# FIU CHM 4130 - Key_for Chapters 1 and 5 (4 pages)

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## Key_for Chapters 1 and 5

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- Pages:
- 4
- School:
- Florida International University
- Course:
- Chm 4130 - Instrumental Analysis

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CHAPTER 1 Key 1 A transducer is a device that converts chemical or physical information into an electrical signal or the reverse The most common input transducers convert chemical or physical information into a current voltage or charge and the most common output transducers convert electrical signals into some numerical form 3 The detector in a spectrograph is a photographic film or plate 5 A data domain is one of the modes in which data may be encoded Examples of data domain classes are the analog digital and time domains Examples of data domains are voltage current charge frequency period number 7 0 1 2 1 3 4 5 Output Transducer Use 6 78 961 LCD display Alphanumeric information Computer monitor Alphanumeric information text graphics 85 u 8 0 u 8 AB C D E8 u C Laser printercx B8EF 8 0 G 8 0 H Alphanumeric and graphical information F 85 u 8 0 H Motor Rotates to change position of attached elements I 8 J6 1 6 K 6 17 6 L K8 10 a Slope m 0 0701 intercept b 0 0083 F1H M 4 m D 8 B 4 4 b D 8 A FLH N 0 OPMJ 4 MQ 4 sm D 8 B4 MQ 4 sb D 8 F H E R 9 m m r t m K6 t 6 M 7 t S1 E R L1L 3 1 7 N 1 b c d From LINEST results SD slope sm 0 0007 SD intercept sb 0 0040 95 CI for slope m is m tsm where t is the Student t value for 95 probability and N 1 5 degrees of freedom 2 57 95 CI for m 0 0701 2 57 0 0007 0 0701 0 0018 or 0 070 0 002 For intercept 95 CI b tsb 0 0083 2 57 0 004 0 0083 0 010 or 0 08 0 01 cu 4 87 0 086 mM or 4 87 0 09 mM 2 c Thermal andshot noise 5 3 103 to 105 Hz and 106 to 107 Hz Enviromental noise is at a minimum in these regions see Figure 5 3 5 4 At the high CHAPTER 5 impedance Key of a glass electrode shielding is vital to minimize induced currents from power lines which can be amplified and can disturb the output 1 Frequency dependent noise sources flicker and environmental noise Frequency independent sources thermal and shot 5 5 a High pass filters are used to remove lownoise frequency flicker noise from higher 2 a Thermal noise frequency analytical signals b Certain types of environmental noise c Thermal and shotfilters noise are used to remove high frequency noise from dc analytical signals b Low pass 4 6 At the high impedance of a glass electrode shielding is vital to minimize induced 5 6 We estimate the maximum and theminimum in the recorded signal 0 9 u 10 15 A to be currents from power lines which can be amplified and can disturb the output 1 5 u 10 15 and 0 4 u 10 15 A The standard deviation of the signal is estimated to be oneWe estimate the maximum and the minimum in the recorded signal 0 9 10 15 A to be 1 5 10 15 and 0 4 10 15 A The standard deviation of the signal is estimated to 15 fifth of the difference or 0 22 u 10 15 Thus be onefifth of the difference or 0 22 10A A Thus S N 0 9 u 10 15 A 0 22 u 10 15 A 4 Principles of Instrumental Analysis 6th ed 5 7 a Chapter 5 7 a 1 Hence S N 358 for these 9 measurements b Hence S N 358 for these 9 measurements S N b 358 Sn Nn n Sn 9 Nn Equation 5 11 For the nine measurements 3 Hence S N 358 for these 9 measurements b S N Sn Nn Equation 5 11 For the nine measurements n Sn 9 Nn 358 For the S N to be 500 requires nx measurements That is Sn Nn 500 nx Principles of Instrumental Analysis 6th ed Chapter 5 Dividing thespectrum secondS N equation by the gives rearranging 200 squaring 14 1 overand the top spectrum The bottom is improved byfirst a factor of after 2 The bottom is the result of 200 50 4 times as many scans so the S N should be 500 spectrum nx u 3 358 17 6 improved by a factor of or 18 measurements 4 2 over the middle spectrum 2 5 12 The magnitudes thea signals therequires noise in the in Figure 5 15 may be 10 To increase the S Nofby factor and of 10 10spectra 2 more measurements So n 100 estimated directly from the plots The results from our estimates are given in the table 12 The magnitudes of the signals and the noise in the spectra in Figure 5 15 may be estimated from the plots The results ourflat estimates in the below directly Baselines for spectra A and D are taken from from the retions onare thegiven right side of table below Baselines for spectra A and D are taken from the flat retions on the right side thefigure figure Noise Noise is from one fifth of theofpeak to peak excursions of the of the of the is calculated calculated from one fifth the peak to peak excursions signal signal Spectrum A Spectrum D Spectrum A Spectrum D A255 0 550 1 125 S255 0 549 0 525 S425 0 579 0 550 A425 0 580 1 150 Ab peak 0 080 0 620 N Ab peak Ab valley 5 0 0324 0 0078 Ab valley 0 082 0 581 Ab mean 0 001 0 600 S N 255 17 67 S N 425 18 70 Note that the difference in S N for the two peaks is due only to the difference in the peak Note that the difference in S N for the two peaks is due only to the difference in the heights peak heights at 255 D 67 17 S N A 3 9 S N A at 425 nm S N D 79 18 S N A So So at 255 nm nm S N S N D 67 17 S N A 3 9 S N A at 425 nm S N D 79 18 S N A 3 9 S N A 3 9 S N A 4

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