Transcript sensors
BIOMEMS Class I. Introduction: From MEMS to BIOMEMS/ Definitions Winter 2011 Dr. Marc Madou Aequorea victoria Content From MEMS to BIOMEMS BIOMEMS and analytical chemistry Definition of sensors Sensitivity Cross-sensitivity and crosstalk Signal-to-noise-ratio and drift Resolution Span or range and bandwidth Dynamic range, gain and dynamic error Selectivity Hysteresis Accuracy Calibration From MEMS to BIOMEMS ‘Miniaturization engineering’ is a more appropriate name than MEMS (NEMS), but the name MEMS (NEMS) is more popular. It involves a good understanding of scaling laws, different manufacturing methods and materials. Initially it involved mostly Si and mechanical sensors (e.g., pressure, acceleration, etc). Miniaturization engineering or MEMS applied to biotechnology is called BIOMEMS. In BIOMEMS the number of materials involved is much larger, modularity is often a must (not integration as in ICs !), costs often need to be less than what’s possible with Si and batch processes are not always the answer ( continuous manufacturing need !). From MEMS to BIOMEMS Silicon Valley Micromachining 1972 Foxboro/ICT 1972 Sensym/National Semiconductor (sold to Hawker Siddley in 1988) 1975 Endevco 1975 IBM Micromachining 1976 Cognition (sold to Rosemount in 1978) 1980 Lawrence Livermore Lab 1981 Microsensor Technology (sold to Tylan in 1986) 1982 Transensory Devices (sold to ICSensors in 1987) 1982 ICSensors (sold to EG&G in 1994) 1985 NovaSensor (sold to Lucas in 1990) 1986 Captor (sold to Dresser in 1991) 1988 Redwood Microstructures 1988 TiNi Alloys 1989 Teknekron Sensor Development Corporation (dissolved in 1993) 1990 Microflow 1991 Sentir 1992 Silicon Microstructures 1992 Rohm Micromachining 1993 Silicon Micromachines 1993 Fluid IC 1993 Next Sensors 1994 Berkeley Microstructures 1994 Piedmont Microactuators 1995 Caliper 1995 Cepheid BIOMEMS as part of analytical chemistry BIOMEMS may often be seen as a type of analytical technique used in many research areas : – Chemistry – Biochemistry – Biology – Geology – Oceanography, etc. Analytical techniques which are also used in many industrial areas : – Forensic science (e.g. O.J.’s DNA) – Clinical diagnostics (e.g.glucose in blood) – Product development (e.g. new drug) – Quality control (e.g.pH of swimming pool) Both instruments and sensors (see next viewgraph for definition) are used in BIOMEMS both will be discussed in this course- the distinction between the two is rather vague (e.g. size, complexity, parts of an instrument might be called a sensor, etc.) Definitions of sensors Chemical sensors are defined as measurement devices Effector (magnetic, chemical, physical, which utilize chemical or biological reactions to detect etc.) and quantify a specific analyte or event. They are ususally a lot more difficult to make than physical Active surface sensors which measure physical parameters. For the distinction between biosensors and chemical sensors we define a biosensor as one which contains a Transducer biomolecule (such as an enzyme, antibody, or receptor), Sensor a cell or even tissue as the active detection component. Integrated sensor A sensor, a transducer, transmitter and detector or often Smart sensor used as synonyms. They are devices that convert one form of energy into another and provide the user with a usable energy output in response to a specific Amplification/Filtering/A/D, etc measurable input. In the chemical sensor area a transducer plus an active surface is called a sensor. Data storage and processing Output Control Sensor system Sensitivity A sensor detects information input, Iin, and then transduces or converts it to a more convenient form, Iout i.e Iout = F(Iin). So sensitivity is the amount of change in a sensor’s output in response to a change at a sensor’s input over the sensor’s entire range. NOT THE SAME AS LOWER LIMIT OF DETECTION! Very often sensitivity approximates a constant; that is, the output is a linear function of the input Sensitivity may mathematically be expressed as = dIout dI in Germanium Resistance Thermometers Sensitivity 35,000 Ohms/K @ 4.2 K http://www.sciinst.com/sensors/grt.htm Cross-sensitivity and crosstalk Cross-sensitivity: The influence of one measurand on the sensitivity of the sensor for another measurand (e.g., OH- influences F- detection) Crosstalk: Electromagnetic noise transmitted between leads or circuits in close proximity to each other Signal-to-noise-ratio-S/N and drift S/N: The ratio of the output signal with an input signal to the output signal with no input signal Drift: Gradual departure of the instrument output from the calibrated output. An undesirable change of the output signal. Noise is normally measured "peak-to-peak": i.e., the distance from the top of one such small peak to the bottom of the next, is measured vertically. Sometimes, noise is averaged over a specified period of time. The practical significance of noise is the factor which limits detector sensitivity. A practical limit for this is a 2 x signal-to-noise ratio. Resolution The smallest increment of change in the measured value that can be determined from the instrument’s readout scale. Span or range (also called bandwidth) Span or range: The difference between the highest and lowest scale values of an instrument Bandwidth: The range of scale values over which the measurement system can operate within a specified error range ( also used as another word for span) Dynamic range, gain and dynamic error Dynamic range: The ratio of the largest to the smallest value of a range, often expressed in decibels (dB), Gain:The ratio of the amplitude of an output to input signal. Dynamic error: The error that occurs when the output does not precisely follow the transient response of the measured quantity. Selectivity Selectivity: The ability of a sensor to measure only one parameter, in the case of a chemical sensor, to measure only one chemical species Because of the lack of perfect selectivity arrays are often implemented (e.g., electronic nose and tongue) The electronic nose The sensitivity of certain gas sensors to different gases depends on the choice of catalytic sensor material and the operating temperature. By combining several different gas sensors into a sensor array, complex gas mixtures can be analysed. Although the selectivity of the sensors is limited, qualitative and quantitative gas analysis can be performed using pattern-recognition techniques. The combination of multiple gas sensors and signal analysis using patternrecognition techniques is the concept behind the electronic nose and tongue. These instruments have been successfully used in a number of applications, e.g., the quality estimation of ground meat, the identification of different paper qualities, the classification of grains with respect to microbial quality, and the screening of irradiated tomatoes. Hysteresis The difference in the output when a specific input value is approached first with an increaseing and then with a decreasing input. Piezoelectric ceramics display hysteretic behavior. Suppose we start at zero applied voltage, gradually increase the voltage to some finite value,and then decrease the voltage back to zero. If we plot the extension of the ceramic as a function of the applied voltage, the descending curve does not retrace the ascending curve - it follows a different path. Accuracy The degree of correctness with which a measuring system yields the “true value” of a measured quantity (e.g. bull’s eye) --see calibration http://ull.chemistry.uakron. edu/analytical/animations/ Precision QuickTime™ and a Graphics decompressor are needed to see this picture. The difference between the instrument’s reported values during repeated measurements of the same quantity. Typically determined by statistical analysis of repeated measurements http://ull.chemistry.uakron. edu/analytical/animations/ Accuracy, precision and standard deviation A measurement can be precise but may not not be accurate The standard deviation (s) is a statistical measure of the precision in a series of repetitive measurements (also often given as with N the number of data, xi is each individual measurement, and X is the mean of all measurements. The value is called the residual for X xi each measurement QuickTime™ and a Graphics decompressor are needed to see this picture. Calibration: standard curve A process of adapting a sensor output to a know physical or chemical quantity to improve sensor output accuracy i.e. remove bias A working or standard curve is obtained by measuring the signal from a series of standards of known concentration. The working curves are then used to determine the concentration of an unknown sample, or to calibrate the linearity of an analytical instrument-for relatively simple solutions What is Next?