alted
Joined 6 years ago
Joined 6 years ago
But maybe the easiest way to do (very low resolution) photolithography at home is to use dry film photoresist, which is like tape you can stick onto a copper PCB you then expose and etch; a cheap roll is ~$20 from eBay/Amazon.
[1] https://docs.hackerfab.org/home [2] https://dspace.mit.edu/handle/1721.1/93835 [3] https://www.inchfab.com/
If you're already using it for large file version control for, e.g., gamedev, and don't mind the cost, how well does it work to store all other company documents? I'd assume it has better scalability and permissions management than Nextcloud (not to mention the version control on par with git).
For a minimum 100 wafers = 10k chips, Groq may have paid $100M = $10k/chip purely in amortizing design costs.
Chip design (software + engineer time) and fabrication setup (lithography masks) grow exponentially [1][2] with smaller nodes, e.g., maybe $100M for Groq's current 14nm chips to ~$500M for their planned 4nm tapeout. Once you reach mass production (>>1000 wafers, which have ~150 large chips each), wafers are $10k each. On top of this, it takes ~1 year to design then have prototypes made. (These same issues still exist on older slower nodes, albeit not as bad.)
This could be reduced somewhat if chip design software were cheaper and margins were lower, but maybe 20% of this cost is due to fundamental manufacturing difficulty.
(disclosure: I don't work with recent tech nodes myself; this is my best guess)
[1] https://www.semianalysis.com/p/the-dark-side-of-the-semicond... [2] https://www.extremetech.com/computing/272096-3nm-process-nod...
They claim [1] to be able to make chips from a new design in only ~4 weeks compared to the usual 3-6 months required by anyone else, which is huge for R&D. They manage this by using an unusual relatively low-performance process (which is also what allows them to use plastic substrates), but it's arguably a worthwhile tradeoff (in return for slower larger transistors, you get significantly lower equipment cost and lead times). That the chips are flexible is almost an afterthought, I think, albeit a nifty one.
They've also announced efforts [2] toward open-sourcing their PDK, joining the growing movement toward open source chip design.
[1] https://www.pragmaticsemi.com/foundry [2] https://www.pragmaticsemi.com/newsroom/blogs/democratising-i...
Parasolid, the library used to perform the geometric operations (the most difficult and important part of a CAD program) also powers the likes of SolidWorks (the industry standard), NX, and Onshape, and is arguably the best in the world. Its licensing cost is presumably a large part of the Plasticity price.
Any given energy storage technology can store a maximum amount of energy in a fixed volume or mass. Behold one of my favorite plots: [1]
From lowest to highest energy density:
- springs, which use mechanical elastic potential energy, are kinda horrible
- capacitors, which use electric permittivity, aren't great
- next are both batteries and combusted fuels, which both use chemical reactions.
- nuclear gets us another few orders of magnitude
- finally, antimatter (E=mc^2) is a ways beyond that
Both batteries and fuels rely on the energy difference between unreacted molecules, so their theoretical energy density is the same. Well, actually, fuels are burnt to create heat which is converted to energy, and this heat->energy conversion is fundamentally thermodynamically inefficient (only ~tens of percent), whereas batteries are the same sorts of reaction but much more controlled. A sufficiently clever battery, which moves atoms around to react in the right places at the right time, is thus more efficient and thus energy-dense than fuel. However, moving atoms around like this to make a more efficient battery is much more advanced nanotech than what we currently have. But it's theoretically possible.
This is what biology does: us humans are powered by chemical storage (sugar/fat/glucose), which is used more efficiently than current batteries but without combustion. (lithium-ion is ~0.8 MJ/kg, glucose is ~16 MJ/kg, gasoline ~46 MJ/kg)
In other fields, a hobbyist can do wood/metalworking or learn programming or build a robot kit. There's an onramp for people to start learning the skills, which makes a huge ecosystem of gradually improving talent.
But in microfabrication, even though it's the only way to make chips, screens, cameras, inkjets, and LEDs, the minimum equipment cost is millions of dollars. Even worse, it takes even professionals months to fine-tune a manufacturing process to make a new thing.
As a result, R&D is much lower than it could be, and most fabrication is limited to circumstances with a high chance of mass production payoff.
- The Zero to ASIC course (and Tiny Tapeout) [1] explains transistor circuits and teaches you an open source software stack---and you get a chip physically manufactured! You could make the Nand to Tetris computer in actual silicon (if you can get enough transistors).
- To learn how things are manufactured on silicon wafers, get textbooks on microfabrication. A decent starting point is [2]. There's also a good video series [3] for a quick overview.
- To understand how a single transistor or diode works, get textbooks on "semiconductor devices". A good starting point is the free online [4].
[1] https://www.zerotoasiccourse.com/ https://tinytapeout.com/
[2] "Introduction to Microelectronic Fabrication" by Jaeger
[3] https://siliconrun.com/our-films/silicon-run-1/
[4] "Modern Semiconductor Devices for Integrated Circuits" by Chenming Hu, https://www.chu.berkeley.edu/modern-semiconductor-devices-fo...
Right now y'all look focused on digital logic somewhere between ASICs and FPGAs.
Any plans for custom chiplets? Custom analog layout might be much cheaper if done MPW or Tiny Tapeout style: design a mere ~100x100um area, then bond it to standardized chiplets for control/power.
Wikipedia estimates the Carrington was anywhere from -800 to -1750 [2].
[1] "On the probability of occurrence of extreme space weather events", Pete Riley, 2012, doi:10.1029/2011SW000734
[1] "Low-cost, open-source XYZ nanopositioner for high-precision analytical applications", https://doi.org/10.1016/j.ohx.2022.e00317