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Effective Thickness of Bulk Materials and of Thin Films for Internal Reflection Spectroscopy
Abstract
In internal reflection spectroscopy effective thickness is defined as the thickness of material required to give a spectrum of the same contrast in a transmission measurement as that obtained via internal reflection. Simple expressions for effective thickness are given for bulk materials and for thin films which are useful as guide lines in determining the optimum conditions required to record internal reflection spectra. Depending on angle of incidence and index of refraction, the effective thickness for bulk materials may be much greater or much less than the wavelength of light. Similarly for thin films the effective thickness may be much greater or much less than the actual thickness.
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Citations
Cited by
Hansen, W. N. (1968) · Journal of the Optical Society of America · doi:10.1364/josa.58.000380 · Cited by 729
Corujo, M. P., Sklepari, M., Ang, D. L., Millichip, M., Reason, A., Goodchild, S. C., Wormell, P., Amarasinghe, D. P., Lindo, V., Chmel, N. P., et al. (2018) · Chirality · doi:10.1002/chir.23002 · Cited by 23
Metadata
- Authors
- Harrick, N. J., & du Pré, F. K.
- Venue
- Applied Optics
- Publisher
- Optica Publishing Group
- Published
- 1966-11-01
- Volume
- 5
- Issue
- 11
- Pages
- 1739
- ISSN
- 0003-6935 (ISSN-L)
- 1539-4522
- OpenAlex
- W2045840044
- Cited by
- 169
- References
- 0
- FWCI
- 2.81
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Effective Thickness of Bulk Materials and of Thin Films for Internal Reflection Spectroscopy. https://app.cochat.ai/papers/10.1364/ao.5.001739
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- Harrick, N. J., & du Pré, F. K. (1966). Effective Thickness of Bulk Materials and of Thin Films for Internal Reflection Spectroscopy. Applied Optics. https://doi.org/10.1364/ao.5.001739
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
