@krisi: 5,000 photons is quite a good enough number for statistical process control. When it gets down to 500 or less things become really tricky for high reliability over huge numbers of elements which must be exposed. This is because the delivery is a stochastic process, there is no possible feedback loop to correct it.
It is the same reason why your digicam shows noise in low light, when it may be depending on less than 100 photons per pixel.
@resistion: I cited 8 sigma, not 6, since that is the level of reliability needed to make chips with a billion elements. So long as 88% of 5,000 is enough energy delivered to develop the resist, that is good. Of course there is also statistical variation in the resist chemistry, and some variation in the illumination. When a 20mJ/cm2 value is quoted that will normally allow for some variation in characterizing the resist. If not, then add 10% to the input power to be sure to meet the threshold.
thank you Dan for the elaborate explanation...would you be interested in presenting this technology at the emergin technologies symposium in Vancouver in 2015? preliminary program at www.cmosetr.com, firstname.lastname@example.org
To help folks who do not understand the value of the results identified in Rick's EETimes article, I submit the following:
One of the primary challenges holding back the insertion of EUV is the source's power and reliability. Imaging performance is not a primary concern as it is well characterized, robust and operational on IBM's NXE3300. The upgrade to our EUV source was intended to improve its power level and reliability. The 24 hour performance test was intended to stress those two parameters. It was never the intent of the test to generate 637 wafer exposures. That result was a by-product of the source operating correctly, at the increased power and reliably during the test period. Putting resist on the wafers would have had no value whatsoever, other than to test how well our rework process was working. At the EUV Center of Excellence in Albany, we are focused on understanding the "fundamentals of why", so that robust solutions can be developed for high volume manufacturing. The endurance test that we performed was expected to generate a number of performance anomalies. The anomalies would have provided us with learning opportunities to identify root causes and develop subsequent improvements to the technology. It was an unintended output that our source performed so well. However, the result did provide the first data point in the industry, that demonstrates that the current source technology does have the capability to achieve near term performance goals (wafer exposures per day). Since this result was significantly better than previously reported performance, IBM decided to share this with the semiconductor industry so that all could understand the significance and adjust their EUV activities accordingly. For IBM and our Alliance partners, this secured the EUV capability to support our 7nm technology node development.
This is my last response on this topic. It is time for us to get back to work on the maturing of EUV technology.
@resistion: The EUV photon energy is around 92eV or 15 attoJ. This implies about 5,000 photons to provide the 80 pJ necessary to expose a 20nm square. That should not have a shot noise problem. 8 sigma would be +-12%.
Perhaps you are thinking of e-beam, where the beams are typically > 5kV so the number of electrons is a real problem for shot noise?
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.