This work was made possible through the NSF Major Research Instrumentation program that established the multi-user laser facility for transient absorption (CHE-1428633).&#160;This material is based upon work supported by the National Science Foundation under Grant No. CHE-2313290.

Decoding Transient Absorption - Processing, Fitting, and Interpreting Data

<ol>
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M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrafast+transient+absorption+spectroscopy:+Principles+and+application+to+photosynthetic+systems.">Ultrafast transient absorption spectroscopy: Principles and application to photosynthetic systems.</a> Photosynth Res. 101, 105-118 (2009).</li><li>Ruckebusch, C., Sliwa, M., Pernot, P., de Juan, A., Tauler, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comprehensive+data+analysis+of+femtosecond+transient+absorption+spectra:+A+review.">Comprehensive data analysis of femtosecond transient absorption spectra: A review.</a> J Photochem Photobiol C Photochem Rev. 13 (1), 1-27 (2012).</li><li>Van Stokkum, I. H. M., Larsen, D. 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P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Femtosecond+spectroscopy+of+condensed+phases+with+chirped+supercontinuum+probing.">Femtosecond spectroscopy of condensed phases with chirped supercontinuum probing.</a> Phys Rev A - At Mol Opt Phys. 59 (3), 2369-2384 (1999).</li><li>Villa, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Broadly+tunable+mid-infrared+femtosecond+pulses+directly+generated+by+an+optical+parametric+amplifier.">Broadly tunable mid-infrared femtosecond pulses directly generated by an optical parametric amplifier.</a> OSA Contin. 4 (11), 2837-2844 (2021).</li><li>Brodeur, A., Chin, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrafast+white-light+continuum+generation+and+self-focusing+in+transparent+condensed+media.">Ultrafast white-light continuum generation and self-focusing in transparent condensed media.</a> J Opt Soc Am B. 16 (4), 637650 (1999).</li><li>Lang, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Photometrics+of+ultrafast+and+fast+broadband+electronic+transient+absorption+spectroscopy:+State+of+the+art.">Photometrics of ultrafast and fast broadband electronic transient absorption spectroscopy: State of the art.</a> Rev Sci Instrum. 89 (9), 093112 (2018).</li><li>Beckwith, J. S., Rumble, C. A., Vauthey, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Data+analysis+in+transient+electronic+spectroscopy+-+an+experimentalist's.">Data analysis in transient electronic spectroscopy - an experimentalist's.</a> Int Rev Phys Chem. 39 (2), 135-216 (2020).</li><li>Devos, O., Mouton, N., Sliwa, M., Ruckebusch, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Baseline+correction+methods+to+deal+with+artifacts+in+femtosecond+transient+absorption+spectroscopy.">Baseline correction methods to deal with artifacts in femtosecond transient absorption spectroscopy.</a> Anal Chim Acta. 705 (1-2), 64-71 (2011).</li><li>. Surface Xplorer from Ultrafastsystems Available from: <a target="_blank" href="https://ultrafast.systems/products/spectrometers-a">https://ultrafast.systems/products/spectrometers-a</a> (2023)</li><li>Gampp, H., Maeder, M., Meyer, C. J., Zuberbuhler, A. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Calculation+of+equilibrium+constants+from+multiwavelngth+spectroscopic+data-i+mathematical+considerations.">Calculation of equilibrium constants from multiwavelngth spectroscopic data-i mathematical considerations.</a> Talanta. 32 (2), 95-101 (1985).</li><li>Snellenburg, J. J., Laptenok, S., Seger, R., Mullen, K. M., van Stokkum, I. H. 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R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Principles of fluorescence spectroscopy, 3rd Ed. , 883-886 (2006).</li><li>Maciejewski, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transient+absorption+experimental+set-up+with+femtosecond+time+resolution.+Femto-+and+picosecond+study+of+DCM+molecule+in+cyclohexane+and+methanol+solution.">Transient absorption experimental set-up with femtosecond time resolution. Femto- and picosecond study of DCM molecule in cyclohexane and methanol solution.</a> J Mol Struct. 555 (1-3), 1-13 (2000).</li><li>Lorenc, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Artifacts+in+femtosecond+transient+absorption+spectroscopy.">Artifacts in femtosecond transient absorption spectroscopy.</a> Appl. Phys. B Lasers Opt. 74, 19-27 (2002).</li><li>. Transient absorption spectroscopy Available from: <a target="_blank" href="https://mediaspace.unm.edu/media/Physical+Inorganic+Tutorials+Transient+Absorption+Specctrscopy/1_t5pdqzgx">https://mediaspace.unm.edu/media/Physical+Inorganic+Tutorials+Transient+Absorption+Specctrscopy/1_t5pdqzgx</a> (2023)</li><li>Ma&#231;&#244;as, E. M. S., Mustalahti, S., Myllyperki&#246;, P., Kunttu, H., Pettersson, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Role+of+vibrational+dynamics+in+electronic+relaxation+of+Cr(acac)3.">Role of vibrational dynamics in electronic relaxation of Cr(acac)3.</a> J Phys Chem A. 119 (11), 2727-2734 (2015).</li><li>Brown, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Vibrational+relaxation+and+redistribution+dynamics+in+Ruthenium(II)+polypyridyl-based+charge-transfer+excited+states:+a+combined+ultrafast+electronic+and+infrared+absorption+study.">Vibrational relaxation and redistribution dynamics in Ruthenium(II) polypyridyl-based charge-transfer excited states: a combined ultrafast electronic and infrared absorption study.</a> J Phys Chem A. 122 (40), 7941-7953 (2018).</li><li>Vl&#269;ek, A., Kvapilov&#225;, H., Towrie, M., Z&#225;li&#353;, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electron-transfer+acceleration+investigated+by+time+resolved+infrared+spectroscopy.">Electron-transfer acceleration investigated by time resolved infrared spectroscopy.</a> Acc Chem Res. 48 (3), 868-876 (2015).</li><li>Horng, M. 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The authors have nothing to disclose.

Transient absorption (TA) spectroscopy is a time-resolved spectroscopic technique that monitors the evolution of photo-excited species through time-dependent changes to their absorption spectrum following excitation with a pulse of light. Because TA is an absorptive technique, spectroscopic signals that arise from states that undergo both radiative transitions (i.e., states that typically emit a photon) and non-radiative transitions (states that are typically non-fluorescent and undergo internal conversion, intersystem crossing or participate in photoreactions) can be identified and their evolution followed1,2. Depending upon the specifics of the excitation source and detection method, TA allows access to kinetics from femtoseconds to beyond microseconds and from the UV to the far IR, making it a versatile spectroscopic tool. Commercialization of TA spectrometers has advanced significantly over the past several decades, leading to more laboratories and facilities having access to this powerful technique2.
Modern TA systems are capable of producing large datasets with high energetic and temporal resolution. The datasets generally take the form of a 2D matrix of transmittance or absorbance difference values as a function of wavelength and time delay relative to the excitation pulse. This dataset can be viewed as a two-dimensional heat map or a three-dimensional topographical&#160;map. Interpretation of these data has become more complex as researchers strive to include the entire dataset when generating fits that best describe their system of interest3.
Although TA can cover a broad range of wavelengths and time scales, this protocol focuses on one of its most widely accessible forms4: broadband spectroscopy in the UV-visible region driven by a femtosecond pulsed laser. A schematic5,6 of such an instrument is provided in Figure 1. The experiment begins by taking a pulse from the laser and splitting it into two copies. One copy of the pulse, called the &#39;pump,&#39; is used to excite the sample. A device such as an optical parametric amplifier (OPA) is typically used to transform the pump pulse to the desired excitation wavelength5,7. The second copy of the pulse, called the &#39;probe,&#39; enters a mechanical delay stage, which can vary the time delay between the pump and probe pulses by varying the distance the pulse travels. The single-wavelength probe pulse is then transformed into a white-light continuum using a sapphire or calcium fluoride (CaF2) crystal8. The white-light pulse is passed through the sample, and its spectrum is measured using a broadband detector such as a charge-coupled device (CCD) camera. By measuring changes in the spectrum of the white-light pulse with and without the pump, changes in the sample&#39;s absorption spectrum induced by the pump, &#916;A(T), can be measured. Interested readers are directed toward this useful review9 for more information about the detection process.
In all forms of TA spectroscopy, the&#160;&#916;A(t) spectra are calculated by taking the difference between the ground-state absorption, Aprobe, and that of the excited state, Apump+probe, at a given time delay, t, between the two pulses2,5,9,10.
<img alt="Equation 1" src="/files/ftp_upload/65519/65519eq01.jpg" style="margin: auto;" />&#160; &#160; (1)
Note that Aprobe is equivalent to the sample steady-state absorption spectrum and is time-independent; the experiment&#39;s time resolution arises from the delay between the pump and probe captured in Apump+probe(t). A simulation of these data is shown in Figure 2A.
In contrast to steady-state absorption spectra, TA spectra can have both positive and negative features due to the difference taken in Equation 1. Positive features are the result of new absorbing species created by the pump pulse and can represent excited chromophore states, triplet states, geometric rearrangements, solvation effects, or excited-state photoproducts3. General guidelines for identifying these features and assigning them to chemical species will be presented in the Discussion. Negative features can arise from either the ground-state bleach (GSB) or stimulated emission (SE) (Figure 2B). The GSB is due to the loss of ground-state population following absorption of the pump pulse. Molecules promoted to the excited state no longer absorb in the same region as their ground state; therefore, less of the probe pulse is absorbed, and the difference in Equation 1 can be negative in that region. The GSB is characterized by having the same spectral shape as that of the ground-state absorption but with an opposite sign. SE signals result from emission from an excited-state species stimulated by the probe pulse3. Emission from these species results in more light reaching the detector, which is equivalent to having less absorption at those wavelengths. The SE signal will have a similar spectral shape as the spontaneous emission spectrum of the species, but with a negative sign and a different frequency weighting10.
In addition to information about excited-state species, TA spectra can contain a number of artifacts and extraneous features that can distort the underlying dynamics and obscure the assignment of absorption bands11. Improper treatment of these artifacts in the data preparation and analysis can lead to the application of inappropriate photophysical models to the data and, consequently, to misleading conclusions11. Therefore, the first part of this protocol focuses on how to properly process TA datasets after they are collected. The goal of this section is to provide researchers new to TA with a set of guidelines that will help develop an intuition and appreciation for the rigorous preparation and processing of their data.
After a dataset is processed, a plethora of tools and models are available for fitting and interpreting the spectra with various levels of complexity and rigor10. The goal of the second section of this protocol is to prepare the reader to apply single-wavelength fitting and global analysis to data and to provide guidance as to when these models are appropriate for describing their data. Commercial software is now readily available for preparing and treating TA data, such as Surface Xplorer12,13 from Ultrafast systems (free to download and use, see Table of Materials). Other free alternatives have been released by academic researchers, such as Glotaran14. Glotaran is a free software program developed for global and target analysis of time-resolved spectroscopy and microscopy data. It serves as a graphical user interface (GUI) for the R-package TIMP14. Additionally, users can use programming languages like Python to write their own codes that carry out the analysis. Each of these fitting software and programming solutions have&#160;positive features that make them important contributions. For the purpose of this study, we can present only one software for the visual component of this activity. An in-depth discussion of each fitting software is beyond the scope of this article.
This article provides a step-by-step procedure for (1) processing TA data, (2) fitting TA data using single-wavelength kinetics and global analysis, and (3) extracting data and fitting it to other models. A set of representative TA data is included for the reader to use as practice (Supplementary File 1 and Supplementary File 2). The data is&#160;a measurement of a 165 &#181;M sample of 1, 4-bis(5-phenyloxazole-2-yl)benzene (POPOP) in ethanol excited at 330 nm and collected over a range of &#8722;5 ps to 5.5 ns. Additionally, a &#34;blank&#34; sample containing ethanol only and no sample was collected under the same experimental conditions over a range of &#8722;5 ps to 5 ps, which is used in preparing the data for fitting (step 1). Spectra were collected using an ultrafast transient absorption spectrometer.&#160;The sample was contained in a 2-mm pathlength cuvette and subjected to constant stirring. The processing and fitting procedure described is based on the Surface Xplorer software that fits data in the *.ufs format, and that will herein be called the &#34;fitting program&#34;. Programs for converting datasets in other formats to *.ufs files are available15. Although the details of this protocol are specific to Surface Xplorer, the steps that follow are generalizable to any software package, commercial or home-built. Additionally, the results of data processing may be extracted and fit using these other software packages. A supporting information file (Supplementary File 3) provides additional advice on fitting.

<table><tbody><tr><td>EtOH 200% Proof</td><td>Decon Laboratories Inc</td><td>CAS 64-17-5</td><td>Solvent used to prepare Sample</td></tr><tr><td>Helios transient absorption spectrometer&amp;nbsp;</td><td>Ultrafast systems&amp;nbsp;</td><td>https://ultrafast.systems/products/spectrometers-accessories/helios/</td><td>Transient absorption spectrometer</td></tr><tr><td>POPOP&amp;nbsp; 1,4-Bis[2-(5-phenyloxazolyl)]benzene</td><td>Tokyo Chemical Industry</td><td>CAS 1806-34-4</td><td>Sample used for Examples</td></tr><tr><td>Surface Xplorer</td><td>Ultrafast systems</td><td>https://ultrafast.systems/products/spectrometers-accessories/surface-xplorer/</td><td>Fitting program</td></tr></tbody></table>

an introduction to processing, fitting, and interpreting transient absorption data

Transient absorption (TA) spectroscopy is a powerful time-resolved spectroscopic method used to track the evolution of excited-state processes through changes in the system&#39;s absorption spectrum. Early implementations of TA were confined to specialized laboratories, but the evolution of commercial turn-key systems has made the technique increasingly available to research groups across the world. Modern TA systems are capable of producing large datasets with high energetic and temporal resolution that are rich in photophysical information. However, processing, fitting, and interpreting TA spectra can be challenging due to the large number of excited-state features and instrumental artifacts. Many factors must be carefully considered when collecting, processing, and fitting TA data in order to reduce uncertainty over which model or set of fitting parameters best describes the data. The goal of data preparation and fitting is to reduce as many of these extraneous factors while preserving the data for analysis. In this method, beginners are provided with a protocol for processing and preparing TA data as well as a brief introduction to selected fitting procedures and models, specifically single wavelength fitting and global lifetime analysis. Commentary on a number of commonly encountered data preparation challenges and methods of addressing them is provided, followed by a discussion of the challenges and limitations of these simple fitting methods.

Preparation and analysis of a sample of 1,4-Bis[2-(5-phenyloxazolyl)]benzene, POPOP in ethanol was carried out following the procedure outlined above. Measurements were carried out using an ultrafast transient absorption spectrometer, as described in Figure 1, with fluid solutions in 2-mm cuvettes using an adjustable cuvette holder and a magnetic stirrer to ensure mixing. Samples were measured in ambient conditions with no additional controls for temperature or atmosphere. The optical window of 340 nm to 680 nm was generated using a calcium fluoride crystal. Two hundred fifty (250) time points were collected between &#8722;5 ps to ~5500 ps, and three scans were averaged to generate the final dataset, Figure 3. The POPOP data was prepared as described in the protocol. An example of sub-optimal chirp correction is shown in Supplementary Figure 16. Single-wavelength kinetic fitting was performed on POPOP, selecting 632 nm as the wavelength of interest. Additionally, global analysis was carried out on POPOP as described in the protocol.
Single-wavelength kinetic fitting of POPOP at 632 nm produced two lifetimes. These lifetimes were allowed to vary and no further adjustments were made. The final parameters obtained were as follows: t0 = &#8722;0.1176 ps, IRF = 0.436 ps, A1 = 0.0956, t1 = 1.614 ps, A2 = 0.0646, t2 = 522.2 ps (Figure 4). These results are in good agreement with global analysis carried out subsequently and reported emission lifetime values for POPOP (&#964; = 1.35 ns)17. An example of single-wavelength&#160;fitting with too few lifetime components is shown and discussed in Supplementary Figure 16.
Global analysis fitting on POPOP was performed after selecting 15 principal components (PCs) when performing SVD. Two lifetimes were selected after fitting, no parameters were fixed. The final parameters obtained from fitting were as follows: t0 = &#8722;0.1586 ps, tp (IRF) = 0.4408 ps, t1 = 1459 ps, t2 = 267.5 ps. The decay-associated difference spectra are displayed in Figure 5. Results were in good agreement with those from single kinetic fitting at 632 nm and lifetime values for POPOP17. Two examples of sub-optimal global analysis are shown and discussed in Supplementary Figure 16.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65519/65519fig01.jpg" /> 
Figure 1: Schematic representation of the femtosecond broadband transient absorption instrument described in this protocol. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/65519fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65519/65519fig02.jpg" /> 
Figure 2: Simulation of TAS data and contributions to TAS signal. (A) Gaussian curves simulating a ground-state absorption spectrum (blue dotted line) and an excited-state spectrum (red dotted line, red-shifted from the ground-state spectrum). The difference spectra of these two spectra (purple, solid line) is the difference spectrum as viewed in TA. The differences between the ground- and excited-state spectra have been exaggerated for illustrative purposes. (B) A representative TA difference spectrum of POPOP at 1.04 ps after excitation at 330 nm. The dotted lines show ground-state absorbance and steady-state emission of POPOP. Highlighted regions show common TA features, ground-state bleach (GSB), stimulated emission (SE), and excited-state absorbance (ESA) observed within this data. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/65519fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/65519/65519fig03.jpg" /> 
Figure 3: Prepared data for POPOP that result from the application of step 1 - Preparation of data. The data are shown as the corrected heat map and representative spectra. These results demonstrate how the data should look after the corrections have been applied and one is ready to apply a fit to the dataset. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/65519fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/65519/65519fig04.jpg" /> 
Figure 4: Results of single wavelength fitting of POPOP at 632 nm after application of step 2.3 - Single wavelength fitting. The figure shows (top section) the lifetimes obtained in a table format, (middle section) the data (blue dots) and the fit to the data (red fit line), and (bottom section) the residual plot. Note that under the &#34;current fit&#34; section, the amplitudes (A) are shown as the &#916;A values from the data that represent the contribution of that specific lifetime component at t0. However, when the current fit is saved and appears in the &#34;Fit Coefficients&#34; Table, the default setting is to show the normalized amplitudes. This setting can be changed by unchecking the box next to the &#34;Fit Coefficients&#34; label &#34;Normalized&#34;. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/65519fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/65519/65519fig05v2.jpg" /> 
Figure 5: Results of global analysis fitting of POPOP obtained after step 2.4 fitting. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/65519fig05largev2.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/65519/65519fig06.jpg" /> 
Figure 6: Example of stimulated Raman scattering observed in experimental TA data. In this dataset (not the POPOP data shown in the tutorial), the sample was excited at 550 nm (indicated by the dotted line). Raman scattering is seen around time zero and generally appears both to the blue (anti-Stokes Raman scattering) and to the red (Stokes Raman scattering) of pump excitation wavelength. Stimulated Raman scattering is short-lived, typically only around ~200 fs, because it occurs as the result of the probe beam interacting with the sample at the same time as the pump beam, thereby stimulating the Raman process. However, the feature cannot be avoided and should be removed with cropping. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/65519fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary Figure 1: Main menu when data is initially loaded. Generally, in this fitting software there will be option&#160;boxes that appear in the lower right corner of a window when the window is moused over. These boxes allow for alteration to the cursor interaction with the window, either moving selections, zooming, or panning the selected windows. There are also options for adjusting the precision of both the x-axis and y-axis scales for the window as well as switching the display from linear to logarithmic. The axes can also be locked or unlocked. While locked, an axis will remain at the zoom level or range of values specified; when unlocked, the range will switch to contain the full set of data. Other options allow for adjusting the display of numbers and the coloring of grids if present. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S1.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 2: Surface menu to carry out scattered light subtraction. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S2.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 3: Subtract scattered light screen - setting the spectra to average. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S3.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 4: Setting cropping range. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S4.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 5: Cropping dataset. Cropped data will be removed permanently. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S5.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 6: Fit solvent response window and example of solvent response fit (in red line) to the data (blue dots). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S6.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 7: Chirp correction window with &#34;blank&#34; sample data. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S7.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 8: Chirp correction shown along with the dataset. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S8.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 9: Single Kinetic Fit window. Additionally, a slider at the top allows the user to select the wavelength at which to perform the fit. Selecting an appropriate wavelength requires knowledge of the spectroscopy of the system to identify where processes of interest occur. Examples include charge-transfer products, triplet formation, or photoproduct formation, the spectral features of which are known to correlate with specific wavelengths. These specific wavelengths can be fit in order to obtain the lifetimes of those specific events. Additionally, a selection of wavelengths can be used in order to provide validation to a selected global fit model. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S9.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 10: Setting Single Kinetic Fit parameters. Individual fit parameters can be fixed or altered by hand if desired to fine tune the fit and minimize the standard deviation of the residual. Note: Parameters can be easily adjusted by clicking on the value in the box and then adjusting using a slider or manually typing in a value. The displayed fitting will be adjusted in real-time as values are changed. When an acceptable fit is achieved, the fit can be exported by right-clicking on the fit screen, which allows exporting the data to the clipboard for pasting into a desired program or as a picture for rapid viewing. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S10.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 11: Constraining and fixing values of Single Kinetic Fit parameters can be done if one or more parameters are well-known. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S11.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 12: Single Value Decomposition window with Principal Components showing how the trace and components will look when enough principal components are added. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S12.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 13: Global Fit window before global analysis fit is generated. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S13.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 14: Global Fit window showing the results of the global analysis fitting. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S14.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 15: File Menu for saving and exporting files. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S15.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 16: Examples of sub-optimal chirp correction and fitting. (A) demonstrates a poor single kinetic fit. The type of structured residual shown in panel A typically indicates that an additional lifetime is required to fit the data. Notice that the residual dips below zero at shorter times and is raised above the zero line at longer lifetimes. (B) demonstrates a correct chirp correction using the preview button, in which features are straightened and no curvature is present in the data. (C) demonstrates an incorrect chirp correction in which there is noticeable curvature present in the blue portion of the spectrum, indicating that the chirp function is overcorrecting in this region. (D) displays a poor global lifetime analysis fit in which overfitting (including too many parameters) has resulted in &#34;symmetrical&#34; DADS (that look like mirror images of each other across the x-axis) of similar lifetime ranges that essentially cancel each other out. When these features are observed, the fit should not be used. (E) displays a poor global fit in which too many parameters have resulted in a very short lifetime with a very large amplitude. The issue present in (E) may also appear if artifacts around time zero are not properly corrected and the fitting becomes focused on minimizing the residual by overemphasizing the very short lifetime (one that is not physically meaningful). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_Figures_S16.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 17: Example of TAS data with Raman scattering. Scattering is present around time zero, and coincides with the pump excitation wavelength. Scattering consists of a series of sharp peaks with a very intense positive peak blue of the pump excitation&#160;and a negative peak red of the pump excitation. This feature cannot be prevented reasonably and should be cropped out of the data to avoid interfering with the fitting results. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Jove_SI_FIgures_S17.pdf" target="_blank">Please click here to download this File.</a>
Supplementary File 1: File that contains the dataset for this tutorial (POPOP data_POPOP-inEtOH.ufs). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/POPOP data_POPOP-inEtOH.zip" target="_blank">Please click here to download this File.</a>
Supplementary File 2: File that contains blank dataset for this tutorial (POPOP data_BLANK.ufs). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/POPOP data_BLANK.zip" target="_blank">Please click here to download this File.</a>
Supplementary File 3: Supporting Information files containing additional comments on fitting solvent response, correcting for scatting, and subtracting surfaces. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65519/Supplementary File 3.zip" target="_blank">Please click here to download this File.</a>

Watch this Scientific Journal Video about Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research at JoVE.com

Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research

This protocol is a beginner's entryway into processing, fitting, and interpreting transient absorption spectra. The focus of this protocol is the preparation of datasets, and fitting using both single wavelength kinetics and global lifetime analysis. Challenges associated with transient absorption data and its fitting are discussed.

An Introduction to Processing, Fitting, and Interpreting Transient Absorption Data

Transient absorption (TA) spectroscopy is a powerful time-resolved spectroscopic method used to track the evolution of excited-state processes through ...

an-introduction-to-processing-fitting-interpreting-transient

Research

JoVE Journal

Chemistry

7.7K Views.  Lehigh University. This protocol is a beginner's entryway into processing, fitting, and interpreting transient absorption spectra. The focus of this protocol is the preparation of datasets, and fitting using both single wavelength kinetics and global lifetime analysis. Challenges associated with transient absorption data and its fitting are discussed. 

Video: Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research

Real-time Monitoring of Reactions Performed Using Continuous-flow Processing: The Preparation of 3-Acetylcoumarin as an Example

By using inline monitoring, it is possible to optimize reactions performed using continuous-flow processing in a simple and rapid way. It is also possible to ensure consistent product quality over time using this technique. We here show how to interface a commercially available flow unit with a Raman spectrometer. The Raman flow cell is placed after the back-pressure regulator, meaning that it can be operated at atmospheric pressure. In addition, the fact that the product stream passes through a length of tubing before entering the flow cell means that the material is at RT. It is important that the spectra are acquired under isothermal conditions since Raman signal intensity is temperature dependent. Having assembled the apparatus, we then show how to monitor a chemical reaction, the piperidine-catalyzed synthesis of 3-acetylcoumarin from salicylaldehyde and ethyl acetoacetate being used as an example. The reaction can be performed over a range of flow rates and temperatures, the in-situ monitoring tool being used to optimize conditions simply and easily.

Real-time monitoring allows for fast optimization of reactions performed using continuous-flow processing. Here the preparation of 3-acetylcoumarin is used as an example. The apparatus for performing in-situ Raman monitoring is described, as are the steps required to optimize the reaction.

By using inline monitoring, it is possible to optimize reactions performed using continuous-flow processing in a simple and rapid way. It is also possible ...

Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy

Monitoring the dynamics of protonation and protein backbone conformation changes during the function of a protein is an essential step towards understanding its mechanism. Protonation and conformational changes affect the vibration pattern of amino acid side chains and of the peptide bond, respectively, both of which can be probed by infrared (IR) difference spectroscopy. For proteins whose function can be repetitively and reproducibly triggered by light, it is possible to obtain infrared difference spectra with (sub)microsecond resolution over a broad spectral range using the step-scan Fourier transform infrared technique. With ~102-103 repetitions of the photoreaction, the minimum number to complete a scan at reasonable spectral resolution and bandwidth, the noise level in the absorption difference spectra can be as low as ~10-4, sufficient to follow the kinetics of protonation changes from a single amino acid. Lower noise levels can be accomplished by more data averaging and/or mathematical processing. The amount of protein required for optimal results is between 5-100 &#181;g, depending on the sampling technique used. Regarding additional requirements, the protein needs to be first concentrated in a low ionic strength buffer and then dried to form a film. The protein film is hydrated prior to the experiment, either with little droplets of water or under controlled atmospheric humidity. The attained hydration level (g of water / g of protein) is gauged from an IR absorption spectrum. To showcase the technique, we studied the photocycle of the light-driven proton-pump bacteriorhodopsin in its native purple membrane environment, and of the light-gated ion channel channelrhodopsin-2 solubilized in detergent.

Key steps of protein function, in particular backbone conformational changes and proton transfer reactions, often take place in the microsecond to millisecond time scale. These dynamical processes can be studied by time-resolved step-scan Fourier-transform infrared spectroscopy, in particular for proteins whose function is triggered by light.

Monitoring the dynamics of protonation and protein backbone conformation changes during the function of a protein is an essential step towards ...

Engineering

Supercritical Nitrogen Processing for the Purification of Reactive Porous Materials

Supercritical fluid extraction and drying methods are well established in numerous applications for the synthesis and processing of porous materials. Herein, nitrogen is presented as a novel supercritical drying fluid for specialized applications such as in the processing of reactive porous materials, where carbon dioxide and other fluids are not appropriate due to their higher chemical reactivity. Nitrogen exhibits similar physical properties in the near-critical region of its phase diagram as compared to carbon dioxide: a widely tunable density up to ~1 g ml-1, modest critical pressure (3.4 MPa), and small molecular diameter of ~3.6 &#197;. The key to achieving a high solvation power of nitrogen is to apply a processing temperature in the range of 80-150 K, where the density of nitrogen is an order of magnitude higher than at similar pressures near ambient temperature. The detailed solvation properties of nitrogen, and especially its selectivity, across a wide range of common target species of extraction still require further investigation. Herein we describe a protocol for the supercritical nitrogen processing of porous magnesium borohydride.

Nitrogen is an effective supercritical fluid for extraction or drying processes due to its small molecular size, high density in the near-liquid supercritical regime, and chemical inertness. We present a supercritical nitrogen drying protocol for the purification treatment of reactive, porous materials.

Supercritical fluid extraction and drying methods are well established in numerous applications for the synthesis and processing of porous materials. ...

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Proton Transfer Reaction (PTR), combined with a Time-of-Flight (ToF) Mass Spectrometer (MS) is an analytical approach based on chemical ionization that belongs to the Direct-Injection Mass Spectrometric (DIMS) technologies. These techniques allow the rapid determination of volatile organic compounds (VOCs), assuring high sensitivity and accuracy. In general, PTR-MS requires neither sample preparation nor sample destruction, allowing real time and non-invasive analysis of samples. PTR-MS are exploited in many fields, from environmental and atmospheric chemistry to medical and biological sciences. More recently, we developed a methodology based on coupling PTR-ToF-MS with an automated sampler and tailored data analysis tools, to increase the degree of automation and, consequently, to enhance the potential of the technique. This approach allowed us to monitor bioprocesses (e.g. enzymatic oxidation, alcoholic fermentation), to screen large sample sets (e.g. different origins, entire germoplasms) and to analyze several experimental modes (e.g. different concentrations of a given ingredient, different intensities of a specific technological parameter) in terms of VOC content. Here, we report the experimental protocols exemplifying different possible applications of our methodology: i.e. the detection of VOCs released during lactic acid fermentation of yogurt (on-line bioprocess monitoring), the monitoring of VOCs associated with different apple cultivars (large-scale screening), and the in vivo study of retronasal VOC release during coffee drinking (nosespace analysis).

Proton Transfer Reaction Time of Flight Mass Spectrometry allows high-sensitivity, rapid and non-invasive analysis of volatile organic compounds. To demonstrate its potential, we give three examples: lactic acid fermentation of yogurt (on-line bioprocess monitoring), different apple genotypes (large-scale screening), and retronasal space after drinking coffee (nosespace analysis).

Proton Transfer Reaction (PTR), combined with a Time-of-Flight (ToF) Mass Spectrometer (MS) is an analytical approach based on chemical ionization that ...

Facet-to-facet Linking of Shape-anisotropic Colloidal Cadmium Chalcogenide Nanostructures

Here, we describe a protocol that allows for shape-anisotropic cadmium chalcogenide nanocrystals (NCs), such as nanorods (NRs) and tetrapods (TPs), to be covalently and site-specifically linked via their end facets, resulting in polymer-like linear or branched chains. The linking procedure begins with a cation-exchange process in which the end facets of the cadmium chalcogenide NCs are first converted to silver chalcogenide. This is followed by the selective removal of ligands at their surface. This results in cadmium chalcogenide NCs with highly reactive silver chalcogenide end facets that spontaneously fuse upon contact with each other, thereby establishing an interparticle facet-to-facet attachment. Through the judicious choice of precursor concentrations, an extensive network of linked NCs can be produced. Structural characterization of the linked NCs is carried out via low- and high-resolution transmission electron microscopy (TEM), as well as energy-dispersive X-ray spectroscopy, which confirm the presence of silver chalcogenide domains between chains of cadmium chalcogenide NCs.

A protocol detailing how shape-anisotropic colloidal cadmium chalcogenide nanocrystals can be covalently linked via their end facets is presented here.

Here, we describe a protocol that allows for shape-anisotropic cadmium chalcogenide nanocrystals (NCs), such as nanorods (NRs) and tetrapods (TPs), to be ...

Quantifying X-Ray Fluorescence Data Using MAPS

The quantification of X-ray fluorescence (XRF) microscopy maps by fitting the raw spectra to a known standard is crucial for evaluating chemical composition and elemental distribution within a material. Synchrotron-based XRF has become an integral characterization technique for a variety of research topics, particularly due to its non-destructive nature and its high sensitivity. Today, synchrotrons can acquire fluorescence data at spatial resolutions well below a micron, allowing for the evaluation of compositional variations at the nanoscale. Through proper quantification, it is then possible to obtain an in-depth, high-resolution understanding of elemental segregation, stoichiometric relationships, and clustering behavior.
This article explains how to use the MAPS fitting software developed by Argonne National Laboratory for the quantification of full 2-D XRF maps. We use as an example results from a Cu(In,Ga)Se2 solar cell, taken at the Advanced Photon Source beamline 2-ID-D at Argonne National Laboratory. We show the standard procedure for fitting raw data, demonstrate how to evaluate the quality of a fit and present the typical outputs generated by the program. In addition, we discuss in this manuscript certain software limitations and offer suggestions for how to further correct the data to be numerically accurate and representative of spatially resolved, elemental concentrations.

Here, we demonstrate the use of the X-ray fluorescence fitting software, MAPS, created by Argonne National Laboratory for the quantification of fluorescence microscopy data. The quantified data that results is useful for understanding the elemental distribution and stoichiometric ratios within a sample of interest.

The quantification of X-ray fluorescence (XRF) microscopy maps by fitting the raw spectra to a known standard is crucial for evaluating chemical ...

Electrochemical Impedance Spectroscopy as a Tool for Electrochemical Rate Constant Estimation

Electrochemical impedance spectroscopy (EIS) was used for advanced characterization of organic electroactive compounds along with cyclic voltammetry (CV). In the case of fast reversible electrochemical processes, current is predominantly affected by the rate of diffusion, which is the slowest and limiting stage. EIS is a powerful technique that allows separate analysis of stages of charge transfer that have different AC frequency response. The capability of the method was used to extract the value of charge transfer resistance, which characterizes the rate of charge exchange on the electrode-solution interface. The application of this technique is broad, from biochemistry up to organic electronics. In this work, we are presenting the method of analysis of organic compounds for optoelectronic applications.

Electrochemical impedance spectroscopy (EIS) of species that undergo reversible oxidation or reduction in solution was used for determination of rate constants of oxidation or reduction.

Electrochemical impedance spectroscopy (EIS) was used for advanced characterization of organic electroactive compounds along with cyclic voltammetry (CV). ...

Time-resolved Photophysical Characterization of Triplet-harvesting Organic Compounds at an Oxygen-free Environment Using an iCCD Camera

Here, we present a sensible method of the acquisition and analysis of time-resolved photoluminescence using an ultrafast iCCD camera. This system enables the acquisition of photoluminescence spectra covering the time regime from nanoseconds up to 0.1 s. This enables us to follow the changes in the intensity (decay) and emission of the spectra over time. Using this method, it is possible to study diverse photophysical phenomena, such as the emission of phosphorescence, and the contributions of prompt and delayed fluorescence in molecules showing thermally activated delayed fluorescence (TADF). Remarkably, all spectra and decays are obtained in a single experiment. This can be done for solids (thin film, powder, crystal) and liquid samples, where the only limitations are the spectral sensitivity of the camera and the excitation wavelength (532 nm, 355 nm, 337 nm, and 266 nm). This technique is, thus, very important when investigating the excited state dynamics in organic emitters for their application in organic light-emitting diodes and other areas where triplet harvesting is of paramount importance. Since triplet states are strongly quenched by oxygen, emitters with efficient TADF luminescence, or those showing room temperature phosphorescence (RTP), must be correctly prepared in order to remove any dissolved oxygen from solutions and films. Otherwise, no long-lived emission will be observed. The method of degassing solid samples as presented in this work is basic and simple, but the degassing of liquid samples creates additional difficulties and is particularly interesting. A method of minimizing solvent loss and changing the sample concentration, while still enabling to remove oxygen in a very efficient and a repeatable manner, is presented in this work.

Here, we present a method of the spectroscopic characterization of organic molecules by means of time-resolved photoluminescence spectroscopy on the nanosecond-to-millisecond timescale in oxygen-free conditions. Methods to efficiently remove oxygen from the samples and, thus, limit luminescence quenching are also described.

Here, we present a sensible method of the acquisition and analysis of time-resolved photoluminescence using an ultrafast iCCD camera. This system enables ...

A Technical Guide for Performing Spectroscopic Measurements on Metal-Organic Frameworks

Metal-organic frameworks (MOFs) offer a unique platform to understand light-driven processes in solid-state materials, given their high structural tunability. However, the progression of MOF-based photochemistry has been hindered by the difficulty in spectrally characterizing these materials. Given that MOFs are typically larger than 100 nm in size, they are prone to excessive light scatter, thereby rendering data from valuable analytical tools like transient absorption and emission spectroscopy nearly uninterpretable. To gain meaningful insights of MOF-based photo-chemical and physical processes, special consideration must be taken toward properly preparing MOFs for spectroscopic measurements, as well as the experimental setups that garner higher quality data. With these considerations in mind, the present guide provides a general approach and set of guidelines for the spectroscopic investigation of MOFs. The guide addresses the following key topics: (1) sample preparation methods, (2) spectroscopic techniques/measurements with MOFs, (3) experimental setups, (3) control experiments, and (4) post-run stability characterization. With appropriate sample preparation and experimental approaches, pioneering advancements toward the fundamental understanding of light-MOF interactions are significantly more attainable.

Here, we use a polymer stabilizer to prepare metal-organic framework (MOF) suspensions that exhibit markedly decreased scatter in their ground-state and transient absorption spectra. With these MOF suspensions, the protocol provides various guidelines to characterize the MOFs spectroscopically to yield interpretable data.

Metal-organic frameworks (MOFs) offer a unique platform to understand light-driven processes in solid-state materials, given their high structural ...

Optimizing VIS-SWIR Spectroscopy for Biological Molecules

Characterization of Biological Absorption Spectra Spanning the Visible to the Short-Wave Infrared

For noninvasive light-based physiological monitoring, optimal wavelengths of individual tissue components can be identified using absorption spectroscopy. However, because of the lack of sensitivity of hardware at longer wavelengths, absorption spectroscopy has typically been applied for wavelengths in the visible (VIS) and near-infrared (NIR) range from 400 to 1,000 nm. Hardware advancements in the short-wave infrared (SWIR) range have enabled investigators to explore wavelengths in the ~1,000 nm to 3,000 nm range in which fall characteristic absorption peaks for lipid, protein, and water. These molecules are difficult to visualize in the VIS-NIR and can provide label-free sources of biological contrast. Furthermore, lower SWIR absorption has been observed for melanin, the primary chromophore responsible for skin pigmentation. In vivo&#160;optical devices like clinically standard pulse oximeters have been found to have reduced accuracy in people with darkly pigmented skin, possibly because of the stronger melanin absorption in the VIS range. Thus, error associated with skin pigmentation could be reduced by using devices operating in the SWIR. Optical instrument design is facilitated by the understanding of the absorption properties of core tissue components from the VIS to the SWIR range. This article describes protocols and instrumentation for obtaining VIS-SWIR absorption spectra of common tissue absorbers: oxygenated hemoglobin, deoxygenated hemoglobin, melanin, water, and lipid.

Biological samples have distinct optical characteristics in the short-wave infrared (SWIR) compared to the visible (VIS) and near-infrared (NIR) wavelength ranges. However, recording pure SWIR absorption spectra is challenging and rarely conducted for biological molecules. This article presents a method to characterize the VIS-SWIR absorption spectra of biological absorbers.

For noninvasive light-based physiological monitoring, optimal wavelengths of individual tissue components can be identified using absorption spectroscopy. ...