The sample structures made are about 100 nanometer in feature size using silicon oxide
More structures that they have fabricated. Height about 4 nanometers. Features are precise down to +- 30 nanometers nanometer range. The circle has a measured diameter in the x direction of 457 ± 28.4 nm and in the y direction of 483 ± 45.4 nm, which demonstrates good replication of the desired size, exhibiting 8.6% distance inaccuracy in the x control. Height is accurate to + or – 0.1 nanometers. The triangle is + or – 17 nanometers.
NOTE: they are going to open source this and make the software freely available. combine this with the fab a lot of your own AFM parts and the Nvidia personal supercomputer. and a lot of people will be able to make very precise things. Admittedly mostly university and commercial labs right now, but pretty much any decent university or commercial lab could be working on nanoscale construction.
This looks like it should be big step (top down) towards molecular manufacturing.
“These tools allow you to go from basic, one-off scientific demonstrations of what can be done at the nanoscale to repetitively engineering surface features at the nanoscale,” said Rob Clark, Thomas Lord Professor and chair of the mechanical engineering and materials science department at Duke University’s Pratt School of Engineering.
The feat was accomplished by using the traditional computing language of macroscale milling machines to guide an atomic force microscope (AFM). The system reliably produced 3-D, nanometer-scale silicon oxide nanostructures through a process called anodization nanolithography, in which oxides are built on semiconducting and metallic surfaces by applying an electric field in the presence of tiny amounts of water.
“That’s the key to moving from basic science to industrial automation,” Clark said. “When you manufacture, it doesn’t matter if you can do it once, the question is: Can you do it 100 million times and what’s the variability over those 100 million times? Is it consistent enough that you can actually put it into a process?”
Clark and Matthew Johannes, who recently received his doctoral degree at Duke, will report their findings in the August 29 issue of the journal Nanotechnology (now available online) and expect to make their software and designs freely available online. The work was supported by the National Science Foundation.
They say that they can perform 3D work.
The papers and patents seem to talk about 15 nanometer feature sizes. AFMs can get down to smaller sizes 1 nanometer but less consistently.
Being able to repeat 100 million times the milling of features at 15-1000 nanometers in 3D using silicon oxide seems like a powerful step up from MEMS. They can always use chemical vapor deposition or dip ink pen lithography or other means to work in other materials.
Arrays of AFMs (which go up to 1 million probes) that could perform repetitive milling work as they describe would be a big step.
So how fast and easy will it be to get mastery of the work that they propose? (the industrial scaling of 100 million repetitions).
Seems then a short step to adapting the arrays of AFMs.
I think it could be use to produce high grade Claytronics.
current claytronics node, currently 3 centimeters or bit bigger than one inch.
The millimeter sized catom that this could enable
Millimeter sized – poor man’s utility fog.
100 nanometer utility foglet
I am guessing 4-6 years if things go right and if they are delivering what seems to be implied by the press release.
I think if this gets rolled out in a big and affordable way it will be significant validation of the vision of nanotechnology manufacturing.
If we work in some minimal bottom up and we would close the gap from molecules to macroscale. Using self assembly and other means to get molecules up to the size that this system can handle we could kluge together a molecular manufacturing process.
Success and scale form this plus success from Robert Freitas and Ralph Merkle and we would be pretty much all the way into useful molecular manufacturing.
We need the to see the paper on exact error rates and details of this work and to get a clear path and timing of industrialization and scaling.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
A frequent speaker at corporations, he has been a TEDx speaker, a Singularity University speaker and guest at numerous interviews for radio and podcasts. He is open to public speaking and advising engagements.