Solar-Driven Water Desalination Technology—A Case Study

  • T. Sasilatha*
  • , K. Manikandan
  • , R. Srinivasan
  • , J. Padmapriya
  • , R. Karthickmanoj
  • , S. Priya
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Nowadays solar-driven water desalination technologies are rapidly increasing with the advent of various techniques and methodologies. The best way to improve the performance of the still using solar energy is by storing the latent heat efficiently in the storage system. By selecting suitable combinations of nano material and paraffin wax acts as the NPCM holds the latent heat, improving the thermal performance of the solar still in a very efficient way. Further, the heat transfer to the environment was prevented by the composite material coating consisting of polyurethane foam. The thermal conductivity of NPCM is improved by 57% compared to that of PCM without nanomaterials.

Original languageEnglish
Title of host publicationHuman-Centric Smart Computing - Proceedings of ICHCSC 2022
EditorsSiddhartha Bhattacharyya, Jyoti Sekhar Banerjee, Mario Köppen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages263-271
Number of pages9
ISBN (Print)9789811954023
DOIs
StatePublished - 2023
Externally publishedYes
Event1st International Conference on Human-Centric Smart Computing, ICHCSC 2022 - Virtual, Online
Duration: 27 Apr 202229 Apr 2022

Publication series

NameSmart Innovation, Systems and Technologies
Volume316
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

Conference1st International Conference on Human-Centric Smart Computing, ICHCSC 2022
CityVirtual, Online
Period27/04/2229/04/22

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Keywords

  • Double slope solar still
  • Graphite polyurethane foam
  • Latent heat capacity
  • Nano phase change materials
  • Water desalination

ASJC Scopus subject areas

  • General Decision Sciences
  • General Computer Science

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