy, and even public health could not be ignored.³ Microorganisms display a strong tendency to attach on metal and alloy surfaces, and biofilms could provide protection for the survival of microorganisms to a certain degree,^4,5 which result in changes in environmental factors such as pH, O₂/CO₂, organic acids, etc.⁶ Therefore, microorganisms could indirectly influence the corrosion behaviour of metals and alloys and, further, could disturb their natural corrosion process.^7–9

Recently, many scientists have researched the corrosion behaviour of microorganisms such as sulfate-reducing bacteria (SRB),^10,11 acid-producing bacteria,¹² and manganese/iron-oxidizing bacteria.¹³ They found that the mechanisms involved in MIC include cathodic depolarisation,¹⁰ fixing the anodic site,¹⁴ under-deposit acid attack¹⁵ and the formation of occluded areas on the metal surface.^16,17 However, the above bacteria are not the only bacteria or even the most important bacteria, but these are also the microflora that simultaneously or successively participate in MIC.

Copper is widely used in the transportation, machinery and building industries.¹⁸ Currently, to meet the needs of high-level radioactive waste (HLW) disposal,^19,20 copper is the selected packaging layer for the double-structured repository containers of Finland, Sweden, etc.^21,22 MIC is a complex process²³ that could occur in the atmosphere,^24,25 oceans²⁶ and the soil environment.^27,28 Copper is still corroded by microorganisms despite its superior performance on thermal stability and the protective film on its surface.²⁹ In a simulated underground storage tank sump environment containing acid-producing bacteria, Sowards et al.³⁰ reported that copper was superior to other metals in corrosion resistance, but the continued activity of microbial metabolites accelerates the corrosion course of copper. Chen et al.¹¹ found that SRB metabolism decreased the anodic zone area and promoted the localized corrosion of copper. The microflora environment of soil is very complex; microbial communities should be considered in researching microbiologically influenced corrosion.

HLW contains large radionuclides that might bring inestimable harm to humans and the environment. Studies on the corrosive behaviour of microorganisms on copper have concentrated on bacterial strains in seawater,²⁶ ground water³¹ and cooling water environments.³² However, research on the corrosion effect of soil microflora on copper is lacking. With the safe period of high-level radioactive waste repositories required to reach up to ten thousand years, the corrosion effect of soil microflora on copper, as the outer layer, may become a problem.¹⁹ This paper analyzes the corrosion behaviour of copper by actinomyces, fungi and bacteria after 180 days of immersion, based on the different corrosion processes of copper by each microflora independently, as each microflora could cause damaging effects on copper in optimal corrosion conditions. We use surface analytical and electrochemical techniques^33,34 to characterize the corrosion mechanism. Scanning electron microscopy (SEM) allows us to visualize the morphology of copper corrosion caused by different microorganisms. Energy-dispersive spectroscopy (EDS) evaluates the changes in the compositions of the corrosion product. Electrochemical techniques (Tafel polarization curves and electrochemical impedance spectra, EIS) analyze the corrosive behaviour of actinomyces, fungi and bacteria on copper.

Experimental method

Materials

The nominal composition of copper (wt%) is shown in Table 1, and the chemical composition of copper was determined by X-ray fluorescence spectrometer (Axios, Netherlands). The copper samples were 10 mm × 10 mm × 2 mm in size. Prior to the experiments, the test samples were sequentially ground with a series of grit SiC papers (400, 1000, 1500 and 2000#) to a smooth surface and sonicated sequentially in distilled (DI) water, ethanol, acetone and DI water for 10 min to degrease and clean the surface. The copper samples were vacuum-dried and then placed under ultraviolet lamp to sterilize the front and back for 20 min each prior to use.

Table 1 Chemical composition of copper (wt%)

Cu	Si	Ca	Al	P	S
98.86	0.76	0.26	0.08	0.02	0.02

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The actinomyces, fungi and bacteria were isolated from the soil (Gansu, China) by enrichment cultivation.^35,36 The compositions of Gause medium used to enrich and culture actinomyces are described by Cao et al.;³⁷ additionally, casein was added at a concentration of 0.3 g L⁻¹ and 1% K₂Cr₂O₇ was added at a ratio of 1 mL/100 mL before inoculating. The compositions of PDA medium used to enrich and culture fungi are described by Yadav et al.;³⁸ 1% streptomycin was added at a ratio of 0.3 mL/100 mL before inoculating. The compositions of LB medium used to enrich and culture bacteria are described in Kram et al.³⁹ A 5.5-fold higher concentration of medium than the original was used as feeding medium in the fed-batch culture method.⁴⁰ The pH of Gause medium was adjusted to 7.2 ± 0.1 using a 2 M NaOH, the LB medium was adjusted to 7.1 ± 0.1, and the pH of PDA medium was nature. Prior to the experiments, these strains were protected in a −20 °C refrigerator with glycerol.

Corrosion system establishment

In this work, three test groups were employed, with each group having a sterile and inoculated sector, i.e. actinomyces-sterile Gause medium (AS) and actinomyces-inoculated Gause medium (AI); fungi-sterile PDA medium (FS) and fungi-inoculated PDA medium (FI); and bacteria-sterile LB medium (BS) and bacteria-inoculated LB medium (BI). Using a fed-batch culture method, a 180 day continuous corrosion system was set up as shown in Table 2. Each sector had 4 copper that were immersed in a 250 mL Erlenmeyer flask containing 100 mL culture medium. A suspension of actinomyces, fungi and bacteria (1 mL, 24 h old) were added into the AI, FI and BI sectors (100 mL culture medium), respectively, as the treatments; these suspensions were not added in the controls. The flasks were incubated on a rotary shaker (DHZ-DA, Taicang, China) at 35 ± 1 °C and 110 rpm, 28 ± 1 °C and 110 rpm, 37 ± 1 °C and 110 rpm, respectively. A 5.5-fold higher concentration medium was added into each sector after 2, 9, 30, 60, 90, 120 and 150 days of immersion; meanwhile, copper samples were collected after 2, 9, 30, 60, 120 and 180 days of immersion. Each testing sector was performed in three parallel cycle repeats. The microflora cell number was determined using the plate count method as described by Falcone-Dias et al.⁴¹

Table 2 Experimental program^a

Group	Sector	Medium	Initial medium (mL)	24 h-old strains (mL)	Incubation temperature (°C)	Shaking speed (rpm)	Feeding medium (mL)	Fed-batch time (days)	Sampling time (days)
a “—” represent sectors without addition of these strains.
Actinomyces	Sterile	Gause	100	—	35 ± 1	110	10	2, 9, 30, 60, 90, 120, 150	2, 9, 30, 60, 120, 180
	Inoculated	Gause	100	1	35 ± 1	110	10	2, 9, 30, 60, 90, 120, 150	2, 9, 30, 60, 120, 180
Fungi	Sterile	PDA	100	—	28 ± 1	110	10	2, 9, 30, 60, 90, 120, 150	2, 9, 30, 60, 120, 180
	Inoculated	PDA	100	1	28 ± 1	110	10	2, 9, 30, 60, 90, 120, 150	2, 9, 30, 60, 120, 180
Bacteria	Sterile	LB	100	—	37 ± 1	110	15	2, 9, 30, 60, 90, 120, 150	2, 9, 30, 60, 120, 180
	Inoculated	LB	100	1	37 ± 1	110	15	2, 9, 30, 60, 90, 120, 150	2, 9, 30, 60, 120, 180

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Surface characterisation

The copper samples were sequentially rinsed of surface corrosion products using DI water, ethanol, acetone and DI water, prior to being dried.^9,27 The copper surface morphology was photographed by scanning electron microscope (SEM, Ultra55 model, Zeiss, Germany). To further observe the underlying corrosion damage to the metal, typical corrosion pits were selected for measurement. Elemental compositions of corrosion products were analyzed by energy-dispersive spectroscopy (EDS, Oxford IE450X-Max80 model, Zeiss, Germany). All measurements were repeated three times, and good reproducibility of the results was observed.

Electrochemical measurements

The copper samples were prepared as described in the Surface characterisation section. A conventional three-electrode cell was used to measure Tafel polarization curves and electrochemical impedance spectra (EIS) of the copper samples. The copper samples were prepared using epoxy glue to expose a 1 cm² surface, which was fixed at the wire as the working electrode. Platinum rod was used as the counter electrode and Na/NaCl as the reference electrode, with 2 wt% NaCl electrolyte solution at 25 ± 1 °C. CHI760c software was used to measure Tafel polarization curves and EIS in a CHI760c electrochemical workstation. At the open-circuit potential (OCP), the EIS measurements were conducted with 10 mV sinusoidal signal and frequency range from 50 mHz to 100 kHz. Polarization curves were tested at 10 mV s⁻¹ (scan rate) and −1.3 to +0.2 V (potential), which determine the corrosion current density (I_corr) and linear polarization resistance (R_LPR). The instantaneous corrosion rate can be measured by I_corr, and the following equation expresses the relationship between the corrosion rate and I_corr:^9,31where K is a constant that defines the units for the corrosion rate (K = 3.27 × 10⁻³), and the parameters V_depth, A, I_corr, n, M and ρ are the corrosion rate, surface area of samples, corrosion current density, electron number, molar weight and density of copper. All measurements were repeated at least three times, and good reproducibility of the results was observed.

Results and discussion

The number of viable microbial cells in microflora groups

In a closed environment and with certain nutrients provided, the growth curve of microorganisms includes four periods: lag phase, logarithmic phase, stationary phase, and decline phase.⁴² The fed-batch culture method can prolong the stable phase of microbial growth and maintain the count of viable microbial cells.

Fig. 1 shows the growth curves of actinomyces, fungi and bacteria in the inoculated sectors. The number of viable microbial cells increase rapidly in the earlier stage and range from 10⁶ to 10⁷ during the immersion period. The maximal value of the growth curves emerge in actinomyces after 18 days, fungi after 14 days and bacteria after 10 days. The slope of the growth curve of bacteria shows the highest maximal value among bacteria, fungi and actinomyces; the reason might be that bacteria grow and reproduce more quickly. From 15 to 120 days, the viable counts decrease slowly for these microorganisms, but the active cells of bacteria are higher than those of fungi and actinomyces. In the last stage, viable fungi cells have the maximum value. With the constant self-renewal of microbes, the death rate is faster than the regeneration rate, which makes the number of viable microbial cells decrease slowly. However, the microbial count is still maintained at a relatively high level in the last phase of the experiment.

Fig. 1 Growth curves of actinomyces, fungi and bacteria.

Surface morphology

Fig. 2 shows the representative SEM images of copper samples after 180 days of immersion in the actinomyces, fungi and bacteria groups, respectively. There are significant differences on the copper sample surfaces between the control and inoculated sectors. In the actinomyces groups, the copper surface has densely distributed corrosion pits both in the control and inoculated sectors, whereas the pore sizes range from 0.45 ± 0.15 to 4.63 ± 0.57 μm in the AI copper samples, which are larger than those in the control (Fig. 2a and b). In the fungi groups, the corrosion pits are sporadically distributed on the copper surface in the control, different from the FI, which has many larger distributed corrosion pits with pore size ranging from 6.22 ± 0.39 to 12.19 ± 0.83 μm (Fig. 2c and d). In the bacteria groups, the copper surface morphologies are different from those of actinomyces and fungi groups. The corrosion products are distributed loosely on the copper surface in the control, but in the BI copper, samples show adjacent pits, with craters from 9.59 ± 0.26 to 18.41 ± 0.77 μm linking to form wide cracks (Fig. 2e and f). Taken together, the pitting corrosion is accelerated by microflora, which is consistent with Natarajan et al.¹⁶ and Güngör et al.,³² who obtained pit or crevice corrosion images caused by microorganisms on metal surfaces.

Fig. 2 Representative SEM images of copper sample surfaces after 180 days of immersion in (a) actinomyces-sterile Gause medium (AS), (b) actinomyces-inoculated Gause medium (AI), (c) fungi-sterile PDA medium (FS), (d) fungi-inoculated PDA medium (FI), (e) bacteria-sterile LB medium (BS), and (f) bacteria-inoculated LB medium (BI).

Fig. 3 shows the corrosion product morphologies on the copper sample surfaces after 180 days of immersion. In the actinomyces groups, the corrosion product morphologies are hardly distinguished in the control and inoculated copper samples. However, after incubation with fungi and bacteria, copper samples show square or diamond-shaped corrosion in the control, different from the acicular products found in the inoculated samples. Another noteworthy feature is that biofilms covered the copper sample surfaces, and for the fungi groups, the biofilm layer was more intact than those of the other two groups. These results may be associated with the hyphae easily formed by fungi, and these extracellular polymeric substances (EPS) are helpful to the homogeneous structure of the biofilm.

Fig. 3 Corrosion product morphologies of copper samples after 180 days of immersion in (a) actinomyces-sterile Gause medium (AS), (b) actinomyces-inoculated Gause medium (AI), (c) fungi-sterile PDA medium (FS), (d) fungi-inoculated PDA medium (FI), (e) bacteria-sterile LB medium (BS), and (f) bacteria-inoculated LB medium (BI).

EDS was used to obtain elemental information of the corrosion products from representative areas on the copper surface.⁷ Fig. 4 shows the EDS results of copper samples after 180 days of immersion. For the different microflora groups, the carbon (C) content in the control is less than in the inoculated samples, which is attributed to the biofilm layer covering the copper surface (Fig. 3b, d and f). The Cu and O contents are different after corrosion by the different microfloras listed in Table 3. In the actinomyces and fungi groups, the Cu content in the inoculated samples is less than in the control, but it was opposite in the bacteria groups. This result in bacteria groups can be explained by the discontinuous craters that are linked to form cracks on the copper surface, which probably enlarges the specific surface area of copper substrate, and by the fact that biofilms were inhomogenous in the BI copper sample surfaces (Fig. 2f and 3f).

Fig. 4 EDS results of copper samples after 180 days of immersion in (a) actinomyces, (b) fungi and (c) bacteria groups.

Table 3 The EDS data of copper samples after 180 days of immersion in microflora groups

Component (wt%)	Actinomyces		Fungi		Bacteria
	Sterile	Inoculated	Sterile	Inoculated	Sterile	Inoculated
O	10.29	29.08	5.58	27.75	50.52	32.04
Cu	89.71	70.92	94.42	72.25	49.48	67.96

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Electrochemical behaviour of copper samples

In order to further evaluate the corrosion behaviour of copper, the study measured Tafel polarization curves and electrochemical impedance spectra (EIS) of copper samples in the actinomyces, fungi and bacteria groups.

Tafel polarization curves

Microorganisms may attach on metal and alloy surfaces concurrently with several electrodes in the reaction during the characterization of Tafel polarization curves at certain conditions.

Fig. 5 shows the Tafel polarization curves of copper samples after 0, 2, 9, 30, 60, 120 and 180 days of immersion in the actinomyces, fungi and bacteria groups. The anodic polarization curves of copper go into the passive region directly, without an active–passive transition area. The polarization curves of copper samples inoculated with actinomyces, fungi and bacteria display a shock tendency different from the control, suggesting that the microflora could interfere with the copper corrosion process. Moreover, the changes in polarization curves are also discrepant among these three microfloras. In the bacteria groups, the polarization curves of copper samples have a larger shift compared with the actinomyces and fungi groups, which indicates that bacteria have greater effect on the corrosion of copper. This result is probably caused by the accumulated states of passive films and corrosion products on the copper surface, leading to different anodic dissolution rates.

Fig. 5 Tafel polarization curves of copper samples after 0, 2, 9, 30, 60, 120 and 180 days of immersion in (a) actinomyces-sterile Gause medium (AS), (b) actinomyces-inoculated Gause medium (AI), (c) fungi-sterile PDA medium (FS), (d) fungi-inoculated PDA medium (FI), (e) bacteria-sterile LB medium (BS), (f) bacteria-inoculated LB medium (BI).

The anodic polarization curves show discrepant changes among microflora groups, indicating that anodic dissolution kinetics are different on the copper surfaces. In order to directly describe the degree of damage caused by MIC, the corrosion rate was investigated concretely. Various researchers have explored the corrosion rate caused by microorganisms using different methods, such as gravimetric measurement of corrosion mass loss and electrochemical measurement of the corrosion charge transfer Q and Faraday's law.^31,32,43 For the electrochemical measurement, the corrosion current density (I_corr) could be available to estimate the rate of copper corrosion by different microorganisms.^11,34 It should be noted that we only choose a standard to indicate the discrepancies among actinomyces, fungi and bacteria and to compare and analyze the corrosion behaviour induced by the microbial consortia in copper.

Table 4 shows the electrochemical parameters of the Tafel polarization curves of copper samples after 0, 2, 9, 30, 60, 120 and 180 days of immersion in the microflora groups. In theory, there should be an inversely proportional relation between corrosion current density (I_corr) and linear polarization resistance (R_LPR).³⁴ But in the test result, there are some points revealing a proportional relationship, which may be caused by the lower value of polarization value |E| and the higher value of the solution resistance (R_s) in the polarization curve testing process. The copper samples reach maximum R_LPR values after 9 days of immersion in the three microflora-inoculated groups, which indicates an intact biofilm layer distributed on the copper surface due to the number of viable microbial cells that increased rapidly in the earlier stage (Fig. 1).

Table 4 Analysis of Tafel polarization curves of copper samples after 0, 2, 9, 30, 60, 120 and 180 days of immersion in microflora groups

Time (days)	Sector	Actinomyces		Fungi		Bacteria
		I (μA cm^−2)	RLPR (Ω)	I (μA cm^−2)	RLPR (Ω)	I (μA cm^−2)	RLPR (Ω)
0	Sterile	5.50	7465	5.50	7465	5.50	7465
	Inoculated	5.50	7465	5.50	7465	5.50	7465
2	Sterile	10.44	4495	7.42	5689	11.15	3898
	Inoculated	9.81	4212	11.31	5130	17.93	2320
9	Sterile	14.37	3164	8.80	5090	16.91	2202
	Inoculated	3.17	10 866	2.90	11 170	9.39	4524
30	Sterile	9.97	5071	9.72	4109	99.64	503
	Inoculated	8.54	5124	7.94	5073	41.51	1377
60	Sterile	18.03	2279	8.71	5278	88.92	445
	Inoculated	21.31	2189	8.23	5222	113.20	488
120	Sterile	13.84	3396	21.85	1919	126.30	391
	Inoculated	24.11	1856	37.36	2096	139.60	316
180	Sterile	16.44	2797	39.52	1231	295	132
	Inoculated	32.72	1425	14.91	3081	340.40	170

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There is a proportional relationship between I_corr and the instantaneous corrosion rate. With the corrosion rate of the metal generally changing over time, the instantaneous corrosion rate of copper with respect to corrosion current density (I_corr) is of great significance in research.^31,34 The corrosion rate was calculated according to formula (1). The changes in the corrosion rate of copper samples immersed in microflora groups as a function of time are shown in Fig. 6. The corrosion rate, V_depth, displays increased tendency with prolonged immersion time, and the rate of increase also rises. The V_depth value of the copper sample in BI is approximately ten times larger than those in the AI and FI after 180 d of immersion. In the actinomyces groups, the V_depth values fluctuate within a small range in the AS copper samples, while AI values display an inhibition tendency before 30 days of immersion, and then undergo a significantly accelerated increase (Fig. 6a). In the fungi groups, there are no significant changes before 60 days of immersion, but increase is observed thereafter in the FS copper samples. Meanwhile, the V_depth values fluctuate with a large amplitude in the FI copper samples (Fig. 6b). In the bacteria groups, the variation tendency of corrosion rate is coincident with that of the actinomyces groups, but the rate of increase is larger than that of the actinomyces (Fig. 6a and c). The corrosion rate of copper samples in these three groups is basically in accordance with their respective SEM images. In other words, the corrosion morphologies and biofilms covering the copper sample surfaces are closely related to the corrosion process.⁴⁴

Fig. 6 The changes in corrosion rate of copper samples immersed in (a) actinomyces, (b) fungi and (c) bacteria groups as a function of time.

Electrochemical impedance spectra (EIS)

SEM images and Tafel polarization curves have shown that differences exist in the corrosion behaviour of copper in different microfloras. This assumes that the result is caused by the corrosion morphology and passive film that are formed with the participation of biofilms. EIS was used to investigate the electrochemical properties of corrosion morphology and passive film on copper sample surfaces after 180 days of immersion in different microflora groups.

As shown in Fig. 7a, the Nyquist semicircles of the copper samples have significant difference after 180 days of immersion in microflora groups, and the diameters are smaller than those in the untreated copper. The BI copper sample displays the minimum value. Warburg impedance is formed in the actinomyces groups, which could be associated with the quantity and size of corrosion pits, and the scale of coverage of the passive film (comprising biofilm and chemical deposits) on the copper surface.^34,45,46 In the fungi groups, a noteworthy feature is that the Nyquist semicircle diameter in the FI copper sample is larger than that of the control. The results may be mainly caused by the active fungi, which form a relatively dense and intact biofilm that act as a protective layer (Fig. 2d and 3d). The changes in Bode plots are in accordance with the Nyquist plots. As shown in Fig. 7b and c, the impedance modulus |Z| of copper samples show infinite values in the actinomyces groups. In the fungi groups, the phase angle peak in the FI copper sample shifts to the higher-frequency range, and the value of |Z| is also larger than that of the control. In the bacteria groups, the |Z| values undergo a dramatic decrease, leading to detrimental effects more serious than those in actinomyces and fungi groups. These results may be caused by the different activities of microfloras that have diverse kinds of metabolites (organic acid, enzymes, etc.) leading to different corrosion behaviours on copper, which are consistent with the above Tafel polarization curve analyses.

Fig. 7 Nyquist plots (a) and Bode plots (b and c) of copper samples after 180 d of immersion in AS (actinomyces-sterile Gause medium), AI (actinomyces-inoculated Gause medium), FS (fungi-sterile PDA medium), FI (fungi-inoculated PDA medium), BS (bacteria-sterile LB medium) and BI (bacteria-inoculated LB medium).

Fig. 8 shows the equivalent electric circuit based on (1) emerging Warburg impedance spectra and (2) the time constant, which can be appropriately used for fitting these impedance spectra. In addition, equivalent electric circuits were fitted by the electrochemical impedance analysis software Zsimpwin to achieve the impedance parameters tabulated in Table 5. For the AI copper sample, the value of Warburg impedance, Z_W, is approximately two-fold higher than that in the control. The increase in Z_W value is probably caused by the biofilms involved in the passive film formation processes, leading to a complicated ion diffusion process on the copper surface. An oxygen concentration cell might be formed due to the inhomogeneous biofilms, thus increasing the corrosion susceptibility. Compared with untreated copper, the values of passive film/biofilm resistance, R_f, of copper samples are decreased in fungi and bacteria groups, and the continuous decrease of η_f values further supports the view that the increased surface inhomogeneity is due to microbiologically influenced corrosion. However, the value of the charge transfer resistance, R_ct, of the copper sample in the FI is increased, suggesting that a barrier layer against ion transformation is formed by the intact biofilms, and large amounts of O₂ are consumed by fungal metabolism, which could induce the formation of a hypoxic area and reduce corrosion susceptibility. The R_ct value is further decreased for the BI copper sample, suggesting that the cumulated corrosion products aggravate the localized corrosion on the copper surface. These results are consistent with the above SEM observation of the porous structure and the biofilms covered on the copper surface.

Fig. 8 Equivalent electric circuits used for fitting the impedance spectra: (a) the copper samples in the actinomyces group, (b) the copper samples in the fungi and bacteria groups.

Table 5 Electrochemical model impedance parameters of copper samples after 180 days of immersion in microflora groups

	Untreated	Actinomyces		Fungi		Bacteria
		Sterile	Inoculated	Sterile	Inoculated	Sterile	Inoculated
Rs (Ω cm^2)	12.19	12.80	15.43	12.30	13.26	9.50	8.30
Rf (Ω cm^2)	2472	3993	4688	1640	18.07	90.21	220.10
Qf × 10^−5 (Ω^−1 cm^−2)	2.40	1.19	2.74	2.58	2.21	4.12	2.49
ηf	0.85	0.90	0.80	0.82	0.51	0.63	0.57
Rct (Ω cm^2)	2654	—	—	649.10	4378	697.20	194.20
Qdl × 10^−5 (Ω^−1 cm^−2)	1.72	—	—	11.35	2.40	10.71	5.47
ηdl	0.94	—	—	0.84	0.73	0.61	0.84
ZW × 10^−5 (Ω^−1 cm^−2)	—	94.73	174.30	—	—	—	—

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Through the above analysis, it can be easily concluded that the features of passive film could be influenced by the biofilms. The biofilms change the ion transfer between the electric double layer and the bulk solution, leading to discrepancies found in the control and inoculated copper samples, and also in the different microfloras. Microbiologically influenced corrosion is extremely complex; in order to understand the discrepancy among actinomyces, fungi and bacteria explicitly, future research should explore the relationships among metabolites and chemical factors under the biofilms.

Conclusion

Acting as an important factor, microorganisms affect the corrosion behaviour of copper. Biofilms are involved in the formation of passive film and influence the properties and structure of the passive film. The corrosion environment of a microbattery was constructed by microflora under the biofilms, which might be correlated with the accelerated pitting corrosion on copper. SEM images of copper samples immersed in inoculated test sectors show larger pits and craters on the surface.

The results of electrochemical measurements show different corrosion rates on copper among the actinomyces, fungi and bacteria, which are associated with the anodic dissolution rates. The corrosion rates of copper are gradually accelerated by actinomyces and bacteria, in which the bacterial corrosion rate presents the maximum value. In the fungi groups, we conclude that the dense and intact biofilms might act as a protective layer, which makes the corrosion rates display a volatile change with a large amplitude.

Acknowledgements

The authors wish to acknowledge financial support of this study under the national decommissioning of nuclear facilities and radioactive waste management research (12ZG6104).

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