Next Article in Journal
Effect of Carbon Content on Friction and Wear Properties of Copper Matrix Composites at High Speed Current-Carrying
Next Article in Special Issue
Optical Dispersions of Bloch Surface Waves and Surface Plasmon Polaritons: Towards Advanced Biosensors
Previous Article in Journal
Field Investigation of Clay Balls in Full-Depth Asphalt Pavement
Previous Article in Special Issue
In Situ Synthesis of Silicon–Carbon Composites and Application as Lithium-Ion Battery Anode Materials
Review

Nanosilicon-Based Composites for (Bio)sensing Applications: Current Status, Advantages, and Perspectives

NanoBioMedical Centre, Adam Mickiewicz University, 3, Wszechnicy Piastowskiej Str., 61-614 Poznan, Poland
*
Author to whom correspondence should be addressed.
Materials 2019, 12(18), 2880; https://doi.org/10.3390/ma12182880
Received: 12 August 2019 / Revised: 2 September 2019 / Accepted: 3 September 2019 / Published: 6 September 2019
(This article belongs to the Special Issue Multifunctional Nanostructured Silicon Composites)

Abstract

This review highlights the application of different types of nanosilicon (nano-Si) materials and nano-Si-based composites for (bio)sensing applications. Different detection approaches and (bio)functionalization protocols were found for certain types of transducers suitable for the detection of biological compounds and gas molecules. The importance of the immobilization process that is responsible for biosensor performance (biomolecule adsorption, surface properties, surface functionalization, etc.) along with the interaction mechanism between biomolecules and nano-Si are disclosed. Current trends in the fabrication of nano-Si-based composites, basic gas detection mechanisms, and the advantages of nano-Si/metal nanoparticles for surface enhanced Raman spectroscopy (SERS)-based detection are proposed.
Keywords: silicon; nanomaterials; (bio)sensors; nanocomposites silicon; nanomaterials; (bio)sensors; nanocomposites

1. Introduction

Nanoscale (porous) silicon (Si) was accidentally discovered in 1956 by Arthur Uhlir Jr. and Ingeborg Uhlir in the process of developing a technique for polishing and shaping the surface of silicon [1]. However, for a long time, this material was beyond the concerns of the scientific community until A. G. Cullis and L. T. Canham reported on the visible light emission due to the quantum size effects in highly porous crystalline silicon (PSi) in 1990 [2]. This discovery provided another opportunity for further investigation and application.
Up until now, nano-Si remains one of the most popular and sought-after materials in applied science. The fabrication procedure of nanoscale silicon is not labor intensive and does not require special (expensive) equipment and chemicals. Depending on the structure/morphology, for example, porous silicon (PSi) [3,4,5], silicon nanopillars (SiNPs) [6,7], and silicon nanowires (SiNWs) [8], this material can be used for Li-ion batteries [9], water-splitting [10], solar cell [11], sensor and biosensor applications [12,13], etc.
(Bio)sensors are devices designed for the selective detection of (bio)molecules in a multimolecular environment. Generally, they consist of a detection platform (transducer) with a selective layer and target (bio)molecules in liquids or gases. The main idea is to observe the modification of the transducer response (optical, electrical, chemical, thermal, etc.) through “surface–target analyte” interaction in real-time or express detection [14].
Nowadays, sensors and biosensors based on nano-Si have been successfully applied to molecules [15], biomolecules [16] and light [17] detection using different responses (PL [18,19], SERS [20], I–V [21], reflectance [22,23], resistance [24], capacitance [25], fluorescence [26]) and material modifications (PSi, SiNWs, SiNPs). Such strong interest in (bio)sensors based on nano-Si can be explained by their enhanced surface to volume ratio, biocompatibility, and low-cost.
The most common methods for PSi sample fabrication are metal-assisted chemical etching (MACE), stain etching, and electrochemical etching [27]. Use of these methods enables the fabrication of PSi substrates with different pore sizes (from nanoporous to macroporous), depending on the chemical/physical procedure parameters. Currently, many works have been dedicated to PSi-based (bio)sensor application as well as PSi-based nanocomposites (PSi/Au [13], PSi/ZnO [8], PSi/TiO2 [28,29,30]) with enhanced selectivity, sensitivity, and tailored properties.
SiNWs and SiNPs are the most advanced modifications of nano-Si due to their enhanced surface to volume ratio when compared with PSi. On the other hand, their fabrication involves additional steps such as etching mask deposition by using photolithography [31], polystyrene nanosphere lithography [6], or electron-beam lithography [32]. Recently, attention from the scientific community has been given to the fabrication of highly-sensitive (bio)sensor platforms based on SiNW and SiNP nanocomposites. It has been established that Au, Ag, Pd, and Pt nanoparticles deposited over silicon nanopillars or nanowires can be aggregated to “hot spots” and demonstrate a high enhancement factor in SERS-based biosensors with a detection limit less than 10-12 M [33]. Furthermore, SiNWs and SiNPs in conjunction with metal oxides (TiO2, ZnO, WO3, F2O3, TeO2) have shown promising results for gas and biomolecule detection via an electrochemical response with a detection limit of about 1 ppm [34,35,36,37,38]. Recently, a number of new composites have been developed based on SiNWs and SiNPs with sulfides (CdS, MoS2) [39,40] and nitrides (Si3N4) [41] that are suitable for sensitive light, humidity, and gas detection due to enhanced absorption and adsorption.
Tailored and advanced properties of nano-Si and silicon nanocomposites open great possibilities for use in novel trends in (bio)sensor applications. This paper is dedicated to nano-Si and silicon nanocomposites suitable for (bio)molecule detection as well as future prospects of this research area. Additionally, the application of nano-Si and its nanocomposites for (bio)sensors was discussed. The effects of metal and metal oxide nanoparticles on the structural, optical, electrical, and (bio)sensor properties were analyzed. The mechanism of interaction between nano-Si/silicon nanocomposites and (bio)molecules was also clarified. New trends, affecting the development of nano-Si-based biosensors are presented.

2. Types of Nano-Si Morphology and Methods of Fabrication

2.1. Porous Silicon (PSi)

PSi is a well-studied Si-based nanomaterial. As above-mentioned, PSi has obtained great interest within the scientific community after light emission was discovered in 1990. PSi has a number of unique properties such as visible light emission, enhanced light absorption, and biocompatibility. Recently, a number of publications have been dedicated to PSi and PSi-based nanocomposite fabrication and its application in (bio)sensing. As previously mentioned, electrochemical anodization, stain etching, and MACE (Figure 1a–d) [42] remain the most common methods for PSi substrate fabrication, which enable the production of PSi (Figure 2a) with tailored morphological properties (porosity, pore size, and depth of pores).

2.2. Silicon Nanowires (SiNWs)

SiNWs (Figure 2c) are another type of nano-Si, where the height of the Si nanoelements is much higher than its diameter (h >> d). Due to the high surface to volume ratio, SiNWs have found successful applications in solar cells, sensors, biosensors technologies, photovoltaics, etc. [43]. Traditionally, this nanomaterial can be fabricated from bulk Si by RIE [44] and MACE [45] in combination with lithographic techniques (photolithography, polystyrene nanosphere lithography) or bottom-up and top-down technologies [46]. In addition, the initial synthesis of SiNWs is often accompanied by thermal oxidation steps to yield structures with an accurately tailored size and morphology [47].

2.3. Silicon Nanopillars (SiNPs)

A SiNP (Figure 2b) substrate (h ≥ d) is a kind of nano-Si with densely packed and well-ordered morphology. This substrate, like that of SiNWs, possesses an enhanced surface to volume ratio and absorption when compared with bulk silicon. Relying on this fact, SiNP arrays have become popular and prospective for solar, cell water-splitting, and (bio)sensors application. This kind of nano-Si is generally fabricated by RIE and MACE with different types of lithographic masks (Figure 1f) [48,49]. The mechanical robustness of the SiNP area is substantially better when compared with SiNWs due to h~d and a well-ordered morphology.

3. (Bio)sensors Based on PSi, SiNWs, SiNPs and Their Composites with Polymers

Nowadays, nano-Si remains one of the most popular materials for sensor and biosensor applications. A number of unique properties make it prospective for (bio)molecules, pH, and light detection via different sensing techniques (optical, resistive, volt-amperometry, etc.). High surface to volume ratio allows for an increase in the number of adsorbed (bio)molecules, resulting in enhanced sensitivity when compared with planar Si surfaces. The selectivity of nano-Si to the target analyte can be achieved via (bio)functionalization such as a bioselective layer for target biomolecules (e.g., antigen–antibody interaction) [3,19]. Additionally, significant interest by the scientific community has been paid to real-time measurements and the design of a microfluidic system with embedded nano-Si transducers [53].
As mentioned below, biofunctionalization plays a very important role in bioselective layer evolution and allows for the binding of organic molecules to a non-organic nano-Si surface without unspecific interaction. Currently, a number of biofunctionalization protocols have been proposed: silanization [3,19,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67], aminosilanization [68,69,70], direct immobilization [16,22,71,72], enzyme [18] or peptide [73] treatment, phospholipid bilayers formation [74], hydrosilylation treated by N-Hydroxysuccinimide and 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide (NHS/EDC) [75,76,77] or resazurin [78], and polymer synthesis [79]. However, the most common technique is silanization, due to the possibility of controlling the thickness of the(3-Aminopropyl)triethoxysilane (APTES) layer as well as using different cross-linking agents (glutaraldehyde, NHS/EDS) [18,80].
In recent years, nano-Si has been widely used for optical (bio)sensor applications due to its portability and high sensitivity. Among all of the optical detection approaches, photoluminescence (PL)-based measurement looks the most promising, especially for real-time monitoring [3,18,19,72,78,81,82,83,84]. Previously, we reported on low-cost, highly sensitive PSi-based immunosensors for ochratoxin A (OTA) detection using a PL approach. It was established that the intensity of PL changes under different OTA concentrations via antibody–antigen interaction onto the PSi surface. The limit of detection (4.4 pg/mL) and the sensitivity range (0.01–5 ng/mL) to OTA were estimated [3,19]. In [18], Syshchyk et al. reported on a PSi-based photoluminescence platform for heavy metals, urea, and glucose detection. PSi surface biofunctionalization was performed by enzyme (urease and glucose oxidase) treatment. The sensor mechanism was based on the effect of PL changing with the varying pH of the solution caused by the enzymatic reactions [18]. Furthermore, it was reported that the PL-based detection approach could be utilized for O2 detection on a SiNW platform [84]. SiNWs were fabricated by the MACE method and O2 detection was carried out through the measurement of different oxygen flow pressure. The general sensing mechanism was based on the PL intensity change, which can be explained by the reversible charging/recharging of surface defects (Pb-centers) due to the oxygen adsorption/desorption.
Another nano-Si optical response suitable for (bio)molecule detection is reflectance or other optical parameters related to reflectance [22,48,53,55,56,57,58,62,65,67,68,70,71,74,76,85,86,87,88,89,90,91,92,93,94,95,96]. Generally, the (bio)sensor technique based on reflectance response can be performed via reflective index (RI) [71] or optical density [16] (OD) measurements in the initial state and after the addition of the analyte. The changes in RI and OD caused by analyte-transducer surface interaction can be processed and used as the effective (bio)sensor signal. Other pathways for detection based on reflectance usually involve the analysis of the interferogram average over wavelength (IAW–IAW0) [89,97] as well as the estimation of effective optical thickness ratio (EOT/EOT0) [53,54]. For instance, PSi sensors based on the reflectance response for heavy metal detection were studied in [61,97,98,99]. Politi et al. reported on the highly-sensitive (LOD ~ 1.2 ± 0.3 ppb) method for Pb(II), As(III), and Cd(II) detection via the modification of PSi surfaces by lysine and oligopeptides [98]. The advanced optical approach for E. coli detection was also proposed by Y. Tang et al. [53]. Real-time measurements were performed in a microfluidic system with a PSi oxidized substrate via indirect Fourier transformed reflectometric interference spectroscopy (FT-RIS) measurements. Detection included two steps: capture of the bacteria on the PSi surface and measurement of pore accessibility by BSA treatment. It was assumed that the EOT shift of PSi decreased with increased E. coli concentration on its surface, causing a block of the porous array. Furthermore, Luan et al. developed photonic waveguides and microring resonators based on SiNPs for a high sensitivity label-free transducer that was suitable for isopropyl and streptavidin detection [71]. The sensitivity of each resonator to isopropyl (228–580 nm/RIU) was calculated as the ratio of the wavelength shift slopes to the change of reflective index (RI). The authors noted that sensitivity could be enhanced by minimizing the scattering loss by applying the new advanced fracturing strategies and single line edge smoothing (SLS) in the process of nano-Si fabrication.
Fluorescent optical response is usually used for the labeled biomolecule detection technique [60,64,66]. The general idea of this approach is based on analysis of a fluorescence signal from labeled biomolecules via their binding with previously functionalized nano-Si structures. In [64,66], the PSi Bragg mirror was used to enhance the fluorescence signal from the CdSe/ZnS QD embedded within the PSi pores for single-stranded DNA (ssDNA) detection. Target DNA hybridization was labeled with a cyanine (Cy3) fluorophore and the detection limit to DNA hybridization was estimated as 1 nM [60]. The novel “label-free” fluorescent detection approach was proposed by Piya and coauthors [75]. Arginylglycylaspartic acid (RGD) peptides have been used to provide non-selective adhesion of target J774 macrophage cells on (polyethylene glycol) PEG hydrogel patterned PSi Bragg reflectors. The J774 cells previously stained by calcein AM and adhered over peptides were lysed chemically. When the cells were lysed, there was a leakage of calcein from inside the cells due to the rupture of the cell membrane that led to a decrease in fluorescence intensity (Figure 3). This approach was suitable even for single cell detection, however, the selective layer was not described [75].
In [73,100], the authors reported on the visual colorimetric sensing techniques suitable for (bio)molecule detection. Photonic polymer modified PSi templates have shown prospective results for non-pathogenic E. coli and isopropanol alcohol detection. The key idea for the development of composite sensors capitalized on the high refractive index contrast afforded by Si. It was established that composite sensors gave a strong reflectance spectrum that was more readily seen by the eye when the sensor was wetted with the isopropanol solution. These photonic PSi/polymer composites have also shown enhanced sensitivity to E. coli when compared with all-polymer photonic sensors. This can be attributed to differences in their wettability, which affects E. coli adhesion [100]. Ramakrishan et al. reported on a PSi microcavity for autoimmune disease detection based on H2 B antigens or antibodies quantification via red, green, and blue (RGB) spectral analysis (Figure 4). Images for RGB analysis were captured by smartphone camera and blue color information was extracted. An extremely low concentration (10 fg/mL) of autoimmune antibody was detected, making this approach suitable for application [73].
Optical transmittance of PSi microring resonators and microcavities was used as the signal for sensor and biosensor applications [101,102,103,104]. Weiss et al. reported on 10 μm and 25 μm microring waveguides for nucleic acid (PNA) detection via transmittance measurements. It was established that PNA hybridization shifts the resonance peak at 2.00 nm and 1.48 nm for the 10 μm and 25 μm radius PSi rings, respectively. This difference in resonance shift with PNA treatment can be explained by the variation in molecular adsorption on the two samples [101,102]. Girault et al. proposed a similar approach for glucose quantification in aqueous solutions. Despite the fact that the LOD was estimated as 0.7 g/L, information about the selectivity to glucose was not available [103].
In parallel with the above-mentioned optical transducers, nano-Si is widely used for (bio)sensor application based on electrical and electrochemical responses [77]. For instance, I(J)-V measurements were carried out for the detection of biomolecules [79,105], gases [21,49,106,107,108], light [109,110,111], and pH [112,113,114]. Shashaani et al. reported about Mebendazole (MBZ) drug activity on breast cancer cells (MCF-7) adhered over a SiNW chip [105]. It was established that MCF-7 cells treated with MBZ drugs caused a significant (increased from 5 nA to 300 nA for 2 nM of MBZ) effect on I–V patterns due to the change in the ionic state of cytoplasm, and subsequently, the ionic equilibrium between the cell’s inner and outer parts. The detection limit to the MBZ drug tracing was calculated as 0.01 nM [105].
Capacitive [21,115,116] and resistive [45,115,117,118] responses of the nano-Si substrates were examined for gas and alcohol detection. Qin et al. reported on enhanced H2 adsorption on SiNWs fabricated by MACE and post-etched in KOH to enhance the surface rough. It was shown that relative resistance response to 200 ppm H2 was equal to 83% and significantly higher than for the same concentration of methanol, ethanol, isopropanol, acetone, or methane at room temperature [45]. In addition, Qin et al. reported on Polypyrrole (PPy) shell/Np functionalized SiNWs ([email protected] and [email protected]) suitable for ultra-low detection resolution (130 ppb) and excellent selectivity toward NH3 [118]. The underlying mechanism for the enhanced relative resistance response of [email protected] in comparison to the [email protected] was analyzed based on the modulation of PPy sensitization on axial conductance. In [115], PSi sensing elements on paper for humidity sensing were demonstrated. The detection approach was based on the relative resistance and capacitance measurements in environments with different humidity. The PSi based humidity sensor was used for real-time measurements and a relatively fast recovery was observed even though no refreshing methods were employed.
Thual et al. proposed a theoretical model of hybrid Psi–polymer optical waveguides for BSA detection [119]. Due to the PSi high specific surface and biocompatibility, it was used as the sensing part of the sensor. Additionally, polymer waveguides were fabricated for the reference part of the sensor due to their low optical losses. The theoretical limit of detection and sensitivity were calculated as 0.019 pg mm−2 and 12.5 nm/(pg mm−2), respectively.

4. (Bio)sensors Based on Nano-Si and Metals Oxides Nanocomposites

Currently, there is a growing number of publications dedicated to the (bio)sensing properties of nanocomposites based on nano-Si and metal oxide (MOx). Such significant interest in these types of nanomaterials can be explained by the enhanced sensitivity [17,24,120,121] and surface stability [25,26,122] of these nanocomposites. MOx nanoparticles and nanolayers synthesized over nano-Si can positively effect nano-Si surface passivation and degradation. The advances in nano-Si fabrication and MOx deposition enable the production of nanocomposites with tailored morphologies and electro-optical properties (photoluminescence, type of conductivity, etc.), which play a crucial role for the effective detection of (bio)molecules. Mainly, MOx nanolayers/nanoparticles can be deposited over a nano-Si surface through the following techniques: (i) RF and DC magnetron sputtering [24,34,36,37,120,121,123,124,125,126]; (ii) sol–gel/hydrothermal synthesis + spin coating [17,26,127,128,129,130,131]; (iii) drop casting technique + pulsed laser ablation in liquid [132]; (iv) vapor–liquid–solid growth and chemical vapor deposition [25,40,133]; (v) catalytic immersion method [134]; and (vi) electrochemical and chemical deposition [35,122,135].
Some types of nano-Si/MOx nanocomposites used as a (bio)sensor platform are shown in Figure 5.
It has been ascertained that silicon/MOx nanocomposites are widely used for gas detection through the I–V curve characterization [136], resistance [24,34,35,37,39,120,121,122,124,125,126,129,131,133,135,137,138], and capacitance [25,40] measurements. Generally, the main gas sensing mechanism is based on oxygen adsorption on the nano-Si/ MOx surface, causing electron extraction from the conductive band of semiconductors. This leads to a reduction in the electron concentration and hence the initial resistance increase or decrease for p-type and n-type semiconductors, respectively [37]. In the next step, chemisorbed oxygen species react with different molecules (H2, CO2, ethanol, acetone, isopropanol, toluene gas, etc.), releasing the electron back to the conductive band of the semiconductor, and causing a reverse change in resistance.
It was found that p-p and p-n heterojunctions formed at the interface of nano-Si/MOx nanocomposites play an important role in charge separation and charge life-time increasing due to the barrier layer formation. Liu et al. proposed that the composition of p-CuO and p-PSi led to a p-p heterojunction formation due to the different electron affinity (χ(CuO) = 4.07 eV, χ(PSi) = 4.01 eV) [124]. As the Fermi levels are not at the same level, electrons from CuO migrate to Psi, and holes migrate in the opposite direction until the Fermi energies become equal. This charge transfer leads to a formation of the depletion layers in PSi and CuO, respectively. The heterojunction effectively separates charges, resulting in the high concentration of holes in the accumulation layer and increased the lifetime of the charge carriers. This simplifies the electrons extracted from the conductive band of heterostructures during the gas adsorption. A similar mechanism was proposed for p-TiO2/p-PSi [34], p-Cu2O/p-PSi [135] and proven by experimental measurements.
A number of works have also been published on the p-n heterojunction by using a combination of p-type PSi and n-type ZnO [24,35,36,122,125,134], WO3 [36,129,137,138,139], SnO2 [122,133], V2O5 [37], and TiO2 [120]. The sensitivity of these nanocomposites was enhanced in comparison to the bare semiconductors and this can be explained as follows [120]: (a) a reduction in the surface activation energy Ea upon the formation of the p-n heterojunction, resulting in increased analyte adsorption; (b) the presence of oxygen species and dangling bonds on PSi/MOx, and as a consequence, more reaction sites on the surface, which improved the adsorption of target molecules. As an example, Figure 6 shows the band diagram of TiO2/PSi. The formation of the heterojunction produces the barrier effect, so electrons lose their capacity to move from the n to p side. In this case, the holes play a main role in sensing. When the surface of the nanocomposites is exposed to air, the number of holes on the surface increases (Equation (1)) [120].
1/2 O2 (g) → O(ads) + h+,
when the sensor is treated with some gases, free electrons are injected to the surface, and neutralized holes result in an increase in sensor resistance.
It should be noted that tuning the scale of the MOx nanolayer or nanoparticles and the morphology of the Si surface are very important elements for sensor design. Husairi et al. showed that the PSi/ZnO sensor response to ethanol depends on the concentration and type of defects and area of active sites for absorption as the number of defects and active species on the PSi/ZnO surface was directly affected by the precursor (Zn(NO3)26H2O) concentration [134]. In [122,125], ZnO nanolayers were deposited over PSi and c-Si by using zinc acetate (ZA) and carbonate (ZC) precursors via chemical bath deposition (CBD) and the magnetron-sputtering technique, respectively. It was demonstrated that PSi/ZnO possessed enhanced sensitivity in comparison to c-Si/ZnO. This was due to the increase in the PSi/ZnO effective surface area, resulting in higher adsorption on its surface [125]. On the other hand, the PSi/ZnO substrate deposited using ZC showed a better response to CO2 than film deposited using ZA due to a more homogeneous covering [122].
Nano-Si/MOx nanocomposites have been applied as biosensors [26,130,140]. In [26], PSi/TiO2 substrates showed enhanced sensitivity to mycotoxins in comparison with pure PSi. Before the sensing experiment, PSi/TiO2 and Psi were functionalized by (3-Glycidyloxypropyl)trimethoxysilane (GPTMS) and selectivity to the mycotoxins was achieved by using hybridized aptamers of mycotoxins. Furthermore, both substrates were exposed to the same concentration of Cy3-labeled mycotoxins and fluorescence intensities were collected by utilizing a fluorescence scanner. It was found that the fluorescence intensity of the analyte on the PSi/TiO2 surface was almost 14 times higher than the thermally oxidized PSi surface. This result can be attributed to the following reasons: (i) the surface of PSi/TiO2 was more stable than PSiO2; and (ii) the surface of PSi/TiO2 had more active sites for analyte immobilization. The emission intensity of the dye was increased because the polar TiO2 surface enhanced the delocalization of the π electrons and lowered the highest occupied molecular orbital and lowest unoccupied molecular orbital energy levels of the dye [26].
The sensitivity of nano-Si/MOx via noble metal deposition [15,36,38,121,139,141,142,143] has also been studied. It a found that noble metal (Ag, Au, Pt, Pd) nanoparticles, imbedded into nano-Si /MOx nanocomposite play an important role in charge generation and significantly increases the quantity of the chemisorption of oxygen ions O and creates additional active sites, leading to the formation of a deeper depletion region in comparison to that of pure sensors [80,112,115]. Herein, Qiang et al. reported on enhanced sensitivity of PSi/WO3/Pd nanocomposites to NH3 [139] (Figure 7a) and NO2 [15] gases. The main differences between the PSi/WO3/Pd and PSi/WO3 sensing mechanisms were explained by the following (Figure 7b,c) [139]:
  • In the case of the PSi/WO3 nanocomposite, the sensing mechanism directly depends on the heterojunction parameters and efficiency of O2 absorption-desorption;
  • PSi/WO3 substrates decorated with Pd NPs would possess enhanced catalytic activity that will lead to enhanced dissociation of oxygen molecules O2 and absorption of oxygen ions O on the PSi/WO3/Pd surface. More ion absorbed oxygen on the surface would provide more sensing sites, leading to enhanced gas response and reaction rate.
  • Additionally, the work function of Pd was larger than that of WO3, therefore the electrons from WO3 will transfer to Pd, causing the generation of the Schottky barrier at the interface between Pd and WO3. By these reasons, the conduction band of PSi/WO3/Pd will become much narrower when compared with WO3 and the concentration of the conduction electrons will be reduced. As a consequence, the interaction of NH3 molecules with the PSi/WO3/Pd substrate will lead to more significant resistance variation and higher sensor response.

5. (Bio)sensors Based on Nano-silicon and Metals Nanoparticles

The large active surface of nano-Si as well as enhanced stability, catalytic activity, and surface-enhanced Raman scattering (SERS) of the metal nanoparticles in combination are very promising for highly-sensitive (bio)sensor applications. Therefore, different nano-Si/metal nanocomposites (MNps) have been widely employed for rationally designing and fabricating high-performance (bio)sensors for the detection of various chemical and biological species [144]. The deposition of metal nanoparticles/nanofilms over all types of nano-Si can be implemented by the following techniques: (i) magnetron sputtering [31,51,145,146,147,148,149]; (ii) immersion, chemical, and electrochemical depositions [13,20,27,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170]; (iii) thermal evaporation [32,44,171,172,173,174,175,176,177,178,179]; and (vi) laser ablation technique/pulsed laser deposition [180,181].
Nowadays, nano-Si/MNps nanocomposites have been utilized for (bio)sensors based on SERS [12,20,31,32,51,145,149,150,151,152,153,154,155,165,168,173,175,176,177,178,182,183,184], optical [13,44,158,164,167,171,180], and electrical [27,146,148,156,159,160,161,162,166,169,170,172,173,179,181,185,186] responses. Among all of these approaches, SERS of MNps decorated nano-Si is extensively exploited as the most efficient spectroscopic phenomenon for high-sensitive sensing. The development of a practically applicable SERS-based (bio)sensor requires an efficient SERS substrate, which possesses strong enhancement factors (EF), robustness, stability, uniformity, and reproducibility. It was found that PSi has a major flaw for these applications because the surface morphology has an uncontrolled stochastic character, making it impossible for hot spots to be uniformly distributed over the surface [51,177]. Therefore, 3D nano-Si substrates such as SiNPLs and SiNWs are more suitable for SERS-based (bio)sensors because of their well-ordered surface, leading to uniform distribution and the accessibility of hot spots (see Section 2). Furthermore, arrays of SiNPLs and SiNWs stabilize the distribution of MNps, which results in high EF and excellent reproducibility with a low detection limit [149]. For instance, in [31,51,149,177], 3D SiNPs/Ag and SiNPs/Au nanocomposites were utilized for Rhodamine 6G (R6G) molecule detection via SERS. The authors showed that the smallest limit of R6G detection was equal to 10−13 M [149]. This was attributed to the high EF (2.4 × 108) achieved due to the well-organized fabrication and variation of wavelength excitation.
In order to obtain a high-sensitive SERS–active platform, the authors in [20] proposed a multi-step fabrication process including the following steps: (i) fabrication of Ag dendrites; (ii) AuNPs deposition over Ag dendrites; (iii) synthesis of Si nanoneedles; and (iv) nanoneedle decoration by AgNPs. The authors noted that such 3D multi-structures were fabricated to achieve a much stronger enhancement when compared with the SERS-active AgNPs or 1DAg dendrites. Additionally, the hierarchical scaffolds and the hydrophilic performance could endow the substrates with improved sensitivity and reproducibility. Eventually, the substrates showed a low limit of detection to malachite green (~10−13 M), which may be promising in the field of sensing, imaging, and clinical diagnosis.
In [12,184], SERS measurements were applied for real sample investigation. Hakonen et al. constructed a handheld (Figure 8a,b) device based on the SiNWs/Au SERS signal for polar organic liquids O-ethyl S-(2-diisopropylaminoethyl) methylphosphonothiolate (VX) and Tabun detection at ambient conditions [12]. The low detection limits were achieved for nerve gases due to high droplet adhesion. The high sensitivity result of the small droplet contact area and target molecule accumulation within the SERS hot-spots were formed by clustered nanopillars. Cui et al. reported on flexible, transparent, and self-standing SiNWs/Au consisting of ultrathin three- dimensional SiNW networks suitable for pesticide residue detection via SiNWs/Au wrapping onto the lemon surface [184]. SERS signals were collected by two approaches: (i) directly, from the lemon surface with a previously adhered small piece of SiNWs/Au and treated with ethanol; (ii) SiNWs/Au paper could be torn off the lemon surface before the ethanol completely evaporated and the Raman signal could be recorded from the sample placed on a flat Si substrate or glass. The limit of detection to pesticides on the lemon surface was estimated as 72 ng/cm2 for both approaches, meaning that this technique has the potential for fast in situ and nondestructive sensing (Figure 8c).
In [52,181], SiNWs/Pt/Pd and SiNWs/Pd were used for H2 detection via resistance and I–V measurements, respectively. It was suggested that H2 physical and chemical adsorption on Pt/Pd nanoparticles takes place through the incorporation of hydrogen atoms into a metal lattice (MHx) [181]. Physisorbed molecules on the nanoparticle’s surface and H species incorporated in the interstitial sites of the Pt/Pd NPs can act as electron scattering centers and decrease the carrier mobility, causing an increase in the electrical resistance of the Pt/Pd ultra-thin film. When Pt/Pd is deposited over the SiNWs, it is also will take the place of the shortest current path by contacting the neighboring clusters and thus perfect contacts can be formed between almost all nanowires inside each cluster at higher H2 concentration ranges. For this reason, after hydrogen absorption, electron scattering was reduced and the resistance change was rapid, this phenomenon forms the basis of H2 detection. Such a point of view has correlation with the results published in [52]. In the process of the H2 deposition over SiNWs/Pd, they dissociated into hydrogen atoms, causing the I–V curve to shift and a significant reduction in the current. These processes can be explained by the SiNWs/Pd Schottky barrier increasing (from 0.678 meV to 0.685 meV) when H2 was adsorbed. It was noted, that according to the Butler theory, the absorption and desorption of H2 in a thin layer of Pd at room temperature and pressure leads to the reversible hydride PdHx, where x is the atomic ratio H/Pd [52]. The absorption of H2 can be related to a crystallographic phase transition.
In our previous research [13], we showed that Au nanoparticles deposited onto the PSi surface led to an increase in the sensitivity to the target (Aflatoxin B1) and decreased the response time of the immunosensors. The analytical performance of the PSi/Au PL-based immunosensor showed very good characteristics with a maximal sensitivity range within 0.01–10 ng/mL. Compared to the standard enzyme-linked immunosorbent assay (ELISA) [3] method, the Au/PSi immunosensor showed about 100 times lower concentration range. In [180], PL-based sensing was performed for ethanol, n-hexane, and trichloroethylene detection on a PSi/Au platform. It was found that the PL intensity of the PSi/Au nanocomposite in ethanol vapor was significantly less compared with the PL intensity in n-hexane and/or trichloroethylene. This can be attributed to the larger dipole moment in ethanol, leading to the enhancing of non-radiative emissions in the PSi/Au surface layer.
Cui et al. reported on the 2D PSi/Au platform for explosives detection and identification [164]. The main idea of this approach was based on the simultaneous measurements of PSi/Au electroluminescence (ELC) peak intensity and position under interaction with explosives including nitro compounds, peroxides with nitrogen atoms, and peroxides without nitrogen atoms due to their different oxidation and electron transfer ability. In this case, Au nanoparticles catalyze the oxidation reaction between PSi and H2O2 and due to this, the ELC change is faster in comparison with bare PSi. Consequently, it was established that pre-oxidation of PSi with oxidants could introduce surface defects and, accordingly not only quench the ECL intensity, but also decrease the rate of the initial peak shift when compared with the blank PSi. In contrast, explosives containing the nitro group could just quench the ECL of PSi through the electron transfer process but without a pre-oxidative effect, whereas compounds with an electron donating ability (e.g., amine group) could enhance the ECL intensity. However, if this compound also contains a peroxy group, the quenching and enhancing effect might be counteracted.

6. (Bio)sensors Based on Nano-Si and Carbon-based Nanomaterials

As previously mentioned, the current trends in (bio)sensors are oriented toward the development of novel composite nanomaterials in order to obtain sensing substrates with enhanced surface to volume ratio, biocompatibility, and sensitivity. In the last decade, carbon based materials (carbon nanotubes (CNT), graphene (G), graphene oxide (GO)) have recommended themselves as efficient platforms suitable for (bio)sensor applications due to their high electron mobility, large surface area, and biocompatibility. Therefore, it is expected that materials based on carbon nanomaterials incorporated with nano-Si will possess more efficient sensing with a wide detection range and low detection limit. Another advantage lies in the fabrication process, which is not labor intensive and not time consuming, for instance, graphene can be synthesized over nano-Si through the in situ CVD process [187]. In [188,189], fabrication processes were carried out by the separate preparation of nano-Si and graphene substrates with the following graphene transfer on the nano-Si surfaces. In the case of graphene oxide, it can be covalently bonded to the PSi in the presence of EDC/NHS [190] and added dropwise over the substrate followed by spin coating [191].
Currently, nano-Si/carbon-based nanomaterials have been examined as (bio)sensor platforms with optical [187,190,192,193] and electrical [188,189,191,192,194] responses and have shown prospective results for future investigation and application. For instance, in [187] and [193], SiNWs/GNP/AuNP and GO/AgNPs/[email protected] substrates were utilized for R6G determination via SERS measurements. Additionally, it was found that GO modified AgNPs/[email protected] substrates possessed higher SERS enhanced factor (2 × 1012) in comparison with bare AgNPs/[email protected] (6,7 × 1011) [193]. This can be attributed to the well distributed hot spots and the GO films covering both AgNPs and spaces could make the probe molecule more effectively absorbed around the hot spots. While in the case of the absence of the GO film, the molecules will be distributed unevenly on the AgNPs/[email protected] substrate, which will lead to the weak homogeneity of the SERS signal.
Eom et al. reported on PSi/graphene substrates suitable for room-temperature H2 gas detection via resistance measurements [194]. The main idea of this technique is similar to that of gas detection using nano-Si materials decorated with metal and/or MOx nanospecies. Generally, the sensing mechanism can be explained by the Schottky junction generation and formation of an electric depletion layer near the p-type Si and the hole accumulation layer near the graphene due to the difference in the Si and G work functions. Upon adsorption of the hydrogen gas molecules to the surface of the PSi/graphene, the accumulated holes near the graphene react with hydrogen molecules. As a consequence of this interaction, ionized hydrogen is formed, consequently leading to the reduction in the carrier density in the graphene layer. The conductivity of G-doped/p-Si becomes weaker due to the decreased graphene carrier concentration. Additionally, when the hydrogen gas was removed, the oxygen molecules in air react with the formed ionized hydrogen on the graphene and p-type Si, which increases the hole accumulation layer of graphene and decreases the ionized hydrogen in the p-type silicon, consequently, the conductivity of the PSi/graphene becomes higher (Figure 9).
Table 1 presents some of the main results on the application of nano-Si composites for (bio)sensor application. Table is divided into four sections, each of them corresponding to the nanostructures presented in Section 3, Section 4, Section 5 and Section 6.

7. Conclusions and Future Work

In this paper, we have provided an overview of the recent progress in (bio)sensing with nano-Si and nano-Si composites with polymers, MOx, metal nanoparticles, and carbon-based materials. It was found that novel nanocomposites are suitable for different detection techniques whereas pure nano-Si did not show acceptable results. For instance, pure nano-Si is hardly used for the SERS-based detection approach, while the nano-Si/MNps composites have recommended themselves as efficient SERS-active platforms with a high enhanced factor. Additionally, nano-Si, combined with the above-mentioned nanomaterials, possesses a number of different advantages such as the opportunity to obtain material with the necessary parameters and properties as well as using different surface (bio)functionalization protocols.
Significant attention has been paid to the estimation of gas sensing mechanisms. It should be noted that the nano-Si/MOx sensing mechanisms that have been provided in different publications have good correlation between each other and could be established as the fundamental knowledge in gas detection theory. Furthermore, novel sensing mechanisms have been proposed for more complicated nanostructures such as nano-Si/MOx/MNps. In this case, new effects are appearing and totally changing the type and rate of “sensor surface–gas” interaction.
Basic approaches and biosensing mechanisms that are now in use for nano-Si sensors have also been presented in detail. The advantages of this class of materials are that they can detect the target molecules in real-time with minimal sample damage and good repeatability. It can clearly be seen that researchers working in the area of improving the design and scheme of sensing equipment will gradually move to the size of microfluidic systems that possess a high precision of sample analysis. However, the fast response time, sensitivity, selectivity, long-term stability, and portable nano-Si based sensor devices remain important challenges for their future commercial applications.
To summarize the above-mentioned, there are many important challenges for the further prospective of nano-Si for fast and real-time diagnostic/detection. However, it can be clearly seen that all of the points of challenge could be solved through different approaches and techniques. For instance, filters can help to avoid the noise and background signal. A thick polymer layer coverage or combination of nano-Si with MOx, MNps, etc. could be used to achieve the nano-Si surface stability. The sensor’s signal homogeneity directly depends on the sensor’s surface homogeneity, which can be achieved by precise fabrication techniques such as electron beam lithography, photolithography, reactive ion lithography, etc. Microfluidic systems with incorporated nano-Si are the most prospective for the field of medicine and allows for the minimization of the necessary volume of detection solution. Other advantages of the microfluidic system are the small dimensions and the possibility of monitoring samples in real-time. The area of nano-Si sensor design is a multidisciplinary field, and many researchers are working on these challenges, furthermore, the rapid development of nanoscience and the appearance of novel tools will speed up the applied use of nano-Si.

Author Contributions

I.I. conceived the original idea and supervised the project. V.M. wrote the manuscript with support from I.I.

Funding

This research was funded by NCBR of Poland through the project “Środowiskowe interdyscyplinarne studia doktoranckie w zakresie nanotechnologii”, grant number POWR.03.02.00-00-I032/16. This research was also funded by NCN of Poland through the SONATA 11 project, grant number UMO-2016/21/D/ST3/00962 and MSCA-RISE - Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) through the “Novel 1D photonic metal oxide nanostructures for early stage cancer detection” project, grant number 778157.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Uhlir, A. Electrolytic Shaping of Germanium and Silicon. Bell Syst. Tech. J. 1956, 35, 333–347. [Google Scholar] [CrossRef]
  2. Cullis, A.G.; Canham, L.T. Visible light emission due to quantum size effects in highly porous crystalline silicon. Nature 1991, 353, 335–338. [Google Scholar] [CrossRef]
  3. Myndrul, V.; Viter, R.; Savchuk, M.; Shpyrka, N.; Erts, D.; Jevdokimovs, D.; Silamiķelis, V.; Smyntyna, V.; Ramanavicius, A.; Iatsunskyi, I. Porous silicon based photoluminescence immunosensor for rapid and highly-sensitive detection of Ochratoxin A. Biosens. Bioelectron. 2018, 102, 661–667. [Google Scholar] [CrossRef] [PubMed]
  4. Iatsunskyi, I.; Nowaczyk, G.; Jurga, S.; Fedorenko, V.; Pavlenko, M.; Smyntyna, V. One and two-phonon Raman scattering from nanostructured silicon. Optik 2015, 126, 1650–1655. [Google Scholar] [CrossRef]
  5. Brytavskyi, I.; Hušeková, K.; Myndrul, V.; Pavlenko, M.; Coy, E.; Zaleski, K.; Gregušová, D.; Yate, L.; Smyntyna, V.; Iatsunskyi, I. Effect of porous silicon substrate on structural, mechanical and optical properties of MOCVD and ALD ruthenium oxide nanolayers. Appl. Surf. Sci. 2019, 471, 686–693. [Google Scholar] [CrossRef]
  6. Pavlenko, M.; Coy, E.L.; Jancelewicz, M.; Załęski, K.; Smyntyna, V.; Jurga, S.; Iatsunskyi, I. Enhancement of optical and mechanical properties of Si nanopillars by ALD TiO2 coating. RSC Adv. 2016, 6, 97070–97076. [Google Scholar] [CrossRef]
  7. Pavlenko, M.; Myndrul, V.; Iatsunskyi, I.; Jurga, S.; Smyntyna, V. Study on structural and optical properties of TiO2 ALD coated silicon nanostructures. In Proceedings of the Nanophotonics VI, Brussels, Belgium, 3–7 April 2016; Andrews, D.L., Nunzi, J.-M., Ostendorf, A., Eds.; SPIE: Bellingham, DC, USA, 2016; p. 98842H. [Google Scholar]
  8. Graniel, O.; Fedorenko, V.; Viter, R.; Iatsunskyi, I.; Nowaczyk, G.; Weber, M.; Załęski, K.; Jurga, S.; Smyntyna, V.; Miele, P.; et al. Optical properties of ZnO deposited by atomic layer deposition (ALD) on Si nanowires. Mater. Sci. Eng. B 2018, 236, 139–146. [Google Scholar] [CrossRef]
  9. Ge, M.; Rong, J.; Fang, X.; Zhou, C. Porous doped silicon nanowires for lithium ion battery anode with long cycle life. Nano Lett. 2012, 12, 2318–2323. [Google Scholar] [CrossRef]
  10. Pavlenko, M.; Siuzdak, K.; Coy, E.; Jancelewicz, M.; Jurga, S.; Iatsunskyi, I. Silicon/TiO2 core-shell nanopillar photoanodes for enhanced photoelectrochemical water oxidation. Int. J. Hydrogen Energy 2017, 42, 30076–30085. [Google Scholar] [CrossRef]
  11. Fan, Q.; Wang, Z.; Cui, Y. Optimal design of an antireflection coating structure for enhancing the energy-conversion efficiency of a silicon nanostructure solar cell. RSC Adv. 2018, 8, 34793–34807. [Google Scholar] [CrossRef]
  12. Hakonen, A.; Rindzevicius, T.; Schmidt, M.S.; Andersson, P.O.; Juhlin, L.; Svedendahl, M.; Boisen, A.; Käll, M. Detection of nerve gases using surface-enhanced Raman scattering substrates with high droplet adhesion. Nanoscale 2016, 8, 1305–1308. [Google Scholar] [PubMed]
  13. Myndrul, V.; Viter, R.; Savchuk, M.; Koval, M.; Starodub, N.; Silamiķelis, V.; Smyntyna, V.; Ramanavicius, A.; Iatsunskyi, I. Gold coated porous silicon nanocomposite as a substrate for photoluminescence-based immunosensor suitable for the determination of Aflatoxin B1. Talanta 2017, 175, 297–304. [Google Scholar] [CrossRef] [PubMed]
  14. Tereshchenko, A.; Bechelany, M.; Viter, R.; Khranovskyy, V.; Smyntyna, V.; Starodub, N.; Yakimova, R. Optical biosensors based on ZnO nanostructures: Advantages and perspectives. A review. Sens. Actuators B Chem. 2016, 229, 664–677. [Google Scholar]
  15. Qiang, X.; Hu, M.; Zhao, B.; Qin, Y.; Yang, R.; Zhou, L.; Qin, Y. Effect of the Functionalization of Porous Silicon/WO3 Nanorods with Pd Nanoparticles and Their Enhanced NO2-Sensing Performance at Room Temperature. Materials 2018, 11, 764. [Google Scholar] [CrossRef] [PubMed]
  16. Rahimi, F.; Mohammadnejad Arough, J.; Yaghoobi, M.; Davoodi, H.; Sepehri, F.; Amirabadizadeh, M. A novel approach for osteocalcin detection by competitive ELISA using porous silicon as a substrate. Biotechnol. Appl. Biochem. 2017, 64, 871–878. [Google Scholar] [CrossRef] [PubMed]
  17. Shahkarami, M.M.H.; Koohsorkhi, J.; Fard, H.G. Fabrication of High Sensitive UV Photodetector Based on n-ZnO Nanowire/n-Porous-Si Heterojunction. Nano 2017, 12, 1–9. [Google Scholar]
  18. Syshchyk, O.; Skryshevsky, V.A.; Soldatkin, O.O.; Soldatkin, A.P. Enzyme biosensor systems based on porous silicon photoluminescence for detection of glucose, urea and heavy metals. Biosens. Bioelectron. 2015, 66, 89–94. [Google Scholar] [CrossRef]
  19. Iatsunskyi, I.; Myndrul, V.; Smyntyna, V.; Viter, R.; Melnyk, Y.; Pavlova, K. Porous silicon photoluminescence biosensor for rapid and sensitive detection of toxins. In Proceedings of the Organic Sensors and Bioelectronics X, San Diego, CA, USA, 6–10 August 2017; Shinar, R., Kymissis, I., Torsi, L., Eds.; SPIE: Bellingham, DC, USA, 2017; p. 28. [Google Scholar]
  20. Huang, J.; Ma, D.; Chen, F.; Bai, M.; Xu, K.; Zhao, Y. Ag Nanoparticles Decorated Cactus-Like Ag Dendrites/Si Nanoneedles as Highly Efficient 3D Surface-Enhanced Raman Scattering Substrates toward Sensitive Sensing. Anal. Chem. 2015, 87, 10527–10534. [Google Scholar] [CrossRef]
  21. Harraz, F.A.; Ismail, A.A.; Faisal, M.; Al-Sayari, S.A.; Al-Hajry, A.; Al-Assiri, M.S. Organic analytes sensitivity in meso-porous silicon electrical sensor with front side and backside contacts. Arab. J. Chem. 2017. [Google Scholar] [CrossRef]
  22. Basu, D.; Sarkar, T.; Sen, K.; Hossain, S.M.; Das, J. Multi-Parametric Optical Glucose Sensor Based on Surface Functionalized Nano-Porous Silicon. IEEE Sens. J. 2018, 18, 9940–9947. [Google Scholar] [CrossRef]
  23. Iatsunskyi, I.; Smyntyna, V.; Pavlenko, M.; Kanevska, O.; Kirik, Y.; Myndrul, V. Ammonia detection using optical reflectance from porous silicon formed by metal-assisted chemical etching. In Proceedings of the SPIE—The International Society for Optical Engineering, Dresden, Germany, 23–26 September 2013; Zamboni, R., Kajzar, F., Szep, A.A., Burgess, D., Owen, G., Eds.; SPIE: Bellingham, DC, USA, 2013; Volume 8901, p. 89010K. [Google Scholar]
  24. Al-Salman, H.S.; Abdullah, M.J. Preparation of ZnO nanostructures by RF-magnetron sputtering on thermally oxidized porous silicon substrate for VOC sensing application. Meas. J. Int. Meas. Confed. 2015, 59, 248–257. [Google Scholar] [CrossRef]
  25. Wang, L.L.; Kang, L.P.; Wang, H.Y.; Chen, Z.P.; Li, X.J. Capacitive humidity sensitivity of SnO2: Sn thin film grown on silicon nanoporous pillar array. Sens. Actuators B Chem. 2016, 229, 513–519. [Google Scholar] [CrossRef]
  26. Liu, R.; Li, W.; Cai, T.; Deng, Y.; Ding, Z.; Liu, Y.; Zhu, X.; Wang, X.; Liu, J.; Liang, B.; et al. TiO2 Nanolayer-Enhanced Fluorescence for Simultaneous Multiplex Mycotoxin Detection by Aptamer Microarrays on a Porous Silicon Surface. ACS Appl. Mater. Interfaces 2018, 10, 14447–14453. [Google Scholar] [CrossRef] [PubMed]
  27. Qin, Y.; Liu, D.; Wang, Z.; Jiang, Y. Ag nanoparticles-functionalized rough silicon nanowires array and its unique response characteristics to ultrararefied NO2. Sens. Actuators B Chem. 2018, 258, 730–738. [Google Scholar] [CrossRef]
  28. Iatsunskyi, I.; Jancelewicz, M.; Nowaczyk, G.; Kempiński, M.; Peplińska, B.; Jarek, M.; Załęski, K.; Jurga, S.; Smyntyna, V. Atomic layer deposition TiO2 coated porous silicon surface: Structural characterization and morphological features. Thin Solid Films 2015, 589, 303–308. [Google Scholar] [CrossRef]
  29. Iatsunskyi, I.; Pavlenko, M.; Viter, R.; Jancelewicz, M.; Nowaczyk, G.; Baleviciute, I.; Załęski, K.; Jurga, S.; Ramanavicius, A.; Smyntyna, V. Tailoring the structural, optical, and photoluminescence properties of porous silicon/TiO2 nanostructures. J. Phys. Chem. C 2015, 119, 7164–7171. [Google Scholar] [CrossRef]
  30. Iatsunskyi, I.; Kempiński, M.; Nowaczyk, G.; Jancelewicz, M.; Pavlenko, M.; Załeski, K.; Jurga, S. Structural and XPS studies of PSi/TiO2 nanocomposites prepared by ALD and Ag-assisted chemical etching. Appl. Surf. Sci. 2015, 347, 777–783. [Google Scholar] [CrossRef]
  31. Zhao, Y.; Zhang, Y.L.; Huang, J.A.; Zhang, Z.; Chen, X.; Zhang, W. Plasmonic nanopillar array embedded microfluidic chips: An in situ SERS monitoring platform. J. Mater. Chem. A 2015, 3, 6408–6413. [Google Scholar] [CrossRef]
  32. Bryche, J.F.; Bélier, B.; Bartenlian, B.; Barbillon, G. Low-cost SERS substrates composed of hybrid nanoskittles for a highly sensitive sensing of chemical molecules. Sens. Actuators B Chem. 2017, 239, 795–799. [Google Scholar] [CrossRef]
  33. Bandarenka, H.; Girel, K.; Zavatski, S.; Panarin, A.; Terekhov, S. Progress in the Development of SERS-Active Substrates Based on Metal-Coated Porous Silicon. Materials 2018, 11, 852. [Google Scholar] [CrossRef]
  34. Dwivedi, P.; Dhanekar, S.; Das, S.; Chandra, S. Effect of TiO2 Functionalization on Nano-Porous Silicon for Selective Alcohol Sensing at Room Temperature. J. Mater. Sci. Technol. 2017, 33, 516–522. [Google Scholar] [CrossRef]
  35. Yan, D.; Li, S.; Liu, S.; Tan, M.; Li, D.; Zhu, Y. Electrochemical synthesis of ZnO nanorods/porous silicon composites and their gas-sensing properties at room temperature. J. Solid State Electrochem. 2016, 20, 459–468. [Google Scholar]
  36. Kumar, A.; Sanger, A.; Kumar, A.; Chandra, R. Porous silicon filled with Pd/WO3-ZnO composite thin film for enhanced H2 gas-sensing performance. RSC Adv. 2017, 7, 39666–39675. [Google Scholar] [CrossRef]
  37. Yan, W.; Hu, M.; Wang, D.; Li, C. Room temperature gas sensing properties of porous silicon/V2O5 nanorods composite. Appl. Surf. Sci. 2015, 346, 216–222. [Google Scholar] [CrossRef]
  38. Zhao, X.-Y.; Wang, G.; Hong, M. Hybrid structures of Fe3O4 and Ag nanoparticles on Si nanopillar arrays substrate for SERS applications. Mater. Chem. Phys. 2018, 214, 377–382. [Google Scholar] [CrossRef]
  39. Zhao, S.; Li, Z.; Wang, G.; Liao, J.; Lv, S.; Zhu, Z. Highly enhanced response of MoS2/porous silicon nanowire heterojunctions to NO2 at room temperature. RSC Adv. 2018, 8, 11070–11077. [Google Scholar] [CrossRef]
  40. Feng, M.H.; Wang, W.C.; Li, X.J. Capacitive humidity sensing properties of CdS/ZnO sesame-seed-candy structure grown on silicon nanoporous pillar array. J. Alloy. Compd. 2017, 698, 94–98. [Google Scholar] [CrossRef]
  41. Visser, D.; Choudhury, B.D.; Krasovska, I.; Anand, S. Refractive index sensing in the visible/NIR spectrum using silicon nanopillar arrays. Opt. Express 2017, 25, 12171. [Google Scholar] [CrossRef]
  42. Iatsunskyi, I.; Jurga, S.; Smyntyna, V.; Pavlenko, M.; Myndrul, V.; Zaleska, A. Raman spectroscopy of nanostructured silicon fabricated by metal-assisted chemical etching. In Proceedings of the SPIE—The International Society for Optical Engineering, Brussels, Belgium, 13–17 April 2014; Gorecki, C., Asundi, A.K., Osten, W., Eds.; SPIE: Bellingham, DC, USA, 2014; Volume 9132, p. 913217. [Google Scholar]
  43. Lv, J.; Zhang, T.; Zhang, P.; Zhao, Y.; Li, S. Review Application of Nanostructured Black Silicon. Nanoscale Res. Lett. 2018, 13, 110. [Google Scholar] [CrossRef]
  44. Zhao, X.; Alizadeh, M.H.; Reinhard, B.M. Harnessing Leaky Modes for Fluorescence Enhancement in Gold-Tipped Silicon Nanowires. J. Phys. Chem. C 2016, 120, 20555–20562. [Google Scholar] [CrossRef]
  45. Qin, Y.; Wang, Y.; Liu, Y.; Zhang, X. KOH post-etching-induced rough silicon nanowire array for H2 gas sensing application. Nanotechnology 2016, 27, 465502. [Google Scholar] [CrossRef] [PubMed]
  46. Albuschies, J.; Baus, M.; Winkler, O.; Hadam, B.; Spangenberg, B.; Kurz, H. High-density silicon nanowire growth from self-assembled Au nanoparticles. Microelectron. Eng. 2006, 83, 1530–1533. [Google Scholar] [CrossRef]
  47. Liu, M.; Jin, P.; Xu, Z.; Hanaor, D.A.H.; Gan, Y.; Chen, C.Q. Two-dimensional modeling of the self-limiting oxidation in silicon and tungsten nanowires. Theor. Appl. Mech. Lett. 2016, 6, 195–199. [Google Scholar] [CrossRef]
  48. Cornago, I.; Hernández, A.L.; Casquel, R.; Holgado, M.; Laguna, M.F.; Sanza, F.J.; Bravo, J. Bulk sensing performance comparison between silicon dioxide and resonant high aspect ratio nanopillars arrays fabricated by means of interference lithography. Opt. Mater. Express 2016, 6, 2264. [Google Scholar] [CrossRef]
  49. Li, W.; Ding, C.; Cai, Y.; Liu, J.; Wang, L.; Ren, Q.; Xu, J. Enhanced Humidity Sensitivity with Silicon Nanopillar Array by UV Light. Sensors 2018, 18, 660. [Google Scholar] [CrossRef] [PubMed]
  50. Chang, C.C.; Liu, Y.R.; Chen, C.Y. Highly-antireflective porous Si films prepared with metal-assisted chemical etching. Surf. Coat. Technol. 2016, 303, 232–236. [Google Scholar] [CrossRef]
  51. Lin, D.; Wu, Z.; Li, S.; Zhao, W.; Ma, C.; Wang, J.; Jiang, Z.; Zhong, Z.; Zheng, Y.; Yang, X. Large-Area Au-Nanoparticle-Functionalized Si Nanorod Arrays for Spatially Uniform Surface-Enhanced Raman Spectroscopy. ACS Nano 2017, 11, 1478–1487. [Google Scholar] [CrossRef]
  52. Zhu, L.S.; Zhang, J.; Xu, X.W.; Yu, Y.Z.; Wu, X.; Yang, T.; Wang, X.H. Room temperature H2 detection based on Pd/SiNWs/p-Si Schottky diode structure. Sens. Actuators B Chem. 2016, 227, 515–523. [Google Scholar] [CrossRef]
  53. Tang, Y.; Li, Z.; Luo, Q.; Liu, J.; Wu, J. Bacteria detection based on its blockage effect on silicon nanopore array. Biosens. Bioelectron. 2016, 79, 715–720. [Google Scholar] [CrossRef]
  54. Arshavsky-Graham, S.; Massad-Ivanir, N.; Paratore, F.; Scheper, T.; Bercovici, M.; Segal, E. On Chip Protein Pre-Concentration for Enhancing the Sensitivity of Porous Silicon Biosensors. ACS Sens. 2017, 2, 1767–1773. [Google Scholar] [CrossRef]
  55. Vilensky, R.; Bercovici, M.; Segal, E. Oxidized Porous Silicon Nanostructures Enabling Electrokinetic Transport for Enhanced DNA Detection. Adv. Funct. Mater. 2015, 25, 6725–6732. [Google Scholar] [CrossRef]
  56. Massad-Ivanir, N.; Shtenberg, G.; Raz, N.; Gazenbeek, C.; Budding, D.; Bos, M.P.; Segal, E. Porous Silicon-Based Biosensors: Towards Real-Time Optical Detection of Target Bacteria in the Food Industry. Sci. Rep. 2016, 6, 38099. [Google Scholar] [CrossRef] [PubMed]
  57. Urmann, K.; Reich, P.; Walter, J.G.; Beckmann, D.; Segal, E.; Scheper, T. Rapid and label-free detection of protein a by aptamer-tethered porous silicon nanostructures. J. Biotechnol. 2017, 257, 171–177. [Google Scholar] [CrossRef] [PubMed]
  58. Li, P.; Jia, Z.; Lü, X.; Liu, Y.; Ning, X.; Mo, J.; Wang, J. Spectrometer-free biological detection method using porous silicon microcavity devices. Opt. Express 2015, 23, 24626. [Google Scholar] [CrossRef] [PubMed]
  59. Wu, W.; Mao, H.; Han, X.; Xu, J.; Wang, W. Fabrication and characterization of SiO2/Si heterogeneous nanopillar arrays. Nanotechnology 2016, 27, 305301. [Google Scholar] [CrossRef] [PubMed]
  60. Serre, P.; Stambouli, V.; Weidenhaupt, M.; Baron, T.; Ternon, C. Silicon nanonets for biological sensing applications with enhanced optical detection ability. Biosens. Bioelectron. 2015, 68, 336–342. [Google Scholar] [CrossRef] [PubMed]
  61. Shtenberg, G.; Massad-Ivanir, N.; Segal, E. Detection of trace heavy metal ions in water by nanostructured porous Si biosensors. Analyst 2015, 140, 4507–4514. [Google Scholar] [CrossRef] [PubMed]
  62. Zhao, Y.; Gaur, G.; Retterer, S.T.; Laibinis, P.E.; Weiss, S.M. Flow-through porous silicon membranes for real-time label-free biosensing. Anal. Chem. 2016, 88, 10940–10948. [Google Scholar] [CrossRef]
  63. Sola-Rabada, A.; Sahare, P.; Hickman, G.J.; Vasquez, M.; Canham, L.T.; Perry, C.C.; Agarwal, V. Biogenic porous silica and silicon sourced from Mexican Giant Horsetail (Equisetum myriochaetum) and their application as supports for enzyme immobilization. Colloids Surf. B Biointerfaces 2018, 166, 195–202. [Google Scholar] [CrossRef]
  64. Li, Y.Y.; Jia, Z.H.; Wang, J.J.; Lü, C.W. Biological reaction signal enhancement in porous silicon Bragg mirror based on quantum dots fluorescence. Optoelectron. Lett. 2017, 13, 172–174. [Google Scholar] [CrossRef]
  65. Zhang, H.; Lv, J.; Jia, Z. Detection of Ammonia-Oxidizing Bacteria (AOB) Using a Porous Silicon Optical Biosensor Based on a Multilayered Double Bragg Mirror Structure. Sensors 2018, 18, 105. [Google Scholar] [CrossRef] [PubMed]
  66. Li, Y.; Jia, Z.; Lv, G.; Wen, H.; Li, P.; Zhang, H.; Wang, J. Detection of Echinococcus granulosus antigen by a quantum dot/porous silicon optical biosensor. Biomed. Opt. Express 2017, 8, 3458. [Google Scholar] [CrossRef] [PubMed]
  67. Mariani, S.; Robbiano, V.; Strambini, L.M.; Debrassi, A.; Egri, G.; Dähne, L.; Barillaro, G. Layer-by-layer biofunctionalization of nanostructured porous silicon for high-sensitivity and high-selectivity label-free affinity biosensing. Nat. Commun. 2018, 9, 5256. [Google Scholar] [CrossRef]
  68. Mariani, S.; Pino, L.; Strambini, L.M.; Tedeschi, L.; Barillaro, G. 10000-Fold Improvement in Protein Detection Using Nanostructured Porous Silicon Interferometric Aptasensors. ACS Sens. 2016, 1, 1471–1479. [Google Scholar] [CrossRef]
  69. Mariani, S.; Strambini, L.; Tedeschi, L.; Barillaro, G. Porous silicon interferometers for high-sensitivity label-free detection of biomolecules. In Proceedings of the 2017 IEEE SENSORS, Glasgow, UK, 29 October–1 November 2017; IEEE: Piscataway, NJ, USA, 2017; pp. 1–3. [Google Scholar]
  70. Mariani, S.; Strambini, L.M.; Tedeschi, L.; Barillaro, G. Interferogram Average over Wavelength Spectroscopy: An Ultrasensitive Technique for Biosensing with Porous Silicon Interferometers. ECS Trans. 2017, 77, 1815–1823. [Google Scholar] [CrossRef]
  71. Luan, E.; Yun, H.; Laplatine, L.; Dattner, Y.; Ratner, D.M.; Cheung, K.C.; Chrostowski, L. Enhanced Sensitivity of Subwavelength Multibox Waveguide Microring Resonator Label-Free Biosensors. IEEE J. Sel. Top. Quantum Electron. 2019, 25, 1–11. [Google Scholar] [CrossRef]
  72. Irrera, A.; Leonardi, A.A.; Di Franco, C.; Lo Faro, M.J.; Palazzo, G.; D’Andrea, C.; Manoli, K.; Franzò, G.; Musumeci, P.; Fazio, B.; et al. New Generation of Ultrasensitive Label-Free Optical Si Nanowire-Based Biosensors. ACS Photonics 2018, 5, 471–479. [Google Scholar] [CrossRef]
  73. Ramakrishan, S.K.; Martin Fernandez, M.; Cloitre, T.; Agarwal, V.; Cuisinier, F.J.G.; Gergely, C. Porous silicon microcavities redefine colorimetric ELISA sensitivity for ultrasensitive detection of autoimmune antibodies. Sens. Actuators B Chem. 2018, 272, 211–218. [Google Scholar] [CrossRef]
  74. Li, Z.; Luo, Q.; Wu, J. Label-free discrimination of membrane-translocating peptides on porous silicon microfluidic biosensors. Biomicrofluidics 2016, 10, 064113. [Google Scholar] [CrossRef]
  75. Piya, R.; Zhu, Y.; Soeriyadi, A.H.; Silva, S.M.; Reece, P.J.; Gooding, J.J. Micropatterning of porous silicon Bragg reflectors with poly (ethylene glycol) to fabricate cell microarrays: Towards single cell sensing. Biosens. Bioelectron. 2019, 127, 229–235. [Google Scholar] [CrossRef]
  76. Chhasatia, R.; Sweetman, M.J.; Harding, F.J.; Waibel, M.; Kay, T.; Thomas, H.; Loudovaris, T.; Voelcker, N.H. Non-invasive, in vitro analysis of islet insulin production enabled by an optical porous silicon biosensor. Biosens. Bioelectron. 2017, 91, 515–522. [Google Scholar] [CrossRef] [PubMed]
  77. Reta, N.; Michelmore, A.; Saint, C.; Prieto-Simón, B.; Voelcker, N.H. Porous silicon membrane-modified electrodes for label-free voltammetric detection of MS2 bacteriophage. Biosens. Bioelectron. 2016, 80, 47–53. [Google Scholar] [CrossRef] [PubMed]
  78. Jenie, S.N.A.; Prieto-Simon, B.; Voelcker, N.H. Development of L-lactate dehydrogenase biosensor based on porous silicon resonant microcavities as fluorescence enhancers. Biosens. Bioelectron. 2015, 74, 637–643. [Google Scholar] [CrossRef] [PubMed]
  79. Tücking, K.S.; Vasani, R.B.; Cavallaro, A.A.; Voelcker, N.H.; Schönherr, H.; Prieto-Simon, B. Hyaluronic Acid–Modified Porous Silicon Films for the Electrochemical Sensing of Bacterial Hyaluronidase. Macromol. Rapid Commun. 2018, 39, 1–7. [Google Scholar] [CrossRef] [PubMed]
  80. Armenia, I.; Balzaretti, R.; Pirrone, C.; Allegretti, C.; D’Arrigo, P.; Valentino, M.; Gornati, R.; Bernardini, G.; Pollegioni, L. L-Aspartate Oxidase Magnetic Nanoparticles: Synthesis, Characterization and L-Aspartate Bioconversion. RSC Adv. 2017, 7, 21136–21143. [Google Scholar] [CrossRef]
  81. Nayef, U.M.; Khudhair, I.M. Study of porous silicon humidity sensor vapors by photoluminescence quenching for organic solvents. Opt. Int. J. Light Electron Opt. 2017, 135, 169–173. [Google Scholar] [CrossRef]
  82. Jenie, S.N.A.; Plush, S.E.; Voelcker, N.H. Singlet Oxygen Detection on a Nanostructured Porous Silicon Thin Film via Photonic Luminescence Enhancements. Langmuir 2017, 33, 8606–8613. [Google Scholar] [CrossRef]
  83. Kayahan, E. Porous silicon based CO2 sensors with high sensitivity. Optik (Stuttg) 2018, 164, 271–276. [Google Scholar] [CrossRef]
  84. Georgobiani, V.A.; Gonchar, K.A.; Zvereva, E.A.; Osminkina, L.A. Porous Silicon Nanowire Arrays for Reversible Optical Gas Sensing. Phys. Status Solidi Appl. Mater. Sci. 2018, 215, 1–5. [Google Scholar] [CrossRef]
  85. Shi, Y.M.; Rong, G.G.; Wang, D.N.; Zhang, S.L.; Zhu, Y.X. A Label-Free Biosensor Based on Nanoscale Porous Silicon Thin Film for Tuberculosis Detection. Adv. Mater. Res. 2014, 1082, 555–561. [Google Scholar] [CrossRef]
  86. Urmann, K.; Walter, J.G.; Scheper, T.; Segal, E. Label-free optical biosensors based on aptamer-functionalized porous silicon scaffolds. Anal. Chem. 2015, 87, 1999–2006. [Google Scholar] [CrossRef] [PubMed]
  87. Qiao, H.; Soeriyadi, A.H.; Guan, B.; Reece, P.J.; Gooding, J.J. The analytical performance of a porous silicon Bloch surface wave biosensors as protease biosensor. Sens. Actuators B Chem. 2015, 211, 469–475. [Google Scholar] [CrossRef]
  88. Terracciano, M.; De Stefano, L.; Borbone, N.; Politi, J.; Oliviero, G.; Nici, F.; Casalino, M.; Piccialli, G.; Dardano, P.; Varra, M.; et al. Solid phase synthesis of a thrombin binding aptamer on macroporous silica for label free optical quantification of thrombin. RSC Adv. 2016, 6, 86762–86769. [Google Scholar] [CrossRef]
  89. Mariani, S.; Strambini, L.M.; Barillaro, G. Femtomole Detection of Proteins Using a Label-Free Nanostructured Porous Silicon Interferometer for Perspective Ultrasensitive Biosensing. Anal. Chem. 2016, 88, 8502–8509. [Google Scholar] [CrossRef]
  90. Urmann, K.; Arshavsky-Graham, S.; Walter, J.G.; Scheper, T.; Segal, E. Whole-cell detection of live: Lactobacillus acidophilus on aptamer-decorated porous silicon biosensors. Analyst 2016, 141, 5432–5440. [Google Scholar] [CrossRef] [PubMed]
  91. Azuelos, P.; Girault, P.; Lorrain, N.; Dumeige, Y.; Bodiou, L.; Poffo, L.; Guendouz, M.; Thual, M.; Charrier, J. Optimization of porous silicon waveguide design for micro-ring resonator sensing applications. J. Opt. 2018, 20, 085301. [Google Scholar] [CrossRef]
  92. Rahimi, F.; Fardindoost, S.; Ansari-Pour, N.; Sepehri, F.; Makiyan, F.; Shafiekhani, A.; Rezayan, A.H. Optimization of porous silicon conditions for DNA-based biosensing via reflectometric interference spectroscopy. Cell J. 2019, 20, 584–591. [Google Scholar] [PubMed]
  93. Mariani, S.; Strambini, L.M.; Paghi, A.; Barillaro, G. Low-Concentration Ethanol Vapor Sensing with Nanostructured Porous Silicon Interferometers Using Interferogram Average over Wavelength Reflectance Spectroscopy. IEEE Sens. J. 2018, 18, 7842–7849. [Google Scholar] [CrossRef]
  94. Bui, H.; Pham, V.H.; Pham, V.D.; Hoang, T.H.C.; Pham, T.B.; Do, T.C.; Ngo, Q.M.; Nguyen, T. Van Determination of low solvent concentration by nano-porous silicon photonic sensors using volatile organic compound method. Environ. Technol. 2018. [Google Scholar] [CrossRef] [PubMed]
  95. Caroselli, R.; Martín Sánchez, D.; Ponce Alcántara, S.; Prats Quilez, F.; Torrijos Morán, L.; García-Rupérez, J. Real-Time and In-Flow Sensing Using a High Sensitivity Porous Silicon Microcavity-Based Sensor. Sensors 2017, 17, 2813. [Google Scholar] [CrossRef]
  96. Zhao, Y.; Gaur, G.; Mernaugh, R.L.; Laibinis, P.E.; Weiss, S.M. Comparative Kinetic Analysis of Closed-Ended and Open-Ended Porous Sensors. Nanoscale Res. Lett. 2016, 11, 395. [Google Scholar] [CrossRef] [PubMed]
  97. Mariani, S.; Strambini, L.M.; Barillaro, G. Electrical Double Layer-Induced Ion Surface Accumulation for Ultrasensitive Refractive Index Sensing with Nanostructured Porous Silicon Interferometers. ACS Sens. 2018, 3, 595–605. [Google Scholar] [CrossRef] [PubMed]
  98. Politi, J.; Dardano, P.; Caliò, A.; Iodice, M.; Rea, I.; De Stefano, L. Reversible sensing of heavy metal ions using lysine modified oligopeptides on porous silicon and gold. Sens. Actuators B Chem. 2017, 244, 142–150. [Google Scholar] [CrossRef]
  99. Tsai, W.T.; Nguyen, M.H.; Lai, J.R.; Nguyen, H.B.; Lee, M.C.; Tseng, F.G. ppb-level heavy metal ion detection by electrochemistry-assisted nanoPorous silicon (ECA-NPS) photonic sensors. Sens. Actuators B Chem. 2018, 265, 75–83. [Google Scholar] [CrossRef]
  100. Kumeria, T.; Wang, J.; Chan, N.; Harris, T.J.; Sailor, M.J. Visual Sensor for Sterilization of Polymer Fixtures Using Embedded Mesoporous Silicon Photonic Crystals. ACS Sens. 2018, 3, 143–150. [Google Scholar] [CrossRef] [PubMed]
  101. Rodriguez, G.A.; Hu, S.; Weiss, S.M. Porous silicon ring resonator for compact, high sensitivity biosensing applications. Opt. Express 2015, 23, 7111. [Google Scholar] [CrossRef] [PubMed]
  102. Zhao, Y.; Rodriguez, G.A.; Graham, Y.M.; Cao, T.; Gaur, G.; Weiss, S.M. Resonant Photonic Structures in Porous Silicon for Biosensing. In Proceedings of the Frontiers in Biological Detection: From Nanosensors to Systems IX, San Francisco, CA, USA, 28 January–2 February 2017; Danielli, A., Miller, B.L., Weiss, S.M., Eds.; SPIE: Bellingham, DC, USA, 2017; Volume 10081, p. 100810D. [Google Scholar]
  103. Girault, P.; Azuelos, P.; Lorrain, N.; Poffo, L.; Lemaitre, J.; Pirasteh, P.; Hardy, I.; Thual, M.; Guendouz, M.; Charrier, J. Porous silicon micro-resonator implemented by standard photolithography process for sensing application. Opt. Mater. 2017, 72, 596–601. [Google Scholar] [CrossRef]
  104. Jiménez Vivanco, M.; García, G.; Doti, R.; Faubert, J.; Lugo Arce, J. Time-Resolved Spectroscopy of Ethanol Evaporation on Free-Standing Porous Silicon Photonic Microcavities. Materials 2018, 11, 894. [Google Scholar] [CrossRef]
  105. Shashaani, H.; Faramarzpour, M.; Hassanpour, M.; Namdar, N.; Alikhani, A.; Abdolahad, M. Silicon nanowire based biosensing platform for electrochemical sensing of Mebendazole drug activity on breast cancer cells. Biosens. Bioelectron. 2016, 85, 363–370. [Google Scholar] [CrossRef]
  106. Abbas, R.A.; Alwan, A.M.; Abdulhamied, Z.T. Synthesis and characterization of porous silicon gas sensors. J. Phys. Conf. Ser. 2018, 1003, 012087. [Google Scholar] [CrossRef]
  107. Li, W.; Dai, E.W.; Bai, G.; Xu, J. Depth-dependent humidity sensing properties of silicon nanopillar array. Sens. Actuators B Chem. 2016, 237, 526–533. [Google Scholar] [CrossRef]
  108. Li, W.; Feng, Z.; Dai, E.; Xu, J.; Bai, G. Organic vapour sensing properties of area-ordered and size-controlled silicon nanopillar. Sensors 2016, 16, 1880. [Google Scholar] [CrossRef] [PubMed]
  109. Karadan, P.; Parida, S.; Kumar, A.; Anappara, A.A.; Dhara, S.; Barshilia, H.C. Charge transport studies on Si nanopillars for photodetectors fabricated using vapor phase metal-assisted chemical etching. Appl. Phys. A Mater. Sci. Process. 2017, 123, 1–10. [Google Scholar] [CrossRef]
  110. Abdul-Hameed, A.A.; Mahdi, M.A.; Ali, B.; Selman, A.M.; Al-Taay, H.F.; Jennings, P.; Lee, W.J. Fabrication of a high sensitivity and fast response self-powered photosensor based on a core-shell silicon nanowire homojunction. Superlattices Microstruct. 2018, 116, 27–35. [Google Scholar] [CrossRef]
  111. Liu, J.Q.; Gao, Y.; Wu, G.A.; Tong, X.W.; Xie, C.; Luo, L.B.; Liang, L.; Wu, Y.C. Silicon/Perovskite Core-Shell Heterojunctions with Light-Trapping Effect for Sensitive Self-Driven Near-Infrared Photodetectors. ACS Appl. Mater. Interfaces 2018, 10, 27850–27857. [Google Scholar] [CrossRef] [PubMed]
  112. Al-Hardan, N.H.; Hamid, M.A.A.; Ahmed, N.M.; Jalar, A.; Shamsudin, R.; Othman, N.K.; Keng, L.K.; Chiu, W.; Al-Rawi, H.N. High sensitivity pH sensor based on porous silicon (PSi) extended gate field-effect transistor. Sensors 2016, 16, 839. [Google Scholar] [CrossRef] [PubMed]
  113. Nasser, A.R.; Ali, G.M. A Porous Silicon P-Type Interdigitated Extended-Gate Field Effect Transistor pH Sensor. Silicon 2018, 1–8. [Google Scholar] [CrossRef]
  114. Huang, B.R.; Hsu, C.L.; Wang, Y.K.; Yang, W.L. Core-Shell P-N Junction Si Nanowires as Rapid Response and High-Sensitivity pH Sensor. IEEE Sens. J. 2017, 17, 3967–3974. [Google Scholar] [CrossRef]
  115. Jalkanen, T.; Määttänen, A.; Mäkilä, E.; Tuura, J.; Kaasalainen, M.; Lehto, V.P.; Ihalainen, P.; Peltonen, J.; Salonen, J. Fabrication of Porous Silicon Based Humidity Sensing Elements on Paper. J. Sens. 2015, 2015, 1–10. [Google Scholar] [CrossRef]
  116. Cheng, W.; Yu, L.; Kong, D.; Yu, Z.; Wang, H.; Ma, Z.; Wang, Y.; Wang, J.; Pan, L.; Shi, Y. Fast-response and low-hysteresis flexible pressure sensor based on silicon nanowires. IEEE Electron Device Lett. 2018, 39, 1069–1072. [Google Scholar] [CrossRef]
  117. Mirzaei, A.; Kang, S.Y.; Choi, S.W.; Kwon, Y.J.; Choi, M.S.; Bang, J.H.; Kim, S.S.; Kim, H.W. Fabrication and gas sensing properties of vertically aligned Si nanowires. Appl. Surf. Sci. 2018, 427, 215–226. [Google Scholar] [CrossRef]
  118. Qin, Y.; Cui, Z.; Zhang, T.; Liu, D. Polypyrrole shell (nanoparticles)-functionalized silicon nanowires array with enhanced NH3-sensing response. Sens. Actuators B Chem. 2018, 258, 246–254. [Google Scholar] [CrossRef]
  119. Azuelos, P.; Girault, P.; Lorrain, N.; Poffo, L.; Hardy, I.; Guendouz, M.; Thual, M. Theoretical investigation of Vernier effect based sensors with hybrid porous silicon-polymer optical waveguides. J. Appl. Phys. 2017, 121, 144501. [Google Scholar] [CrossRef]
  120. Dwivedi, P.; Chauhan, N.; Vivekanandan, P.; Das, S.; Sakthi Kumar, D.; Dhanekar, S. Scalable fabrication of prototype sensor for selective and sub-ppm level ethanol sensing based on TiO2 nanotubes decorated porous silicon. Sens. Actuators B Chem. 2017, 249, 602–610. [Google Scholar] [CrossRef]
  121. Kwon, Y.J.; Choi, S.W.; Kang, S.Y.; Choi, M.S.; Bang, J.H.; Kim, S.S.; Kim, H.W. Enhancement of the benzene-sensing performance of Si nanowires through the incorporation of TeO2 heterointerfaces and Pd-sensitization. Sens. Actuators B Chem. 2017, 244, 1085–1097. [Google Scholar] [CrossRef]
  122. Karthik, T.V.K.; Martinez, L.; Agarwal, V. Porous silicon ZnO/SnO2 structures for CO2 detection. J. Alloy. Compd. 2018, 731, 853–863. [Google Scholar] [CrossRef]
  123. Dalvand, R.; Mahmud, S.; Shabannia, R. Fabrication of UV photodetector using needle-shaped ZnO nanostructure arrays prepared on porous silicon substrate by a facile low-temperature method. J. Mater. Sci. Mater. Electron. 2018, 29, 4999–5008. [Google Scholar] [CrossRef]
  124. Liu, X.; Hu, M.; Wang, Y.; Liu, J.; Qin, Y. High sensitivity NO2 sensor based on CuO/p-porous silicon heterojunction at room temperature. J. Alloy. Compd. 2016, 685, 364–369. [Google Scholar] [CrossRef]
  125. Martínez, L.; Holguín-Momaca, J.T.; Karthik, T.V.K.; Olive-Méndez, S.F.; Campos-Alvarez, J.; Agarwal, V. Sputtering temperature dependent growth kinetics and CO2 sensing properties of ZnO deposited over porous silicon. Superlattices Microstruct. 2016, 98, 8–17. [Google Scholar] [CrossRef]
  126. Zhang, W.; Hu, M.; Liu, X.; Wei, Y.; Li, N.; Qin, Y. Synthesis of the cactus-like silicon nanowires/tungsten oxide nanowires composite for room-temperature NO2 gas sensor. J. Alloy. Compd. 2016, 679, 391–399. [Google Scholar] [CrossRef]
  127. Antunez, E.E.; Salazar-Kuri, U.; Estevez, J.O.; Campos, J.; Basurto, M.A.; Jiménez Sandoval, S.; Agarwal, V. Porous silicon-VO2 based hybrids as possible optical temperature sensor: Wavelength-dependent optical switching from visible to near-infrared range. J. Appl. Phys. 2015, 118, 134503. [Google Scholar] [CrossRef]
  128. Keramatnejad, K.; Khorramshahi, F.; Khatami, S.; Asl-Soleimani, E. Optimizing UV detection properties of n-ZnO nanowire/p-Si heterojunction photodetectors by using a porous substrate. Opt. Quantum Electron. 2015, 47, 1739–1749. [Google Scholar] [CrossRef]
  129. Wei, Y.; Hu, M.; Yan, W.; Wang, D.; Yuan, L.; Qin, Y. Hydrothermal synthesis porous silicon/tungsten oxide nanorods composites and their gas-sensing properties to NO2 at room temperature. Appl. Surf. Sci. 2015, 353, 79–86. [Google Scholar] [CrossRef]
  130. Miao, F.; Lu, X.; Tao, B.; Li, R.; Chu, P.K. Glucose oxidase immobilization platform based on ZnO nanowires supported by silicon nanowires for glucose biosensing. Microelectron. Eng. 2016, 149, 153–158. [Google Scholar] [CrossRef]
  131. Liao, J.; Li, Z.; Wang, G.; Chen, C.; Lv, S.; Li, M. ZnO nanorod/porous silicon nanowire hybrid structures as highly-sensitive NO2 gas sensors at room temperature. Phys. Chem. Chem. Phys. 2016, 18, 4835–4841. [Google Scholar] [CrossRef] [PubMed]
  132. Nayef, U.M.; Hubeatir, K.A.; Abdulkareem, Z.J. Ultraviolet photodetector based on TiO2 nanoparticles/porous silicon hetrojunction. Optik (Stuttg) 2016, 127, 2806–2810. [Google Scholar] [CrossRef]
  133. Wang, L.L.; Li, Z.J.; Luo, L.; Zhao, C.Z.; Kang, L.P.; Liu, D.W. Methanol sensing properties of honeycomb-like SnO2 grown on silicon nanoporous pillar array. J. Alloy. Compd. 2016, 682, 170–175. [Google Scholar] [CrossRef]
  134. Husairi, F.S.; Rouhi, J.; Eswar, K.A.; Ooi, C.H.R.; Rusop, M.; Abdullah, S. Ethanol solution sensor based on ZnO/PSi nanostructures synthesized by catalytic immersion method at different molar ratio concentrations: An electrochemical impedance analysis. Sens. Actuators A Phys. 2015, 236, 11–18. [Google Scholar] [CrossRef]
  135. Yan, D.; Li, S.; Hu, M.; Liu, S.; Zhu, Y.; Cao, M. Electrochemical synthesis and the gas-sensing properties of the Cu2O nanofilms/porous silicon hybrid structure. Sens. Actuators B Chem. 2016, 223, 626–633. [Google Scholar] [CrossRef]
  136. Liu, D.; Lin, L.; Chen, Q.; Zhou, H.; Wu, J. Low Power Consumption Gas Sensor Created from Silicon Nanowires/TiO2 Core–Shell Heterojunctions. ACS Sens. 2017, 2, 1491–1497. [Google Scholar] [CrossRef]
  137. Wei, Y.; Hu, M.; Wang, D.; Zhang, W.; Qin, Y. Room temperature NO2-sensing properties of porous silicon/tungsten oxide nanorods composite. J. Alloy. Compd. 2015, 640, 517–524. [Google Scholar] [CrossRef]
  138. Yan, D.; Li, S.; Liu, S.; Tan, M.; Cao, M. Electrodeposited tungsten oxide films onto porous silicon for NO2 detection at room temperature. J. Alloy. Compd. 2018, 735, 718–727. [Google Scholar] [CrossRef]
  139. Qiang, X.; Hu, M.; Zhao, B.; Qin, Y.; Zhang, T.; Zhou, L.; Liang, J. Preparation of porous silicon/Pd-loaded WO3nanowires for enhancement of ammonia sensing properties at room temperature. Mater. Sci. Semicond. Process. 2018, 79, 113–118. [Google Scholar] [CrossRef]
  140. Baker, C.; Gole, J.L. Detection of Liquid Organic Solvents on Metal Oxide Nanostructure Decorated Porous Silicon Interfaces. ACS Sens. 2016, 1, 235–242. [Google Scholar] [CrossRef]
  141. Zhou, F.; Wang, Q.; Liu, W. [email protected] nanostructures on porous silicon for photocatalysis and gas-sensing: The effect of plasmonic hot-electrons driven by visible-light. Mater. Res. Express 2016, 3, 085006. [Google Scholar] [CrossRef]
  142. Yuan, L.; Hu, M.; Wei, Y.; Ma, W. Enhanced NO2 sensing characteristics of Au modified porous silicon/thorn-sphere-like tungsten oxide composites. Appl. Surf. Sci. 2016, 389, 824–834. [Google Scholar] [CrossRef]
  143. Wang, D.-F.; Liang, J.-R.; Li, C.-Q.; Yan, W.-J.; Hu, M. Room temperature NO2 gas sensing of Au-loaded tungsten oxide nanowires/porous silicon hybrid structure. Chin. Phys. B 2016, 25, 028102. [Google Scholar] [CrossRef]
  144. Wang, H.; Jiang, X.; He, Y. Highly sensitive and reproducible silicon-based surface-enhanced Raman scattering sensors for real applications. Analyst 2016, 141, 5010–5019. [Google Scholar] [CrossRef]
  145. Novara, C.; Dalla Marta, S.; Virga, A.; Lamberti, A.; Angelini, A.; Chiadò, A.; Rivolo, P.; Geobaldo, F.; Sergo, V.; Bonifacio, A.; et al. SERS-active Ag nanoparticles on porous silicon and PDMS substrates: A comparative study of uniformity and Raman efficiency. J. Phys. Chem. C 2016, 120, 16946–16953. [Google Scholar] [CrossRef]
  146. Sanger, A.; Kumar, A.; Chauhan, S.; Gautam, Y.K.; Chandra, R. Fast and reversible hydrogen sensing properties of Pd/Mg thin film modified by hydrophobic porous silicon substrate. Sens. Actuators B Chem. 2015, 213, 252–260. [Google Scholar] [CrossRef]
  147. Mohaček-Grošev, V.; Gebavi, H.; Bonifacio, A.; Sergo, V.; Daković, M.; Bajuk-Bogdanović, D. Binding of p-mercaptobenzoic acid and adenine to gold-coated electroless etched silicon nanowires studied by surface-enhanced Raman scattering. Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 2018, 200, 102–109. [Google Scholar] [CrossRef] [PubMed]
  148. Hsu, C.W.; Feng, W.C.; Su, F.C.; Wang, G.J. An Electrochemical Glucose Biosensor with a Silicon Nanowire Array Electrode. J. Electrochem. Soc. 2015, 162, B264–B268. [Google Scholar] [CrossRef]
  149. Karadan, P.; Aggarwal, S.; Anappara, A.A.; Narayana, C.; Barshilia, H.C. Tailored periodic Si nanopillar based architectures as highly sensitive universal SERS biosensing platform. Sens. Actuators B Chem. 2018, 254, 264–271. [Google Scholar] [CrossRef]
  150. Novara, C.; Lamberti, A.; Chiadò, A.; Virga, A.; Rivolo, P.; Geobaldo, F.; Giorgis, F. Surface-enhanced Raman spectroscopy on porous silicon membranes decorated with Ag nanoparticles integrated in elastomeric microfluidic chips. RSC Adv. 2016, 6, 21865–21870. [Google Scholar] [CrossRef]
  151. Bandarenka, H.V.; Girel, K.V.; Bondarenko, V.P.; Khodasevich, I.A.; Panarin, A.Y.; Terekhov, S.N. Formation Regularities of Plasmonic Silver Nanostructures on Porous Silicon for Effective Surface-Enhanced Raman Scattering. Nanoscale Res. Lett. 2016, 11, 262. [Google Scholar] [CrossRef] [PubMed]
  152. Yakimchuk, D.; Kaniukov, E.; Bundyukova, V.; Osminkina, L.; Teichert, S.; Demyanov, S.; Sivakov, V. Silver nanostructures evolution in porous SiO2/p-Si matrices for wide wavelength surface-enhanced Raman scattering applications. MRS Commun. 2018, 8, 95–99. [Google Scholar] [CrossRef]
  153. Harraz, F.A.; Ismail, A.A.; Bouzid, H.; Al-Sayari, S.A.; Al-Hajry, A.; Al-Assiri, M.S. Surface-enhanced Raman scattering (SERS)-active substrates from silver plated-porous silicon for detection of crystal violet. Appl. Surf. Sci. 2015, 331, 241–247. [Google Scholar] [CrossRef]
  154. Kalimuthu, V.; Rath, S. One-step synthesis of Au-coated porous silicon as a surface enhanced Raman scattering substrate for biomolecule detection. Mater. Lett. 2017, 204, 115–119. [Google Scholar] [CrossRef]
  155. Mikac, L.; Ivanda, M.; Derek, V.; Gotić, M. Influence of mesoporous silicon preparation condition on silver clustering and SERS enhancement. J. Raman Spectrosc. 2016, 47, 1036–1041. [Google Scholar] [CrossRef]
  156. Ensafi, A.A.; Rezaloo, F.; Rezaei, B. Electrochemical sensor based on porous silicon/silver nanocomposite for the determination of hydrogen peroxide. Sens. Actuators B Chem. 2016, 231, 239–244. [Google Scholar] [CrossRef]
  157. Wang, Y.W.; Kao, K.C.; Wang, J.K.; Mou, C.Y. Large-Scale Uniform Two-Dimensional Hexagonal Arrays of Gold Nanoparticles Templated from Mesoporous Silica Film for Surface-Enhanced Raman Spectroscopy. J. Phys. Chem. C 2016, 120, 24382–24388. [Google Scholar] [CrossRef]
  158. Tsao, C.W.; Yang, Z.J. High Sensitivity and High Detection Specificity of Gold-Nanoparticle-Grafted Nanostructured Silicon Mass Spectrometry for Glucose Analysis. ACS Appl. Mater. Interfaces 2015, 7, 22630–22637. [Google Scholar] [CrossRef] [PubMed]
  159. Song, Z.; Chang, H.; Zhu, W.; Xu, C.; Feng, X. Rhodium Nanoparticle-mesoporous Silicon Nanowire Nanohybrids for Hydrogen Peroxide Detection with High Selectivity. Sci. Rep. 2015, 5, 1–4. [Google Scholar] [CrossRef] [PubMed]
  160. Rashid, J.I.A.; Yusof, N.A.; Abdullah, J.; Hashim, U.; Hajian, R. A Novel Disposable Biosensor Based on SiNWs/AuNPs Modified-Screen Printed Electrode for Dengue Virus DNA Oligomer Detection. IEEE Sens. J. 2015, 15, 4420–4421. [Google Scholar] [CrossRef]
  161. Kumar, A.; Karadan, P.; Barshilia, H.C. Synthesis of silver nanowires towards the development the ultrasensitive AgNWs/SiNPLs hybrid photodetector and flexible transparent conductor. Mater. Sci. Semicond. Process. 2018, 75, 239–246. [Google Scholar] [CrossRef]
  162. Lee, J.; Hong, M.H.; Han, S.; Na, J.; Kim, I.; Kwon, Y.J.; Lim, Y.B.; Choi, H.J. Sensitive and Selective Detection of HIV-1 RRE RNA Using Vertical Silicon Nanowire Electrode Array. Nanoscale Res. Lett. 2016, 11, 1–7. [Google Scholar] [CrossRef] [PubMed]
  163. Silina, Y.E.; Koch, M.; Herbeck-Engel, P.; Iatsunskyi, I. Exploring the potential of high resolution inductively coupled plasma mass spectrometry towards non-destructive control and validation of electroless gold nanoparticles onto silicon nanowires hybrids. Anal. Methods 2019, 11, 3987–3995. [Google Scholar] [CrossRef]
  164. Cui, Y.; Jin, Y.; Chen, X.; Wu, J. Two-Dimensional Electrochemiluminescence on Porous Silicon Platform for Explosive Detection and Discrimination. ACS Sens. 2018, 3, 1439–1444. [Google Scholar] [CrossRef]
  165. Arzumanyan, G.; Doroshkevich, N.; Mamatkulov, K.; Shashkov, S.; Girel, K.; Bandarenka, H.; Borisenko, V. Phospholipid detection by surface-enhanced Raman scattering using silvered porous silicon substrates. Phys. Status Solidi 2017, 214, 1600915. [Google Scholar] [CrossRef]
  166. Ensafi, A.A.; Ahmadi, N.; Rezaei, B.; Abarghoui, M.M. A new electrochemical sensor for the simultaneous determination of acetaminophen and codeine based on porous silicon/palladium nanostructure. Talanta 2015, 134, 745–753. [Google Scholar] [CrossRef]
  167. Wang, J.; Jia, Z. Metal Nanoparticles/Porous Silicon Microcavity Enhanced Surface Plasmon Resonance Fluorescence for the Detection of DNA. Sensors 2018, 18, 661. [Google Scholar] [CrossRef] [PubMed]
  168. Kosovic, M.; Balarin, M.; Ivanda, M.; Derek, V.; Marcius, M.; Ristic, M.; Gamulin, O. Porous silicon covered with silver nanoparticles as Surface-Enhanced Raman Scattering (SERS) substrate for ultra-low concentration detection. Appl. Spectrosc. 2015, 69, 1417–1424. [Google Scholar] [CrossRef] [PubMed]
  169. Ensafi, A.A.; Abarghoui, M.M.; Rezaei, B. Simultaneous determination of morphine and codeine using Pt nanoparticles supported on porous silicon flour modified ionic liquid carbon paste electrode. Sens. Actuators B Chem. 2015, 219, 1–9. [Google Scholar] [CrossRef]
  170. Harraz, F.A.; Faisal, M.; Al-Salami, A.E.; El-Toni, A.M.; Almadiy, A.A.; Al-Sayari, S.A.; Al-Assiri, M.S. Silver nanoparticles decorated stain-etched mesoporous silicon for sensitive, selective detection of ascorbic acid. Mater. Lett. 2019, 234, 96–100. [Google Scholar] [CrossRef]
  171. Colombelli, A.; Manera, M.G.; Taurino, A.; Catalano, M.; Convertino, A.; Rella, R. Au nanoparticles decoration of silica nanowires for improved optical bio-sensing. Sens. Actuators B Chem. 2016, 226, 589–597. [Google Scholar] [CrossRef]
  172. Sainato, M.; Strambini, L.M.; Rella, S.; Mazzotta, E.; Barillaro, G. Sub-Parts Per Million NO2 Chemi-Transistor Sensors Based on Composite Porous Silicon/Gold Nanostructures Prepared by Metal-Assisted Etching. ACS Appl. Mater. Interfaces 2015, 7, 7136–7145. [Google Scholar] [CrossRef]
  173. Convertino, A.; Mussi, V.; Maiolo, L. Disordered array of Au covered Silicon nanowires for SERS biosensing combined with electrochemical detection. Sci. Rep. 2016, 6, 1–10. [Google Scholar] [CrossRef]
  174. Ahn, J.-H.; Yun, J.; Moon, D.-I.; Choi, Y.-K.; Park, I. Self-heated silicon nanowires for high performance hydrogen gas detection. Nanotechnology 2015, 26, 095501. [Google Scholar] [CrossRef]
  175. Convertino, A.; Mussi, V.; Maiolo, L.; Ledda, M.; Lolli, M.G.; Bovino, F.A.; Fortunato, G.; Rocchia, M.; Lisi, A. Array of disordered silicon nanowires coated by a gold film for combined NIR photothermal treatment of cancer cells and Raman monitoring of the process evolution. Nanotechnology 2018, 29, 415102. [Google Scholar] [CrossRef]
  176. Rindzevicius, T.; Barten, J.; Vorobiev, M.; Schmidt, M.S.; Castillo, J.J.; Boisen, A. Detection of surface-linked polychlorinated biphenyls using surface-enhanced Raman scattering spectroscopy. Vib. Spectrosc. 2017, 90, 1–6. [Google Scholar] [CrossRef]
  177. Xu, D.; Teng, F.; Wang, Z.; Lu, N. Droplet-Confined Electroless Deposition of Silver Nanoparticles on Ordered Superhydrophobic Structures for High Uniform SERS Measurements. ACS Appl. Mater. Interfaces 2017, 9, 21548–21553. [Google Scholar] [CrossRef] [PubMed]
  178. Lauridsen, R.K.; Sommer, L.M.; Johansen, H.K.; Rindzevicius, T.; Molin, S.; Jelsbak, L.; Engelsen, S.B.; Boisen, A. SERS detection of the biomarker hydrogen cyanide from Pseudomonas aeruginosa cultures isolated from cystic fibrosis patients. Sci. Rep. 2017, 7, 45264. [Google Scholar] [CrossRef]
  179. Maiolo, L.; Polese, D.; Pecora, A.; Fortunato, G.; Shacham-Diamand, Y.; Convertino, A. Highly Disordered Array of Silicon Nanowires: An Effective and Scalable Approach for Performing and Flexible Electrochemical Biosensors. Adv. Healthc. Mater. 2016, 5, 575–583. [Google Scholar] [CrossRef] [PubMed]
  180. Nayef, U.M.; Khudhair, I.M.; Kayahan, E. Organic vapor sensor using photoluminescence of laser ablated gold nanoparticles on porous silicon. Optik (Stuttg) 2017, 144, 546–552. [Google Scholar] [CrossRef]
  181. Hassan, K.; Uddin, A.S.M.I.; Chung, G.S. Hydrogen sensing properties of Pt/Pd bimetal decorated on highly hydrophobic Si nanowires. Int. J. Hydrogen Energy 2016, 41, 10991–11001. [Google Scholar] [CrossRef]
  182. Durucan, O.; Wu, K.; Viehrig, M.; Rindzevicius, T.; Boisen, A. Nanopillar-Assisted SERS Chromatography. ACS Sens. 2018, 3, 2492–2498. [Google Scholar] [CrossRef] [PubMed]
  183. Ashley, J.; Wu, K.; Hansen, M.F.; Schmidt, M.S.; Boisen, A.; Sun, Y. Quantitative detection of trace level cloxacillin in food samples using magnetic molecularly imprinted polymer extraction and surface-Enhanced raman spectroscopy nanopillars. Anal. Chem. 2017, 89, 11484–11490. [Google Scholar] [CrossRef] [PubMed]
  184. Cui, H.; Li, S.; Deng, S.; Chen, H.; Wang, C. Flexible, Transparent, and Free-Standing Silicon Nanowire SERS Platform for in Situ Food Inspection. ACS Sens. 2017, 2, 386–393. [Google Scholar] [CrossRef] [PubMed]
  185. Cao, A.; Shan, M.; Paltrinieri, L.; Evers, W.H.; Chu, L.; Poltorak, L.; Klootwijk, J.H.; Seoane, B.; Gascon, J.; Sudhölter, E.J.R.; et al. Enhanced vapour sensing using silicon nanowire devices coated with Pt nanoparticle functionalized porous organic frameworks. Nanoscale 2018, 10, 6884–6891. [Google Scholar] [CrossRef] [PubMed]
  186. Abdul Rashid, J.I.; Yusof, N.A.; Abdullah, J.; Hashim, U.; Hajian, R. Surface modifications to boost sensitivities of electrochemical biosensors using gold nanoparticles/silicon nanowires and response surface methodology approach. J. Mater. Sci. 2016, 51, 1083–1097. [Google Scholar] [CrossRef]
  187. Li, Y.; Dykes, J.; Gilliam, T.; Chopra, N. A new heterostructured SERS substrate: Free-standing silicon nanowires decorated with graphene-encapsulated gold nanoparticles. Nanoscale 2017, 9, 5263–5272. [Google Scholar] [CrossRef] [PubMed]
  188. Shiraz, H.G.; Astaraei, F.R.; Fardindoost, S.; Hosseini, Z.S. Decorated CNT based on porous silicon for hydrogen gas sensing at room temperature. RSC Adv. 2016, 6, 44410–44414. [Google Scholar] [CrossRef]
  189. Das, N.; Basu, J.; RoyChaudhuri, C. Graphene coated nanoporous silicon immunosensor for food toxin detection. Int. J. Adv. Eng. Sci. Appl. Math. 2015, 7, 204–209. [Google Scholar] [CrossRef]
  190. Moretta, R.; Terracciano, M.; Dardano, P.; Casalino, M.; De Stefano, L.; Schiattarella, C.; Rea, I. Toward Multi-Parametric Porous Silicon Transducers Based on Covalent Grafting of Graphene Oxide for Biosensing Applications. Front. Chem. 2018, 6, 1–10. [Google Scholar] [CrossRef] [PubMed]
  191. Shiraz, H.G. Efficient room temperature hydrogen gas sensing based on graphene oxide and decorated porous silicon. Int. J. Hydrogen Energy 2017, 42, 15966–15972. [Google Scholar] [CrossRef]
  192. Kim, J.; Park, S.Y.; Kim, S.; Lee, D.H.; Kim, J.H.; Kim, J.M.; Kang, H.; Han, J.S.; Park, J.W.; Lee, H.; et al. Precise and selective sensing of DNA-DNA hybridization by graphene/Si-nanowires diode-type biosensors. Sci. Rep. 2016, 6, 1–9. [Google Scholar] [CrossRef]
  193. Li, Z.; Xu, S.C.; Zhang, C.; Liu, X.Y.; Gao, S.S.; Hu, L.T.; Guo, J.; Ma, Y.; Jiang, S.Z.; Si, H.P. High-performance SERS substrate based on hybrid structure of graphene oxide/AgNPs/Cu [email protected] Si. Sci. Rep. 2016, 6, 2–11. [Google Scholar] [CrossRef]
  194. Eom, N.; Cho, H.-B.; Song, Y.; Lee, W.; Sekino, T.; Choa, Y.-H. Room-Temperature H2 Gas Sensing Characterization of Graphene-Doped Porous Silicon via a Facile Solution Dropping Method. Sensors 2017, 17, 2750. [Google Scholar] [CrossRef]
Figure 1. (ad) Schematic illustrations of the formation mechanism for synthesizing porous Si films using the MACE process [50]. (e) Electrochemical energy diagram of corresponding reaction. The illustration of the Si NPAs fabrication process [50]. (f) Schematic illustration of the fabrication of SiNP arrays. Close-packed monolayer of polystyrene (PS) nanospheres on a clean Si reduced diameter of PS by reactive ion etching, Au deposition, metal-assisted chemical etching, and the removal of Au/PSi [51].
Figure 1. (ad) Schematic illustrations of the formation mechanism for synthesizing porous Si films using the MACE process [50]. (e) Electrochemical energy diagram of corresponding reaction. The illustration of the Si NPAs fabrication process [50]. (f) Schematic illustration of the fabrication of SiNP arrays. Close-packed monolayer of polystyrene (PS) nanospheres on a clean Si reduced diameter of PS by reactive ion etching, Au deposition, metal-assisted chemical etching, and the removal of Au/PSi [51].
Materials 12 02880 g001
Figure 2. Scanning electron microscopy images of PSi (a) [4], SiNPs (b) [10], and SiNWs (c) [52].
Figure 2. Scanning electron microscopy images of PSi (a) [4], SiNPs (b) [10], and SiNWs (c) [52].
Materials 12 02880 g002
Figure 3. (a) Bright field (BF) and (b) fluorescence images of J774 macrophage cells on pattern before and after lysis. The dye for cells staining was calcein AM. When the cells were lysed, pores were created on the cell membrane, thus causing the leakage of calcein from the cells. Thus, the fluorescence intensity started to decrease due to the leakage of calcein. Cells were still on the micropatterns after lysis, as can be seen from the BF images. Scale bar 100 μm [75].
Figure 3. (a) Bright field (BF) and (b) fluorescence images of J774 macrophage cells on pattern before and after lysis. The dye for cells staining was calcein AM. When the cells were lysed, pores were created on the cell membrane, thus causing the leakage of calcein from the cells. Thus, the fluorescence intensity started to decrease due to the leakage of calcein. Cells were still on the micropatterns after lysis, as can be seen from the BF images. Scale bar 100 μm [75].
Materials 12 02880 g003
Figure 4. (a) The sequence of the 21-mer Si-specific peptide conjugated with the H2 B antigen (the site of acetylation is annotated); (b) Schematic representation of the H2 B glass sensor; (c) The measuring scheme, (d) the red-green-blue (RGB) layers of the obtained colored product; (e) Generation of colored solution by TMB-HRP reaction after capture of H2 B antibody on PSi. Color intensity depends on the concentration of the captured Anti-H2 B antibody [73].
Figure 4. (a) The sequence of the 21-mer Si-specific peptide conjugated with the H2 B antigen (the site of acetylation is annotated); (b) Schematic representation of the H2 B glass sensor; (c) The measuring scheme, (d) the red-green-blue (RGB) layers of the obtained colored product; (e) Generation of colored solution by TMB-HRP reaction after capture of H2 B antibody on PSi. Color intensity depends on the concentration of the captured Anti-H2 B antibody [73].
Materials 12 02880 g004
Figure 5. Scanning electron microscopy (SEM) images of some nano-Si/MOx nanocomposites: (a) SEM images of the PSi/ZnO nanocomposite [125]; (b) SEM images of the SiNWs/WO3 nanocomposite [126]; (c) SEM image of the SiNPs/TiO2 nanocomposite [136]; (d) SEM images of the PSi/V2O5 nanocomposite [37].
Figure 5. Scanning electron microscopy (SEM) images of some nano-Si/MOx nanocomposites: (a) SEM images of the PSi/ZnO nanocomposite [125]; (b) SEM images of the SiNWs/WO3 nanocomposite [126]; (c) SEM image of the SiNPs/TiO2 nanocomposite [136]; (d) SEM images of the PSi/V2O5 nanocomposite [37].
Materials 12 02880 g005
Figure 6. Band diagram of the TiO2 decorated PSi heterojunction (a) before contact, (b) after contact (in air) [120].
Figure 6. Band diagram of the TiO2 decorated PSi heterojunction (a) before contact, (b) after contact (in air) [120].
Materials 12 02880 g006
Figure 7. Mechanism diagram of PSi/WO3/Pd to NH3: (a) Before Pd loading, (b) After Pd loading [139].
Figure 7. Mechanism diagram of PSi/WO3/Pd to NH3: (a) Before Pd loading, (b) After Pd loading [139].
Materials 12 02880 g007
Figure 8. (a) The handheld Raman instrument. (b) SERS spectrum of 0.75 nmol VX and normal Raman spectrum of >98% VX solution [12]; (c) pathways for the in situ detection of pesticide residues on lemon peels using flexible SiNPs/Au [184].
Figure 8. (a) The handheld Raman instrument. (b) SERS spectrum of 0.75 nmol VX and normal Raman spectrum of >98% VX solution [12]; (c) pathways for the in situ detection of pesticide residues on lemon peels using flexible SiNPs/Au [184].
Materials 12 02880 g008
Figure 9. Schematic illustration showing (a) initial state of PSi/graphene substrate and formation of the depletion layer, (b) the adsorption-desorption process of H2 [194].
Figure 9. Schematic illustration showing (a) initial state of PSi/graphene substrate and formation of the depletion layer, (b) the adsorption-desorption process of H2 [194].
Materials 12 02880 g009
Table 1. Summarized data about nano-Si and nano-Si composites suitable for (bio)sensing applications.
Table 1. Summarized data about nano-Si and nano-Si composites suitable for (bio)sensing applications.
(Bio)sensors Based on PSi, SiNWs, SiNPs and Their Composites with Polymers
Type of transducerDetection approachMaterial for detectionLOD a/Sensitivity b range/Sensitivity cReference
PSiPhotoluminescenceGlucose, ureab 0–3.0 mM[18]
Cu2+, Pb2+, Cd2+c 10 nM
Colorimetric sensingAutoimmune antibodiesa 10 fg/mL[73]
FluorescenceJ774 macrophage cellsa few and/or single cells[75]
Visual colorimetric sensingNon-pathogenic E. colia 1.5 ± 0.4 × 105 CFU/mL[100]
SiNWsResistanceH2Ob 10–50 ppm[117]
CapacitancePressurea 0.1 Pa[116]
LuminescenceStreptavidina 1.6 fM[72]
I–V curvesNear-infrared (NIR) lightc 14.86–844.33 mA/W[111]
SiNPLsI–V curvesRelative humidity (RH)a 10%[49]
Refractive indexIsopropyl alcohola 579.5 nm/RIU[71]
I–V curvesEthanol, acetone gasa 0.25%[108]
I–V curvesLightc 1.3 mA/W[109]
UV lightc 0.82 mA/W
(Bio)sensors based on nano-Si and MOx nanocomposites
PSi/WO3ResistanceNO2a 100 ppb
b 100 ppb–3 ppm
[129]
PSi/ZnOElectrochemical impedance analysisEthanol solutionb 0.05–0.6 M[134]
PSi/TiO2FluorescenceAflatoxins B1a 15.4 pg/mL[26]
Ochratoxin Aa 1.48 pg/mL
Fumonisin B1a 0.21 pg/mL
PSi/ZnOPhotocurrentUV Light (325 nm)c 1.98 A/W[123]
PSi/TiO2I–V curveUV illuminationc 0.045 A/W[132]
PSi/SnO2:SnCapacitanceRelative Humidityb 11–95%[25]
SiNWs/TeO2/PdResistanceC6H6, CO, C7H8, N2Ob 10–50 ppm[121]
SiNWs/ZnOI–V curvesGlucosea 12 μM
c 129 μA mM−1
[130]
SiNWs/WO3ResistanceN2Ob 0.25–5 ppm[126]
SiNWs/ZnOResistanceN2Ob 5–50 ppm[131]
SiNPLs/Fe2O3/AgSERSMalachite green (MG)a 10−8 M[38]
SiNPLs/TiO2I–V curvesCH4a 20 ppm[136]
(Bio)sensors based on nano-Si and metals nanoparticles
PSi/AgSERSRhodamine 6Ga 10−15 M[168]
Crystal violeta 100 pM[153]
Porphyrin CuTMPyP4a 10−11 M[151]
PSi/AuPhotoluminescenceAflatoxin B1a 2.5 ± 0.5 pg/mL
b 0.01–10 ng/ml
[13]
PSi/AgAmperometric responseAscorbic acida 0.83 μM
c 1.279 mA mM−1 cm−2
b 20–600 μM
[170]
SiNWs/AuDifferential pulse voltammetryDNAa 1.63 × 10−12 M[160]
SiNWs/AgResistanceNO2a10 ppb[27]
SiNWs/AuI–V measurementsGlucosea 11 μM
b 55.1 μM–16.53 mM
[148]
SiNWs/AuImpedance measurementsAvidina 10 × 10−12 M[179]
SiNWs/Pd/PtResistanceH2b 1–40,000 ppm[181]
SiNPs/AuSERSNerve gases VXa 13 fM[12]
Tabuna 630 fM
SiNPs/AgSERSRhodamine 6Ga 10−11 M[177]
a 10−13 M
b 10−7–10−13 M
[149]
SiNPs/AuSERSRhodamine 6Gb 10−10–10−6 M[51]
Cloxacillinb 15.6–500 pM[183]
(Bio)sensors based on nano-Si and carbon-based nanomaterials
PSi/GO substrateImpedanceAflatoxin B1b 1 fg/mL–1 pg/mL[189]
PSi/GO AgNPs/PCuSERSRhodamine 6 Ga 10−15 M[193]
PSi/Pd/GOResistanceH2a 200 ppm at 15 °C[191]
PSi/GrapheneI–V curvesH2b 100–1000 ppm[194]
SiNWs/GrapheneSERSR6Ga 10−6 M[187]
SiNWs/GrapheneI–V curves characterization, PL measurementsDNAb 0.1–500 nM[192]
Superscript letter a—indicates the limit detection (LOD), b—indicates sensor sensitivity range and c—indicates sensor sensitivity.
Back to TopTop