Early degradation of high power packaged LEDs under humid conditions and its recovery — Myth of reliability rejuvenation

Singh, Preetpal; Tan, Cher Ming; Chang, Liann‐Be

doi:10.1016/j.microrel.2015.12.036

Cited by 23 publications

(17 citation statements)

References 8 publications

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“…The difference in the degradation observed is due to the much shorter test time for the white LEDs. Finite element analysis of the moisture diffusion into the LED packages as done previously 6 can provide a much clearer explanation as shown in Fig. 2 .…”

Section: Resultsmentioning

confidence: 83%

“…As a result, no significant lumen degradation is observed. On the other hand, for the blue LEDs tested for 336 hours, die attach delamination has already occurred, and that the moisture in the die attach cannot be evaporated during testing 6 , this renders significant lumen degradation as observed. The total amount of moisture in the blue LEDs is 40% more than the white LEDs, and this 40% is all in the die attach material.…”

Section: Resultsmentioning

confidence: 99%

“…LEDs are considered to be the next generation light source due to its several advantages, including its long life 1 2 3 Thus, for practical applications, long life LEDs must be ensured, and many high temperature stress tests are indeed performed by manufacturers for this purpose, with international standards such as TM-21 and LM-80 1 formulated. As high power LEDs are increasingly employed in outdoor environment as well as some other harsher environment than indoor applications, effect of moisture on their reliability cannot be overlooked as its effect can indeed be important as shown by the literatures 4 5 6 7 8 .…”

mentioning

confidence: 99%

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Degradation Physics of High Power LEDs in Outdoor Environment and the Role of Phosphor in the degradation process

Singh

Tan

2016

Sci Rep

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A moisture- electrical – temperature (MET) test is proposed to evaluate the outdoor reliability of high power blue LEDs, with and without phosphor, and to understand the degradation physics of LEDs under the environment of combined humidity, temperature and electrical stresses. The blue LEDs with phosphor will be the high power white LEDs. Scanning acoustic microscopy is used to examine the resulted delamination during this test for the LEDs. The degradation mechanisms of blue LEDs (LEDs without phosphor) and white LEDs (LEDs with phosphor) are found to be different, under both the power on (i.e. with 350 mA through each LED) and power off (i.e. without current supply) conditions. Difference in the coefficient of thermal expansion between the molding part and the lens material as well as the heat generated by the phosphor layer are found to account for the major differences in the degradation mechanisms observed. The findings indicate that the proposed MET test is necessary for the LED industry in evaluating the reliability of LEDs under practical outdoor usage environment.

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Section: Resultsmentioning

confidence: 83%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

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Degradation Physics of High Power LEDs in Outdoor Environment and the Role of Phosphor in the degradation process

Singh

Tan

2016

Sci Rep

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“…Increased lifetime and efficiency led to rapid expansion of LED’s application areas 1 – 5 , but the cost of high power white LED (W-LED) is still on the high side. Hence works are done to increase the lumen flux of W-LEDs so as to reduce the number of LEDs required for a given illumination level, and helps in cost saving.…”

Section: Introductionmentioning

confidence: 99%

“…While these methods can indeed achieve the intended goals, the physical limitations of these methods have not been investigated. Also, the reliability consequences of the abovementioned two methods are not addressed due to several reasons as discussed in literatures 1 , 5 , 25 , 26 . For the case of remote phosphor technology, it has been shown that this method can cause an increase in the phosphor temperature upto 40 °C or in some cases 60 °C due to the lack of effective heat dissipation path, and this leads to rapid discoloration and overall light output degradation 27 , 28 .…”

Section: Introductionmentioning

confidence: 99%

Physical Limitations of Phosphor layer thickness and concentration for White LEDs

Tan

Singh

Zhao

et al. 2018

Sci Rep

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Increasing phosphor layer thickness and concentration can enhance the lumen flux of white LED (W-LED). In this work, we found that increasing the phosphor layer thickness and concentration can increase its temperature, and there is also a maximum thickness and concentration beyond which their increase will not lead to lumen increase, but only temperature increase. Higher thickness and higher concentration also results in warm light instead of White light. The maximum thickness and concentration are found to be limited by the scattering of light rays with higher % decrease of blue light rays than the yellow light rays. The results obtained in this work can also be used to compute the temperature and thermo-mechanical stress distribution of an encapsulated LED, demonstrating its usefulness to the design of encapsulated LED packages. Simulation software like ANSYS and TracePro are used extensively to verify the root cause mechanisms.

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Machine Learning and Digital Twin Driven Diagnostics and Prognostics of Light‐Emitting Diodes

Ibrahim

Fan

Yung

et al. 2020

Laser & Photonics Reviews

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Light-emitting diodes (LEDs) are among the key innovations that have revolutionized the lighting industry, due to their versatility in applications, higher reliability, longer lifetime, and higher efficiency compared with other light sources. The demand for increased lifetime and higher reliability has attracted a significant number of research studies on the prognostics and lifetime estimation of LEDs, ranging from the traditional failure data analysis to the latest degradation modeling and machine learning based approaches over the past couple of years. However, there is a lack of reviews that systematically address the currently evolving machine learning algorithms and methods for fault detection, diagnostics, and lifetime prediction of LEDs. To address those deficiencies, a review on the diagnostic and prognostic methods and algorithms based on machine learning that helps to improve system performance, reliability, and lifetime assessment of LEDs is provided. The fundamental principles, pros and cons of methods including artificial neural networks, principal component analysis, hidden Markov models, support vector machines, and Bayesian networks are presented. Finally, discussion on the prospects of the machine learning implementation from LED packages, components to system level reliability analysis, potential challenges and opportunities, and the future digital twin technology for LEDs lifetime analysis is provided.

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Early degradation of high power packaged LEDs under humid conditions and its recovery — Myth of reliability rejuvenation

Cited by 23 publications

References 8 publications

Degradation Physics of High Power LEDs in Outdoor Environment and the Role of Phosphor in the degradation process

Degradation Physics of High Power LEDs in Outdoor Environment and the Role of Phosphor in the degradation process

Physical Limitations of Phosphor layer thickness and concentration for White LEDs

Machine Learning and Digital Twin Driven Diagnostics and Prognostics of Light‐Emitting Diodes

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