Chem. 133 – 2/16 Lecture.

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Presentation transcript:

Chem. 133 – 2/16 Lecture

Announcements HW1.2 problems due Quiz 2 today Today’s Lecture Noise

Signal Averaging If the noise is random and well known, repeat measurements improve S/N because signal is additive while noise adds as (n)0.5 (based on propagation of uncertainty rules) Note: in some cases, averaging can affect qualitative information as well as quantitative information (e.g. mass spectrometer measured mass) (S/N)n = [(S/N)n=1]n/(n)0.5 = [(S/N)n=1](n)0.5

Signal Averaging - Question A 1H NMR is performed on a small amount of sample expected to be the compound at right: With 16 scans the S/N observed for the c 1H peak is 17. How many scans are needed so that the minimum peak has a S/N of 3? (Assume all peaks have the same width) b c a

Signal Averaging Another Example In mass spectrometry, and in particular with time-of-flight mass spectrometers, mass measurement is measured on many ions Instrument resolution is good, but insufficient for high resolution on single measurements (resolution of 15,000 gives s ~ 0.1 amu for 1344 peak) To meet “accurate mass” requirement, errors less than 5 ppm (0.007 amu) are required. 2s ~ 0.2 amu x axis is mass A single measurement will never meet high resolution requirement, but averaging will result in an improved average value (mean mass). For n > 50, 95% CI becomes mean + 1.96s/(n)0.5 or to reach 0.007 amu, would require roughly 784 “counts” or individual measurements

Noise Sources – Fundamental Types Thermal Noise = Johnson Noise (voltage associated) - where: kB = Boltzmann’s constant, T = temp. (K), R = resistance (W), and B = bandwidth (Hz) = range of frequencies accepted - Solutions: cool devices, use lower R values, reduce bandwidth B. Shot noise (current associated) - Solutions: reduce bandwidth, use internally amplified transducers where q= fundamental charge = 1.6 x 10-19 C and I = current

Noise Sources – Other Types Flicker Noise (or 1/f noise or pink noise) Occurs at low frequencies Can result from environmental changes (e.g. change in light intensity over time, change in temperature) Can be reduced through modulating source

Noise Flicker Noise Example Example of equipment for noise reduction chopper (alternatively reflects light or lets light through) sample cell light detector high pass filter rectifier blank cell lamp To Digitizer mirrors 8

Noise Flicker Noise Example: Signals RC Filter + diode RC Filter only light detector signal Signal following digital filtration low f noise removed slow increase in noise over 1st ~100 s 9

Noise Sources – Other Types B. Interference Noise originating from other electrical signals (especially ones that use more power) Examples: 60 Hz from power lines, spikes from solenoids, turning heaters on/off Solution to problems: 1) use shielded cables, 2) shield major power sources, 3) use differential amplifiers

Noise Processing to Reduce Both analog and digital means can be used to reduce noise Band width reduction can reduce noise Low pass filters (e.g. RC filters) reduce high frequency noise but lose high frequency signals Similar methods (e.g. moving averages) for removing high frequency noise can easily be done on digital data A separate way to reduce noise is to signal average (e.g. collection and averaging spectra), provided experiment can be replicated closely

Noise Processing to Reduce Example of moving average (0.5, 2, 10, and 30 s) to remove high frequency noise Raw + 2 s data Raw + 30 s data Clearly over filtered (resolution lost by broadening) Raw Data (collected at 10 Hz) Definite reduction of noise observed Raw + 0.5 s data 5 0.1 s points averaged to make 0.5 s point Only slight reduction of noise observed Raw + 10 s data Even more noise reduction observed, but peak starting to broaden and flatten

Peak Width at half height Noise HPLC Example Type Noise Baseline Signal Baseline corrected signal S/N Peak Width at half height Unfiltered 0.002891 0.999447 1.0519 0.052470125 18 0.202 0.5 s MA 0.002166 0.999461 1.0489 0.049437891 23 2 s MA 0.001232 0.99946 1.0458 0.046335795 38 0.2282 10 s MA 0.000535 0.999457 1.0414 0.041971743 79 0.255 30s MA 0.00047 0.999512 1.0221 0.022616734 48 0.507 Best S/N with 10 s filter Minimal increase in peak width until 2 s

Noise Questions What type of noise is likely to be present when using thermocouples to measure temperature? Why is modulation normally required to reduce 1/f noise? What is the percent noise on a current producing transducer which generates signal over a 1000 Hz band if the signal is 10 nA? if the signal is 2.0 pA? What specific type of noise is reduced best by shielding electronics? How would use of a low pass filter reduce shot noise? Suggest one method for reducing thermal noise. What type of noise is not effectively reduced by using a low pass filter?

Electronics Additional Questions Answer the questions 1-3 from the following plots which were obtained from background measurements (instrument noise): Which plot is most likely shows 1/f noise: ______________________ Which plot when Fourier transformed will produce a plot with a peak at 55 Hz: ______________ If plot c) shows noise from a GC signal in which peaks typically are on the order of 2 s (2000 ms) wide, what can be done to reduce the noise? a) b) c)