P
Perapong Tekasakul
Researcher at Prince of Songkla University
Publications - 79
Citations - 1697
Perapong Tekasakul is an academic researcher from Prince of Songkla University. The author has contributed to research in topics: Natural rubber & Aerosol. The author has an hindex of 20, co-authored 72 publications receiving 1234 citations. Previous affiliations of Perapong Tekasakul include University of Missouri & Thammasat University.
Papers
More filters
Journal ArticleDOI
Natural dyes for dye sensitized solar cell: A review
TL;DR: In this article, a review discusses development of natural dyes and their effect on various performance parameters of dye-sensitized solar cell and discusses their application in the field of this technology.
Environmental Problems Related to Natural Rubber Production in Thailand
TL;DR: In this paper, environmental problems and existing control techniques in each rubber production are reviewed and appropriate technologies are needed in dealing with both smoke particles and wastewater problems in rubber sheet drying industry.
Journal ArticleDOI
Applications of software in solar drying systems: A review
TL;DR: This comprehensive review of the various software applications in different solar drying systems is useful for academician, scientist and researchers.
Journal ArticleDOI
Mathematical modeling and performance investigation of mixed-mode and indirect solar dryers for natural rubber sheet drying
TL;DR: In this paper, performances of mixed-mode and indirect solar drying systems have been investigated for 30 natural rubber sheets, and the mixedmode dyer is 15.4% which is higher than the indirect solar dryer (13.3%).
Journal ArticleDOI
Inertial Classification of Nanoparticles with Fibrous Filters
TL;DR: In this article, a new concept for the utilization of fibrous filters for the classification of nanoparticles was proposed and confirmed that the filter employed in the present work can separate particles smaller than 100 nm, and the main conclusions obtained in this paper are as follows: (1) Inertial filter utilizes inertial impaction of particles and the classification performance can be predicted by the log penetration law and the single fiber collection efficiency, (2) 50% cutoff size is reduced by increasing the filtration velocity and is predicted by Stk50 = 1, (3) In