Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

book chapter · Review of Progress in Quantitative Nondestructive Evaluation · 1996

Materials Characterization by a Time-Resolved and Polarization-Sensitive Ultrasonic Technique

D. Xiang, N. N. Hsu, G. V. Blessing

Cited by 14Abstract and details only

Abstract

The index has no abstract for this paper. The publisher’s page may have one.

Cite this paper

APA 7

Xiang, D., Hsu, N. N., & Blessing, G. V. (1996). Materials Characterization by a Time-Resolved and Polarization-Sensitive Ultrasonic Technique. Review of Progress in Quantitative Nondestructive Evaluation, 1431–1438. https://doi.org/10.1007/978-1-4613-0383-1_187

MLA 9

Xiang, D., et al. “Materials Characterization by a Time-Resolved and Polarization-Sensitive Ultrasonic Technique.” Review of Progress in Quantitative Nondestructive Evaluation, 1996, pp. 1431–38, https://doi.org/10.1007/978-1-4613-0383-1_187.

Chicago

Xiang, D., N. N. Hsu, and G. V. Blessing. 1996. “Materials Characterization by a Time-Resolved and Polarization-Sensitive Ultrasonic Technique.” Review of Progress in Quantitative Nondestructive Evaluation: 1431–38. https://doi.org/10.1007/978-1-4613-0383-1_187.

Harvard

Xiang, D., Hsu, N.N. and Blessing, G.V. (1996) ‘Materials Characterization by a Time-Resolved and Polarization-Sensitive Ultrasonic Technique’, Review of Progress in Quantitative Nondestructive Evaluation, pp. 1431–1438. Available at: https://doi.org/10.1007/978-1-4613-0383-1_187.

BibTeX
@incollection{xiang1996materials,
  title = {{Materials Characterization by a Time-Resolved and Polarization-Sensitive Ultrasonic Technique}},
  author = {Xiang, D. and Hsu, N. N. and Blessing, G. V.},
  booktitle = {Review of Progress in Quantitative Nondestructive Evaluation},
  pages = {1431--1438},
  year = {1996},
  doi = {10.1007/978-1-4613-0383-1_187}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers