Synthesis of Electrical Conductive Silica Nanofiber/Gold Nanoparticle Composite by Laser Pulses and Sputtering Technique
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Biocompatible-sensing materials hold an important role in biomedical applications where there is a need to translate biological responses into electrical signals. Increasing the biocompatibility of these sensing devices generally causes a reduction in the overall conductivity due to the processing techniques. Silicon is becoming a more feasible and available option for use in these applications due to its semiconductor properties and availability. When processed to be porous, it has shown promising biocompatibility; however, a reduction in its conductivity is caused by its oxidization. To overcome this, gold embedding through sputtering techniques are proposed in this research as a means of controlling and further imparting electrical properties to laser induced silicon oxide nanofibers. Single crystalline silicon wafers were laser processed using an Nd:YAG pulsed nanosecond laser system at different laser parameters before undergoing gold sputtering. Controlling the scanning parameters (e.g., smaller line spacings) was found to induce the formation of nanofibrous structures, whose diameters grew with increasing overlaps (number of laser beam scanning through the same path). At larger line spacings, nano and microparticle formation was observed. Overlap (OL) increases led to higher light absorbance’s by the wafers. The gold sputtered samples resulted in greater conductivities at higher gold concentrations, especially in samples with smaller fiber sizes. Overall, these findings show promising results for the future of silicon as a semiconductor and a biocompatible material for its use and development in the improvement of sensing applications.
KeywordsNanomaterials Silicon Laser materials processing Biological sensing and sensors Materials and process characterization Nanostructure fabrication
Biocompatible sensing materials tend to be costly to produce as well as having a low signal-to-noise ratio (SNR); A signal-to-noise ratio is a measure of signal power to a level of noise power (background noise) and is expressed as a measurement of decibels (dB). Nanomaterials were introduced as an attempt to reduce the muffling caused by the noise. Two main methods are used to reduce muffling, namely, carbon nanotube formation and nanomaterials . The success of carbon nanotubes as sensors may be attributed to their increased effective surface area, which decreases the electrode impedance and increases current [1, 2, 3, 4]. The increased surface area also immobilizes more enzymes thereon in biomedical applications . However, there are some disadvantages to fabricating carbon nanotubes. For instance, it is expensive and has low purity, a shortage in alignment control, a lack of aqueous solubility, and a high reactivity caused by dangling nanotubes .
Adverse tissue reactions and resistance to degradation are important biocompatibility factors . Porous silicon, which is formed of a unique structure of nanocrystallites and pores, exhibits properties that are valuable for its use as a biomaterial and potential biosensing applications . Silicon—a commonly used material—is versatile in contemporary microprocessing techniques because of its availability and low cost [8, 9]. Silicon can be processed to form macro, micro, and nanopores. The ideal pore diameter for biocompatible sensing devices is between 2 and 50 nm. These pore sizes enable biomolecular diffusion and larger surface exposure, resulting in increased biomolecule immobilization compared to 2D surfaces and make it an excellent material for biosensing applications .
Various methods can be used to modify the surface of silicon substrates to fabricate silicon-based sensors. Electrochemical etching is used in many cases to modify silicon into a porous structure. This method requires the use of various chemicals and specialized equipment. The procedure initially requires thorough cleansing of the wafer. Certain chemicals may highly react to defects in the structure of silicon and release toxic gases [9, 10]. Electrochemical etching also strongly influences the surface topography, making it more difficult to control . Achieving a uniform porous surface using this technique is complex and highly dependent on and sensitive to the etching parameters, also resulting in the production of large quantities of waste . Moreover, a high concentration of hydrogen bonds subsides on the surface post preparation, making it highly unstable . Photolithography is another method for modifying the surface of silicon substrates in order to fabricate a biocompatible silicon-based sensor [13, 14]. This method enables the patterning and control of cell behavior. Its main disadvantage is that due to the optical diffraction of the light beam, the resolution is limited to a maximum of 1 μ in practice.
Laser processing is another method for modifying the surface of silicon substrates. It is used to optimize a material’s performance such as its absorption, susceptibility to wear, surface chemistry, and crystal structure. Surface properties can be controlled in this manner without affecting the bulk of the material [8, 9].
The addition of gold nanoparticles is an attractive method for modifying the surface of silicon substrates in order to fabricate a silicon sensor. Gold nanoparticles have important properties including their conductivity, high surface-to-volume ratio, excellent molecular recognition, and high surface energy [15, 16]. Their unique chemical and physical properties help to transfer electrons from the biospecific layer to the electrode surface . Gold nanoparticles also increase the sensitivity of biochemical detection of electrochemical biosensors [17, 18].
Previously published results by Colpitts and Kiani have proven the usage of a nanosecond pulsed laser system in the formation of biocompatible fibrous structures on silicon [12, 19]. Their initial results inspired the aim of this research to propose a method of customizing the properties of laser processed silicon to improve its viability in future biological sensing applications which require properties of both biocompatibility and electrical conductivity. Also outlined is an effective method of generating nanofibrous silicon oxide using a commercial nanosecond pulsed laser. This involved the processing of a crystalline silicon wafer using an Nd:YAG nanosecond pulsed laser at a constant power of 12 W with a variation in the overlaps (number of laser beam scanning through the same path) and line spacings (distance between scanning paths). Gold sputtering was then conducted on its surface for duration of either 4 or 8 min. Changes in absorption and conductivity as well as surface topography were investigated and are discussed.
Materials and Methods
An Nd:YAG nanosecond pulsed laser with a wavelength of 1064 nm was used for this experiment. The circular output beam of the laser has a diameter of 9 mm and is reduced to 8 mm using an iris diaphragm before entering an XY galvanometer scanner (JD2204 by Sino-Galvo). This scanner has an aperture of 10 mm and a beam displacement of 13.4 mm. A F-theta lens with a focal length of 63.5 mm was used to control the focus of the laser on the sample surface, resulting in a theoretical laser spot diameter of 20 μm. EZCAD software was used to control laser parameters, e.g., to specify scanning speeds, overlaps, frequency, and line patterning.
Microscopy and Surface Characterization: Scanning Electron Microscope (SEM) and Scanning Transmission Electron Microscope (TEM) and Energy Dispersive X-Ray (EDS)
A variety of means were employed for surface characterization, including a JEOL JSM-6400 scanning electron microscope (SEM) mounted with an EDAX Genesis 4000 energy dispersive X-ray (EDS) and A JEOL JEM-2010 scanning transmission electron microscope (TEM) adapted with a Gatan UltraScan camera using DigitalMicrograph was used to collect the desired images.
The STS-NIR Spectro Radiometer (Ocean Optics, Dunedin, Florida, USA) was used to determine the optical properties of the samples, namely, to measure the reflectivity coefficient of the samples at varying overlaps and line spacing at wavelengths between 175 and 885 nm and an optical resolution of 1.5 nm .
A CH Instruments Inc. (USA) model 760 potentiostat was used to measure the conductivity of the processed silicon samples using AC impedance spectroscopy. The samples were connected via alligator clips to the spectrometer (two-electrode mode) and measurements were obtained at frequencies between 0 and 1 × 106 Hz and at the potential amplitude of 10 mV.
The software ImageJ 1.501 by Wayne Rasband at the National Institutes of Health, USA, is used to determine particle and fiber diameters. It allows for the manual import and measurement of the features captured by SEM and TEM images.
Results and Discussion
Generation of Nanofibrous Structures
Silicon samples were processed at one, three, and five overlaps at an average power of 12 W with line spacings of 0.025, 0.10, and 0.15 mm. SEM images were collected to determine the type of nanostructures present.
It is not surprising that optimal nanofiber generation was observed at the smallest line spacing of 0.025 mm. Since the laser diameter is theoretically very close to the size of this line spacing, little to no area is left that does not come into direct contact with the laser. This results in a more heated region and the plume density is kept stable for a longer period. This further increases the overall light absorption of the sample due to the change in topography. By creating a fiber network, the surface area increases and therefore all the mechanisms directly linked to area are enhanced.
Removing material from a solid surface using pulsed laser technology can induce nanoparticle formation. When the laser is shined on a surface, it induces vaporization and removes atoms from the bulk surface, thus enabling the laser pulse to go deeper into the material. Laser depth depends on factors such as its wavelength and the material’s physical properties. The laser’s electromagnetic fields eject electrons by discharging energy and momentum on the surface of the material. The energy transfer involved in the laser’s interaction with the material causes its temperature to rise, which in turn causes the formation of an ionized gas known as plasma that will expand like a shockwave around the laser’s focus. Particles are removed from the surface when the laser’s intensity (fluence) is greater than the material’s ablation threshold. The contents of the plasma take the shape of a plume: a region containing a mixture of ions, electrons, and nanoparticles that are highly reactive. When laser ablation is conducted in air, oxidation of the ejected particles may result. As the plume expands, its extremities are cooler than its core . As a result, newly formed particles move toward cooler regions, which causes them to supersaturate, further nucleate, and crystallize into a solid structure. Collisions between gas atoms and the ablated plume in the thin interface layer generate nanoparticles and aggregates. The ambient gas coalesces with the evaporated atoms and ions at high temperatures. As the plume cools, aggregate formation begins. By the end of the laser pulse, aggregate-aggregate and atom-aggregate attachments occur .
Laser ablation is highly dependent on the heat transfer to the material. With nanosecond lasers, it is generally assumed that most of the absorption is due to single photon interactions. Increases in light absorption result in higher temperatures and plume pressures , which encourage nanofibrous structure formation.
When the thermalization rate is greater than the laser-induced excitation rate, the process is referred to as photothermal or pyrolytic, where the absorbed laser energy is assumed directly transformed into heat. This is the case when the laser pulse times are greater than the nanosecond range. Photothermal processing leads us to the modeling of heat flow through the material. Its response to the laser is due to thermal effects in both its temporal and spatial coordinates and can be modeled from derivations of the heat equation.
From the temperature profiles shown in Fig. 6, there is a gradient that forms before the maximum average temperature is reached. This gradient causes the formation of the plasma mentioned earlier. The steady state maximum values for each of the samples were determined and as concluded, the samples at three overlaps reached a higher average surface temperature than those at one overlap. This can be explained by the increase in the size of the nanoparticles, hence leading to higher absorptions. The only exceptions are the samples at a line spacing of 0.025 mm, where both these samples resulted in the same maximum average temperature. This is due to the very close correlation in their reflectivity values.
As absorption increases, the average number of particles as well as the rate begins by increasing seemingly parabolically. There is a rapid increase in the number of evaporated particles at lower absorption values. Although a higher number of atoms can be achieved as the absorption increases, the curve no longer grows as rapidly. This explains why silicon laser processed surfaces with higher absorption coefficients are more likely to have nanoparticles and fiber formations as the number of evaporated atoms increases, thus allowing for more structural rearrangement.
Gold Sputtering of Laser-Generated Silicon Oxide Nanofibers
The samples prepared at an average power of 12 W and at a line spacing of 0.025 mm were sputtered with gold to assess their conductive properties. Samples were gold sputtered for either 4 or 8 min. The conductivity and particle size effects were measured and compared at different overlaps.
Theoretically, longer pulse durations and higher plume density and temperatures result in larger nanostructure formation. Nanostructure sizes depend highly on the plume diffusion time scale while their type depends on the density of the evaporated atoms. For this reason, to achieve nanofibrous structures, the laser pulses must be kept continuous for the plume density to remain at the critical level required for their formation. Hence, the larger particle sizes with growing overlaps can be explained in this fashion due to the higher overall surface temperatures and absorption coefficients .
In this report, a method of nanofiber generation using a nanosecond pulsed laser is proposed along with a technique to customize the electrical properties of laser processed silicon to improve its viability in sensing applications requiring a biocompatible environment using gold sputtering techniques. Micro and nanofibrous structures were achieved using a nanosecond Nd:YAG pulsed laser system on a single crystalline silicon wafer. Laser pulses enable to precisely deliver large amounts of energy into the surface of a material in order to achieve a desired nanofibrous structures. For silicon as an opaque material, the laser energy is absorbed near the surface, synthesizing thin-film of nanofibrous silicon without altering the bulk properties. The processed silicon samples were sputtered with gold for duration of either 4 or 8 min to impart and compare its effects on the conductive properties. Overlap number and line spacing were varied in this experiment, and the changes in the absorption capabilities of the samples were experimentally measured and compared. The absorption was found to increase at smaller line spacings and at higher overlaps, allowing for the rearrangement of the silicon substrate into fibers and agglomerates capable of absorbing more light. It was shown that both gold and silicon particles exhibited growth as the absorption coefficients of the materials increased. Fibrous structures were seen to form at shorter line spacings and at higher powers. As the overlap numbers were increased, the fiber diameters grew as well due to the growth in particle sizes. Finally, the conductivity showed some controllability in terms of the duration of sputtering undergone by the samples.
Identifying the fabrication technique for such biocompatible sensor devices is vital and is still being in progress. More studies, in current future direction of this project, need to be conducted to distill the proposed method and propose the guidelines to ascertain the scientific challenges as well as the prerequisites to make this technology market-viable. Although there is yet more research to be done in this area, these findings act as an important preliminary review as to the direction in which biological sensing surfaces can be further adapted and made cost effective. Silicon, being a semiconductor and one of the most common resource for electronic and circuit building, can now impart conductive and biocompatible properties. This method outlines an economic, simple, and yet effective way to process silicon to achieve nanofibrous structures able to increase its biocompatibility while still allowing for electrical conductance.
This research was funded by the National Sciences and Engineering Research Council (NSERC) Discovery Grant program, the New Brunswick Innovation Foundation (NBIF), and the McCain Foundation.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
SH and AK carried out the laser processing of the samples and the characterization and drafted the manuscript. AI held the conductivity examination of the samples and participated in characterization of the materials. AK conceived of the study and participated in its design and coordination. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
- 1.Shi J, Porterfield DM (2011) Surface modification approaches for electrochemical biosensors. INTECH Open Access PublisherGoogle Scholar
- 2.He P, Dai L (2006) Carbon nanotube biosensors. BioMEMS and biomedical nanotechnology, Springer US, p 171-201Google Scholar
- 5.Eatemadi A, et al (2014) Carbon nanotubes: properties, synthesis, purification, and medical applications. Nanoscale Res Lett 9(1):393. doi: 10.1186/1556-276X-9-393. https://nanoscalereslett.springeropen.com/articles/10.1186/1556-276X-9-393
- 6.Davis JR (2003) Overview of biomaterials and their use in medical devices. Handbook of materials for medical devices, Illustrated edition. ASM International, Ohio, pp 1–11Google Scholar
- 7.Jamois C, Li C, Gerelli E, Orobtchouk R, Benyattou T, Belarouci A, Chevolot Y, Monnier V, Souteyrand E (2011) New concepts of integrated photonic biosensors based on porous silicon. Biosensors-Emerging Materials and ApplicationsGoogle Scholar
- 9.Buckberry L, Bayliss S (1999) Porous silicon as a biomaterial. Mater World 7(4):213–215Google Scholar
- 10.Jones MH, Jones SH (2003) Wet-chemical etching and cleaning of silicon. Virginia Semiconductor, FredericksburgGoogle Scholar
- 12.Colpitts C, Ektesabi AM, Wyatt RA, Crawford BD, Kiani A (2016) Mammalian fibroblast cells show strong preference for laser-generated hybrid amorphous silicon-SiO2 textures. J Appl Biomater Funct Mater 15(1):e84–e92Google Scholar
- 14.Mitra SK, Saha AA (2015) Surface modification, methods. Encyclopedia of Microfluidics and Nanofluidics, pp 3115-3123. doi: 10.1186/1556-276X-9-393. https://link.springer.com/referenceworkentry/10.1007%2F978-0-387-48998-8_1503
- 15.Presnova G, Presnov D, Krupenin V, Grigorenko V, Trifonov A, Andreeva I, Ignatenko O, Egorov A, Rubtsova M (2017) Biosensor based on a silicon nanowire field-effect transistor functionalized by gold nanoparticles for the highly sensitive determination of prostate specific antigen. Biosens Bioelectron 88:283–289CrossRefGoogle Scholar
- 16.Chang HY, Arshad MM, Fathil MFM, Hashim U (2016) Gold nanoparticles embedded silicon channel biosensor for improved sensitivity. In Mahmood MR, Soga T, Nagaoka S, Mamat MH, Jafar SM (eds) AIP Conference Proceedings (Vol. 1733, No. 1, p. 020074). AIP Publishing. doi:http://dx.doi.org/10.1063/1.4948892
- 21.Gaharwar AK, Sant S, Hancock MJ, Hacking SA (eds) (2013) Nanomaterials in tissue engineering: fabrication and applications. Elsevier. doi: 10.1533/9780857097231.1
- 24.Brown MS, Arnold CB (2010). Fundamentals of laser-material interaction and application to multiscale surface modification. In Laser precision microfabrication (pp. 91-120). Springer Berlin Heidelberg. doi: 10.1007/978-3-642-10523-4_4
- 29.Mukherjee R, (2014). Correlation effects in nanoparticle composites: percolation, packing and tunnelingGoogle Scholar
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