BS EN ISO 21363:2022
$215.11
Nanotechnologies. Measurements of particle size and shape distributions by transmission electron microscopy
Published By | Publication Date | Number of Pages |
BSI | 2022 | 94 |
PDF Catalog
PDF Pages | PDF Title |
---|---|
2 | undefined |
5 | European foreword Endorsement notice |
9 | Foreword |
10 | Introduction |
11 | 1 Scope 2 Normative references 3 Terms, definitions and symbols 3.1 Core terms — Particles |
14 | 3.2 Core terms — Image capture and analysis |
15 | 3.3 Core terms — Statistical symbols and definitions |
17 | 3.4 Core terms — Measurands |
20 | 3.5 Core terms — Metrology |
23 | 3.6 Core terms — Transmission electron microscopy |
24 | 3.7 Statistical symbols, measurands and descriptors 3.7.1 Statistical symbols 3.7.2 Measurands and descriptors |
25 | 4 Stakeholder needs for TEM measurement procedures |
26 | 5 Sample preparation 5.1 General |
27 | 5.2 Sample sources 5.3 Use a representative sample 5.3.1 General 5.3.2 Powder samples 5.3.3 Nanoparticle dispersions in liquids |
28 | 5.4 Minimize particle agglomeration in the sample dispersion 5.5 Selection of the mounting support 6 Instrument factors 6.1 Instrument set-up |
29 | 6.2 Calibration 6.2.1 General 6.2.2 Calibration standards 6.2.3 General calibration procedure |
31 | 6.3 Setting TEM operating conditions for calibration |
32 | 7 Image capture 7.1 General 7.2 Setting a suitable operating magnification |
33 | 7.3 Minimum particle area 7.4 Number of particles to count for particle size and shape distributions |
34 | 7.5 Uniform background 7.6 Measurement procedure 7.6.1 General |
35 | 7.6.2 Developing a test sample 7.6.3 Effects of magnification 7.6.4 Frames (micrographs) 7.7 Revision of image capture protocols 8 Particle analysis 8.1 General 8.2 Individual particle analysis |
36 | 8.3 Automated particle analysis 8.4 Example — Automated particle analysis procedure |
37 | 9 Data analysis 9.1 General 9.2 Raw data triage — Detecting touching particles, unselected particles, artefacts and contaminants |
38 | 9.3 Data quality assessment — Repeatability, intermediate precision and reproducibility |
40 | 9.4 Fitting distributions to data |
41 | 9.5 Assessing measurement uncertainty for samples under repeatability, intermediate precision or reproducibility conditions 9.5.1 Grand statistics for fitted parameters — Three or more datasets 9.5.2 Measurement uncertainty of fitted parameters |
42 | 9.5.3 Example — Measurement uncertainty for a size descriptor 9.6 Bivariate analysis |
43 | 10 Reporting |
46 | Annex A (informative) Case studies overview |
48 | Annex B (informative) Discrete spheroidal nanoparticles |
51 | Annex C (informative) Size mixture |
63 | Annex D (informative) Shape mixture |
68 | Annex E (informative) Amorphous aggregates |
72 | Annex F (informative) Nanocrystalline aggregates |
76 | Annex G (informative) Nanofibres with irregular cross-sections |
83 | Annex H (informative) Nanoparticles with specific crystal habits |
90 | Bibliography |