) surface, which is critical for its catalytic activity, has been determined using ultrahigh-vacuum Fourier transform infrared (FT-IR) spectroscopy equipment dedicated to the spectroscopic characterization of oxides, single crystals, and powders. IR data achieved for powder particles can be compared directly for the first time with a single crystal reference system. By combining these experimental results and the density functional theory calculations, the accordant catalytic activity of the oxide surface can be deduced. 

The fundamental advantage of using Fourier transform infrared (FT-IR) spectroscopy in vacuum is that the absorption of atmospheric moisture and other gas species (CO

) is avoided. Vacuum spectrometers provide a better stability and reproducibility in comparison to dry air or nitrogen-purged spectrometers. Furthermore, their ability to operate under ultrahigh-vacuum (UHV) conditions allows IR characterization of samples that have to be prepared and stored under UHV conditions without sample-transfer in air, and, therefore, enables the close combination of the FT-IR technique with other UHV experimental methods.   

The defect density on an oxide surface is crucial for its catalytic activity. Understanding the role of the defects in particular is the precondition for investigating numerous catalytic reactions in detail. Recently, the oxygen defects on titanium dioxide (TiO

) have been considered using scanning tunneling microscopy (STM) combined with density functional theory (DFT) calculations (1–8). Unfortunately, many standard experimental techniques in this research field can be applied only to single crystalline oxides in a straightforward fashion, but not to powders or nanoparticles, which are technologically the most important forms of oxide materials. In contrast, FT-IR spectroscopy is not limited to only the single crystalline phase, but can also be applied to powders, nanoparticles, and so forth (9). Therefore, UHV-FT-IR spectroscopy was applied to both the well-understood single crystal reference system and the powder particles, to determine the density of O vacancies and to demonstrate the role of O vacancies for the surface chemistry of formaldehyde on TiO

. For this purpose, CO was used as a probe molecule to identify the defect sites on a rutile TiO

A newly established UHV-FT-IR apparatus dedicated to the spectroscopic characterization of oxides, single crystals, and powders has been used in this work. It combines a Bruker Vertex 80v vacuum FT-IR spectrometer with a Prevac UHV system consisting of load-lock, preparation, distribution, measurement, magazine, and analysis chambers. The UHV system enables additional characterizations using combined measurement techniques, such as X-ray photoelectron spectroscopy, ultraviolet photoelectron spectroscopy, Auger electron spectroscopy, low energy electron diffraction, and thermal desorption spectroscopy. The FT-IR experiments on the r-TiO

 single crystal and powder samples were performed in the UHV chamber dedicated for IR measurements, which was internally adapted in the sample compartment of the spectrometer. The adaptation is achieved by vacuum-compliant window flanges that are mounted directly to the window fitting of the UHV chamber. The spectrometer can be demounted from and attached to the UHV-IR chamber by sliding it backwards and forwards along its supporting frame. The system's entire optical path is evacuated to avoid absorption of atmospheric moisture and other background signals from the gas phase (CO

), thus providing the possibility to record IR data with the highest sensibility and stability. This is an essential prerequisite for monitoring molecular species adsorbed on oxide surfaces, because the optical properties of oxides result in a decreased signal-to-noise ratio (S/N) by one to two orders of magnitude relative to metals. A spectrometer internal motorized off-axis paraboloidal mirror in front of the spectrometer sample compartment together with another motorized 90° off-axis ellipsoidal mirror adjusted to the detector can be driven in two positions for transmission (powders) and IR reflection absorption spectroscopy (IRRAS) measurements at grazing incidence with an incident angle of 80° to surface normal (for flat substrates such as single crystals) (11).  

 (110) single crystalline surface was cleaned with several cycles of an Ar ion sputtering and heating procedure up to 800 K in an O

/g) were pressed against a gold-coated stainless steel grid (0.5 cm × 0.5 cm) and fixed on a sample holder. The grid was then heated at 700 K in the UHV chamber to remove contaminants such as water and OH groups. The low-vacancy (perfect) surface of the powder sample was achieved by exposing the powder to a small amount of oxygen in UHV at 110 K. The reduction was carried out by controlled sputtering or over-annealing at an elevated temperature (900 K) to produce O vacancies. To identify the defects, CO was adsorbed onto a perfect and reduced r-TiO

 single-crystal measurements were performed using IRRAS and the data for powder samples were recorded in transmission geometry. All spectra were measured with comparable parameters, 1024 scans, and a resolution of 4 cm

Figure 1 presents a surface structure model of r-TiO

 (10). As supported by calculations and previous works, the exposed CO molecules will populate only the adsorption sites labeled 1 and 2 in Figure 1 (and sites located further away from the O vacancy), but will not bind to the Ti atoms exposed within or next to the O vacancy (labeled 0) (12).  

Figure 1: Ball-and-stick model of the r-TiO2 surface. The CO molecules adsorbed at different Ti sites (labeled 0â5) are sketched. Adapted from reference 10.			

The IRRAS data shown in Figure 2 (left) demonstrate that on a fully oxidized (perfect) r-TiO

 surface with a low density of defects only one absorption band at 2188 cm

  is visible in the CO-stretching regime related to CO adsorbed on perfect parts of the surface (labeled 2–5 in Figure 1), whereas on reduced r-TiO

  appears, which is assigned to CO bound to Ti cations located on sites labeled 1 in Figure 1. To corroborate the assignment of the band at 2178 cm

, we blocked the sites close to the O defects by exposing the substrates to small amounts of O

 at 110 K. Previous work has shown that under such conditions molecular O

 adsorbs exclusively at oxygen vacancies (7,13,14). As expected, in the IR spectra recorded after such substrates with preadsorbed O

 were exposed to CO at 110 K, the band at 2178 cm

  was found to be strongly reduced relative to the band at 2188 cm

. DFT calculations with the vienna ab initio simulation package (VASP) program support our deduction, that CO molecules only occupy the adsorption sites 1 and 2 labeled in Figure 1. On the basis of the intensity ratio of the two bands (at 2188 cm

) and considering the maximum coverage of CO on r-TiO

 at 110 K (0.5 monolayer) (15), the concentration of O vacancies can be estimated to an amount of around 10%.  

Figure 2: Left: IRRAS data for CO adsorbed on perfect and reduced r-TiO2 single-crystal surface at 110 K. The absorbance amounts to 10-5 AU. Right: UHV-FT-IR data for CO adsorbed on (a) oxidized and (b) reduced r-TiO2 powder particles at 110 K recorded in transmission mode. Adapted from reference 10.			

The same procedure was applied to the r-TiO

 powder particles. The FT-IR spectra are shown in Figure 2 (right). On oxidized powder particles (Figure 2a, right) only one absorption band at 2184 cm

  related to CO bound to Ti cations distant to O vacancies or other defects was detected. On reduced powder particles (Figure 2b, right) a new band appears at 2174 cm

  related to CO adsorbed on site 1, which is in accordance with the IRRAS data for  r-TiO

 single crystal surface. Furthermore, the defect density on the powder particles can be calculated from a comparison of the relative band intensities and amounts to about 8%.  

To demonstrate the potential of this established method for determining defects densities in a semiquantitative fashion, the reductive coupling of formaldehyde to ethylene catalyzed by TiO

, an important C-C coupling reaction was investigated. IRRAS experiments on differently treated r-TiO

 powder samples were carried out. After exposure of fully oxidized powder particles to formaldehyde at 400 K, no adsorbate-induced absorption bands could be detected (Figure 3b), indicating that CH

O adsorbed at perfect Ti cation sites is not stable at 400 K. In contrast, UHV-IR results recorded for reduced r-TiO

 powder particles after exposure to formaldehyde at the same temperature reveal a distinct IR band at 1040 cm

  (Figure 3c), which can be assigned on the basis of the previous data for single-crystal r-TiO

 (110) surface to the C-O stretching vibration within a surface-bound C

O-) formed by activation of formaldehyde at O vacancy sites. Upon heating to 600 K, the diolate-related IR band disappears (Figure 3d) as a result of the ethylene formation and the subsequently desorption from the particle surface (16). Only on the reduced powder was the intermediate of the catalyzed surface reaction identified and the yield of ethylene correlates well with the above estimated density of defects on the r-TiO

Figure 3: UHV-FT-IR data obtained for r-TiO2 powder samples. (a) Clean r-TiO2 powder. Powder was (b) oxidized and then exposed to formaldehyde (1 Ã 10-4 mbar) at 400 K; (c) reduced and then exposed to formaldehyde (1 Ã 10-4 mbar) at 400 K. (d) The sample form (c) was heated to 600 K before the spectrum was measured. All UHV-FT-IR spectra were collected in transmission mode at 110 K. Adapted from reference 10.			

Combined experimental and computational investigation methods were used to estimate the defect density on a rutile surface, which indicates its catalytic activity. UHV-IR data from both single crystal and powder r-TiO

 have been collected and compared with each other for absorption bands assignment. The design of the UHV-FT-IR apparatus enabled comparable measurement conditions in both reflection (for single crystal) and transmission (for powder) modes and demonstrated that it can be used in developing methods for the determination of defect densities on catalyst surfaces in a semiquantitative manner.  

The reliability of this method for catalyst activity forecasting has been successfully demonstrated by the C-C coupling reaction catalyzed by TiO

. The reduced catalyst powder with more defects, or rather O vacancies, was proven to exhibit higher activity. Furthermore, the product yield is directly related to the estimated density of defects.   

We greatly thank Professor Dr. Christof Wöll (director of Institute of Functional Interfaces, KIT) and his coworkers for the measurements data and the helpful discussion, whom contributed a lot to the optimization of the UHV-FT-IR apparatus with their valuable feedback and suggestions from the application side.   

 (1) R. Schaub, P. Thostrup, N. Lopez, E. Laegsgaard, I. Stensgaard, J.K. Norskov, and F. Besenbacher, 

 (2) Z. Zhang, O. Bondarchuk, B.D. Kay, J.M. White, and Z. Dohnalek, 

 (3) A.C. Papageorgiou, N.S. Beglitis, C.L. Pang, G. Teobaldi, G. Cabailh, Q. Chen, A.J. Fisher, W.A. Hofer, and G. Thornton, 

 (4) S. Wendt, R. Schaub, J. Matthiesen, E.K. Vestergaard, E. Wahlstrom, M.D. Rasmussen, P. Thostrup, L.M. Molina, E. Laegsgaard, I. Stensgaard, B. Hammer, and F. Besenbacher, 

 (5) S. Wendt, P.T. Sprunger, E. Lira, G.K.H. Madsen, Z.S. Li, J.O. Hansen, J. Matthiesen, A. Blekinge-Rasmussen, E. Laegsgaard, B. Hammer, and F. Besenbacher, 

 (6) O. Bikondoa, C.L. Pang, R. Ithnin, C.A. Muryn, H. Onishi, and G. Thornton, 

 (7) P. Scheiber, A. Riss, M. Schmid, P. Varga, and U. Diebold, 

 (9) C. Lamberti, A. Zecchina, E. Groppo, and S. Bordiga,

(10) M. Xu, H. Noei, K. Fink, M. Muhler, Y. Wang, and Ch. Wöll, 

(11) Y. Wang, A. Glenz, M. Muhler, and Ch. Wöll, 

(12) Y. Zhao, Z. Wang, X.F. Cui, T. Huang, B. Wang, Y. Luo, J.L. Yang, and J.G. Hou, 

(14) M.A. Henderson, W.S. Epling, C.L. Perkins, C.H.F. Peden, and U. Diebold, 

(15) M. Kunat, F. Träger, D. Silber, H. Qui, Y. Wang, A.C. van Veen, Ch. Wöll, P.M. Kowalski, B. Meyer, C. Hattig, and D. Marx, 

(16) H. Qiu, H. Idriss, Y.M. Wang, and Ch. Wöll, 

is a chemist at Bruker Optik GmbH, in Ettlingen, Germany. 

is a lab leader with the Karlsruher Institut für Technologie (KIT) in Eggenstein-Leopoldshafen, Germany.  

Articles

Combined experimental and computational investigation methods are used to estimate the defect density on a rutile surface, indicating its catalytic activity.

FT-IR Spectroscopy in Ultrahigh-Vacuum Conditions: A Surface Science Approach to Understanding Reactions on Catalytic Oxide Powders

When images are measured in reflectance, the observed structure is not necessarily just that of the sample surface. The two-dimensional (2D) images produced by near-infrared (NIR) and mid-IR imaging are representations of three-dimensional (3D) objects. In reflectance images the effective spatial resolution is affected by how far the radiation penetrates into the sample as well as by diffraction and the pixel size. NIR images are typically dominated by diffuse reflection with the result that in practice spatial resolution is limited by the penetration depth. Mid-IR reflectance images may contain both specular and diffuse components. These have different spatial resolutions as the specular component shows purely surface structure. In attenuated total reflectance (ATR) images the resolution has a component that depends on the distribution of components within a surface layer corresponding to the penetration depth, which is proportional to wavelength. We illustrate these different contributions to the observed resolution with images of materials with known 2D and 3D structures. 

What do we measure in reflection? For the majority of samples, transmission measurements are not possible so spectra have to be obtained by reflectance. This involves either external reflection, often divided into specular and diffuse reflection, or attenuated total reflection (ATR). What you see in external reflection is the sum of what is reflected from the surface (specular or Fresnel reflection) and what penetrates into the sample before emerging (diffuse reflection). You see only surface reflection from a continuous uniform material where radiation that penetrates is not scattered back to the surface. Very strongly absorbing materials also show only surface reflection as the radiation that penetrates is all absorbed. With scattering materials some radiation that penetrates the material returns to the surface by encountering interfaces where there is a change of refractive index. The relative amounts of surface and diffuse reflection depend on the absorptivity and particle sizes of the sample and are wavelength dependent. Small particle size and weak absorption increase the amount of diffuse reflection. In practice, diffuse reflection dominates in the near infrared (NIR) whereas spectra in the mid-IR often show significant contributions from both surface and diffuse reflection.   

How does this affect spatial resolution? In an imaging experiment, separate spectra are measured for each pixel while the incident radiation covers the whole area. If reflection comes only from the surface, the spatial resolution should depend simply on diffraction and the pixel size. However, any radiation that penetrates a scattering sample takes a random path through the material and will not all return to the point at which it entered the sample. Thus, the radiation contributing to any pixel in the image is a combination of rays from some volume underneath the point on the surface that is being observed. The deeper the radiation can penetrate into the sample and return without being absorbed, the larger this volume will be. If we assume isotropic scattering, the average lateral displacement from the point of incidence to where the radiation emerges will be similar to the average depth to which the radiation penetrates. This will cause blurring of the image by an amount that depends on the average penetration depth. There have been several attempts to estimate the depth that the radiation penetrates (1,2). These suggest average values in the range of 50–100 μm for NIR observations of materials such as pharmaceutical tablets. As a result, the spatial resolution achieved in NIR reflection images is likely to be in this range. This is in contrast to what is observed with the metal-on-glass reflection targets normally used where diffraction limited spatial resolution is better at the shorter wavelengths of the NIR region than in the mid-IR.  

Figure 1: Diffuse reflection and transmission.			

One way to estimate the penetration depth is by comparing the band intensities in transmission and reflection for a scattering sample. The absorbance is proportional to the distance traveled inside the sample. In transmission, this distance is proportional to the thickness of the sample, but in reflection it is proportional to twice the average penetration depth (Figure 1). One sample used was an acetaminophen tablet ground down to a thickness of 1.1 mm. The ratio of the absorbances at 8800 cm

  measured in transmission and reflection is 18:1. From this, the average penetration depth is calculated as 30 μm (Figure 2). Similar measurements on pressed pellets of other materials give average depths of 40 μm to 60 μm (Table I). Because these are average depths we can conclude that some rays must penetrate significantly further. This will produce blurring of 50–100 μm.  

Figure 2: Spectra of an acetaminophen tablet.			

Measuring Spatial Resolution in Scattering Materials

We prepared a sample by pressing a pellet of microcrystalline cellulose on top of a pressed pellet of polyethylene, giving a flat boundary between the two materials. Microtoming one edge of the pellet in a direction parallel to the interface gave a flat sample with the boundary perpendicular to the surface. Images were obtained with a PerkinElmer Spotlight system with a pixel size of 6.25 μm over the 6000–1400 cm

 range (Figure 3). The spectra include dispersive features characteristic of Fresnel surface reflection such as the polyethylene CH

, strong absorptions such as the broad cellulose OH band at 3500 cm

Table I: Estimated NIR penetration depths			

As expected, an image based on the polyethylene CH

  (Fresnel reflection) has a sharp boundary. In addition, it reveals an anomaly on the surface of the polyethylene layer at a distance of about 50 μm from the interface. An image of the strong cellulose OH absorption at 3600–3400 cm

  shows a similar sharp boundary and indicates that the anomaly results from a flake of cellulose, something that is confirmed from the individual spectra. The sharp boundary illustrates how the strong absorption limits radiation that penetrates the sample returning to the surface. In contrast, the weak absorptions of the NIR region lead to much more diffuse images with features from one layer visible up to 100 μm away from the boundary. The polyethylene layer has significantly less scattering than the cellulose layer, which probably explains why the cellulose features appear to extend farther beyond the boundary.  

Figure 3: Images from a two-layer sample.			

What Is the Penetration Depth in ATR Imaging?

The effective penetration depth is related to the wavelength λ, the refractive indices of crystal and sample 

 is the refractive index of the crystal, θ is the angle of incidence, and 

 is the ratio of refractive indices of sample and crystal. 

In the converging beam of a microscope there is a range of angles of incidence, so it is appropriate to determine the effective penetration depth experimentally. We have compared the absorbance of liquid paraffin measured by ATR and by transmission of a film with known thickness. In the Spotlight system, using a germanium crystal the penetration depth with an organic material of refractive index 1.4 

 is expected to vary from about 0.6 μm at 3000 cm

. Comparison with a transmission spectrum of paraffin oil demonstrates that the equivalent pathlengths for ATR are fairly similar to this (Table II).  

Table II: Effective pathlengths for ATR imaging			

When the boundary between regions is not normal to the surface, the penetration depth will affect the spatial resolution. To demonstrate this we prepared samples consisting of two layers, polystyrene and an acrylic resin. In one the boundary was normal to the surface and in the other the boundary was at 10° to the surface (Figure 4). In the latter, the polystyrene layer 10 μm from the boundary at the surface is 1.8 μm thick. Images of the two were obtained with a pixel size of 1.56 μm.  

Figure 4: ATR images of two-layer samples.			

Images of the two samples show that the edge appears much more diffuse in the sample where the boundary is at 10° to the surface (Figure 4). Penetration through the polystyrene layer allows the acrylic material to be detected up to 10 μm away from the apparent boundary on the surface. Intensity profiles of the acrylic resin at different wavelengths clearly show how longer wavelengths detect the subsurface layer at greater depths. The profile at 1137 cm

  is very unsymmetrical, extending about 15 μm beyond the surface boundary (Figure 5).  

In looking at reflection images it is important to remember that samples are three dimensional and that spectra may be generated from a finite volume, not just from the immediate surface. The boundaries between regions may, therefore, appear broader than those seen in visible images. This is most apparent in near-IR images where the resolution is likely to be limited by lateral scattering within the sample rather than by diffraction or the pixel size. In ATR images, the penetration depth allows spectral contributions to be seen from subsurface material. 

(2) S.J. Hudak, K. Haber, G. Sando, L.H. Kidder, and E.N. Lewis, 

are with PerkinElmer in Seer Green, Bucks, United Kingdom.  

In these types of IR imaging, various factors contribute to the observed resolution. These factors are illustrated with images of materials with known structures.

Spatial Resolution in IR Reflectance Imaging — NIR, Mid-IR, and ATR

The analysis of dynamic systems such as chemical reactions has generally been relegated to "macro" analysis methods. Infrared imaging techniques can provide chemical and spatial information about a sample on a microscale and as the speed of imaging methods improves it is only natural to apply imaging to the analysis of samples that are changing chemically within a defined time scale. This "dynamic imaging" method could be used to probe many different kinds of samples on a defined time scale, providing insights to the kinetics of chemical reactions on a microscopic basis. This paper investigates the use of imaging to study the reaction process involved in the curing of a cyanoacrylate adhesive. 

The use of "time-resolved" or "dynamic imaging" methods for various samples has been described previously in various texts (1–7). To our knowledge, however, there has not been a comparison of the reaction rates for a macro observation of a chemical kinetics reaction to the same reaction observed on the micro scale. It was of interest to us to review the chemical kinetics observed for the curing of a cyanoacrylate adhesive compound in both the macroscale and microscale (Figure 1) to see if the reaction rates would compare for both observation methods.  

Figure 1: Polymerization reaction sequence of ethylcyanoacrylate adhesive.			

Figure 1 outlines the polymerization reaction of the cyanoacrylate adhesive as it cures. The reaction is initialized by an absorption of an OH group from atmospheric water by the adhesive and the polymerization reaction proceeds continuously until the unpolymerized ethylcyanoacrylate molecules are depleted. The analysis of the polymerization reaction was determined by utilizing Fourier transform infrared (FT-IR) spectroscopy in a time-resolved mode. The spectra were collected as individual macro- or microspectra of the adhesive in a time-based sequence. By collecting several sets of spectra of the adhesive until the completion of the curing reaction, which can take as long as 1300–1800 s, the degree of polymerization was observed in the infrared spectra as the reaction progressed.  

Figure 2: Mid-infrared spectra of ethylcyanoacrylate adhesive at 0 s (blue) and 1000 s (red).			

For the macro experiment, the cyanoacrylate adhesive was spread on a 10 × 10 mm KBr window and another window was placed on top of the adhesive to obtain a uniform layer of the adhesive. Infrared sample spectra were collected using a Jasco FT-IR-6300 instrument at 8 cm

  resolution, utilizing four sample scans per spectrum ratioed against a 256-scan background spectrum. A time resolution of 4 s between sample scans was used to obtain spectra for approximately 1800 s (30 min).  

Figure 3: Fingerprint region of mid-IR spectra at 0 s (blue) and 1000 s (red).			

For the microscopy experiments, the adhesive was prepared in the same manner, but discrete microscope spectra were collected of the adhesive in a "lattice mapping" mode. For the mapping experiments, mid-infrared spectra were collected using a Jasco IRT-7000 FT-IR microscope system equipped with a 16 × 1 linear-array MCT detector. Mapping spectra of four co-added sample scans of 8 cm

  resolution ratioed vs. 256 background scans were obtained for the adhesive sample as it cured. Mapping data were collected from a 16 × 16 point matrix of 187.5 × 187.5 μm, with an effective spatial resolution of 12.5 μm per sample spectrum. A time resolution of 20 s per sample mapping was utilized for observations of the mapping area during a total observation time of approximately 1400 s.  

Figure 4: Extracted absorption traces observed during the macro reaction for the 1290 cm-1 (blue) and 1254 cm-1 (red) mid-IR peaks.			

Figure 2 outlines the mid-infrared spectra of the adhesive at the beginning of the reaction (blue trace) and near the end of the curing (red trace).  Figure 3 is a closer examination of the fingerprint region, with specific peaks labeled in the traces. The C-H and C-C peaks at 1254 and 858 cm

, respectively, are increasing during the reaction, indicating the increase in the number of the CH

 bonds as the polymerization proceeds. Conversely, the C-H and C=C modes at 1290 and 804 cm

, respectively, are decreasing as the bonds associated with the C=C group are rearranged during the curing reaction.  

Figure 5: Extracted absorption traces observed during the macro reaction for the 858 cm-1 (red) and 804 cm-1 (blue) mid-IR peaks.			

The changes in the vibrational modes were observed for multiple examples of the cyanoacrylate curing reaction and the reaction kinetics calculated for the increasing and decreasing peak absorbance in the infrared spectra for the 1290 and 1254 cm

  peaks (Figure 4) and the 858 and 804 cm

  peaks (Figure 5) for the macro experiment. Additional plots of the 1290 and 1254 cm

  peaks (Figure 6) and the 858 and 804 cm

  (Figure 7) peaks for the micro experiment are also displayed. These figures all display the increasing and decreasing absorbance values for the vibrational motions outlined earlier. The reaction kinetics values are calculated for these peak absorbance changes and the results for these calculations are displayed as Table I.  

Figure 6: Extracted absorption traces observed during the micro reaction for the 1290 cm-1 (blue) and 1254 cm-1 (red) mid-IR peaks.			

As outlined in Table I, the macro and micro sampling methods provide reaction rate values of the time constant, reaction rate, and half-life values that agree well within each experiment. However, there is a significant disagreement between the macro and micro sampling methods themselves. Presumably this may be because of the thickness of the adhesive layer prepared for the experiments or changes in the atmospheric water levels during the reaction, but these variables were unable to be verified in the current study.  

Figure 7: Extracted absorption traces observed during the micro reaction for the 858 cm-1 (red) and 804 cm-1 (blue) mid-IR peaks.			

The macro and micro sampling methods for observation of an ethylcyanoacrylate adhesive curing reaction can provide useful kinetics data for the adhesive curing. Although the reaction data calculated from the mid-infrared data does not compare well between the macro and micro observation methods, it was felt that this could be caused by thickness of the adhesive preparation. These experiments demonstrate that additional information can be gained by using an infrared imaging method so that the reaction kinetics on a microscale can be investigated for other chemical systems. In this instance, standard commercial instrumentation was used for the imaging experiments and no special instrumentation or accessories were required.  

Table I: Comparison of reaction rates for macro samples (black) vs. micro sampling (red)			

(1) C.A. Coutts-Lendon, N.A. Wright, E.V. Miseo, and J.L. Koenig, 

(3) T. Tadokoro, T. Fukazawa, and H. Toriumi, 

(7) H. Sugiyama, J. Koshoubu, S. Kashiwabara, T. Nagoshi, R.A. Larsen, and K. Akao, 

is a spectroscopy products manager with Jasco, Inc., in Easton, Maryland.  

is a chiroptical  spectroscopy products manager with Jasco, Inc. Direct correspondence to:  

The use of imaging to study the reaction process involved in the curing of a cyanoacrylate adhesive is investigated.

Infrared Dynamic Imaging for the Examination of Chemical Reactions

Manufacturing processes in the semiconductor and electronics industry have advanced such that depositing very thin layers of lubricant on hard disk drives is now routine. Such thin layers of lubricants often have thicknesses at the angstrom level, pushing the limits of Fourier transform infrared spectroscopic sensitivity, which is the primary coating thickness measurement tool. Presented here is a method that demonstrates the ability to measure 11-Å layers, with potential for sub-1-Å determinations.

The electronics and semiconductor industries continue to demand more advanced and sensitive sample analysis techniques to keep up with the continuing miniaturization trends in their products.   

The demand to measure and characterize smaller and thinner samples is becoming increasingly common these days because of technological advances. Hard disk manufacturers are developing new processes whereby extremely thin layers of lubricant can be coated onto hard disk surfaces. This poses a challenge as the lubricant thickness approaches sub-1-Å levels.  

Such thin layers are not straightforward to analyze with traditional Fourier transform infrared (FT-IR) spectroscopy. Findings in this article focus mainly on providing a solution to characterizing angstrom-level thin layers of lubricant on hard disk samples. 

An Agilent Cary 660 FT-IR spectrometer coupled with a PIKE Technologies Advanced Grazing Angle (AGA) accessory was used to analyze three hard disk samples for lubricant thickness measurements. The AGA accessory was mounted onto the main sample compartment of the spectrometer. The three hard disk samples (HD1, HD2, and HD3) have highly reflective, smooth surfaces with lubricant thicknesses of 12.5 Å, 14 Å, and 11 Å, respectively.  

Sample collection conditions are as follows: The detector was a linearized narrow-band MCT detector. The spectral resolution was 16 cm

Agilent Resolution Pro software was used for quantitative calibration.  

The hard disk samples HD1, HD2, and HD3 were analyzed in grazing angle reflectance mode using the grazing angle accessory. This accessory is designed to optimize grazing angle measurements at 80°. Figure 1 shows the optical design (1) of the accessory, in which the beam from the spectrometer is focused onto a circular pin mirror. The reflected beam from this mirror strikes the sample at an 80° angle of incidence. The area of the sample that is being measured is equivalent to the size of the circular pin mirror, in this case, a 0.5-in. diameter spot size.  

Figure 1: Optical design of the grazing angle accessory.			

Measurements were taken with and without a polarizer and the respective results were compared. For each sample, four different surface locations were analyzed, with quadruplicate measurements at each of the four locations. The sample spectrum was ratioed against a background spectrum obtained with a gold mirror. An average FT-IR spectrum was obtained from the 16 spectra collected from each of the three hard disk samples. The subsequent three FT-IR spectra were used to study and deduce the difference in lubricant thickness between the three hard disk samples. Figure 2 shows the three overlaid spectra obtained without the polarizer.  

Figure 2: IR Absorption band at 1290 cm-1 for HD1, HD2, and HD3 samples, without polarizer.			

The absorbance intensities of the three samples were quantified at the IR absorbance peak of 1290 cm

. This peak typically represents the characteristic fluorocarbon used in the coating of surfaces of such hard disk drives.  

A calibration can be based on a user-defined peak area or peak height as shown in Figure 3. The left and right baseline points of the peak can be altered by simply clicking and dragging the points dynamically.  

Figure 3: Quantitative analysis: peak height of sample HD1.			

    The quantitative calibration was prepared from the different thicknesses of the hard disk samples of known thickness. A data point in the calibration curve can be included or excluded from the calibration. The quantitation software selects the data points for plotting the calibration curve, as well as the samples' respective thicknesses. 

Figure 4 gives a representation of how the calibration shows excellent linearity and a correlation coefficient of 1.000.  

Figure 4: Linear calibration plot of fluorocarbon peak height at 1290 cm-1.			

As shown in Table I, the peak height absorbances correspond accordingly to the known sample thickness, that is, HD1, HD2, and HD3 — 12.50 Å, 14.00 Å, and 11.00 Å, respectively.  

Table I: Corresponding absorbance intensities of samples HD1, HD2, and HD3			

A polarizer was used to get maximum sensitivity and increase the signal. P-polarized light will enhance the surface species measured, making features in the spectrum more prominent. The use of a polarizer with a liquid-nitrogen-cooled MCT detector is an ideal way to achieve optimum results. The results shown in Figure 5 verify this approach, whereby the peak intensities of HD1, HD2, and HD3 are enhanced by a factor of two.  

Figure 5: Increased absorbance intensities with use of p-polarizer.			

The quantitative calibration curve confirms excellent linearity and sensitivity of the data collected from the different lubricant thickness samples HD1, HD2, and HD3. The use of a polarizer (p-polarized light) also intensified the specific peak of interest by a factor of ~2, facilitating the possibility of sub-1-Å measurements. 

The recent trend and popularity in the semiconductor and electronics industries to measure monolayer thin lubricants continues to increase. Lubricant monolayers can decrease to sub-1-Å levels, posing a significant challenge to FT-IR analysis. An FT-IR spectrometer combined with a grazing angle specular reflectance accessory and linearized high sensitivity MCT detector is suitable to measure ultrathin layers of lubricants on hard disk surfaces.  

(1) PIKE Technologies Advanced Grazing Angle Accessory User Manual. 

(2) S. Boyd and J. Kirkwood, "Quantitative Analysis using ATR-FTIR Spectroscopy," Application Note SI-1374. 

are with Agilent Technologies in Yishun, Singapore. 

is with Agilent Technologies in Mulgrave, Victoria, Australia. Direct correspondence to: 

A method is presented that demonstrates the ability to measure 11-Ã… layers, with potential for sub-1-Ã… determinations.

Analysis of Angstrom-Level Lubricant Thicknesses on Hard Disk Surfaces with FT-IR Spectroscopy

Issue PDF

Click the title above to open the Spectroscopy August 2013 FT-IR Technology Supplement, Vol 28 No s8, in an interactive PDF format.

Special Issues-08-01-2013

FT-IR Spectroscopy in Ultrahigh-Vacuum Conditions: A Surface Science Approach to Understanding Reactions on Catalytic Oxide Powders

Spatial Resolution in IR Reflectance Imaging — NIR, Mid-IR, and ATR

Infrared Dynamic Imaging for the Examination of Chemical Reactions

Analysis of Angstrom-Level Lubricant Thicknesses on Hard Disk Surfaces with FT-IR Spectroscopy

Vol 28 No s8 Spectroscopy August 2013 FT-IR Technology Supplement PDF