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.
Geometry optimization corresponds to a system in equilibrium. It is the "average" position of a molecule vibrating in a well.
However, there are many cases where the system is "non-equilibrium" which are important to model.
For example, photochemistry can involve important non-equilibrium processes.
In photochemistry, relaxation to the ground-state ...
Ah, yes, the fun of force-field building.
For the answer to a simple geometry optimization, see I. Camps response below.
Skip to the end if you want what is a more general answer to building an entire force-field. Read the whole thing if you want some insight into force-fields, particularly partial charges.
First, doing an electronic structure calculation (...
In the examples below, you can generate a POSCAR by using a variety of tools, such as the Atomic Simulation Environment, to convert between CIF and POSCAR.
Experimental MOF Structures
CoRE MOF Database: The Computation-Ready, Experimental (CoRE) MOF database (paper, database link). This database contains experimental crystal structures of MOFs obtained from ...
All Gaussian jobs when completed without any error, will have, at the end of the output file, a phrase/thought/quote from someone famous. It is kind off an easteregg. My latest Gaussian successful job finished with this quote:
THERE IS NO SCIENCE WITHOUT FANCY, NOR ART WITHOUT FACTS.
-- VLADIMIR NABAKOV
Anyway, answering your second question:
There are three main Python tools that I am aware of that can do what you want and much more (and in all fairness, since you have access to all coordinates, you can code up literally whatever you want with any of these). Disclaimer: I haven't worked extensively with all of these, so make sure you try all of them, since I am not listing them in any particular ...
Gaussian can do all the way up to MP5 for single-point energies, but analytic gradients are only available for MP2, MP3, MP4(DQ) and MP4(SDQ), the latter including only single, double and quadruple substitutions.
MP4(SDTQ) which is like MP4(SDQ) but also with triple substitutions, and MP5, are listed in the manual as being able to do numerical gradients. ...
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 ...
Normally, if various proteins have the "same" cavities/clefts, this means that they are part of the same family and the amino acids that form the cavity are conserved.
I really don't think that the electronic properties (charges and electrostatic potential surface) are directly related to the geometrical shape. Instead, they are related to the ...
Complementing the @Nike answer:
Can we optimize a molecular structure using Moller-Plesset MP4 method
on GAUSSIAN software?
If yes what keyword do we have to add?
You need to add the corresponding keywords like below:
# opt mp4(sdtq)/6-31++g(d,p) geom=connectivity
From Gaussian site:
This keyword requests that a geometry optimization be ...
Yes, you can! In the Quantum ESPRESSO input file, in the "ATOMIC_POSITIONS" card, you have to present the atom name and its coordinates, something like:
Atom_name x_atom y_atom z_atom
There are three default variables: if_pos(1), if_pos(2), and if_pos(3) set to unity, acting as weights for the force. So to keep ...
You can safely use a dispersion corrected DFT method for 2D systems if your vacuum space is large enough, but there is another issue that must be explained.
Most of the current dispersion correction methods such as DFT-D(Grimmes D2/D3/D4), TS, MBD, etch methods are overestimating interlayer interaction, exfoliation energies. They are not safe to use if you ...
The SIESTA code has a branch (rel-Max-2) developed by researchers from Max Plank institute that include the calculations of forces and real-time TDDFT.
The TDDFT is merged into the main development branch and will be released in versions newer than 4.1 (i.e. 4.2 or 5.0).
To download it, go to the Gitlab page: https://gitlab.com/siesta-project/siesta/-/tree/...
1) Using CALYPSO with Quantum ESPRESSO
I want to create a nanoparticle of CuO and predict it's structure.
I've done unit cell relaxation with Quantum ESPRESSO. One tool to
predict nanocluster structure is Calypso which is PSO-based. I'm using
Quantum ESPRESSO with it. If anyone does Calypso structure prediction,
what are some ways for predicting nanocluster ...
In Bragg's law, $n\lambda=2d\sin(\theta)$. Here, $n$ is the order of the reflection, and corresponds to the path length difference between X-rays diffracted from two different layers of atoms, in terms of the number of wavelengths. So if the path lengths differ by exactly one wavelength, it is a first order reflection.
By convention, we treat all reflections ...
The VESTA package should be able to do it. But I'm not sure if it had rhombohedral or not. I recommend that you download and try Edit data -> Unit cell option. You should be able to find enough tutorials doing this.
Alternatively, the Quantum ATK package can handle the job. Refer to the Tutorial.
The question makes no sense, since a solid state system might have different phases, or a molecule might have different conformers. They may all be proper local minima of the energy functional, and with very small overall total energy differences.
For instance, J. Phys. Chem. A 117, 2269 (2013) is a benchmark study for the 52 different conformers of the ...
Not always the research pipeline is from experimental to theory. The group of Professor Artem Oganov had very interesting results where they started predicting theoretical structures (at extreme conditions) and then synthetize them in the lab. to confirm the predictions. One of their results is about $Na_3Cl$, $Na_2Cl$, $Na_3Cl_2$, $NaCl_3$, and $NaCl_7$.