AI / Machine Learning

Mitsubishi Chemical has disclosed that it has long been developing Quantum Approximate Optimization Algorithms (QAOA) for the development of advanced OLED emitter materials. One of the main challenges in this route has been that calculation accuracy that could not be guaranteed due to the accumulation of noise that affected the state of the quantum computer. 

Mitsubishi Chemical has thus teamed up with Deloitte Tohmatsu and Classiq to compress the two quantum circuits used by Mitsubishi Chemical. The three companies managed to demonstrate up to 97% compression in the size of the first circuit and up to 54% on the second circuit. This dramatic compression will enable more accurate calculations as it mitigates the risk of errors during calculation. 

US-based Ares Materials announced that it Japan's Denka invested in the company, with an aim to expand its high-functional materials business. Denka invested via its corporate VC that is jointly managed with Pegasus Tech Ventures.

Ares Materials developed a design technique that utilizes materials informatics (AI) for using enethiols as a raw material and possesses the technology to produce high-performance optical films using the design technique. The company says its optical films offer high performance, low cost and a reduced environmental impact.

This is a guest post by Anastasiia Pusenkova, Quantum Application Lead at Nord Quantique

Quantum computing has seen explosive growth in recent years, offering phenomenal potential across multiple industries such as pharmaceuticals, logistics, energy and cryptography, to name a few. One of quantum’s most promising applications is simulation of materials, where advanced algorithms combined with error-corrected hardware could soon transform the entire industry.

Classically Intractable tasks

Classical computational methods ⁱ have driven scientific progress for decades, particularly in computational chemistry. However, computational demands increase significantly for larger molecules, making classical methods insufficient as they struggle with the exponential growth in the complexity of these calculations, and the resources required. This makes accurate simulations close to impossible for large chemical systems such as complex proteins, large biomolecules and advanced materials.

OLED emitter materials are the heart of the OLED device, and the materials that make the most impact on the performance of the OLED display. Most OLED displays utilize red, green and blue emitters.

The efficiency of the current state-of-the-art commercial red and green OLED emitters is excellent - it is in fact close to 100% internal quantum efficiency (IQE) which means that you cannot improve much on the efficiency of the emitter itself (there's still work to be done on getting the light out of the device). Blue OLED emission is a completely different story - current commercial blue emitters suffer from very low efficiency, around 25%. This means that three quarters of the energy goes to waste. Changing to a 100% IQE blue emitter could end up improving the total display efficiency by 20-30%.

August 7th, 2024 10:00 AM PT / 1:00 PM ET / 6:00 PM BST / 7:00 PM CEST

The rapid evolution of display technology requires the use of cutting-edge research methods to maintain progress. Industry innovators such as Panasonic, Samyang, and Samsung are adopting Schrödinger’s digital chemistry platform to drive innovation in their organic electronics R&D.

This webinar, “Leveraging atomistic simulation, machine learning, and cloud-based collaborative ideation for display materials discovery” will explore the union of physics-based simulations, machine learning (ML), and cloud-native collaboration and informatics tools in revolutionizing R&D innovation for display materials.

Japan-based Hyperfluorescence materials developer Kyulux announced that Jimyeong Yu will join its executive management team, as the company's new Chief Financial Officer (CFO). 

Jimyeong Yu will take over as Kyulux’s CFO, replacing Akira Minakuchi, who passed away in September 2023. As CFO of Kyulux, Jimyeong Yu will oversee financial accounting operations including procurement activities, and as a member of the management team, will be involved in formulating and implementing future business plans.

Researchers from Chung-Ang University developed a new AI model to predict the characteristics of blue OLED devices. The new model is highly accurate - and achieved a prediction accuracy of 99.2% for the triplet fusion rate constant and 99.9% for the triplet emission rate.

To develop this model, the researchers first developed modeling that improved the calculation accuracy of the triplet emission ratio, one of the key properties of blue light emitting materials. Based on this modeling, an AI model was created to predict the triplet emission ratio and fusion rate constant by generating a transient EL extinction curve.

Merck KGaA is a pioneer in high performance OLED material development, supplying a range of materials for AMOLED makers since the industry’s inception.

To learn more about Merck’s materials and views on the OLED industry, we conducted an interview with Dr. Georg Bernatz, Merck Electronics’ Global Head of OLED Technical Marketing. Georg Bernatz has received a PhD in Physics from the Philipps-Universität in Marburg, Germany in 2000. In 2004, Georg joined Merck, where, over the years, he worked in various functions and on various topics in the field of Liquid Crystals for displays. In 2018, Georg changed to OLED, leading OLED Physics Product Research, and in 2020 he became responsible for all Physics & Application Labs in Darmstadt for Display materials. Since October 2023, Georg is heading Merck’s Global Technical Marketing for OLED materials.

Hello Dr. Bernatz. Can you bring us up to date quickly on Merck's current OLED material products? What do you offer to OLED display makers?

Merck KGaA, Darmstadt, Germany is very active in the design, development and production of a broad variety of high performing OLED materials, with a strong focus on hole and electron transport materials (HTM, ETM), host materials for phosphorescent emitters as well as activities in the field of high efficiency blue.

Researchers from Japan's Keio University, in collaboration with Mitsubishi Chemical Corporation, developed a new method to accelerate the design of OLED materials, using a combination of classical computing with quantum computing.

The new approach combines a 'classic' machine learning model with a quantum-classical computational molecular design. Demonstrating the new approach, the researchers discovered a highly efficient OLED emitter, a deuterated derivative of Alq₃. The new emitter is not only highly efficient, it is also easy to synthesize. 

In recent years, we have seen accelerated OLED materials development, aided by software tools based on machine learning and Artificial Intelligence. This is an excellent development which contributes to the continued improvement in OLED efficiency, brightness and lifetime.

Kyulux's Kyumatic AI material discover system

The promise of these new technologies is the ability to screen millions of possible molecules and systems quickly and efficiently. Materials scientists can then take the most promising candidates and perform real synthesis and experiments to confirm the operation in actual OLED devices.