Semiconductor technology is on the cusp of a new era of innovation thanks to significant leaps in material science – particularly in next-generation memories and advanced logic. To further enhance the inherent properties of semiconductor devices, there is a growing need for co-optimization of device and materials technology at higher levels of abstraction. This leads to an inflection point in materials research methodologies. Traditionally, the discovery of new materials relies on arduous, iterative, and costly lab synthesis and testing processes between semiconductor makers, tool manufacturers, and material suppliers. With AI pushing the demand for semiconductors to unprecedented levels, this model is challenged to meet the demand for rapid, co optimized, and efficient introduction and scaling of new materials. At the same time, there is a risk-averse tendency in the semiconductor industry when it comes to deploying new materials into established product lines in multi-billion-dollar fabs. As a consequence, materials suppliers need to spearhead innovation efforts in to accelerate, but also mitigate the risks associated with the introduction of new materials.
At EMD Electronics, the Electronics business sector of Merck KGaA Darmstadt, Germany, we are revolutionizing material discovery by our scientists and engineers using the most advanced digital tools coupled with the powerful capabilities at our Silicon Valley innovation center, Intermolecular. This focus on co-optimization of devices and materials using advanced device testing capabilities enable us to harness the potential of AI in scientific discovery. This, in turn, drives further AI advancements and accelerates innovation across various fields.
Our research primarily revolves around co-optimizing molecular design, process technology and materials integration. By studying the interactions between different materials, processes, and device architectures, we can identify solutions that exhibit superior performance at an earlier stage. Our work in areas such as DRAM capacitor stack engineering, Atomic Layer Etching (ALE), and Neuro-inspired Computing fully embrace and demonstrate this digital transformation. Using the rapidly evolving digital tools for materials modeling and discovery, we can expand the breadth and depth of our exploration space, and efficiently identify new molecules and integrated solutions that drive innovation for our customers.
In the new era of materials science, innovation is no longer solely determined by device size, but by the ability to create more intelligence within the material itself. In our presentation, we will showcase how we leverage data and AI to enable confident decision-making in building materials atom by atom throughout the entire materials R&D workflow – from ideation to experimentation.
