| AN52
Picosecond Time Analyzer Applications |
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This
note explains the concepts of Multiple-Stop Time Spectrometry and the
capabilities of the ORTEC model 9308 Picosecond Time
Analyzer. The note describes how to use the instrument with stochastic
input signals, such as those generated in Time-of-Flight Mass
Spectrometry, as well as from LIDAR/DIAL and
Fluorescence/Phosphorescence Lifetime Spectrometry. Advice is given on
how to obtain optimum data acquisition in such applications, while the
use of the Picosecond Time Analyzer for analyzing periodic signal
analysis is also described. |
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| AN53
Diving Deep into Single-Ion Counting with FASTFLIGHT®
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According
to common knowledge in Time-of-Flight mass spectrometry, the
correlated noise in a digital signal averager sets the detection
limits for peaks exhibiting exceptionally-low ion rates. Normally,
that would cause one to choose a time digitizer to optimize
detection limits at low ion rates. This note describes how a trivial
adjustment of the Vertical Offset control allows FASTFLIGHT to
duplicate the detection limits of a time digitizer at low ion rates. |
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| AN54
Triggering MALDI Time-of-Flight Mass Spectrometers with the FASTFLIGHT®
Digital Signal Averager |
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Although
the FASTFLIGHT Digital Signal Averager is optimized
for handling the ultra-high data rates encountered when an
Electrospray Time-of-Flight Mass Spectrometer (ES TOF-MS) analyzes
the output of a chromatograph, FASTFLIGHT can also
enable higher data acquisition rates with most modern MALDI
Time-of-Flight Mass Spectrometers (MALDI TOF-MS). This note
describes how to configure such systems. |
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| AN57
Dealing with Dead Time Distortion in a Time Digitizer |
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This
note examines the dead time distortions inherent with time
digitizers when used to record high event rates. It includes a
practical scheme for making dead time corrections to the time
spectrum after the spectrum has been acquired. The principles are
elucidated by the typical application in Time-of-Flight Mass
Spectrometry |
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| AN58
How Histogramming and Counting Statistics Affect Peak Position
Precision |
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This
note discusses how the quantization inherent in presenting spectra
as histograms affects the precision with which the position of a
peak in the spectrum can be determined. This is particularly
relevant when stochastic events are being counted for the vertical
scale in the spectrum, such as Time Digitizers used for
Time-of-Flight Mass Spectrometry |
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| AN59
How Counting Statistics Controls Detection Limits and Peak
Precision |
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This
note examines the contribution of counting statistics to the
uncertainty in determining spectral peak areas, and in controlling
detection limits, in situations when counting statistics limit the
event measurement precision. A typical case where this applies is
the use of Time Digitizers in Time-of-Flight Mass Spectrometry. |
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| AN
61 How Counting Statistics and the ADC Sampling Interval
Control Mass Accuracy in Time-of-Flight Mass Spectrometry |
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Compared
to a Time-to-Digital Converter, a Digital Signal Averager enables
several orders of magnitude higher ion rates to be processed in a
time-of-flight mass spectrometer. A Time-to-Digital Converter is
limited by a ceiling on the acceptable ion rate, because it can
respond only to single-ion pulses. A Digital Signal Averager, on
the other hand, can respond linearly to any number of ions in each
pulse, because it employs an ADC to sample the signal. This
difference in performance is important, because mass accuracy,
isotope ratio accuracy, and detection limits are inversely
proportional to the square root of the number of ions counted in a
peak. More ions yield better accuracy and lower detection limits.
This application note develops the formulae defining the
dependence of mass accuracy and peak area uncertainty on a) ion
counting statistics and b) the sampling interval of the ADC in the
Digital Signal Averager.
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| AN
62 Suppressing Noise in TOF-MS with FASTFLIGHT-2
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This
application note describes the sources of noise that determine
mass accuracy and detection limits in Time-of-Flight Mass
Spectrometry, when employing a digital signal averager for data
acquisition. Techniques are described for reducing both the random
and correlated noise contributions to achieve better mass accuracy
and lower detection limits. The discussions of random and
correlated noise are relevant to several other signal-processing
applications. |
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