This work was supported by grants from the Deutsche Forschungsgemeinschaft to J.H. (FOR-1279, SFB-1078, B3). We thank Tom Resler and Bj&#246;rk S&#252;ss for helpful comments.

1. General Aspects of Sample and Instrument Preparation
<ol>
	<li>Use a commercial FT-IR spectrometer equipped for time-resolved step-scan measurements. For best results place the FT-IR spectrometer on top of a vibration-decoupled table.</li>
	<li>Evacuate the optics compartment to a few mbar. Purge the sample compartment with dry air or nitrogen.</li>
	<li>Place an IR transparent material opaque to visible radiation in front of the MCT detector of the FT-IR spectrometer. This precaution is essential to prevent artifacts from the exciting laser pulse during step-scan experiments. Note: We use a germanium (Ge) window of 25 mm diameter. Its high refractive index causes undesirable intensity loses, largely avoided using a Ge filter with antireflecting coating.</li>
	<li>Cool down the MCT detector dewar with liquid nitrogen. Note: The use of photovoltaic MCT detectors is preferred over photoconductives because of their linear response and, thus, superior photometric accuracy and baseline reliability31,53.</li>
	<li>Pre-concentrate the sample used for the experiments to at least 2 mg protein/ml in a buffer of low (&#60;20 mM) ionic strength to prevent formation of salt crystals while drying the protein suspension to form a homogenous protein film. For samples that sediment, wash/concentrate them by applying ultracentrifugation (e.g., membrane proteins in a liposomes or in cell membrane patches). Use centricons of proper cutoff for proteins that do not sediment (e.g., detergent solubilized membrane proteins).</li>
	<li>For optimum results use: a) protein preparations as pure and active as possible; b) lipid/protein ratios &#8804; 3 in weight for proteins in cell membrane patches or reconstituted in liposomes; c) detergent/protein ratios &#8804; 1 in weight for detergent solubilized proteins. Avoid the use of detergents or lipids whose vibrational bands overlap with those of the protein (e.g., CHAPS).</li>
</ol>
2. Preparation of Attenuated Total Reflection Experiments on Bacteriorhodopsin
<ol>
	<li>Mount the ATR accessory into the sample compartment of the FT-IR spectrometer. Note: We use a ZnSe/diamond ATR with 5 active reflections. Avoid semiconductor materials such as germanium or silicon as internal reflection element (IRE) of the ATR accessory, as their optical properties are affected by the exciting visible laser.</li>
	<li>Measure a broad-range (approx. 4,000-800 cm-1) energy spectrum at 4 cm-1 resolution of the clean IRE surface by conventional rapid-scan FT-IR spectroscopy. Use this spectrum as a reference spectrum to compute absorption spectra at a later stage.</li>
	<li>Cover the IRE surface of the ATR with 20 &#956;l of the buffer used later to rehydrate the sample (e.g., 4 M NaCl and 100 mM NaPi at pH 7.4). Measure the IR absorption of the buffer.</li>
	<li>Remove the buffer, and rinse the IRE surface with water. Avoid touching the surface. Remove residual liquid from the IRE surface by an intense air flow.</li>
	<li>Spread ~3 &#956;l of bacteriorhodopsin (bR) in purple membranes (~6 mg protein/ml in deionized water) on top of the IRE surface (~0.2 cm2 area). Dry the protein suspension under a gentle stream of dry air until a film is attained.</li>
	<li>Measure the absorption spectrum of the dry film (see Figure 1).</li>
	<li>Gently add 20-40 &#956;l of a buffer of high ionic strength to rehydrate the dry film (e.g., 4 M NaCl and 100 mM NaPi at pH 7.4). Note: The high ionic strength prevents excessive swelling of the membrane film, allowing to retain as much protein as possible close to the probed surface (Figure 2).</li>
	<li>Cover the ATR holder with a lid to prevent water evaporation. Optionally, place a cover-jacket connected to a circulatory bath set to 25 &#176;C for temperature control. For proteins with long photocycles (&#62;seconds), temperature control might increase baseline stability.</li>
	<li>Measure an absorbance spectrum. Estimate the percentage of sample remaining near the surface after rehydration of the film by subtracting the absorption spectrum of the buffer (Figure 3).</li>
	<li>Confirm stabilization of the film swelling by recording absorption spectra at 5-20 min intervals after rehydration (Figure 4). This step is optional but recommended.</li>
</ol>
3. Performing Transmission Experiments on Detergent-solubilized Channelrhodopsin-2
<ol>
	<li>Add 10 &#956;l of ChR2 (~10 mg protein/ml) dissolved in 5 mM NaCl, 5 mM HEPES (pH 7.4) and decyl-maltoside (DM) at the center of a BaF2 window of 20 mm diameter. Spread it with the help of the micropipette tip to a 6-8 mm diameter (protein surface density of ~ 200 &#956;g/cm2).</li>
	<li>Form a film using a gentle flow of dry air. For best results ensure that the film is homogeneous and has a diameter roughly matching the size of the IR beam at the largest aperture.</li>
	<li>Hydrate the film by adding 3-5 &#956;l of a mixture of glycerol/water distributed in 3-5 drops around the dry film, and tightly close it with a second window using a flat silicone O-ring of &#8805;1 mm thickness. Note: The ratio of the glycerol/water mixture controls the relative humidity between the windows54. For hydroscopic samples use a 3/7 or 2/8 glycerol/water ratio (w/w). The glycerol/water drops should never be in direct contact with the protein film.</li>
	<li>Insert the BaF2 sandwiched windows in a holder. Prevent straight light from reaching the detector by covering the sample window with an IR opaque material, such as paper, with a hole matching the size of the hydrated film. Place the holder in the sample compartment.</li>
	<li>Control the temperature of the holder to 25 &#176;C by a thermostatic jacket connected to a temperature controlled circulatory bath.</li>
	<li>Measure an absorption spectrum. Ensure that the maximum absorption in the amide I region (~1,700-1,620 cm-1) is in the range of 0.6-1.0.</li>
	<li>Estimate the mass and molar ratio of protein/detergent/water from the absorption spectrum of the hydrated film (Figure 5) using reference extinction coefficient spectra for water, DM, and representative membrane proteins (Figure 6).</li>
	<li>Wait until the hydration level stabilizes before performing step-scan experiments (&#8805;1 hr).</li>
</ol>
4. Adjustment and Synchronization of the Exciting Laser
For experiments on bR use the second harmonic emission of a pulsed Nd:YAG laser (&#955;&#160;= 532 nm) to trigger the photocycle. For experiments involving ChR2, use an excitation of &#955;&#160;= 450 nm as provided by an optical parametric oscillator (OPO) driven by the third harmonic (&#955;&#160;= 355 nm) of a Nd:YAG laser. Ensure that the laser pulse is sufficiently short (~10 nsec) to minimize secondary photo-excitation. Note: The energy of the laser pulses should be as constant as possible. In our setup, the laser intensity fluctuates &#8804;10% around the mean value, as confirmed by measuring a reflex of the laser by a photodiode connected to a transient recorder and integrating the response (Figure 8).
<ol>
	<li>Couple the laser to the sample. Adjust the energy density of the laser at the sample to 2-3 mJ/cm2 per pulse using a power-meter.
	<ol>
		<li>For the ATR setup, use an optical fiber placed atop of the ATR lid.</li>
		<li>For transmission experiments, use mirrors to bring the laser to the sample and, if required, lenses to either collimate or diverge the laser beam to a diameter slightly above the sample film size.</li>
	</ol>
	</li>
	<li>Synchronize the laser pulse with data recording by the spectrometer. Use the Q-switch sync-out TTL pulse of the electronics of the Nd:YAG laser to trigger the spectrometer. Set the excitation rate of the Nd:YAG laser to 10 Hz for bR and 0.25 Hz for ChR2, respectively.</li>
	<li>Use a pulse delay generator (PDG) to control the laser excitation rate if the repetition rate of the Nd:YAG laser is not easily adjustable.
	<ol>
		<li>Connect the lamp sync-out of the Nd:YAG laser to the PDG external trigger input. The PDG provides a ~190 &#956;sec delayed TTL pulse output to the Q-switch sync-in input of the Nd:YAG laser to trigger the lasing. Gate the PDG to accept an external trigger only after certain period of time since the last accepted trigger (100 msec for bR or 4 sec for ChR2).</li>
	</ol>
	</li>
</ol>
5. Time-resolved Step-scan Preparations and Settings
<ol>
	<li>Place a low pass optical filter in the optical path. To perform time-resolved step-scan measurements in the 1,800-850 cm-1 spectral range, use a filter opaque above 1,950 cm-1 and with good transmission (&#62;50-80%) below 1,800 cm-1 (Figure 7).</li>
	<li>Change the detector from AC to DC-coupled mode. Note: After this adjustment the interferogram signal will no longer oscillate around zero but around a value known as the DC-level.</li>
	<li>Use the largest possible beam aperture of the spectrometer for higher photon flux and, thus, better signal-to-noise, but within the linearity limits of the detector.</li>
	<li>Bring the DC-level of the interferogram to zero and readjust the electronic gain to make better use of dynamic range of the analog digital converted (ADC). Achieve DC-level offset by applying a voltage bias to the signal provided by the pre-amplifier. Note: This option is included in modern FT-IR spectrometers. Otherwise, a home-made external device can be used instead, placed between the preamplifier and the ADC 38. Care is then needed to ensure that the electronics of such device are fast and linear.</li>
	<li>Start the step-scan menu of the FT-IR spectrometer. Set the target spectral bandwidth for the step-scan measurement to 1,975.3-0 cm-1. Adjust the spectral bandwidth to a fraction of the He-Ne laser wavenumber (1/8th in the present case), slightly exceeding the cutoff of the optical filter.</li>
	<li>Disable any high-pass electronic filter to prevent distortions of the kinetics at later times. A low-pass electronic filter can be beneficial when its cutoff frequency is in the order or above the sampling rate of the ADC (reduces noise aliasing).</li>
	<li>Set the spectral and phase resolution to 8 cm-1 and 64 cm-1, respectively. Set the interferogram acquisition mode to single-side forward. With these options one interferogram requires about 500 points.</li>
	<li>Set the sampling rate of the ADC to the highest available in the spectrometer (e.g., 160 kHz, or 6.25 &#956;sec). Set the &#8220;trigger for experiment&#8221; to &#8220;External&#8221;, i.e., the laser is the master. Set the number of linearly-spaced data points to be recorded: 7,000 for bR (up to 42 msec) and 20,000 for ChR2 (up to 125 msec). Note: Longer time-scales can be covered without overflowing the ADC memory using a quasi-logarithmically time-spaced external TTL pulses from a wave generator to trigger data acquisition 38, or by using two parallel transient recorders as substitutes of the internal ADC31,32.</li>
	<li>Save approximately 100 pre-trigger points as a reference for the dark state of the sample. Note: In the millisecond time-scale the data quality is often limited by fluctuations in the mobile mirror. Increasing the pre-trigger points above 100 is, therefore, not expected to significantly improve the data quality.</li>
	<li>Set the number of co-additions, i.e., number of averages of the photoreaction per mirror position. For bR, use 20 co-additions (20 min of measuring time at 10 Hz excitation rate). For ChR2 use 2 co-additions (70 min of measuring time at 0.25 Hz excitation rate)</li>
	<li>Repeat the experiment 10x&#160;for bR, and 35x&#160;on three different sample films for ChR2, to have finally ~200 co-additions per mirror position.</li>
</ol>
6. Data Processing
<ol>
	<li>Confirm the status of the sample by comparing the light-induced IR difference spectrum obtained from the first and the last measurement. Consider discarding any measurements where the intensity of the difference spectrum drops below 60% of the first measurement.</li>
	<li>Average the recorded interferograms.
	<ol>
		<li>Using the OPUS software from the FTIR spectrometer select the time-resolved interferograms to average and add them to the &#8220;Spectrum Calculator&#8221;.</li>
		<li>Click &#8220;=&#8221; to obtain the average of the interferograms. 
		Note: When the phase of the interferogram is constant during the measurement it is indifferent to average interferograms or single-channel spectra. A constant phase can be confirmed by computing and comparing the phase spectrum for the first and the last recorded interferogram.</li>
	</ol>
	</li>
	<li>Perform the Fourier transform of the averaged time-resolved interferograms to obtain averaged time-resolved single channel spectra.
	<ol>
		<li>Using the same software as in step 6.2.1, select the averaged time-resolved interferogram and click the icon for &#8220;interferogram to spectra&#8221;. Use the Mertz phase-correction method, a zero-filling factor of 2 (two digital points per instrumental resolution), and an apodization function (e.g., triangle, Blackmann-Harris 3-terms, etc.).</li>
		<li>Click the bottom &#8220;convert&#8221; to transform the time-resolved interferogram into time-resolved spectra.</li>
	</ol>
	</li>
	<li>Export the time-resolved single channel data as a &#8220;data point table&#8221; or a &#8220;matlab&#8221; file using the &#8220;save as&#8221; icon in the OPUS software. Continue the data processing in an external program.
	<ol>
		<li>Average the single channel spectra before the laser, and convert the time-resolved single channel data to time-resolved absorption difference spectra.</li>
		<li>Compute a vector for the expected noise standard deviation in the difference spectra as a function of wavenumber (Figure 12), using the noise standard deviation, &#949;, and mean, S0(&#957;), of the 100 single channel spectra preceding the laser: &#949;&#160;/ S0(&#957;). The value of &#949; is estimated subtracting consecutive single channel spectra and calculating the standard deviation corrected by &#8730;2.</li>
		<li>Remove spectral regions too noisy to be of use (e.g., above 1,825 cm-1 and below 850 cm-1).</li>
		<li>Perform a quasi-logarithmically averaging (e.g., 20 spectra/time decade). The appearance of the data will improve and the number of spectra will be reduced from ~104 to ~102 without any significant information lost (Figure 9).</li>
		<li>Increase four times the spectral density of points (to 1 point/cm-1) using Fourier interpolation (post zero-filling). 
		Note: We perform steps 6.4.1 to 6.4.4 in a home-made program running in MATLAB.</li>
	</ol>
	</li>
	<li>Process the obtained time-resolved spectra (Figure 10A) with singular value decomposition, SVD, (Figure 13). Accomplish data denoising by reconstructing the data with a limited number of significant SVD components (Figure 10B). Note: We perform SVD in MATLAB, using the built-in &#8220;svd&#8221; function.</li>
</ol>

The authors declare no competing financial interest.

One of the first aspects that needs consideration when performing time-resolved step-scan FT-IR experiments on a protein is the preparation of a sample in a suitable form for IR spectroscopy. The IR absorption from substances other than the protein of interest needs to be reduced, especially that from water. The most common approach is to evaporate the bulk water of the sample to form a film. The film can be rehydrated either by adding some droplets of an aqueous solution or by exposing the film to an atmosphere of controlled humidity. We have shown how in both cases it is possible to estimate the hydration level obtained by means of IR absorption spectroscopy (see Figure 3 and Figure 5). Although the obtained hydration levels might appear low compared to those in solution, they are actually close to those found in living cells70, making the study of hydrated films of proteins functionally relevant. Besides water, it is also important to know and to control the amount of lipid or detergent in the sample. Both should be kept low enough to have a reduced spectroscopic impact in the IR absorption, but high enough to preserve the integrity and functionality of the protein of interest.
Time-resolved step-scan spectroscopy is only straightforwardly applicable to proteins showing reversible reactions that can be triggered reproducibly by light (but see progress in coupling step-scan with rapid buffer exchange)71. In step-scan the reaction needs to be reproducible for at least ~500x, the minimum number to complete an interferogram covering the 1,800-850 cm-1 region at 8 cm-1 resolution. In practice, however, additional data averaging is generally required to push the noise level down. For 200 co-additions/mirror position (105 repetitions of the reaction) a 6.25 &#956;sec resolution absorbance difference spectrum can display a noise standard deviation between 2 x 10-5 and 2 x 10-4 for an ATR and between 5 x 10-6 and 3 x 10-5 for a transmission experiment (Figure 15). Thanks to its higher photon throughput, transmission allows for ~7 lower noise levels than ATR, a key aspect for successfully studying samples giving weak absorption changes such as ChR2. On the other hand, ATR requires 5 to 25 times less sample than a transmission experiment.
The application of time-resolved step-scan FT-IR spectroscopy is problematic for proteins displaying slow photocycles: recording an interferogram by step-scan can become unpractical long. Some solutions have been presented for dealing with such cases72,73, often based on using multiple exchangeable samples to speed up measurements at the cost of increased protein consumption and experimental complexity27,74. In some instances it is possible to circumvent this problem by exciting the sample before the photocycle is strictly completed. For ChR2, with a photocycle requiring after photo-excitation 60 sec for 99% recovery, the recovery at 4 sec is already of 80%48. With an excitation efficiency of 10% per laser pulse, 98% of ChR2 molecules are in the dark state 4 sec after photo-excitation, making possible to perform experiments at a laser repetition rate to 0.25 Hz.
Data processing is a final technical aspect required to attain the best possible results. Logarithmic averaging reduces noise and, also important, reduces the size of the data without distortions, a feature essential for posterior data analysis using singular value decomposition or global fitting. Logarithmic averaging is, however, not very successful in averaging out fluctuations in the time-traces caused by oscillations in the mobile mirror and other 1/f noise sources during the measurements (Figure 9). These fluctuations in the baseline can exceed the noise in the millisecond range and corrupt the quality of the data. Singular value decomposition takes advantage of the redundancy of the data to reduce the noise, and with some modifications57 it can reduce as well fluctuations in the baseline.
Finally, the harder and most time-consuming part of a time-resolved step-scan FT-IR experiment corresponds to the assignment of bands and to the spectral and kinetic interpretation of the data. For bacteriorhodopsin many of the bands appearing in the IR difference spectra have been assigned or interpreted thanks to the accumulated work of many researcher groups over decades. For a much less studied protein, such as channelrhodopsin-2, the above presented time-resolved IR experiments need to be accompanied by parallel experiments on site-directed mutants and combined with information from complementary techniques to reach a mechanistic interpretation48.

To fully elucidate how proteins perform their function, it is required to measure them as they work, i.e. along a reaction path that often involves a series of intermediates and extends several orders of time. Key steps of protein function often take place in the microsecond to millisecond time range1, in particular backbone conformational changes and proton transfers reactions in membrane proteins. X-ray crystallography, arguably the pillar of structural biology, provides static (time-averaged) electron densities from well-diffracting protein crystals, notoriously difficult to grow with membrane proteins2. A 3D atomic model can be built based on electron densities, although rarely including the location of hydrogen atoms. Remarkable progress in time-resolved X-ray crystallography, relying either on Laue diffraction3 or on femtosecond X-ray pulses4, adds the time dimension to the high structural information inherent to X-ray crystallography5. But setting aside technical and analytical challenges, the crystal lattice can impair backbone conformational changes and alter protein dynamics, an unavoidable shortcoming of methods based on protein crystals5. Consequently, dynamical aspects of proteins are still best covered by optical methods, as pioneered by flash photolysis6,7, although with the general drawback of limited structural insight.
Fourier transformed infrared spectroscopy (FT-IR) combines the temporal resolution of optical spectroscopies with a valuable sensitivity to protein structure, the last feature exploited in innumerable static structural and functional investigations on membrane proteins8-11. In particular, FT-IR difference spectroscopy has proven to be an ideal tool to study tiny spectral changes as a protein transits from one metastable state to another12-19.
Studies on protein dynamics, other than at the single molecule level20,21, require a triggering process for synchronization. A reaction is conveniently initiated fast and not invasively using light as trigger, as done in the study of proteins with cyclic photoreactions. A major challenge associated with time-resolved studies is the attainment of sufficient time resolution while maintaining good spectral resolution and appropriate signal-to-noise ratio. Also essential is to cover a sufficiently broad spectral and temporal range. Time-resolved step-scan FT-IR spectroscopy excels in all of these aspects22, with published examples covering spectral ranges as wide as 3,900-850 cm-1 and dynamics extending ~9 orders of time, with up to 3.5 cm-1 spectral and 30 nsec temporal resolution23-28.
Fourier-transform IR spectrometers show reduced noise and improved photometric accuracy over dispersive ones29. However, in the normal rapid-scan recording mode FT-IR spectrometers suffer from a time-resolution limited to &#8805;5-10 msec as a consequence of the minimum time the mobile mirror of the interferometer requires to complete a scan. With the step-scan technique, in contrast, the time dependence of the dynamic event is decoupled from the scan duration of the interferometer. Briefly, the mobile mirror moves in discrete steps rather than continuously scanning to complete a scan. At each of these steps the (mobile) mirror is held fixed and a transient is recorded. Thus, the time-resolution is limited by the rise time of the mercury-cadmium-telluride (MCT) detector, which is typically in the range of 10-100 nsec. In practice, the large dynamic range of the interferogram (containing an intense signal in the centerburst and small signals in the wings), requires for proper digitalization an analog/digital converter (ADC) with as many as 16-24 bits, leading to sampling rates not higher than ~200 kHz (5 &#181;sec)30. Nanosecond time-resolution can be accomplished by measuring only the changes in the interferogram, for which a 8-12 bit ADC is sufficient23,31-33. Technical aspects30,34,35 and applications36-38 of time-resolved step-scan have been discussed in detail elsewhere.
The purpose of the current contribution is to provide a protocol describing the practicalities of time-resolved step-scan FT-IR spectroscopy on photosensitive membrane proteins. Here, the performance of the technique is shown for two sampling methods: transmission and attenuated total reflection (ATR). The use of ATR allows working in the presence of excess water, which not only ensures full hydration conditions for the protein but also allows acute control of the sample pH and ionic strength49,50. Step-scan experiments are illustrated on two selected systems: bacteriorhodopsin and channelrhodopsin-2.
The light-driven proton pump bacteriorhodopsin (bR) has been the subject of numerous biophysical studies for over forty years39,40, making it the best-understood membrane protein so far. Among the numerous techniques applied to the study of bR functionality FT-IR spectroscopy has arguably exerted one of the largest impacts. Namely, FT-IR spectroscopy has been key to resolve the groups involved in proton transfer across the membrane as accounted elsewhere13,41,51.
Channelrhodopsin (ChR) is the first light-gated ion channel found in nature42,43. Light excitation of ChR leads to the transient opening of an ion channel. Its discovery settled the way for the development of optogenetics, where molecular processes are controlled by light44,45. ChR belongs, as bR, to the family of microbial rhodopsins but in contrast to bR, much less is known about its functional mechanism52. ChR2 combines its function as an ion channel with proton-pumping activity46,47. Recently, we applied time-resolved step-scan FT-IR spectroscopy to resolve intra-protein proton transfer reactions and the dynamics of protein backbone conformation changes in ChR2 48.

<table border="0" cellpadding="0" cellspacing="0" width="750">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Name of Material/ Equipment</td>
			<td style="width:248px;">Company</td>
			<td style="width:119px;">Catalog Number</td>
			<td style="width:167px;">Comments/Description</td>
		</tr>
		<tr height="37">
			<td height="37" style="height:37px;width:216px;">FT-IR spectrometer</td>
			<td style="width:248px;">Bruker</td>
			<td style="width:119px;">Vertex 80v</td>
			<td>Equipped with photovoltaic-MCT detector, an external global, and an oil-free pump. Firmware 2.3.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">BaF2 windows</td>
			<td style="width:248px;">korth Kristalle</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">diamond ATR accesory</td>
			<td style="width:248px;">Smiths detection</td>
			<td style="width:119px;"></td>
			<td>Nine-reflection DuraDisk</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">thermostatic bath</td>
			<td style="width:248px;">Julabo&#160;</td>
			<td style="width:119px;">F25</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">vibration decoupled table</td>
			<td style="width:248px;">OPTA</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Pulsed Nd:YAG laser with a second harmonic generator</td>
			<td style="width:248px;">Continuum electro-Optics</td>
			<td style="width:119px;">Minilite&#160;</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Optical parametric oscillator (OPO)</td>
			<td style="width:248px;">OPTA</td>
			<td style="width:119px;">BBO-355-VIS/IR S/N 1009</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Digital delay/pulse generator&#160;</td>
			<td style="width:248px;">Stanford Research Systems</td>
			<td style="width:119px;">DG535</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Pulsed Nd:YAG laser with a third harmonic generator</td>
			<td style="width:248px;">Spectra-Physics</td>
			<td style="width:119px;">Quanta-Ray</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Various optical mirrors and lenses</td>
			<td style="width:248px;">ThorLabs</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">OPUS 7.0&#160;</td>
			<td style="width:248px;">Bruker</td>
			<td style="width:119px;"></td>
			<td>Software to control Vertex 80v spectrometer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Matlab run time</td>
			<td style="width:248px;">Mathworks</td>
			<td style="width:119px;"></td>
			<td>Used to run home-made executable programs to preprocess the data</td>
		</tr>
	</tbody>
</table>

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.

Figure 1 shows an absorption spectrum of a dry film of bR deposited on the surface of the diamond internal reflection element used for ATR spectroscopy. Characteristic bands from vibrations of the peptide bond (amide A, amide I and amide II) are clearly distinguishable. The approximate thickness of the dry film can be estimated as ~1 &#956;m, considering the amount of added protein (18 &#956;g) and the surface of the ATR (~0.2 cm2), and taking the density of protein as ~1.4 g/cm3,58 and of lipids as 1.0 g/cm3,59 and a lipid/protein ratio of 1/3 (w/w) in purple membrane60.
The dry film was rehydrated with excess of 4 M NaCl, 100 mM NaPi at pH 7.4 (Figure 3). The hydration level and effective protein concentration in the volume probed by the evanescent wave can be deduced from the scaling factor needed to digitally remove absorption bands from water. The optimum scaling factor was 0.87, meaning that in this case the buffer occupies 87% and the sample 13% of the volume near the surface. Taking into account protein and lipid density and the lipid/protein ratio in purple membranes (see above), we can deduce an effective protein concentration of 125 mg/ml in the volume probed by the evanescent wave. We can deduce from the hydration level that, in this particular case, the sample film thickness expanded ~6 times upon rehydration, from ~1 to ~6 &#956;m. For a 45&#176; incident angle, typical for our and for most ATR arrangements, the penetration depth of the evanescent field (dp) for a hydrated protein film varies between 0.3 and 0.6 &#956;m in the 1,800-850 cm-1 interval 61. Because the evanescent field is almost insensitive to the sample located two times above dp 61, we infer that the amount of protein used in the ATR experiment could be in principle reduced 5x&#160;without any significant loss of signal.
When using buffers of lower ionic strength the film expands more, and the amount of protein in the volume probed by the evanescent field is reduced (Figure 2). The exact dependence between film swelling and the ionic strength of the buffer will depend, among other factors, on the nature of the lipids. For instance, a similar film swelling as obtained here for bR in purple membrane using 4 M NaCl was obtained for a membrane protein reconstituted in polar E. coli lipids using just 0.1 M NaCl 62. If the sample occupies less than 5% of the probed volume consider re-doing the hydration step using a buffer of higher ionic strength. Film swelling after hydration requires some time to reach stabilization (Figure 4). For bR in purple membrane the process is monoexponential, with a time constant of 12 min: it takes no more than 30-60 min to have a stable rehydrated film
Figure 5 shows an IR absorption spectrum of a hydrated film of ChR2 obtained by transmission. Here, hydration was achieved by exposing the dry film to an atmosphere of controlled humidity provided by a mixture of glycerol/water. The spectrum can be decomposed into contributions from water, detergent and protein. We could estimate the amount of each of them using extinction coefficient spectra, scaled to fit the experimental spectrum. For water we took the extinction coefficient spectrum from the literature63, and for DM we measured it from a 100 mg/ml solution (Figure 6). We also used extinction coefficients for two representative membrane proteins: the mitochondrial ADP/ATP carrier64 and bR (Figure 7). The scaling factor indicates a water and DM mass surface density of 260 &#956;g/cm2 and 200 &#956;g/cm2 in the film, respectively. The remaining absorption (Figure 5, red line) comes mainly from the protein, estimated to be at a surface density of 250 &#956;g/cm2 using the amide II extinction coefficient from two different membrane proteins (see Figure 6). The molar ratio for protein/detergent/water was calculated to be 1/60/2000 using a molecular mass of 35 kDa, 480 Da, and 18 Da, respectively.
A 3D plot from typical time-resolved step-scan FT-IR experiment on bR is presented in Figure 10A, obtained by ATR and involving 200 min of data acquisition. Spectra can be extracted at specific times, for instance when the L, M and N intermediates of the bR photocycle are expected to reach their highest population (Figure 11). Their spectral features have been described extensively13,41,65 and will be not discussed further here. Figure 12 shows time-traces at some selected wavenumbers. Namely, the rise of the kinetics at 1,762 cm-1 (t1/2 ~60 &#956;sec) reports on the dynamics of Asp85 protonation from the retinal Schiff base66, and its decay to zero indicates its deprotonation upon ground-sate recovery67. The negative rise of the kinetics at 1,740 cm-1 (t1/2 ~1 msec) reports on the deprotonation of Asp96 side chain, the proton donor to the Schiff base68. The decay of the intensity to zero reports on its reprotonation from the cytoplasm67. The dynamics of protein conformational changes can be probed by absorption changes in the amide I and amide II region, which reaches a maximal change at ~3 msec at room temperature67,69.
The application of SVD to spectroscopic problems has been reviewed before55,56. Briefly, SVD factorizes the experimental data, arranged into a matrix A, as: A = U S VT. This factorization can be modified to account for the noise dependence on wavenumber and to penalize fluctuations/drifts in the baseline57. The columns of U and V contain orthonormal spectra and time-traces vectors for each SVD component, respectively. S is a diagonal matrix containing the so-called singular values. The (abstract) spectro-temporal components in U and V appear in decreasing relevance to describe the experimental data in the least-square sense, quantified by their associated singular value. Figure 13A shows the singular values as a function of the component number, and reproduces the first eight columns/components of U (abstract spectra, Figure 13B) and V (abstract time-traces, Figure 13C). The signal is concentrated in the first five components (as expected for a photocycle containing five intermediate states), with components above largely dominated by random noise and other sources of errors. The experimental data was reconstructed using only the first five columns of U and V, and the first five columns and rows of S. The data reconstructed by SVD represents the best least-square approximation of the experimental data to a matrix of rank five. The reconstructed data shows improved quality (Figure 10B). Namely, the noise is largely reduced, as well as some barely noticeable fluctuations and drifts in the baseline (common in time-resolved step-scan spectroscopy 25). SVD processing is especially beneficial for improving the quality of the experimental time-traces in the millisecond range (red lines in Figure 12).
Time-resolved step-scan data for the ChR2 photocycle were obtained using the above described protocol for transmission experiments (Figure 14A), roughly involving 120 hr of accumulated measurements. The time-resolved data collected by step-scan extends from 6.25 &#181;sec to 125 msec. The photocycle of ChR2 requires approximately 60 s for full recovery. The latest part of the photocycle can be covered using rapid-scan FT-IR, and both step-scan and rapid-scan data sets merged as presented elsewhere48. The spectral changes of ChR2 are ~10-fold smaller than those obtain from bR, making the measurements more challenging. Specially, oscillations in the baseline in the millisecond range become clearly evident at these low absorption changes. These are due to small oscillations in the mobile mirror in the millisecond time scale25. The oscillations, together with part of the noise, can be largely removed by SVD, remarkably improving the appearance of the data (Figure 14B).
<img alt="Figure 1" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig1highres.jpg" width="500" /> 
Figure 1. Absorption spectrum of bR in purple membrane dried on top the diamond surface of an ATR accessory. Bands from vibrations of the peptide bond (amide I, II, and A) are indicated.
<img alt="Figure 2" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig2highres.jpg" width="500" /> 
Figure 2. Absorption spectrum of a film of bR after rehydration using buffers of various ionic strengths (dilutions of 4 M NaCl, 100 mM Na2HPO4/NaH2PO4 at pH 7.4). Notice the decrease of the amide II band, i.e., increased film swelling, with decreasing ionic strength of the buffer. (Insert) Relative amount of protein near the surface, quantified by the intensity of the absorbance at 1,541 cm-1 (amide II maximum) after subtraction of the absorption contribution of the buffer.
<img alt="Figure 3" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig3highres.jpg" width="500" /> 
Figure 3. Absorption spectrum of a film of bR rehydrated with bulk buffer (4.3 M ionic strength) and after subtraction of the buffer contribution. The subtraction factor, 0.87, was chosen to remove the strong water absorption between 3,700-3,000 cm-1 and to obtain a flat baseline between 2,700-1,800 cm-1.
<img alt="Figure 4" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig4highres.jpg" width="500" /> 
Figure 4. Absorption spectrum of bR after rehydration with a buffer of 4.3 M ionic strength (buffer absorption has been subtracted for clarity as in Figure 3). The insert shows the evolution of the film swelling after rehydration, followed by the protein amide II absorbance at 1,541 cm-1. A fit to a single exponential indicates a time constant for film swelling stabilization of 12 min.
<img alt="Figure 5" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig5highres.jpg" width="500" /> 
Figure 5. Absorption spectrum of a hydrated film of ChR2 measured by transmission (blue line). The extinction coefficient spectrum of water (dashed orange line) and DM (dashed cyan line) was scaled and subtracted (red line).
<img alt="Figure 6" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig6highres.jpg" width="500" /> 
Figure 6. Reproduced mass extinction coefficient spectra at 25 &#176;C for liquid water (http://www.ualberta.ca/~jbertie/JBDownload.HTM#Spectra) and for a hydrated film of the ADP/ATP carrier (AAC)64. The mass extinction coefficient spectrum was measured in solution for DM (100 mg/ml), and in a hydrated film for bR.
<img alt="Figure 7" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig7highres.jpg" width="500" /> 
Figure 7. Transmittance of the optical filter used in the time-resolved scan-scan FT-IR measurements.
<img alt="Figure 8" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig8highres.jpg" width="500" /> 
Figure 8. Performance of the laser pulses provided by the second harmonic (532 nm) of a Nd:YAG laser. Histogram of the variation of the relative energy of 1,000 laser pulses, and fit to a Gaussian distribution with a standard deviation of 0.05.
<img alt="Figure 9" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig9highres.jpg" width="500" /> 
Figure 9. Light-induced absorbance changes of bR at three representative wavenumbers at uniform time spacing intervals (green, black, and blue lines) and after quasi-logarithmic averaging to ~20 points/decade (red lines). Notice the noise reduction after logarithmic averaging, revealing oscillation of the time traces in the millisecond range.
<img alt="Figure 10" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig10highres.jpg" width="500" /> 
Figure 10. 3D representation of light-induced absorbance changes for bR recorded by ATR at pH 7.4 (4 M NaCl, 100 mM NaPi). A) Raw data. B)&#160;Data reconstructed with five SVD components. <a href="https://www.jove.com/files/ftp_upload/51622/51622fig10highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 11" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig11highres.jpg" width="500" /> 
Figure 11. FT-IR difference absorption spectra of the bR photocycle at three selected times where the L (12.5 &#181;sec), M (300 &#181;sec), and N (6 msec) intermediates are most enriched.
<img alt="Figure 12" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig12highres.jpg" width="500" /> 
Figure 12. Proton transfer and protein backbone dynamics in the bR photocycle as resolved by time-resolved step-scan FT-IR difference spectroscopy. The absorbance changes at 1,762 cm-1 reports on the protonation/deprotonation dynamics of Asp85, and at 1,741 cm-1 on the deprotonation/reprotonation dynamics of Asp96 (including H-bonding changes before 300 &#956;sec). The time-traces at 1,670 and 1,555 cm-1 report changes in amide I and II vibrations, both sensitive to the conformation of the peptide backbone. The back traces correspond to the raw data, and the red ones to SVD-treated data. <a href="https://www.jove.com/files/ftp_upload/51622/51622fig12highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 13" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig13highres.jpg" width="500" /> 
Figure 13. Singular value decomposition (SVD) of the experimental time-resolved step-scan FT-IR data of the bR photocycle (see Figure 10A). SVD was performed after weighing the experimental data taking into account the noise standard deviation dependence on wavenumber (Figure 15); combined with the 1st derivative to reduce the statistical weight of baseline fluctuations, as described before57. A)&#160;Plot of the relative singular values of the first 50 components (black circles). The first five components are assigned to signal components (red circles). The rest of components decay exponentially as expected for noise-components (see dashed gray line). B)&#160;First eight abstract spectra (U1 to U8). C)&#160;First eight abstract time-traces (V1 to V8). The abstract spectra and time-traces assigned to signal are depicted in red lines, and with black lines otherwise. <a href="https://www.jove.com/files/ftp_upload/51622/51622fig13highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 14" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig14highres.jpg" width="500" /> 
Figure 14. 3D representation of light-induced IR absorbance changes for ChR2 recorded by step-scan in transmission mode. The step-scan data extends until 125 msec, only covering a part of the photocycle. A)&#160;Raw data. B)&#160;Data reconstructed with five SVD components. <a href="https://www.jove.com/files/ftp_upload/51622/51622fig14highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 15" fo:content-width="5in" src="/files/ftp_upload/51622/51622fig15highres.jpg" width="500" /> 
Figure 15. Estimated noise level in an FT-IR.&#160;Difference absorption spectrum at 6.25 &#956;sec temporal and 8 cm-1 spectral resolution for an experiment involving 1 co-addition/mirror position (500 photoreactions) or ~200 co-addition/mirror position (105 photoreactions). Values are shown for the attenuated total reflection (ATR) and the transmission setup.

Watch this Scientific Journal Video about Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy at JoVE.com

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

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 ...

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17.9K Views.  Freie Universität Berlin. 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.

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

Investigating Single Molecule Adhesion by Atomic Force Spectroscopy

Atomic force spectroscopy is an ideal tool to study molecules at surfaces and interfaces. An experimental protocol to couple a large variety of single molecules covalently onto an AFM tip is presented. At the same time the AFM tip is passivated to prevent unspecific interactions between the tip and the substrate, which is a prerequisite to study single molecules attached to the AFM tip. Analyses to determine the adhesion force, the adhesion length, and the free energy of these molecules on solid surfaces and bio-interfaces are shortly presented and external references for further reading are provided. Example molecules are the poly(amino acid) polytyrosine, the graft polymer PI-g-PS and the phospholipid POPE (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine). These molecules are desorbed from different surfaces like CH3-SAMs, hydrogen terminated diamond and supported lipid bilayers under various solvent conditions. Finally, the advantages of force spectroscopic single molecule experiments are discussed including means to decide if truly a single molecule has been studied in the experiment.

A protocol to couple a large variety of single molecules covalently onto an AFM tip is presented. Procedures and examples to determine the adhesion force and free energy of these molecules on solid supports and bio-interfaces are provided.

Atomic force spectroscopy is an ideal tool to study molecules at surfaces and interfaces. An experimental protocol to couple a large variety of single ...

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores

Developing low-cost, efficient processes for recovering and recycling palladium, gold and cobalt metals from urban mine remains a significant challenge in industrialized countries. Here, the development of optical mesosensors/adsorbents (MSAs) for efficient recognition and selective recovery of Pd(II), Au(III), and Co(II) from urban mine was achieved. A simple, general method for preparing MSAs based on using high-order mesoporous monolithic scaffolds was described. Hierarchical cubic Ia3d wagon-wheel-shaped MSAs were fabricated by anchoring chelating agents (colorants) into three-dimensional pores and micrometric particle surfaces of the mesoporous monolithic scaffolds. Findings show, for the first time, evidence of controlled optical recognition of Pd(II), Au(III), and Co(II) ions and a highly selective system for recovery of Pd(II) ions (up to ~95%) in ores and industrial wastes. Furthermore, the controlled assessment processes described herein involve evaluation of intrinsic properties (e.g., visual signal change, long-term stability, adsorption efficiency, extraordinary sensitivity, selectivity, and reusability); thus, expensive, sophisticated instruments are not required. Results show evidence that MSAs will attract worldwide attention as a promising technological means of recovering and recycling palladium, gold and cobalt metals.

Because of the importance and extensive use of palladium, gold and cobalt metals in high-technology equipment, their recovery and recycling constitute an important industrial challenge. The metal recovery system described herein is a simple, low-cost means for the effective detection, removal, and recovery of these metals from the urban mine.

Developing low-cost, efficient processes for recovering and recycling palladium, gold and cobalt metals from urban mine remains a significant challenge in ...

Integration of Light Trapping Silver Nanostructures in Hydrogenated Microcrystalline Silicon Solar Cells by Transfer Printing

One of the potential applications of metal nanostructures is light trapping in solar cells, where unique optical properties of nanosized metals, commonly known as plasmonic effects, play an important role. Research in this field has, however, been impeded owing to the difficulty of fabricating devices containing the desired functional metal nanostructures. In order to provide a viable strategy to this issue, we herein show a transfer printing-based approach that allows the quick and low-cost integration of designed metal nanostructures with a variety of device architectures, including solar cells. Nanopillar poly(dimethylsiloxane) (PDMS) stamps were fabricated from a commercially available nanohole plastic film as a master mold. On this nanopatterned PDMS stamps, Ag films were deposited, which were then transfer-printed onto block copolymer (binding layer)-coated hydrogenated microcrystalline Si (&#181;c-Si:H) surface to afford ordered Ag nanodisk structures. It was confirmed that the resulting Ag nanodisk-incorporated &#181;c-Si:H solar cells show higher performances compared to a cell without the transfer-printed Ag nanodisks, thanks to plasmonic light trapping effect derived from the Ag nanodisks. Because of the simplicity and versatility, further device application would also be feasible thorough this approach.

A viable transfer printing-based methodology to introduce plasmonic metal nanostructures in solar cells is described. Using nanopillar poly(dimethylsiloxane) stamps, an Ag-based ordered nanodisk array was integrated with standard hydrogenated microcrystalline Si solar cells, which led to improved device performances due to plasmonic light trapping.

One of the potential applications of metal nanostructures is light trapping in solar cells, where unique optical properties of nanosized metals, commonly ...

Characterizing Far-infrared Laser Emissions and the Measurement of Their Frequencies

The generation and subsequent measurement of far-infrared radiation has found numerous applications in high-resolution spectroscopy, radio astronomy, and Terahertz imaging. For about 45 years, the generation of coherent, far-infrared radiation has been accomplished using the optically pumped molecular laser. Once far-infrared laser radiation is detected, the frequencies of these laser emissions are measured using a three-laser heterodyne technique. With this technique, the unknown frequency from the optically pumped molecular laser is mixed with the difference frequency between two stabilized, infrared reference frequencies. These reference frequencies are generated by independent carbon dioxide lasers, each stabilized using the fluorescence signal from an external, low pressure reference cell. The resulting beat between the known and unknown laser frequencies is monitored by a metal-insulator-metal point contact diode detector whose output is observed on a spectrum analyzer. The beat frequency between these laser emissions is subsequently measured and combined with the known reference frequencies to extrapolate the unknown far-infrared laser frequency. The resulting one-sigma fractional uncertainty for laser frequencies measured with this technique is &#177; 5 parts in 107. Accurately determining the frequency of far-infrared laser emissions is critical as they are often used as a reference for other measurements, as in the high-resolution spectroscopic investigations of free radicals using laser magnetic resonance. As part of this investigation, difluoromethane, CH2F2, was used as the far-infrared laser medium. In all, eight far-infrared laser frequencies were measured for the first time with frequencies ranging from 0.359 to 1.273 THz. Three of these laser emissions were discovered during this investigation and are reported with their optimal operating pressure, polarization with respect to the CO2 pump laser, and strength.

We describe the generation of far-infrared radiation using an optically pumped molecular laser along with the measurement of their frequencies with heterodyne techniques. The experimental system and techniques are demonstrated using difluoromethane (CH2F2) as the laser medium whose results include three new laser emissions and eight measured laser frequencies.

The generation and subsequent measurement of far-infrared radiation has found numerous applications in high-resolution spectroscopy, radio astronomy, and ...

Emission Spectroscopic Boundary Layer Investigation during Ablative Material Testing in Plasmatron

Ablative Thermal Protection Systems (TPS) allowed the first humans to safely return to Earth from the moon and are still considered as the only solution for future high-speed reentry missions. But despite the advancements made since Apollo, heat flux prediction remains an imperfect science and engineers resort to safety factors to determine the TPS thickness. This goes at the expense of embarked payload, hampering, for example, sample return missions. 
Ground testing in plasma wind-tunnels is currently the only affordable possibility for both material qualification and validation of material response codes. The subsonic 1.2MW Inductively Coupled Plasmatron facility at the von Karman Institute for Fluid Dynamics is able to reproduce a wide range of reentry environments. This protocol describes a procedure for the study of the gas/surface interaction on ablative materials in high enthalpy flows and presents sample results of a non-pyrolyzing, ablating carbon fiber precursor. With this publication, the authors envisage the definition of a standard procedure, facilitating comparison with other laboratories and contributing to ongoing efforts to improve heat shield reliability and reduce design uncertainties.
The described core techniques are non-intrusive methods to track the material recession with a high-speed camera along with the chemistry in the reactive boundary layer, probed by emission spectroscopy. Although optical emission spectroscopy is limited to line-of-sight measurements and is further constrained to electronically excited atoms and molecules, its simplicity and broad applicability still make it the technique of choice for analysis of the reactive boundary layer. Recession of the ablating sample further requires that the distance of the measurement location with respect to the surface is known at all times during the experiment. Calibration of the optical system of the applied three spectrometers allowed quantitative comparison. At the fiber scale, results from a post-test microscopy analysis are presented.

Development of new ablative materials and their numerical modeling requires extensive experimental investigation. This protocol describes procedures for material response characterization in plasma flows with the core techniques being non-intrusive methods to track the material recession along with the chemistry in the reactive boundary layer by emission spectroscopy.

Ablative Thermal Protection Systems (TPS) allowed the first humans to safely return to Earth from the moon and are still considered as the only solution ...

Free-form Light Actuators &#8212; Fabrication and Control of Actuation in Microscopic Scale

Liquid crystalline elastomers (LCEs) are smart materials capable of reversible shape-change in response to external stimuli, and have attracted researchers&#39; attention in many fields. Most of the studies focused on macroscopic LCE structures (films, fibers) and their miniaturization is still in its infancy. Recently developed lithography techniques, e.g., mask exposure and replica molding, only allow for creating 2D structures on LCE thin films. Direct laser writing (DLW) opens access to truly 3D fabrication in the microscopic scale. However, controlling the actuation topology and dynamics at the same length scale remains a challenge.
In this paper we report on a method to control the liquid crystal (LC) molecular alignment in the LCE microstructures of arbitrary three-dimensional shape. This was made possible by a combination of direct laser writing for both the LCE structures as well as for micrograting patterns inducing local LC alignment. Several types of grating patterns were used to introduce different LC alignments, which can be subsequently patterned into the LCE structures. This protocol allows one to obtain LCE microstructures with engineered alignments able to perform multiple opto-mechanical actuation, thus being capable of multiple functionalities. Applications can be foreseen in the fields of tunable photonics, micro-robotics, lab-on-chip technology and others.

Free-form Light Actuators &amp;#8212; Fabrication and Control of Actuation in Microscopic Scale

Here, we fabricate 3D polymeric micro/nano structures in which both the shape and the molecular alignment can be engineered with nanometer scale accuracy by the use of direct laser writing. Light induced deformation of several types of liquid crystalline elastomer microstructures can be controlled in the microscopic scale.

Liquid crystalline elastomers (LCEs) are smart materials capable of reversible shape-change in response to external stimuli, and have attracted ...

Recombination Dynamics in Thin-film Photovoltaic Materials via Time-resolved Microwave Conductivity

A method for investigating recombination dynamics of photo-induced charge carriers in thin film semiconductors, specifically in photovoltaic materials such as organo-lead halide perovskites is presented. The perovskite film thickness and absorption coefficient are initially characterized by profilometry and UV-VIS absorption spectroscopy. Calibration of both laser power and cavity sensitivity is described in detail. A protocol for performing Flash-photolysis Time Resolved Microwave Conductivity (TRMC) experiments, a non-contact method of determining the conductivity of a material, is presented. A process for identifying the real and imaginary components of the complex conductivity by performing TRMC as a function of microwave frequency is given. Charge carrier dynamics are determined under different excitation regimes (including both power and wavelength). Techniques for distinguishing between direct and trap-mediated decay processes are presented and discussed. Results are modelled and interpreted with reference to a general kinetic model of photoinduced charge carriers in a semiconductor. The techniques described are applicable to a wide range of optoelectronic materials, including organic and inorganic photovoltaic materials, nanoparticles, and conducting/semiconducting thin films.

A Time Resolved Microwave Conductivity technique for investigating direct and trap-mediated recombination dynamics and determining carrier mobilities of thin film semiconductors is presented here.

A method for investigating recombination dynamics of photo-induced charge carriers in thin film semiconductors, specifically in photovoltaic materials ...

Measurements of Soil Carbon by Neutron-Gamma Analysis in Static and Scanning Modes

The herein described application of the inelastic neutron scattering (INS) method for soil carbon analysis is based on the registration and analysis of gamma rays created when neutrons interact with soil elements. The main parts of the INS system are a pulsed neutron generator, NaI(Tl) gamma detectors, split electronics to separate gamma spectra due to INS and thermo-neutron capture (TNC) processes, and software for gamma spectra acquisition and data processing. This method has several advantages over other methods in that it is a non-destructive in situ method that measures the average carbon content in large soil volumes, is negligibly impacted by local sharp changes in soil carbon, and can be used in stationary or scanning modes. The result of the INS method is the carbon content from a site with a footprint of ~2.5 - 3 m2 in the stationary regime, or the average carbon content of the traversed area in the scanning regime. The measurement range of the current INS system is &#62;1.5 carbon weight % (standard deviation &#177; 0.3 w%) in the upper 10 cm soil layer for a 1 hmeasurement.

Here, we present the protocol for in situ measurement of soil carbon using the neutron-gamma technique for single point measurements (static mode) or field averages (scanning mode). We also describe system construction and elaborate data treatment procedures.

The herein described application of the inelastic neutron scattering (INS) method for soil carbon analysis is based on the registration and analysis of ...

Quantitative Analysis of Vacuum Induction Melting by Laser-induced Breakdown Spectroscopy

Vacuum induction melting is a popular method for refining high purity metal and alloys. Traditionally, standard process control in metallurgy involves several steps, include drawing samples, cooling, cutting, transport to the laboratory, and analysis. The whole analysis process requires more than 30 minutes, which hinders on-line process control. Laser-induced breakdown spectroscopy is an excellent on-line analysis method that can satisfy the requirements of vacuum induction melting because it is fast and noncontact and does not require sample preparation. The experimental facility uses a lamp-pumped Q-switched laser to ablate melted liquid steel with an output energy of 80 mJ, a frequency of 5 Hz, a FWHM pulse width of 20 ns, and a working wavelength of 1,064 nm. A multi-channel linear charge coupled device (CCD) spectrometer is used to measure the emission spectrum in real time, with a spectral range from 190 to 600 nm and a resolution of 0.06 nm at a wavelength of 200 nm. The protocol includes several steps: standard alloy sample preparation and an ingredient test, smelting of standard samples and determination of the laser breakdown spectrum, and construction of the elements concentration quantitative analysis curve of each element. To realize the concentration analysis of unknown samples, the spectrum of a sample also needs to be measured and disposed with the same process. The composition of all main elements in the melted alloy can be quantitatively analyzed with an internal standard method. The calibration curve shows that the limit of detection of most metal elements ranges from 20-250 ppm. The concentration of elements, such as Ti, Mo, Nb, V, and Cu, can be lower than 100 ppm, and the concentrations of Cr, Al, Co, Fe, Mn, C, and Si range from 100-200 ppm. The R2 of some calibration curves can exceed 0.94.

During vacuum induction melting, laser-induced breakdown spectroscopy is used to perform real-time quantitative analysis of the main-ingredient elements of a molten alloy.

Vacuum induction melting is a popular method for refining high purity metal and alloys. Traditionally, standard process control in metallurgy involves ...

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

Unlike macroscopic process variables, near-infrared spectroscopy provides process information at the molecular level and can significantly improve the prediction of the components in industrial processes. The ability to record spectra for solid and liquid samples without any pretreatment is advantageous and the method is widely used. However, the disadvantages of analyzing high-dimensional near-infrared spectral data include information redundancy and multicollinearity of the spectral data. Thus, we propose to use partial least squares regression method, which has traditionally been used to reduce the data dimensionality and eliminate the collinearity between the original features. We implement the method for predicting the o-cresol concentration during the production of polyphenylene ether. The proposed approach offers the following advantages over component regression prediction methods: 1) partial least squares regression solves the multicollinearity problem of the independent variables and effectively avoids overfitting, which occurs in a regression analysis due to the high correlation between the independent variables; 2) the use of the near-infrared spectra results in high accuracy because it is a non-destructive and non-polluting method to obtain information at microscopic and molecular scales.

The protocol describes a method of predicting o-cresol concentration during the production of polyphenylene ether using near-infrared spectroscopy and partial least squares regression. To describe the process more clearly and completely, an example of predicting the o-cresol concentration during the production of polyphenylene is used to clarify the steps.

Unlike macroscopic process variables, near-infrared spectroscopy provides process information at the molecular level and can significantly improve the ...