Materials Science

Enabling Fabrication Beyond 7nm

Share this post:

How did we get from the Palm Pilots of the 90s to the ultra-powerful smart phones of today? In large part, because of scaling, where integrated circuits are made with smaller feature sizes fitting more and more circuit elements in the same area of silicon at each technology generation. This sets our expectations that in 20 more years, our mobile devices of today will look like the Palm Pilot of yesterday. However, as current semiconductor fabrication processes are nearing fundamental limits, and the emergence of AI is driving demand for non-traditional computing architectures, new methods to fabricate at the nanoscale are required.

My team at IBM Research – Almaden in Silicon Valley has invented several new materials and material science processes that help address these issues. Our work, published recently in Applied Materials & Interfaces, shows a method of selectively depositing a material on feature sizes as small as 15nm (that’s 75,000x smaller than the diameter of a strand of hair) by simply growing a film in a selected area. With traditional methods of fabrication, this would require coating a substrate with resist, patterning the resist through an exposure step, developing the image, depositing an inorganic film and then stripping the resist to give you a patterned inorganic material. We found a way of depositing this inorganic film much more simply, using a self-aligned process, where we immerse a prepatterned substrate in a solution containing a special material and then add that coated substrate it to a deposition chamber and you’re done. We are literally able to grow a component of a device in a controllable manner at the nanoscale.


Scanning Electron Micrograph of a large field region showing low defectivity in a selectively deposited film, highlighted region is a large area with 100nm line spaces. Inset, enlarged area of a prepatterned tungsten surface where highlighted (blue) areas contain an inhibitory molecule synthesized at IBM Research – Almaden.

This simple process of self-alignment is one tool required to continue scaling as it promises to simplify complex processes, saving money and reducing errors in final devices.  In addition, our ability to compute complex problems is rapidly advancing, fueled by emerging technologies like AI and neuromorphic computing, each of which have very different hardware requirements in comparison to traditional semiconductor processes. Our self-alignment process provides an additional tool to fabricate non-traditional hardware that may require three dimensional structures such as cross-point arrays.

The idea of a selective deposition is not new. What is new is the synthesis and demonstration of a new material that enabled us to do this at a scale relevant for the semiconductor industry. We’ve primarily drawn from a depth of knowledge in the synthesis of new materials and the ability to tailor a chemical structure for demanding applications;1 in my time at Almaden, we’ve demonstrated this in the development of unique polymerizations,2 materials3,4 and characterization methods5,6. Once we develop methods of scaling this process, we can begin to integrate it as we build next generation hardware, whether it is for new AI hardware or making devices at the 7nm technology node or beyond. The thought of being a part of a technology advancement that could be in every smart phone or AI hardware in the future is an incredibly exciting endeavor.

Fifteen Nanometer Resolved Patterns in Selective Area Atomic Layer Deposition—Defectivity Reduction by Monolayer Design, R.J. Wojtecki, M. Mettry, N.F. Fine Nathel, A. Friz, A. De Silva, N. Arellano, H. Shobha. ACS Appl. Mater. Interfaces (2018), 10(44), 38630-38637.


(1) R.J. Wojtecki, A. Nelson. J. Poly. Sci. A. (2016), 54(4), 457-472.

(2) R.J. Wojtecki, G.O. Jones, A.Y. Yuen, W. Chin, D.J. Boday, A. Nelson, J.M. Garcia, Y.Y. Yang, J.L. Hedrick. J. Am. Chem. Soc. (2015), 137(45), 14248-14251.

(3) M. Zhang, A. Vora, W. Han, RJ Wojtecki, H. Maune, A. Le, L.E. Thompson, G.M. McClelland, F., Ribet, A.C. Engler, A. Nelson. Macromolecules (2015), 48(18), 6482-6488.

(4) J.M.W. Chan, R.J. Wojtecki, H. Sardon. A.L.Z. Lee, C.E. Smith, A. Shkumatov, S. Gao, H. Kong, Y.Y. Yang, J.L. Hedrick (2017), 6(2), 176-180.

(5) A. Vora, R.J. Wojtecki, K. Schmidt, A. Chunder, J.Y. Cheng, A. Nelson, D.P. Sanders. Polymer Chemistry (2016), 7(4), 940-950.

(6) R.J. Wojtecki, A.Y. Yuen, T.G. Zimmerman, G.O. Jones, H.W. Horn, D.J. Boday, J.L. Hedrick, J.M. Garcia. Analyst (2015), 140(15), 5184-5189.

More Materials Science stories

Unlocking the Potential of Today’s Noisy Quantum Computers for OLED Applications

Scientists at Mitsubishi Chemical, a member of the IBM Quantum Hub at Keio University in Japan, reached out to our team about experimenting with new approaches to error mitigation and novel quantum algorithms to address these very challenges. In the new arXiv preprint, “Applications of Quantum Computing for Investigations of Electronic Transitions in Phenylsulfonyl-carbazole TADF Emitters,” we – along with collaborators at Keio University and JSR - describe quantum computations of the “excited states,” or high energy states, of industrial chemical compounds that could potentially be used in the fabrication of efficient organic light emitting diode (OLED) devices.

Continue reading

IBM Research at SIGMOD 2020

ACM SIGMOD/PODS 2020 like many other events impacted by COVID-19 pandemic will be taking place virtually from June 14 through June 19. The focus of work at SIGMOD 2020 ranges from adding graph querying to relational databases, to natural language interfaces to data, to operationalizing data for new AI workloads. Results to be presented includes work done at our IBM Research-Almaden and IBM Research-India labs, as well as by our summer interns from universities and our partners in other IBM units.

Continue reading

Learning Chinese-Specific Encoding for Phonetic Similarity

Performing the mental gymnastics of making the phoenetic distinction between words and phrases such as “I’m hear” to ‘I’m here’ or “I can’t so but tons” to “I can’t sew buttons,” is familiar to anyone who has encountered autocorrected text messages, punny social media posts and the like. Although at first glance it may seem […]

Continue reading