 is with Analytical Science at Dow Chemical, in Midland, Michigan. Direct correspondence to: 

Xiaoyun Chen

Double metal cyanide (DMC) catalyst is widely used for the alkoxylation reaction to produce polyether polyol from ethylene/propylene/butylene oxides. It is challenging to optimize the synthesis process, due to the lack of real-time understanding of the speciation of the reaction mixture. Powder X-ray diffraction (XRD), transmission electron microscopy (TEM), and actual alkoxylation reaction performance are effective ways for the evaluation of success of each synthesis, but it is difficult to guide process optimization. An in situ Raman method is developed in this study to monitor the DMC catalyst synthesis in real time to accelerate the process optimization. The synthesis involves the reaction of ZnCl

 (ZHCC). ZHCC is then converted to DMC in the presence of excess of t-butanol and ZnCl

 in the second step. Characteristic KHCC Raman peaks were observed at 2138 and 2153 cm

, respectively. This enables realtime tracking of both steps’ conversion. Both t-butanol and ZnCl

 concentrations were found to substantially influence the kinetics of DMC formation, but not the Raman spectra of the final DMC products. The reaction time could be adjusted from hours to minutes through the control of reactant concentrations.

Double metal cyanide (DMC) and potassium hydroxide serve as catalysts for the manufacture of polyether polyols from ethylene oxide (EO), propylene oxide (PO), and butylene oxide (BO). The heterogeneous catalyst, DMC, is replacing the incumbent potassium hydroxide (KOH) technology which requires an added neutralization step (1). Another drawback with KOH catalyst is the competitive side polymerization initiated by allylic alkoxides affecting the polyol end properties, but this can be resolved by using DMC. The DMC technology has a reduced “footprint” compared to KOH, as it has lower unreacted oxide concentrations (hence safer design), lower capital and maintenance costs, and reduced energy consumption.

DMC catalyst technology was developed in the 1960s; however, there is still debate over the actual structure of the Lewis acid and the active site for alkoxylation. The quality of DMC is highly sensitive to the method of preparation and is dictated by a combination of factors: order and rate of addition of reactants, type of agitation, concentration of reactants and rinse solutions, and mixing time. A potential risk with making DMC is the final material can be inactive. Synthesizing DMC in a reproducible manner is therefore the first step in de-bottlenecking the scale-up process. In the invention by Kuyper and associates, it is noted that alkali metal ions, in particular sodium and potassium ions, act as catalyst poisons in the polymerization reaction of epoxides using DMC catalysts (2). Another observation by Le-Khac is the necessity to wash away potassium chloride (KCl), as it will render the catalyst inactive if not removed (3). Based on prior literature, catalyst characterization is carried out after the entire work flow (multiple washing and drying steps) which is time- and effortintensive. These characterization tools typically include X-ray powder diffraction, elemental analysis, and scanning electron microscopy (4).

Huang and associates synthesized DMC with various water soluble Zn salts such as zinc chloride, zinc sulfate, and zinc acetate with complexing agents such as t-butanol, dioxane, tetrahydrofuran, and dimethoxyethane to observe that the DMC made using zinc chloride and t-butanol (t-BuOH) showed highest specific rate of polyether polyol formation (5). Catalytic activity is strongly dependent on the composition of catalysts and the morphology of DMC complexes (6). Several earlier studies demonstrated that Raman spectroscopy can potentially be a sensitive technique to investigate metal cyanides (7–9). In this work, the use of Raman spectroscopy for real-time monitoring of DMC formation is reported, in particular the DMC containing Zn and Co. The following two steps are monitored.

Reaction between potassium hexacyanocobaltate (KHCC) and zinc chloride (ZnCl

) resulting in the formation of zinc hexacyanocobaltate (ZHCC): 3ZnCl

Complexation of ZHCC with t-butanol (t-BuOH) and water in the presence of excess ZnCl

Note that from here on, DMC specifically refers to the active DMC catalyst, but not the KHCC starting material, or the ZHCC intermediate.

In industrial research, it is important to find optimal processes to produce product. Often, many competing fac tors are involved. Therefore, it is challenging to understand how these variables may impact the process. Raman spectroscopy is found to be a powerful tool that yields real-time process information enabling researchers to track reaction conversion without having to carrying out tedious ex situ analysis, and thus, accelerates overall project progress. To demonstrate the utility of in situ Raman spectroscopy for such process development and optimization, two example synthesis routes are included, with DMC-A route being the initial recipe prior to optimization, and DMC-B route being the improved process.

Potassium hexacyanocobaltate (III) (≥ 97.0%), zinc chloride (≥ 98.0%), t-butanol (≥ 99.0%), potassium chloride (≥ 99.0%) were used as received from MilliporeSigma. Zinc hexacyanocobaltate was purchased from Alfa Chemistry.

A design of experiment (DOE) approach was used to explore the vast process variable space. Results from two such experiments are presented to demonstrate the utility of in situ Raman monitoring. These two synthesis protocols will be referred to as DMC-A and DMC-B, with the major difference between them being the relative molar ratio of ZnCl

 to KHCC, the sequence of reagent addition, and also several other process differences as described below.

In Step 1 of DMC-A, aqueous zinc chloride solution (97.5 g, 38.5 wt% ZnCl2) is added at 4 mL/min using a peristaltic pump to a solution containing KHCC and water (222 g, 5.4 wt% KHCC). The process is carried out in a 1 L jacketed glass reactor under atmospheric pressure at 300 in the aqueous solution, which was almost identical to those observed in the solid form. As ZnCl

 solution was added, both peaks diminished in a proportional manner, and concurrently a pair of new peaks at 2185 and 2204 cm

started to gain intensity. These new peaks are believed to be from ZHCC, since their positions closely matched the two lower frequency peaks observed in solid ZHCC at 2192 and 2205 cm

 It can then be inferred based on such results that the 2224 cm

 peak observed in the earlier sample (see Figure 1) is likely from a partially dehydrated material.

 Reference Raman spectra from solid phase ZHCC (blue), t-butanol (green), DMC catalyst (red), and KHCC (orange). Spectra are offset for clarity. Raman intensity in a.u. is the ordinate axis.

The almost identical peak positions of ZHCC to that reported for DMC-I (12) provided strong evidence that the DMC-I in the earlier paper was actually ZHCC hydrate, instead of DMC. A close examination of the reference showed that the DMC-I solid cake was washed with DI water, which is believed to convert DMC back to ZHCC. Such sample preparation induced changes further highlight the importance of in situ analysis for such unstable samples.

The sapphire window gave rise to several sharp features at 378, 418, 431, 450, 577, and 750 cm

. Several other weak features could also be observed between 200 and 300 cm

 solution itself showed a weak feature around 300 cm

 feature was consistent with that of ZHCC catalyst (see red spectrum in Figure 2 for comparison). It should be noted that, although the end ZHCC signal appeared to be substantially weaker than that of starting KHCC, this was mostly due to the decrease in the sampling volume as the system changed from a clear KHCC solution to a highly turbid ZHCC suspension. Such a turbidity change also led to the suppression of the water signal above 3000 cm

 Representative spectra from Step 1 synthesis during ZnCl2 solution addition to KHCC solution. Inset shows an enlarged view of the C≡N stretching region. Raman intensity in a.u. is the ordinate axis.

Figure 3 shows representative spectra from DMC-A during the ZHCC to DMC conversion. The number in the figure refers to the spectrum number, with 115 being the first spectrum collected during this stage. All spectra are normalized to the t-BuOH 750 cm

 peak for ease of comparison. A monotonic decrease of the ZHCC peaks at 2185 and 2206 cm

 was observed concurrent with a monotonic increase of the DMC peaks at 2203 and 2225 cm

, spectral changes corresponding to the ZHCC to DMC transformation could also be observed, though they were of weaker intensity and sitting on a large slope of a strong feature (unknown origin).

Representative spectra from Step 2 synthesis. Labels specify the time of spectral collection after the t-BuOH addition. Raman intensity in a.u. is the ordinate axis.

The close proximity of the DMC and ZHCC CN stretch peaks would lead to significant inter ference based on simple peak area analysis. As a result, classical least squares (CLS) analysis was used for spectral deconvolution (13,14). The two pure component spectra used were the starting ZHCC spectrum and the end spectrum of the final DMC product. The 2160 to 2240 cm

spectral region of each reac tion spectrum, after a linear baseline correction, is assumed to be a linear combination of these two pure component spectra. The weight, or CLS response, of both components can then be used to track their relative concentration more effectively than univariate spectral analysis such as peak height or area. Figure 4 shows the CLS response of the ZHCC and DMC components.

Time-dependent ZHCC to DMC transformation as reflected by the CLS response of the two components from a representative reaction (DMC-A).

The rate of ZHCC to DMC conversion appeared to accelerate in the first 40 min of the reaction, presumably due to the continuous feed of ZnCl

 during this period, which led to a faster reaction rate. Upon completion of ZnCl

 feed, the conversion continued but at a slower rate, though the rate appeared to increase about 5 hours into the reaction, and full conversion appeared to be reached after about 15 hours.

DMC-A is time-intensive and thus costly to scale up as an industrial process. Based on reaction kinetics insights from both the in situ Raman results and other complementary tools, a new DMC-B procedure is identified. Instead of adding tBuOH in a separate step, it is included initially in the solution. A higher ZnCl2 concentration was also used. These process changes led to a greatly accelerated process. Figure 5 shows the representative reaction spectra from synthesis of DMC-B. The overall spectral changes are consistent with those observed in DMC-A, with KHCC bands first giving way to transient ZHCC bands (similar to that observed in DMC-A Step 1) which eventually all converged to DMC bands (similar to that observed in DMC-A Step 2).

Representative reaction spectra from DMC-B. Raman intensity in a.u. is the ordinate axis.

The rate of reaction for DMC-B was an order of magnitude faster than that observed for DMC-A, as clearly illustrated by comparing Figure 4 to Figure 6. The ZHCC signal appeared to be completely consumed after 0.5 hr, which coincided with the DMC signal reaching its maximum.

 Time-dependent KHCC, ZHCC and DMC CLS profiles from DMC-B.

In situ Raman was used to monitor the DMC synthesis for the first time. Characteristic CN stretch bands were identified from KHCC, ZHCC, and DMC, enabling real-time tracking of the reactions throughout the KHCC to ZHCC and finally to DMC stages. While the KHCC to ZHCC appears to be robust and straightforward, the ZHCC to DMC reaction is demonstrated to be more sensitive to process conditions. The use of the in situ Raman method was especially useful in this study because it eliminated the need of multiple sample withdrawal for off-line analysis. Real-time reaction progress information from in situ Raman results enabled researchers to accurately determine the reaction end point. Even though conventional off-line analytical tools such as XRD, TEM, and actual alkoxylation reaction performance test are needed to fully characterize the final DMC catalyst product, in situ Raman results accelerated the completion of the DOE study, which drastically reduced reaction time from more than 10 hours to about 0.5 hours. This study clearly demonstrates the power of in situ Raman monitoring of industrial processes.

(1) Herzberger, J.; Niederer, K.; Pohlit, H.; Seiwert, J.; Worm, M.; Wurm, F. R.; Frey, H. Polymerization of Ethylene Oxide, Propylene Oxide, and Other Alkylene Oxides: Synthesis, Novel Polymer Architectures, and Bioconjugation. 

 2170–2243 (2016). DOI: 10.1021/acs.chemrev.5b00441

(2) Kuyper, J.; Schaik-Struykenkamp, P. v. Process for the Polymerization of Epoxides. U.S. Patent US4472560A, 1984.

(3) Le-Khac, B. Highly Active Double Metal Cyanide Catalysts. U.S. Patent US5482908A, 1996.

(4) O’Connor, J. M.; McAdon, M. H.; Laycock, D. E. 

New DMC Catalysts for Manufacturing Polyols. In API Polyurethanes Expo 2001.

(5) Huang, Y. J.; Qi, G. R.; Chen, L. S. Effects of Morphology and Composition on Catalytic Performance of Double Metal Cyanide Complex Catalyst. 

 263–271. DOI: 10.1016/S0926-860X(02)00452-0

(6) Kim, I.; Ahn, J.-T.; Ha, C. S.; Yang, C. S.; Park, I. Polymerization of Propylene Oxide by Using Double Metal Cyanide Catalysts and the Application to Polyurethane Elastomer.

 3417–3428. DOI: 10.1016/S0032-3861(03)00226-X

(7) Lukey, G.; Van Deventer, J.; Huntington, S.; Chowdhury, R.; Shallcross, D. Raman Study on the Speciation of Copper Cyanide Complexes in Highly Saline Solutions. 

 233–244. DOI: 10.1016/S0304-386X(99)00047-X

(8) Cho, K.; Jang, Y. S.; Gong, M.-S.; Kim, K.; Joo, S.-W. Determination of Cyanide Species in Silver and Gold Plating Solutions by Raman Spectroscopy. 

 1147–1151. DOI: 10.1366/000370202760295377

Infrared and Raman Spectra of Inorganic and Coordination Compounds.

(10) McAllister, W. A. Raman Spectrum of Potassium Hexacyanocobaltate (III). 

(11) Swanson, B. I. Aspects of the Structure and Bonding in Prussian Blues. Single-Crystal Raman Study of Trimanganese Hexacyanocobaltate Hydrate (Mn

O) and Tricadmium Bis(hexacyanocobaltate) Hydrate (Cd

(12) Sebastian, J.; Darbha, S. Structure-Induced Catalytic Activity of Co–Zn Double-Metal Cyanide Complexes for Terpolymerization of Propylene Oxide, Cyclohexene Oxide and CO

(13) Haaland, D. M.; Easterling, R. G. Application of New Least-Squares Methods for the Quantitative Infrared Analysis of Multicomponent Samples. 

 665–673. DOI: 10.1366/0003702824639114

(14) Haaland, D. M.; Easterling, R. G.; Vopicka, D. A. Multivariate Least-Squares Methods Applied to the Quantitative Spectral Analysis of Multicomponent Samples. 

 is with Analytical Science at Dow Chemical, in Midland, Michigan. 

Mrunmayi Kumbhalkar, Jason Fisk, and Brian Murdoch

 are with Engineering & Process Sciences, at Dow Chemical, in Midland, Michigan. Direct correspondence to: 

Articles

Double metal cyanide (DMC) can be monitored in real time using 
an in situ Raman spectroscopy method. In this study, real-time reaction 
progress information from in situ Raman results enabled researchers 
to accurately determine the reaction end point of DMC.

In situ Monitoring of Double  Metal Cyanide (DMC) Catalyst  Synthesis by Raman Spectroscopy

Have you used Raman spectroscopy? If not, you’re really missing out, and now is a great time to try. Raman spectroscopy has come a long way since its discovery in the 1920s. Named after the Indian scientist C. V. Raman, who won the 1930 Nobel Prize in physics, Raman spectroscopy had remained for a long time mostly a specialized tool only accessible to trained scientists. Since the early 2000s, however, advances in laser technology, fiber optics, and grating technology have come together to break down technology barriers and revolutionized and democratized Raman spectroscopy technology.

Most modern Raman spectroscopy instruments focus a laser beam to a tight focal point where Raman signals are generated. The back-scattered signals are then collected and dispersed using a grating onto a charge-coupled device (CCD) camera to generate Raman spectra. Such vibrational spectra contain information similar and complementary to that provided by infrared spectroscopy. The sampling mode in Raman spectroscopy is highly versatile, and can be achieved using microscopes or probes in both contact and non-contact fashion, and even in a remote-sensing setup. The development of these versatile sampling capabilities has enabled users to carry out many unique types of analysis not previously possible, such as the non-invasive analysis of historical paintings or archaeological artifacts.

Advances in chemometrics, big data, and artificial intelligence are now enabling maximum extraction of the rich information embedded in Raman spectra. Compared to separations-based analytical technologies such as gas chromatography (GC) and liquid chromatography (LC), chemical resolution by Raman spectroscopy is achieved through analyte spectral separation, rather than through physical separation of analytes via the use of separation columns. Analysis of convoluted spectra has often been a bottleneck in Raman spectroscopy, but this challenge is being addressed through the use of the abovementioned computational tools.

Raman spectroscopy has found its way into numerous application fields, a number of them shown in Figure 1. The reason behind such a wide range of successful applications stems from the robustness and versatility of modern Raman spectrometers, as well as the rich information available from the Raman spectra. Robust and miniaturized Raman instruments enable users to deploy Raman spectroscopy not only in everyday life, such as for the analysis of microplastics and the identification of unknown substances by law enforcement, but also in remote reaches of science, such as deployment on the Mars rover to study the geology of the red planet.

Numerous commercial options for portable and handheld Raman spectrometers are available. This range of options makes it a “buyers” market for users interested in exploring Raman spectroscopy for their own unique applications, but may also make it a daunting task to select the right tool. Interested readers are recommended to find expert opinions on such topics from professional organizations such as the Society for Applied Spectroscopy (https:// www.s-a-s.org/index.html) and the Coblentz Society (http://www.coblentz.org/).

Raman spectroscopy is a maturing technology, and there are many areas under active academic and industrial investigation. For example, surface enhanced Raman spectroscopy (SERS) enables orders-of-magnitude improvements in detection limits. Spatially offset Raman scattering (SORS) allows chemical analysis of objects beneath opaque packages. Tip-enhanced Raman spectroscopy (TERS) overcomes the diffraction limit and offers chemical information with a spatial resolution on the order of tens of nanometers. From the nanoscale to microscopy to applications of handheld and portable instruments to analyzing industrial-scale reactions, Raman spectroscopy is a widely used and valuable analytical technique.

Raman Spectroscopy

) is a highly reactive oxidant, and its reactions with polyethylene fibers in chlorinated solvents can be used to functionalize and stabilize the polyethylene fibers for subsequent carbonization to produce carbon fiber. In this study, the apparent reaction kinetics between SO

 and polyethylene were investigated in various halogenated solvents using in situ Raman spectroscopy with an immersion Raman probe. This work demonstrates the power of in situ Raman spectroscopy to monitor hazardous reactions, and the results show that both solvent and polyethylene properties have a large influence on the reaction kinetics.

	Carbon fiber is being used in an increasingly wider range of applications, such as in light structural materials and polymer composites (1–5). Polyethylene (PE) has been suggested to be a lower-cost precursor material to carbon fibers than the traditional precursor polyacrylonitrile (PAN). Polyethylene fibers can be converted to carbon fibers by a stabilization step (by sulfonation) followed by a carbonization step (1,6–10). Sulfur trioxide (SO

) in halogenated solution was proposed to be an effective way for the stabilization and sulfonation of polyethylene (11).

	The main hypothesized sulfonation reaction is shown in Figure 1a. Various side reactions can also occur as shown in Figures 1b and 1c, and will sequester SO

 that is then unavailable for the main sulfonation reaction (Figure 1a). Knowledge of the SO

 solution concentration is of vital importance because it affects the reaction rate and process economics. However, the high reactivity of SO

 makes this reaction difficult to monitor by off-line analysis, because SO

 readily reacts with water to form sulfuric acid (H

), and traditional titration methods cannot differentiate between SO

. Raman spectroscopy was found to be a powerful tool that allowed in situ monitoring of key reaction species in the solution phase such as SO

	Raman spectroscopy has previously been applied to study the molecular structure and oligomerization of SO

 (14–16) Furthermore, a Raman method has been developed to determine the concentration of SO

 in the gas phase. This article describes a calibration method that was first developed to quantify SO

 in halogenated solvents based on a classical least squares (CLS) fit of Raman spectra. This calibration was then applied to monitor the SO

 reaction with polyethylene fibers with a goal to understand the influence of various experimental variables such as the polyethylene density, branching, and crystallinity (three properties interrelated to each other), and the reaction-solvent type. Scanning electron microscopy and X-ray energy-dispersive spectroscopy (SEM-XEDS) was used as a complementary tool to directly obtain the radial sulfur distribution from thin sections of polyethylene fibers as a function of sulfonation time. 

	Polyethylene fibers were prepared from three types of Dow proprietary polyethylene resins with different crystallinity and density. These three fibers will be referred to by their densities, with PE-950, PE-926, and PE-917 having a density of 0.950, 0.926, and 0.917 g/mL, respectively. Polyethylene fibers were melt spun using a Hills Inc. commercial melt spinning line. The resulting fibers were ~20 µm in diameter with a tenacity of ~2 g/denier. SO

 was received from Aldrich in 40-g lots in solid form in glass bottles. To be able to transfer the SO

 in a safe fashion, the bottles were stored in a low-temperature oven in a vented hood at 37–39 °C with the appropriate high-temperature cut-off safety features (monomeric SO

 is in its liquid form, it is easily manipulated in a well-vented hood (significant fuming is always evident) for dissolution into inert solvents. SO

 is exceedingly hazardous: inhalation or contact with skin results immediately in severe burns.

	Several halogenated solvents were investigated in this study: 1,2-dichloroethane (ClCH

). All solvents were acquired from Aldrich and were used as received.

	A Kaiser RXN1 Raman spectrometer with 785-nm laser excitation was used with a fiber-optic probe. A Kaiser 0.25-in. diameter short-focus immersion optic was used to collect signals in the backscattering geometry. The signal was dispersed by a grating and projected onto a charge-coupled device (CCD) camera for spectral collection. The body of the immersion optic was made of Hastelloy C alloy and the tip of it was sealed with a sapphire window. No corrosion was observed even after multiday experiments. Typical laser power ranged from 100 mW to 400 mW, and typical spectral acquisition conditions were 1-s exposure time with 10 accumulations and with the cosmic ray filter on (20 s per spectrum). In some reactions, strong fluorescence was observed and the exposure time was shortened correspondingly. All experiments were carried out at room temperature (unless otherwise specified) with stirring inside a customized glass reactor. Care was taken to ensure that the laser beam was not focused onto a sulfonated fiber; otherwise overwhelmingly strong fluorescence would result. 

	Spectral visualization was performed using OMNIC 8.2 software (Thermo Fisher Scientific Inc.). Because of spectral overlapping, quantitative analysis was carried out using a CLS algorithm as implemented in MATLAB. Details of the CLS method can be found elsewhere (17–19).

	The polyethylene fiber surface turned brown and then black during its reaction with SO

, and the solution remained clear. The surface color change is believed to be mostly due to the formation of the conjugated double bond system shown in Figure 1a. Attempts to collect Raman spectra from the fiber surface were made but strong fluorescence overwhelmed the Raman signal. As a result, all the Raman spectra were collected from the solution-phase composition change to monitor the reaction progress. The majority of the reactions were carried out in DCE. Several other halogenated solvents were tested. Some of them showed a fast reaction with SO

, and others showed negligible reaction. Several other inert solvents were also tested as reaction solvents. The calibration results obtained in the DCE solution are discussed below. As a complementary tool, SEM-XEDS was used to directly measure the sulfur distribution on the cross sections of partially sulfonated polyethylene fibers, and those results are also discussed below.

	A quantitative method was needed to monitor the SO

 generation in the solution phase during the polyethylene and SO

 reaction. Standard spectra of pure DCE solvent, 3 wt% SO

 in DCE are shown in Figure 2. At such concentrations, SO

 exist mostly in their free monomer form as indicated by the strong 1066 cm

 (16,20–22). DCE was the initial solvent selected for this study because of its compatibility with SO

. Its Raman spectrum is consistent with that previously reported (23) and had a peak at 1054 cm

	Because of the severe spectral interference from DCE, a CLS model was developed to deconvolute the spectra for quantitation of SO

 concentrations. The CLS algorithm uses a linear combination of all the pure component spectra to reproduce a reaction spectrum by minimizing the sum of squares of the differences (19,24). The CLS response, also referred to as the 

, is proportional to the concentration of the corresponding species. The spectral range between 1000 and 1250 cm

 was used for the CLS analysis with the spectra of three pure components: DCE, and the SO

 solution spectra after subtraction of solvent contributions. For the quantitation of SO

, their CLS responses were normalized by the DCE solvent CLS response. The normalized CLS response ratios were found to be linearly proportional to the weight ratio of SO

 to DCE solvent within a certain concentration range (<10 wt%). The reason for such a limited concentration range is that in addition to free monomer, SO

 may exist in forms such as dimer, trimer, tetramer, or polymers, and each form has different Raman features (13). An example of such a correlation is shown in the inset plot in Figure 2. When the SO

 concentration was sufficiently high, a nonlinear correlation behavior was observed because of dimer and oligomer formation.

 concentrations can be determined using the method described above. Raman spectra collected as a function of reaction time could thus be used to monitor the sulfonation reaction of polyethylene fibers. Representative reaction spectra from an example reaction are shown in Figure 3. In this experiment, 106 mg of PE-926 fiber (0.025 g/m) was reacted with 1.75 g of SO

 dissolved in 14.54 g of DCE. Upon contact, the fiber surface quickly darkened in color (25), and the solution remained mostly colorless. The consumption of SO

 can be seen clearly in the inset spectra in Figure 3. The CLS model and calibration were applied to the reaction spectra so that the concentrations of SO

 could be calculated. Based on the main reaction shown in Figure 1a, the amount of polyethylene should lead to the consumption of only approximately 35% of the starting SO

 consumption was much higher, indicating that a significant consumption resulting from side reactions occurred. The observed concentration increase of SO

 was also greater than the 1.5% concentration expected if only the main reaction shown in Figure 1a was operable. Although the overconsumption of SO

 readily could be explained by the side reactions (Figures 1b and 1c), the reaction mechanism responsible for overgeneration of SO

	With such a method, it became possible to gain a deeper understanding of the influence on the reaction kinetics of various key process variables such as crystallinity, fiber diameter, and solvent type. To further aid the comparison of reaction kinetics, the SO

 concentrations were converted to extent of conversion, assuming only the main reaction shown in Figure 1a occurred. The conversion can then be calculated based on the amount of polyethylene, which was always the limiting reagent (that is, the number of moles of SO

- repeating units in polyethylene). Figure 4 compares the reaction conversion for three experiments with similar conditions but with three different polyethylene fibers (with similar diameter) in terms of SO

 production. It is obvious that the PE-950 fiber, with the highest crystallinity, exhibited the slowest reaction, and a reaction with an overall lower extent was noted when the profiles plateaued.

	Similarly, the influence of solvent type on the reaction kinetics was investigated. Only solvents that showed negligible reactivity toward SO

 (see next section) were used. Five reactions using the same type of polyethylene fiber and a similar starting amount of SO

 and polyethylene were carried out in various inert solvents (see the next section). Figure 5 compares the percentage of SO

 remaining (after normalizing against the starting concentration). The type of solvent appeared to have a large influence on the reaction kinetics. The same type of methodology was used as outlined above for the SO

–DCE mixture system to develop CLS models for the SO

 quantitation for each solvent system (or using peak area if a solvent spectrum did not interfere with the SO

 peak), but the details are not shown here. In all five reactions, the SO

 solution was added into the reactor shortly after time 0. The consumption rate appeared to be the slowest with DCE as the solvent. When methylene chloride was used as the solvent, a significantly faster reaction rate was observed. It was hypothesized that such a rate increase might be a result of partial swelling by methylene chloride (26,27). To test this hypothesis, another experiment was performed by pre-immersing polyethylene fibers in methylene chloride and then immediately carrying out the reaction with SO

 in a DCE solution. Almost identical reaction kinetics were observed, disproving the swelling hypothesis. In another experiment, a mixture solvent with 1:1 (w/w) DCE and methylene chloride was used; the initial kinetics profile resides between that of the pure DCE and of pure methylene chloride. Among all the solvents tested, 1,1,2,2-tetrachloroethane appeared to facilitate the reaction most effectively.

SEM-XEDS Characterization of Sulfonated Fiber Cross-Sections

	SEM-XEDS analysis was used to directly measure the radial sulfur distribution within the polyethylene fiber as a way to monitor the extent of sulfonation with time. This information is less quantitative but complementary to the solution concentration provided by the Raman results. Fibers withdrawn after various lengths of sulfonation time were immediately placed into a water bath to quench the reaction and then were prepped for analysis.

	Figure 6 shows a comparison of radial distributions of S/Cl ratio for PE-926 and PE-950 fibers sulfonated for 25 and 60 min after immersion in a 1.58 M solution of SO

 in DCE. The slower rate of sulfur concentration increase in the PE-950 fiber relative to the PE-926 fiber is clearly shown, suggesting that the sulfonation reactions for PE-950 are slower. In fact, the overall magnitude of sulfur in the PE-926 fiber after only 25 min was greater than that observed in the PE-950 fiber after 60 min of sulfonation. These observations are consistent with the differences in reaction rates observed via Raman spectroscopy as shown in Figure 4. These results clearly demonstrated that the reaction kinetics between SO

 and polyethylene are sensitive to the polyethylene material’s density, branching, and crystallinity, which are three properties closely related to each other.

	In situ Raman spectroscopy was used to monitor the SO

 generation in DCE and other chlorinated solvents during polyethylene and SO

reactions. CLS analysis was used to quantify the spectral contribution of SO

 in the presence of strong solvent interference. The reaction kinetics data could thus be obtained from the solution-phase measurements when different types of polyethylene reacted with SO

 in various solvents. It was found that solvent type and polyethylene crystallinity, density, and branching have a substantial influence on the reaction kinetics. The exact mechanism behind such influences remains to be investigated and is likely related to diffusion and mass transfer limitation. Complementary SEM-XEDS measurements of sulfur distribution within the polyethylene fiber as a function of time were also obtained to further confirm these results. This study clearly demonstrates the power of in situ Raman spectroscopy to monitor these hazardous reactions.

		E. Frank, F. Hermanutz, and M.R. Buchmeiser, 

		E. Thostenson, W. Li, D. Wang, Z. Ren, and T. Chou, 

		W. Jonda, “Lightweight structural part formed of carbon fiber-reinforced plastic” (Google Patents, 1978).

		M. Tavakkolizadeh and H. Saadatmanesh, 

 (Butterworth-Heinemann, Oxford, UK, 2012).

		J.M. Younker, T. Saito, M.A. Hunt, A.K. Naskar, and A. Beste, 

		A.R. Postema, H. De Groot, and A.J. Pennings, 

		S. Horikiri, J. Iseki, and M. Minobe, “Process for production of carbon fiber,” Patent US4070446 A, 1978.

		J.T. Patton, B.E. Barton, M.T. Bernius, X. Chen, E.J. Hukkanen, C.A. Rhoton, and Z. Lysenko, “Processes for preparing carbon fibers using sulfur trioxide in a halogenated solvent,” Patent WO2014011462 A1, 2013.

		Y. Song, Z. Liu, H.-K. Mao, R.J. Hemley, and D.R. Herschbach, 

		D.M. Haaland, R.G. Easterling, and D.A. Vopicka, 

Handbook of Infrared and Raman Spectra of Inorganic Compounds and Organic Salts: Infrared Spectra of Inorganic Compounds

 (Academic Press, Cambridge, Massachusetts, 2012).

		E.T.H. Chrysostom, N. Vulpanovici, T. Masiello, J. Barber, J.W. Nibler, A. Weber, A. Maki, and T.A. Blake, 

		A.J. Dorney, A.R. Hoy, and I.M. Mills, 

		S. Mizushima, T. Shimanouchi, I. Harada, Y. Abe, and H. Takeuchi, 

		K.R. Beebe, R.J. Pell, and M.B. Seasholtz, 

(Wiley-Interscience, Secaucus, New Jersey, 1998).

		A. Peterlin, J.L. Williams, and V. Stannett, 

 are with Analytical Sciences at The Dow Chemical Company in Midland, Michigan. 

 work in the organic polymer and organometallic group at The Dow Chemical Company. Direct correspondence to: 

The apparent reaction kinetics between SO3 and polyethylene are investigated in various halogenated solvents using in situ Raman spectroscopy with an immersion Raman probe, demonstrating the power of in situ Raman spectroscopy to monitor hazardous reactions.

Xiaoyun Chen

Articles

In situ Monitoring of Double Metal Cyanide (DMC) Catalyst Synthesis by Raman Spectroscopy

Raman Spectroscopy

In Situ Raman Spectroscopy Monitoring of the Reaction of Sulfur Trioxide with Polyethylene Fibers in Chlorinated Solvents