Phosphor Material Produces White LEDs with Better Color Quality

Using computational tools and data mining, researchers have discovered a new type of phosphor material for white LEDs that is not only inexpensive but also easy to fabricate. Headed by engineers at the University of California San Diego, the researchers used the new phosphor material to build prototype white LED light bulbs which displayed better color quality than many LEDs commercially available on the market today.

The team published the results of the new phosphor on February 19 in the journal, Joule.

Phosphors are substances that produce light. They are one of the main ingredients used for making white LEDs. Phosphors are crystalline powders that are capable of absorbing energy from near-UV or blue light and emitting light in the visible spectrum. White light is produced through the combination of the different colored light.

However, several disadvantages are associated with the phosphors utilized in many commercially available white LEDs. Most of these phosphors are made of rare-earth elements, which are very costly, and some are also difficult to manufacture. They even create LEDs with poor color quality.

A research team at Chonnam National University in Korea and UC San Diego has created a new type of phosphor that prevents all these problems. This phosphor is mostly made of earth-abundant elements such as aluminum, oxygen, strontium, and lithium; it can be produced using industrial techniques, and it can produce LEDs that make colors more vivid and accurate.

A systematic, high-throughput computational method was used to discover the new phosphor, Sr₂LiAlO₄, or simply known as SLAO. This method was developed in the laboratory of Shyue Ping Ong, lead principal investigator of the study and a nanoengineering professor at the UC San Diego Jacobs School of Engineering.

Using supercomputers, Ong’s team predicted SLAO – the first known material made of lithium, strontium, oxygen, and aluminum elements. Based on calculations, it was predicted that this material would be stable and would also perform well as an LED phosphor. For instance, it was predicted that the material would absorb light in the blue and near-UV region and also have high photoluminescence, which is the ability of the material to produce light when activated by a light source of higher energy.

Scientists in the lab of Joanna McKittrick, a materials science professor at the Jacobs School of Engineering, eventually came up with the recipe required to make the novel phosphor material. The team also proved the predicted light absorption and emission properties of the phosphor in the laboratory.

A research team, headed by materials science professor Won Bin Im at Chonnam National University in Korea, improved the phosphor recipe for industrial manufacturing and developed prototypes of white LED using the new phosphor material. The researchers assessed LEDs by using the Color Rendering Index (CRI) – a scale that rates from 0 to 100 on how accurate the colors are under a light source. The majority of commercially available LEDs possess CRI values at around 80. However, CRI values greater than 90 were yielded by LEDs developed with the new phosphor material.

The Computational Quest for a New Material

The discovery of phosphor took only three months, thanks to the computational method developed by Ong’s team. This is indeed a short time frame when compared to decades of trial-and-error experiments it usually takes to find a novel material.

Calculations are quick, scalable and cheap. Using computers, we can rapidly screen thousands of materials and predict candidates for new materials that have not yet been discovered.

Shyue Ping Ong

Ong, who heads the Materials Virtual Lab and is a faculty member in the Sustainable Power and Energy Center at UC San Diego, utilizes high-throughput calculations along with machine learning to discover futuristic materials for energy applications, such as LEDs, fuel cells, and batteries. The calculations were carried out using the National Science Foundation’s Extreme Science and Engineering Discovery Environment at the San Diego Supercomputer Center.

In this analysis, Ong’s research team first collected a list of elements that occur most often in known phosphor materials. Surprisingly, the researchers did not find any known materials that contain a combination of lithium, strontium, oxygen, and aluminum, which are four standard phosphor elements. They then used a data mining algorithm to produce new phosphor candidates that contain all these four elements and carried out a set of first-principles calculations to estimate which would perform exceedingly well as a phosphor. Among the 918 candidates, SLAO was identified as the top material. This material was predicted to be stable and show remarkable photoluminescence properties.

“It’s not only remarkable that we were able to predict a new phosphor compound, but one that’s stable and can actually be synthesized in the lab,” said Zhenbin Wang, co-first author of the study and a nanoengineering Ph.D. candidate in Ong’s research group.

The main limitation of phosphor is its less than ideal quantum efficiency i.e., how efficiently it changes the incoming light to a different colored light—of about 32%. Yet, the team notes that the phosphor retains over 88% of its emission at usual LED operating temperatures. In the case of commercially available LEDs, there is often a tradeoff with color quality, Ong noted. “But we want the best of both worlds. We have achieved excellent color quality. Now we are working on optimizing the material to improve quantum efficiency,” Ong said.

Paper title: “Mining Unexplored Chemistries for Phosphors for High-Color-Quality White-Light-Emitting Diodes.” Study authors are Zhenbin Wang*, Jungmin Ha*, Joanna McKittrick and Shyue Ping Ong at UC San Diego; and Yoon Hwa Kim* and Won Bin Im at Chonnam National University, Republic of Korea.

*These authors contributed equally to this work

The work was funded by the National Science Foundation, Ceramics Program (grant 1411192). Computational resources were provided by the Triton Shared Computing Cluster at UC San Diego, the National Energy Research Scientific Computing Centre, and the Extreme Science and Engineering Discovery Environment supported by the National Science Foundation (grant ACI-1053575). The work was also supported by the Basic Science Research Program through the National Research Foundation of Korea, which is funded by the Ministry of Science and ICT (NRF-2017R1A2B3011967).