When we activate a cell phone screen, an LED flashlight, or a device that glows in the dark, the microscopic event is light emission or luminescence. This phenomenon occurs when a material absorbs energy, exciting its electrons. When these electrons return to their ground state, they release that absorbed energy, which is then transformed into light.
That released light can be visible, like the colors on a display, or invisible, such as the infrared light used in many technological devices. For a material to be considered truly useful and efficient, it must convert a majority of the absorbed energy into light, minimizing energy wasted as heat. This measure of performance—the ratio of emitted light to absorbed energy—is key for high brightness and efficiency. The better the conversion, the higher its luminescent efficiency.
The major hurdle today is the lack of a reliable, non-laboratory method to predict a material's light emission efficiency. Researchers are currently forced to manufacture numerous different luminescent compounds, test them individually in a lab, and analyze the results to find the best performer. This trial-and-error approach is time-consuming, costly, and often produces avoidable chemical waste. Given the thousands of possible chemical combinations and structures, it’s impossible to test them all, which severely limits the rapid and sustainable development of new light-based technologies.
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💡 Enhancing Light Emission: A New Computational Approach for Efficient Luminescent Materials
When we activate a cell phone screen, an LED flashlight, or a device that glows in the dark, the microscopic event is light emission or luminescence. This phenomenon occurs when a material absorbs energy, exciting its electrons. When these electrons return to their ground state, they release that absorbed energy, which is then transformed into light.
That released light can be visible, like the colors on a display, or invisible, such as the infrared light used in many technological devices. For a material to be considered truly useful and efficient, it must convert a majority of the absorbed energy into light, minimizing energy wasted as heat. This measure of performance—the ratio of emitted light to absorbed energy—is key for high brightness and efficiency. The better the conversion, the higher its luminescent efficiency.
The Challenge of Efficient Material Design
The major hurdle today is the lack of a reliable, non-laboratory method to predict a material's light emission efficiency. Researchers are currently forced to manufacture numerous different luminescent compounds, test them individually in a lab, and analyze the results to find the best performer. This trial-and-error approach is time-consuming, costly, and often produces avoidable chemical waste. Given the thousands of possible chemical combinations and structures, it’s impossible to test them all, which severely limits the rapid and sustainable development of new light-based technologies.
Introducing the Predictive Computational Model
To overcome this materials science challenge, Dr. Daniel Aravena, an academic in the Department of Materials Chemistry at the University of Santiago de Chile (Usach), is spearheading a Fondecyt Regular project. The goal is to develop a computational model capable of predicting which luminescent materials are most likely to emit light efficiently, circumventing the need for initial, costly synthesis. Using advanced simulations, the project aims to identify the most promising compounds for laboratory study, thereby reducing research time, effort, and environmental impact associated with traditional experimentation.
"What we aim to build is a computational model that accurately predicts the quantum yield of a material—that is, the ratio of emitted light to absorbed energy. We are merging theoretical simulations with highly detailed laboratory experiments. While our team designs and analyzes compounds on the computer, collaborating teams will synthesize them and precisely measure their light emission under various conditions, including temperature and time. All this data will train and refine the model, enabling us to identify the most promising materials in the future without synthesizing every possible option," explains Dr. Aravena.
The project relies on a close, dynamic collaboration between theory and experiment. Dr. Aravena's team will utilize computational tools to simulate how different materials behave upon energy absorption, estimating their potential light emission output. These simulations will be crucial for identifying underlying patterns and relationships between the chemical structure of the compounds and their luminous efficiency.
Concurrently, the potential luminescent materials will be synthesized and experimentally studied by specialized teams at Usach, the University of Chile, and associated laboratories in Brazil and Spain. These groups will conduct detailed light emission measurements, considering variables like time, temperature, and excitation energy. This essential experimental data will be used to validate and adjust the model, ensuring its predictions are increasingly accurate and practical for the design of new, efficient materials.
"This project presents a significant experimental challenge. We require difficult-to-obtain data, such as measuring light emission across a wide temperature range, including very low ranges near absolute zero. For this, we are collaborating with Professor Ricardo Costa de Santana’s group in Brazil and Professor Juan Cabanillas in Madrid, who possess the necessary, high-temporal-resolution equipment. These are key contributions that enable us to build a truly useful database to feed and validate our predictive model," the academic states.
While the core focus is on fundamental understanding of molecular light emission, the potential applications are vast. Luminescent materials are essential components in displays, LED lighting, optical sensors, medical devices, security tags, and advanced bio-visualization technologies for the human body. By developing a model that predicts the most promising compounds for specific uses, it becomes possible to design more efficient materials precisely tailored to different needs, significantly bypassing lengthy, traditional testing phases.
"If we successfully establish this predictive model, we can partner with high-level groups globally in the development of more efficient emissive technologies, marking a significant advancement for Chile. This approach will make materials research faster, cleaner, and more strategic, allowing us to contribute from fundamental science to the development of new technologies with concrete, real-world applications," the Usach academic concludes.