The DOI matches its Crossref record; 133 of the 133 references it cites were found in a registry or an index.
Sonochemistry: Science and Engineering
Open accessAbstract
Sonochemistry offers a simple route to nanomaterial synthesis with the application of ultrasound. The tiny acoustic bubbles, produced by the propagating sound wave, enclose an incredible facility where matter interact among at energy as high as 13 eV to spark extraordinary chemical reactions. Within each period - formation, growth and collapse of bubbles, lies a coherent phase of material formation. This effective yet highly localized method has facilitated synthesis of various chemical and biological compounds featuring unique morphology and intrinsic property. The benign processing lends to synthesis without any discrimination towards a certain group of material, or the substrates where they are grown. As a result, new and improved applications have evolved to reach out various field of science and technology and helped engineer new and better devices. Along with the facile processing and notes on the essence of sonochemistry, in this comprehensive review, we discuss the individual and mutual effect of important input parameters on the nanomaterial synthesis process as a start to help understand the underlying mechanism. Secondly, an objective discussion of the diversely synthesized nanomaterial follows to divulge the easiness imparted by sonochemistry, which finally blends into the discussion of their applications and outreach.
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Metadata
- Authors
- Pokhrel, N., Vabbina, P. K., & Pala, N.
- Venue
- Ultrasonics Sonochemistry
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 29
- Pages
- 104-128
- ISSN
- 1350-4177 (ISSN-L)
- OpenAlex
- W1442220550
- Cited by
- 397
- References
- 133
- FWCI
- 9.06
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Pokhrel, N., Vabbina, P. K., & Pala, N. (2016). Sonochemistry: Science and Engineering. Ultrasonics Sonochemistry. https://doi.org/10.1016/j.ultsonch.2015.07.023
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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.