Pico–nano bubble column flotation using static mixer-venturi tube for Pittsburgh No. 8 coal seam

International Journal of Mining Science and Technology 25 (2015) 347–354

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International Journal of Mining Science and Technology journal homepage: www.elsevier.com/locate/ijmst

Pico–nano bubble column flotation using static mixer-venturi tube for Pittsburgh No. 8 coal seam Peng Felicia F. ⇑, Yu Xiong The Department of Mining Engineering, West Virginia University, Morgantown 26506-6070, USA

a r t i c l e

i n f o

Article history: Received 10 September 2014 Received in revised form 5 November 2014 Accepted 12 December 2014 Available online 29 April 2015 Keywords: Pico–nano bubble generation Cavitation venturi tube Fine coal flotation Statistical analysis method

a b s t r a c t The flotation process is a particle-hydrophobic surface-based separation technique. To improve the essential flotation steps of collision and attachment probabilities, and reduce the step of detachment probabilities between air bubbles and hydrophobic particles, a selectively designed cavitation venturi tube combined with a static mixer can be used to generate very high numbers of pico and nano bubbles in a flotation column. Fully embraced by those high numbers of tiny bubbles, hydrophobic particles readily attract the tiny bubbles to their surfaces. The results of column flotation of Pittsburgh No. 8 seam coal are obtained in a 5.08 cm ID and 162 cm height flotation column equipped with a static mixer and cavitation venturi tube, using kerosene as collector and MIBC as frother. Design of the experimental procedure is combined with a statistical two-stepwise analysis to determine the optimal operating conditions for maximum recovery at a specified grade. The effect of independent variables on the responses has been explained. Combustible material recovery of 85–90% at clean coal product of 10–11% ash is obtained from feed of 29.6% ash, with a much-reduced amount of frother and collector than that used in conventional column flotation. The column flotation process utilizing pico and nano bubbles can also be extended to the lower limit and upper limit of particle size ranges, minus 75 lm and 300–600 lm, respectively, for better recovery. Ó 2015 Published by Elsevier B.V. on behalf of China University of Mining & Technology.

1. Introduction The separation efficiency of column flotation is determined by fine coal feed characteristics and the operating parameters associated with feed slurry-reagent conditioning, air bubble– hydrophobic coal particle contact, attachment and detachment, and size of air bubbles [1]. The feed characteristics can be particle size fraction by weight and density distribution, feed slurry volumetric flow rate, and solid concentration. Fine particles are known to have low momentum during the particle–air bubble collision due to their low mass. This results in low attachment and thus, low flotation rate. Coarser coal particles, with their higher mass and weak attachment force to air bubbles, often result in high detachment rates of particles from air bubbles, thus lowering flotation recovery [2,3]. Much research during the past two to three decades has centered on the development of air bubble sparger design to generate tiny bubbles for better attachment and lower detachment probabilities during flotation [4,5]. The recent development of bubble generation through use of a properly and ⇑ Corresponding author. Tel.: +1 304 2937680. E-mail address: [email protected] (F.F. Peng).

selectively designed cavitation venturi tube makes it possible to produce bubbles in the pico and nano size range [6–8]. These tiny bubbles are capable of attaching to and accumulating on the hydrophobic surfaces of fine coal particles, and forming multiple layers of hydrophobic bubbles over the surface of a particle [9,10]. In contrast, larger bubbles have higher mobility than the tiny bubbles, which provides a faster flotation rate. These have been reported by several research groups using visual high-speed cameras [11–13]. In this study, the systematic determination of the optimal operating performance for a flotation column with a combination of static mixer for micro bubble generation and a cavitation venturi tube for pico and nano bubble generation, is established based on empirical models obtained from test results. Initially, a six factors three levels center composite design of experimental procedure is used. Coefficient values for the parameters and interaction effects are determined. The three most significant key parameters are collector dosage, feed solid concentration and volumetric feed rate. Further, the experiment for a three factors three levels central composite design of experiment is conducted. Response surface methodology is applied to analyze the experimental data. The study of the effects of pico and nano bubbles on

http://dx.doi.org/10.1016/j.ijmst.2015.03.004 2095-2686/Ó 2015 Published by Elsevier B.V. on behalf of China University of Mining & Technology.

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flotation performance and optimized operating conditions on combustible material recovery and clean coal ash content, as functions of three key operating parameters is presented and discussed.

Wash water

2. Experimental

Clean coal Feed

Collector Frother

Valve

2.1. Materials

Pump Valve

A bituminous coal sample from the Pittsburgh No. 8 seam was acquired from Greene County, Pennsylvania, USA, for this study. After three days of air-drying, the coal sample was crushed, grinded, and pulverized through a Holms mill to prepare a minus 700 lm size fraction for the pico–nano bubble column flotation tests. The feed coal particle size and ash distributions are determined by the wet sieving method and ash analysis following the ASTM method. The results are given in Table 1, which is distributed over a wide size range, as indicated by 35.05% particles of coarser than 212 lm and 27.98% particles of finer than 45 lm. The feed ash content is 29.6%.

Valve Pump Flow meter Static mixer Valve

Flow Cavitation meter tube

Static mixer

Regulator Air

Flash water Tailings

Pump

2.2. Pico–nano bubble column flotation

Fig. 1. A schematic diagram of the flotation column, which is equipped with a static mixer and cavitation venturi tube for pico, nano and micro bubble generation.

Fig. 2. Basic cavitation venturi tube used for pico and nano bubble generation.

20 18 16 14 12 10 8 6 4 2 0 0.01

100 90 80 70 60

Population frequency Cumulative frequency under size

0.1

1

10

100

1000

50 40 30 20 10 0

Cumulative frequency (%)

Population frequency (%)

Fig. 1 shows the schematic diagram of a 5.08 cm ID and 210 cm height open flotation column equipped with a cavitation venturi tube and static mixer for pico, nano and micro bubble generation. The fine coal slurry is fed into a feed tank. The appropriate amount of collector and frother is then added to the slurry for preconditioning with a circulating pump. The feed slurry is then fed into the upper portion of the flotation column. Fresh water, air, and recirculating tailings are passed through the static mixer and cavitation venturi tube, connected in series, before being injected into the lower portion of the flotation column. The flotation column is also equipped with a wash water device to flush down the entrained ultrafine mineral particles, and a specially designed tailings discharge section to improve the mixing and contact of bubbles and solids by recirculating about one-third of the solids back into the flotation column. The cavitation venturi tube is specifically designed for generating pico and nano bubbles [14–16]. The basic cavitation venturi tube is shown in Fig. 2. Pico and nano bubbles have lower mobility characteristics than larger bubbles. The static mixer is used to generate micro bubbles and, more importantly, to improve the mixing and contact of bubbles and solids in the tailings recirculating stream. Fig. 3 shows the distribution of pico–nano bubbles, nano bubbles and micro bubbles generated by the optimally designed static mixer and cavitation venturi tube in a series configuration. There are three distinct modes observed on each population frequency curve, which are 0.08 lm, 0.7 lm and 11 lm, respectively representing pico–nano bubbles and nano bubbles generated by

Regulator Water

Bubble diameter (μ P) Table 1 Particle size and ash distributions for Pittsburgh No. 8 seam coal. Size range (lm)

+600 600 + 425 425 + 300 300 + 212 212 + 150 150 + 125 125 + 75 75 + 45 45 + 38 38

Individual

Fig. 3. Pico–nano, nano, and micro bubbles generated by static mixer-cavitation venturi tube with 20  106 MIBC.

Cumulative

Wt (%)

Ash (%)

Wt (%)

Ash (%)

7.15 6.02 8.09 13.79 10.78 2.24 12.77 11.17 1.71 26.28

33.88 34.41 29.44 19.34 16.25 21.65 17.08 22.54 35.39 47.48

100.00 92.85 86.83 78.74 64.95 54.17 51.92 39.15 27.98 26.28

29.56 29.23 28.87 28.81 30.82 33.72 34.24 39.84 46.74 47.48

the cavitation venturi tube and micro bubbles produced by the static mixer. The combustible material recovery and separation efficiency are defined as follows:

Yc ¼

At  Af At  Ac

Rc ¼ Y c

100  Ac 100  Af

ð1Þ

ð2Þ

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F.F. Peng, X. Yu / International Journal of Mining Science and Technology 25 (2015) 347–354 Table 2 Levels of variables for a six-factor three-level central composite design of experiment for column flotation using pico–nano bubbles. Variable

Table 5 Levels of variables for the three-factor three-level center composite design of experiment for column flotation using pico–nano bubbles.

Level

Gas flow rate, A (cm/s) Collector dosage, B (kg/mton) Frother concentration, C (106) Solid concentration, D (%) Feed rate, E (cm/s) Superficial wash water rate, F (cm/s)

Variable

Low 1

Middle 0

High 1

0.5 0.15 5 5 0.2 0.1

1.5 0.30 20 10 0.6 0.3

2.5 0.45 40 20 1 0.5

Level

Collector dosage, A (kg/ton) Solid concentration, B (%) Feed rate, C (cm/s)

Low 1

Middle 0

High +1

0.15 4 0.2

0.30 7 0.4

0.45 10 0.6

Note: Gas flow rate = 1.5 cm/s; frother dosage = 20  106 (ppm); superficial wash water rate = 0.3 cm/s. Table 6 Estimated coefficients (t-ratios and p-values) for the three-factor three-level central composite design of experiment.

Table 3 Estimated coefficients (t-ratios and p-values) for the six-factor three-level central composite design of experiment. Term

Intercept A B C D E F AB BC CD DE EF

Combustible material recovery model

Clean coal ash model

Estimate

Estimate

t Ratio

Prob. > |t|

9.05 0.48 0.006 0.03 2.5 0.99 0.68 0.11 6.00 1.07 9.08 0.06

8.19 1.4 2.41 1.14 2.53 2.78 0.45 1.37 1.5 1.46 0.67 1.13

<0.0001* 0.18 0.03* 0.27 0.02* 0.01* 0.66 0.19 0.15 0.16 0.51 0.28

95.21 1.07 4.73 0.10 1.07 10.18 4.56 6.00 3.86 0.0001 0.007 9.08

t Ratio

Prob. > |t| *

25.55 1.46 4.11 1.23 5.67 6.10 0.61 1.5 2.15 0.01 0.03 0.67

<0.0001 0.16 0.0009* 0.24 <0.0001* <0.0001* 0.55 0.15 1.88 0.99 0.98 0.51

Term

Intercept A B C AB AC BC AA BB CC

Clean coal ash model

Estimate

t Ratio

Prob > |t|

Estimate

t Ratio

Prob > |t|

83.04 64.47 126.49 221 4.73 57.08 0.66 73.02 0.01 18.48

3.83 1.3 1.70 2.63 2.20 1.77 0.20 1.95 0.05 1.38

0.0087* 0.24 0.14 0.04* 0.07 0.13 0.85 0.10 0.96 0.22

24.08 19.2 12.07 2.82 9.96 22.40

4.70 2.44 2.03 8.25 1.84 0.92

0.0033* 0.05 0.9 0.0002* 0.11 0.39

10.20

1.66

0.15

19.92

1.26

0.25

Note: * Means significant factors.

Arej ¼

Note: * Means significant factors.

Combustible material recovery model

ð100  Y c ÞAt Af

ð3Þ

Esp ¼ Rc  ð100  Arej Þ Table 4 ANOVA for the combustible material recovery and clean coal ash models based on the six-factor three-level central composite design of experiment. Source

Sum of squares

Degree of freedom

F value

Prob. > F

(a) Combustible material recovery model Model 1179.66 11 13.36 Error 120.41 15

<0.0001

(b) Clean coal ash model Model 31.21 8 Error 10.59 18

<0.0001⁄

4.02

⁄

R2

Adjusted R2

0.93

0.89

0.89

0.82

ð4Þ

where Ac stands for the clean coal product ash, %; Af the feed ash, %; At the tailings ash, %; Arej the Ash rejection, %; Esp the separation efficiency, %; Rc the combustible material recovery, %; Yc the clean coal yield, %; Yf the feed yield, %; and Yt the tailings yield, %. 3. Results and discussion 3.1. Design of experiment and statistical analysis method The analysis of column flotation test results is carried out using the statistics software package JMP program (SAS Institute, Inc.). In this study, combustible material recovery and clean coal ash are

12 90

Actual clean coal ash (%)

Actual combustible recovery (%)

95

85 80 75 70

65

70

75

80

85

90

Predicted combustible recovery (%) (a) Combustible recovery (%)

11 10 9 8

7

8

9

10

11

12

Predicted clean coal ash (%) (b) Clean coal ash (%)

Fig. 4. Predicted combustible recovery versus actual combustible recovery and predicted clean coal ash versus actual clean coal ash.

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Table 7 ANOVA for the combustible material recovery and clean coal ash models based on the three-factor three-level central composite design of experiment test results. Prob. > F

R2

Adjusted R2

(a) Combustible material recovery model Model 1290.41 9 4.78 Lack of fit 154.45 5 1.22

0.04⁄ 0.59

0.95

0.89

(b) Clean coal ash model Model 117.25 7 Lack of fit 15.44 7

0.0041⁄ 0.4700

0.93

0.88

Source

Sum of squares

Degree of freedom

F value

8.17 2.28

selected as the response surfaces. In running the JMP program, ‘‘Stepwise’’ regression analysis was selected. The Stepwise platform allows for searching through models with combinations of effects and choosing the desired model by setting the probabilities (p-value) threshold for statistical analysis.

The main and interaction coefficients are evaluated and tested for significance as shown in Table 3. The main effects of collector dosage, feed solid concentration and feed rate on recovery of combustible material and clean coal ash content are significant at the 95% confidence level, as indicated by the Probability > |t| values less than 0.05 when assessing the estimated coefficient. These findings indicate that the feasibility of producing pico and nano bubbles plays an important role in determining flotation performance. High solid concentration and feed rate would lead to a lack of pico and nano bubbles in the flotation process, which would affect the product grade. Also, collector dosage is very important in determining the clean coal grade. By using the optimal dosage of collector, a clean coal product with low ash content and high combustible material recovery is obtained. The order of main effects is: feed rate > feed solid concentration > collector dosage > gas flow rate > frother dosage > superficial wash water rate. Based on the statistical analysis results, the reduced combustible material recovery and clean coal ash models for the sixfactor three-levels design of experiment are:

Combustible Material Recovery ð%Þ ¼ 95:21 þ 1:07  A 3.2. Statistical analysis for the six-factor three-level central composite design of experiment

þ 4:73  B þ ð0:1Þ  C

The specific levels of individual variables are given in Table 2. The process parameters include collector dosage, frother concentration, gas flow rate, feed solid concentration, feed rate, and superficial wash water rate. Each factor is varied over three levels. A total of 27 six-factor three-level experimental designs are run for the column flotation using pico, nano, and micro bubbles.

 E þ ð4:56Þ  F þ ð6Þ  A  B þ 3:86  B  C

þ ð1:07Þ  D þ ð10:18Þ

þ ð0:0001Þ  C  D þ 0:007  D  E þ ð9:08Þ EF

0.5 90 80 70 60 50 40 30 0.4

Col

75

70

80

) (% 7 ion t a 8 tr cen 9 on c 10 lid So 6

lect

or d 0.3 osa ge (

0.2

kg/t

on)

Collector dosage (kg/ton)

Combustible recovery (%)

100 0.4 0.3

70

0.2

75 80

0.1 0

5

85 4

6

5

7

8

9

10

Solid concentration (%)

(a) Combustible material recovery

0.4

(%) Clean coal ash

13 11 9 7 5

13 12

3 1

11

0.4

Co

llec

tor

age

5

) (% on i t 8 tra en 9 nc o c 10 lid So

/ton

)

13

0.2

10

0.1

6

0.2

(kg

16

0.3

7

0.3

dos

10

11

Collector dosage (kg/ton)

15

0 4

5

6

7

8

9

Solid concentration (%)

(b) Clean coal ash

Fig. 5. Effect of solid concentration and collector dosage on combustible material recovery and clean coal ash.

10

ð5Þ

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F.F. Peng, X. Yu / International Journal of Mining Science and Technology 25 (2015) 347–354

Clean Coal Ash ð%Þ ¼ 9:05 þ ð0:48Þ  A þ ð0:006Þ  B þ 0:03  C þ 2:5  D þ ð0:99Þ  E þ 0:68  F þ 0:11  A  B þ ð6:00Þ  B  C þ 1:07  C  D þ ð9:08Þ  D  E þ ð0:06Þ  E  F

ð6Þ

In Table 4, model and error are listed separately to examine the error involved in the predictive equation. All major statistics analysis results in Table 4 show that the models for the combustible material recovery and clean coal ash models can adequately describe the effects of the operating parameters on the response variables. The comparison of the observed responses and predicted responses with the reduced model is shown in Fig. 4. 3.3. Three-factor three-level central composite design of experiment The study of the effects of pico and nano bubbles on flotation performance is carried out using a three-factor three-level central composite experimental design and analyzed by using the JMP program. The levels and variables for the three-factor three-level central composite design of experiment are given in Table 5. A total of 16 test runs are conducted for column flotation using pico, nano, and micro bubbles. The process parameters include collector dosage, feed solid concentration, and feed rate. Response surface methodology was used to analyze the three-factor three-level central composite design of experiment data. Response surface and contour curves were generated for the combustible material recovery and clean coal ash

content as a function of the operating process parameters. The specific levels of individual variables are indicated in Table 5. Each numeric factor is varied over three levels: plus and minus 1 (factorial points) and the center point. The levels of process variables are coded as 1, 0, and +1, where ‘‘1’’ represents the low or middle-low level, ‘‘0’’ represents the middle level, and ‘‘+1’’ represents the middle-high or high level of the factors. Figs. 5–7 show the effects of the three operating parameters on the combustible material recovery and clean coal ash content. The statistical analysis data in Table 6 show that statistically significant factors include collector dosage, feed solid concentration and feed rate. The data clearly show the importance of feed rate in determining the combustible material recovery and clean coal ash content, as indicated by the Probability > |t| values less than 0.05 when assessing the estimated coefficient. Table 7 is the ANOVA for the combustible material recovery and clean coal ash models. All major statistics indicate that the models can adequately describe the operating parameters’ effects on the response variables since the models do not have a significant lack of fit (Probability > F is greater than 0.1). To improve the model prediction for the clean coal ash model, as indicated by higher R2 and adjusted R2 values, two terms are removed (i.e., interaction between solid concentration and feed rate, BC, and double interaction of solid concentration, B2) based on their lack of significance in the evaluation. Based on the design of experiment tests and statistical analysis results, the combustible material recovery and ash content models for the three-factor three-level center composite design of experiment are: 0.6

90 0.5

90

Collector dosage (kg/ton)

Combustible recovery (%)

100

80 70 60 50 40

80

85

30

85

80 75

0.4

Col lect or d 0.3 osa 0.2 ge ( kg/t on)

0.3

85

0.4 0.3

80 80

80

0.2

75 82.5

0.1

/s) (cm e t ra

0.4 0.5

ed Fe

0.6

85

0 0.2

0.3

0.5

0.4

0.6

Feed rate (cm/s)

(a) Combustible material recovery

0.6

16

12 10 8 6 4

0.4 Co llec tor 0.3 dos age

13

10

11

12

0.2

Collector dosage (kg/ton)

(%) Clean coal ash

14

0.5

14

13 0.4

12 0.3

11 0.2 0.1

10 9

8

0.3

/s) (cm e t ra

0.4

0.2 (kg /ton )

0.5 0.6

ed Fe

0

0.1

0.2

0.3

0.4

Feed rate (cm/s) (b) Clean coal ash

Fig. 6. Effect of feed rate and collector dosage on combustible material recovery and clean coal ash.

0.5

352

F.F. Peng, X. Yu / International Journal of Mining Science and Technology 25 (2015) 347–354

10

75

9

80 70 60 50 40

85

80 30 75 So 5 0.5 lid 6 7 0.4 co nc /s) en 8 9 0.3 (cm tra e t a r tio n ( 10 0.2 Feed %)

Solid concentration (%)

ery (%) ible recov Combust

90

80

8 7 6

85

5 4 0.2

0.3

0.6

0.5 0.4 Feed rate (cm/s)

(a) Combustible material recovery

Solid concentration (%)

ash (%) Clean coal

8 12 11 7 10 9 6 8 7 5 6 5 4 4 12 So 5 lid 11 co 6 7 3 0.5 nc 10 0.4 en 8 ) tra 9 s / 0.3 cm tio te ( n 10 0.2 d ra (% e e F ) (b) Clean coal ash

10

11 12

0.1

0.2 0.3 Feed rate (cm/s)

0.4

Fig. 7. Effect of solid concentration and feed rate on combustible material recovery and clean coal ash.

Combustible Material Recovery ð%Þ ¼ 83:04 þ ð64:47Þ  A þ 126:49  B þ ð221Þ  C þ ð4:73Þ  A  B þ 57:08  A  C þ 0:66  B  C þ 73:02  A  A þ ð0:01Þ  B  B þ ð18:48Þ  C  C

ð7Þ

Clean Coal Ash ð%Þ ¼ 24:08 þ 19:20  A þ 12:07  B þ ð2:82Þ  C þ 9:96  A  B þ 22:4  A  C þ ð10:2Þ  A  A þ ð19:92Þ CC

ð8Þ

Fig. 5 indicates the effects of the feed solid concentration and the collector dosage on the combustible material recovery and clean coal ash content when the gas flow rate, frother concentration, superficial wash water rate, and feed rate are 1.6 cm/s, 20  106, 0.2 cm/s, and 0.2 cm/s, respectively. It can be clearly seen from the response surface and the contours of the combustible material recovery shown in Fig. 5a that the combustible material recovery considerably decreases with increasing the feed solid concentration and slightly increases with increasing the collector dosage. The contours of the combustible material recovery shown in Fig. 5a show that when the solid concentration decreases from 10% to 4%, the combustible material recovery increases from 75% to 85%, from 65% to 87%, and from 74% to 93% at the collector dosages of 0.15, 0.30, and 0.45 kg/mton, respectively. This means that pico and nano bubbles have a more significant effect on the combustible material recovery at the medium collector dosage

than at the higher collector dosage. It can be observed from the response surface and the contours of the clean coal ash content shown in Fig. 5b that the clean coal ash content increases with increasing the solid concentration and the collector dosage. Probably the overdosing of the collector caused a decrease in clean coal ash content at the high collector dosage and the high solid concentration. Fig. 5b shows that when the solid concentration increases from 4% to 10%, the clean coal ash content changes from 9.0% to 10.5%, from 11% to 10.3%, and from 15.0% to 9.8% at collector dosages of 0.15, 0.30, and 0.45 kg/mton, respectively. Thus, the optimal operating condition would be obtained at a medium collector dosage and low level of solid concentration, with 85–90% combustible material recovery and 10–11% clean coal ash. Fig. 6 shows the effects of the feed rate and the collector dosage on the combustible material recovery and clean coal ash content when the gas flow rate, frother concentration, superficial wash water rate, and feed solid concentration are 1.6 cm/s, 20  106, 0.2 cm/s, and 7%, respectively. It can be seen from the response surface and the contours of the clean coal ash content shown in Fig. 6b that clean coal ash content increases with increasing feed rate when the collector dosage ranges from 0.14 kg/mton to 0.27 kg/ton, and the decrease in clean coal ash content at higher collector dosages is caused by the overdosing of the collector. As can be observed in Fig. 6a, the flotation feed rate has remarkable impacts on the combustible material recovery. At a given collector dosage, the combustible material recovery significantly decreases with increasing feed rate, while, at a given feed rate, the combustible material recovery slightly increases as the collector dosage

Combustible material recovery (%)

F.F. Peng, X. Yu / International Journal of Mining Science and Technology 25 (2015) 347–354

620 lm. For example, the separation efficiency was increased by about 10% for 32 lm particles and 20% for 600 lm particles.

100 90 80

4. Conclusions

70 60 Release analysis

50 40

The following conclusions can be drawn from the findings of the factorial three-level central composite design of experiment test results for pico–nano column flotation of Pittsburgh No. 8 coal seam.

Six-factor threelevel DOE

30 20 10 0

Three-factor three-level DOE

10

20

30

Ash (%)

100

100

Separation efficiency (%)

90 90

80 70

80

60 70

50 40

60

40 10

30

With pico/nano bubble With micro bubble With pico/nano bubble With micro bubble 100

20 10 0 1000

Combustible material recovery (%)

Fig. 8. Combustible material recovery versus ash content for pico–nano bubble column flotation and release analysis.

50

353

Particle size (μP ) Fig. 9. Particle size effect on separation efficiency and combustible material recovery.

increases from 0.15 kg/mton to 0.45 kg/mton. The highest combustible material recovery was obtained at a collector dosage of 0.35 kg/mton and feed rate of about 0.4 cm/s, with clean coal ash at about 10.5%. Fig. 7 depicts the effects of the feed solid concentration and feed rate on the combustible material recovery and clean coal ash content when the gas flow rate, frother concentration, superficial wash water rate, and collector dosage are 1.6 cm/s, 20  106, 0.2 cm/s, and 0.15 kg/mton, respectively. It can be seen from Fig. 7a that the combustible material recovery increases considerably with decreasing feed rate from 0.6 cm/s to 0.4 cm/s and slightly increases with decreasing the solid concentration. As can be seen in Fig. 7b, the clean coal ash content increases with increasing the flotation feed rate from 0.2 cm/s to 0.6 cm/s and decreasing the solid concentration from 10% to 4%. After that, there is a slight decrease in the clean coal ash content. The experimental results provide a broad range of clean coal ash values, as shown in Fig. 8. The flotation column using pico, nano, and micro bubbles gives a reduction in ash content from 17.05% to a minimum of 7.25%, while recovering from 95% to 66.13%, respectively, from the six-factor three-level test results. For the three-factor three-level test results, a reduction in ash content from 11% to 7% was achieved with 90% to 66% combustible material recovery, respectively. The separation performances are significantly higher than the theoretical best performance predicted for froth flotation obtained from release analysis test results. Fig. 9 shows that the presence of pico, nano, and micro bubbles expanded the particle size range for effective flotation separation. The most significant improvement in separation efficiency was observed with particles finer than 75 lm and coarser than

(1) With the use of pico, nano, and micro bubbles in column flotation, the maximum combustible recovery of 85–90%, and minimum clean coal ash of 10–11% are achieved at solid concentration of 4%, collector dosage of 0.35 kg/mton, and feed flow rate of 0.4 cm/s, while maintaining air flow rate of 1.5 cm/s, frother dosage of 20  106, and superficial wash water rate of 0.3 cm/s, from 29.6% ash content of Pittsburgh No. 8 coal seam. (2) All three variables evaluated-feed solid concentration, collector dosage, and feed flow rate are significant in regard to achieving the maximum combustible recovery and producing the range of ash contents of fine clean coal products. (3) At the same combustible recovery, half of the collector dosage and frother dosage can be saved with column flotation in the presence of pico and nano bubbles, compared to the requirements of those reagents in conventional column flotation. (4) Use of a static mixer prior to a cavitation venturi tube in series for pico and nano bubble generation provides better mixing and contact of water, air, bubbles, and particulates from the tailings recirculation, which enhances pico and nano bubble generation. (5) The column flotation performance in the presence of pico, nano and micro bubbles exceeds the capability of conventional column flotation, with larger bubbles or micro bubbles alone, to float as fine as minus 75 lm ultrafines and as coarse as 300–600 lm particle size fractions.

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