I agree with the other answer but there are many other resources:
Open Crystallographic Database which includes a large set of experimental crystal structures.
There's a related Theoretical Crystallographic Open Database
For zeolites, there's the IZA Database
For MOFs, there's the CoRE MOF database
Aflow also has a good repository
NOMAD has a variety of ...
There is the Materials Project:
From the site:
Harnessing the power of supercomputing and state of the art electronic structure methods, the Materials Project provides open web-based access to computed information on known and predicted materials as well as powerful analysis tools to inspire and design novel materials.
An open computational database of two-dimensional materials. A large dataset of 2D materials, with more than 6,000 monolayer structures, obtained from both top-down and bottom-up discovery procedures
2D structures and layered materials
Results from screening all known 3D crystal structures finding those that can be computationally exfoliated ...
Depending on what kind of materials looking for the following crystallographic databases can be relevant, too (unfortunately, for a cost):
Inorganic Crystal Structure Database (ICSD) by Karlsruhe University:
ICSD by FIZ/NIST: https://icsd.nist.gov/
Cambridge Crystal Data Centre (CCDC):
In addition to above recommendations, I also use American Mineralogist Crystal Structure Database.
The good thing about this place is that you can check the publications related to a specific geometry.
I usually use AMCSD and Materialsproject.
The problem is that this is a highly volatile question. In order to meaningfully benchmark programs, you have to use the exact same compiler flags (may require heavy hacking) and use the same algorithms and parameters (accuracy, cutoffs, quadrature grids, etc). But, if a program supports many kinds of algorithms, then each of them would have to be ...
Disclaimer: I'm the lead developer of Open Babel and Avogadro - and currently mentoring Google Summer of Code projects.
The biggest question is more "what kind of topics" interest you and/or what kind of skills you want to learn. Data Science? Informatics? Visualization? Reaction Prediction? QSAR? etc. That would help you refine the possible projects to ...
First, there are general-use repositories that are not specific to materials modeling.
Zenodo. Like several other approaches, each project gets a permanent DOI associated with it, and new versions can be uploaded with the same unique parent DOI for the project and version-specific DOI. One major upside of Zenodo is that it is managed by CERN, which is ...
Unfortunately, I don't believe such a resource exists. One should keep in mind that it's not just a matter of a single U value for every metal, of course. The "best" empirical U value will depend on the property of interest. Perhaps more problematic, not every metal environment is made equal. Different oxidation states, coordination environments, and overall ...
And the related Pybel are excellent platforms for starting a project because they have well written C++ and python APIs, and are specifically designed for cheminformatics 101. For example, cheminformatics involves
Storing a Molecule in various formats (e.g. smiles, twirlymol, 2d, xyz, etc)
Finding exact molecule
A locally interacting system displaying a continuous phase transition belongs to a universality class that is determined solely by the system symmetries and dimensionality.
Drawing from Wikipedia's list (itself mostly based on Ódor's paper) and this answer from Physics SE, here's a partial list of universality classes and critical exponents:
[Disclaimer - I am one of the co-authors of the 2D database on Materials Cloud (What you call "2D structures and layered materials", publishing the data of this work: N. Mounet et al., Nature Nanotech. 13, 246–252 (2018) so I will mostly refer to it below]
In general, these studies "extract" a layer from a bulk 3D material, and then often ...
Go to Basis Set Exchange and click on the elements in which you're interested, then click the basis set in which you're interested (in your question, you mentioned 6-31G) and then for "Format" you can choose "Gaussian" or any of various other programs. After all that, when you click "Get Basis Set" you will get the basis set ...
I have a different page on the NIST website (https://cccbdb.nist.gov/vibscale.asp) that gives uncertainties in the scaling factors. I believe many of these were actually established by NIST themselves from the database itself.
But many of them are in the paper you cite, in Table 1:
As you probably know, one problem is that most quantum chemical methods ...
The NIST Materials Resource Registry is not limited to computational resources, but refers to many of the codes you're looking for. Searching for "hub" only turns up two listings, both of which are tied to nanoHUB and Purdue.
When writing some simple Python script in Spyder code editor, I always feel envious of computer science people every time its linting tool points some silly mistake I do, for example, forgetting a ":" in the end of a function definition, or using a "=" instead of "==" in a logic expression. I think myself, why can't we have such nice things in computational ...
I'm not sure if this will exactly answer your question because dashboard is loosely defined, but I find "networks" to be a great way to represent reaction data.
For example, Rxn4Chemistry categorizes reactions in a way that "would be too large or complex to be simply visualized in a small number of plots."
A Java library for automated functional group implemented with the Chemical Development Kit (CDK) program. It should run on Windows/Mac/Linux operating systems.
It relies on the Ertl algorithm, which is also used by the RDKit for functional group detection. A key difference between the two implementations seems to be in their ...
I don't think any studies such as this are currently available, however I think they violate a general feeling I have about "benchmarking". Studies which do general benchmarks are designed more to highlight when a method is good, not which method is good.
If I benchmark pbesol vs pbe and I find that pbesol works well for solids for example, this ...
As an additional comment, the OPTIMADE consortium is developing a standard REST API to query many different databases with the same API.
Version 1.0 of the specs is out (on GitHub, and a version with DOI for 1.0 on Zenodo).
Many of the DBs mentioned earlier are now working to expose their data via OPTIMADE.
Beside performing the queries with any browser or ...
Running simulations with small molecules is one thing that I found quite difficult especially because most online guides/tutorials are focused on proteins. So, here's a rough idea of what to do:
Getting forcefield parameters: Your question is about this, so I will give a detailed explanation. There are many forcefields to choose from, e.g. MMFF94, UFF, ...
While it doesn't include intended uses directly and isn't necessarily exhaustive, check out the list of exchange-correlation functionals implemented by Libxc. There are a lot! They also include the literature references for each functional.
I don't think so. The Minnesota functional wiki page is a bit weird, since general density functional approximations don't have a page, and much more popular functionals like various LDAs, GGAs (e.g. BP86, PBE) and meta-GGAs (e.g. TPSS) haven't been described.
Most functionals are intended for ground-state energy calculations, while some are fit for ...
You can find a list of what you are looking for, in this link attached.
Most of them have experimental properties of molecular materials. I have shared a few examples below:
The PDBbind database is designed to provide a collection of experimentally measured binding affinity data (Kd, Ki, and IC50) exclusively for the protein-ligand complexes ...
I recently made charge densities available for the MOFs and coordination polymers of the Quantum MOF (QMOF) Database. Please read the GitHub page for details on how to access the charge densities. That being said, given the large size of the files, I wish you luck downloading it in bulk.
Thanks to Tyberius for pointing out one issue in the database in their comment.
The pycalphad database parser is strict, but also tries to prevent ambiguities or mistakes.
I made the following corrections:
Changed ELEMENT Y HCP_A3 8.89059+01 5.9664E+03 4.4434E+01 ! to ELEMENT Y HCP_A3 8.89059E+01 5.9664E+03 4.4434E+01 (adding E to the exponent of the mass)
The brief answer, remodeled from the comments earlier given: See the entries of COD, https://www.crystallography.net/cod/4331895.html, and their #4331896, #7220156, and #7220157 -- all coordinated with Al, and all (more or less) dish-like flat:
(credit to COD, entry #4331895).
This is because the ligand is engaged in complexation of the Al in the centre. ...
The Crystallography Open Database is a good database of experimental crystal structures, take a look at their .hkl files which contain structure factors.
The Materials Project, a computational database, also calculations X-ray diffraction patterns and absorption patterns (disclosure, I'm on the Materials Project staff).
You can also generate your own once ...
Ioffe: New Semiconductor Materials. Biology systems. Characteristics and Properties
From the site:
This section is intended to systematize parameters of semiconductor
compounds and heterostructures based on them. Such a WWW-archive has a
number of advantages: in particular, it enables physicists, both
theoreticians and experimentalists, to rapidly retrieve ...