data preparation for transient absorption spectra fitting

Decoding Transient Absorption - Processing, Fitting, and Interpreting Data

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.

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

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

We are a group of experimental photo chemists exploring how to use light to drive important chemical reactions and energy harvesting devices such as solar cells. We use a range of spectroscopy such as transient absorption spectroscopy, the data of which we use in this tutorial to monitor and quantify these dynamics. One of the current challenges is to monitor and quantify chemical dynamics and devices under more realistic conditions or what one would call operational conditions that truly represent how they would be implemented in real life.The advantage of this protocol is to provide a relatively easy entry point for beginners. We wanted to outline the basics of fitting and some of the common challenges in an approachable way for those new to this area. We will always keep using light as our inspiration.We hope to apply our expertise to understand how photo-activated devices function under real life operating conditions to help address environmental pollution challenges and to harness energy from the sun to benefit our society.

Data Preparation for Transient Absorption Spectra Fitting

data-preparation-for-transient-absorption-spectra-fitting

Research

JoVE Journal

Chemistry

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