128
Views
1
CrossRef citations to date
0
Altmetric
Electronic Engineering

Selection of scattering enhancement particles for improving color homogeneity and luminous flux of phosphor-converted LEDs

, &
Pages 307-312 | Received 24 Sep 2016, Accepted 28 Mar 2017, Published online: 23 Apr 2017
 

Abstract

At the present time, color homogeneity and luminous flux are the two essentials utilized to appraise high-quality phosphor-converted LEDs (pcLEDs). In this paper, we present the search for the optimal selection among scattering enhancement particles (SEPs) to apply to improve these essentials for pcLEDs having correlated color temperature of 8500 K. The interested contenders include CaCO3, CaF2, SiO2, and TiO2. Each of them is added to yellow phosphor compounding (Y3Al5O12:Ce3+). Firstly, the LightTools program is employed to do the optical simulations. Secondly, the obtained results are verified and analyzed based on Mie scattering theory. The scattering computation of SEPs includes the scattering coefficients, the anisotropic scattering, the reduced scattering and the scattering amplitudes at 455 and 595 nm. It is observed that TiO2 particles provide the highest color homogeneity among the SEPs but the luminous flux reduces significantly as its concentration increases. By using CaCO3 particles, the highest luminous flux of 792 lm is obtained. CaCO3 particles can also reduce the deviation of color correlated temperature to 620 K at 30% concentration. Therefore, CaCO3 particles should be selected to enhance both color homogeneity and luminous flux.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 199.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.