C. RoyChaudhuri

Macroporous silicon based simple and efficient trapping platform for electrical detection of Salmonella typhimurium pathogens

A thermally oxidized macroporous silicon substrate with simple electrode structure without interdigitated electrode configuration has been reported for the detection of Salmonella typhimurium pathogens by electrical impedance measurement using antibody-antigen binding method. Macroporous silicon which has been fabricated by anodizing silicon in HF and DMF solution is a regular network of pores of 1-2 microm diameters. This has been thermally oxidized to yield the surface hydrophilic for antibody immobilization as well as provide suitable electrical insulation of the metal contacts from the underlying conducting silicon substrate. The macroporous silicon surface has been immobilized by Salmonella specific antibody and has been tested with different concentration of S. typhimurium pathogens in phosphate buffer solution (PBS). It has been found that such macroporous silicon substrates is capable of detecting down to 10(3)CFU/ml in pure culture using a 3 mm x 1 mm electrode structure with a wide spacing of 1mm. The selectivity of the macroporous silicon substrates with reference to S. typhimurium has been tested to be satisfactory by carrying out controlled experiments with Escherichia coli O157:H7.

Palladium-silver-activated ZnO surface: highly selective methane sensor at reasonably low operating temperature.

Metal oxide semiconductors (MOS) are well known as reducing gas sensors. However, their selectivity and operating temperature have major limitations. Most of them show cross sensitivity and the operating temperatures are also relatively higher than the value reported here. To resolve these problems, here, we report the use of palladium-silver (70-30%) activated ZnO thin films as a highly selective methane sensor at low operating temperature (∼100 °C). Porous ZnO thin films were deposited on fluorine-doped tin oxide (FTO)-coated glass substrates by galvanic technique. X-ray diffraction showed polycrystalline nature of the films, whereas the morphological analyses (field emission scanning electron microscopy) showed flake like growth of the grains mainly on xy plane with high surface roughness (107 nm). Pd-Ag (70-30%) alloy was deposited on such ZnO films by e-beam evaporation technique with three different patterns, namely, random dots, ultrathin (∼1 nm) layer and thin (∼5 nm) layer as the activation layer. ZnO films with Pd-Ag dotted pattern were found show high selectivity towards methane (with respect to H2S and CO) and sensitivity (∼80%) at a comparatively low operating temperature of about 100°C. This type of sensor was found to have higher methane selectivity in comparison to other commercially available reducing gas sensor.

Ultrasensitive food toxin biosensor using frequency based signals of silicon oxide nanoporous structure

We report an electrochemically fabricated silicon oxide nanoporous structure for ultrasensitive detection of AfB1 in food by shift in peak frequency corresponding to maximum sensitivity. It has been observed that the impedance sensitivity changes from 19% to 40% (which is only twice) where as the peak frequency shifts from 500 Hz to 50 kHz, for a change in concentration from 1 fg/ml to 1 pg/ml. This has been attributed to the combined effect of the significant pore narrowing with increasing AfB1 concentration and the opposing nature of impedance change within the nanopores and the conducting substrate immediately below the nanoporous layer.

A graphene field effect capacitive Immunosensor for sub-femtomolar food toxin detection

In this paper we report the sensing of aflatoxin B1(AFB1) by field effect capacitive method using electrophoretically deposited reduced graphene oxide (RGO) films for the first time. The RGO film has been characterized using SEM, surface profilometer and Raman spectroscopy. It has been observed that both quantum capacitance of RGO (Cq) and effective electrical double layer capacitance (C(EDL)) contribute significantly towards the overall sensitivity for molar concentration in the range of 20-50 mM. As Cq and CEDL changes in opposite direction after AFB1 capture and the nature of frequency dependence of Cq and CEDL are different, the sensitivity shows a minima at a particular frequency. Interestingly, the sensitivity minima is also dependent on AFB1 concentration. Further, the maximum sensitivity obtained is around 30% for 10(-4) ppt (0.1 fg/ml) AFB1 which is greater than 1.5 times that of previous reports. This has been possible through the enhanced biomolecule immobilization capability of RGO. Thus the RGO based field effect capacitive sensor provides a combined advantage of both a high sensitivity and concentration dependent frequency behavior.

Noise spectroscopy as an efficient tool for impedance based sub-femtomolar toxin detection in complex mixture using nanoporous silicon oxide.

In this paper we demonstrate an efficient and non-interfering computational method for sub-femtomolar food toxin detection in complex mixture based on nanoporous silicon oxide impedance immunosensor by employing noise spectroscopy analysis at the peak frequency. It has been observed that the peak frequency (fp) values obtained from steady state impedance measurements cannot distinguish between solution with only the specific toxin, which is aflatoxin B1 (AfB1) and mixture of AfB1 with other non-specific toxins (NSTs), thus leading to erroneous quantification of AfB1 in complex mixture. On the other hand, the first cut-off frequency (fc) ranges obtained from noise spectroscopy analysis can qualitatively differentiate between solution containing only AfB1, AfB1 and NSTs and no AfB1. However fc values being very close for different concentration of AfB1 in pure solution and being overlapping for different mixtures cannot quantify AfB1 either in pure solution or in complex mixture. To address this problem, the proposed computational method first clusters the fp and fc values in 11 categories each using k-means clustering algorithm and then applies a simple combinational digital logic on the clusters of fps and fcs to obtain the final output, realizable with standard NAND-NOR gates. The output digital word differs only with AfB1 concentration and not with concentration of NSTs and is found to be capable of detecting sub-femtomolar AfB1 range down to 0.1 fg/ml not only in pure solution but also in complex mixture with as high as 1000 ng/ml NSTs. This is the most sensitive and selective report so far on electrochemical food toxin immunosensors.

Optimized Electrode Geometry for an Improved Impedance Based Macroporous Silicon Bacteria Detector

This paper reports the optimization of electrode geometry on macroporous silicon biosensor for improved bacteria detection. Macroporous silicon of 8 μm thickness and 55% porosity has been fabricated on a 10-20 Ω-cm wafer using hydrofluoric acid and dimethyl sulfoxide. The electrode configurations selected for optimization are coplanar rectangular types with simple two-electrode, interdigitated comb finger-like electrode, and a combination of simple electrode and comb-shaped electrode designs. With these configurations, 14 different patterns have been generated with varying lengths and spacing within the technological constraints of low cost screen printing method of electrode fabrication with a wide range of effective exposed area from 0.04 to 0.6 mm2 by techniques from design of experiments. The sensitivity toward bacteria detection for all the patterns has been estimated by computation of an area utilization factor (AUF) which has been defined as the ratio of the effective area occupied by the captured bacteria to the effective exposed area available for capture. From the AUF values, eight patterns have been selected which are above a lower cut-off threshold for experimentation with E.coli O157 in the range of 102CFU/ml to 106 CFU/ml. It has been observed that the pattern with the highest AUF is capable of detecting 102CFU/ml E.coli O157 with a sensitivity of 11% without any pre-concentration which was not possible in the earlier reports of macroporous silicon.

Reliability Study of Nanoporous Silicon Oxide Impedance Biosensor for Virus Detection: Influence of Surface Roughness

The reliability issues of biosensors have been primarily attributed to the stability and degradation problems of biorecognition elements. However, a critical factor that has never been considered is the time-related device integrity with respect to the interfacial behavior of the material under prolonged exposure to buffer solution at a low temperature. In the presence of electrolyte, the interfacial properties of a particular material are expected to depend largely on surface roughness. In this paper, we have fabricated thick and stoichiometric nanoporous silicon oxide with varying surface roughness by controlling the ratio of hydrofluoric acid and dimethyl sulfoxide during anodic etching. The impact of surface roughness on the degradation of impedance characteristics during virus detection in blood has been studied extensively after different preservation time in buffer solution. It has been observed that reliability (i.e., repeatability) is significantly better for surfaces with higher roughness, but response magnitude and sharpness of sensitivity peak improve with lower surface roughness.

Electrical Sensing of Biochemicals using Macroporous Silicon

Electrical sensing of biochemical solutions has been reported in this paper using macroporous silicon formed by anodic etching of silicon with DMF and HF solutions. The fabricated porous silicon layers are around 30µ m thick with pore diameter around 1µ m and has been electrically characterised over a wide frequency range. The value of the capacitance can be varied over a wide range from pF to nF by tailoring the nature and dimensions of the electrical contacts over and above the values determined by its morphology. The C-V and I-V characteristics have been studied with two types of contacts—vacuum evaporated aluminium and aluminium paste. An electrical model of the porous silicon along with the contact geometry has been used to explain the basic device characteristics and the large variation of capacitances. The response of the porous silicon layer has been studied after oxidation both by hydrogen peroxide and by thermal method with different concentrations of glucose, potassium and sodium chloride solutions due to the physiological importance of the solutions. The macroporous silicon sensor has also been used to estimate the conditions of dehydration electrically as a function of osmolality of the solution which is essentially a manifestation of the concentration of sodium and potassium ions in solution. The porous silicon layer with thermally grown oxide shows a more significant difference in response with the varying concentrations of the solvents depending on their dielectric constant, dipole moment and molecular dimension.

Quantitative differentiation of multiple virus in blood using nanoporous silicon oxide immunosensor and artificial neural network

In spite of the rapid developments in various nanosensor technologies, it still remains challenging to realize a reliable ultrasensitive electrical biosensing platform which will be able to detect multiple viruses in blood simultaneously with a fairly high reproducibility without using secondary labels. In this paper, we have reported quantitative differentiation of Hep-B and Hep-C viruses in blood using nanoporous silicon oxide immunosensor array and artificial neural network (ANN). The peak frequency output (fp) from the steady state sensitivity characteristics and the first cut off frequency (fc) from the transient characteristics have been considered as inputs to the multilayer ANN. Implementation of several classifier blocks in the ANN architecture and coupling them with both the sensor chips, functionalized with Hep-B and Hep-C antibodies have enabled the quantification of the viruses with an accuracy of around 95% in the range of 0.04fM-1pM and with an accuracy of around 90% beyond 1pM and within 25nM in blood serum. This is the most sensitive report on multiple virus quantification using label free method.

Erratum to “Design Issues for Performance Enhancement in Nanostructured Silicon Oxide Biosensors: Modeling the Frequency Response”

Nanostructured silicon oxide impedance biosensors with ordered nanopores promise highly sensitive and selective label-free electrical detection of biomolecules through unique frequency-dependent sensitivity characteristics. Despite these promising experimental results, the fundamental mechanisms controlling the frequency-dependent phenomena and hence the design considerations have not been explored. In this paper, we consistently model the fluid and the solid regions of the sensors and discuss the design issues with respect to the pore dimensions for enhancing the sensitivity, selectivity, and repeatability toward detection of ultralow and moderate concentration of target biomolecules. The simulation results have been validated with experiments. The results indicate that the optimal design of nanoporous silicon oxide biosensors is different from the conventional idea of increasing the surface-to-volume ratio of such sensors. Instead, the design approach is nontrivial and the optimum pore dimensions are dependent on the target biomolecule charge, concentration, and distribution. It has been observed that a figure of merit is essential to design such sensors with improved commercial viability.