Nice explanation. How to apply it in case of hydrogen adsorption using Freundlich Isotherm model??
@isaacvicentini5747
4 ай бұрын
This was such a good explanation. Thankyou so much for putting out such educational content
@hiramob
10 ай бұрын
Very clear explanation. Exactly what i needed! I see it was uploaded 2y ago but id love to see more uploads like this.
@Javsaful
10 ай бұрын
To determine the value of qe a volume is needed, this volume influences the final result of qm and I have seen that some authors use 1 liter and a better qm is obtained. Is this feasible? thanks for the reply
@nelumjayarathne7811
10 ай бұрын
Thank you Jay. This is very useful vedio and you explained it clearly
@Orian366
11 ай бұрын
Hello thank you for the nice video. I would like to ask if you happen to know how to fit data of multicomponent adsorption systems to modified extended langmuir model, SRS and extended freundich model in excel. I wonder is it possible to find the eg. interaction factor η of modified extended langmuir model with the excel solver you showed here?Thank you
@zxcvb2003
Жыл бұрын
hello! I am following this video, and the intercept value is negative, so the KL value is also negative. No matter how much I think about it, I don't know why, so I'm leaving a comment. Do you know anything about this issue? Thank you and have a good day!!
@tamarapozo4204
Жыл бұрын
Hello! first of all thank you very much for the video! and the second thing is to ask a question, I do not understand very well the difference between the qe used at the beginning to calculate the y-axis (Ce/qe) in the linear regression graph, and the qe calculated later from the data obtained from the first one. Thank you!
@drsaqibscienceacademy
10 ай бұрын
The qe value calculated earlier (using Ce/qe) is derived from your experimental data, while the qe value, which is theoretical, is determined based on the Langmuir model. Therefore, they differ in terms of being experimental and calculated values, respectively.
@iryna9324
Жыл бұрын
I am confused. Where you took these R2 values for linear Langmuir and Freundlich? They are different on the linear graph and the last spreadsheet yiu have created? Where you took numbers as R^2 = 0.785254325 for linear Langmuir and R^2 = 0.966167778 for Freundlich? Thanks!
@jaybullen2887
Жыл бұрын
Hi there - great question. The R^2 values in the comparison table at around 16:25 are worse than those in the linear graphs, yes. This is because when comparing linearised and non-linear fits, we should compare R^2 values calculated using y-axis data in the original format, with the original units! This means using data expressed as (mg g-1) and not expressed as (Ce/qe) or as ln(qe). if you download the spreadsheet, you can explore the formulae and maths used
@sufiasiddiqui
Жыл бұрын
I have a question. It's written that R2=1-(sum of squared differences between model and experiment/sum of square differences between model and average). However, in the excel sheet in the denominator the term is calculated for sum of square differences between experiment and average. Can you please clarify?
@jaybullen2887
Жыл бұрын
Hi there - great question. We want to compare the quality of our optimised model with optimised parameters k and qe with a very poor model. The poor model is a simple average of all y-values (i.e. no model at all!). So we calculate (a) sum of squared differences between experiment and model, and then calculate (b) sum of squared differences between experiment and average of all y-values. And we compare the two. Further explanation can be found elsewhere: www.ncl.ac.uk/webtemplate/ask-assets/external/maths-resources/statistics/regression-and-correlation/coefficient-of-determination-r-squared.html
@zaraakubra4118
Жыл бұрын
How to apply shrinking core models i.e ( 1-(1-x)^1/3=kt ,, 1- 2/3x -(1-x)^2/3 =kt and other equation is mixed controlled kinetic modeling) And arrhenius equation on iron extraction ( as i extract iron with varying different parameters like temp ,time) . i don't know how to apply these equations in Excel sheets to find that which model is best fit on iron dissolution.
@martljn6431
Жыл бұрын
Why can't you use the excel function to calculate R²? Isn't that an easier method to determine the R² if you got the calculated qe values?
@jaybullen2887
Жыл бұрын
Definitely! But in this spreadsheet, we show all the mathematical steps, one by one, to improve our understanding of what R^2 is and what it means and how we calculate it :-)
@baghalimathapa1302
Жыл бұрын
Thank you Jay Bullen
@nathanvinicius3381
Жыл бұрын
Hello, very nice work! Would you please make a tutorial teaching how to use the pseudo first order model? Thanks
@patino.gelver
Жыл бұрын
Thanks a lot Jay...great help for the community
@SIAHSI
Жыл бұрын
Thank you for the explanation. I have a question, what is the unit of KF, I can't deduce it, hope you can give me some hints. Waiting for good news.
@jaybullen2887
Жыл бұрын
Imagine that qe (mg g-1) = KF (UNITS) * Ce (ug L-1)^(1/n). We can rearrange to get KF (UNITS) = qe (mg g-1) / [Ce (ug L-1)]^(1/n). This is the same as KF (UNITS) = [qe (mg g-1)]*[Ce (ug L-1)]^(-1/n). If we look at the units only, we see that the units for KF will be equal to (mg g-1)*(ug L-1)^(-1/n). Or more generically, the units are (aqueous concentration units)*(adsorbed adsorbate units)*(-1/n). These units are very strange indeed!
@sandervanduinen6248
Жыл бұрын
Thank you for the amazing and clear explanation.
@paragineema4101
Жыл бұрын
Hi Jay, thank you very much for this detailed video regarding model fitting. It was a delight to read your research paper as well. Is it acceptable to see that the adsorption rate constants, k1 and k2 for pseudo first and second order models differ significantly? There is not much statistically significant difference in your results. However, my k1 values are in the range of 1.0-0.5 whereas the k2 values are in the range of 0.09-0.02. Is that acceptable? The R2 and qe values are quite close.
@jaybullen2887
Жыл бұрын
That is fine. k1 and k2 have different units, so the comparison of the absolute size of the numbers of k1 and k2 is not a useful comparison to make. For example... pseudo-first order: rate = k1 * (qe-qt) pseudo-second order: rate = k2 * (qe-qt)^2 PFO: rate units = mg g-1 min-1 PSO: rate units = mg g-1 min-1 (the same units for both rate equations) PFO: (qe-qt) units = mg g-1 PSO: (qe-qt)^2 units = mg^2 g-2 PFO: k1 units = min-1 PSO: k2 units = g mg-1 min-1 Different units = comparing the size of the numbers isn't necessarily useful. One example of this is to calculate the initial rates (use the rate equation, but set qt equal to 0). This gives you PFO: rate = k1*(qe-0) PSO: rate = k2*(qe-0)^2 experimentally observed 'rate' is the same for PFO and PSO experimentally observed 'qe' is the same for PFO and PSO However, PFO rate equation uses qe^1, whilst PSO rate equation uses qe^2. So if qe is greater than 1, then k2 has to be smaller than k1 in order for PFO and PSO models to both give the same initial rate. If qe is smaller than 1, then k2 has to be bigger than k1 for PFO and PSO models to both give the same initial rate. Your experiment gives k1 > k2, so my guess is that your qe is greater than 1 (whatever units you are using...). Your k1 values are approximately 10 times bigger than k2. So I guess than your qe is about 10 (with whatever units you are using)... Best wishes
@fajin8992
Жыл бұрын
Why you use Ln instead of Log?
@jaybullen2887
Жыл бұрын
You should get the same answer either way, whether you use natural logs or base 10.
@aminnaifar4442
2 жыл бұрын
thanks a lot Could you give us another example please
@dosentekim
2 жыл бұрын
thank you sir
@refalka4970
2 жыл бұрын
i think the first langmuir equation is also can be linearized and it can be fitted to the y = mx+c also. But the m value you got is different with the second equation...
@abdulhaseeb6573
2 жыл бұрын
great work. Some thing i was really looking for! thanks for sharing.
@savvinalazarou442
2 жыл бұрын
Thanks for making this video, really saved me! I'd like to ask why did you use the linearised equation for the non-linear fitting? I've seen a lot of works using qt=qe^2*k2*t/(1+k2*qe*t) as model equation so I don't know which one to choose...
@jaybullen2887
2 жыл бұрын
Hi there, the PSO equation you wrote is directly rearranged into the linearised equation used in this video. (To check this, [1.] inverse your equation to give 1/qt=(1+k2*qe*t)/qe^2*k2*t. [2.] Cancel terms to give 1/qt=(1/qe^2*k2*t)+(1/qe). Then [3.] multiple both sides by t to give t/qt=(1/qe^2*k2)+(t/qe). In my spreadsheet, I would have taken the linearised equation, as I am most familiar to working with this, then rearranged to essentially give the original equation (non-linear) that you write in your comment. Hope that helps
@wijisena9214
2 жыл бұрын
Great it helped a lot cheers😊
@mahamajmal5495
2 жыл бұрын
which data is required to applying langmuir adsorption isotherm?
@Aminulchem
2 жыл бұрын
Good job!
@Aminulchem
2 жыл бұрын
Thanks for making such a helpful video.
@SasaCecaSole
2 жыл бұрын
Thank you! Very well explained.
@rawan4297
2 жыл бұрын
I like how you explain, i never understood these models till i saw your video, thank you very sooo much
@asharayub
2 жыл бұрын
Excellent work, have read it and will use the same statistics in my study. Thanks a lot for sharing!
@wanniebuzz4177
2 жыл бұрын
Great day sir! If I have different concentrations (10 ppm, 15 ppm, 20 ppm, 25 ppm), do I need to do repeating experiments for each of these concentrations to find out their respective equilibrium concentration? Hope to hear from you soon.
@Aminulchem
2 жыл бұрын
Kinetic experiment is usually carried out at a fixed concentration (e.g., 10 ppm), adsorebt dose, pH and temperature as a variation of contact time to get the optimum equilibration time. So, if you wanna use different conecntrations then you need to carry out separate experiment for each concentration such as 10 ppm, 20 ppm etc.
@jaybullen2887
2 жыл бұрын
Yes, and you will see some interesting effects, like PSO rate constant k2 decreasing by a factor of x2 when the initial adsorbate concentration is increased x2. We discuss these effects in our paper published in Langmuir journal
@loyiso3335
2 жыл бұрын
Your a legend bro🔥🙌🏾. You have helped many of us a lot.
@priyankakhare4469
3 жыл бұрын
Sir Plesae make vedio tutorial for dubnin non linear isotherm..
@priyankakhare4469
3 жыл бұрын
Hello sir, this vedio lecture is very helpful for non linear fitting. Thanks a lot. Could you please help me in non linear fitting of Elovich model and intra particle diffusion model. Please send me final equation for non linear fitting.
@eduardotcb
3 жыл бұрын
Rifas machín chicharrín!
@md.nahidpervez8525
3 жыл бұрын
Can I get your email to discuss about my data
@lucaslima5731
3 жыл бұрын
Hi, could you perform data plot using pseudo-first order model? Preferably with the regression (linear), I would like to check how you find the values of qt, to perform the plotting of the graph with the experimental and theoretical data.
@alexdavidabaddelgado5936
2 жыл бұрын
pudiste sacar el valor de qt?
@lucaslima5731
3 жыл бұрын
Do you have any videos about the Freundlich-Langmuir (Sips) isotherm? I am in doubt about getting the Ks and ns parameters of the regression.
@vahidmousalou8870
3 жыл бұрын
you are a genus man (like), plz calculate a fit an 3 parameter and more isotherm like Sips and... plzzzz.
@karunratsakulnarmrat7993
3 жыл бұрын
I've tried solver for 4 unknowns to optimize value. Two times run with exactly data have got different values. Do you have any suggestion please?
@jaybullen2887
3 жыл бұрын
Hi there, what is the model you're trying to fit? Is it an adsorption isotherm with 4 fitting parameters? When we increase the number of fitting parameters, we increase the probability that the Solver algorithm fails to find the true best fit, and instead it finds a not-so-good fit. If you can, try to simplify the problem so that you can optimise just two unknowns first. After you know what those two unknowns are, you can use them in the model and calculate the other two unknowns.
@karunratsakulnarmrat7993
3 жыл бұрын
@@jaybullen2887 Thank very much for your suggestion. I used Peleg's model (MC = A(aw)^C + B(aw)^D; C<1, D>1) for sorption isotherm.
@jaybullen2887
3 жыл бұрын
@@karunratsakulnarmrat7993 I'm not familiar with the Peleg sorption isotherm model. Looking at a paper called "Comparison of the Sorption Properties of Fruit Powder Shampoos Using the BET, GAB, and Peleg Models" - They use a Monte Carlo algorithm to solve the non-linear regression and optimise all four constants. This should avoid the algorithm getting stuck in a local minimum rather than the true minimum. Unfortunately I don't know how to do this using Microsoft Excel's Solver without a lot of manual work (i.e. constrain two parameters, optimise the second two parameters, write down R^2, change the first two parameters, and repeat the optimisation, and generate a whole table of R^2 values then choose the best) - If you solve the problem, then please do share your progress. Good luck!
@karunratsakulnarmrat7993
3 жыл бұрын
@@jaybullen2887 Thanks for your information. I recalculate Peleg model same as your way. But this time I change the initial value (previously assigned as "1" for 4 unknows). After I run the solver the results look good. I will try Monte Carlo in order to compare the results. Highly appreciate your time and suggestion.
@jaybullen2887
3 жыл бұрын
@@karunratsakulnarmrat7993 Thanks for the update. Glad that you're making progress. You can also make a very nice graph where the x-axis is the value you fix unknown 1 or unknown 2 to be, and the y-axis is the R^2 value after you optimise unknown 3 and unknown 4. You change unknown 1 and 2 to many different values, and write down the R^2 results. Let us know how you get on with the Monte Carlo method and how you implement it.
@azanhk1
3 жыл бұрын
great tutorials... so many thesis compared the R-squared between models in their linearized forms..
@ry8361
3 жыл бұрын
This is for single adsorption system. How to fit Binary-Adsorption isotherm models??
@jaybullen2887
3 жыл бұрын
Hi there, when you say binary adsorption isotherm models, do you mean (a) two different adsorbates, (b) two different adsorbent materials, or (c) two different adsorption mechanisms, e.g. monolayer adsorption followed by multilayer adsorption-surface precipitation?
@ry8361
3 жыл бұрын
@@jaybullen2887 Thank you for your reply. I mean adsorption of two different adsorbates. How can I use non-linear method to fit the data to different multiple adsorption models such as extended Langmuir model, modified Langmuir model and so forth?
@jaybullen2887
3 жыл бұрын
@@ry8361 Perhaps you could provide the equation that you would like to model? I am not familiar with multi-adsorbate Langmuir adsorption isotherms and I imagine that there are many different approaches. Perhaps contact the author from a recent paper than interests you. Looking at the "Non-modified Langmuir multi-component isotherm" in the following paper: pubs.rsc.org/en/content/articlelanding/2019/ra/c9ra04865k the authors provide the following adsorption isotherm equation: qe,j = Qmax,j * (KL,j * Ce,j) / (1 + Σ,j (KL,j * Ce,j)) where parameter j refers to either adsorbate A, adsorbate B or adsorbate C etc... (It's very hard to write the equation in KZitem so please refer to the paper!) You could model an adsorption isotherm using this equation in Microsoft Excel, using the Solver function. You would add extra columns since for a binary system you don't just have one independent variable (Ce) and one dependent variable (qe), but you instead have two independent variables (Ce,A and Ce,B) and two dependent variables (qe,A and qe,B). Just like the single-adsorbate system, you would run the Solver and try to improve the R^2 value. The challenge is that you now have 4 fitting parameters instead of 2 (KL,A and KL,B and Qmax,A and Qmax,B). The Solver function is likely to fail to give the best fit, since the algorithm may get stuck at a local minima rather than the universal minimum when trying to minimise the error between the experimental data and the model. To solve this, you could first determine KL,A and Qmax,A by fitting an experimental adsorption isotherm where you only have adsorbate A, and there is zero adsorbate B. Then you can constrain (fix) the values of KL,A and Qmax,A in the binary model to the results from your single-adsorbate experiment, and you will only have to optimise the fitting parameters KL,B and Qmax,B. When you are dealing with complex systems with multiple adsorbates and multiple adsorbents, you may wish to consider using a Surface Complexation Model (SCM) instead. In an SCM, you calculate adsorption equilibrium constants for one adsorbate and one adsorbent at a time, then you combine your experimental parameters with a database of literature parameters to achieve a model that is sensitivity to many factors: not just adsorbate concentration but also pH, ionic strength and competitor ions. I have a short tutorial article about surface complexation modelling here: www.researchgate.net/publication/349947876_Surface_complexation_modelling_Building_tools_to_understand_and_predict_adsorption
@lucaslima5731
3 жыл бұрын
Salvou minha vida! obrigado :)
@jaybullen2887
3 жыл бұрын
De nada - estou feliz que foi util
@김도토리_0129
3 жыл бұрын
Thanks a lot :)
@fatinahza6531
3 жыл бұрын
Thank you for your videos. I came to this video after watching your video on adsorption isotherms. It helps A LOT. THANK YOU~
@waddema
3 жыл бұрын
wow, this will definetly pimp my masterthesis to another level. Thank you sooooo much for this tutorial and your excel sheets :*
@chandrabhan2715
3 жыл бұрын
Thank you sir, this is well explained concept.
@shikhabhogal7254
3 жыл бұрын
Thank you so much. It really helps to understand the fitting of data. Is there any mode to contact you like email?
@jaybullen2887
3 жыл бұрын
Hi Sikha, I have some contact options listed here: www.jaybullen.com/#contact
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