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Dear colleagues,
I received this question from a reviewer:
Among different metal ions and anions, why Question: the chemosensor exhibit high selectivity towards Cr3+ only?
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The chemosensor I used to detect Cr3+ ion is a Schiff-base, and to the best of my knowledge, the related papers do not explain clearly the reason why a molecule is a selective sensor towards a specific ion.
So, my response the following:
"The sensing mechanism and selectivity towards Cr3+ can be supported by computational calculations, which estimate the sensing capability of molecules mainly basing on intermolecular interactions and compatibility between ion size and the geometry of chelating site. Hence, the selectivity observed for Cr3+ ion can be explained by its interactional and geometrical affinity to the chelating site."
Despite our response, we received a second revision in which reviewer is asking the same question!
Anyone can help me please!
Waiting for your responses.
With Thanks
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The HSAB principle also plays a crucial role here. Cr3+ being a hard acid tends to bind stronger to the hard centers in the schiff base ligand due to hard-hard interaction.
Moreover, the cavity size produced by the ligand for the host-guest interactions is ideal for Cr3+ ion to strongly bind with the ligand. For other ions, the cavity size may not be suitable for the interaction to take place as that of Cr3+.
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Predictive models that use ordinary least squares (OLS) for parameter estimation must show residuals with normal distribution and constant variance (homoscedastic).
However, in most scientific articles (in engineering-related areas, at least) I don't see a concern with meeting these assumptions. In your opinion, why does this happen? In the end, the results do not change that much when we make the necessary transformations so that these assumptions are met?
If you have had any experience with this topic, please feel free to share.
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The OLS is a short cut to the ML solution. It can be derived directly from the assumption that Y|X ~ N(µ(X), s²), but the solution is correct for any distribution model: justlike the ML estimate, the OLS estimate estimates the expected value (of the parameter) and this is independent of the assumed distribution model ("under some mild regularity conditions", eg. as long as it has a finite expectation and variance).
The difference, therefore, is not in the predicted value, but rather in the uncertainty attributed to this prediction. Depending on the research context, this uncertainty may or may not be relevant. If it is not relevant, then there is no need invest much mental work in figuring out a "most correct" or "least wrong" distribution model.
When models are really used for prediction, the "model inherent" uncertainty (that is determined by the chosen distribution model) associated with a prediction is usually not relevant. What is of much greater relevance and impact here is the differences in predictions between possible alternative models. This is particularily relevant when the predictions are forecasts. Provided there is sufficient data, this pleiotropy of possible alternative models can be adressed by heavily over-parametrized models where the impact of the assumed distributional model approaches zero (such models are nowadays called "deep-learning" models, neural networks, AI etc,). This is then very much on the side of getting most correct predictions at the cost of gaining the least amount of insight. But it works to get predictions with good or acceptable positive and negative predictive values.
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Dear Colleagues,
I'm studying the optical limiting effect in organic material due to reverse saturation absorption. As we know, in reverse saturation absorption, the transmission coefficient decreases as the intensity increases, or the absorption coefficient increases as the intensity increases, resulting in power loss. So, when we increase the laser power to a threshold P0, there are two competing processes: the increase in input power and the power loss due to reverse saturation absorption. If these two processes are in equilibrium, the optical limit curve is horizontal (as in the attached pictures.) However, if the amount of lost power is greater than the increase in input power, the curve must go down at P0. Why in the paper on optical limiting don’t we  see such cases?
Thank you and hoping for your insightful response.      
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The absorption coefficient of a material showing RSA will increase when the input optical fluence is increased. However, the processes underlying RSA (mostly excited state absorption in organic molecules) do not result in the absorption of more light than what is fed into it. Therefore, the scenario you envisage will not happen.
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Generally, FFT is used to obtain the spectrum in the frequency domain. What are the informations we can get from the FFT analysis of a spectrum?
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Aparna Sathya Murthy thank you so much, madam.
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In field sensors of fruit maturity are a logical precision fruiticulture step ... but there if the sensor is attached to the fruit there is a cost and sampling issue? On the operational side, if LED based, does change in ambient temperature effecting LED emission wavelength cause issues?
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Yes Pol, your kinetic analysis will be needed again. We have now temporally resolved much higher frequency of the data (every 10 minutes - maybe more data than we need), which are provided via mobile app to each lab.
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Prof. Mukherjee Sir, The attenuation coefficient /mm is ~1.96 for alumina based  thin OSL discs. Its possible to make OSL discs in large scale within +-5% sensitivity; batch production. 
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I am working on a project on optical detection of heavy metals in water. In the related published I could find some researchers have used nanoparticles of noble metals doped with some ligands instead of using the nanoparticle itself. What is the function of this ligand?
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I am using optical frequency comb for Absolute distance measurements. and interested in Factors that affect the accuracy of these measurements.
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I'm not using a camera to record the interference pattern, but i am just doing a simulation on optisystem, then i collect both the Input power and output pour to unwrap the phase, to get the value of the distance, This is my supervisor's request: "What you should focus on is the stochastic effects such as noises in the comb generation process and other places on the ranging accuracy". But i'm not specialized in this field so i couldn't get his meaning. can you give me so hints
Thanks  
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I need to prepare a closed gas cell (with input and output for gas) which will sit on a waveguide (without damaging it) for gas sensing measurement. IR light will focus from an optical fibre on one end of waveguide and has to be collected at the other end by an optical fibre and the waveguide has to be closed from top for gas flow.
If any one has some insights or any relevant reference please share........ 
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Dear Vishal, I understand now. I would try to work with flow through cuvette/cell. They are cheap and can find them with many different shapes and sizes. Maybe you can find one that is like a box with a lid. You could just use the "box" with the lid and cover the waveguide with it. If you don't find, there is always the way to open a normal cell, but you will need some specific facilities to do it (people who know glass milling or work with femto lasers).
To keep hermetic you can glue it to the wafer or the part that holds the waveguide. Torr Seal is a very effective glue for gas and vacuum applications and can be found through Thorlabs. Maybe a little pump will help to flow the gas inside the cell and then allow a good interaction with the waveguide. But input and output from the flow through cuvettes will be very helpful.
I hope this will help and good luck !
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For some years, optical E-field sensors (plus remote units) are commercially available; main advantage: the field is much less disturbed than by electrically conductive sensors.
We would like to measure UWB near-fields with field strengths from 50 mV/m to 500 V/m, frequency range from 100 kHz to at least 3 GHz, in the time-domain (the electric output signal of the remote unit should represent the temporal course of the field strength).  Since we are interested in the geometry of the field we would prefer monaxial sensors.
If you have any experience with such systems, could you please recommend certain manufacturers or models (or advice against certain types)? Many thanks in advance!
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Hello Joerg,
I'm a bit late - just now discovered your question...
Happens that a colleague of mine did her PhD on EMC measurements using EO sensors. She has an account on RG - including some applications:
Regards
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I'm trying to build a datalogger in our lab that will record PAR in canopy and sub canopies of cove forests, and came across a paper by Melbourne & Daniel (2004) "A low-cost sensor for measuring spatiotemporal variation of light intensity on the streambed.  Seems promising... but has anyone tried it outside of stream systems and under canopies?
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Licor sells an industry-standard silicon-based PAR sensor...
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Does anyone know the reason for poor sensitivity and commercial unavailability of Resonant Fiber Optic Gyro (RFOG)?
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I suppose the answer is that Resonant Fiber Optic Gyro (RFOG) just does not work well enough, despite many tricks attempted to do so.
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Just need the data from 850 nm to 1200 nm. Many thanks.
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I can send you the cross-sections of the Yb fibers we have at our company.
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What is the best way to cleave/cut/break sapphire fibres?
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You could try cleaving with a CO2 laser
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See above.
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I'm trying to size particles in the half micron and up range, with additional information about physical properties. 
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Looking for some wireless sensors (mechanical) that are used to detect quality changes in food.
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I have a relative who is a mechanical engineering student at MIT. Last summer he worked in the MIT Media Lab where his task was to develop a system that could remotely monitor the location of a dog in a room. I think his work could be modified to do what you need, and it would relatively inexpensive to develop.
Here is what he had to say:
"For my project, I was using a library for Python called OpenCV. I programmed in Python because someone else started the project in Python, but if you wanted to use the library I would recommend programming in C++ since there is more documentation for the library. It's an open source computer vision library that's capable of doing all sorts of things from object recognition and 3D mapping to image processing. I was using the image processing part of it to threshold each frame from a stationary camera with a known background to create a contour around the parts that changed in order to find the location of the dog. I used a standard webcam with a wide angle lens so that I had as wide a viewing angle as possible, but OpenCV can work with all sorts of different input devices, I think. It's a pretty powerful tool. As far as wireless, I'll bet that could be done with Bluetooth or a wireless card on an Arduino or something like that.
The main trick would just be figuring out how you could distinguish the information you're interested in. In my case, I took some frames of video and played with them in Photoshop to figure out what processes I would have to use in order to create a mask over the dog.
Sounds like you could certainly use OpenCV for that problem."
I hope this is helpful.
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Being transparent or creating an illusion? I may propose a device to transfer the images from one location to display at another location using the optical fibers. Furthermore, invisibility may be re-defined over different IR-visible and UV spectral ranges. What optical materials, nanostructures or hybrid mechanisms can be used to enhance the invisibility process?
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I believe the answer to your question is: no.
The reason is that when you try to do cloaking (eg. using metamaterials) all the techniques are narrowband. To get true invisibility you need your technique to work over a wide band. I there are no good wideband techniques.
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I have been working on metal-ion sensor based on conjugated polymer systems. It was observed that the fluorescence quenched using Cd and Fe, but the anomaly is the efficiency of conducting polymers to quench collectively (single metal can quench the entire polymer fluorescence as it is expected). Can anybody can help me regarding the Stern-Volmer plot for these kind of systems? How will it vary when considered for polymer based chemosensors from small molecule based sensors?
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I also got a S-V characteristic stright line plot for Co and Fe. bit confused to see how the collective quenching property is acting here.
Thanks Andy Monkman and for the reference also.
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What is the future of fiber optic chemical sensors? Is it an attractive field? what's your opinion?
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Hi Harri
At first I want to appreciate for your nice comments.
Optical circuits are very low power circuits and they are much faster than electrical circuits. Actually they work at light speed. But one of the biggest problems is their size. They have still micron or even millimeter size. Today integrating the opitcal circuits is one of the most important branches in optical technologies.