Advancing semiconductor technology

Developing next-gen semiconductor technologies

Universities are making significant contributions to the growth and competitiveness of semiconductor manufacturing in the U.S. by leveraging their research capabilities, educational programs, industry partnerships, and advocacy efforts.

Carnegie Mellon University is well-positioned to develop the next generation of semiconductor technologies. The College of Engineering and the Manufacturing Futures Institute are bringing together scientists and engineers, including those in the mechanical, materials science, and electrical and computer departments who have the expertise needed to advance semiconductor manufacturing in the U.S. They are conducting research in state-of-the-art laboratories, including the Claire and John Bertucci Nanotechnology Laboratory.

Designing and developing innovative devices

Carnegie Mellon engineers and scientists are contributing to the evolution of electronics and computing technologies by optimizing speed, power consumption, and reliability, enabling continued miniaturization, and implementing new functionalities and architectures to improve the design of semiconductor devices and expand their range of applications and capabilities.

Among the efforts to prepare its students to foster innovation is the chip design course that the College of Engineering has added to the curriculum. A new initiative to work with industry partners to fund scholarships and fellowships for students who want to learn how to design integrated circuits is also helping to satisfy the demand for skilled engineers with these critical skills.


Researchers at Carnegie Mellon have been advancing information storage technology by reducing the size and power needs of digital data.

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New techniques for manufacturing semiconductors

The unique culture of collaboration at Carnegie Mellon has created opportunities for engineers and scientists with diverse expertise in manufacturing processes, material science, soft and stretchable electronics, 3D printing, robotics, nanotechnology, and more to work together. They are applying their diverse areas of expertise to developing novel approaches for producing scalable, reproducible, controllable, and low-cost semiconductor devices.

The Claire and John Bertucci Nanotechnology Laboratory houses more than 80 deposition, etch, lithography, and metrology processing and characterization tools for making nano-scale devices, including microchips and semiconductor components. Its Eden Hall Foundation Cleanroom features state-of-the-art controls, 19 new wet chemistry decks, 3 EMI-shielded rooms, and other advancements that support a continuously growing and diversified set of users.


The Carnegie Mellon nanofabrication facility provides multiple academic and industry users access to state-of-the-art equipment, as well as technical support for the making of nanoscale devices.


Researchers designed chips that can explain what caused newly manufactured chips to malfunction.

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Advanced materials for enhanced performance and flexibility

Materials science engineers at Carnegie Mellon are studying and developing new materials and optimizing existing materials for semiconductor applications. They are exploring novel manufacturing processes and working closely with electrical engineers to design and improve semiconductor devices. They are leading the development of flexible electronics and other emerging technologies that will be critical for achieving breakthroughs in performance, functionality, and sustainability.

The Carnegie Mellon Materials Characterization Facility is a world-class facility where advanced characterization techniques are being used to analyze the structure, composition, and properties of semiconductor materials and devices at atomic and nanoscale levels.

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Digital twins to ensure greater productivity and reliability

The widespread application of digital twin technology in manufacturing research at Carnegie Mellon University ensures that our engineers and computer scientists have the necessary skills and experience to develop accurate predictive digital models of physical twins. These models can significantly boost the productivity of chip and semiconductor manufacturing.

Digital twins have enormous potential to advance manufacturing systems. A digital twin operates in a bidirectional manner. That means live data continually updates the model so that the computing system is aware of the most current information, can understand both the equipment and the physical environment in which it is operating, and can then execute or recommend appropriate actions. Digital twin technology enables real-time monitoring and predictive maintenance, and in the future, it will enable co-optimized efficiencies with other digital and physical assets throughout the manufacturing ecosystem.

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More digital twin research