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Toward Rapid, “Green”, Predictable Microwave-Assisted Synthesis
Abstract
Continuous and batch microwave reactors were constructed for efficient, "green" synthesis with low-boiling solvents at high temperature in closed vessels. Capabilities for rapid heating and cooling, concurrent heating and cooling, and differential heating facilitated novel chemical reactions and processes. Commercial microwave systems based on these developments are available. Times required for conventional reactions typically are decreased by 2-3 orders of magnitude. Green processes also have resulted through use of less or no catalyst, readily recyclable solvents, or media and yields that are often higher than normal. Complementary interactive software for calculating optimal conditions was developed.
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Citations
Cited by
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Müller, T. E., Hultzsch, K. C., Yus, M., Foubelo, F., & Tada, M. (2008) · Chemical Reviews · doi:10.1021/cr0306788 · Cited by 2,090
Supported gold nanoparticles as catalysts for organic reactions
Corma, A., & Garcia, H. (2008) · Chemical Society Reviews · doi:10.1039/b707314n · Cited by 1,883
Sub-nanometre sized metal clusters: from synthetic challenges to the unique property discoveries
Lu, Y., & Chen, W. (2012) · Chemical Society Reviews · doi:10.1039/c2cs15325d · Cited by 1,152
Assessing the greenness of some typical laboratory ionic liquid preparations
Deetlefs, M., & Seddon, K. R. (2010) · Green Chem. · doi:10.1039/b915049h · Cited by 280
Metadata
- Authors
- Roberts, B. A., & Strauss, C. R.
- Venue
- Accounts of Chemical Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2005-05-19
- Volume
- 38
- Issue
- 8
- Pages
- 653-661
- ISSN
- 0001-4842 (ISSN-L)
- 1520-4898
- OpenAlex
- W2135049180
- Cited by
- 430
- References
- 0
- FWCI
- 16.27
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
