Sieving or screen analysis is a common technique used to separate particles by size. It involves shaking a sample through a series of sieves with decreasing mesh sizes to separate particles. This document describes conducting a sieve analysis experiment on calcium carbonate over different time intervals. The results show that longer sieving times of 6 minutes produced the best separation of particles into different size fractions compared to 2 and 4 minute intervals. Sieve analysis provides useful information about particle size distribution that is important for understanding properties and performance.

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1. INTRODUCTION
Sieving or screen analysis is the oldest and most commonly used process for solid - solid
separation and it use in the analysis of the differences between the fine particles and coarse
particles. Thus, putting it in simple words, sieving is a simple and convenient technique of
separating particles of different sizes. It is commonly analyze using to methods, namely the
differential distribution and the cumulative distribution. By the analysis, one can identify the
particle population and determine average particle sizes of the sample particle.
Experiments in sieving is crucial to conduct sieve analysis of a product or a sample. This is
used to know some properties that might be involved in production. Examples of these
properties are rate of reactions, potential to dissolve, packing density, etc. Also, this prevents
bulking or aggregation of particles into unwanted larger sizes. Some common industrial use of
sieving is in construction and cement industries. General use of this method is common to all
production involving particulate matters in their process. Manufacturers can know their
products and find ways to develop some of its properties such as texture and appearance.

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2. REVIEW OF RELATED LITERATURE
A sieve analysis also known as gradation test procedure used to assess and determine
the particle size distribution of a particulate material by allowing the material to pass through
a series of sieves of progressively smaller mesh size. This is done by weighing the amount of
material that is retained by each sieve as a fraction of the whole mass.
The size distribution is often of crucial importance to the way the material performs in
use. A sieve analysis can be performed on any type of non-organic or organic granular
materials. Being such a simple technique of particle sizing, it is probably the most common.[1]
Sieves are equipment or device for separating wanted elements from unwanted element
or for characterizing the particle size distribution of a sample, usually using a woven screen
such as a mesh or net or metal. Terms linked to sieves or screen are mesh number, sieve
diameter and sieve aperture. Mesh size is the mesh number (a US measurement standard) and
its relationship to the size of the openings in the mesh and thus the size of particles that can
pass through these openings. Figuring out the mesh number is simple. It is defined as the
number of the wire strands (of same diameter) per inch weaved to square mesh pattern, sieve
diameter is defined as the width of the minimum square aperture through which the particle
will pass. A 100-mesh screen has 100 openings per inch, and so on. Thus, a higher mesh
number indicated a finer diameter of sieve. Sieve apertures or also known as screen openings
are the openings, gaps or holes in the sieves.
Particle size distribution of granular material or particles dispersed in fluid is a list of
values or a mathematical function that describes the relative amount, usually by mass, of
particles present according to size. This is very crucial since it estimates the population of
particles in a given dimension. Particle size is a property that is very important and critical to
industrial production or use of the material. Particle size affects many properties of granular

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materials, such properties are: stability of suspension, texture, rate of dissolution, packed
density, efficacy of delivery, flowability and handling, appearance, porosity and viscosity.
Units used for particle size depend of the size of particles, for coarse particles in inches or
millimeters, for fine particles the screen/sieve size, for very fine particles in micrometers or
nanometers and for ultra-fine particles the surface per unit mass (m2/g).
Differential or Distinctive particle size distribution is the percentage of particles from
the total that is within an instance size range. Differential screen analysis a type of sieve
analysis used to determine differential particle size distribution, sieve results are obtained in
differential weight/ mass percent retained on each sieve or the individual sieve weight/ mass
percent retained in each sieve.
Average Particle diameter = Screen opening of mesh x + Screen opening of mesh y(mesh
after x) /2
(Eq 3.1)
This equation estimates the average particle size for the graph of the differential
distribution.
Total Mass (g) = ∑ Individual Sieve Mass Retained (g)
(Eq 3.2)
% Mass Retained= Sieve mass Retained (g) in each individual Mesh
no.x100/Total Mass
(Eq 3.3)

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Progressive or cumulative particle size distribution is the sum of the differential
distributions. The cumulative distribution is acquired by the collection of differential
distribution. Cumulative screen analysis a type of sieve analysis used to determine cumulative
particle size distribution, sieve results obtained are in cumulative weight/ mass percent less
than the sieve size or cumulative percent passing.
Cumulative % Retained = Cumulative mass x 100/Total Mass
(Eq 3.5)
Cumulative % Passing = 100- Cumulative % Retained
(Eq 3.6)
Sieve analysis has, in general, been used for decades to monitor material quality based
on particle size. For coarse material, sizes that range down to #100 mesh (150μm), a sieve
analysis and particle size distribution is accurate and consistent.
However, for material that is finer than 100 mesh, dry sieving can be significantly less
accurate. This is because the mechanical energy required to make particles pass through an
opening and the surface attraction effects between the particles themselves and between
particles and the screen increase as the particle size decreases.

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3. EXPERIMENTAL SECTION: APPARATUS AND PROCEDURE
3.1 Materials
• Standard Tyler testing sieve (with cover and pan) with Mesh Number 20, 40,
60, 80, 100, 200
• Sieve Shaker
• Beakers (400 mL)
• Brush
• Analytical balance
• 200 grams of Calcium Carbonate (CaCO3)
3.2 Methods
200 grams of Calcium Carbonate was weighed in the beaker using an analytical
balance. Before commencing with the experiment, all equipment was freed from
suspended solids and dust. The sieves are arranged from the top to the bottom with
increasing mesh number (smallest sieve number from the topmost of the setup). The
weighed 200 grams of CaCO3 was placed in the topmost sieved and was covered. The
sieved was shaken at two-minute interval. After 2 minutes, the stack was carefully
removed from the shaker and each sieve was weighed accordingly. After weighing, the
sieves were carefully stacked again and was shaken with the same interval. The
procedure is repeated two times thus reaching the maximum time of 6 minutes. Data
were recorded each interval. The whole procedure was repeated for trial 2.

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4. RESULTS AND DISCUSSION
A. Differential Distribution
Figure 4a.1 : Differential Distribution
Based from the graph, the particles size which was based from the screen size with the
greatest mass fraction in each trials of the different time intervals can be determined. For time
interval 2 minutes trial 1 is 0.64 mm and for trial 2 is 0.64 mm. For time interval 4 minutes trial 1
is 0.325 mm and for trial 2 is 0.325 mm. For time interval 6 minutes trial 1 is 0.3 mm and for trial
2 is 0.3 mm. Since all trial in each time interval is the same, it can be said that the experiment is a
success. The graph shows the mass fraction in each sieve where only a specific size can pass
through. The six-minute sieving shows that a small portion of the sample was left in the first sieve.
Thus, this gives the idea that the more longer a sieve operate, the more particles are separated by
size.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
MassFraction
Particle size (mm)
Differential Distribution
Trial 1 (2
mins)
Trial2
(2mins)
Trial1
(4mins)
Trial2(4m
ins)
Trial1(6m
ins)
Trial2(6m
ins(

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B. Cumulative Distribution
Figure 4b.1: Cumulative Analysis for Two minutes sieving
The graph shows the percent of the sample passing through each sieve. Logarithmic
scale is used in the sieve size to compress the length of the line. It shows that in 2 minutes of
sieving, only 53% in the first trial and 47% in the 2nd
trial has passed the first sieve. The
curve also is not steep. This tells us that the mass fraction in each of the sieve is nearly equal.
0
10
20
30
40
50
60
70
80
90
100
0.11
%CumulativePassing
Sieve size mm (Logarithmic scale)
Cumulative Analysis (Two Minutes)
Trial 1
Trial 2

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Figure 4b.2: Cumulative Analysis for Four Minutes
The graph shows the percent of the sample passing through each sieve. Logarithmic
scale is used in the sieve size to compress the length of the line. It shows that in 4 minutes of
sieving, only 81% in the first trial and 82% in the 2nd
trial has passed the first sieve. This is
higher than the first trial. The curve also is medium steeper compared to the 2-minute sieving.
This shows that the difference between the mass fraction in each sieve is greater compared to
that of the 2-minute.
0
10
20
30
40
50
60
70
80
90
100
0.11
%CumulativePassing
Sieve size mm
Cumulative Analysis (Four Minutes)
Trial 1
Trial 2
0.0000
10.0000
20.0000
30.0000
40.0000
50.0000
60.0000
70.0000
80.0000
90.0000
100.0000
0.11
%CumulativePassing
Sieve Size mm (Logarithmic Scale)
Cumulative Analysis (Six Minutes)
Trial 1
Trial 2

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Figure 4b.2: Cumulative Analysis for Four Minutes
The graph shows the percent of the sample passing through each sieve. Logarithmic
scale is used in the sieve size to compress the length of the line. It shows that in 6 minutes of
sieving, 97% in the first trial and 97% in the 2nd
trial has passed the first sieve. The curve also
is the steepest among other trials. This tells us that the mass fraction in each of the sieve greatly
differs. This is because more of the particles are distributed among the holes of the sieves.

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5. CONCLUSION
Particle size and particle size distribution are the properties determined in the experiment
conducted. Screening or sieve analysis is used in this experiment. It is a very effective method to
determine the relative proportions of various sizes among different ranges. The sieve analyses
results are reported in a mass distribution of particles, the Differential Screen analysis reports the
individual retained mass in each sieve while Cumulative Screen Analysis reports the increasing
count of mass in the sieve, or the successive addition of the different sieve mass retained. The
experiment is a success because the date for trial 1 and 2 in the 2, 4, and 6 minutes of interval is
not far from each other. However, it is shown in the experiment that for longer time of sieving,
efficient separation of particles by its size is more observed.
6. RECOMMENDATION
It is recommended by the student to all of the sieves every after use.

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7. REFERENCES
https://www.retsch.com/applications/knowledge-base/sieve-
analysis?retsch_news2%5BnewsKey%5D=1191
http://www.solidswiki.com/index.php?title=Sieving
https://en.wikipedia.org/wiki/Sieve
https://www.911metallurgist.com/sieve-analysis-calculations-graph/
http://web.iyte.edu.tr/~sedatakkurt/me488/sieves2.html
David, 2017, Sieve Analysis and Graph (https://www.911metallurgist.com/sieve-analysis-
calculations-graph/)
Retch GmbH Haan . 2009, Sieve Analysis Taking a close look at quality

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8. APPENDICES
A. Raw data
Table 8a.1: Experiment Raw data
item Test Number
Test 1 (2mins) Test 2 (4mins) Test 3 (6mins)
Trial 1 Trial 2 Trial 1 Trial 2 Trial 1 Trial 2
Feed
Material CaCO3 CaCO3 CaCO3 CaCO3 CaCO3 CaCO3
Quantity 200 g 200 g 200 g 200 g 200 g 200 g
** through retained
** +20 mesh 96.25 107.67 39.01 35.59 7.48 7.37
-20 mesh +40 mesh 51.11 53.66 102.63 109.54 110.14 122.86
-40 mesh +60 mesh 41.79 31.72 47.68 45.08 64.8 54.83
-60 mesh +80 mesh 6.62 4.14 6.4 5.93 18.02 8.77
-80 mesh +100
mesh
2.54 1.65 2.46 2.36 4.22 3.61
-100 mesh +200
mesh
2.11 1.12 1.66 1.26 3.2 2.28
-200 mesh pan 0 0 0 0 0 0
Total (g) 200.42 199.96 199.84 199.76 207.86 199.72

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B. Computed data
Table 8b.1: Data for 2 minutes of Sieving
Table 8b.2: Data for 4 minutes of Sieving
Sieve Retained Cumulative
Mesh
Number
Size
(mm)
Retained
weight
(grams)
Retained percent %
Cumulative
weight (g)
Cumulative percent % Pass percentage %
Trial
1
Trial 2 Trial 1 Trial 2 Trial 1 Trial 2 Trial 1 Trial 2 Trial 1 Trial 2
20 0.841 96.25 107.67 0.480241 0.537222 96.25 107.67 48.02414929 53.835 51.97585 46.165
40 0.42 51.11 53.66 0.255014 0.267738 147.36 161.33 73.52559625 80.665 26.4744 19.335
60 0.25 41.79 31.72 0.208512 0.158268 189.15 193.05 94.3768087 96.525 5.623191 3.475
80 0.177 6.62 4.14 0.033031 0.020657 195.77 197.19 97.67987227 98.595 2.320128 1.405
100 0.149 2.54 1.65 0.012673 0.008233 198.31 198.84 98.94721086 99.42 1.052789 0.58
200 0.074 2.11 1.12 0.010528 0.005588 200.42 199.96 100 99.98 0 0.02
pan 0 0 0 0 0 200.42 199.96 100 99.98 0 0.02
Sieve Retained Cumulative
Mesh
Number
Size
(mm)
Retained
weight (grams)
Retained percent %
Cumulative
weight (g)
Cumulative percent % Pass percentage %
Trial 1 Trial 2 Trial 1 Trial 2 Trial 1 Trial 2 Trial 1 Trial 2 Trial 1 Trial 2
20 0.841 39.01 35.59 0.194641 0.177577 39.01 35.59 19.46412534 17.795 80.53587 82.205
40 0.42 102.63 109.54 0.512075 0.546552 141.64 145.13 70.67158966 72.565 29.32841 27.435
60 0.25 47.68 45.08 0.2379 0.224928 189.32 190.21 94.46163058 95.105 5.538369 4.895
80 0.177 6.4 5.93 0.031933 0.029588 195.72 196.14 97.65492466 98.07 2.345075 1.93
100 0.149 2.46 2.36 0.012274 0.011775 198.18 198.5 98.88234707 99.25 1.117653 0.75
200 0.074 1.66 1.26 0.008283 0.006287 199.84 199.76 99.71060772 99.88 0.289392 0.12
pan 0 0 0 0 0 199.84 199.76 99.71060772 99.88 0.289392 0.12

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Table 8b.3: Data for 6 minutes of Sieving
Sieve Retained Cumulative
Mesh
Number
Size
(mm)
Retained weight
(grams)
Retained
percent %
Cumulative weight
(g)
Cumulative percent
%
Pass percentage %
Trial 1 Trial 2 Trial 1 Trial 2 Trial 1 Trial 2 Trial 1 Trial 2 Trial 1 Trial 2
20 0.841 7.4800 7.3700 0.0360 0.0355 7.4800 7.3700 3.5986 3.5457 96.4014 96.4543
40 0.42 110.1400 122.8600 0.5299 0.5911 117.6200 130.2300 56.5862 62.6527 43.4138 37.3473
60 0.25 64.8000 54.8300 0.3117 0.2638 182.4200 185.0600 87.7610 89.0311 12.2390 10.9689
80 0.177 18.0200 8.7700 0.0867 0.0422 200.4400 193.8300 96.4303 93.2503 3.5697 6.7497
100 0.149 4.2200 3.6100 0.0203 0.0174 204.6600 197.4400 98.4605 94.9870 1.5395 5.0130
200 0.074 3.2000 2.2800 0.0154 0.0110 207.8600 199.7200 100.0000 96.0839 0.0000 3.9161
pan 0 0.0000 0.0000 0.0000 0.0000 207.8600 199.7200 100.0000 96.0839 0.0000 0.0000

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