Among the developed methods for growing CNTs, the catalytic chemical vapor deposition (CCVD) of hydrocarbon gases turns out to be very promising because of its comparative simplicity, ease of control and low cost. The way how certain operation conditions and catalyst properties influence the characteristics of the resulting CNTs has been so far analyzed via trial and error investigations. Nevertheless, the CNTs nucleation and growth mechanism is not fully understood yet.

Therefore, we introduce an in situ measurement strategy, which is based on linear Raman spectroscopy and which allows to analyze also the intermediate processes in the gas phase, which take place inside the CNT reactor and are not accounted for conventionally.

Thus, a series of experiments were carried out to measure the gas flow temperature and composition inside the CNT reactor during the CCVD of CNTs using a continuous wave (cw) excitation source. Due to the rather weak Raman signal intensities in a low gas density ambient (high temperature and low pressure), the signal-to-noise ratio (SNR) has to be improved by several measures. Among them, an important issue is the selection of a high-efficient signal dispersion and detection system.

In this concern, the QE65000 scientific-grade spectrometer equipped with a back-thinned CCD-detector of high quantum efficiency exhibits the best performance when compared to other options.

Some exemplary spectra recorded during the experiments are shown in Figure 1. The upper spectrum is the so-called reference spectrum, since it was taken at known operation conditions, i.e. room temperature, atmospheric pressure, a gas flow composition of 97 vol.-% nitrogen, 2 vol.-% hydrogen and 1 vol.-% acetylene and an overall gas flowrate of 85 SCCM.

The spectrum shown at the bottom was taken during the CCVD of CNTs, at the same flow conditions but at a wafer temperature of 953 K. The spectra shown in Figure 1 were recorded with an exposure time of 30 s and five accumulations, so that the effective measurement time was 2.5 minutes in order to get a single spectrum with an evaluable signal-to-noise ratio (SNR).

As noticeable, the peak intensities corresponding to the vibrational bands of acetylene, nitrogen and hydrogen decrease by increasing the gas flow temperature, since on the one side, the Raman signal intensity is proportional to the number density of molecules and on the other side, the Raman scattering cross section is a function of temperature.

Since nitrogen acts here as a carrier/inert gas, its Raman intensity decrement can be merely attributed to the high temperature level. In the case of acetylene and hydrogen, this cannot be assumed since acetylene starts to decompose at high temperatures, thereby releasing some hydrogen, which can also recombine with other radicals.

Thus, the concentration of acetylene and hydrogen decrease because of both, the chemical reactions and the high temperature level.

Figure 1: Raman spectra recorded during the CCVD of CNTs. The gas flow is composed of 97 vol.-% nitrogen, 2 vol.-% hydrogen and 1 vol.-% acetylene and the overall gas flowrate is 85 SCCM. The effective measurement time is 2.5 minutes (5 accumulations, each 30 s exposure time).

On the basis of these two spectra, it is possible to determine simultaneously the gas temperature and composition. On the one hand, the gas temperature can be evaluated via the ideal gas law taking the ratio of two peak integrals.

On the other hand, with the knowledge of the gas temperature, the effect of the Raman cross section can be evaluated and consequently, the composition can be determined. The disadvantage of this method is the low accuracy of the temperature calculation and due to the very large measurement times, it is not possible to monitor the gas temperature and composition with a high temporal resolution.

Karla Reinhold-López, M.Sc., Lehrstuhl für Technische Thermodynamik and Erlangen Graduate School in Advanced Optical Technologies, Universität Erlangen-Nuernberg

More – QE65000 Scientific Grade Spectrometer

The customer supplied us with a special wheel used for chlorine content measurements.  The provided sample has nine windows of varying shades of yellow, with a clear center window for reference, as shown in Figure 1.  The window numbering sequence can be seen on the perimeter of the sample in permanent marker; the sequence is from 1 to 9 in order of yellow intensity (9 = most yellow).  Transmission and reflection measurements were performed for each window in the sample in order to provide accurate spectrometric data for different film characteristics.

Figure 1. Chlorine Content Color Wheel

Experimental Procedure

We analyzed the wheel’s films using a USB4000 UV/VIS Spectrometer, an LS-1 tungsten-halogen light source with BG34 lens installed, and SpectraSuite Spectrometer Operating Software.  For the reflection measurements, a reflection probe (R400-7-VIS/NIR), reflection stage (STAGE), and the PTFE diffuse reflectance standard (WS-1) were utilized.  The overall distance from the tip of the reflection probe ferrule to the sample surface was around 3-mm. Figure 2 shows a photograph of the reflection experimental setup. Given the transparency of the windows, we used the WS-1 reflection standard as background for all reflection measurements.  Figure 3 shows the sample mounted on the WS-1 in the reflection stage.  The reference spectrum for the reflection measurements was the clear center window with the WS-1 background.

Figure 2. Reflection Experimental Setup

The transmission setup included an adjustable collimation lens holder (74-ACH), two collimating lenses (74-UV) and two premium grade 300-micron fibers (QP400-1-UV/VIS) as shown in Figure 4, utilizing the same light source and spectrometer. The transmission measurements were conducted using two different references.  In the first experiment, the clear center window was mounted in the transmission stage and a reference spectrum was captured.  All of the subsequent window spectra are referenced to the central window spectrum.  In the second experiment we removed the sample from the optical path and obtained the reference spectrum.  We captured spectra from all nine windows and the clear central window with respect to the free optical path reference.

Figure 3. Sample shown with WS-1 background

Results

The reflection and transmission results for each window in the chlorine content color wheel are shown in Figure 5 – Figure 7. A summary of the measurement  parameters used in SpectraSuite software is presented in Table 1.

The following results are color-coded as labeled in the figure legends.  All figures employ the same color-coding (e.g., window one is blue in all diagrams).  The measurement parameters from Table 1 are also visible in the left frame of the figures.

There is good correlation between the reflection data and transmission data (using the center window as reference).  Based on the setup of the reflection experiment, we would expect similar spectral shape to the transmission data because of the PTFE diffuse reflection standard background.  Essentially, the light is transmitted through each window, reflects off the 99% diffuse reflection standard, the reflection is transmitted back through the window and is read by the spectrometer.  Therefore, the spectral shapes should be essentially the same.

Figure 5. Reflection Experiment Results

From the comparison of the two sets of transmission data, it is clear that using the results obtained with the clear center window spectrum as a reference would be most advantageous for classifying the subtle differences in the sample windows.  This is primarily due to the nature of the clear center  window in the region from 350 – 500 nm.  The center window spectrum is actually concave down (negative second derivative) over that region, which actually enhances the light source signal over that region.  This region best classifies the sample windows.

Figure 6. Transmission data with center window as reference

Figure 7. Transmission data with no sample in optical path as reference

More on the web

- USB4000 UV-VIS Spectrometer
- LS-1 Light Source
- WS-1 Reflection Standard

]]> http://www.spectroscopytips.com/apps/reflection-and-transmission-of-chlorine-content-color-wheel/feed/ 0 http://www.spectroscopytips.com/apps/raman-analysis-of-pharmaceutical-ingredients/ http://www.spectroscopytips.com/apps/raman-analysis-of-pharmaceutical-ingredients/#comments Thu, 02 Sep 2010 17:45:36 +0000 Admin http://www.spectroscopytips.com/apps/?p=281 A range of options is available for Raman analysis, including systems suitable for handheld, laboratory and educational applications. Systems typically include a spectrometer, laser, operating software and sampling accessories, while modular options are available for users to configure their own Raman systems. Most applications are handled in the 150-3200 cm-1 range, with resolution of ~6-10 cm-1.

Introduction
Raman spectroscopy offers a number of benefits for testing and characterization. It is rapid and non-destructive, requires only limited sample preparation and allows for sample volumes in the microliter range. In addition, Raman can be used to measure aqueous samples or samples with high moisture content, and allows researchers to capture data from a sample contained in plastic or other materials that are optically transparent to the wavelengths of interest.

Raman is particularly useful for pharmaceutical applications. For example, Raman techniques are used to discern characteristics of pharmaceutical raw materials, including active ingredients, binders, fillers, lubricants and other excipients. Raman is also useful for through-container measurements of pharmaceutical blister packs, pill bottles and vials.

Experimental Conditions
To illustrate the capabilities of our Raman systems we analyzed Paracetamol (acetaminophen) and Carbamazepine, which are pharmaceutical active ingredients, and the excipients alpha and beta lactose. The samples studied consisted of simple organic compounds contained in standard, clear borosilicate scintillation vials. No additional preparation was necessary.

Samples were analyzed using a modular Raman setup comprising our QE65000 Spectrometer, a 785 nm laser with 500 mW output and a fiber optic probe. The spectrometer was set from ~780-940 nm and configured with a 50 µm slit for good optical resolution. High reflectivity optical bench mirrors increased spectrometer sensitivity.

To collect signal, we placed the tip of the probe at the bottom of three glass vials containing the samples. We measured the samples at an integration time of 8 seconds and averaged three spectra.

Results
Our measurements confirmed that this Raman configuration can differentiate various pharmaceutical raw materials based on their spectral fingerprints. Also, the experiment helped demonstrate that, with proper method development and application of chemometric analysis, our Raman setups can be used to obtain semi-quantitative data of active ingredients in a pharmaceutical mixture.

Our experiment also showed that fluorescence occurs in the lactose samples. Fluorescence is a common phenomenon in Raman measurements of some organic compounds and depends on the wavelength of the laser utilized.

Conclusions
The availability of both turnkey and modular Raman systems, complemented by sophisticated chemometric analysis packages and spectral libraries, makes Raman spectroscopy a versatile choice for a host of applications.

Experimental Conditions:
Several encoder wheels were sent for analysis. The samples are described below.

50% Sandblasted sample (Zn encoder wheel with 50% of one of the surfaces sandblasted)
Sample 1: Zn plated encoder wheel (not sandblasted)
Sample 2: ABS or POM encoder wheel – 1 sandblasted and 1 unsandblasted wheel
Sample 3: POM encoder wheel – 1 sandblasted and 1 unsandblasted wheel

Specular reflectance measurements at 90 degrees relative to the sample surface were performed on each sample on both the top and bottom sides of the samples. Specular reflectance was measured at 90 degrees with diffuse reflectance measurements for some of the samples at 45 degrees relative to the sample surface using the RPH-1 reflection probe holder. The shiny Zn plated encoder wheels (50% sandblasted sample and sample 1) were analyzed with the STAN-SSH high reflectivity specular reflectance standard as a reference. The dull black encoder wheels (samples 2 and 3) were analyzed with the WS-1 diffuse reflectance standard as a reference. One additional set of data was acquired for the 50% sandblasted Zn plated and POM (sample 3) encoder wheels with the unsandblasted samples used as a reference for the sandblasted samples.

Since the samples had different shapes, various methods were used to acquire the reflection spectra. Measurements of the Zn plated encoder wheels (50% sandblasted and sample 1) were configured as shown in Figure 1 with measurements of the sandblasted and unsandblasted ABS and POM encoder wheels configured as shown in Figure 2. Measurements of the taller POM sandblasted and unsandblasted encoder wheels were configured as shown in Figure 3.

Hardware Used:
HR4000-CG (HR4C349) high resolution spectrometer
DH2000-BAL tungsten deuterium light source
R400-7-UV-VIS reflection probe
RPH-1 reflection probe holder
WS-1 diffuse reflectance standard
STAN-SSH high reflectivity specular reflectance standard
Experimental Parameters:
Zn plated samples (50% Sandblasted and Sample 1)
Integration Time (msec): 45
Spectra Averaged: 50
Boxcar Smoothing: 1

ABS or POM samples (Sample 2)
Integration Time (msec): 375
Spectra Averaged: 20
Boxcar Smoothing: 1

POM sample (Sample 3)
Integration Time (msec): Top 420 Bottom 750
Spectra Averaged: Top 20 Bottom 10
Boxcar Smoothing: 1
Measurement Mode:
Reflectance

Results:
For specular reflectance measurements at 90 degrees, reflectance always decreased following sandblasting. To provide a more quantitative assessment of the decrease, the specular reflectance at 400 nm (wavelength chosen arbitrarily) was compared for the sandblasated versus unsandblasted samples. The results shown in Table 1 are the percent reflectance values at 400 nm for an average of 3 to 5 replicates measurements at different locations on the sample. There was an ~84% difference in specular reflection for the unsandblasted versus sandblasted side of the 50% sandblasted Zn plated encoder wheel. Note (as shown in the last rows of the table) that there was an 8.5% difference in specular reflection when the top and bottom of the unsandblasted Zn encoder wheel (Sample 1) were compared suggesting that there is some variability when various locations on the sample were measured. For the ABS or POM (Sample 2) and POM (Sample 3) encoder wheels, specular reflection differed by 63 to 69% and 41 to 69%, respectively for the sandblasted versus unsandblasted samples. Note that specular measurements from the top and bottom of the same sample varied in most cases. The other data shown in the table is the specular reflection measured for the sandblasted 50% sandblasted Zn plated and POM encoder wheels using the unsandblasted samples as the reference. In this case, specular reflection of the Zn plated encoder wheel at 400 nm was only ~17% of the unsandblasted sample with the POM sample showing a decrease of 45% with sandblasting relative to the unsandblasted POM sample. Specular reflectance data are shown in Figures 4 through 7.

An additional set of measurements was done with the probe placed in the 45 degree position in the reflection probe holder for the 50% sandblasted Zn plated and ABS or POM encoder wheel (Sample 2) samples. Note that the diffuse reflection at 45 degrees was much lower than the specular reflection measured at 90 degrees. The WS-1 diffuse reflectance standard was used as a reference for these measurements. In contrast to the specular reflection measurements at 90 degrees, the diffuse reflectance increased after sandblasting. The data acquired for the 50% sandblasted Zn plated encoder wheel is shown in Figure 8.

Figure 1: Specular reflection measurements of the Zn plated encoder wheels (50% sandblasted sample and Sample 1)

Figure 2: Specular reflection measurements of the ABS or POM encoder wheels (Sample 2)

Figure 3: Specular reflection measurements of the POM encoder wheels (Sample 3)

Table 1: Summary of Specular Reflectance Results

Figure 4: Specular reflection from the 50% Sandblasted Zn Plated Encoder Wheel

Figure 5: Specular reflection from the ABS or POM Encoder Wheel (Sample 2)

Figure 6: Specular reflection from the POM Encoder Wheel (Sample 3)

Figure 7: Specular reflection from sandblasted samples (unsandblasted samples used for reference)

Figure 8: Diffuse Reflection Measurements for the 50% Sandblasted Zn Plated Encoder Wheel

Hardware Used:
USB2000-FLG
EG&G pulsed xenon light source
CUV-ALL-UV
600 micron optical fibers

Acquisition Parameters:
Integration Time (msec): 10
Spectra Averaged: 100
Boxcar Smoothing: 20

Measurement Mode:
Gated Fluorescence

Experimental Conditions:
The sample used was Bacillus globigii spores in terbium reagent. Data acquisition delayed from 5 to 500 usec after the lamp was triggered.

Results:
The effect of gating on the spectral shape is shown in the figures below. As the delay between lamp trigger and data acquisition is increased, the terbium/DPA photoluminescence becomes more distinct. Shorter lived background fluorescence and lamp pulse are not observed. Longer delay times (above 50 usec) lead to a decrease in sensitivity as a portion of the terbium/DPA photoluminescence is missed at long delay times.

Conclusions:
The optimal delay for these samples is 40 microseconds. A 40 microsecond delay between the lamp trigger and data acquisition minimizes the contribution of the xenon source (and fluorescence due to other fluorophores) to the photoluminescence spectrum while maximizing the photoluminescence signal.

Images:

Introduction:
Currently, the materials generated during the zinc refinement process are analyzed with wet chemistry and LA-ICP-MS for CaO, MgO, SiO2, Al2O3, TiO2, Cr205 and F to monitor the refinement process. Typical concentrations are 0.5 to 35%. Four samples were sent representing various stages in the refinement process – Calcine, Zinc Ferrite Cake, Cobalt Cake and Copper/Cadmium Cake. The elements of interest for Calcine and Zinc Ferrite were Fe, Pb, S and Zn with the presence of Cu, Co, Cd, Ni, Pb and Zn of interest in the Cobalt and Copper/Cadimium Cakes.

Hardware Used:
LIBS2000+ broadband, high-resolution spectrometer
200 mJ Nd:YAG Big Sky laser
LIBS-SC sampling chamber with imaging module

Acquisition Parameters:
Laser setting 8 (highest setting ~200 mJ)
Analysis in air
-1 Q-switch setting for all samples except Calcine (Q-switch delay was increased to -2.5 setting to elminate the bright continuum background)
Element ID Parameters: +/-1 pixel search width and 50 count peak height

Measurement Mode:
LIBS

Experimental Conditions:
The four samples varied in color and consistency. Calcine was a brown powder, Zinc Ferrite was large chunks of brown material similar in consistency to clay and the Cobalt and Copper Cadmium Cakes were dark grey material with the consistency of thick mud. All four samples were analyzed on double-sided photo mounting tape adhered to glass microscope slides. Calcine and the Cobalt and Copper Cadmium Cakes were easily dispersed on the tape.

Due to an inability to spread the Zinc Ferrite sample, it was analyzed as large chunks. Three single shot spectra were acquired for different locations on each sample with two additional locations analyzed with 5 and 10 shot spectra for all samples except Calcine. Three and five shot spectra were used for Calcine due to the thin layer of sample present on the tape.

The use of 10 and possibly even 5 shot spectra would have drilled through the thin sample and into the tape and microscope slide. The other samples provided a thick enough layer that analysis of the underlying tape and microscope slide substrates was not a concern.

Results:
The results from the Elemental Identification software are summarized for each of the samples below. The complete list of elements identified by the software are found in an Excel spreadsheet with the results for each sample found on a separate worksheet.

Calcine
All the elements of interest (Fe, Pb, S and Zn) were detected in all replicates.
Decreased intensity and inability to detect S was observed when the dusty powdered sample coated the optics following the laser events. Compressed air was used to clean the sampling optics probe between each measurement.
Signal averaging did not improve detection (no additional lines were detected when spectra were acquired as the accumulation of multiple laser shots).

Zn Ferrite
Fe, Pb and Zn were detected in all replicates.
S was detected in one single shot replicate.
The sample was moist as observed visually and by the strong H alpha line at ~656 nm. If S was expected in this sample, the moisture in sample may have quenched the plasma making it more difficult to see some elements. Note that the Cobalt and Copper/Cadium Cakes appeared to have a higher moisture content.
Signal averaging did not improve detection.

Copper/Cadmium Cake
Less elemental lines were detected for the Copper/Cadmium Cake than for the Calcine and Zn Ferrite samples.
All elements of interest were detected in all replicates (Cd, Co, Cu, Ni, Pb and Zn).
The Cu lines were very intense (even stronger than the hydrogen alpha line).
The sample was moist as observed visually and by the strong H alpha line at ~656 nm.
Signal averaging did not improve detection.

Cobalt Cake
The least number of elemental lines was observed for the Cobalt Cake sample.
Cd, Co, Cu, Ni and Zn were detected in all replicates.
Pb was not detected in any of the replicates.
The sample was moist as observed visually and by the strong H alpha line at ~656 nm.
Signal averaging did not improve detection.

A reflective pH patch was affixed to the inner wall of a small 7mL tube, and was held in place using a ring stand and clamp. A 600um bifurcated reflective probe was connected to an LS-1 light source with a blue filter, as well as a USB2000 spectrometer with grating #1, 200um slit, and no lens installed. The first feasibility test used clear buffers instead of the muddied buffers, in order to observe the performance. The experimental setup is pictured below, along with the plot of the resulting titration.

Although the curves showed a slight distortion, they followed the expected trend and produced a linear calibration plot. Dirt was obtained and mixed in with the buffer solutions; the experimental setup is shown below.

This yielded a very interesting titration plot, unlike any that had been seen before:

Typically for reflective pH patches, the peak is observed at 620nm and the baseline correction is done at 509nm. In this case, however, we see the peak had shifted closer to 635nm, and the 509nm region was distorted completely. As a result, 750nm was used as the baseline correction wavelength, which produced an incredibly linear calibration plot, as seen below.

This application has been critical in determining the effect of turbidity on the absorbance curves for the reflective pH patches, and has concluded that the correct wavelengths for acquisition and baseline need to be chosen based on the nature of the analyte solution.

Background
The Chemistry Department at the University of Washington is performing a research study where the measurement of oxygen in the headspace of Acetonitrile is critical. Since acetonitirle is an organic solvent and the vapors of acetonitrile are harsh, a sensor which can resist the fumes is applicable for this environment. The Hioxy oxygen sensor design my Ocean Optics was tested for this application.

Equipment
* Phase Fluorometer Electronics (MFPF)
* Bifurcated Fiber Optic Cable
* Hioxy-R Sensor

Feasibility Test Procedure
The MFPF electronics is an instrument platform for measurement of fluorescence lifetime and phase. This frequency domain electronics uses a blue LED excitation and a photodiode for detection. A fluorescence method is used to measure the partial pressure of dissolved or gaseous oxygen. A bifurcated optical fiber carries excitation light produced by the blue LED to the thin-film coating of the Hioxy-R sensor.. Fluorescence generated at the tip of the probe is collected by the probe and carried by the optical fiber to the detector of the MFPF. The phase shift between the blue LED excitation and emission signal of fluorescence is used to calculate the lifetime.  The Lifetime is an essential parameter for the calculation of oxygen.

To test the feasibility of the Hioxy sensor in the Acetonitrile headspace, the Hioxy Sensor is evaluated for its performance before exposure to the acetonitrile vapor.

The Hioxy sensor is exposed to Nitrogen and then to Air as show in Figure 1. The ratio of the lifetime from Nitrogen to Air is noted to be approximately 4.01. Now the sensor is exposed to the vapors of acetonitrile for about 2 hours. After the exposure the sensor is pulled out from the vapors and left in ambient conditions. The ratio of Nitrogen to air is measured again in terms of lifetime. The ratio after this exposure has changed to 4.27. The sensor is again exposed to acetonitrile vapor and the ratio is measured after exposure to be the same at 4.27.

Results
As shown in Figure 1, the Hioxy Sensor looks very stable in the headspace of the Acetonitrile container. The ratio of Nitrogen to Air has changed after the first exposure to Acetonitrile vapor. After the first exposure the ratio stays the same. This means there is a one time effect on the sensor when exposed to acetonitrile vapor.

Conclusion
The Hioxy sensor can be used to measure oxygen in the headspace of Acetonitrile. When a sensor is sold for this application, the sensor needs to be cured with acetonitrile vapor before calibration.

Also note: The sensor needs to be placed in acetonitrile vapor for at least 2 hours before use.

1    INTRODUCTION

1.1    Microorganisms in blood

Microorganisms are one celled organisms such as viruses, fungi and bacteria. Presence of microorganisms is harmful and cause diseases. The presence of microorganisms in blood cultures plays an important role in the diagnosis of different diseases. Different methods have been in existence to detect the presence of microorganisms in blood cultures. Early detection of such organisms is of primary importance to the selection of appropriate therapies and doses to be adopted on patients . Blood culturing systems are bioreactor system which involves the process of selectively growing microorganisms under optimized conditions. Blood culturing systems are closed culture systems where blood along with the growth media is operated under constant temperature along with continuous mixing. The numbers of microorganism increase due to respiration process and establish reactions with blood components changing the forms of hemoglobin. In the absence of microorganisms irrespective of the growth media present, the blood components do undergo changes due to aging of the red blood cells. As the microorganism’s density increases in the blood culture, partial pressure of oxygen is reduced and partial pressure of carbon dioxide is increased as a part of respiration process.

Automated systems are being developed to continuously monitor the different metabolic changes happening in the blood contents along with the changes in the partial pressure of oxygen/carbon dioxide consumed/generated respectively. The instruments primarily constitute the detection system to capture the data points at different intervals to form mathematical models to study the behavior of microorganisms and their growth patterns. The information collected using such systems helps us to understand the time period when the microorganisms have grow and aid in the selection of system parameters optimum to detect the different microorganisms. Some of the changes such as conversion of oxy to deoxyghemoglobin within the red blood cells have been detected using spectroscopy methods which provide growth behavior of organisms . As oxygen is necessary for cell respiration and is consumed during the growth phase of a cell processes for aerobic microorganisms. The cells reproduce and their cell density increases during the growth phase leading to increased oxygen consumption by the cells. The cells consume the dissolved oxygen from the liquid media (blood culture).

This paper presents the application of smart cuvette coated with oxygen sensitive sol gel coating which acts as a detection system to measure the dissolved partial pressure of oxygen in blood culture systems and the trend in oxygen consumption in response to the increasing density of microorganisms

2    SYNTHESIS OF NANO POROUS SOL GEL MATRIX AS A MOLECULAR PROBE FOR DISSOLVED OXYGEN

A ruthenium compound was immobilized in an organically modified silicate (ORMOSIL) using sol gel process. Methyltrimethoxysilane (MTMS) was used as the sol gel precursor. Appropriate amount of water and alcohol is added to the precursor to induce hydrolysis and condensation polymerization. Sub ppb levels of DO were able to be detected using the sol gel coating. Organically modified silicate (ormosil) sol-gel thin films have many advantages over their inorganic sol-gel and polymeric counterparts for sensing applications .

3    MATERIALS AND METHODS

3.1    Cell culture system design (Bioreactor)

An optical system is integrated to monitor the oxygen levels in a bioprocess system in a continuous fashion. The system built is a small scale version of the bioreactor. The integration involves the optical oxygen sensing system with the bioprocess system built to grow cells at constant temperature. Each of the components is described in detail in the following section:

3.2    Smart Oxygen Cuvette

Smart oxygen is a revolutionary oxygen sensing product designed for monitoring the dissolved oxygen in samples for biological and medical applications. Smart oxygen cuvette consists of a sensor coating formulation trapped in a sol gel matrix, immobilized and protected from the package contents. .The cuvette (Glass flourometer cell, Rectangular, Starna Cells Inc, CA) is the cell growth container of the bioprocess system. The Smart Oxygen cuvette has oxygen sensor coating formulation integrated with the cuvette on the inner lining of one of the side as shown in Figure 1

3.3    Qpod

The qpod is a complete sample compartment for fiber optic spectroscopy, including a peltier-controlled cuvette holder with magnetic stirring, and fused silica lens systems with SMA fiber optic connectors. The collimating /imaging/mirror optics enables the collection of rays and focus on the collection fiber. The qpod is equipped with Quantum Northwest TC125 Temperature Controller for temperature control and magnetic stirring to enable the cells in the cuvette to be in continuous stirring mode. As the cells have to be in a continuous stirring mode in a bioreactor, so magnetic stirring feature enables a good control on the stirring aspect integrated into the system .

3.4    NeoFox

The NeoFox Phase Fluorometer is an instrument platform for measurement of fluorescence lifetime and phase. This frequency domain electronics uses a blue LED excitation and a photodiode for detection. A fluorescence method is used to measure the partial pressure of dissolved or gaseous oxygen. A bifurcated optical fiber carries excitation light produced by the blue LED to the thin-film coating of the Smart Cuvette. Fluorescence generated at the surface of the patch is collected by the probe and carried by the optical fiber to the detector of PF. The phase shift between the blue LED excitation and emission signal of fluorescence is used to calculate the lifetime. The Figure 2 below is a representation of the phase measurement.  A new compact phase flourometer, NeoFox developed by Ocean Optics is used in this system design.

Oxygen as a triplet molecule is able to quench efficiently the fluorescence and phosphorescence of certain luminophores. This effect (first described by Kautsky in 1939) is called “dynamic fluorescence quenching.” Collision of an oxygen molecule with a fluorophore in its excited state leads to a non-radiative transfer of energy. The degree of fluorescence quenching relates to the frequency of collisions, and therefore to the concentration, pressure and temperature of the oxygen-containing media. When oxygen in the gas or liquid sample diffuses into the thin-film coating, it quenches the fluorescence. The degree of quenching correlates to the level of oxygen pressure.

4    SENSOR CALIBRATION

In order to make accurate oxygen measurements inside the cuvette, the calibration of the Smart Oxygen Cuvette was performed using the Linear (Stern-Volmer) algorithm. Since this experiments were performed at room temperature (~25C), temperature compensation during the calibration was not required.
Temperature does not affect the fluorescence decay time, fluorescence intensity, collision frequency of the oxygen molecules with the fluorophore, and the diffusion coefficient of oxygen as long as the temperature is maintained between ± 1 °C of the calibrated temperature.

Linear (Stern-Volmer) Algorithm: The Linear (Stern-Volmer) algorithm requires at least two standards of known oxygen concentration. The first standard must have 0% oxygen concentration and the last standard must have a concentration in the high end of the concentration range. The Smart Oxygen Cuvette patch was calibrated at 0% and 20.9% oxygen. The calibration curves were generated from these standards and the linear algorithm was used to calculate oxygen concentration values for unknown samples.

The fluorescence lifetime (?) can be expressed in terms of the Stern-Volmer equation where the fluorescence is related quantitatively to the partial pressure of oxygen:

Where t0 is the lifetime of fluorescence at zero pressure of oxygen, ? is the lifetime of fluorescence at a pressure p of oxygen, and k is the Stern-Volmer constant.

For a given media, and at a constant total pressure and temperature, the partial pressure of oxygen is proportional to oxygen mole fraction. The Stern-Volmer constant (k) is primarily dependent on the chemical composition of the sensor formulation. The Stern-Volmer constant (k) is temperature dependent. All measurements should be made at the same temperature (± 1 °C) from the calibration experiments. If temperature compensation is needed, then the relationship between the Stern-Volmer values and temperature is defined as:

The lifetime of fluorescence at zero pressure of oxygen depends on details of the optical setup: the power of the LED, the optical fibers, loss of light at the probe due to fiber coupling, and backscattering from the sample. It is important to measure the lifetime of fluorescence at zero pressure of oxygen (I0) for each experimental setup .

5    OPTICAL SENSING SYSTEM INTEGRATION WITH CELL CULTURE SYSTEM

The Smart Oxygen cuvette is placed in a qpod and the side of the cuvette which has the oxygen sensor coated material is interfaced with the bifurcated reflectance probe. The bifurcated reflectance probe is connected to the NeoFox system. The LED source on the NeoFox provides the excitation light and is coupled to one of the legs of the bifurcated optical probe. The reflected florescence light is coupled back into the other leg of the bifurcated probe and terminated at the detector surface on NeoFox. The NeoFox interfaces with the NeoFox Viewer Software (Ocean Optics Inc.) which measures the oxygen levels. The complete system used to measure oxygen levels is shown in Figure 3

5.1    Experimental Setup

The oxygen sensing experiment was carried out in a Smart Oxygen Cuvette. To build a two point calibration, the nitrogen gas is diffused into the cuvette for 0% oxygen and then air is diffused into the cuvette for 20.9% oxygen. The two points are captured and a calibration curve is built to quantify the oxygen levels in the range of 0 – 21% from the life time measurements. We start our experiment by placing Whole goat blood and water (1:1.5) in the cuvette, magnetic stirrer is placed in the cuvette and the stirring speed is set to a maximum using the qpod temperature and magnetic controller interface. The temperature is set at room temperature. The NeoFox viewer software starts logging the data from the instant diluted blood is placed in the cuvette. The oxygen concentration in blood starts at a low concentration of oxygen and increases until almost air saturation. Once the oxygen level increases and is stable, yeast cells are added to the blood in the cuvette. The oxygen quenching is observed over a period of time. After each run all of the dissolved oxygen sensor data is logged. The cuvette is washed and dried and placed back into the qpod for the next run. The experiment is conducted 3 times.

To replicate the bioprocess conditions, nutrients were added to the blood to study the rate of dissolved oxygen in the cell culture media. The experiments were repeated with the yeast cells of 200mgrams. The sensor data was logged for a period of 30 minutes and after each run, the cuvette was rinsed and dried with vacuum for the next run. The experiment was repeated three times.
Another set of experiments was run to study the time it takes to quench the dissolved oxygen in a closed cuvette. Different amounts of yeast were added to the diluted blood and the time it takes to quench the dissolved oxygen is recorded.

Figure 3 shows the bioreactor setup with oxygen sensor patch interfaced with bifurcated fiber optic probe. The legs of the fiber optic probe are connected to the LED excitation source and detector on the NeoFox. The USB interface on the NeoFox transfers the data to the NeoFox Viewer Software for the data logging process

6    RESULTS AND DISCUSSION

The Smart Oxygen cuvette is a small-scale system used to study the effects on the oxygen partial pressure of the blood sample in the presence of microorganisms in the blood. During the experiment while the blood is diluted with water and added to the cuvette very low concentration of dissolved oxygen is present. Due to stirring the blood in a closed system cuvette the oxygen level in the dissolved blood eventually rises up to air saturation. Once the dissolved oxygen level is stabilized at air saturation, the yeast cells are added to observe the consumption of the oxygen

The yeast cells when dissolved in blood started consuming the oxygen through the liquid cell membrane interface by the diffusion process. The system is calibrated and the dissolved oxygen levels are monitored when the yeast cells are added and the measurements have been carried out for a time period of approximately 30 minutes. The experimental results (n = 3) in Figure 4 show the performance of Smart Oxygen Cuvette in measuring the oxygen levels continuously as the bioprocess happens in the cell culture system. As the cells are consuming the oxygen in the liquid media through diffusion, the oxygen depleted in the liquid media is what the Smart Oxygen Cuvette is really sensing. The same experiment can be extended to a single cell, in a micro fluidic well culture system. The one side of the cuvette has the oxygen sensing coating which measures the oxygen level depleted in the liquid media surrounding the cell. Using the diffusion parameters of the cell, one can calculate the oxygen consumed by each cell. It is observed that adding 200 milligrams of yeast to about 2.5mL of diluted blood can quench the oxygen to approximately 1 % within 20 minutes. The three runs show very similar results as shown in Figure 4.

Figure 4 shows the dissolved oxygen levels in a bioreactor system measured using a Smart Oxygen Cuvette

The small scale culture applications have the advantage of the studying the effect of multiple nutrients/environmental conditions on the oxygen levels consumed and also on the process throughput. With an objective to study the performance of the performance of Smart Cuvette in sensing oxygen levels in the cell culture, we have performed another set of experiment varying the amount of yeast dissolved in blood. The oxygen is consumed by the cells faster if the amount of cells is more. Figure 5 shows the performance of Smart Oxygen Cuvette in measuring the dissolved oxygen levels in cell culture environment with different yeast amount added to diluted blood.

Figure 5 shows the oxygen consumed by cells when different amounts of yeast is added to diluted blood as measured by Smart Oxygen Cuvette

7    CONCLUSION

A Smart Oxygen cuvette is reported to provide superior measurements of dissolved oxygen in important biological experiments such as in blood culture/bioreactor systems. The integration of Smart oxygen cuvette when combined with advanced phase fluorometry can be used to develop portable systems to measure presence of bacteria in different blood cultures. The fluorescent technology based on oxygen quenching has already proven it success in the mycobacterial growth indicator(TB test)  and is used to accurately identify mycobacteria .Development of a cost effective system integrated with multiplexing capabilities would open a new approach to study the presence of microorganisms in blood culture  system. As healthcare costs are rising and especially with the increasing incidence of TB cases, the proposed system can be used in the preventive healthcare to diagnose the presence of bacteria at an early stage from blood sample. Systems of this nature would accelerate the intervention procedures and facilitate the reduction of healthcare costs.

[ii] Debra E. Huffman, et al, “J.New method for the detection of micro-organisms in blood: application of quantitative interpretation model to aerobic blood cultures”, Biomed. Opt. 14, 034043 (2009), DOI:10.1117/1.3156837

Hardware Used:
•    Phase Fluorometer Electronics (MFPF)
•    Bifurcated Fiber Optic Cable
•    HiOXY-R Sensor.

Abstract:
This application note explains how partial pressure of oxygen is measured even in the presence of gases like Methane.

Background:
Methane is a chemical compound with the chemical formula CH4. It is the simplest alkane, and the principal component of natural gas. Burning methane in the presence of oxygen produces carbon dioxide and water. The relative abundance of methane makes it an attractive fuel. Several oil companies have approached Ocean Optics to provide a solution of measuring oxygen in the presence of Methane.

The HiOXY oxygen sensor design by Ocean Optics was tested for this application.

Feasibility Test Procedure:
The MFPF electronics is an instrument platform for measurement of fluorescence lifetime and phase. This frequency domain electronics uses a blue LED excitation and a photodiode for detection. A fluorescence method is used to measure the partial pressure of dissolved or gaseous oxygen. A bifurcated optical fiber carries excitation light produced by the blue LED to the thin-film coating of the Hioxy-R sensor. Fluorescence generated at the tip of the probe is collected by the probe and carried by the optical fiber to the detector of the MFPF. The phase shift between the blue LED excitation and emission signal of fluorescence is used to calculate the lifetime.  The Lifetime is an essential parameter for the calculation of oxygen.

A short term feasibility test has been performed using HiOXY sensor in Methane gas.

The chart below first shows the response of the HiOXY sensor in Nitrgoen and Air first.  The sensor is again exposed to nitrogen and a small flow of methane is introduced. There is no observed change in the lifetime due to the introduction of methane in the nitrogen flow.
The sensor is now exposed back to air to see if there are any effects or changes caused in the lifetime due exposing the sensor to Methane gas. It is observed that there is no change in the lifetime in Air. A small flow of Methane is introduced in the air stream and a slight increase in the lifetime caused from the methane.

When only methane is exposed to the sensor, it behaves in the same way as nitrogen as the sensor does not see any oxygen.

In conclusion, the HiOXY sensor can be used to measure oxygen in the presence of Methane gas without affect the intensity or the lifetime of the sensor.

To measure oxygen concentration is measured in the headspace of organic solvents such as Acetonitrile) using a phase fluorometer systemMethod:
O2 Sensing

Hardware Used:
Phase Fluorometer Electronics (MFPF)
Bifurcated Fiber Optic Cable
Hioxy-R Sensor

Feasibility Test Procedure
The MFPF electronics is an instrument platform for measurement of fluorescence lifetime and phase. This frequency domain electronics uses a blue LED excitation and a photodiode for detection. A fluorescence method is used to measure the partial pressure of dissolved or gaseous oxygen. A bifurcated optical fiber carries excitation light produced by the blue LED to the thin-film coating of the Hioxy-R sensor.. Fluorescence generated at the tip of the probe is collected by the probe and carried by the optical fiber to the detector of the MFPF. The phase shift between the blue LED excitation and emission signal of fluorescence is used to calculate the lifetime.  The Lifetime is an essential parameter for the calculation of oxygen.

To test the feasibility of the Hioxy sensor in the Acetonitrile headspace, the Hioxy Sensor is evaluated for its performance before exposure to the acetonitrile vapor.
The Hioxy sensor is exposed to Nitrogen and then to Air as show in Figure 1. The ratio of the lifetime from Nitrogen to Air is noted to be approximately 4.01. Now the sensor is exposed to the vapors of acetonitrile for about 2 hours. After the exposure the sensor is pulled out from the vapors and left in ambient conditions. The ratio of Nitrogen to air is measured again in terms of lifetime. The ratio after this exposure has changed to 4.27. The sensor is again exposed to acetonitrile vapor and the ratio is measured after exposure to be the same at 4.27.

Results
As shown in Figure 1, the Hioxy Sensor looks very stable in the headspace of the Acetonitrile container. The ratio of Nitrogen to Air has changed after the first exposure to Acetonitrile vapor. After the first exposure the ratio stays the same. This means there is a one time effect on the sensor when exposed to acetonitrile vapor.

Conclusion
The Hioxy sensor can be used to measure oxygen in the headspace of Acetonitrile. When a sensor is sold for this application, the sensor needs to be cured with acetonitrile vapor before calibration.

Note:
The sensor needs to be placed in acetonitrile vapor for at least 2 hours before use.

Method:
pH Sensing

Hardware Used:
USB2000 Spectrometer: Grating #1, 200um slit, no lens installed
LS-1 Light Source
Bifurcated Reflective Probe, 600um
SpectraSuite Software

Measurement Mode:
Absorbance

Notes:

There was an interest in non-intrusively monitoring pH in tubes containing wet soil samples. This was significant for a number of reasons; this was the first time the reflective patches were to be tested in something other than a cuvette, on a curved surface rather, and this was also the first time an analyte solution was observed that contained sediment or turbidity.

A reflective pH patch was affixed to the inner wall of a small 7mL tube, and was held in place using a ring stand and clamp. A 600um bifurcated reflective probe was connected to an LS-1 light source with a blue filter, as well as a USB2000 spectrometer with grating #1, 200um slit, and no lens installed. The first feasibility test used clear buffers instead of the muddied buffers, in order to observe the performance. The experimental setup is pictured below, along with the plot of the resulting titration.

Although the curves showed a slight distortion, they followed the expected trend and produced a linear calibration plot. Dirt was obtained and mixed in with the buffer solutions; the experimental setup is shown below.

This yielded a very interesting titration plot, unlike any that had been seen before:

Typically for reflective pH patches, the peak is observed at 620nm and the baseline correction is done at 509nm. In this case, however, we see the peak had shifted closer to 635nm, and the 509nm region was distorted completely. As a result, 750nm was used as the baseline correction wavelength, which produced an incredibly linear calibration plot, as seen below.

This application has been critical in determining the effect of turbidity on the absorbance curves for the reflective pH patches, and has concluded that the correct wavelengths for acquisition and baseline need to be chosen based on the nature of the analyte solution.

Algorithm Used:

Method:
Fluorescence

Hardware Used:
USB2000-FL (USB2E3295)
USB-LS-450 (U45EA229)
CUV-ALL-UV
P400, P600, P1000 UV/VIS optical fibers

Acquisition Parameters:
Integration Time: 100 msec
Spectra Averaged: 1
Boxcar Smoothing: 10

Measurement Mode:
Fluorescence

Experimental Conditions:
10 uM fluorescein contained in a disposable cuvette (CVD-UV1S) (cuvette oriented with 1 cm pathlength towards spectrometer)

Results:
Fluorescein fluorescence measured with various combinations of 400 to 1000 micron optical fibers is shown in the figure below.

Conclusions:
For fluorescence measurements with the CUV-ALL-UV (90 degree configuration), the optimal optical fiber sizes for detecting fluorescein fluorescence are a 1000 micron fiber on the illumination/excitation side (from light source to cuvette holder) and 1000 micron fiber on the read/detection side (from cuvette holder to spectrometer). As shown in the figure, the use of a 600 micron fiber on the detection side does not have a significant impact on the fluorescence intensity measured.

These results can most likely be extrapolated for other fluorophores meaning ideal fiber sizes for fluorescence measurements are 1000 um fibers.