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. 2020 Jul 29;5(31):19820–19826. doi: 10.1021/acsomega.0c02689

Additive Combination of Spectra Reflected from Porous Silicon and Carbon/Porous Silicon Rugate Filters to Improve Vapor Selectivity

Joshua D Kittle 1,*, John S Gofus III 1, Andrea N Abel 1, Benjamin D Evans 1
PMCID: PMC7424702  PMID: 32803077

Abstract

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Selectivity remains a challenge for rapid optical vapor sensing via light reflected from porous silicon photonic crystals. This work highlights a method to increase optical vapor selectivity of porous silicon rugate filters by analyzing additive spectra from two rugate filter substrates with different functionalities, an oxidized and carbonized surface. Individually, both porous silicon rugate filters demonstrated sensitivity but not selectivity toward the vapor analytes. However, differences in peak shift trends between the two substrates suggested differences in vapor affinities for the surfaces. By adding the two spectra, improvements to selectivity relative to the individual surfaces were observed even at low vapor pressures and for analytes of similar polarity, refractive index, and concentration. These results are expected to contribute toward optical vapor selectivity improvements in one-dimensional porous silicon photonic crystals.

Introduction

Optical vapor sensing via porous silicon photonic crystals (PhCs) remains an active area of research. Generally, PhCs are composed of a periodic structure with two or more materials with different dielectric constants.1 Visible light incident on a PhC with nanoscale periodicity is reflected and refracted at these periodic interfaces, giving rise to photonic band gaps (e.g., structural color).2 Vapor detection at low concentrations is based on changes in refractive index of the PhC brought about by microcapillary condensation of the analyte into the nanoarchitecture of the PhC. Optical vapor sensing via PhCs is of considerable interest to the environmental monitoring community due to its potential as a low-cost, continuous passive sensor.3

While a number of studies have investigated vapor sensing via both natural and synthetic PhCs,4,5 one-dimensional (1D) porous silicon (pSi) rugate filters offer a number of advantages. Both pSi rugate filters and distributed Bragg stacks (DSBs) are similar in that both use variations in pore size to change the refractive index between layers. Rugate filters, though, are formed by continuously modulating current when etching, resulting in a smooth transition in pore sizes, and thus refractive index layers, not found in DBRs. This leads to sharper photonic band gaps and absences of higher-order harmonics relative to DBRs.6 High-surface-area 1D PhCs from silicon are generally inexpensive to manufacture and can be tailored to various pore sizes and morphologies to increase sensitivity and selectivity.7 These PhCs can then be functionalized via a variety of methods to increase specificity toward analytes of interest.8,9 Porous silicon PhCs offer the additional advantage of relatively straightforward integration into microelectronics, as well as opportunities for multiparameter sensing via conductivity.3,10 Despite these advantages, significant challenges remain in using a porous silicon PhC as a sensitive, selective, rugged, passive, optical vapor sensor.

Though improvements in sensor recovery, long-term stability, and sensitivity are required, this work focuses on improving selectivity of 1D porous silicon PhCs. Some natural PhCs, such as those in wing scales of the Morpho butterfly, have a polarity gradient within their nanoarchitecture.11 Analytes migrate to certain regions of these natural PhCs based on their polarity, causing unique spectra shifts. However, the spectral response for a 1D porous silicon PhC depends primarily on the refractive index (n) of an analyte and its concentration, often modeled as a thin film with thickness (d).12 Thus, these silicon PhCs are not selective because many combinations of n and d will yield the same optical response to different vapors. To address this, a number of studies have improved the selectivity of 1D silicon-based PhCs, typically through surface functionalization or coatings,10,13−15 chemical reaction to alter periodic spacing,16,17 complex nanostructures,18,19 time-resolved spectroscopy,20 or a combination of these techniques.21

Several studies have examined the spectral response of vapor analytes to pSi rugate filters with different surface functionalities or coatings as a means to improve selectivity.22−28 An array-based approach in which a number of rugate filters were filled with different ionic liquids yielded unique responses to organic vapors when decreases in peak intensity across the array were analyzed via principal component analysis (PCA).24,25 A number of these studies focused on using one PhC as a reference channel. For example, Ruminski et al. used a rugate filter double-stack in which one stack was hydrophobic and one stack was hydrophilic, each stack with a different peak wavelength.27 After determining the weighted difference in peak shift of each stack when exposed to various water vapor concentrations, the response to an organic/water vapor mixture could be corrected to remove the contribution of humidity. While the authors note that the rugate filter double-stack was not selective to different organic vapor analytes, the study did show that the spectral response to water of a particular concentration was different for each surface.27 Similarly, a silicon rugate filter with an oxidized surface showed different organic vapor response trends when compared to a carbonized silicon rugate filter, presumably because of differences in interactions of the vapors with the surface.28 Despite these improvements, challenges remain in fabricating 1D porous silicon PhCs for sensitive, selective identification of a broad class of analyte vapors and mixtures that rivals the performance of natural PhCs.11,30

In this work, an array-based approach to improve optical vapor selectivity was examined by analyzing spectra from two pSi silicon rugate filters with different surface functionalities, an ozone-oxidized surface and a carbonized surface. Each rugate filter was exposed separately to five different vapor concentrations of water, methanol (MeOH), ethanol (EtOH), dichloromethane (DCM), and dichloropentane (DCP). The spectra for a particular vapor concentration for each of the two substrates were then additively combined, resulting in improved selectivity to a particular analyte relative to the response of the individual rugate filters.

Results and Discussion

The rugate sensors used in this study were prepared using the method developed by Kelly et al.28 In brief, a p-type silicon wafer was etched with hydrofluoric acid, yielding a substrate determined to be ∼25 μm thick using the spectroscopic liquid infiltration method (SLIM).7 Films were then oxidized with ozone to provide a uniform silicon oxide surface prior to carbonization.31,32 A dilute furfuryl alcohol solution was applied to the substrate and catalyzed with oxalic acid to yield a poly(furfuryl alcohol) (PFA)-infiltrated pSi film. The film was then heated to produce a carbonized pSi sensor.

Reflectance spectra of the oxidized pSi showed the characteristic peak of pSi rugate filters etched using a sinusoidally varying current.33 The wavelength of the peak was adjusted by altering the periodicity of the sinusoidal current to yield a peak centered at 641 nm. Carbonization of the pSi film caused a red shift in the stop band, yielding a peak centered at 667 nm. Figure 1 shows the reflectance spectra for the freshly etched and carbonized pSi films. The stop band shows a large decrease in intensity upon carbonization, and the Fabry–Pérot interference fringes are no longer visible. As noted by Kelly et al., the shift in the peak position for the carbonized pSi film is caused by changes in the effective refractive index of the system.28 The decrease in peak intensity and disappearance of the Fabry–Pérot interference fringes have previously been attributed to the strong light absorption of carbon within the pores of the pSi film.28

Figure 1.

Figure 1

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Reflectance spectra of the (a) oxidized (solid line) and (b) carbonized (dashed line) pSi surfaces used in this study.

The extent of carbon infiltration in the pSi template was qualitatively characterized by Fourier transform infrared (FTIR) spectroscopy. As shown in Figure 2, the spectra of the freshly etched pSi film showed characteristic bands assigned to the Si–H stretching modes at ∼2100 cm–1. Oxidized and carbonized surfaces showed a broad peak centered at 1020 cm–1, attributed to the Si–O stretching mode. The broad band centered at ∼3290 cm–1 was attributed to a terminal O–H stretching mode. These peaks were also observed in literature spectra.34 This broad O–H peak was absent from the carbonized surface, showing that terminal O–H groups are no longer present following the carbonization process.

Figure 2.

Figure 2

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FTIR spectra of (a) freshly etched, (b) oxidized, and (c) carbonized pSi films. The freshly etched spectrum showed a characteristic Si–H stretching band at 2100 cm–1, which was no longer observed following ozone oxidation. The oxidized spectrum had a broad peak centered at 3290 cm–1 from the terminal O–H stretching, which was no longer observed following carbonization.

Freestanding, porous films of ozone-oxidized and carbonized rugate filters were prepared for elemental and nitrogen adsorption/desorption analysis. CHNS elemental analysis yielded a carbon content of 0.2% carbon by mass for the ozone-oxidized pSi surface, while subsequent carbonization yielded 4.8% carbon by mass. The porous structures of freestanding oxidized and carbonized pSi rugate filters were characterized using nitrogen adsorption/desorption analysis. As shown in Figure 3, the bimodal desorption isotherm typically observed in carbonized pSi composites is not observed in either sample.28,35 This absence of a bimodal desorption isotherm for the carbonized substrate was not unexpected, as ethanol was used in this work to dilute the furfuryl alcohol, resulting in a lower carbon content relative to other studies.28,35 The hysteresis present in both the oxidized and carbonized pSi substrates indicates multilayer gas adsorption, followed by capillary condensation.36 The desorption slope for the oxidized pSi surface was consistent with a mesoporous substrate with high pore size uniformity, while the desorption slope for the carbonized pSi surface indicated a less uniform pore size and shape.36 There is a large initial decrease in the Barrett–Joyner–Halenda (BJH) pore diameter from 15.43 ± 0.08 nm for the ozone-oxidized substrate to 10.07 ± 0.26 nm for the carbonized substrate. Similar results were observed in the BJH pore volume. There is a large initial decrease from 0.90 cm3 g–1 for the oxidized pSi rugate filter to 0.55 cm3 g–1 for the carbonized pSi rugate filter. Collectively, these results suggest that the carbonization process yielded carbon within the pores of the pSi rugate filter, reducing the pore diameter, pore volume, and pore uniformity relative to the oxidized pSi rugate filter.

Figure 3.

Figure 3

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Nitrogen adsorption (solid black circles) and desorption (solid gray diamonds) isotherms for the (a) oxidized and (b) carbonized silicon rugate filters used in this work.

The spectral response of both the oxidized and the carbonized pSi rugate filters to a number of analyte vapors was tested separately using the instrumentation schematic shown in Figure 4. Nitrogen at a flow rate of 400 mL min–1 was used to obtain a spectral baseline. An analyte vapor of a particular concentration was introduced into the measurement chamber by bubbling nitrogen through the liquid analyte. Digital mass flow controllers were used to keep a constant total flow rate of 400 mL min–1. Spectra for vapor concentrations of 0.02P0, 0.05P0, 0.10P0, 0.20P0, and 0.30P0 were collected after 10 minutes of exposure of a particular pSi rugate filter to an analyte, where P0 is the saturated vapor at 20 °C.4 Before switching to a different analyte, the measurement chamber was flushed with nitrogen, coupled with mild heating,28 to return the reflectance spectra to the original baseline. The differential reflectance spectra (ΔR) could be obtained by subtracting the baseline spectra from the analyte spectra.37,38

Figure 4.

Figure 4

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Instrumentation schematic for monitoring stop band peak shifts of a pSi rugate filter upon introduction of the vapor analyte at a particular concentration.

A comparison of the maximum peak shifts after exposure of the oxidized and carbonized substrates to each analyte can be seen in Figure 5. Introduction of the analyte vapor leads to a red shift of the photonic band gap and an increase in the reflectance intensity. Of particular note, the average maximum peak shift of an analyte is not the same for the two different pSi rugate filters. Based on previous studies, one expects different peak shifts for the same vapor at a particular concentration.27,28 While the differences in pore size and pore volume certainly contribute to differences in the peak shift between two pSi substrates, differences in analyte trends presumably indicate differences in the interaction (e.g., affinity) of an analyte for that surface.28 Thus, while the generally lower peak shifts for the carbonized pSi relative to the ozone-oxidized pSi can be readily attributed to the lower pore volume of the carbonized pSi substrate, the differences in the analyte trends suggest that some analytes interact more strongly with the carbonized pSi and vice versa. For example, the magnitude of the peak shift for DCM is significantly higher on the carbonized surface versus the oxidized surface, while that of MeOH remains unchanged despite the lower pore volume of the carbonized surface. Differences in the peak shift for water and DCP on the two surfaces are also observed. This apparent affinity of certain vapor analytes for one functionalized surface versus another has been suggested elsewhere.24,25,27,28 Partition of liquids across hydrophobic and hydrophilic rugate filters has been demonstrated, and it is likely that a similar phenomenon is occurring in the vapor phase.39 However, the challenge of selective sensing via the rugate filters in this study is illustrated in Figure 5c for the third data point of water and DCP—the spectral response to both vapors is similar because the products of the refractive index and concentration (e.g., condensed film thickness d) of each vapor happen to coincide.

Figure 5.

Figure 5

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Example reflectance spectra of the (a) oxidized pSi rugate filter and (b) carbonized pSi rugate filter after exposure to nitrogen (black line) and 0.30P0 ethanol (red line) showing a red shift upon introduction of ethanol. (5c, d) show the average maximum peak shifts after exposure to DCM, DCP, EtOH, MeOH, and water at concentrations ranging from 0.02P0 to 0.30P0, where the solid markers (c) are the peak shifts for the oxidized pSi rugate filter and the open markers (d) are the peak shifts for the carbonized pSi rugate filter. Lines are provided as a guide to the eye. The last data points show the representative standard deviation error bars unless the marker is larger than the standard deviation.

The challenge of using individual pSi rugate filters to differentiate between vapor analytes is further illustrated in the PCA plots shown in Figure 6. PCA is a multivariate analysis technique that highlights the variation between spectra by determining principal components that capture the variance within a data set. In Figure 6, each point on the PCA plot indicates the differential reflectance spectra for a particular analyte and concentration. Again, differential reflectance spectra (ΔR) reports the percentage difference of the reflectance with the analyte relative to the nitrogen baseline without the analyte.38 Significant spacing between points of the same analyte indicates good sensitivity, while separation of analyte curves indicates good selectivity.40 Thus, Figure 6 shows a tested sensitivity down to ∼30 ppm for DCP on both the oxidized and carbonized pSi substrates. Low ppm sensitivities of 1D pSi photonic crystals have been reported in a number of studies.21,27,28,41,42 Also similar to literature results, neither the oxidized nor carbonized pSi rugate filter individually demonstrated selectivity.28 As shown in Figure 6 for both pSi surfaces, all analytes generally fell along the same line, a product of refractive index and vapor concentration.11 However, the different trends of the analyte peak shift for the two pSi rugate filters (Figure 5c,d) suggested that a parallel examination of the data (e.g., an array-type data analysis) could lead to enhanced vapor selectivity.

Figure 6.

Figure 6

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PCA score plots of differential reflectance spectra in the presence of analyte vapors for (a) oxidized and (b) carbonized pSi rugate filters. The first two principal components capture (a) 92% and (b) 98% of the total spectral variance, respectively. The x-axis is intentionally extended to facilitate comparisons with Figure 7d.

Toward that end, the individual reflectance spectra for a particular analyte concentration for the oxidized and carbonized pSi substrates were additively combined. An example of this additive combination is shown in Figure 7a–c. PCA was then performed on this additive combination of spectra from the oxidized and the carbonized pSi rugate filters, the results of which are shown in Figure 7d,e. In comparing Figure 7d and Figure 6, selectivity improvements are apparent when the two data sets are analyzed together versus individually, as evidenced by the y-axis separation of analyte traces in Figure 7d relative to Figure 6. Additionally, even analytes that appear to potentially overlap in the two-dimensional PCA plot (Figure 7d) show good separation in the three-dimensional PCA plot (Figure 7e).

Figure 7.

Figure 7

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Differential reflectance spectra (ΔR) for (a) the oxidized pSi rugate filter exposed to 0.30P0 ethanol, (b) the carbonized pSi rugate filter exposed to 0.30P0 ethanol, and (c) the additive combination of the spectra from (a) and (b). The two-dimensional (d) and three-dimensional (e) PCA plots for the additively combined spectra of the two pSi rugate filters after exposure to each vapor at concentrations ranging from 0.2P0 to 0.30P0 show improved selectivity. The first three principal components capture 86, 6, and 4% of the data spectral variance for a total of 96% of the variance.

Based on similar studies, this increase in selectivity by spectral analysis from the two different pSi rugate filters is somewhat expected. A limited number of studies have used various functional coatings on 1D porous silicon and analyzed the resulting spectra in a number of ways, resulting in improved sensitivity. PCA of peak shifts and peak reflectance intensity from an array of 1D porous silicon substrates coated with different ionic liquids yielded selectivity to common organic vapors, though concentrations less than 0.20P0 were not tested.24,25 Additionally, an array of functionalized silica and titania Bragg stacks exposed to organic vapors demonstrated selectivity when monitored for changes in pixels from color images of the array.43 Again, though, only high (e.g., saturated) vapor concentrations were examined. Unique to the work presented here, though, an additive combination of the spectra of only two 1D pSi with different functionalities tested at low vapor concentrations (e.g., 0.02P0) showed good sensitivity and selectivity. Indeed, the selectivity and sensitivity rival those of some natural photonic crystals when exposed to the same vapors and concentrations.37,38

Further improvements to the sensitivity and selectivity of 1D pSi optical vapor sensors could be realized by a combination of a variety of methods to include aperiodic structures with high surface areas,44 optimized numbers and types of functional coatings,24,25 monitoring of multiple parameters to include additive spectra and color images,43 and optimized analysis techniques of multiparameter sensing methods based on machine learning. Notably, DCP is a mustard gas simulant, and the sensitivity and selectivity demonstrated in this work approach the useful range for mustard gas sensing.45 Combined with the other inherent advantages of 1D pSi, to include facile integration with electronics and other sensing mechanisms via conductivity, optical vapor sensing based on 1D pSi should be possible at a sensitivity and selectivity requisite for most environments, to include the homeland defense and battlespace operation communities.

Conclusions

In summary, this work highlights a method to increase the optical vapor selectivity of 1D pSi photonic crystals by analyzing additive spectra from two pSi substrates with different surface functionalities. Individually, both pSi rugate filters demonstrated sensitivity but not selectivity toward the vapor analytes. However, differences in peak shift trends between the two surfaces suggested differences in vapor affinities for the surfaces. By adding the two spectra, improvements to selectivity relative to the individual surfaces were observed even at low vapor pressures and for analytes of similar polarity, refractive index, and concentration. These results are expected to contribute toward optical vapor selectivity improvements in 1D porous silicon that exceeds the performance of some natural systems.

Materials and Methods

Materials

Oxalic acid dihydrate (ACS grade, 247537), furfuryl alcohol (98%, 185930), and 1,5-dichloropentane (DCP, 99%, D69602) were purchased from Sigma-Aldrich. Ethanol (EtOH, ACS grade, 111000190), methanol (MeOH, ACS grade, 339000000), and dichloromethane (DCM, ACS grade, 313000ACSPL) were purchased from Pharmco-Aaper. Ultrapure water (Milli-Q Gradient A-10, Milli-Q, 18.2 ΩM cm, <5 ppb organic impurities) and ultrahigh purity nitrogen (Airgas, UHP300) were used for all experiments.

Porous Silicon Preparation

Reflectance Measurements

Porous silicon samples were prepared from highly doped p-type silicon wafers (boron-doped, ρ = 0.845 mΩ cm–1, (100) orientation, obtained from Virginia Semiconductor Inc.) by electrochemical anodization in a solution of 49% aqueous HF in absolute ethanol (3:1 v/v HF/ethanol). Silicon chips were etched using an aluminum foil backing and a platinum coil counter electrode in a Teflon cell with an exposed area of 8.6 cm2. Porous silicon rugate filters were etched by applying a sinusoidally varying current density of 10–100 mA cm–2, with a period of 8 s for 100 cycles. Samples were rinsed with ethanol and dried under a stream of nitrogen gas. Freshly etched chips were cut into smaller samples measuring approximately 1.5 cm2 and then oxidized in a flow of ozone gas (1.5 SCFH) for 20 min.

Freestanding Substrates for Characterization

Freestanding pSi porous membranes for elemental and Brunauer–Emmett–Teller (BET)/BJH analyses were prepared from highly doped p-type silicon (boron-doped, ρ = 1.26 mΩ cm–1, (100) orientation, obtained from Virginia Semiconductor Inc.) by electrochemical anodization in a solution of 49% aqueous HF in absolute ethanol (3:1 v/v HF/ethanol). Porous silicon rugate filters were etched by applying a sinusoidally varying current density of 10–100 mA cm–2 with a period of 6.67 s for 600 repetitions (HF solution was replaced every 100 repeats). The freshly etched pSi film was lifted off from the bulk underlying silicon substrate by replacing the etching solution with 3.33% HF in ethanol and etching at 50 mA cm–2 for 480 s. The freshly etched pSi film thickness was determined to be ∼150 μm by SLIM.

Carbonized Porous Silicon Preparation

Reflectance Measurements

Carbon/pSi sensors used in this study were prepared using the method developed by Kelly et al.28 Freshly etched pSi films were oxidized for 20 min under a stream of ozone to provide a uniform silicon oxide surface prior to carbonization.31 Furfuryl alcohol solutions for carbonization of the oxidized films were prepared by diluting 100 μL of furfuryl alcohol with 900 μL of absolute ethanol and using 5 mg mL–1 oxalic acid to catalyze the polymerization process, yielding a poly(furfuryl alcohol) (PFA)-infiltrated pSi film.46 Films were heated at 50 °C for 30 min and then at 700 °C for 2 h to produce carbonized pSi sensors.

Freestanding Substrates for Characterization

Freestanding carbonized pSi membranes for elemental and BET/BJH analyses were prepared by immersing a freestanding pSi membrane into a 9:1 v/v ethanol/furfuryl alcohol solution catalyzed by oxalic acid, followed by heating at 50 °C for 30 min and then at 700 °C for 2 h.

Characterization

Infrared Spectroscopy

Fourier transform infrared (FTIR) spectroscopy was utilized to characterize the pore wall surface chemistry. Spectra were acquired on a Nicolet 6700 FTIR spectrometer (Thermo Scientific) equipped with an attenuated total reflectance (ATR) accessory.

Elemental Analysis

The carbon content of the carbonized pSi samples was determined on freestanding samples using a PerkinElmer 2400 Series II CHNS/O Elemental Analyzer. Three trials were run per sample with masses between 2 and 3 mg each.

Nitrogen Adsorption/Desorption

The average pore diameter of freestanding samples was characterized via nitrogen adsorption–desorption isotherms obtained at 77 K using a Micromeritics ASAP 2020 instrument. The samples were degassed for 5 h at 250 °C prior to adsorption measurements. Pore dimensions were determined using the Brunauer–Emmett–Teller (BET) theory.47

Reflectance Measurements

Reflectance spectra were collected using a halogen light source (Ocean Optics, HL-2000) and a spectrometer (Ocean Optics, HR2000+) equipped with a bifurcated optical probe (Ocean Optics, QR400–7-UV/Vis). The optical probe was normal to the rugate filter surface, generating an illuminated area of about 2 mm in diameter. Vapor concentrations were varied by bubbling the nitrogen carrier gas at a particular flow rate into the analyte liquid so that the partial pressure of the analyte vapor was between 0.02P0 and 0.30P0, where P0 is the saturated vapor pressure at 20 °C. The total gas flow rate for all measurements was held constant at 400 mL min–1 by mass flow controllers (Alicat Scientific), and the temperature was held constant at 20 °C. The reflectance measurement cell had a volume of 500 mL, while the gas tubing had a total volume of 270 mL. Each spectrum was collected after 10 min of exposure to the vapor. Mild heating of the pSi rugate filter to 80 °C facilitated the rapid return of the spectra to the nitrogen baseline between analyte tests.28 For both pSi rugate filters, three separate runs of each analyte concentration were collected and averaged. Rather than a reflectance standard, differential reflectance spectra were collected and analyzed.4,11,38 PCA was performed on the averaged differential spectra relative to nitrogen after mean-centering the data.

Acknowledgments

This work was supported by the Defense Threat Reduction Agency (DTRA)—Joint Science and Technology Transfer Officer for Chemical and Biological Defense (MIPR No. HDTRA13964) and the Air Force Office of Scientific Research (AFOSR).

The authors declare no competing financial interest.

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