Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
researchgate.net
researchgate.net
But I think the main problem was that they never managed to scale up the clock speeds sufficiently, even though structure size (=> density) was already highly promising from the start.
Maybe in a slightly different history with some discoveries in different orders these could have replaced flash memory in SSDs completely.
But that whole episode thought me that betting on early technology is hard, and always a risky business, because no matter how promising an approach looks, if it turns out that you can not find the necessary improvements in only a single dimension, then the whole thing is kinda doomed and will probably never be competitive (=> a highly relevant insight especially when speculating about things like novel battery chemistries or the like).
That said, I think this is something a bit different, or at least a different application. If my translation of the summary is correct (I'm not very fluent in sciencese), it's basically using them as some kind of matrix multiplier rather than memory. Whether they're making use of power-off data retention at all was unclear to me, but then I just skimmed it.
Interesting, but I was really hoping for fast, persistent memory to appear.
As far as I know, they have no application apart from academic toy/reseearch subject right now. And you have to consider that there are a lot of niches for storage technology that they could have taken over (because there is a lot of tradeoffs to make, e.g. latency, bandwidth, persistence, density, power consumption).
We might be just a few breakthoughs from those things replacing flash memory in SSDs, or revolutionizing neural-network accelerator hardware, but I am quite skeptical for now.
Note: I still believe that this (and other stuff i'm skeptical about) is SUPER worthwhile to research and always a huge uphill battle, simply because we have invested hundreds of billions of dollars into improvements of CMOS technology and processes, and collected over half a century of experience with it...
But new tech is to me kinda like a startup-- not every technology is the future, just like not every startup is a unicorn. Investing is still the right move, but you have to be realistic about expectations (which modern media is absolutely not)
There is still, to this day, a numerical niche for these drives, which is being served imperfectly by either normal TLC drives of very large size, SLC cache drives, or DRAM expansion cards connecting to the CPU through a PCIE bus. Just not at the prices they wanted to charge.
I recall their early R/W speed performance projections being far faster than what they ever achieved with Optane drives.
WP:
"Development of 3D XPoint began around 2012.[8] Intel and Micron had developed other non-volatile phase-change memory (PCM) technologies previously;[note 1] Mark Durcan of Micron said 3D XPoint architecture differs from previous offerings of PCM, and uses chalcogenide materials for both selector and storage parts of the memory cell that are faster and more stable than traditional PCM materials like GST.[10] But today, it is thought of as a subset of ReRAM.[11] According to patents a variety of materials can be used as the chalcogenide material.[12][13][14]
3D XPoint has been stated to use electrical resistance and to be bit addressable.[15] Similarities to the resistive random-access memory under development by Crossbar Inc. have been noted, but 3D XPoint uses different storage physics.[8] Specifically, transistors are replaced by threshold switches as selectors in the memory cells.[16] 3D XPoint developers indicate that it is based on changes in resistance of the bulk material.[2] Intel CEO Brian Krzanich responded to ongoing questions on the XPoint material that the switching was based on "bulk material properties".[3] Intel has stated that 3D XPoint does not use a phase-change or memristor technology,[17] although this is disputed by independent reviewers.[18]
According to reverse engineering firm TechInsights, 3D XPoint uses germanium-antimony-tellurium (GST) with low silicon content as the data storage material which is accessed by ovonic threshold switches (OTSes)[19][20] made of ternary phased selenium-germanium-silicon with arsenic doping.[21][22]"
I mean, that's not because graphene has become a routine part of our material repertoire. It has no reason to be in those things, does nothing, and is just marketing fuel. We may put "graphene" in things, but we are not much closer to using its interesting properties.
We don't put it on a lot of things. It's expensive as hell.
I don't know, we've been working on digital computers since at least the late 1800s. Sometimes technology just takes a while.
That does make it hard to gamble on it if the time horizon is longer than you need to make a profit.
But I don't think we should convince ourselves that a technology that takes longer than 15 years to become profitable is doomed. If we thought like that we'd still be subsistence hunter gatherers.
My point is just that even with research-tech that sounds absolutely amazing (low power, persistent, high density) you just need to fail on a single dimension for it to basically become irrelevant.
This is also why its so easy for media to overhype research results, which (predictably) results in continuous disappointments and loss of trust (of the public) in science reporting and/or even science in general...
- The effect first discovered: 1907.
- First prototype device built: 1927.
- First commercially viable parts shipping: early 1960s.
- Ubiquitous and cheap as an indicator device: 1980s.
- Highly efficient, used for lighting: 2010s.
The principle never changed along the way. The specific materials changed quite a bit.
> To address the challenge of EUV lithography, researchers at Lawrence Livermore National Laboratory, Lawrence Berkeley National Laboratory, and Sandia National Laboratories were funded in the 1990s to perform basic research into the technical obstacles. The results of this successful effort were disseminated via a public/private partnership Cooperative R&D Agreement (CRADA) with the invention and rights wholly owned by the US government, but licensed and distributed under approval by DOE and Congress.[3] The CRADA consisted of a consortium of private companies and the Labs, manifested as an entity called the Extreme Ultraviolet Limited Liability Company (EUV LLC).[4]
> Intel, Canon, and Nikon (leaders in the field at the time), as well as the Dutch company ASML and Silicon Valley Group (SVG) all sought licensing. Congress denied[citation needed] the Japanese companies the necessary permission, as they were perceived[by whom?] as strong technical competitors at the time and should not benefit from taxpayer-funded research at the expense of American companies.[5] In 2001 SVG was acquired by ASML, leaving ASML as the sole benefactor of the critical technology.[6]
>By 2018, ASML succeeded in deploying the intellectual property from the EUV-LLC after several decades of developmental research
Those things where hyped out of nowhere, with lots of blatant lies making into the popular discourse (like that high-density prediction). I don't even know why, because nobody was making any serious bet on them. They are a very interesting design, that may still get some real-world usage (the manufacturing problems are a showstopper right now), but won't ever compete with flash.
Of course, then the question becomes one of refreshing their state, like DRAM.
which is probably a less spammy source than the ResearchGate link.
Any website that constantly asks me to login is spammy in by book. It's a for profit website that adds little value other than duplicating information from primary sources and occasionally mangling pdfs with redundant information to advertise themselves.
There's a reason millions of researchers have joined. That you don't find value or know what they provide is no reason others should not learn the value they add.
As a researcher I don’t see any value there. I’ll stick with Arxiv, thanks.
I use arxiv nearly every day, and also a few places that get things not on arxiv because the majority of papers are simply not there. Arxiv is paid for by universities paying subscriptions, locked in for five years at a time. It's also funded by Simons Foundation (which may not pay forever) and Cornell and many individual donors. Affiliate groups like professional societies and govts pay huge sums to keep it running. Many companies pay 10's of thousands annually to be members.
Piggybacking on their money while taking affront at a bigger, more comprehensive service, because they dare post an ad, seems somewhat short sighted, but to each his own.
ResearchGate is the largest academic social network, so many use it for that reason. Here's an (2014) Nature article on researcher usage of various sites that may surprise you https://www.nature.com/news/online-collaboration-scientists-...
Since a significant number of job postings for researchers as well and communication and networking opportunities are widely used on Research Gate, none of which is present on Arxiv, you are simply missing likely useful contacts and tools for your career. And I write this as a researcher for several decades, long before any of these were live.
As I said, enough people find value at research gate that millions do pay.
The brain is running on 20W of power and it has the best LLM, the best robotics control unit, very good sensor integration and all the other exciting stuff which we* want** AIs to have. I'd rather have that than nuclear powerplants feeding data centers.
* overreaching a bit
** also not really true for everyone
With a SOFC topping cycle they might approach 70-80% efficiency. SOFC with just a combustion turbine (no steam bottoming) could exceed 60%. Granted, SOFCs are direct chemical->electrical conversion, but their waste heat is very usefully hot.
I don't think it's entirely a coincidence that nuclear power plants in the US stopped being built about the same time combustion turbines (by themselves, without the steam bottoming cycle) reached efficiency parity with high temperature steam turbines.
(SOFC = solid oxide fuel cell, which operate around 1000 C.)
("Lower heating value" is based on energy that could be obtained burning natural gas to CO2 and water vapor. An additional 10% could be obtained by condensing the water vapor to liquid, this is "higher heating value".)
What's even more shocking is that conversion of food to energy period is ~90% efficient, which is crazy to me. The fact that you can burn food and measure the energy given off, and that's very close to how much energy you get from eating it- that's insane.
The efficiency of the human body is all over the place. Muscles are only ~30% efficient, and the rest is waste heat... but humans walk using orders of magnitude less power than any walking robot. As far as I know we have never made a powered walking machine that is 10% as efficient as a person. The only way we can beat it is with a carefully balanced, specially-lubricated pair of legs that is leaned downhill on a treadmill and powered by gravity.
Beating human locomotion in the general case is pretty far off. It's a combination of body plan, extreme optimization of joints and energy storage, and really good algorithms.
One killer feature of the human body is synovial fluid. It's very thin, non-newtonian, self-replenishing and contained in particularly low-friction bearing surfaces. It's certainly better than 99.9% of mechanical joints, because these surfaces filter, heal and re-lubricate themselves. Mechanical joints have sticky grease so they stay lubricated without maintenance, and work in the presence of water and grit. It's doubtful that any joint that doesn't heal itself can compete, long-term.
[1]: https://spectrum.ieee.org/durus-sri-ultra-efficient-humanoid...
It takes many years to train it though
Now you know why you always see new doctors
(This is also why LLMs passing medical exams, though impressive, has not rendered the profession obsolete: LLMs are book smart, but don't have the implicit knowledge that we humans only gain from practical experience).