The Materials Project
materialsproject.org
materialsproject.org
How do projects like this deal with papers published based on falsified data? Do they reproduce any of the source data themselves?
I can't speak to this specific instance, but Materials Project does try to pay close attention to questions of reproducibility and provenance. Materials Project runs open-source repos[0] so that its methods can be verified, individual calculations are available via an API[1] and we also partner with NOMAD[2] to make larger files and calculation artifacts available for direct download. This is in addition to documenting methods via peer-reviewed papers, online docs, etc.
This is not to say that issues of reproducibility don't still exist, or that we ourselves couldn't be doing better. It's a big problem in the community.
[0] https://github.com/materialsproject [1] https://api.materialsproject.org/docs [2] https://www.nomad-coe.eu
Btw many people (even trained) fail to reproduce legitimate work. It may not actually be fake or falsified, typically not being able to reproduce an experiment is insufficient evidence for retraction. I didn't watch the YouTube video.
People outside academia seem to believe that reproducibility is an explicit goal when publishing papers. Perhaps it should be, but generally speaking it isn't. Instead a paper is a record of the things the authors found interesting and novel when doing the work.
If they are wrong then you publish a paper with conflicting results. If there is fraud (which is different to "I can't replicate the results") then you deal with the publisher of the paper.
[1]: The importance of stupidity in scientific research | https://news.ycombinator.com/item?id=31977918
A few specifics that might be useful for scientists that are considering transitioning to industry.
Pivot sooner rather than later. The transition might be a bit rough early on. In general, you can't get away with the heroic/cowboy approach that you can in a smaller academic setting. The interview process can be rough and might have a bit of RNG to it.
Aim to jump around every 2 years (3 at the absolute most) early on in your career. This will help make sure you're leveling up your skill set, getting those hard earned experience points and seeing different approaches to the software development process.
Be mindful of "infrastructure"-ish positions that might make it hard to get noticed. You probably have a high skill ceiling, but you are rough around the edges. It's essential to find a mentor that sees your potential and can help you level up (this might be challenging for remote positions).
At a minimum, you'll have an order of magnitude more job opportunities and mobility. Mobility in academic projects can be challenging to navigate. It can be easier to find a place outside of the academic space where your interests and skills will be aligned. Industry can also have interesting problems to solve.
I suspect that the current economic climate combined with the current clusterfuck housing market might create challenges for retaining support staff and postdocs in these academic/national lab driven projects.
However, this is not to say there aren't some biases. A lot of the Materials Project collaborators work on battery research, so there is some bias towards battery materials. But people have used MP to search for new photocatalysts, for example (or carbon capture materials, new phosphors, thermoelectrics for solid-state refrigeration, lead-free piezoelectrics, transparent conductors, etc.. the list goes on).
Is there a torrent? How can we ensure that this treasury of materials knowledge is preserved 64, 256, or 1024 years into the future, even if, for example, the US goes to war against Russia or China and decides to criminalize exporting materials data?
We don't seed any torrents ourselves and only support API access (mainly because we're a small team and have to focus our effort), but with the open license I hope the data can live on wherever/however it can.
There seem to be some interesting efforts to run SQLite in the browser so that server infrastructure only has to provide bulk data access, with precomputed indices to avoid full table scans; I wonder if those might be applicable here: https://blog.ouseful.info/2022/02/11/sql-databases-in-the-br... (though of course if you aren't using SQLite as your backend now it might be a headache)
Such an approach, if it were feasible, would have the advantage that bulk data downloads wouldn't look very different from normal use.
Short answer to your question is that the API load should be fine (I regularly download large subsets of the database myself via the API for research purposes), although there are good and bad ways of writing API queries. We have some tutorials, workshops, etc. available to help newcomers to our API write good queries.
We also have an email address set up (heavy.api.use@materialsproject.org) where people can give us a heads up if they are concerned about putting an undue load on our servers; as much as we try to have reasonable automatic limits set, sometimes we have had issues! API traffic continues to grow too, which in some ways is a nice problem to have, but does mean this is a moving target.
By all means email me at mkhorton@lbl.gov if you're interested and I can sort it out.
In contrast, the Materials Project are computed predicted information on inorganic crystals (typically, ideal, on-stochiometric crystals), that might be used for many different device applications like solar, optoelectronics, batteries, etc. Many of these crystals will not be available to purchase and will need to be grown in a laboratory, and Materials Project is therefore much more focused towards active research into new materials.
All our predictions are benchmarked against experimental data wherever possible, but it's always a balancing act between things that can be calculated reliably and at scale, and the latest-and-greatest methods which give the most accurate predictions.
*Supposedly, they possessed conductivity about 10^6 times that of silver at room temperature, along the axis of growth.
Is there any way I could use this to see if there was merit in that idea?
It likely can't give you an instant answer, but it can be a good starting point for a research project. For example, Materials Project has information about the dielectric properties of a material, has datasets for electron conductivities, vibrational (phonon) properties and the like. So you would start by searching the dataset for the properties of interest to get a shortlist of candidate materials, and then do more focused studies based on those.
Note that the Materials Project does also have known materials in its database that are currently used extensively in real-world devices too, so it can also be used to provide additional information about those materials. In this way, if you're looking for an improvement on an existing material, you can start with a known-good material and see if similar materials might exist that offer an improvement on your property of interest.
What if the new materials are necessary to clean up the old messes?
With your method, we'd be stuck forever!
> Until we learn to clean up our messes (using science!) I don’t believe we should get to make new messes
Software, biology and chemistry are not even remotely comparable!
Software pollutes our culture and damages our political environments with toxic platforms, adtech tracking nightmares that have been co-opted by Stasi-esque government agencies. Those are just the first two things that come to mind.
Biology… hasn’t done too much harm. Biology’s biggest crime to date that I can think of is probably suicide seeds. Maybe there are things I’m not thinking of. Certainly crispr and GMOs pose a risk, but the benefits have outweighed the risk pretty well. But maybe we’ve just gotten lucky.
Chemistry… has a very long list. Forever chemicals, mustard gas and other chemical weapons, the chemical dousing chambers of el paso texas (search “bath riots”) and their legacy…
The Materials Project is for inorganic crystals. The project will not unleash new forever chemicals because it doesn't deal with organic molecules.
[1] https://www.epa.gov/international-cooperation/persistent-org...