Hello, thank you for your explanation, it was helpful. Please , for my case I have an experimental data for 7 mesured in function of frequency, so as a result I have more peaks and I don't know how can I do your method ?
To calculate the percentage of beta sheet, turn, and random coil, you can use specialized software or perform a manual analysis. Popular software tools for this purpose include DICHROWEB, K2D3, and CDSSTR, which can assist in deconvoluting FTIR spectra and estimating secondary structure percentages. If you prefer a manual approach, you may want to use established methods like the Reed and Richards method or others based on curve-fitting algorithms. These methods typically involve assigning specific spectral regions to different secondary structures and fitting the experimental spectra accordingly. Thanks
Thank you Dr for another amazing tutorial. I have a question tho, while deconvoluting, I noticed the x values of the cumulative fit are limited to 1000 values only, while my original data has over 2000. So when I try to fit the C fit with my original spectrum, the C fit shape are shrink, thus inable to fit in graph. By any chance, do you know how to resolve this problem? I appreciate your time thank you!
Thank you for your kind words and for bringing up this issue. I understand the frustration you're experiencing with the limitation on the number of x values for the cumulative fit in Origin. It seems like your original data has more data points than the cumulative fit allows, resulting in the fit shape shrinking when you attempt to fit it with your spectrum. To address this problem, I'd be happy to take a closer look at your Origin file. Please feel free to send it to me at sayphysics@gmail.com. Once I receive it, I'll examine the data and see if there's a workaround or solution to ensure that the cumulative fit aligns properly with your original spectrum. Thank you for reaching out, and I appreciate your patience as we work to resolve this issue.
Oh I just figured out the solution, under NLfit: NLfit > Settings > Fitted Curves > Points: 1000 (change to the values you want). Leaving it here in case someone encounter the same problem.
@@SAYPhysics That is very kind of you Dr, I so appreciate how far you went to help others. Fortunately I figured out by playing around with the settings under NLFit and it fits well now! Thank you again for helping, take care Dr
Hello Sir, I am working on the deconvolution of peaks using origin. The problem I faced is during the converging, The width and area of each peaks do not allow the peaks to be properly coverged. How should I select each peak width and area specifically? My second question is how to use the area under the curve for quantification purposes? Thanks
When deconvolving peaks using OriginLab or any other software, selecting appropriate peak widths and areas is crucial for proper convergence. Here are some guidelines to consider: Peak Width Selection: Start with an initial estimate of the peak width based on your prior knowledge or assumptions about the system. Adjust the peak width incrementally to achieve the best fit to your experimental data. You can use peak fitting functions like Gaussian, Lorentzian, or Voigt to model the peak shapes. Each function has a width parameter that you can adjust. Peak Area Selection: The area under a peak represents the integrated intensity or quantity of the corresponding component in the sample. The area should be selected in such a way that it accurately reflects the true quantity of the component. The area calculation depends on the peak fitting function used. For example, for a Gaussian peak, the area is proportional to the amplitude (height) multiplied by the square root of 2π times the standard deviation. It is important to ensure that the peak area is not affected by nearby overlapping peaks. In such cases, appropriate baseline corrections or baseline modeling techniques can be employed to separate the peaks and accurately determine their individual areas. Regarding your second question, the area under the curve (AUC) can be used for quantification purposes in several ways: Concentration Determination: If you have a calibration curve relating the analyte concentration to the AUC, you can use the AUC of your sample to estimate its concentration. The calibration curve should be constructed using standards with known concentrations and their corresponding AUCs. Comparative Analysis: The AUC can be used for comparative analysis between samples. By comparing the AUCs of different samples, you can infer the relative quantities or concentrations of the analytes present in those samples. Quality Control: AUC can be used as a quality control parameter to assess the reproducibility of a measurement technique or the stability of a sample over time. By monitoring the AUC of a known standard or control sample, you can determine if the measurement system or sample integrity is consistent. Remember, when using AUC for quantification, it is essential to establish a reliable calibration curve or reference standards to ensure accurate and precise measurements. Further, I'll suggest watching the following tutorials for FWHM. th-cam.com/video/tziXRV4XM0k/w-d-xo.html th-cam.com/video/1ZiDJ3NZnL8/w-d-xo.html th-cam.com/video/hhh1dUli7BI/w-d-xo.html Thanks
This is amazing!! ✨Thanks a lot! I'm doing some data analysis and I was strugling with the deconvolution on Origin. You've saved me a lot of headaches 🤩💯 Greetings from Ecuador ✌️
Thank you for your comment! While the tutorial focused on the basics of deconvolution in OriginLab, I appreciate your interest in applying it to protein structure analysis. Deconvolution can indeed be a valuable tool in some aspects of structural biology. However, the process of analyzing protein structures is more complex and involves techniques like X-ray crystallography, NMR spectroscopy, and computational modeling. Deconvolution is then performed on these spectra for further deep insight.
Nice video well done sir I was waiting for that one , thanks you so much , now I have learned many techniques from this video. Please in next video also make the video about “ how to find crystalline size from XRD which is partial crystalline and also overlapped peaks”.
Yes. Deconvolution is a process in which you isolate all contributing peaks in the composite. Any calculation you can perform, if you're able to identify your peak (s) of interest. Thanks
Yes, it is possible to perform deconvolution in OriginLab even if the peaks are very sharp. Deconvolution is a mathematical technique used to enhance the resolution of signals by separating overlapping peaks or removing unwanted contributions from a signal. Thanks
Sir, from 2 weeks I'm stuck for deconvolution, which I want for amide region (in FTIR). As I m confused whether to go for secondary derivative or from smooth one. I saw your baseline correction video too, but with little success. Sir, please gv your precious time to overcome sleepless nights and If you allow may I share my data once.
When a noise is such that it's reflected all over the spectrum, you may only go then for the smoothness of the plot. If the deconvolution isn't working on the whole spectrum, try to plot only that region of the plot where you're interested to deconvolute the peaks. Try this, I hope you'll have a peaceful sleep. Thanks 👍
Very helpful. A question is whether there is a criterion or benchmark for comparing the cumulative fitted curve with the original curve. Or, just by "seeing" the difference of two curves can we decide whether the fitted one is good or not.
Thanks for the appreciation dear. Yes, there's a criteria. The adjusted R2 value is supposed to be closed to 1. This value is shown in the data sheet or table after fitting.
Highlight the desired column. Select Analysis: Mathematics: Differentiate from the Origin menu to open the differentiate dialog. The X-Function differentiate is called to perform the calculation. Then do it again of the 1st derivative column. Thanks
Sir deconloution and multiple peak fitting bith are same? Or not? If mot how we distinguish sir? Please clarify my doubt sir. Thanking you sir, nice video
Although the result is same, however both are different. In deconvolution, you find the individual contribution of merged peaks. While in multiple peaks fitting, we fit the peaks. Thanks for the appreciation.
Sir While deconvolution for my ftir spectra, the fit did not converge. I have tried multiple times and the same repeats. Why does this occur? What may be the solution for this? Nice video sir.
In FTIR, Usually we have two problems. First, either the data is too noisy or it have many peaks. For the first, do smooth you data and for the second, try to deconvolute in segments. Thanks
I am trying to deconvolute the OH PEAK of the spectra .The spectra does not show any peak as seen in your deconvolution. So my confusion is how to choose the peak points. Thankyou for your response.
Please check your email. Your peak seems smooth, but upon taking derivative, some humps were observed, selected those points and applied deconvolution to it. Thanks
They're almost the same with a little difference in their equations. You may check this difference by clicking the equation in the fitting menu. Thanks
Baseline correction is an important pre-processing technique used to separate true spectroscopic signals from interference effects or remove background effects etc. Thanks
Thanks sir. It was very helpful. Can you please guide how to deconvolute the peaks of staggered plots? Mean plotting more than one spectra and then deconvoluting peaks in each spectrum? Please make a video or if there is already one, plz provide me the link.
I tried that. I have an IR spectra and need only one the area from one peak for a calibration. But if I follow the steps in the video, with only one peak selected, my origin tries to fit one gaussian curve that represent the whole spectra, insted of only the selected peak. Du you know what might be the problem? Thanks for the video and anserwring my question in any case. :)
Thank you for your video. I have seen many tutorials but none of them gives a tutorial on complex spectrums (which has 20-30 peaks). Generally, it is impossible to fit them in a single trial. Can you make a video on it?
Thanks for the appreciation. The procedure I have shown has nothing to do with number of peaks (as many as available can be chosen for fitting). If you have some complex peaks, you can share your data file, I can have a look. Thanks
Thank you very much bro you saved a lot of sleeping time.I was breaking my head for this deconvolution techniques you made my day.
Glad to hear that. Sleep tight. Thanks
Hello, thank you for your explanation, it was helpful. Please , for my case I have an experimental data for 7 mesured in function of frequency, so as a result I have more peaks and I don't know how can I do your method ?
Thanks for the appreciation dear 😊.
You will have to do it for each set of data individually. Let me know if not successful in doing it. Thanks
Thank you for your response, I have sent to you my data experimental
@SomayaRiffi right dear. Thanks 😊
sir how to calculate % of beta sheet, turn and random coil from FTIR deconvulated spectra
To calculate the percentage of beta sheet, turn, and random coil, you can use specialized software or perform a manual analysis. Popular software tools for this purpose include DICHROWEB, K2D3, and CDSSTR, which can assist in deconvoluting FTIR spectra and estimating secondary structure percentages.
If you prefer a manual approach, you may want to use established methods like the Reed and Richards method or others based on curve-fitting algorithms. These methods typically involve assigning specific spectral regions to different secondary structures and fitting the experimental spectra accordingly. Thanks
Thank you Dr for another amazing tutorial. I have a question tho, while deconvoluting, I noticed the x values of the cumulative fit are limited to 1000 values only, while my original data has over 2000. So when I try to fit the C fit with my original spectrum, the C fit shape are shrink, thus inable to fit in graph. By any chance, do you know how to resolve this problem? I appreciate your time thank you!
Thank you for your kind words and for bringing up this issue. I understand the frustration you're experiencing with the limitation on the number of x values for the cumulative fit in Origin. It seems like your original data has more data points than the cumulative fit allows, resulting in the fit shape shrinking when you attempt to fit it with your spectrum.
To address this problem, I'd be happy to take a closer look at your Origin file. Please feel free to send it to me at sayphysics@gmail.com. Once I receive it, I'll examine the data and see if there's a workaround or solution to ensure that the cumulative fit aligns properly with your original spectrum.
Thank you for reaching out, and I appreciate your patience as we work to resolve this issue.
Oh I just figured out the solution, under NLfit: NLfit > Settings > Fitted Curves > Points: 1000 (change to the values you want). Leaving it here in case someone encounter the same problem.
@@SAYPhysics That is very kind of you Dr, I so appreciate how far you went to help others. Fortunately I figured out by playing around with the settings under NLFit and it fits well now! Thank you again for helping, take care Dr
Great that you resolved the problem. Sure, others will benefit from it in case they encounter such a problem. Thanks
You're most welcome dear. I feel pleasure in it. Please share the tutorial in your circle. Thanks
Thank you so much it was really helpful. I am just curious are the spectra already baseline corrected or fitted?
my paper will be rejected cause I cant deconvolute my FTIR spectra, pleasesssss
I can give it a try at sayphysics@gmail.com, if you could give a 100 subs to the channel. Thanks
Thanks so much for explaining this. I was having a hard time deconvoluting my FTIR peaks.
Thanks for the appreciation dear 😊. I'll be pleased if you could share it with others
is it free?
No dear. The OriginLab software isn't free. Thanks
Ya, it is free you can download this software from the internet.
Why origin doesnt give the yc value ffs?
When you go to the sheet, each curve has its own data including Yc values. Thanks
@@SAYPhysics thank you for answering but its same y0 value in video
Y0 is set as an offset for all curves, because deconvolution is set. Each peak has its own value of xc, w, A. Thanks
Xas fitting plz
Sure, I have expertise in XANES and EXAFS but they're far from the stage on which I'm currently making tutorials. Thanks
this is very helpful, thank you. but in my case the fitting lines are overlapping on the original peaks , what to do?
Thanks for the appreciation dear. If your peaks are overlapping the original peaks then its a good sign for a perfect fit.
Hello Sir,
I am working on the deconvolution of peaks using origin. The problem I faced is during the converging, The width and area of each peaks do not allow the peaks to be properly coverged. How should I select each peak width and area specifically?
My second question is how to use the area under the curve for quantification purposes?
Thanks
When deconvolving peaks using OriginLab or any other software, selecting appropriate peak widths and areas is crucial for proper convergence. Here are some guidelines to consider:
Peak Width Selection:
Start with an initial estimate of the peak width based on your prior knowledge or assumptions about the system.
Adjust the peak width incrementally to achieve the best fit to your experimental data.
You can use peak fitting functions like Gaussian, Lorentzian, or Voigt to model the peak shapes. Each function has a width parameter that you can adjust.
Peak Area Selection:
The area under a peak represents the integrated intensity or quantity of the corresponding component in the sample.
The area should be selected in such a way that it accurately reflects the true quantity of the component.
The area calculation depends on the peak fitting function used. For example, for a Gaussian peak, the area is proportional to the amplitude (height) multiplied by the square root of 2π times the standard deviation.
It is important to ensure that the peak area is not affected by nearby overlapping peaks. In such cases, appropriate baseline corrections or baseline modeling techniques can be employed to separate the peaks and accurately determine their individual areas.
Regarding your second question, the area under the curve (AUC) can be used for quantification purposes in several ways:
Concentration Determination:
If you have a calibration curve relating the analyte concentration to the AUC, you can use the AUC of your sample to estimate its concentration.
The calibration curve should be constructed using standards with known concentrations and their corresponding AUCs.
Comparative Analysis:
The AUC can be used for comparative analysis between samples.
By comparing the AUCs of different samples, you can infer the relative quantities or concentrations of the analytes present in those samples.
Quality Control:
AUC can be used as a quality control parameter to assess the reproducibility of a measurement technique or the stability of a sample over time.
By monitoring the AUC of a known standard or control sample, you can determine if the measurement system or sample integrity is consistent.
Remember, when using AUC for quantification, it is essential to establish a reliable calibration curve or reference standards to ensure accurate and precise measurements.
Further, I'll suggest watching the following tutorials for FWHM.
th-cam.com/video/tziXRV4XM0k/w-d-xo.html
th-cam.com/video/1ZiDJ3NZnL8/w-d-xo.html
th-cam.com/video/hhh1dUli7BI/w-d-xo.html
Thanks
Must the y-value start at 0? Because my first y-point, it is not in zero.
Not necessarily. Even you may focus on one peak at a time. Thanks
After deconvolution in table where i can find intensity amd FWHM values of individual peaks ?
I've shown this in the video about the specific table. Further, I have a few more videos on the FWHM, you may watch them too. Thanks
This is amazing!! ✨Thanks a lot! I'm doing some data analysis and I was strugling with the deconvolution on Origin. You've saved me a lot of headaches 🤩💯 Greetings from Ecuador ✌️
Thanks for the appreciation dear. I'm happy that my content helped you. Blessings from Pakistan. Please share my content with your friends.
Thank you for your valuable video. Do you have an idea of how to use deconvolution to determine protein structure?
Thank you for your comment! While the tutorial focused on the basics of deconvolution in OriginLab, I appreciate your interest in applying it to protein structure analysis. Deconvolution can indeed be a valuable tool in some aspects of structural biology. However, the process of analyzing protein structures is more complex and involves techniques like X-ray crystallography, NMR spectroscopy, and computational modeling. Deconvolution is then performed on these spectra for further deep insight.
Nice video well done sir I was waiting for that one , thanks you so much , now I have learned many techniques from this video. Please in next video also make the video about “ how to find crystalline size from XRD which is partial crystalline and also overlapped peaks”.
Thanks for the appreciation. Sure, such videos will be covered too soon IA.
This was so fun to watch. I actually learned a lot too. Thank you sir! Keep up the great work
Glad you enjoyed it!
sir how to do multiple fitting with our own developed function?
Here's my tutorial on it. Thanks th-cam.com/video/ViIdEllu5pA/w-d-xo.html
Can this be used to get activation energy & kinetic constants? I’m doing TGA for biomass combustion. Please Dr I need your suggestion. Thank you.
Yes. Deconvolution is a process in which you isolate all contributing peaks in the composite. Any calculation you can perform, if you're able to identify your peak (s) of interest. Thanks
okay i will stop using python and lmfit for data with a lot of different peaks^^ The lmfit guesser disappointed me^^
As you prefer. Thanks
Thank you for making this insightful video! 👍🏻
Glad you enjoyed it!
Thank you, Dr. May I ask a question ? My peaks are sharp. Should I do curve fitting before starting the deconvulotion process?
Yes, it is possible to perform deconvolution in OriginLab even if the peaks are very sharp. Deconvolution is a mathematical technique used to enhance the resolution of signals by separating overlapping peaks or removing unwanted contributions from a signal. Thanks
@@SAYPhysics Thanks a lot for your response 🙏🙏
@igsr1869 welcome dear ☺️
Sir, from 2 weeks I'm stuck for deconvolution, which I want for amide region (in FTIR). As I m confused whether to go for secondary derivative or from smooth one. I saw your baseline correction video too, but with little success. Sir, please gv your precious time to overcome sleepless nights and If you allow may I share my data once.
When a noise is such that it's reflected all over the spectrum, you may only go then for the smoothness of the plot. If the deconvolution isn't working on the whole spectrum, try to plot only that region of the plot where you're interested to deconvolute the peaks. Try this, I hope you'll have a peaceful sleep. Thanks 👍
@@SAYPhysics alright Dr.SAY, as said I will plot accordingly, if fail I will seek again your guidance.
Amazing! Thank you so much, you saved my life! :')
I'm glad it helped. Thanks dear
Very helpful. A question is whether there is a criterion or benchmark for comparing the cumulative fitted curve with the original curve. Or, just by "seeing" the difference of two curves can we decide whether the fitted one is good or not.
Thanks for the appreciation dear. Yes, there's a criteria. The adjusted R2 value is supposed to be closed to 1. This value is shown in the data sheet or table after fitting.
Thank you very much for this tutorial, it was incredibly useful! 😃
Thanks for the appreciation dear 😊
How can i make 2nd derivatives of spectra with origin?
Highlight the desired column.
Select Analysis: Mathematics: Differentiate from the Origin menu to open the differentiate dialog. The X-Function differentiate is called to perform the calculation. Then do it again of the 1st derivative column. Thanks
Here I uploaded a video on a derivative. Thanks
th-cam.com/video/jtHwV24gHu4/w-d-xo.html
sir how deconvolution is done by origin pro 8
You may go through multiple peak fitting options. Thanks
sir deconvolution is done by origin pro8
You may try the mutiple peak fitting as there's no direct option for the deconvolution in origin'pro. Thanks
Thank you so much for this tutorial. It was very clear and helpful
Thanks for the appreciation dear. As a good gesture, I'll appreciate you share it with your friends.
Of course with pleasure keep up doing the good work
Sir deconloution and multiple peak fitting bith are same? Or not? If mot how we distinguish sir? Please clarify my doubt sir. Thanking you sir, nice video
Although the result is same, however both are different. In deconvolution, you find the individual contribution of merged peaks. While in multiple peaks fitting, we fit the peaks. Thanks for the appreciation.
@@SAYPhysics plz make a video how to do deconvolute raman xps data. Would youmind
It's a good idea. Share with me its data at sayphysics@gmail.com. I'll try to make a tutorial on it. Thanks
Thank you very much for this nice video
You're welcome Sameh...Thanks
This very interesting and now I want t learn how to colour those peaks
Thanks for the appreciation dear. Visit the playlist, you'll find many interesting tutorials.
@@SAYPhysics I realised that and we thank you for this kind of light shared to us.
Thanks for the appreciation dear 😊. It's my pleasure
Which version of origin are you using sir ?
In OriginPro 8 I could not find this
I'm using OriginPro 9. In OriginPro 8, this can be accessed through fitting menu. Thanks
ThankYou sir
Thanks for your sharing.
You're welcome dear
Bahut hi acha explane kiye hai
Thanks for the appreciation dear 😊
Sir
While deconvolution for my ftir spectra, the fit did not converge. I have tried multiple times and the same repeats. Why does this occur? What may be the solution for this?
Nice video sir.
In FTIR, Usually we have two problems. First, either the data is too noisy or it have many peaks. For the first, do smooth you data and for the second, try to deconvolute in segments. Thanks
I am trying to deconvolute the OH PEAK of the spectra .The spectra does not show any peak as seen in your deconvolution. So my confusion is how to choose the peak points.
Thankyou for your response.
Send me you data at sayphysics@gmail.com, let me have a look at it...
@@SAYPhysics
Sir
I have sent it via mail.
Please check your email. Your peak seems smooth, but upon taking derivative, some humps were observed, selected those points and applied deconvolution to it. Thanks
What is the difference between Gauss and Gaussian function fit?
They're almost the same with a little difference in their equations. You may check this difference by clicking the equation in the fitting menu. Thanks
@@SAYPhysics And one more thing why do we need baseline correction in first place?
Baseline correction is an important pre-processing technique used to separate true spectroscopic signals from interference effects or remove background effects etc. Thanks
@@SAYPhysics Thank you sir.
You're welcome dear
Thanks sir. It was very helpful. Can you please guide how to deconvolute the peaks of staggered plots? Mean plotting more than one spectra and then deconvoluting peaks in each spectrum? Please make a video or if there is already one, plz provide me the link.
Thanks for the appreciation. I think you'll have to treat each spectrum individually.
@@SAYPhysics I will send you a graph on your email. Can you please see it? I think may be I was not able to convey my msg clearly.
Yes. Sure. Thanks
@@SAYPhysics Please check your email.
Responded. Thanks
You are awesome.
Thanks dear
Start at 6:35
I have discussed a couple of different situations to explain the deconvolution process. You're right that second type starts at 6:35. Thanks
Is it possible to fit just one peak?
Yes. Select one peak and do the same process. Thanks
I tried that.
I have an IR spectra and need only one the area from one peak for a calibration. But if I follow the steps in the video, with only one peak selected, my origin tries to fit one gaussian curve that represent the whole spectra, insted of only the selected peak.
Du you know what might be the problem?
Thanks for the video and anserwring my question in any case. :)
Send it to me at sayphysics@gmail.com and mention your peak. Let me try it. Thanks
It is nice
Thanks
Well done
Thanks
thank you for the good explanation!
Thanks for the appreciation dear 😊
sir modern physics bhi upload kijiy
For example, which topic you’re interested in to be uploaded in Modern Physics. Thanks
Thank you very much ✨
You’re welcome 😊
Thank you for your video. I have seen many tutorials but none of them gives a tutorial on complex spectrums (which has 20-30 peaks). Generally, it is impossible to fit them in a single trial. Can you make a video on it?
Thanks for the appreciation. The procedure I have shown has nothing to do with number of peaks (as many as available can be chosen for fitting). If you have some complex peaks, you can share your data file, I can have a look. Thanks
@@SAYPhysics How can I share it?
sayphysics@gmail.com
@@SAYPhysics sent
@@manish2mech responded...Thanks