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Actually I tried it in QE but the only problem arising where the output file shows no symmetry found. How to turn on that symmetry? (The ibrav tag is given properly)
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Dear Deep Mondal
There are a lot of possibilities, but in most cases, it occurs because QE cannot detect all expected symmetry operations given the numerical precision of your atomic positions or cell matrix. You could try to increase the number of digits to the right of the decimal point.
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Hello Everyone,
My research work involves concentration measurements using a laser-induced fluorescence technique with silicone oils as working fluids. Silicone oils being highly hydrophobic in nature complicates their mixing behavior with typical commercially available inexpensive fluorescent dyes.
I understand there are solvent-based oil-soluble dyes used in petrochemical industries though as far as I know, they fluoresce in the ultra-violet wavelength range.
I also understand that the emission/absorption spectra of fluorescent dyes are also solvent-specific and studies pertaining to that are limited. So I was wondering if anyone is aware of dyes that would mix homogenously with silicone oils and fluoresce in a 527 nm wavelength Nd: YLF laser light source.
Thank you,
Ankit
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Coumarin 153, for example.
(Kim, D. S., Lee, W., Lopez‐Leon, T., & Yoon, D. K. (2019). Self‐regulated smectic emulsion with switchable lasing application. Small, 15(49), 1903818)
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I run the CD spectra of the modified and non-modified protein and the 2ndary are the same. However, there is a change in amide I in the FTIR results. Thus, the functionalization might be expected to change the secondary structure. Kindly any suggestions with references.
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Hi,
I am fairly new to FTIR and I am analysing some inks using ATR. The obtained results were processed using the same background, and plotted against a common scale. When interpreting the results, (a) I notice that the spectra looks very different in Transmittance vs. Absorbance. Is this real? Or could be an artifact of the way the sample interacts with the crystal (e.g. should I repeat the measurement)?
(b) Also, it seems that there is a real vertical offset between sample blue and sample purple. If that is the case, does this suggest that one is overall more absorbent / transmissive than the other?
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I study on some kind of infrared barrier and I don't know how to calculate normalized reflectance spectra weighted by human body radiation?
For example you can see results of this article but authors did not mention the calculation method:
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Based on my understanding, the absorption of infrared for example, band at ~1000 cm-1 caused by the absorption infrared by the Si-O bond in FTIR spectra. So, the XRD results will show a strong peak at a certain 2-theta to show that the SiO2 is there. Is it correct?
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After performing a FTIR test with lime-treated bitumen I am observing the transmittance was reached up to - 40% is that an anomaly. How to understand this behavior of spectra?
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Hi everyone, i have work using paracetamol sample with electrochemical wastewater treatment under special conditions, then analyze with COD (Chemical Oxygen Demand) removal, UV and FTIR.
Analyze by the COD removal, the COD removal is high which were up to 70%. The UV spectra shows that the UV peak were reducing between control and treated. But, the FTIR spectra shows that the FTIR of control (untreated Paracetamol) in blue curve and that of treated in purple curve were same like there's no difference. Whereas, based on the COD removal and UV spectra there is a difference. Can anybody tell the reason why the FTIR curve like that? Is it okay if the curve of FTIR like that? "If the the absorbance of the uv peak were reduces, then the transmittance of the FTIR also reduces" is that statement true? The FTIR curve were confusing, so I need your help.
Thanks in advance...
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Tio2, Nps, Dye degradation, CQDTs
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Hi,
I am working on microplastic contamination in the water samples, and I have prepared the samples as per NOAA. Still, when analyzed using FTIR (Bruker - ATR mode), the transmittance spectrum is more than 100% (nearly 102 or 104). Please explain how to get rid of these and interpret the results?
I am attaching the raw spectra for reference
Thank you in advance
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Dear researcher,
I have FTIR spectra of plastics and I need to identify their chemical composition. there's any software or database for this issue?
I found Poseidon, but I don't know the process or parameters about it...
Thank's in advance for your answers
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Does anyone have some good ref talking about how do the FTIR spectra of EDTA change with the formation of Calcium chelate ? Thanks a lot !
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Get your FTIR results analyzed just for $ 20. Check out the link bellow:
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The blue curve in the attached figure is representative of a thermally treated (1000C) pellet of carbon-13 where the orange curve is for a pellet that was cured at 150C.
The literature for locations and interpretations of Raman spectra bands of amorphous carbon seems...a bit unorganized.
Following Ferrari's amorphization trajectory, I would interpret the increase in Id/Ig between the two as an increase in structural order (going from aC to nC graphite), also following the slight increase in the Gpeak position. Similarly, the D3 band seems to be associated with an amorphous structure. The reduction in D3 intensity would also indicate a decrease in the disorder and higher concentrations of sp2 sites.
I am wondering if those more experienced come to the same conclusion, what the more pronounced separation of D2 and G bands would indicate in the heat-treated samples, and what other information anyone would pick up from these two spectra.
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How did you acquired the Raman spectra (laser power, wavelength, acquisition time, objective)?
The setup is important to make sure that no burning occurred, which can be very spontaneous....
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Please provide a relevant reference
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Please explain what you mean. The inner filter effect is a reduction in fluorescence intensity caused by absorption of the excitation and/or emission light by a substance in solution. If you are exciting the fluorescent probe in the UV range at which DNA absorbs (peak absorption is around 260 nm), the DNA could cause an inner filter effect if its concentration is high enough. However, it should be no problem to avoid this by using a fluorescent probe that is excited at a longer wavelength at which DNA has no absorbance. There are many such probes that increase their fluorescence when bound to DNA, some quite enormously, such as PicoGreen. With excitation maxima in the visible range, there would be no inner filter effect from DNA.
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Dear all,
I made an experiment with polymers and how UV irradiation changes the surface structure. Therefore, ATR spectra of pristine, 24 days and 48 day aged polymer pellets were taken. Now I want to quantify if a significant change occurred.
I am currently working with R, so I would be very thankful for R compatible ways. Thank you in advance.
Best,
Sefine
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R packages mdatools (optimized for beginners) or chemometrics will give you all the functions that you need.
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By using kubelka - munk function to DRS data how to calculate urbach energy values for thinfilms
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Hello,
I have commissioned four Raman analysis last week.
But when I looked at data, one of it looks like somewhat enlarged.
It's intensity was about 10 times larger then others.
(one data shows intensity range from 3000 to 13000 while others show 200~1500)
I want to compare two of them, but it's hard to see peak of smaller spectra due to propotion difference. I could shift data parrel to y-axis if it was just baseline difference, But can I shrink/enlarge data to y-axis direction?
I have attached part of my data.
thank you for your time.
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Thank you for your reply,
What I was going to do was comparing catalyst before recation, and after reaction. I thought it would be funny to plot them in different scale. But when I read your recommendation, It seems some research plot different raman spectra in 2-axis I think I should concern plotting specrtra in 2-axis.
I appreciate your kindness.
thank you, have a nice day.
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I am mentoring a trainee who is writing a dissertation on phototherapy for neonatal jaundice. She has been using a spectroradiometer and has noticed that the spectra from LED-based units are all slightly asymmetric. I have also noticed this in publlished papers. In the attached drawing I have exagerated the effect, where the emission of wavelengths longer than the peak emission, but many spectra that I have seen show this effect. Anybody know why this may be?
Thanks in advance
Mike
Michael Lynn
CIE rapporteur
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LED emits non-coherence light, Commercial LED has a layer of phosphor-compound material deposited on the emitting area to convert and control the light output spectrum, Without knowing how the emitted light is measured, and what type of LED is under test (What type of active materials, power output, etc.) it is difficult to explain, yet the light output spectrums is not going to be symmetric
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I am getting some anomalous response on the ESR spectra.
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Thank you for this interesting question. Under identical preparation conditions, the magnetization of film is depending on the average grain size and also on thickness of the film. Now, at constant thickness the magnetization is inversely related to grain size and, at constant grain size, the magnetization is directly related to the film thickness. The question here is whether this relationship is absolute. The answer is "No", as there are critical grain sizes for each thickness below which the above relation become reverse. In my opinion, this anomalous behavior may report only when one experimentally practiced on a wide range of particle size and film thickness. For that I recommend you to go through the results reported in [1] as it is in line with above explanations.
Best regards
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Hello, this is my first post on this site. I'm an undergraduate student doing some Raman spectroscopy of CVD-grown graphene strained on silicon dioxide nanospheres. I notice that D and G' peaks show up in some measurements. The transfer process of the graphene to the silicon dioxide nanosphere-coated silicon chips I would think is far from perfect, as in certainly interferes with the structure of the graphene as there are rips and tears across the sample, as well as impurities and other things. You do however have "pristine" regions that only show G and 2D peaks.
On a loosely related tangent, I'm interested in how the molecular symmetry of graphene plays a role in its Raman spectra, and how that can be expressed mathematically. I wonder if perhaps the mathematical description of graphene in terms of group theory can possibly help explain the redshifts that occur in strained graphene versus unstrained graphene. If anyone has some advice or things to read about that, please let me know!
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In perfect graphene, the D-peaks are by symmetry not Raman active. ideal graphene should only show the single G-peak. However, when there is anything disturbing the symmetry and structure, the condition is relaxed and the D-peaks become visible. Hence, their name D for "defect" peaks. Based on the relation of peak intensity or the integrated intensity below the modes, the quality of graphene layers can be quantified.
There are numerous reviews on Raman spectroscopy in graphene, explaining which information can be extracted and how they can be extracted from analyzing the spectra.
Check, for example, this article by Andrea Ferrari:
You should be able to quickly find numerous more articles.
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I have two questions, actually:
1 - Is it possible to "drag" one spectrum to reposition it against another spectrum for a better match/comparison? I know I can go to Process > X Offset and adjust but can I do it using thus the mouse?
2 - When I'm pasting the spectra directly into Spectragryph's canvas is there a way to keep the unity used for x and y axis fixed? most of the time when I paste the second spectrum it changes the units to cm-1 and mess with the whole view.
Thanks.
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For 1): please use the "Scale & Shift" function from the Plot/Views ribbon. It allows exactly that. Also read the explanation which is shown when the mouse resting over the button, and use the options form the dropdown menu
For 2) Spectragryph will seek for x axis type information within the spectrum file. If nothing is found, it will use the default values, which can be set from File > Options. After loading or pasting a new spectrum, the displayed axis types always change to those of the most recent spectrum introduced.
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I am using Spectragryph V1.2.15 to visualize FTIR Spectra. But it is showing values in "nm" on x-axis. When i chose the "wavenumber(1/cm)" instead of "nm", it changes the range to 16000-25000. Please suggest where can be the problem?
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What about directly asking the expert on this software (me), who developen it and answers a couple of requests every day? You could even use the Researchgate messaging tool...
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Currently, I want to compare between the output power of a rooftop PV system which can be obtained direct measurements of (Isc and Voc) and the estimation power output of C-Si based on the incident solar spectra and spectral response.
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Dear Balázs,
Thanks for your response, I sent you a message. I am looking forward for hearing from you soon.
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Similarly In XAS (X-ray absorption spectroscopy) spectra for 3d elements, why BE of the L3 edge has lower in energy than the L2 edge?
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Ah, yes. I just have never seen it as an acronym before.
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I have prepare copper nanoparticle of plant extract and taking uv spectra but how to analyse peaks
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Hello! the plasmon resonance of copper nanoparticle is at 540 nm approximately, usually characteristic peaks of various compounds in plant extract are in the range from 200 to 450nm, therefore you don't have interference. You did not mention a clear question what information you need to extract from the UV -vis spectrum
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Hello,
I want a program that i can use to get the raman spectra of crystals not just molecules. Do you have any idea of how i can do that and if there is some way to do it using python.
Best Regards,
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Well, first you need to run a "ground state" DFT calculation. Getting from there to a Raman spectrum requires additional packages, for example in Turbomole the aoforce tool for the frequencies, see p. 48 here:
Then you have the normal modes and can go for the Raman intensities. You can use the dynamic or static polarizability approach within Turbomole (see 8.4.9 in https://www.turbomole.org/wp-content/uploads/2019/10/Turbomole_Manual_7-4.pdf) or use an external package like SNF:
SNF also works with other quantum chemistry packages if you have something different licensed.
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I have come across studies which have mentioned Raman and FTIR to be complementary. So, why are some bands present in FTIR but are absent in Raman or vice-versa.
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In short, the two techniques are sensitive to different types of vibrations and therefore provide complementary vibrational spectra. In general, FTIR is used for the identification of functional groups of molecules while Raman works great for the identification of skeletal structures. When used together they can provide a comprehensive (almost complete) characterization of the molecular vibrations of the investigated sample.
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I have acquired my Raman result of microplastic in SPA files, but i have trouble in identifying them. I also found reference spectra from the Spectragryph website (https://www.effemm2.de/spectragryph/down_databases.html) but I can't find how to match the reference with my Raman result. Is there a way to do so in Spectragryph?
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There is a video that explains how to use the spectral database features in Spectragryph: https://www.youtube.com/watch?v=InRWl5qTuH0
Also, you should check SLoPP and SLoPP-E Raman Spectral Libraries for Microplastics Research. The authors have provided free access to the data files: https://plasticactioncentre.ca/directory/slopp-and-slopp-e-raman-spectral-libraries-for-microplastics-research/. Maybe you will find these resources helpful.
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I have three MS spectra of an unknown protein. The protein has been separated and directly analyzed with a MS without trypsinization (top down approach). How can I know the identity of the protein? I suppose I can search for a matched spectrum in a library. However, I have no experience with top down proteomics and I don't know which software to use for the protein identification. Any help please?
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Hello! Thank you for your reply. I used MaxQuant but it is for shotgun approach. I was having a look to fragpipe but it seems it also can be used only for shotgun approach
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Hello,
When I run a fluorescence spectra measurement on Jasco FP-8300 Spectrofluorometer, the intensity does not exceed 10000 even after changing the scale. As shown in the picture, once the intensity reaches 10000, I get this plateau. I would like to ask whether it's a parameters issue or a machine issue; and if there is a way to fix it?
Thank you in advance.
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This is because the detector was saturated, meaning that it cannot detect any more light. Solutions to this problem are (1) dilute your sample, (2) narrow the slit widths, (3) use a cuvette with a shorter path length, (4) use non-optimal wavelengths of excitation and emission, or (5) put neutral density filters in the light paths.
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It is known that bands at 2920 and 2850 cm-1 in FTIR spectra are assigned to the asymmetric and symmetric stretching vibrations of (CH2) groups.
One peak at 1920 cm-1 was observed in the FTIR spectra of the control treatment in my experiment, but when the plant was subjected to varied salinity levels, a new band at 2850 cm-1 appeared.
Anyone who could assist me would be greatly appreciated.
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I assume you are studying salinity response in a certain type of plant (or..?). Please provide more details about your experiment (FTIR method, experimental conditions, salinity treatments). O regard the 2850 cm-1 band, you may have some changes in lipids.
Maybe you will find useful the bellow papers:
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I have the Raman spectra for WO3 samples. I have peaks at 270, 324, 714 and 805 cm-1 for the stretching and bending modes of O-W-O. A small peak for the W=O can be observed at 943 cm-1. For which peaks should I calculate the ratio? Also how do I interpretate the results? (eg: if the ratio is smaller than 1 or close to 0.5, respectively 0 - what would that mean?). Thank you in advance!
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Hi Istvan, EPR spectroscopy could be of help to determine defects in WO3. Low temp Q band would be the best. If you want I can help you with that.
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I am trying to understand the magnon spectra in simple magnetic compounds like BCC Fe. Can anyone help me with plotting the magnon band structure for BCC Fe? I am very much new to this field. Thank you.
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Thanks, Martin Rotter, I will have a look into it.
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More specifically, I want the comparison in wavenumber-based power spectra, opposed to frequency-based. That would include converting multiple signals into a cross spectrum, finding the phase, and then the final conversion to wavenumber.
Extra points if it is in the field of plasma physics and magnetic signals.
Thanks in advance!
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I would recommend and references within. There is a reasonably extensive discussion in the first Sections including Fourier--Wavelet Comparison (with pointers to selected literature).
Best Regards
Alexander
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Why the values of the intensity ratio of doublet spectra of the laser-produced plasma spectrum differ from the theoretical value of the intensity ratio given in NIST data.
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It may be the result of line absorption in plasma.
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I am currently working on characterizing Pd(111) using XPS but I keep getting a low electron count( Intensity)
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If you have a count rate from a previus sample to look at and condifent that the counts are lower then could be any of the following for example - some will be system dependent for example:
1. Sample very dirty so attenuating the Pd peaks
2. X-ray power lower than before
3. Position of sample relative to x-rays and analyser
4. Channel plates/Channeltron needs replacin or at very least plateaued again
5. Wrong slot/aparture used giving small spot analysis
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1. Is it possible to multiple peak fit O 1s spectra of the XPS in case of high entropy alloy.
2. The peak identification, is it possible since most of the metal oxide peaks are within a very narrow range in the O 1s spectra.
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I would recommend checking how wide an O1s peak is for a less complicated compound with your XPS setup. If your alloy has a wider peak, you can put in components at the positions of the individual metal oxides and see if that's a proper reconstruction or whether you need more, eventually mixed, components.
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I am observing two distinct peaks in the XPS high-resolution spectra of O 1s, (the sample is a nanoparticle colloid and Oxygen is only coming from the solvent) the nanoparticle are multimetallic, is it possible to identify which element is forming the oxide by analyzing the O 1s spectra alone.
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From O 1s spectra alone, it is very difficult to find which metal is forming oxides because binding energy values are very close for metal oxides. But you can analyse the high-resolution XPS spectra of each metal present in your sample. This will definitely help you find out which one is forming oxides.
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The researcher shows the CD spectra data wherein x-axis it is wavelength but in Y-axis it is written CD (mdeg), why not ant fixed technical term which can relate both ellipticity and absorbance. the unit of cd signal is deg•cm2•dmol-1 is there any other term we can use in this replacement that Is meaningful and accepted.
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Reporting in degrees of ellipticity recognises that what is being measured is a difference in absorbance (of left and right circularly polarised light) as opposed to a change in absolute absorbance (as in UV). The units of CD are therefore both meaningful and accepted so I don't think there is much mileage in seeking to replace them.
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Hello,
I am investigating interactions of poorly soluble pharmaceutical (nabumetone) with cyclodextrins in solution and solid-state. Complexes of nabumetone and beta cyclodextrins were prepared in different molar ratios by grinding in high-energy vibrational mills and corresponding physical mixtures were prepared using a mortar and the pestle as well (n:n = 5;1, 3:1, 2:1, 1:1, 1:2, 1:3 and 1:5). In the ATR spectra of ground samples with higher content of the pharmaceutical, I noticed an increase in the intensity of characteristic bands of the pharmaceutical (in comparison to corresponding spectra of physical mixture) but I didn't observe the same phenomena in the corresponding transmission spectra. Usually when these kinds of samples are investigated by infrared spectroscopy decrease in the intensity of the characteristic bands of the guest molecule is explained by the inclusion of the molecule in the hydrophobic cavity of cyclodextrin. What is the possible cause of these increments in nabumetone band intensities in ATR spectra? Why aren't these increments visible in transmission spectra as well?
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According to the sucrose experiment I did today, see Figure 3 (because I don't have your sample) (g-grind p-pressure), I think the enhanced spectrum after grinding in your experiment is that grinding increases the contact area between the sample and internal reflection element.
In the meantime, please give me feedback if you experiment on the Diamond-ATR, I'd love to know what's going on, thanks!
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is there any software or methods to identifying bonding~functional groups of Raman spectra
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If there are no references on your particular material, you'll have to perform a DFT calculation and a subsequent normal mode calculation [or get someone who's familiar with the method to do it].
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In laser-induced plasma spectra, an element usually has multiple lines corresponding to it. In theory, how to determine which lines are most likely to excite? In addition, there are two elements in a sample with the same content, the same energy level, the same transition probability. Why are atomic lines detectable for one element and not for another?
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The NIST LIBS database is a very useful resource in predicting what lines should be present in a plasma (https://physics.nist.gov/PhysRefData/ASD/LIBS/libs-form.html). The theory is based on the Saha Ionisation Equilibrium model which is bet suited to low temperature high density plasmas
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  • The transmittance spectra is from a coloured TiO2, but after converting to absorbance, the absorbance spectra look so strange. I used the equation ABS=2 - log(T%). I do not know what is wrong. Because of the transmittance spectra, the line was lightly increased between 350 nm to 400 nm, but for the absorbance spectra, it has a straight increase. I attached the files I did. Hopefully, there is an expert who can help me to work on that.
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To get good absorbance spectra, the transmittance should be not smaller than 0.1. Your transmittance spectrum has ranges where transmittance is zero which means indefinite absorbance. If it is a layer, the thickness would need to be much smaller, otherwise you should measure reflectance instead.
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I want to study blood samples by KBR to visualize spectra occurring between 900 and 1100cm-1. Specifically to see the behavior of glucose and insulin. In fact I would like to know if I can study glucose and insulin solutions by KBR, ¿how do these liquids affect the potassium bromide tablet and the spectra?
¿Could you help me with any reference in the literature that talks about the types of samples that are studied in KBR and why we can't study liquids by this method?
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The important part of the answers is thst you are examining dried blood. KBr is soluble in water. Water has a strong absorbance across the 1100cm-1 region if used on ATR. Even at room temp this will change in time as the water evaporates.
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Hello,
I am trying to recover RNA from nerual N27 cells that I encapsulated within Alginate hydrogels. I am using the PureLink RNA Mini Kit, using the manufacturer's protocol (Starting on pg. 14: https://www.thermofisher.com/document-connect/document-connect.html?url=https%3A%2F%2Fassets.thermofisher.com%2FTFS-Assets%2FLSG%2Fmanuals%2Fpurelink_rna_mini_kit_man.pdf&title=UHVyZUxpbmsgUk5BIE1pbmkgS2l0 )
I believe I have successfully recovered RNA from plain cells in suspension. I attached the NanoDrop Spectra (Cells Only Control RNA.PNG). The 260/280 was 2.1, and the 160/130 was 1.86. The concentration was 229.8 ng/ul.
However, I have been struggling to recover pure RNA from cells in alginate hydrogels. Like with the plain cells, I rinsed them 3x in cold PBS, which broke up the alginate, and tried adding an extra Wash Buffer 2 rinse. The results (Cells in Alginate RNA.PNG) had a nucleic acid conc of 51 ng/ul, a 260/280 of 2.1, and a 160/130 of 0.09, indicating a contamination of some salts/phenols.
Is there any way to purify my sample so that I can carry out qPCR?
I appreciate your guidance!
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Hey Marilyn,
Did you find a solution to this problem?
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could I ask, please, what is the best software or platform for identifying RAMAN Spectra of Microplastics ? Best if it's a free version.
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You should check SLoPP and SLoPP-E Raman Spectral Libraries for Microplastics Research -
The authors have provided free access to the data files. You can download, plot, and compare the spectra with any software dedicated to spectra analysis such as Essential FTIR (https://www.essentialftir.com/).
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Dear all,
Hope you are doing well. Why in some articles the starting point of PL spectra in TCSPC is greater than 0 ns? A graph is as an example in the file. Thanks
Regards
Johar Zeb
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Hi,
In a most TCSPC setups, you can introduce an arbitrary delay between the start of the TCSPC time axis and the laser pulse (which defines the beginning of the decay). Typically you want to capture the whole rising edge of the TCSPC histogram (e.g. to be able to perform re-convolution fit), so you position it at a small positive time.
Radek
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Collected the FTIR spectra of an unknown polymer sample and tried to match with my database.
But it is not matching with any entry of my database. Indeed quite different from the existing entries. So please help me out in identifying its chemistry and how can I do it in future?
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Kamran Nasir Yes, you are right, as long as you compare it to other spectra that are recorded under the same conditions (same angle of incidence, ATR crystal and polarization state) there should be no problem.
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I have used OSRAM tools, as well as LabCognition Panorama and chrislinbloom. com spreadsheets to compute the perceived color from Uv-vis spectra. When I choose a UV-Vis absorbance graph of a completely colorless sample (i.e. absorbance at all wavelengths equal to zero) the color returned by the program is black, instead of white. For "real" spectra" I sometimes get sensible results, and other times (e.g. when selecting a spectrum with a single absorption peak around 400 nm) I get strange results with negative values for one of the three color coordinates. Does anyone have some suggestions regarding (e.g.) mathematical limitations of the conversions formulas used, or whether I should convert my absorbance graphs to transmitances, photon number, or whatever?
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Pedro J Silva Actually, reflectance = 0 is not possible over larger wavelength ranges, because reflection occurs at interfaces of two different materials which have always different dielectric functions. Maybe things become clearer if you use absorptance instead of absorbance - the former is defined as 1-R-T. Anyway, I remember that a colleague once also was interested in calculating colors from spectra some 15 years ago and I guess she succeeded. If you like I can give you her contact details.
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I want to preprocess spectral data using rmies-emsc algorithm in R ( ). Is there any package that I can use?
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Thank you Shima Shafiee for your answer. I don't think that EMSC package have a function for rmies-emsc. I will really appreciate it if you know any package that have such function.
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I am confused at to the broad peaks, for example between 3400 and 2800 cm^-1. I am having difficulty in this respect
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"between 3400 and 2800 cm^-1" - this is a water
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I am doing a 2D simulation of gold electrodes on a glass substrate immersed in liquid - typically biological solutions, such as PBS with ionic strength of around 100mM. In particular, I am simulating the complex electrical impedance as a function of frequency (basically electrical impedance spectroscopy - EIS). Is there a way to stimulate the presence of the EDL in order to include its screening effects in the EIS spectra? I am currently using the AC/DC module, do I need to use a different one? Which parameters should I know to simulate the formation of the EDL?
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I recently tried to do a D-parameter calculation for reduced graphene oxide, and the value came out to be 21. This corresponds to >70% of sp2 contribution as per the available literature of XAENS. I doubt whether the same calculation can be applied to XPS? Any good literature suggestion is highly appreciable.
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Dontt forget that the X-ray induced Auger will have a different information depth to the C1s core level, so depending on how 'clean' your sample is from the reduction of GO may be more sensitive to the surface carbon. However to comment more it would be good to see the C1s and O1s spectra to comment on the values
See my recent paper discussing some analysis of carbon linked below
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In LIBS spectra, how lines having self absorption can be indentified and how self absorption can be removed?
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I have two samples of the same compound and I suspect they are contaminated with acidic impurities. I record 1H NMR spectra in CD2Cl2 and in pure NMR solvent I observe a nice narrow singlet for H2O at 1.53 ppm. When I record the spectrum of one of the samples of my compound (which I assume has less acidic impurities), the water peak disappears and a broad singlet at 1.9 ppm appears. When I record the other sample (presumably more acidic), the broad singlet appears at 4.0 ppm. Then I spike one of the samples with AcOH and along with the CH3- singlet, I now see the broad singlet at 7.3 ppm.
My hypothesis is the following: When acids are present in the sample the H2O signal in the NMR spectrum shifts downfield (gets deshielded). Can anyone confirm/reject this?
Thanks in advance!
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The presence of acids strongly affects the water chemical shift. As an example, lets record the 1H NMR spectrum of acetic acid (100 mM) in CDCl3. The COOH 1H chemical shift will appear as a singlet at 12-13 ppm. The residual water peak will appear at ~ 1.5 ppm. If the concentration of acetic acid will be reduced, for example to 5 mM, then, there will be an extensive broadening of the carboxylic proton and a shift to lower ppm values. This can be attributed to two phenomena: (i) monomer-diamer equilibrium of the acetic acid and (ii) proton exchange between the monomeric acetic acid and the water protons. Depending on the exchange rate of proton transfer, there will be also a shift of the water resonance towards higher ppm values. Under certain conditions the water and the carboxylic resonances may coalescence into a single broad resonance with a chemical shift which depends upon the relative molar concentrations of the acid and the water content. The same also is the case with phenol type OH groups (see for example Molecules, 19, 13643-13682 (2014)).
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Dear all, I am using metabolic fingerprinting for my clinical studies. I am in doubt that I can use the Raman spectra for quantification? Can I use it semi-quantify? Can you provide me with references? I have biological fluid such as serum, seminal plasma or milk?
TX..
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Mr Gilany,
For the purpose of your study, there is unable to employ in Raman spectroscopy. Please, consider chemometric parameters of quantitative Raman spectroscopy of fungicides in reference [1]. So, your doubts are very relevant.
Currently, there is available only one method, which provide exact quantitative data and is applicabl to determine analytes in complex fluids such as serum, milk, et cetera. The method is mass spectrometry.
However, there should be employed our own-authored (to me and my co-author according to the shown authorship, below) innovative stochastic dynamic theory and model formulas developed, more recently. Please, consider references [2-5]. Our method is tested most recently examining urine, thus achieving /r/ = 1 at mg.(mL)-1 analyte concentration. Consider detail on reference [5].
[1] B.Ivanova, M. Spiteller, A quantitative solid-state Raman spectroscopic method for control of fungicides. Analyst, 2012,137, 3355-3364
[2] Analytical Chemistry Letters, 10 (2020) 703-721; Stochastic Dynamic Mass Spectrometric Approach to Quantify Reserpine in Solution; Bojidarka Ivanova, Michael Spiteller;
[3] Steroids, 164 (2020) 108750 Stochastic dynamic mass spectrometric quantification of steroids in mixture — Part II; Bojidarka Ivanova, Michael Spiteller;
[4] B. Ivanova, M. Spiteller, Mass spectrometric stochastic dynamic 3D structural analysis of mixture of steroids in solution – Experimental and theoretical study, Steroids 181 (2022) 109001:
[5] B. Ivanova, M. Spiteller, Stochastic dynamic electrospray ionization mass spectrometric quantitative analysis of metronidazole in human urine, (2022) submitted.
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I'm currently trying to find the differential cross section for the products following proton irradiation of Si. something like the attached plot [Barak et al, Trans. Nucl Sci 2001] but at different proton energies. I believe the reaction is 14 Si(p,X), and I believe the data would be MT=5 in the ENDF data base. But I seem to be stuck in converting ENDF into something that would be easily readable.
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Dear Dr. Dave Hansen,
The following data may help:
ENDF-201 ENDF/B-VI Summary Documentation
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Hello!
I'm having difficulties comprehending how MS and MS/MS spectra are obtained in regard to eachother.
In easy words:
A package of ions ("package 1") is eluted from the LC and MS spectra are obtained from these ions. From these spectra, the most abundant ions are chosen for further dissociation for MS/MS spectra. My question is: the ions used for dissocation is coming from a different package ("package 2") of ions eluting from the LC, since the "package 1" has already been used for MS. How do we know whether the ions chosen for dissocation, based on the MS results of "package 1" can also be found in "package 2"?
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First off the ions are the same, just changed - it's not like the mass spec has to 1st "see" the ions then decides on dissociation. It's all done on the same ions. Lets take caffeine as an example, the positively charged ion has a mass of 195 and the most abundant fragment is 138. The 1st quad is tuned to 195 - the caffeine ion travels through the 1st quad, then passes through collision cell, it is fragmented resulting in the 138 ion - which passes through the 2nd quad and subsequently detected. The parent is caffeine and the daughter is the fragment 138. They name it like this because the fragment (138) actually comes from the parent (195).
Your "package" in terms of mass spec is actually called a scan. Mass specs have a very fast scan rate (how fast a package goes through the mass spec)- this relates to how fast a mass spectrometer "sees" the ions (packages) passing through the quadrupoles. If you took your peak and sliced it up into 20 pieces one of those pieces would constitute one scan. Most MS/MS systems are able to scan at a rate of 10-20 scans per second depending on the m/z range of your acquisition parameters. If you think about this in relation to the time it takes a peak to elute from your column (peak width), you will realize that there is abundant time for the mass spec to easily accomplish the task, and can do it on multiple target compounds eluting at the same time. To verify this zoom in on one of your peaks and using the software determine how many scans the peak is made up of. A good chromatographic peak requires a minimum of 10 scans across the chromatographic peak. Pull up the performance specifications of the mass spec you are using, and look at the MRM acquisition rate - it's likely to be in the range of 250 MRM data points per second.
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I have synthesised quantum dot using green synthesis. Uv vis spectra show peak at 270 nm(protein peak) and 400nm(quantum dot peak). Excitation wavelength for PL measurement is 390nm but i get broad spectra. What is the reason behind this.
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Dear Saqib Khan ,
I would like ti second the colleague V. B. Zaytsev that the major cause may be the presence of size variations in the quantum dots. You can naturally verify the size of the quantum dots by electron microscope.
Best wishes
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Hello,
I am having a difficult time getting Raman spectra for monolayer MoS2. I have used various substrates (Au, Si/SiO2, Au TEM grid with 5-6nm carbon support) but i have been unable to achieve a proper spectrum unless measuring a sample that is several layers thick or 10s of nms. I typically use a 532nm laser, <1 mW power, and 100x objectification lens. I have also varied measurement parameters like exposure time (10-300s) and number of accumulations (1-25) without luck. Am I missing something? I would have thought it was more straightforward. Thank you in advance for your suggestions
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How about employing a substrate that allows interference-enhanced Raman spectroscopy? If this does not work, you can go one step further by employing ATR-interference-enhanced Raman spectroscopy. Both methods are particularly suitable for monolayers.
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As you may know, the site-specific response spectra are usually limited to 5 seconds, while in many cases, such as the design of long-period structures, we need to have the spectra up to 10 or 20 seconds. The problem is even the GMPEs are usually limited to 10 seconds! I was wondering, is there any method to extrapolate the spectra from 5 seconds to 10 or even 20?
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Thanks for your suggestion.
It seems the method used by NBCC2020 is limited to extrapolation to up to 10 seconds as the required ratio to conduct this extrapolation is given only for the periods up to 10. However, I am looking for the less limited method as my period range of interest is from 0 to 20 seconds.
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As per my knowledge, the EIS technique is used for calculating various impedances like Rs (Solution or equivalent series resistance), Rct (Charge transfer resistance), etc. However, is it possible to calculate separator resistance using the EIS technique, and what component of the EIS spectra can help in recognizing the same?
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Typically, the circuit admittance obtained from an EIS measurement is described by an equivalent circuit. This model representation and its application depends on the ingenuity of the experimenter-interpreter. There is also a contribution from the conductivity of the separator...
Of course, it is better to simplify the measuring circuit by excluding "unnecessary" components in the test cell.
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We have 600-600-600 spectra for 3 treatments.
We are looking for a statistical method (or program) to distinguish significant changes in peaks.
Thanks in advance!
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You could try Two-Dimensional Correlation Spectroscopy (2D-COS) Analysis.
The person who promote this methodic and write a lot of paper - Isao Noda
The one of different software realization - https://github.com/shigemorita/2Dpy
The book describing technique - Two-Dimensional Correlation Spectroscopy: Applications in Vibrational and Optical Spectroscopy https://www.amazon.com/Two-Dimensional-Correlation-Spectroscopy-Applications-Vibrational/dp/0471623911
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I have synthesized cerium oxide nanoparticles via hydrolysis method using NaOH. I obtained yellow precipitates at the end of reaction indicating synthesis of cerium oxide nanoparticles. But in UV vis spectral scan showing two small humps around 225 and at 350 nm. The FTIR spectra showed absorbance peak at 664 cm-1. In literature, FTIR peaks of cerium oxide nanoparticles are reported at 476 cm-1 (Ce-O stretching), 556 cm-1 (O-Ce-O) and 668 cm-1 (Ce-O) stretching mode. I also have peaks at 1055 and 1318 cm-1 for nitrate.
Does that indicate reduction wasn't complete?
Or Calcination is necessary for Ce oxide nanoparticles synthesis?
I have attached the UV vis spectrum.
Thanks in advance for your assistance and guidance.
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You write that you obtained cerium nanoparticles by hydrolysis. Then you ask the question the restoration was complete. Not restoration, but hydrolysis was complete? As a result of hydrolysis, you get cerium hydroxide. Therefore, calcination is necessary to remove water and obtain oxide from hydroxide. Hydroxide has no chromophores and therefore will not absorb in the visible spectrum. The best analysis is elemental analysis for cerium. It can be done on an energy dispersive attachment to a scanning microscope.
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Discussing the FTIR spectra and XRD patterns of barium titanate samples in the literature is diverse and somewhat contradicting. Some researchers are looking for a desirable and justifying reference. One of the main aims of the following article is to address the demand:
The full-text of the article has been attached.
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You may want to check the materials project online resources, the you will find diffractograms and structural models for various different bto phases. Good luck, Dirk
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I used two samples, one of pure SiO2 and one of pure Al2O3. For each sample I obtained the corresponding ATR (attenuated total reflection) and DRIFT (diffuse reflection) spectra. The spectra look very different from each other, they seem to be from totally different samples. What can this be due to? For both measurements I used an FTIR spectrum of KBr as Background under the same conditions of each measurement.
Spectrometer: Nicolet™ iS50 FTIR
Spectral range: 4000 – 400 cm-1
Resolution: 4 cm-1
Background and sample scan: 32
Zero filling factor: 2
Apodization function: N-B Stark
Phase correction mode: Mertz
Detector: DTGS ATR
Beam splitter: KBr
Background and sample signal gain: Auto
Mirror velocity: 0,4747 cm/s (ATR), 0,0317 cm/s (DRIFT)
Aperture setting: 100 (ATR), 200 (DRIFT)
Accesory ATR: Smart iTR™ Attenuated Total Reflectance (ATR) Sampling Accessory
Accesory DRIFT: The PrayingMantis™ diffuse reflection accessory (Harrick Scientific Products)
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A few more things to clarify what Ms. Krol said. All of which can impact how your spectrum appears.
1. ATR is a surface technique so if there is something on the surface of your powders it will show up more.
2. The shifts you see are too much to be a difference related to the ATR element. You might expect a few wavenumber shift but not hundreds. see Milosevic, M., Internal Reflection and ATR Spectroscopy. John Wiley & Sons, Inc.: 2012. or 1. Harrick, N. J., Internal Reflection Spectroscopy. 1 ed.; Wiley Interscience: 1967; p 327.
3. For ATR you typically do not use something that has no absorbance as the reference. You just use the clean ATR with no sample.
4. In diffuse reflectance the KBr is used as a diluent and the only reason for using it as a background scan is to "match' particle size and packing. Other diffuse reflectors with no spectral contribution could be used.
5. In the spectra of SiO2 the spectrum does not make sense. SiO2 should show a strong Si-O vibration and that occurs at ~1100cm-1 indicating that the ATR is the correct spectrum. Google SiO2 spectrum and you will get a number of correct spectra illustrating this point.
6. Similar comments for Al2O3. Al-O vibrations are at very low frequencies (typically below 500 cm-1)
7. Although the band positions appear to be about right for the ATR spectra, in addition to the poorly rationed phonon band from the diamond, there are peaks in both spectra that should not be there and might indicate contamination somewhere.
8. Finally - the Praying mantis accessory is a pain to align to properly. Although the spectra look real, you might be getting a spectrum of something you don't think you are.
Summary ATR and diffuse reflectance should not look that different if you are doing the experiments properly. You will see slight peak shifts and slight intensity variations if you have ATR corrected, plotted the diffuse reflectance as KM units etc. I would very strongly recommend going back and starting again.
  • Clean everything.
  • Align everything
  • Check library spectra to make sure you are getting what is expected.
On the Pike Technologies website (www.piketech.com) you can find a number of resources to understand where you might have gone wrong.
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Is it any possibility to compare relative positions of Fermi level of different materials with given XPS valence-band spectra? If spectra are well-calibrated, Fermi level shoud be at 0 eV, thus, Fermi level of all measured materials should be equal, what - obviously - is generally not true. I am surely missthinking, but I'm not able to find any mistakes. Could anyone help me to solve this problem?
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This depends on the material you are looking at. Let's take silicon as an example. For n-doped silicon, the binding energy of the valence band onset will be higher than for p-doped silicon (neglecting surface states). If you know the bandgap, you can determine the Fermi-level position within it. But keep in mind that this is only valid if your samples are conductive enough so that there is no charging.
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Hello everyone
I am doing a microthermometric investigation of my fluid inclusions, I'll be using different equations of state with some of the available programs (Uni Leoben fluid inclusion programs, SoWat, etc.). I want to make a plot of the isochores calculated with the different EoS's for different FIA types in a way that they cover a certain area in a p,T- diagram. Any suggestions on a nice program to do this?
I'm suspecting that I'm having a ternary water salt system for the fluid inclusions in my sample. The freezing temperature is mostly around - 55 centigrade, the initial melting occurs at about - 45 to - 35 centigrade. It's tricky to determine the exact one even with cycling. The final melting temperature is mostly around - 16 centigrade. How would I exactly determine these datasets in terms of whether it's a binary or ternary system? The crystals which appear at the freezing temperatures are of a dark brownish colour and I'm not sure which phase this could be along ice. Raman spectra also does not give a definitive answer. In case of a ternary, how do I know if I have antarcticite or hydrohalite, and which one melts at the temperature of initial melting? I'm still pretty new to this technique and do not have a lot of experience. Also, which program do you suggest for plotting my inclusion composition within a ternary diagram with drawn temperature isolines and drawn out fields of primary crystallization (in case if I do really have a ternary system) of the H2O-NaCl-CaCl2 system?
Many thanks in advance!
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Good question, also correlated with Interdisciplinary approach of subject study.
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There are a lot of software for modeling vibrational spectra, but what is the best one? There are two major branch of software: firs principal (ab initio) and semi empirical. I'm interesting the both. The "best" means is the software gives the relevant result comparing with experimental spectra.
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Nowadays several quantum chemical program packages contain not only geometry optimization but also force field calculation. I have personal experience with ChemBio3DUltra 13.0. The reliability of the result depends on the level of approximation (from semiempirical to ab initio), an can be used for medium sized molecules. I remember when I was young and wrote my PhD you needed a considerable size computer to perform such calculations. Nowadays such programs run on PCs. It does not replace careful interpretation of experiments, but it can be helpful, especially in comparative studies.
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Question to blue and red shift during Raman spectroscopy of coesite:
For me, the significant blue shift of the coesite Raman lines is a mystery, and I cannot find a simple answer on the net. Therefore I have performed Raman measurements on an ideal SOS sample. This sample is characterized by an epitaxial Si layer on a single crystal wafer of sapphire (SOS).
I have taken Raman spectra of Si at different laser power from 10 to 100% of the 532 nm laser - 100% corresponds to 50 mW.
For the Si main line, I obtained a 520.1 ± 1.8 cm-1independents of the power. That means that the used laser power does not generate the blue shift in the coesite spectra, and the blue-red shift is generally reversible. Furthermore, the SOS test has shown that the problem does not come from a lousy device adjustment.
Water determination gives for coesite very high values of about 8500 ppm or more. Can the high OH-concentration be responsible for the blue shift? This high water content is only possible if the coesite is formed at very high pressure. Another possibility is a significant Al content in the coesite lattice (only possible at high pressure, similar to stishovite which can accommodate Al2O3and H2O through coupled substitution at pressures above 30 GPa (see Tschauner 2019)). For that spokes, the very strong 330 cm-1 bands in the Raman spectrum of coesite are generally missing in the “standard coesite.” All other essential lines of Coesite are present.
Tschauner, O. (2019) High-pressure minerals. Am. Miner. 104, 1701-1731
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I would also expect that if lattice mismatch and heteroepitaxy is at play, a broadening of the Raman bands should be detectable. Is this the case? The fact that the whole spectrum is shifted by the same amount is indeed strange; my first guess would be a calibration issue, but since this is covered, cationic substitution or some kind of ''universal'' structural aspect inducing compressive stress/strain on the crystal would be my next guess
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I am a beginner in the synthesis and characterization of metal nanomaterials. I am trying to figure out what information of the nanomaterials can be obtained by UV-Vis spectra.
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Prakash Parajuli To know about the size, morphology, concentration, fraction of spherical to nonspherical nanoparticles, and size distribution of NPs from UV-Vis data, the UV-Vis data (especially the surface plasmon resonance) is fitted with Mie model (for spherical NPs) and Mie-Gans model (for nonspherical NPs). The Mie model is based on the Maxwell equations accounting for the discontinuity of the dielectric constant between the metal sphere and the surrounding medium. It has been successfully applied to free and functionalized metal nanoparticles in various solvents or matrices with diameters in the range 4-25 nm. Despite the differences among samples, an accuracy of about 6% on the nanoparticle's average size with respect to sizes measured by transmission electron microscopy (TEM). Moreover, the fitting model provides other information not available from TEM like the fraction of spherical to nonspherical nanoparticles as well as the concentration and size distribution of NPs in the sample, which is particularly useful for measuring aggregation processes.
In the following video tutorial, I have used two Mathematica codes based on the above two models to calculate various properties associated with the NPS. The codes and other relevant material are provided in the video description. Thanks
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The problem is that I have a UPS spectrum like the one in the attached photo. This spectrum goes to zero near E=1.5 eV without having a step near this value. the nearest step is about 5 eV. Most of the information I found in literature deals with spectra goes to zero around zero eV but I didn't find anything related to my case.
Can I calculate the work function using the width of the spectrum? If not, what is the correct procedure to follow to calculate the work function and the ionization potential energy?
Thanx in advance.
Attached an example and how I tried to analyse it.
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Dear Allaham,
I am not sure I fully answer your question but I have some general comments regarding UPS and workfunction measurements...
  1. Make sure that you know the limits of the analyser. The analyser record kinetic energies and the to make that it uses a series of electron optical elements that guide the electrons to the detector. The settings of these elements are controlled by lens tables and all lens tables can not operate at all kinetic energies. One would have to set for example a given pass energy in order to access a specific kinetic energy range. Different brands of photoelectron analyses have different ways of dealing with this and different pass energies can access different ranges.
  2. Make sure the sample is properly grounded and that sample holder and sample environment is not magnetic or that there are non-conducting parts. UPS is a technique for detecting very low kinetic energy electrons and the sample environment can play a big role for the outcome of the experiments as charged or magnetic objects can affect/alter the trajectories of the electrons.
  3. Make sure that your sample is clean down to the very monolayer of the surface. Things that look ok in XPS can be terrible in UPS (as XPS look sub-surface due to higher electron escape depth whereas UPS spectral contribution mainly come from the surface). If you for example have carbon “dirt” / advantageous carbon on your sample you might not get signal close to the Fermi level as the carbon contribution is very high in the spectrum. The carbon would then most likely not have any electronic states close to the Fermi level but could have it around 5 eV or so.
  4. Make sure the equipment is calibrated such that it gives the right energy (binding or kinetic) and that the scale is linear and the measurements are repetitive in nature. For UPS it would be good to use a metal sample and see if the Fermi level end up at Binding energy zero.
  5. A calibrated analyser UPS measurement on a clean sample would give you a spectrum with info of the occupied electronic states of your sample down to a level which usually is the first 10-15 eV below the Fermi level after that it becomes tricky… The kinetic energy of the electrons here are very low (21.2 eV photon energy minus 10-15 eV binding energy result in some 5-10 eV kinetic energy). The lower kinetic energy the more demand on your sample environment. And at some point the lens table will stop working as well (out of range). A photoelectron analyser can only detect kinetic energies above zero for a grounded sample and a grounded front end of the analyser. This means that in many cases there is no way of detecting the zero energy edge of your UPS spectrum (the once that make it in must be accelerated of some field generated between different elements of your sample environment) such as a bias between the analyser front and sample (which effectively is an additional lens element of your analyser).
  6. In order to measure the vacuum level you would like to access this cut off at zero kinetic energy and that is usually done by biasing the sample such that the kinetic energy of the electrons end up inside the lens table again. When biasing a field between the sample and the analyser is created and this accelerate the electrons. But when generating this field you can easily get artefacts as your field is not homogeneous around the sample (if you tilt your sample you can notice that the spectra differs with tilt angle). Biasing also creates artefacts in the intensity distribution of your sample.
  7. Once you biased and recorded spectra you can calculate the work function by using the cut off (zero energy) and excitation energy of your light and the Fermi level
    1. Here is a link for a Kratos analyser chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/viewer.html?pdfurl=https%3A%2F%2Fwww.kratos.com%2Fsites%2Fdefault%2Ffiles%2Fapplication-downloads%2FMO456%2528A%2529%2520XPS%2520UPS%2520of%2520PbBr%2520perovskite.pdf&clen=658783&chunk=true
    2. Here is a link to a lecture talking about work function and more chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/viewer.html?pdfurl=https%3A%2F%2Fpublic.wsu.edu%2F~pchemlab%2Fdocuments%2F571-UPS-Lecture1.pdf&clen=2341609&chunk=true
    3. Here is a paper showing what to do with the ionization energy for a semiconductor https://www.sciencedirect.com/science/article/pii/S1567173921001796
So looking at your spectrum I would interpret it as follows (not knowing the details) It is an insulator that has a gap of some 5 eV (sample or covered with carbon?) Your work function end up at 16.7 eV and you are using 21.2 eV light. So your ionization energy would be 4,5 +5 eV (see figure 4 in Jeong WonKim et al Current Applied Physics Volume 31, November 2021, Pages 52-59).
Best regards,
John