Surface plasmon resonance detection system
An example SPR detection system includes a first prism having a first surface adjacent to a first metal layer exposed to a sample gas, and a second prism having a second surface adjacent to a second metal layer exposed to a reference gas. At least one light source is configured to provide respective beams to the first and second surfaces, where each of the beams causes SPR of a respective one of the metal layers. At least one photodetector is configured to measure a reflection property of reflections of the respective beams from the metal layers during the SPR. A controller is configured to determine whether a target gas is present in the sample gas based on a known composition of the reference gas and at least one of an electrical property of the first and second metal layers during the SPR and the reflection property of the metal layers.
1. A surface plasmon resonance (SPR) detection system, comprising:
a light propagation structure comprising a surface and a plurality of waveguides;
a plurality of metal layers comprising different metal oxide frameworks (MOFs) that are spaced apart from each other and have differing porosities and different binding affinities for a plurality of different target gases, the plurality of metal layers arranged in an array on the surface and exposed to a sample gas;
a plurality of light sources configured to provide respective beams through the plurality of waveguides to the surface that cause SPR of each metal layer;
an array of photodetectors, each associated with one of the metal layers, and configured to measure a reflection property of a reflection of one of the beams from an interface of the surface and its associated metal layer; and
a controller configured to determine an electrical property of the plurality of metal layers during the SPR, and determine whether any of the target gases are present in the sample gas based on at least one of the electrical properties and the reflection properties of the metal layers.
2. The SPR detection system of claim 1 , wherein:
each metal layer is adjacent to a companion metal layer that is coated to prevent adsorption of analytes to the companion metal layer; and
the controller is configured to compare at least one of the electrical property and the reflection property from each of the plurality of metal layers to at least one of an electrical property and a reflection property from its corresponding companion metal layer as part of the determination of whether any of the target gases are present in the sample gas.
3. The SPR detection system of claim 2 , wherein each metal layer has the same MOF composition as its companion metal layer.
4. The SPR detection system of claim 2 , wherein the plurality of metal layers and companion metal layers are coplanar.
5. The SPR detection system of claim 1 , wherein:
the plurality of light sources comprises a respective light emitter for each row of the array of metal layers; and
wherein each waveguide is configured to guide a beam from a given one of the light emitters towards the metal layers of its associated row at predefined angles.
6. The SPR detection system of claim 1 , comprising:
a plurality of heaters disposed adjacent to individual ones of the metal layers, each configured to induce desorption of analytes from its adjacent metal layer by heating its adjacent metal layer.
7. A chemical detection system, comprising:
a plurality of detectors arranged for collecting data from a gas sample, each detector comprising a respective metal layer, wherein each of the metal layers includes a different metal oxide framework (MOF), the metal layers are spaced apart from each other and have differing porosities, and various ones of the metal layers having differing binding affinities for a plurality of target gases, the plurality of detectors configured to use at least one of surface plasmon resonance (SPR) and photoacoustic detection techniques to collect data about the gas sample; and
a processor configured to perform a machine learning-based analysis to determine whether any of the target gases are present in the gas sample based on the data collected by the plurality of detectors from the gas sample.
8. The chemical detection system of claim 7 , wherein to perform the machine learning-based analysis, the processor is configured to:
apply at least one machine learning technique to a set of historical training data to produce a nodal set that represents at least one of spatial and temporal correlations in the set of historical training data, the training data gathered by the plurality of detectors when exposed to a plurality of different training gases having known compositions; and
utilize the nodal set to determine whether any of the target gases are present in the gas sample based on the data collected by the plurality of detectors from the gas sample.
9. The chemical detector system of claim 8 , wherein the nodal set comprises a neural network comprising at least one of a recurrent neural network and a convolutional neural network.
10. The chemical detector system of claim 7 , wherein the data collected by the plurality of detectors from the gas sample includes a change in resistance across a plurality of the metal layers when the plurality of metal layers are resonating and are exposed to the gas sample.
11. The chemical detector system of claim 7 , wherein the data collected by the plurality of detectors from the gas sample includes a change in amplitude, frequency, or both, of respective electrical signals across respective ones of the metal layers when the respective ones of the metal layers are resonating and are exposed to the gas sample.
12. The chemical detector system of claim 7 , wherein the data collected by the plurality of detectors from the gas sample includes changes in reflection properties of beams reflected from the metal layers when the metal layers are resonating and are exposed to the gas sample.
13. The chemical detector system of claim 7 , wherein the data collected by the plurality of detectors from the gas sample includes desorption data indicative of a time needed for analytes from the gas sample to desorb from various ones of the metal layers.
14. The SPR detection system of claim 1 , wherein:
the plurality of metal layers includes a plurality of rows and a plurality of columns of metal layers; and
the array of photodetectors includes a plurality of rows and a plurality of columns of photodetectors.
15. The SPR detection system of claim 1 , wherein:
the array of photodetectors includes a plurality of rows of photodetectors;
the array of metal layers includes a plurality of rows of metal layers; and
each waveguide is configured to propagate light from a single one of the plurality of light sources to a corresponding single one of the rows of photodetectors.
16. The chemical detector system of claim 7 , wherein:
the plurality of metal layers includes a plurality of rows and a plurality of columns of metal layers; and
the array of photodetectors includes a plurality of rows and a plurality of columns of photodetectors.
17. The chemical detector system of claim 7 , wherein:
the array of photodetectors includes a plurality of rows of photodetectors;
the array of metal layers includes a plurality of rows of metal layers; and
each waveguide is configured to propagate light from a single one of the plurality of light sources to a corresponding single one of the rows of photodetectors.