The DOI matches its Crossref record.
Latent Heat Storage Materials and Systems: A Review
Abstract
The use of a latent heat storage system using Phase Change Materials (PCM) is an effective way of storing thermal energy (solar energy, off-peak electricity, industrial waste heat) and has the advantages of high storage density and the isothermal nature of the storage process. It has been demonstrated that, for the development of a latent heat storage system, choice of the PCM plays an important role in addition to heat transfer mechanism. The information on the latent heat storage materials and systems is enormous and published widely in the literatures. In this paper, we make an effort to gather the information from the previous works on PCMs and latent heat storage systems. This review will help to find a suitable PCM for various pur-poses a suitable heat exchanger with ways to enhance the heat transfer, and it will also help to provide a variety of designs to store the heat using PCMs for different applications, i.e. space heating & cooling, solar cooking, greenhouses, solar water heating and waste heat recovery systems. Measurement techniques of thermophysical properties, studies on thermal cycles for long term stability, corrosion of the PCMs and enhancement of heat transfer in PCM are dis-cussed. New PCM innovations are also included for the awareness of new applications. This paper contains a list of about 250 PCMs and more than 250 references.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Energy storage technologies and real life applications – A state of the art review
Aneke, M., & Wang, M. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.06.097 · Cited by 1,754
Chieruzzi, M., Cerritelli, G. F., Miliozzi, A., & Kenny, J. M. (2013) · Nanoscale Research Letters · doi:10.1186/1556-276x-8-448 · Cited by 381
Chieruzzi, M., Miliozzi, A., Crescenzi, T., Torre, L., & Kenny, J. M. (2015) · Nanoscale Research Letters · doi:10.1186/s11671-015-0984-2 · Cited by 154
Energy and exergy performance assessments for latent heat thermal energy storage systems
Li, G. (2015) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.06.052 · Cited by 147
Metadata
- Authors
- Sharma, S. D., & Sagara, K.
- Venue
- International Journal of Green Energy
- Publisher
- Informa UK Limited
- Published
- 2005-01-01
- Volume
- 2
- Issue
- 1
- Pages
- 1-56
- ISSN
- 1543-5075 (ISSN-L)
- 1543-5083
- OpenAlex
- W2163755005
- Cited by
- 714
- References
- 0
- FWCI
- 16.75
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
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.