CHEMICAL SENSORS BASED ON CUBIC NANOPARTICLES CAPPED WITH AN ORGANIC COATING

• US 20100273665A1
• Filed: 11/20/2008
• Published: 10/28/2010
• Est. Priority Date: 11/20/2007
• Status: Active Grant

• Current Assignee: TECHNION RESEARCH AND DEVELOPMENT FOUNDATION, LTD.
• Original Assignee: TECHNION RESEARCH AND DEVELOPMENT FOUNDATION, LTD.
• Inventors: Haick, Hossam, Dovgolevsky, Ekaterina
• Granted Patent: US 8,999,244 B2
• Time in Patent Office: Days
• US Class Current: 506/8
• CPC Class Codes: B82Y 15/00 Nanotechnology for interacting, sensing or actuating, e.g. quantum dots as markers in protein assays or molecular motors
• CPC Class Codes: B82Y 30/00 Nanotechnology for materials or surface science, e.g. nanocomposites
• CPC Class Codes: G01N 2021/258 Surface plasmon spectroscopy, e.g. micro- or nanoparticles in suspension
• CPC Class Codes: G01N 21/554 detecting the surface plasmon resonance of nanostructured metals, e.g. localised surface plasmon resonance
• CPC Class Codes: G01N 21/77 by observing the effect on a chemical indicator
• CPC Class Codes: G01N 27/127 comprising nanoparticles

Abstract

The present invention provides a sensor apparatus based on 2D films or 3D assemblies of cubic nanoparticles capped with an organic coating. The apparatus is used to determine the composition and preferably measure the concentration of volatile and non-volatile compounds in a sample, with very high sensitivity. Methods for use of the apparatus in applications such as diagnosis of disease, food quality and environmental control are disclosed.

Claims

1. An apparatus comprising at least one chemically sensitive sensor for detecting volatile and non-volatile compounds, wherein the chemically sensitive sensor comprises cubic nanoparticle conductive cores capped with an organic coating.

4. The apparatus according to claim 1, wherein the cubic nanoparticle conductive cores are capped with an organic coating comprising a monolayer or multilayers of organic compounds, wherein the organic compounds are selected from small molecules, monomers, oligomers and polymers.

5. The apparatus according to claim 1, wherein the cubic nanoparticle conductive cores are selected from the group consisting of Au, Ag, Ni, Co, Pt, Pd, Cu, Al, Au/Ag, Au/Cu, Au/Ag/Cu, Au/Pt, Au/Pd, Au/Ag/Cu/Pd, Pt—

Rh, Ni—

Co, and Pt—

Ni—

Fe.

6. The apparatus according to claim 1, wherein the organic coating is selected from the group consisting of alkylthiols with C₃-C₂₄ chains, ω

-functionalized alkanethiolates, arenethiolate, (γ

-mercaptopropyl)tri-methyloxysilane, dialkyl disulfides, xanthates, oligonucleotides, polynucleotides, peptides, proteins, enzymes, polysaccharides, phospholipids, and combinations thereof.

7. The apparatus according to claim 1, wherein the cubic nanoparticles capped with an organic coating are in a configuration selected from 1D wires, 2D films, and 3D assemblies.

8. The apparatus according to claim 1, further comprising at least one of a chemiresistor, chemicapacitor, quartz crystal microbalance, bulk acoustic wave (BAW) and surface acoustic wave (SAW) resonator, electrochemical cell, surface plasmon resonance (SPR), and optical spectroscope.

2. (canceled)

3. (canceled)

9. A system having:

(i) an apparatus comprising an array of chemically sensitive sensors for detecting volatile and non-volatile compounds comprising cubic nanoparticle conductive cores capped with an organic coating, and

(ii) a learning and pattern recognition analyzer, wherein said learning and pattern recognition analyzer receives sensor output signals and compares them to stored data.

12. The system according to claim 9, wherein the cubic nanoparticle conductive cores are capped with an organic coating comprising a monolayer or multilayers of organic compounds, wherein the organic compounds are selected from small molecules, monomers, oligomers and polymers.

13. The system according to claim 9, wherein the cubic nanoparticle conductive cores are selected from the group consisting of Au, Ag, Ni, Co, Pt, Pd, Cu, Al, Au/Ag, Au/Cu, Au/Ag/Cu, Au/Pt, Au/Pd, Au/Ag/Cu/Pd, Pt—

Rh, Ni—

Co, and Pt—

Ni—

Fe.

14. The system according to claim 9, wherein the organic coating is selected from the group consisting of alkylthiols with C₃-C₂₄ chains, ω

-functionalized alkanethiolates, arenethiolate, (γ

-mercaptopropyl)tri-methyloxysilane, dialkyl disulfides, xanthates, oligonucleotides, polynucleotides, peptides, proteins, enzymes, polysaccharides, phospholipids, and combinations thereof.

15. The system according to claim 9, wherein the cubic nanoparticles capped with an organic coating are in a configuration selected from 1D wires, 2D films, and 3D assemblies.

16. The system according to claim 9, further comprising at least one of a chemiresistor, chemicapacitor, quartz crystal microbalance, bulk acoustic wave (BAW) and surface acoustic wave (SAW) resonator, electrochemical cell, surface plasmon resonance (SPR), and optical spectroscope.

17. The system according to claim 9, wherein the learning and pattern recognition analyzer comprises at least one algorithm selected from the group consisting of artificial neural network algorithms, principal component analysis (PCA), multi-layer perception (MLP), generalized regression neural network (GRNN), fuzzy inference systems (FIS), self-organizing map (SOM), radial bias function (RBF), genetic algorithms (GAS), neuro-fuzzy systems (NFS), adaptive resonance theory (ART), partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), discriminant function analysis (DFA), linear discriminant analysis (LDA), cluster analysis, and nearest neighbor.

10. (canceled)

11. (canceled)

18. (canceled)

19. A method for determining at least one of the composition and concentration of selected volatile and non-volatile compounds in a sample, comprising the steps of:

providing a system comprising an apparatus for detecting volatile and non-volatile compounds comprising an array of chemically sensitive sensors of cubic nanoparticles capped with an organic coating, and a learning and pattern recognition analyzer, wherein the learning and pattern recognition analyzer receives sensor output signals and compares them to stored data;

(ii) exposing the sensor array of the apparatus to the sample; and

(iii) using pattern recognition algorithms to detect the presence of volatile and non-volatile compounds in the sample.

20. The method according to claim 19, for detecting volatile and non-volatile compounds indicative of a disease in a subject.

21. The method according to claim 20, wherein the disease is selected from the group consisting of cancer, acute asthma, hepatic encephalopathy, rheumatoid arthritis, renal failure, schizophrenia, ketosis, cardiopulmonary disease, uremia, diabetes mellitus, dysgeusia/dysosmia, cystinuria, cirrhosis, histidinemia, tyrosinemia, halitosis and phenylketonuria.

23. The method according to claim 20, for differentiating between different types of cancer.

24. The method according to claim 20, wherein the sample comprises at least one bodily fluid or secretion selected from the group consisting of serum, urine, feces, sweat, vaginal discharge, saliva, and sperm.

25. The method according to claim 19, for detecting volatile and non-volatile compounds indicative of spoilage in food products.

26. The method according to claim 19, for detecting volatile and non-volatile compounds indicative of environmental pollution.

27. The method according to claim 19 comprising measuring a response selected from an electronic response and optical response.

28. The method according to claim 27, wherein the response is measured using spectroscopic ellipsometry.

22. (canceled)

29-38. -38. (canceled)