experiment of boiling point elevation

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• Elevation Boiling Point

Boiling Point Elevation

What is boiling point elevation.

Boiling point elevation refers to the increase in the boiling point of a solvent upon the addition of a solute. When a non-volatile solute is added to a solvent, the resulting solution has a higher boiling point than that of the pure solvent. For example, the boiling point of a solution of sodium chloride (salt) and water is greater than that of pure water.

Boiling point elevation is a colligative property of matter, i.e. it is dependent on the solute-to-solvent ratio but not on the solute’s identity. This implies that the elevation in the boiling point of a solution depends on the amount of solute added to it. The greater the concentration of solute in the solution, the greater the boiling point elevation.

A graph detailing the elevation in the boiling point of water upon the addition of sucrose is provided above. At 1atm of pressure, pure water boils at 100 o C. However, a 10 molal solution of sucrose in water boils at approximately 105 o C.

Table of Contents

Why does boiling point elevation occur, boiling point elevation formula, solved examples.

The boiling point of a liquid is the temperature at which its vapour pressure is equal to the pressure of its surrounding environment. Non-volatile substances do not readily undergo evaporation and have very low vapour pressures (assumed to be zero). When a non-volatile solute is added to a solvent, the vapour pressure of the resulting solution is lower than that of the pure solvent.

Therefore, a greater amount of heat must be supplied to the solution for it to boil. This increase in the boiling point of the solution is the boiling point elevation. An increase in the concentration of added solute is accompanied by a further decrease in the vapour pressure of the solution and further elevation in the boiling point of the solution.

A pressure v/s temperature graph detailing the boiling point elevation of a solution is provided below.

Here, ΔT b represents the elevation in the boiling point of the solution. From the graph, it can be observed that –

• The freezing point of the solution is lower than that of the pure solvent ( freezing point depression ).
• The boiling point of the solution is higher than that of the pure solvent.

Note: The boiling point of a liquid is also dependent on the pressure of its surroundings (which is why water boils at temperatures lower than 100 o C at high altitudes, where the surrounding pressure is low).

The boiling point of a solution containing a non-volatile solute can be expressed as follows:

Boiling point of solution = boiling point of pure solvent + boiling point elevation (ΔT b )

The elevation in boiling point (ΔT b ) is proportional to the concentration of the solute in the solution. It can be calculated via the following equation.

ΔT b = i × K b × m

• i is the Van’t Hoff factor
• K b is the ebullioscopic constant
• m is the molality of the solute

It is important to note that this formula becomes less precise when the concentration of the solute is very high. Also, this formula doesn’t hold true for volatile solvents.

The ebullioscopic constant (K b ) is often expressed in terms of o C/molal or o C.kg.mol -1 . The values of K b for some common solvents are tabulated below.

The degree of dissociation of the solute and the molar mass of the solute can be calculated with the help of the boiling point elevation formula.

Calculate the boiling point of a 3.5% solution (by weight) of sodium chloride in water.

1 kg of the given solution contains 0.035kg of NaCl and 0.965kg of H 2 O. Since the molar mass of NaCl is 58.5, the number of moles of NaCl in 1 kg of the solution is:

(35g)/(58.5g.mol -1 ) = 0.598 moles

The molality of NaCl in 1kg of the solution can be calculated as:

m = (0.598mol)/(0.965 kg) = 0.619 molal

The boiling point elevation constant of water is 0.512 o C.kg/molal. Since NaCl dissociates into 2 ions, the Van’t Hoff factor for this compound is 2. Therefore, the boiling point elevation (ΔT b ) can be calculated as follows:

ΔT b = 2 × (0.52 o C/molal) × (0.619 molal) = 0.643 o C

Boiling point of the solution = boiling point of pure solvent + boiling point elevation

= 100 o C + 0.643 o C = 100.643 o C

Therefore, the boiling point of the 3.5% NaCl solution is 100.643 o C.

10 grams of a non-volatile and non-dissociating solute is dissolved in 200 grams of benzene. The resulting solution boils at a temperature of 81.2 o C. Find the molar mass of the solute.

Let x = number of moles of solute. The boiling point of pure benzene is 80.1 o C and it’s ebullioscopic constant is 2.53 o C/molal. From the boiling point elevation formula, the following relationship can be obtained:

(81.2 o C – 80.1 o C) = (1) × (2.53 o C.kg.mol -1 )(x/0.2 kg)

x = (1.1 o C × 0.2kg)/(2.53 o C.kg.mol -1 )

x = 0.0869 moles

Since 0.0869 moles of the solute has a mass of 10 grams, 1 mole of the solute will have a mass of 10/0.0869 grams, which is equal to 115.07 grams. Therefore, the molar mass of the solute is 115.07 grams per mole.

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for the second example why is ‘i’ 1?

It is given in the question that the solute is non-dissociating. Therefore, the value of i can be assumed to be 1.

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Salt and the boiling temperature of water

Introduction: (initial observation).

At home hot water is used for cooking and heating systems such as hot water radiators. In laboratories hot water is used in water baths. Hot water has many industrial applications as well.

One problem with water is that it never gets hotter than 100º Celsius. Any additional heat will only cause more evaporation. Being able to control or modify the boiling point of water may be helpful for any applications requiring heat transfer.

In this project you will study the effect of table salt on the boiling temperature of water. Report your results in a table and draw a graph to visually display your results.

If you have any questions, click on the “Ask Question” button at the top of this page to send me your questions. I may respond by email, but often I update this page with the information that you need.

You will also need to know:

• How to select a project?
• What are variables (Dependent, Independent, Control)?
• What is a control experiment?
• How can I do analysis and discussion?
• Do I need a graphs or a chart?
• What is an abstract? How to write it?
• Samples of display boards   
• How to write a report?

Project Advisor

Information Gathering:

Find out about boiling and boiling point point. Read books, magazines or ask professionals who might know in order to learn about the effect of salt on the boiling point of water. Keep track of where you got your information from.

matter : anything that occupies space and has mass.

mass : the quantity of matter contained by an object. Mass is measured in terms of the force required to change the speed or direction of its movement.

liquid : the state in which matter takes the shape of its container, assumes a horizontal upper surface, and has a fairly definite volume.

boiling point : the temperature at which the vapor pressure of a liquid equals the pressure of the gas above it.

temperature : measure of the hotness or coldness of a body.

pressure : force exerted on a unit area. The SI unit of pressure is the Pascal (Pa).

gas : the state in which matter has neither definite volume nor shape.

boiling -point elevation: the elevation of the boiling point of a liquid by addition of a solute.

Effect of air pressure

A liquid boils when its vapor pressure becomes equal to atmospheric pressure. Low atmospheric pressure causes the boiling point to go down; high pressure drives it up. Atmospheric pressure varies a bit from day to day, depending on the weather, and it varies from place to place, depending on the altitude.

Other related links:

• Boiling Point
• Boiling point elevation
• Boiling temperature of water solutions

Question/ Purpose:

What do you want to find out? Write a statement that describes what you want to do. Use your observations and questions to write the statement.

The purpose of this project is to determine the effect of salt on the boiling point of water.

Identify Variables:

When you think you know what variables may be involved, think about ways to change one at a time. If you change more than one at a time, you will not know what variable is causing your observation. Sometimes variables are linked and work together to cause something. At first, try to choose variables that you think act independently of each other.

• The independent variable (also known as manipulated variable) is the amount of salt.
• Dependent variable (also known as responding variable) is the boiling point of water.
• Controlled variables are the air temperature and pressure. Perform all your experiments in the same day while the air pressure and temperature will not be subject to noticeable changes.

Hypothesis:

Based on your gathered information, make an educated guess about the effect of salt on boiling point of water.

Following are two sample hypothesis:

Sample hypothesis 1:

I hypothesize that salt will reduce the boiling point of water. My hypothesis is based on my information that salt reduce the freezing point of water and it is used as an anti freeze in winter.

Sample hypothesis 2:

I hypothesize that salt will increase the boiling point of water. My hypothesis is based on my information that salt does not boil as easy as water, so when mixed with water it may make it hard for water to boil as well.

Experiment Design:

Design an experiment to test each hypothesis. Make a step-by-step list of what you will do to answer each question. This list is called an experimental procedure. For an experiment to give answers you can trust, it must have a “control.” A control is an additional experimental trial or run. It is a separate experiment, done exactly like the others. The only difference is that no experimental variables are changed. A control is a neutral “reference point” for comparison that allows you to see what changing a variable does by comparing it to not changing anything. Dependable controls are sometimes very hard to develop. They can be the hardest part of a project. Without a control you cannot be sure that changing the variable causes your observations. A series of experiments that includes a control is called a “controlled experiment.”

Introduction : In this experiment you will test the effect of table salt (sodium chloride) on the boiling point of water. You may repeat this experiment with other solutes such as sugar, Epsom salt (Magnesium sulfate) and Salt cake (Sodium sulfate). Experiment involve preparing salt-water solutions with different amounts of salt; heat them to the boiling temperature and then measure and record the temperature while the solution is boiling.

• Fill up a glass beaker or a small pot with 100 ml distilled water.
• Place a thermometer in the water several centimeters from the bottom of the pot. Make sure you are using a thermometer with at least one degree markings to insure accurate measurements.
• Begin to heat the water. Take temperature readings every 10 seconds.
• Continue reading the temperature until it remains constant for at least four measurements. This is the boiling point.
• Repeat the steps 1 to 4; however, each time add a different amount of salt to the water. Suggested amounts of salt are 5, 10, 15, 20 and 25 grams as shown in the following table.

Your results table may look like this:

• Use tap water or drinking water if you don’t have access to the distilled water
• If your pot or beaker are big and you need to do your experiment with more water, increase the amount of salt at the same ratio.
• C = Celsius Temperature Scale (Centigrade)
• F = Fahrenheit
• If you don’t have a scale to weight 5 grams salt, use one small tea spoon. That will hold approximately 5 grams of salt.
• The first experiment with pure water is also the control for your other experiments.
• 102ºC and 106ºC in the above table are possible answers reported by other students. Please note that they may be wrong or inaccurate!

Make a bar graph:

For each of the six solutions that you test make a vertical bar (so your graph will have 6 vertical bars). The height of each bar will represent the boiling temperature of one specific solution. The name of the bar will be the amount of salt added.

The bar graph in the right is for a similar experiment with only 3 different solutions. 0 is for no salt, 1 is for 1 table spoon and 2 is for 2 table spoon salt in one quart of water.

Materials and Equipment:

• Thermometer* (available at science suppliers),
• Glass beakers or metal pots,
• Electric stove (hotplate)

* Glass and dial thermometers shown above are available at MiniScience.com and klk.com. Either of the two models may be used for freezing temperatures. Dial thermometers last longer; however, glass thermometers are more accurate.

Results of Experiment (Observation):

The above table will be completed and used as the result of your experiment. You may also write in a paragraph or two the result. What you write may be an answer to the following questions:

1. What was the highest temperature that the salt water reached?

2. At what temperature does the pure water boil?

If the thermometer extends beyond the outside of the pot it reads a higher temperature. Heat from the stove burner makes the thermometer read higher. Keep the thermometer over the pot when making temperature measurements.

Calculations:

No calculation is required

Summary of Results:

Summarize what happened. This can be in the form of a table of processed numerical data, or graphs. It could also be a written statement of what occurred during experiments.

It is from calculations using recorded data that tables and graphs are made. Studying tables and graphs, we can see trends that tell us how different variables cause our observations. Based on these trends, we can draw conclusions about the system under study. These conclusions help us confirm or deny our original hypothesis. Often, mathematical equations can be made from graphs. These equations allow us to predict how a change will affect the system without the need to do additional experiments. Advanced levels of experimental science rely heavily on graphical and mathematical analysis of data. At this level, science becomes even more interesting and powerful.

Conclusion:

Using the trends in your experimental data and your experimental observations, try to describe the effect of salt on freezing point of water. Is your hypothesis correct? Now is the time to pull together what happened, and assess the experiments you did.

Related Questions & Answers:

What you have learned may allow you to answer other questions. Many questions are related. Several new questions may have occurred to you while doing experiments. You may now be able to understand or verify things that you discovered when gathering information for the project. Questions lead to more questions, which lead to additional hypothesis that need to be tested.

Possible Errors:

If you did not observe anything different than what happened with your control, the variable you changed may not affect the system you are investigating. If you did not observe a consistent, reproducible trend in your series of experimental runs there may be experimental errors affecting your results. The first thing to check is how you are making your measurements. Is the measurement method questionable or unreliable? Maybe you are reading a scale incorrectly, or maybe the measuring instrument is working erratically.

If you determine that experimental errors are influencing your results, carefully rethink the design of your experiments. Review each step of the procedure to find sources of potential errors. If possible, have a scientist review the procedure with you. Sometimes the designer of an experiment can miss the obvious.

References:

Visit your local library and find books about salt, water, general chemistry, physical chemistry or chemical physics. Look for chapters that discuss changes in physical properties of a substance when mixed with other substances.

List the books and the online resources that you use in this part of your report.

It is always important for students, parents and teachers to know a good source for science related equipment and supplies they need for their science activities. Please note that many online stores for science supplies are managed by MiniScience.

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Science Project

Δt = i K b m

Substance K b benzene 2.53 camphor 5.95 carbon tetrachloride 5.03 ethyl ether 2.02 water 0.52

1) K m¯ 1 : Kelvin is used rather than degrees Celsius. However, the "distance" between a single Celsius degree and a Kelvin are the same, the numerical value is unaffected. It's seldom seen and I will tend to ignore it. 2) °C kg mol¯ 1 : this one takes molal (mol/kg) and brings the kg (which is in the denominator of the denominator) and brings it to the numerator.

11.4 g / 17.031 g/mol = 0.6693676 mol 0.6693676 mol / 0.200 kg = 3.3468 m

Δt = i K b m Δt = (1) (0.52 °C/m) (3.3468 m) Δt = 1.74 °C

ΔT = i K b m 0.49 °C = (1) (4.95 °C kg mol¯ 1 ) (x / 0.0360 kg) 0.49 °C = (137.5 °C mol¯ 1 ) (x) x = 0.0035636 mol

0.64 g / 0.0035636 mol = 180 g/mol (to two sig figs)

Δt = i K b m 9.1 °C = (1) (3.08 °C kg mol¯ 1 ) (x / 0.937 kg) 9.1 °C = (3.287 °C mol¯ 1 ) (x) x = 2.7684 mol

(2.7684 mol) (180.1548 g/mol) = 499 g (to three sig figs)

Δt = i K b m 3.68 °C = (1) (3.63 °C kg mol¯ 1 ) (x / 0.00100 kg) x = 0.00368 kg °C / 3.63 °C kg mol¯ 1 = 0.0010137741 mol 0.1665 g / 0.0010137741 mol = 164.2 g/mol Note: °C / m equals °C kg mol¯ 1

Δt = i K b m 1.35 °C = (1) (5.03 °C kg mol¯ 1 ) (x / 0.0160 kg) 1.35 °C = (314.375 °C mol¯ 1 ) (x) x = 0.00429423 mol

5.00 g / 0.00429423 mol = 1160 g/mol (to three sig figs)

ΔT = i K f m

0.201 °C = (x) (1.86 °C m¯ 1 ) (0.10 m) x = 1.08

2.6 K = (x) (5.10 K m ¯ 1 ) (1.00 m ) x = 0.51

4.81 g of MgCl 2 95.19 g of H 2 O mole of MgCl 2 ---> 4.81 g / 95.211 g/mol = 0.0505194 mol

Δt = i K b m x = (2.7) (0.512 °C kg mol¯ 1 ) (0.0505194 mol / 0.09519 kg) Note how I modified the unit on the boiling point elevation constant. x = 0.73 °C (to two sig figs)

100.73 °C

(a) 0.25 m sucrose(aq) (b) 0.15 m KNO 3 (aq) (c) 0.048 m C 10 H 8 (naphthalene) in benzene (d) 0.15 m CH 3 COOH(aq) (e) 0.15 m H 2 SO 4 (aq)

(a) 0.25 m x 1 = 0.25 m (b) 0.15 m x 2 = 0.30 m (c) 0.048 m x 1 = 0.048 m (d) 0.15 m x 1 = 0.15 m (e) 0.15 m x 3 = 0.45 m The value to the right of each above calculation is the van 't Hoff factor.

C D A B E Reason: the more particles in solution, the greater the bp elevation

(i) 4.98 g of the compound was dissolved in 100. g of benzene. The boiling temperature of the resulting solution was 82.3 °C. (ii) A separate experiment found the compound to be 46.65% (by mass) nitrogen, 6.71% hydrogen, 26.64% oxygen and the remainder was carbon. (iii) The density of the solution is 0.8989 g/mL

These values are not provided in the problem: bp of benzene = 82.3 °C and K b for benzene = 2.53 °C/m Δt = i K b m 2.1 °C = (1) (2.53 °C/m) (x) x = 0.83 m 0.83 mol/kg = y / 0.1 kg y = 0.083 mol molecular mass ---> 4.98 g / 0.083 mol = 60.0 g/mol

N ---> 46.65 g H ---> 6.71 g O ---> 26.64 g C ---> 20.00 g

N ---> 46.65 g / 14.007 g/mol = 3.330 mol H ---> 6.71 g / 1.008 g/mol = 6.657 mol O ---> 26.64 g / 16.00 g/mol = 1.665 mol C ---> 20.00 g / 12.011 g/mol = 1.665 mol

N ---> 3.330 mol / 1.665 mol = 2 H ---> 6.657 mol / 1.665 mol = 3.998 = 4 O ---> 1.665 mol / 1.665 mol = 1 C ---> 1.665 mol / 1.665 mol = 1

The "empirical formula weight" equals 60.05 g. The molecular weight equals 60.0 g. Since the two values are the same, we can determine the molecular formula to be CH 4 N 2 O, same as the empirical formula.

100. g / 78.1118 g/mol = 1.280 mol

0.083 mol     ––––––––––––––––––  =  0.061 1.280 mol + 0.083 mol    

104.98 g / 0.8989 g/mL = 116.787 mL = 0.116787 L

0.083 mol / 0.116787 L = 0.7107 M Two sig figs would give a final answer of 0.71 M

Azeotrope Number Binary 1743 Ternary 177 Quaternary 21 Quinary 2

Substance Percent by Weight Water 9.45 Nitromethane 37.30 Tetrachloroethylene 21.15 n-Propyl alcohol 10.58 n-Octane 21.52

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Boiling Point Elevation- Definition and Example

Boiling point elevation is the increase in the boiling point of a solvent by dissolving a nonvolatile solute into it. For example, dissolving salt in water raises the boiling point of water so that it is higher than 100 °C. Like freezing point depression and osmotic pressure , boiling point elevation is a colligative property of matter . In other words, the effect depends on how many solute particles dissolve into the solvent and not on the nature of the solute.

How Boiling Point Elevation Works

Dissolving a solute in a solvent lowers the vapor pressure above the solvent. Boiling happens when the vapor pressure of the liquid equals the vapor pressure of the air above it. So, it takes more heat to give the molecules enough energy to transition from the liquid to vapor phase. In other words, boiling occurs at a higher temperature.

The reason this happens is because the solute particles are not volatile , so at any given time they are most likely in the liquid phase and not the gas phase. Boiling point elevation also occurs with volatile solvents, partly because the solute dilutes the solvent. The extra molecules affect interactions between solvent molecules.

While electrolytes have the largest effect on boiling point elevation, it occurs regardless of the nature of the solute. Electrolytes, like salts, acids, and bases, break into their ions in solution. The more particles added to the solvent, the greater the effect on boiling point. For example, sugar has less of an effect than salt (NaCl), which in turn has less of an effect than calcium chloride (CaCl 2 ). Sugar dissolves but does not dissociate into ion. Salt breaks into two particles (Na + and Cl – ), while calcium chloride breaks into three particles (one Ca + and two Cl – ).

Similarly, a solution of higher concentration has a higher boiling point than one of lower concentration. For example, a 0.02 M NaCl solution has a higher boiling point than a 0.01 M NaCl solution.

Boiling Point Elevation Formula

The boiling point formula calculates the temperature difference between the normal boiling point of the solvent and the boiling point of the solution. The temperature difference is the boiling point elevation constant (K b ) or ebullioscopic constant , multiplied by the molal solute concentration. So, boiling point elevation is directly proportional to solute concentration.

ΔT = K b · m

Another form of the boiling point formula uses the Clausius-Clapeyron equation and Raoult’s law:

ΔT b  = molality * K b  * i

Here, i is the van’t Hoff factor . The van’t Hoff factor is the number of moles of particles in solution per mole of solute. For example, the van’t Hoff factor for sucrose in water is 1 because sugar dissolves, but doesn’t dissociate. The van’t Hoff factors for salt and calcium chloride in water are 2 and 3, respectively.

Note: The boiling point elevation formula only applies to dilute solutions! You can use it for concentrated solutions, but it only gives an approximate answer.

Boiling Point Elevation Constant

The boiling point elevation constant is a proportionality factors that is the change in boiling point for a 1 molal solution. K b is a property of the solvent. Its value depends on temperature, so a table of values includes temperature. For example, here are some boiling point elevation constant values for common solvents:

Boiling Point Elevation Problem – Dissolving Salt in Water

For example, find the boiling point of a solution of 31.65 g of sodium chloride in 220.0 mL of water at 34 °C. Assume all of the salt dissolves. The density of water at 35 °C is 0.994 g/mL and K b  water is 0.51 °C kg/mol.

Calculate Molality

The first step is calculating the molalit y of the salt solution. From the periodic table, the atomic weight of sodium (Na) is 22.99, while the atomic weight of chlorine is 35.45. The formula of salt is NaCl, so its mass is 22.99 plus 35.45 or 58.44.

Next, determine how many moles of NaCl are present.

moles of NaCl = 31.65 g x 1 mol/(22.99 + 35.45) moles of NaCl = 31.65 g x 1 mol/58.44 g moles of NaCl = 0.542 mol

In most problems, you assume the density of water is essentially 1 g/ml. Then, the salt concentration is the number of moles divided by the number of liters of water (0.2200). But, in this example, the water temperature is high enough that its density is different.

kg water = density x volume kg water = 0.994 g/mL x 220 mL x 1 kg/1000 g kg water = 0.219 kg m NaCl  = moles of NaCl/kg water m NaCl  = 0.542 mol/0.219 kg m NaCl  = 2.477 mol/kg

Find the van’t Hoff Factor

For nonelectrolytes, the van’t Hoff factor is 1. For electrolytes, it is the number of particles that form when the solute dissociates in the solvent. Salt dissociates into two ions (Na + and Cl – ), so the van’t Hoff factor is 2.

Apply the Boiling Point Elevation Formula

The boiling point elevation formula tells you the temperature difference between the new and original boiling point.

ΔT = iK b m ΔT = 2 x 0.51 °C kg/mol x 2.477 mol/kg ΔT = 2.53 °C

Find the New Boiling Point

From the boiling point elevation formula, you know the new boiling point is 2.53 degrees higher than the boiling point of the pure solvent. The boiling point of water is 100 °C.

Solution boiling point = 100 °C + 2.53 °C Solution boiling point = 102.53 °C

Note that adding salt to water does not change its boiling point a whole lot. If you want to raise the boiling point of water so food cooks faster, it takes so much salt that it makes the recipe inedible!

• Atkins, P. W. (1994). Physical Chemistry (4th ed.). Oxford: Oxford University Press. ISBN 0-19-269042-6.
• Laidler, K.J.; Meiser, J.L. (1982).  Physical Chemistry . Benjamin/Cummings. ISBN 978-0618123414.
• McQuarrie, Donald; et al. (2011). “Colligative Properties of Solutions”. General Chemistry . University Science Books. ISBN 978-1-89138-960-3.
• Tro, Nivaldo J. (2018).  Chemistry: Structure and Properties  (2nd ed.). Pearson Education. ISBN 978-0-134-52822-9.

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Boiling Point Elevation Definition

What Boiling Point Elevation Means in Chemistry

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Boiling point elevation, freezing point depression, vapor pressure lowering, and osmotic pressure are examples of colligative properties . These are properties of matter that are affected by the number of particles in a sample.

Boiling point elevation is the phenomenon that occurs when the boiling point of a liquid (a solvent ) is increased when another compound is added, such that the solution has a higher boiling point than the pure solvent . Boiling point elevation occurs whenever a non-volatile solute is added to a pure solvent .

While boiling point elevation depends on the number of dissolved particles in a solution, their identity is not a factor. Solvent-solute interactions also do not affect boiling point elevation.

An instrument called an ebullioscope is used to accurately measure boiling point and thus detect whether boiling point elevation has occurred and how much the boiling point has changed.

Boiling Point Elevation Examples

The boiling point of salted water is higher than the boiling point of pure water. Salt is an electrolyte that dissociates into ions in solution, so it has a relatively large affect on boiling point. Note nonelectrolytes, such as sugar, also increase boiling point. However, because a nonelectrolyte does not dissociate to form multiple particles, it has less of an effect, per mass, than a soluble electrolyte.

Boiling Point Elevation Equation

The formula used to calculate boiling point elevation is a combination of the Clausius-Clapeyron equation and Raoult's law. It is assumed the solute is non-volatile.

ΔT b  =  K b  ·  b B

• ΔT b is the boiling point elevation
• K b is the ebullioscopic constant, which depends on the solvent
• b B  is the molality of the solution (typically found in a table)

Thus, boiling point elevation is directly proportional to the molal concentration of a chemical solution.

• Colligative Properties of Solutions
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Chapter 12: Solutions and Colloids

Back to chapter, freezing point depression and boiling point elevation, previous video 12.9: ideal solutions, next video 12.11: osmosis and osmotic pressure of solutions.

The temperature at which the vapor pressure of a liquid equals the atmospheric pressure is known as its boiling point. 

Since adding a non-volatile solute lowers the vapor pressure of a solvent, a solution requires a higher temperature to increase its vapor pressure to a point that equals the atmospheric pressure. Thus, the boiling point of a solution is greater than that of a pure solvent.

These changes in vaporization can be examined over a range of temperatures and pressure using a phase diagram.

A solution has a lower vapor pressure than the pure solvent at all temperatures. So, the vaporization curve of the solution would lie below that of the solvent. 

At 1 atm, the curve corresponds to a temperature higher than the boiling point of the pure solvent. 

The increase in the boiling point of the solution compared to that of the pure solvent is known as boiling point elevation.

The boiling point of a solution is a colligative property. The temperature increase, or Δ T b , is directly proportional to the concentration of solute and can be calculated by multiplying the molality of the solute and the molal boiling point elevation constant.

The boiling point elevation constant has the units °C per molality, and is different for each solvent. For water, the constant is 0.512 °C per molal. 

So, a 2.00 molal aqueous solution will elevate the boiling point of water by 1.02 °C to 101.02 °C.

The addition of a non-volatile solute also lowers the freezing point of the solution compared to that of a pure solvent.

At the triple point, the vapor pressures of the solid, liquid, and gaseous states are equal. 

Because a non-volatile solute lowers the vapor pressure of the solution, the entire freezing curve, which extends upward from the triple point, shifts such that the solution freezes at a lower temperature.

This decrease in the freezing temperature of a solution compared to that of a pure solvent is known as freezing point depression.

Like the boiling point, the freezing point of a solution is also a colligative property. 

The temperature decrease or Δ T f is directly proportional to the concentration of solute and can be calculated by multiplying the molality of the solute and the molal freezing point depression constant.

The freezing point depression constant also depends on the solvent and has the units °C/ m .

For water, the freezing point depression constant is 1.86 °C per molal.

Thus, a 0.5 molal glycol solution will lower the freezing point of water by 0.93 °C to −0.93 °C.

Boiling Point Elevation

The boiling point of a liquid is the temperature at which its vapor pressure is equal to ambient atmospheric pressure. Since the vapor pressure of a solution is lowered due to the presence of nonvolatile solutes, it stands to reason that the solution’s boiling point will subsequently be increased. Vapor pressure increases with temperature, and so a solution will require a higher temperature than will pure solvent to achieve any given vapor pressure, including one equivalent to that of the surrounding atmosphere. The increase in boiling point observed when a non-volatile solute is dissolved in a solvent, Δ T b , is called boiling point elevation and is directly proportional to the molal concentration of solute species:

where K b is the boiling point elevation constant, or the ebullioscopic constant and m is the molal concentration (molality) of all solute species. Boiling point elevation constants are characteristic properties that depend on the identity of the solvent.

Freezing Point Depression

Solutions freeze at lower temperatures than pure liquids. This phenomenon is exploited in “de-icing” schemes that use salt, calcium chloride, or urea to melt ice on roads and sidewalks, and in the use of ethylene glycol as an “antifreeze” in automobile radiators. Seawater freezes at a lower temperature than freshwater, and so the Arctic and Antarctic oceans remain unfrozen even at temperatures below 0 °C (as do the body fluids of fish and other cold-blooded sea animals that live in these oceans).

The decrease in freezing point of a dilute solution compared to that of the pure solvent, Δ T f , is called the freezing point depression and is directly proportional to the molal concentration of the solute

where m is the molal concentration of the solute and K f is called the freezing point depression constant (or cryoscopic constant). Just as for boiling point elevation constants, these are characteristic properties whose values depend on the chemical identity of the solvent.

Determination of Molar Masses

Osmotic pressure and changes in freezing point, boiling point, and vapor pressure are directly proportional to the number of solute species present in a given amount of solution. Consequently, measuring one of these properties for a solution prepared using a known mass of solute permits determination of the solute’s molar mass.

For example, a solution of 4.00 g of a nonelectrolyte dissolved in 55.0 g of benzene is found to freeze at 2.32 °C. Assuming ideal solution behavior, what is the molar mass of this compound?

To solve this problem, first, the change in freezing point from the observed freezing point and the freezing point of pure benzene is calculated:

Then, the molal concentration is determined from K f , the freezing point depression constant for benzene, and Δ T f :

Next, the number of moles of the compound in the solution is found from the molal concentration and the mass of solvent that was used to make the solution.

And, finally, the molar mass from the mass of the solute and the number of moles in that mass is determined.

This text is adapted from Openstax, Chemistry 2e, Section 11.4: Colligative Properties.

Suggested Reading

• Steffel, Margaret J. "Raoult's law: A general chemistry experiment." Journal of Chemical Education 60, no. 6 (1983): 500.
• Berka, Ladislav H., and Nicholas Kildahl. "Experiments for Modern Introductory Chemistry: Intermolecular Forces and Raoult's Law." Journal of chemical education 71, no. 7 (1994): 613.

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Enhancement of apple stress resistance via proline elevation by sugar substitutes.

1. Introduction

2.1. low concentration of sugar substitutes promote proline accumulation, 2.2. low concentration of sugar substitutes improves salt resistance, 2.3. low concentration of sugar substitutes enhances cold tolerance in plants, 2.4. low concentration of sugar substitutes enhances drought tolerance in plants, 2.5. low concentration of sugar substitutes enhances plant disease resistance, 2.6. the effect of sugar substitutes on the quality of apple fruits, 3. discussions, 4. materials and methods, 4.1. plant materials and growth conditions, 4.2. fresh weight, 4.3. proline content, 4.4. malondialdehyde content, 4.5. hydrogen peroxide content, 4.6. superoxide anion radical content, 4.7. extraction of plant genomic rna, 4.8. photosynthetic rate and chlorophyll fluorescence, 4.9. relative leaf water content, 4.10. sugar content, 4.11. data analysis, 5. conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Share and Cite

Feng, Z.-Q.; Li, T.; Li, X.-Y.; Luo, L.-X.; Li, Z.; Liu, C.-L.; Ge, S.-F.; Zhu, Z.-L.; Li, Y.-Y.; Jiang, H.; et al. Enhancement of Apple Stress Resistance via Proline Elevation by Sugar Substitutes. Int. J. Mol. Sci. 2024 , 25 , 9548. https://doi.org/10.3390/ijms25179548

Feng Z-Q, Li T, Li X-Y, Luo L-X, Li Z, Liu C-L, Ge S-F, Zhu Z-L, Li Y-Y, Jiang H, et al. Enhancement of Apple Stress Resistance via Proline Elevation by Sugar Substitutes. International Journal of Molecular Sciences . 2024; 25(17):9548. https://doi.org/10.3390/ijms25179548

Feng, Zi-Quan, Tong Li, Xin-Yi Li, Long-Xin Luo, Zhi Li, Chun-Ling Liu, Shun-Feng Ge, Zhan-Ling Zhu, Yuan-Yuan Li, Han Jiang, and et al. 2024. "Enhancement of Apple Stress Resistance via Proline Elevation by Sugar Substitutes" International Journal of Molecular Sciences 25, no. 17: 9548. https://doi.org/10.3390/ijms25179548

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Boosting the kinetics of PET glycolysis †

First published on 5th September 2024

Glycolysis is the most promising chemical recycling method to depolymerize poly(ethylene terephthalate) (PET) with ethylene glycol (EG) into the monomer bis(2-hydroxyethyl) terephthalate (BHET). Boosting the depolymerization kinetics while staying under comparatively mild and green reaction conditions is required to bring glycolysis to industrial scale utilization. This work suggests achieving this goal by a combined pressure, temperature and co-solvent addition approach. By using the environmentally friendly γ-valerolactone (GVL) as a suitable co-solvent in the traditional PET glycolysis system, and slight temperature and pressure elevation, the kinetics was boosted by almost two orders of magnitude compared to the standard literature process. A kinetic model was employed to describe the kinetics as a function of temperature and GVL concentration. The optimized condition allowed nearly full conversion after 2 minutes only.

1. Introduction

Nearly full conversion is achievable in PET glycolysis above 170 °C, 20,21 but reaction kinetics is one of the bottlenecks to bring PET glycolysis towards a commercial scale. Reaction kinetics is influenced by the type and concentration of catalyst, PET particle size, concentration of reactants and temperature as well as using co-solvents that serve as kinetic activators. The homogeneous metal acetate catalyst zinc acetate (ZnAc 2 ) has proven to be a reliable depolymerization catalyst, providing good selectivity towards BHET. 21–24 The most common studies investigate PET glycolysis at 190 °C, since higher temperatures will cause significant EG evaporation. Nevertheless, there are some studies at temperatures up to 275 °C, which was achieved by pressurizing the reaction mixtures. 25,26 Another strategy to increase kinetics is the addition of co-solvents to the initial reaction mixture, such as aniline, nitrobenzene, 1-methyl-2-pyrrolidinone, and dimethyl sulfoxide (DMSO) or a 1,3-dimethylurea (1,3-DMU)/ZnAc 2 deep eutectic solvent system. 27,28 Recently, Le et al. 29 reported beneficial effects of the green solvent anisole on the kinetics.

Based on a reference kinetic dataset, which we determined for the ZnAc 2 -catalysed PET glycolysis at 190 °C and 1 bar, the objectives of this study are to: first, improve kinetics by using the biomass-derived green platform molecule γ-valerolactone (GVL) 30 as additional co-solvent in the traditional reaction mixture. Moreover, individual experiments were performed to understand the kinetic boost of GVL in detail. Second, increase kinetics by elevating the temperature without solvent loss, which we will achieve by increasing the pressure. Third, make use of the combined effect of GVL as co-solvent and a temperature increase to ultimately boost the reaction kinetics. The influence of these individual factors on the reaction kinetics was evaluated by kinetic constants, obtained by the pseudo-first order reversible reaction model, as utilized in other studies. 20,31,32 This combined temperature and co-solvent optimization approach will achieve a kinetic boost of PET glycolysis of about two orders of magnitude over the conventional process, thus contributing to a greener chemical recycling strategy.

2. Experimental section

2.1 materials.

The PET used in this study was sourced from colorless single-use post-consumer bottles. Caps and labels were taken off and surface impurities were removed using small amounts of acetone. The remaining material was manually cut into 5 × 5 × 0.2 mm pieces. Following this, the PET particles were shred into small particles using a grinder. These crushed PET particles underwent fractionation in a sieving tower. Unless otherwise stated, the experiments were carried out with a particle size fraction of 0.2 ≤ d p < 1 mm.

2.2 Sample preparation for PET glycolysis kinetic investigations

2.3 set-up and procedure for pet glycolysis kinetic investigations.

2.4 Analytical quantification of glycolysis products

3. kinetic model.

4. Results and discussion

Table S2 in the ESI † summarises the experimental and modeling results of all kinetic experiments. The experimental results include the approximate reaction time until reaching the reaction equilibrium t eq , the determined equilibrium conversion X eq PET , the equilibrium composition of the reaction mixture K x , the BHET process yield at the reaction equilibrium Y process,eq BHET and the monomer mole fraction x product Monomer in the BHET product. Regarding the modeling, Table S2 † contains the initial composition of the reaction mixture as well as the retrieved values for the kinetic constants k . In addition to the kinetic investigations in Table S2, † individual experiments were conducted to gain a detailed understanding of the kinetic enhancement provided by GVL.

4.1 GVL influence on reaction kinetics

4.2 Temperature influence on reaction kinetics

As expected, the pressure-assisted temperature increase accelerated the reaction, whereby the elevated reaction temperatures were reached after the dead time of 3 minutes, as can be seen in Fig. S2 in the ESI. † The temperature increase had also a slight effect on the reaction equilibrium of the endothermic reaction because the mean equilibrium conversion increased from 93 over 93.5 to 96%. Additionally, Fig. 3 (a) shows the results of the kinetic modeling using eqn (1) , (3) and (4) , wherein the kinetic constant k was retrieved from the experimental data using K x from experimental data obtained at the reaction equilibrium (see Table S2 in the ESI † ). The modeled and experimental data exhibit good agreement, reinforcing the characterization of the reaction as a pseudo-first order reversible reaction, as described in the previous section.

Fig. 3 (b) also provides an overview of all kinetic constants in relation to the reference kinetic series. A 25-fold increase with respect to the reference kinetic series for a temperature of 232 °C at a pressure of 3 bar underlines the substantial temperature effect on the reaction kinetics as known from the Arrhenius approach.

4.3 Combined temperature and GVL influence on reaction kinetics

Evidently, from Fig. 4 , it can be concluded that introducing a small quantity of GVL into the mixture, and simultaneously elevating the reaction conditions to 232 °C at 3 bar, whereby the reaction temperature was reached after the dead time of 3 minutes, (see Fig. S2 in the ESI † ) allowed for a 70-fold increase in reaction kinetics over the reference conditions. Just after 15 seconds of reaction time, the first sample of kinetic series 7 reached a near-equilibrium state. Because experimental data was not available between the reaction times of 0 and 15 seconds, fitting the kinetic constant k using K x from experimental data obtained at the reaction equilibrium (see Table S2 in the ESI † ) might not be that accurate. Nonetheless, the primary objective of the model in this study is to quantify the acceleration of the reaction kinetics through the kinetic constant. However, all obtained experimental data points align closely with the respective modeled kinetic curve in Fig. 4 (a) . The significant amplification of almost two orders of magnitude relative to the reference kinetic series shown in Fig. 4 (b) underlines the substantial impact of temperature increase on the GVL-assisted PET glycolysis reaction.

4.4 Influence of increased reaction temperature and GVL on the reaction products and process yield

In order to evaluate the overall PET glycolysis process, the BHET process yield (see eqn (2) ) at the reaction equilibrium was determined for all kinetic experimental series (see Table 2 ) conducted in this work. Values of about 80% were determined for the reference series no. 1 (190 °C, 1 bar), as well as for series no. 5 and 6 due to identical liquid composition of EG and H 2 O in the downstream process, as anticipated. Comparable literature processes also yielded values ranging between 75 and 82%. 20,27,28 Apart from the beneficial effect of GVL on the kinetics, the overall process yield obtained from maximum conversion samples decreased from about 80% without GVL to 55% with the highest amount of GVL investigated in this study. This decline is attributed to the increasing fraction of GVL in the liquid phase of the downstream process and the enhanced solubility of BHET in GVL. 33

4.5 Analysis of the reasons behind the GVL effect on the kinetics

It can be observed from Fig. 5 that there were no significant differences in the results concerning X PET among the three procedures. Please note that all samples had the same composition of reactants and solvents as well as the same reaction time. This is a surprising effect contrary to the expectations and experience from the literature. 27 These experiments disproved the first hypothesis. Continuing with the remaining hypothesis, we know from other works (“Activity-Based Models to Predict Kinetics of Levulinic Acid Esterification” 37 ) that co-solvents manipulate the thermodynamic activity of the reactants and the catalysts. Hence, we postulate based on the results from Fig. 5 that GVL has a beneficial effect on the activity of ZnAc 2 , EG or PET. Following hypothesis three, we conducted experiments without the ZnAc 2 catalyst with and without GVL in the reaction system. To ensure a measurable conversion within a reasonable timeframe, samples were measured at 232 °C and 3 bar as described in sections 2.2 and 2.3. The conversion of the samples was compared after 7 minutes of reaction time and the results are depicted in Fig. 6 .

Under the same reaction conditions, a 20% conversion was achieved without GVL, whereas only a 13% conversion was attained for the samples with GVL. The results obtained without the catalyst suggest that the enhanced kinetics due to the presence of GVL in the reaction mixture is not attributed to the interaction of GVL with the reactants. Instead, they are more likely attributed to the interaction between GVL and the ZnAc 2 catalyst, possibly involving acid–base synergistic catalysis. 34 Detailed descriptions of reaction mechanisms involving systems containing ZnAc 2 /Lewis base catalysts in PET glycolysis have already been published in the literature. 28,34,38,39 Applied to our Lewis acid (ZnAc 2 ) catalysed reaction system, it is plausible that GVL functions as a Lewis base. This is because the oxygen atom in the lactone ring has a lone pair of electrons, which can be donated to form a bond with the electron-deficient species (Lewis acid). Consequently, GVL can coordinate with ZnAc 2 to promote bond cleavage and catalytic activity.

5. Conclusion and outlook

Conflicts of interest, acknowledgements.

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Development of low-cost ceramic membranes from industrial ceramic for enhanced wastewater treatment

• Original Paper
• Open access
• Published: 05 September 2024

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• M. A. Taha 1 ,
• H. M. Abdel-Ghafar   ORCID: orcid.org/0000-0002-8953-4513 2 ,
• Sh. K. Amin 3 ,
• M. E. A. Ali 4 ,
• E. A. Mohamed 1 &
• F. M. Mohamed 1  

The study examined the feasibility of utilizing the mixture of ceramic sludge and roller kiln wastes, to produce low-cost ceramic-based membranes designated for use in wastewater treatment applications. In recent years, the treatment of wastewater contaminated with humic acid has posed significant challenges due to its complex nature and resistance to conventional treatment methods. To improve the physical, mechanical, and filtration qualities of the membranes, the study involved preparing them using a blend of five distinct composition ratios of totally recycled ceramic sludge and roller kiln wastes, which were then sintered at temperatures ranging from 900 °C to 1300 °C. The most effective membrane showed the best permeate flux and humic acid separation efficiency for the wastewater samples when it was sintered at 1000 °C using only ceramic sludge waste. The produced membranes were thoroughly examined to reveal their structural and chemical characteristics. This confirmed the effective integration of functionalized multi-walled carbon nanotubes (f-MWCNTs) and their influence on the membranes’ functionality. f-MWCNTs were added to the membrane’s surface via wet impregnation and drop casting methods. This resulted in a notable improvement in the membrane’s humic acid separation efficiency, which increased to 92.61%, and the flux increased to 128.46 L/m 2 /h at a concentration of 100 mg L −1 as well. The opportunity to develop effective and environmentally sustainable ceramic membranes for water treatment using industrial ceramic wastes is highlighted by this study.

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Introduction

Humic acids (HA) are pivotal components in terrestrial and aquatic ecosystems, originating from the decomposition of organic matter (Wang et al. 2016 ). While they play a crucial role in maintaining environmental equilibrium by aiding in nutrient cycling and improving soil structure, their presence in water systems presents considerable challenges. These challenges encompass alterations in water taste, odor, and color, as well as the promotion of biofouling in distribution systems (Dehkordi et al. 2015 ). Conventional methods for addressing these issues, such as photocatalytic degradation (PCD), often exhibit limitations. These include slow reaction kinetics and the potential formation of harmful by-products (Szymański et al. 2016 ; Ahmad et al. 2016 ). Consequently, there is an urgent need for more effective and efficient solutions. Among the emerging technologies, ceramic membrane filtration has emerged as a promising approach, demonstrating the effective removal of humic acid contaminants. This method not only addresses environmental concerns but also enhances water quality, positioning it as a focal point for advancing water treatment technologies (Xia et al. 2013 ).

The disposal of ceramic industrial waste, particularly from tile manufacturing processes, presents a significant environmental challenge due to the complexities associated with its accumulation and management (Anggono 2005 ). Roller kilns, integral to ceramic tile production for firing the product, are a critical contributor to this issue. While essential, these kilns raise environmental concerns, particularly regarding the need for regular maintenance, specifically the grinding of roller surfaces. This maintenance becomes imperative as rollers become contaminated with tile glaze or alkali salts, compromising kiln efficiency and operation (Ahmed et al. 2014 ). Additionally, ceramic tile sludge, an inevitable byproduct of wastewater treatment in ceramic tile factories, adds to the disposal conundrum. Comprising approximately 2% of the total product weight, this sludge is traditionally considered waste and its disposal poses both logistical and financial challenges (Roushdy 2019 ; Ramadan et al. 2008 ). However, recent research has highlighted a paradigm shift, considering this sludge not as waste but as a resource (Hegazy et al. 2012 ). Studies demonstrate its potential in manufacturing energy-efficient sintered tiles and blending it with glass proves to be a viable approach to meeting industry standards for tile strength, durability, or another specific characteristic (Nandi et al. 2015 ).

Ceramic membranes are widely used in water filtration and treatment processes because of their high permeability and cost-effectiveness (Jedidi et al. 2009 ; Ali et al. 2018 ). These membranes offer many advantages compared to polymeric ones, including stability at high temperatures, resistance to high pressure, and chemical resilience, especially in extreme pH conditions (Gomaa et al. 2024 ). As water scarcity becomes a critical concern globally, ceramic membranes have established themselves as crucial components in water treatment plants (Jedidi et al. 2011 ; Hanjra and Qureshi 2010 ). Moreover, ceramic membranes have demonstrated efficacy in various food processing industries, such as juice clarification, corn syrup filtration, raw rice wine production, and effluent treatment from fish processing plants (Vladisavljević et al. 2003 ; Emani et al. 2013 ; Almandoz et al. 2010 ; Li et al. 2010 ; Pérez-Gálvez et al. 2011 ). Recently, there has been a growing trend in using ceramic membranes made from low-cost materials or industrial waste streams for water treatment. This trend significantly reduces costs while maintaining superior properties and performance (Samadi et al. 2022 ; Guo et al. 2018 ; Nandi et al. 2008 ; Larbot et al. 2004 ). Thus, ceramic membrane usage holds promise for treating water polluted with humic acid (Xia et al. 2013 ). Ceramic membranes can be prepared by various techniques, including extrusion, pressing, and slip casting, all of which involve three fundamental steps are involved in membrane production. Firstly, a suitable binder is defined to be mixed with the ceramic powder. Then, it is shaped either by forming a suspension for slip casting, by adding sufficient water to form a paste for extrusion, or by molding the powder and pressing it. Finally, the shaped membranes are fired at high temperatures in a sintering process. Multilayer ceramic membranes can also be produced by coating the membrane support with suitable layers (by sol–gel, CVD, etc.) (Elma et al. 2012 , 2015 ; Idakiev et al. 2005 ).

Wet impregnation, a technique used to enhance the adsorbent affinity and capacity of membrane surfaces, involves incorporating chemical species into the pores, followed by the introduction and drying of excess solvent ‏(Abdel-Ghafar and Hamouda 2024 ; Girish 2018 ; Gray et al. 2018 ). Although this process aims to enhance adsorption capabilities, it can decrease the pore size and diameter due to the deposition of materials within the pores, which is commonly utilized in creating mesoporous materials (Yang et al. 2024 ). Additionally, impregnation facilitates the formation of an oxide film on the surface, leading to a decrease in regeneration temperature and an extension of the adsorbent's lifespan (Zhou et al. 2019 ; Liu et al. 2019 ). Alternatively, drop casting, a method for producing thin solid films by depositing liquid droplets onto a substrate, is simple, scalable, and cost-effective (Kumar et al. 2022 ). However, it is most effective for small-area coatings due to scalability limitations (Eslamian and Soltani-Kordshuli 2018 ).

This work introduces an innovative use of high alumina and silica waste materials from grinding roller kilns and ceramic sludge to fabricate stable ceramic membranes for wastewater treatment. The obtained membranes were utilized for humic acid removal with a high concentration of 100 mg L −1 . The surface of the optimized membrane was modified using f-MWCNTs for enhancing the rejection rate.

The alumina and silica ceramic waste materials are collected from Rondy Ceramic company located at the industrial zone, kom Abu Rady city, Beni Suef Governorate, Egypt, in June 2022. The research activities carried out through this study at the laboratories of faculty of Earth Sciences, Beni-Suef University (Beni-Suef, Egypt), Central Metallurgical Research and Development Institute (CMRDI, Cairo, Egypt), and National Research Center (NRC, Cairo, Egypt) between 2022 and 2024.

Materials and methods

The primary precursors for the ceramic membrane preparation comprised ceramic sludge waste and the roller kiln’s hazardous fine waste. These materials were sourced locally from the Ceramic Rondy Company in the industrial zone of Kom Abu Rady city, Beni Suef Governorate, Upper Egypt. Additionally, polyvinyl alcohol (PVA, extra pure, molecular weight of 125,000), ethanol absolute (purity ≥ 99.9%, VWR, Germany), sulfuric acid (H 2 SO 4 , 98%, Adwic), and nitric acid (HNO 3 , 69–72%, Sigma-Aldrich) were procured and used as received. Furthermore, humic acid sodium salt with a technical grade of 50–60% (as humic acid) was obtained from Alfa Aesar Company in Germany. The pristine multi-walled carbon nanotube (p-MWCNTs) used in this study was procured from the Egyptian Petroleum Research Institute (EPRI) in Cairo, Egypt. All chemicals were of analytical grade and utilized as received without the need for further purification. De-ionized water was employed in all experimental procedures.

Characterization

The grind roller kiln and milled ceramic sludge wastes underwent several analyses. The chemical composition was determined using X-ray fluorescence (XRF) with the Malvern Panalytical Axios FAST simultaneous WDXRF Spectrometer, Netherlands. The mineralogical composition was determined using X-ray diffraction (XRD) with the Bruker D8 Discover diffractometer (Germany), operated at 40 kV and 40 mA, with a wavelength of 1.54A°. Thermal analyses (TGA–DTG) were performed using the THEMYS One + —Setaram Thermal Analyzer (France), with a temperature range of 35–1000 °C and a heating rate of 10 °C/min, under N 2 atmosphere. The particle size distribution (PSD) was investigated using the BT–2001(Liquid) Laser Particle Size Analyzer, conforming to ISO 13320 (ISO 2009 ). The true density of the powder was measured using the standard pycnometer test method (Density flask) according to ASTM B 311 (ASTM 2013 ), which is a very precise procedure for determining the density of powders, granules, and dispersions with poor flowability characteristics. Meanwhile, the bulk density was measured according to (ASTM 2009 ) which standardizes the measurement of bulk density (unit weight) and voids in aggregates. The bonding parameters and functional groups of the ceramic membranes were characterized using FT-IR spectroscopy. This analysis was carried out using a Bruker VERTEX 70v spectrometer within the wavenumber range of 400–4000 cm −1 , with thin film samples measuring 2 cm in length and 1 cm in width. Pore size analysis of membranes was determined using a high-pressure mercury porosimeter, specifically the Micromeritics 9320, USA. Surface morphologies of the membranes were observed using a field emission scanning electron microscope (Quanta FEG250), Netherlands, attached to an EDX Unit (Energy Dispersive X-ray Analyses).

Preparation of the ceramic membranes

The ceramic sludge waste particles were milled and sieved to a standard aperture size of 80 µm to ensure uniformity. Following this, they were dried in an oven at 110 °C for 2 h. The roller kiln waste was utilized in its original form. Cylindrical disk samples, with a diameter of 50 mm and a thickness of approximately 10 mm, were formed using a pressing method. Mixtures of ceramic sludge waste and roller kiln waste powders, with varying weight ratios, were pressed with 15% PVA solution (by weight) in stainless steel molds using a laboratory hydraulic press under a uniaxial load of 25 MPa as outlined in Table  1 . The membrane specimens were dried in two steps using a laboratory dryer: first at 80 °C for 8 h, then at 110 °C for another 6 h. The membrane specimens were then fired in a laboratory muffle furnace at five different temperatures (900, 1000, 1100, 1200, and 1300 °C), each for a soaking time of 1 h (Table  1 ).

The heating rate was maintained at a constant 5 °C/min. The firing technique employed in this work was single-slow firing, involving a gradual increase in temperature from room temperature to the required firing temperatures, followed by cooling to room temperature. Additionally, twenty cubic specimens, each measuring 5 × 5 × 5 cm, were prepared under identical manufacturing conditions to assess the mechanical properties of the ceramic membranes. The dimensions of the formed membranes were determined using a digital Vernier caliper, while their masses were measured using a digital analytical balance with a reading accuracy of up to 0.00001 g (AS X7, RADWAG). The obtained membranes are presented in Fig. S1 . The physical and mechanical properties of the prepared membranes were determined according to standard test methods (ASTM 2014 , 2003 , 2011 , 2006 , 2016 ), as ascribed in the supplementary (SI).

Membrane testing and performance assessment

The lab-scale ceramic membrane filtration test unit used in this study, designed by CERAFILTEC, Germany, is a portable unit suitable for short-term filtration applications (Fig.  1 a). It is equipped with a ceramic membrane testing cell featuring a 50 mm diameter, enabling the testing of small sample volumes. The process entails immersing a single test plate into a 10 L feeding water tank containing contaminated water, typically contaminated with humic acid. Subsequently, a pump is employed to draw the polluted water through the ceramic membrane module for filtration, with the filtrated permeate water collected in another 5 L product tank (Fig.  1 b). Backwashing is carried out using pure water and air between operation cycles to recover membrane performance and improve efficiency.

CERAFILTEC lab-scale ceramic membrane filtration test unit showing a photograph and b schematic drawing of the process

The unit can replicate genuine filtration processes such as filtration, backwash on-air, backwash submerged, and air-scouring during filtration or backwash. It is capable of continuous and automatic operation, with adjustable settings, facilitated by a control system developed using Siemens LOGO with TDE software, ensuring precise and effective operation. The control unit records changes in transmembrane pressure (TMP) over time, and the volumetric flow rate can be recorded and adjusted using the control panel by altering the pump frequency. The operating conditions and filtration specifications for this unit are outlined in Table S2.

All membranes underwent testing to evaluate the influence of different composition ratios during ceramic membrane preparation and varying firing temperatures on membrane performance. The assessment involved measuring permeate flux through a pure water permeability test, followed by evaluating flux and humic acid separation efficiency at a consistent concentration of 50 mg L −1 . The experimental setup operated under a maximum feeding filtration pressure of − 0.6 bar.

The water flux (J w ) in this system can be calculated using the following equation (Zhang et al. 2020 )‏:

where V w is the volume of the filtrated water permeate (m 3 ), A is the effective area of the membrane (m 2 ), and t is the permeation time (h).

Additionally, humic acid separation (HR) was conducted in triplicates for each membrane, and the average result was calculated using the following equation (Zhang et al. 2020 )‏:

where C f and C p are the concentrations (mg/L) of feed bulk and permeate solutions, respectively. The concentration of humic acid in both the raw water and the permeate was measured by UV absorbance at 254 nm using a Hach DR6000 UV–VIS Spectrophotometer.

Modification of selected ceramic membrane samples

After evaluating the physical and mechanical properties of twenty fired ceramic membrane samples, it was determined that only one membrane, M1-1000 °C, produced from 100% ceramic sludge waste and sintered at 1000 °C, exhibited the highest efficiency in separating humic acid and permeate flux. To enhance its performance, the M1-1000 °C membrane underwent modifications utilizing functionalized multi-walled carbon nanotubes (f-MWCNTs). The obtained p-MWCNTs were functionalized as previously ascribed (Rashed et al. 2020 ; Wang et al. 2015 ), and as illustrated in the SI. Prior to the modification process, the membrane underwent a cleaning procedure involving immersion in ethanol using a water bath sonicator for 15 min. Subsequently, powdered f-MWCNTs were weighed and suspended in 50 mL of ethanol to produce a 0.1 wt. % solution through sonication for 30 min (Ajmani et al. 2012 ). The f-MWCNTs were then applied to the membrane surface through wet impregnation and drop-casting methods. In the wet Impregnation process, the M1-1000 °C membrane was immersed in an aqueous solution of f-MWCNTs in an ultrasonic bath for 30 min to ensure uniform distribution of f-MWCNTs. It was then dried at 50 °C for 2 h to remove excess liquid (Soroush et al. 2015 ). For drop casting, the prepared f-MWCNT solution was carefully deposited onto the membrane surface using a micropipette. The membrane was then dried at 50 °C for 24 h and subsequently exposed to open air for 2 days to remove excess solvent and facilitate adhesion of f-MWCNTs (Gao et al. 2014 ). Approximately 9.6 mg of f-MWCNTs were quantified to be deposited on the membrane surface using this method.

Following these modifications, the modified membrane (M1-1000 °C) was ready for use. The modified membranes underwent testing using the lab-scale ceramic membrane filtration test unit from CERAFILTEC (Fig.  2 ). The effect of synthetic humic acid solution concentrations ranged from 10 to 100 mg L −1 on membrane performance was assessed by determining the permeate flux and humic acid separation efficiency using specific Eqs.  1 and 2 . Further characterization such as chemical stability and corrosion testing (Rawat and Bulasara 2018 ) was performed as ascribed in SI.

Depicts the XRD patterns of a roller kiln and b ceramic sludge wastes

Results and discussion

Characterization of raw materials, xrf analysis.

The chemical analysis of two ceramic waste samples is detailed in Table  2 . The roller kiln waste sample is primarily composed of alumina, with silica as a secondary component. This composition is attributed to the utilization of high alumina rollers in the kiln, resulting in almost negligible loss of ignition (Amin et al. 2016 ). In contrast, the ceramic sludge waste sample primarily consists of silica, with alumina as the next most abundant component. Its chemical composition is similar to that of brick clay, but with a higher alumina content due to its silica composition (Ramadan et al. 2008 ). The observed loss on ignition value, indicating the presence of limestone and organic matter, is within a reasonable range (Roushdy 2019 ).

XRD-analysis

The X-ray diffraction (XRD) analysis reveals that the roller kiln waste predominantly consists of alumina, with mullite (PDF00-015-0776) and corundum (PDF01-073-5928) as the primary minerals. Additionally, minor quantities of silica, represented by silicon (PDF00-027-1402) and cristobalite (PDF00-071-0087), were identified, as depicted in Fig.  2 a. In contrast, the ceramic sludge waste is primarily composed of silica, with quartz (PDF 00-005-0490) as the dominant phase. Furthermore, the presence of kaolinite (PDF 00-014-0164), albite (PDF 00-009-0466), and calcite (PDF 00-005-0586) phases was observed, as illustrated in Fig.  2 b. As anticipated, the ceramic sludge encompasses a mixture of all the components present in the raw mixtures utilized for the production of wall and floor tiles.

TG/DTG-analysis

The thermal analysis (TGA and DTG) obtained by heating the powder at 10 °C/min in N 2 for the roller kiln waste is presented in Fig.  3 a. An endothermic peak is observed in the 40–135 °C range, indicating minor atmospheric moisture loss. No other significant endothermic peaks or weight loss are observed for the alumina powder waste. The apparent weight increase on the TGA trace is likely due to a sloping baseline and can be disregarded. The negligible change in weight of the specimen up to 1000 °C is expected given the inert nature of its constituents (mullite + cristobalite) (Ahmed et al. 2014 ).

Thermal analysis (TG and DTG curves) of a roller kiln and b ceramic tile sludge wastes

The combined TGA—DTG chart for ceramic sludge waste is depicted in Fig.  3 b, revealing three zones of anomalies. The first zone exhibits an endothermic peak between 70 °C and 150 °C, corresponding to the loss of water contained in the waste sample. The second zone, with an endothermic peak between 350 °C and 610 °C, is attributed to the lattice water of clay due to the dehydroxylation of kaolinite to form metakaolinite, which has a poorly organized structure (Wahyuni et al. 2018 ). The third zone, with an endothermic peak between 615 °C and 710 °C, arises from the decomposition of the calcite mineral (Buregyeya et al. 2018 ).

Particle size distribution (PSD)

Figure S3 displays the cumulative and differential curves for particle size analysis of roller kiln and ceramic sludge wastes. The vertical Y-axis represents the fraction passing through each screen aperture, while the horizontal X-axis shows the particle size range in micrometers (μm). Figure S3a indicates that the ground alumina in roller kiln waste is very fine, with particle diameters ranging from 0.598 µm to 87.05 µm and a median particle size (D50) of 8.282 µm. Similarly, Fig. S3b reveals that the milled silica in ceramic tile sludge waste is also fine, with particle diameters spanning from 0.610 µm to 77.00 µm and a D50 of 7.627 µm.

Powder density

The density of the roller kiln and ceramic sludge waste was determined using the density bottle method. The procedure was repeated five times to ensure accuracy, resulting in mean true densities of 3.157 g/cm 3 for roller kiln waste and 2.554 g/cm 3 for ceramic sludge waste, respectively. Additionally, the bulk densities were measured at 1.188 g/cm 3 for roller kiln waste and 0.607 g/cm 3 for sludge waste.

Characterization of ceramic membranes

Studying the physical and mechanical properties, total shrinkage.

As the firing temperature increases, both linear and volumetric shrinkage of ceramic membranes increases due to enhanced sintering, promoting particle bonding and densification. Membranes with higher roller kiln waste content (M4–M5) exhibit less shrinkage compared to those with higher ceramic sludge waste (M1–M2), as depicted in Fig. S4a and b. This difference arises from the lower or zero weight loss observed in high alumina waste samples, indicating prior pre-firing in ceramic tile processes, which reduces weight loss and minimizes shrinkage in the current sintering process. Conversely, samples with higher silica waste content exhibit partially higher shrinkage due to chemical and physical reactions during firing, leading to structural changes at the chemical and physical levels. Ceramic tiles contain a significant amount of feldspar, serving as the source of liquid phase sintering and contributing to linear and volume firing shrinkage [8]. Ceramic sludge waste also contains feldspar (albite), leading to increased firing shrinkage, while the addition of high alumina refractory waste limits or suppresses liquid phase formation, resulting in reduced firing shrinkage.

Loss on ignition (LOI), water absorption (A), and saturation coefficient (SC)

Figure  4 a demonstrates that with increasing firing temperature, LOI tends to rise due to enhanced chemical reactions and moisture absorption rather than removal. However, the rate of increase may vary depending on the blend ratio. Higher ratios of roller kiln waste (M4–M5) may exhibit lower LOI due to minimal chemical reactions and the absence of decomposable material in the waste. Conversely, higher ratios of ceramic sludge waste (M1–M2) may lead to higher LOI values due to increased chemical reactions, such as limestone, kaolinite, and organic matter.

Effect of firing temperature on both: a Loss on ignition, b cold water absorption, c boiling water absorption, and d saturation coefficient, of all membranes, each with varying composition of roller kiln and ceramic sludge wastes

The analysis of membrane-water interaction and thermal stress resilience, as depicted in Fig.  4 b–d, reveals a correlation between water absorption behavior and firing shrinkage trends. Increased percentages of roller kiln waste correspond to decreased water absorption, while higher ceramic sludge waste percentages lead to increased absorption. This reflects the impact of ceramic sludge waste on firing shrinkage, where its addition reduces porosity, thereby decreasing water absorption rates. Conversely, the integration of roller kiln waste reduces firing shrinkage, possibly by inhibiting liquid phase formation during firing, thus increasing porosity and water absorption values.

These dynamics are crucial for evaluating how the membrane interacts with water and withstands thermal stress. Membranes with higher alumina waste ratios (M5), when exposed to various firing temperatures, particularly at 1000–1300 °C, display notably high rates of cold and boiling water absorption: 28.45% and 24.82% for cold water, and 29.03% and 25.43% for boiling water, respectively. This suggests an increase in porosity and, to some extent, a reduction in densification, although the reduction is slight as temperature rises. Consequently, there is a higher saturation coefficient, indicating decreased resistance to freeze–thaw cycles. In contrast, membranes with higher silica waste concentration (M1) at 1200 °C exhibit the lowest water absorption rates of 0.11% for cold water and 0.3% for boiling water, indicating decreased porosity and enhanced glassification. Consequently, they display lower saturation coefficients, indicative of stronger resistance to freeze–thaw damage. At 900 °C, an increase in water saturation of 17.96% for cold water and 18.76% for boiling water, alongside rising porosity, affects structural integrity and water interaction, resulting in higher absorption rates.

Bulk density and porosity

In Fig.  5 a, the bulk density measurements indicate that increasing the proportion of roller kiln waste results in lower bulk densities (1.73–1.77 g/cm 3 ) in the ceramic membranes (M5) at temperatures ranging from 1000 °C to 1300 °C. This decrease in density is attributed to the alumina-rich nature of roller kiln waste, known for its inert properties, which contributes to less dense structures compared to those containing ceramic sludge waste. Additionally, the trend of increasing bulk density to 1.96 and 2.09 g/cm 3 at higher sintering temperatures of 1200 °C corresponds to the presence of higher sludge waste content (M1 and M2, respectively). This suggests enhanced particle bonding and densification at elevated temperatures during the ceramic membrane sintering process.

Effect of firing temperature on both: a bulk density, b apparent, c closed, and d total porosity of all membranes, each with varying compositions of roller kiln and ceramic sludge wastes

In Fig.  5 b–d, as firing temperatures rise to 1200 and 1300 °C, both the apparent and total porosity decrease. For membranes with higher silica (M1) and alumina (M5) content, the apparent porosity falls to 2.63%–42.02%, and the total porosity drops to 25.3%–45.97%, respectively. This reduction occurs because open pores convert into closed pores during sintering, which promotes denser structures.

Moreover, membranes made with a higher proportion of roller kiln waste (M5) show even lower closed porosity levels (1.22%–3.95%) at these temperatures, reflecting reduced densification. Conversely, those with a higher content of ceramic sludge waste (M1) exhibit greater closed porosity (22.67%) at 1200 °C, indicating higher densification and vitrification as proved in Fig.  5 c. These observations demonstrate that the type of waste used and the firing temperatures significantly impact the density and porosity of the membranes. Roller kiln waste, which is rich in alumina, tends to create less dense structures than silica-rich ceramic sludge waste. Furthermore, the increasing firing temperatures enhance particle bonding and densification, collectively contributing to the overall structural compactness of the membranes.

Compressive strength

The compressive strength of the prepared ceramic membranes was measured and evaluated as shown in Fig. S5.

Membrane performance test

Pure water permeability test.

In Fig.  6 , the pure water permeability as a function of membrane water flux (L/m 2  h) of the prepared ceramic membranes, characterized by varying compositions and sintering temperatures, demonstrates significant variability. At 900 °C, membranes M1 and M2, rich in silica waste, exhibit high flux due to pore expansion, with corresponding low pressures of around 26 mbar for M1 and slightly higher for M2, indicating minimal resistance to flow. However, as the sintering temperature increases to 1000 °C and 1100 °C, the flux for these membranes decreases, and pressure rises to approximately 50.333 mbar, reflecting increased filtration resistance due to membrane densification.

Impact of firing temperature on all membranes’ flux, each with varying composition of roller kiln and ceramic sludge wastes

Conversely, membranes M3, M4, and M5, with varied mixture ratios, show different flux behaviors across temperatures. M5, at 1000 °C, outperforms M3 and M4 with higher flux and lower pressure (8.67 mbar), suggesting better permeability. At 1100 °C and 1200 °C, M3 and M4 exhibit reduced flux and slightly increased pressure compared to M5, which maintains lower pressure, indicative of its higher permeability due to the presence of alumina waste. At the highest temperatures of 1200 °C and 1300 °C, all membranes undergo a sharp decrease in flux and an increase in pressure. This is attributed to vitrification and the transformation of open pores into closed pores, which restricts fluid flow by creating a glassy phase and reducing open pore volume, thereby decreasing membrane permeability.

Humic acid rejection

The effects of firing temperature and composition variability on humic acid filtration and permeate flux at a fixed concentration of 50 mg L −1 was performed. Figure  7 a and b illustrates the performance of ceramic membranes, M1 to M5, in humic acid separation, highlighting the intricate balance between flux, rejection ratio, and operational pressure across varying temperatures. For M1, at 900 °C, a flux of 508.74 L/m 2  h is observed with a humic acid rejection ratio of 13% at a pressure of 112 mbar. Increasing the temperature to 1200 °C, the flux sharply decreases to 22.97 L/m 2  h, while the rejection ratio spikes to 89%, albeit at a significantly higher pressure of 319 mbar. This suggests that elevated temperatures improve M1's rejection towards humic acid but constrict water flux, possibly due to the formation of a glassy phase that adversely impacts membrane porosity and water absorption, as evidenced in Figs. 5 , 6 , and 7 , where the lowest water absorption correlates with vitrification properties. Similarly, M2 at 900 °C shows a flux of 507.85 L/m 2  h with a 13% rejection ratio and a lower pressure of 65 mbar. However, at 1200 °C, the flux diminishes to 31.22 L/m 2  h, and the rejection ratio increases to 47%, with pressure rising to 210 mbar, indicating that the roller kiln component moderately enhances the membrane's filtration performance and thermal stability.

Influence of firing temperature on a humic acid flux and b separation efficiency in membranes with different compositions of roller kiln and ceramic sludge wastes, at a constant concentration of 50 mg L −1

Remarkably, at 1000 °C, M3 exhibits a higher flux of 540.63 L/m 2  h compared to M1 and M2, with a slightly lower rejection ratio of 11% and a reduced pressure of 61 mbar. This pattern of high flux with a gradual increase in rejection continues until 1300 °C, where a notable decrease to 17.86 L/m 2  h in flux and a surge in rejection to 71% are observed, signaling a significant change in membrane characteristics due to extreme temperatures, including densification and pore closure. M4 showcases superior permeability at 1000 °C with the highest flux among the membranes at 556.12 L/m 2  h, an 11% rejection ratio, and the lowest pressure of 56 mbar. Even at 1300 °C, M4 maintains a relatively high flux of 460.96 L/m 2  h with a 17% rejection ratio and a slightly elevated pressure of 96 mbar, underscoring the significant role of alumina waste in preserving membrane permeability at elevated temperatures.

M5, starting at 573.60 L/m 2  h with the lowest rejection of 6% at 1000 °C, demonstrates unparalleled flux capabilities, maintaining high flux up to 1300 °C at 549.56 L/m 2  h and improving rejection to 7%. The consistently low pressure, from 53 to 84 mbar, accentuates M5's exceptional ability to sustain high permeability and minimal humic acid rejection across a broad temperature spectrum. However, this membrane is too porous and brittle and is of no practical value.

Modified ceramic membranes

From previously concluded results, the optimal membrane performance based on humic acid separations and permeate flux was selected for surface modification toward enhancing the humic acid rejection with suitable flux. Based on the evaluation of the twenty membranes in Fig.  7 a and b, M1 and M2 at 1200 °C, and M3 at 1300 °C demonstrated comparable and high humic acid separation efficiencies (89%, 47%, and 71%, respectively). However, their low permeate flux rates (22.97, 31.22, and 17.86 L/m 2  h) prompted a focus on M1 at 1200 °C for its exceptional separation performance. Despite this, M1 at 1000 °C was ultimately chosen for further assessment due to its excellent balance of separation efficiency (19%) and high flux (486.07 L/m 2  h) compared to the other membranes. This membrane is slated for surface modification with f-MWCNTs to enhance its separation efficiency further, following careful consideration of performance testing, physical and mechanical properties, and optimal fabrication conditions of all ceramic membranes.

Performance evaluation of the modified ceramic membrane

The findings from the wastewater treatment test using the modified M1-1000 °C, as depicted in Fig.  8 a–d, indicate a strong correlation between treatment efficiency and feed concentration. As the humic acid (HA) concentration in the feed wastewater increases from 10 to 100 ppm, there’s a corresponding rise in the HA concentration in the permeate water, escalating from 1.08 to 7.59 ppm due to the higher concentration in the feed. Consequently, the rate of HA separation increases from 89.17 to 92.61%. However, this rise in separation efficiency is accompanied by a decrease in permeate flux, dropping from 332.49 to 128.46 L/m 2  h due to the concentration polarization phenomenon. Notably, there's a significant increase in transmembrane pressure from 180 to 210 mbar, indicating a greater shear force that reduces the membrane concentration polarization layer. This reduction positively impacts both membrane transport properties and separation effectiveness.

The impact of varying concentrations of humic acid solutions on a the separation efficiency and flux, b the separation efficiency and transmembrane pressure, c photographs of 100 ppm humic acid solution before and after treatment using the modified M1-1000 °C membrane, and d photograph of the modified ceramic membrane (M1) at 1000 °C using f-MWCNT

Characterization of the modified ceramic membrane

The XRD patterns of the raw high silica waste, fired membrane (M1) at different temperatures (i.e., 1000 and 1200 °C), and modified membrane (M1) at 1000 °C using f-MWCNTs indicated the presence of different mineralogical compositions as depicted in Fig.  9 a. The characteristic peaks observed at 2θ values of 12.36°, 24.69°, and 35.05° were attributed to the presence of the kaolinite mineral (Tironi et al. 2012 ). Additionally, the diffraction peaks detected at 20.84° and 26.66º were indicative of the existence of quartz mineral (Zuo et al. 2016 ).

a XRD-patterns and b FTIR-spectroscopy of raw high silica waste, fired membrane (M1) at different temperatures (i.e., 1000 and 1200 °C), and modified membrane (M1) at 1000 °C using f-MWCNT

Furthermore, the minerals albite and calcite were also observed through the identification of diffraction patterns located at 24.28° and 27.97° (Sánchez-Soto et al. 2021 ), in addition to 29.43°, 36.59°, and 39.47° (El-Mahllawy et al. 2018 ), respectively. The Sintering of the membrane (M1) sample at 1000 °C resulted in the deformation of calcite and kaolinite minerals, as provided by the disappearance of their related peaks, along with enhancing the intensities of the albite characteristic peaks.

Rising the firing temperature up to 1200 °C caused the appearance of a new mullite phase, as distinguished at 30.51°, 39.44°, 42.37°, and 47.28° (Gong et al. 2014 ). Adding f-MWCNTs to the fired membrane sample (M1) at 1000 °C resulted in the appearance of new diffraction peaks positioned at 26.82° and 45.97° (Cao et al. 2001 ), which confirmed the physical adhesion between the fired membrane sample and functionalized-MWCNTs.

Figure  9 b shows the FTIR spectrum of raw high silica waste and fired membrane (M1) samples at different temperatures (i.e., 1000 and 1200 °C), besides the modified membrane (M1) at 1000 °C using f-MWCNT. As for raw ceramic sludge waste, the observed band detected at 3665 cm −1 could be related to the hydroxyl stretching within kaolinite internal structure (Zuo et al. 2018 ). The 700–1200 cm −1 range exhibits Si–O and Al–O stretching modes, while the 150–600 cm −1 range is dominated by Si–O and Al–O bending modes of the kaolinite mineral (Plevova et al. 2020 ). The sintering of the membrane (M1) sample at 1000 °C results in a reduction of the intensity of the chemical water peak and a slight shift to lower values (from 3665 to 3643 cm −1 ). Furthermore, distinct changes in the positions of the Si–O and Al–O stretching and bending modes are observed, accompanied by the appearance of new peaks at 459 and 1728 cm −1 . These changes may be attributed to the deformation of kaolinite minerals and the initial crystallization of new phases. Elevating the firing temperature at 1200 °C leads to enhancing the intensity of the pre-existing absorption bands and the formation of new peaks detected at 2983, 1582 cm −1 . This could be linked to the nucleation/crystallization process of mullite mineral as proved by XRD-data, see Fig.  9 . Additionally, the incorporation of f-MWCNTs to the fired membrane (M1) at 1000 °C resulted in the detection of a new peak located at 1722 cm −1 of the C=O stretching vibration (Hassani et al. 2022 ).

The chemical stability of the modified membrane M1-1000 °C compared to the pristine ones was evaluated and presented as shown in Fig. S6.

The micrographs obtained from SEM-analysis at various magnifications, along with the EDX results of fired ceramic membranes at different temperatures (specifically, 1000 and 1200 °C), as well as fired membrane sample modified with f-MWCNTs at 1000 °C, are presented in Fig.  10 . The surfaces and cross-sectional images and EDX-data of the sintered membrane at 1000 °C (Fig.  10 a and b) depict a porous structure and a moderately sorted distribution of the fired grains, primarily composed of silica and alumina. This composition indicates effective water contaminant treatment efficiency, as evidenced in the measured porosity, along with high levels of porosity and water absorption observed in the analysis of the physical properties of the base membranes. The elevation of temperature to 1200 °C leads to the disruption of the porous structure of the fired membrane sample due to the partial melting of the aluminosilicate phases, resulting in the formation of a solid glassy phase (liquid phase) (Abdallah et al. 2018 ), as evidenced in the surfaces and cross-sectional micrographs (Fig.  10 c and d). Hence, the optimal firing temperature for preserving the porous structure is 1000 °C. To improve the separation efficiency of the synthesized membrane, f-MWCNTs were integrated to reduce the porous structure size to the nanoscale. The introduction of f-MWCNTs to the membrane sample fired at 1000 °C resulted in the emergence of well-distributed dendritic/forked shapes on the external surface of the ceramic membrane, as illustrated in the surface image in Fig.  10 e. This observation substantiates the homogeneous spreading of the f-MWCNTs on the membrane sample surface, which was further confirmed by the EDX-outcomes, indicating the presence of F-MWCNTs on its surface. Moreover, the cross-sectional image depicted in Fig.  10 f, and its EDX analysis demonstrate the presence of f-MWCNTs within the internal structure of the f-MWCNTs-modified membrane sample. Therefore, the presence of f-MWCNTs on the surface and within the internal structure of the fired membrane sample elucidates the enhanced separation efficiency of this sample as proved in Fig.  8 when compared to the fired membrane sample at 1000 °C.

SEM–EDX analyses of fired ceramic membranes at different temperatures a and b at 1000 °C, c and d , at 1200 °C, and e and f fired membrane at 1000 °C modified with f-MWCNTs

The pore size distribution of the modified M1-1000 °C, compared to M1-1000 °C, and M1-1200 °C showed an agreement with the obtained results from the surafce microstructure analysis by SEM, as shown in Fig. S7.

Affordable eco-effective ceramic nano-filtration and ultra-filtration membranes were developed for the treatment of humic acid-contaminated water, utilizing silica-rich ceramic sludge and alumina-rich roller kiln waste as raw materials. The membranes were fabricated using different compositions and firing temperatures (900 to 1300 °C). Exhaustive characterization of the ceramic powders was performed using various analytical techniques, including XRF, XRD, TGA-DTG, and particle size distribution.

Performance assessment revealed substantial impacts of composition ratio and firing temperature on separation efficiency and flux. Among the tested compositions, membranes fired at 1000 °C using solely ceramic sludge waste exhibited an optimal balance, achieving 19% separation efficiency and 486.07 L/m 2  h flux at 50 ppm humic acid solution concentration. These membranes demonstrated adequate mechanical strength to withstand water pressure. Additionally, the surface modification of the optimal membrane sample (M1-1000 °C) with f-MWCNTs significantly enhanced its separation efficiency to 92.61% and permeate flux to 128.46 L/m 2  h at 100 mg L −1 humic acid solution concentration and 210 mbar transmembrane pressure. SEM analysis confirmed numerous small nano-sized pores on the membrane's surface and internal structure, while XRD and FTIR analyses identified the presence of quartz, albite, carbon, Si–O, Al–O, and C=O functional groups in the modified membrane. Ultimately, this study illustrates the potential of utilizing ceramic waste materials for effective membrane technologies in water treatment, offering promising solutions for addressing humic acid pollution challenges.

Future research could expand upon exploring further applications of the developed ceramic membrane in treating industrial wastewater contaminated with pollutants other than humic acid. Additionally, there is potential to enhance the membrane’s properties and performance through conducting more experiments and practical applications, which would contribute to boosting its efficiency and effectiveness in industrial and environmental applications.

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Acknowledgements

The authors extend their appreciation to the Hydrogeology and Environment Department, Faculty of Earth Sciences, Beni-Suef University. The first author, Mohamed Adel Taha, thanks the Center of Excellence for Water (CoE-W) for supporting him. This work is supported by the received fund by the Egyptian Academy of Scientific Research and Technologies (ASRT) through the CNR-ASRT (Italy-Egypt) 2022-2023 international Exchanges (project ID: 18775).

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

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Faculty of Earth Sciences, Beni-Suef University, Beni Suef, Egypt

M. A. Taha, E. A. Mohamed & F. M. Mohamed

Central Metallurgical Research and Development Institute (CMRDI), P.O. Box 87, Helwan, Cairo, Egypt

H. M. Abdel-Ghafar

Chemical Engineering and Pilot Plant Department, Engineering and Renewable Energy Research Institute, National Research Centre (NRC), Dokki, Giza, Egypt

Sh. K. Amin

Egypt Desalination Research Center of Excellence (EDRC), Desert Research Center (DRC), Cairo, 11357, Egypt

M. E. A. Ali

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Mohamed Adel Taha, Hamdy Maamoun Abdel-Ghafar, and Shereen Kamel Amin contributed to the study conception and design, material preparation, experimental, data collection, analysis, visualization, and writing. The first draft of the manuscript was written by Mohamed Adel Taha, and all authors commented on previous versions of the manuscript. Mohamed E. A. Ali, Essam Abdelrahman Mohamed, and Fathy Mohamed Mohamed contributed to the conceptualization and reviewing the final version of the manuscript. All authors read and approved the final manuscript.

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Taha, M.A., Abdel-Ghafar, H.M., Amin, S.K. et al. Development of low-cost ceramic membranes from industrial ceramic for enhanced wastewater treatment. Int. J. Environ. Sci. Technol. (2024). https://doi.org/10.1007/s13762-024-05982-1

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Received : 04 May 2024

Revised : 05 July 2024

Accepted : 14 August 2024

Published : 05 September 2024

DOI : https://doi.org/10.1007/s13762-024-05982-1

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