Glancing angle deposition of nanostructured ZnO films for ultrasonics

Manuel Pelayo Garcia, Kevin Luke McAughey, Des Gibson, David Allan Hughes, Carlos García Núñez

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Ultrasonic sensors have demonstrated great potential for non-destructive testing (NDT) of materials, being widely applicable in health care/monitoring (e.g. biomedical, muscle recovery, cancer early detection), industry, and defence (e.g. proximity sensors used in unnamed aerial vehicles - UAV; detection of submarines). Most conventional ultrasonic sensors are based on monolithic piezoelectric ceramic materials (e.g. PZT, PbTiO 3 or PMN-PT) which are too bulky and nonconforming to enable their integration on flexible substrates. To address these drawbacks, ZnO thin films have emerged as an alternative piezoelectric material for low profile and high-frequency ultrasonic transducers due to properties such as high piezoelectric coefficient, great tuneability of working frequency, large bandwidth, low-cost of materials and manufacturing, compatibility with flexible substrates, and biocompatibility. This work analyses glancing angle deposition (GLAD) of ZnO thin films at different reactive sputtering conditions optimised to meet dual requirements of highly crystalline c-axis orientation while controlling the inclined angle of resulting nanostructured films for their application as piezoelectric material in ultrasonic sensors. Characteristics of ZnO nanostructured films, including morphology, crystallinity, and composition, are analysed as a function of GLAD conditions (gas flux angle with respect the substrate surface (α) and plasma conditions (plasma power, substrate position, substrate temperature, total gas-flow, and processing/reactive gas ratio). The obtained piezoelectric values for β angles of α=88° present d33 values of 33.1±1.7 pm/V, surpassing the piezoelectric coefficient found in ZnO bulk 12.4 pm/V. The influence of film titled angle (β) on piezoelectric performance for ultrasound sensing applications will be studied.
Original languageEnglish
Title of host publicationApplication of deep learning method in web crippling strength prediction
Subtitle of host publicationSevilla, Spain 9-11 June 2021
Place of PublicationPiscataway, NJ
ISBN (Electronic)9781665444521
Publication statusPublished - 25 Jun 2021

Publication series

NameIEEE Conference Proceedings
ISSN (Print)2163-4971
ISSN (Electronic)2643-1300


  • glancing angle deposition
  • reactive sputtering
  • zinc oxide
  • piezoelectric sensor
  • ultrasounds


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