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As previously stated, arguably the most mature and widely used set of tools is currently a combination of Pymatgen, FireWorks, Custodian, and Atomate (which is built upon the prior three Python packages). These tools were constructed as part of the Materials Project but have seen uses in other high-throughput DFT studies.
Another general workflow package for ...
18
I'm just as curious of a user here as you, but I was able to find that a Materials Modeling Wikipedia page does in fact exist. :)
Computational materials science and engineering uses modeling,
simulation, theory, and informatics to understand materials. Main
goals include discovering new materials, determining material behavior
and mechanisms, ...
18
Topological materials form a broad family including insulators, semimetals, and superconductors, of which perhaps the best known are topological insulators. For concreteness, I will focus on topological insulators as these are the ones specifically mentioned in the question.
Topological insulator. A topological insulator is an insulator whose Hamiltonian ...
16
Atomic Simulation Environment (Surfaces)
I am going to narrowly cover surface models in this answer since ASE is more than capable of handling a wide range of models from nanoparticles, surfaces, 2D layered materials, bulk 3D materials, etc.
Metal Surfaces
Pt(111) models for example can be easily created within the ase.build module as follows.
from ase.build ...
16
After a little research I found a great article [1], which provides a good overview to what I asked above in Figure 2. Summarising in a table:
| Method | effort | reliability | system size |
+------------------------+--------+--------------+-------------+
| Interatomic potentials | high | high* / low* | 10^8 |
| Linear-scaling DFT ...
15
I think these are some of the most popular:
pymatgen(+fireworks+custodian --> atomate)
these are all part of materials project, there are some good references available
OpenQD
this is a database like materials project but it's been used for high-throughput calculations
AiiDA
seems relatively newer but the site has a ton of good documentation and ...
13
Answering your last questions: yes, yes and yes.
One thing to consider is which approach do you want/need to use. You can use an atomistic approach where you simulate/model the properties and the material starting from the atomic structure of it (an input file with the list of atoms and its coordinates). The other approach is to use your material as a ...
12
Okay first some basics:
For most reactions we do not need to run molecular dynamics
Molecules are like springs and obey the principles of minimum energy. Therefore, normally the dynamics of a molecule will be distributed around the "minimum energy path" going from reactants to products.
The maximum along this minimum energy path is the transition ...
11
QMCPACK: is a modern high-performance open-source Quantum Monte Carlo (QMC) simulation code. QMCPACK is closely related to Nexus, which is another High Throughput Computing package for Quantum Chemistry calculations.
To add on to something Andrew Rosen said
"There are also many field-specific packages that attempt to automate workflows specific to ...
10
The computations do include quantum physics, since the very bare minimum of electronic structure calculations involve the quantum mechanics of electrons.
There's been quite a lot of development in computational chemistry in synthesis. While computational chemistry was pivotal already in the late 1980s in developing ozone safe alternatives to ...
10
If you are looking for theoretical prediction of candidate perovskite solar cell materials; I have come across several papers that couple high-throughput density functional theory calculations along with machine learning for new material prediction. I haven't seen any solar cell compound discovery theoretical work that eventually validated their predictions ...
8
I am sure there are A LOT of authors publishing papers to answer this very question. Mainly because the theories employed have face a paradigm since "one-size-doesn't-fit-all".
Here are the variables that affect this use of a certain method:
(i) Molecular models or periodic solids
(ii) Chemical Accuracy (energies with accuracy of < 1kcal/mol) - e.g. ...
8
Since the constituent monolayers have generally differing lattice constants, special care is needed in the construction of the atomic models in such a way that the strain is minimized.
Let us denote the primitive cell basis vectors of a hexagonal 2D material $i$ as {$a_i$,$b_i$}. The supercell basis vector may be constructed as $n_ia_i$+$m_ib_i$, where $n_i$...
8
As Thomas mentioned, there are tools from Materials Project that we use for structure similarity. See for example this paper, with code available in pymatgen. This works by creating local environment "fingerprints" (e.g. octahedral, tetrahedral sites, etc.) and creating a distance between structures based on this.
Other that this, one method I'm ...
7
Tensorflow and FireWorks are different kinds of software. The "workflow management" features of Tensorflow are primarily designed to manage running Tensorflow itself, while FireWorks and related tools are designed to manage running other software.
Tensorflow is a library for machine learning. It can be used to develop, train and evaluate machine ...
7
Strontium aluminate can be doped with europium to give a material with properties like you are expecting. This can be optimized to give maximum fluorescent yield as well, but keep in mind this will likely shift the wavelength.
The material must heat and cool in this process since absorption of light will not be 100% efficient and neither will the loss of ...
7
I think you need to know the potential energy surface (PES) of the system. Assuming the system is in equilibrium before applying the deformation, any modification will take it to a non-equilibrium state. Depending on in which points of the PES the system is/go and the amount of strain/stress accumulated during the compression, the tendency is to free the ...
7
Not sure what your input files are, but there's a technique based on spherical harmonics that is relevant described here: High Throughput Profiling of Molecular Shapes in Crystals https://doi.org/10.1038/srep22204
The spherical harmonics approximate the shape of the electron distribution. They are then made rotationally invariant, and result in a descriptor ...
6
The figure you are showing can be made in Adobe Illustrator or Gimp
I've recreated a crude rendition (very quickly) using adobe illustrator
The steps to get this far are:
create a sphere
cut the sphere in half with pathfinder divider tool
Revolve the half sphere with the 3d effect
in the revolve menu select Wireframe surface
in the revolve menu select map ...
6
The community-edited awesome materials informatics list has a section on "software frameworks", which includes many of the tools mentioned in the answers here & more.
Contributions welcome!
5
To add to the previous answer: the new lead-free halide double perovskite $\ce{Cs_2InAgCl_6}$ was discovered by first-principles and then synthesized:
G. Volonakis et al. $\ce{Cs_2InAgCl_6}$: A New Lead-Free Halide Double Perovskite with Direct Band Gap, J. Phys. Chem. Lett. 8, 772 (2017) https://pubs.acs.org/doi/10.1021/acs.jpclett.6b02682
I'm sure there ...
5
I have personally worked on many of these projects, and I consider the following paper as the most simplistic benchmark (as well as the Holy Grail) to better understand the properties of interest that need to be computed for energy storage materials, with necessary proof on why each of such properties are significant: High capacity reversible hydrogen ...
5
Properties that seem experimentally relevant and computationally accessible would include, naïvely:
Density of States at the Fermi level, relation with conductivity
Density of States above and below the Fermi level, relation with how much negative/positive charge the system will accept, and at what voltage
Density (in g/cm$^3$ trivially obtained from unit ...
4
Digital Image Correlation is used a few different ways in mechanical testing. On larger samples, it can be used as a digital extensometer to measure the overall strain in the sample. For ductile samples, it can also show a map of strain fields and how those fields grow fastest around the point of failure. This is especially useful for a heterogeneous sample, ...
3
QCArchive
The MolSSI QCArchive project is designed for running, storing and accessing hundreds of millions of quantum chemistry calculations for individuals and groups of researchers at any scale. The project has been discussed in a recent article, WIREs e1491 (2020), which also has a chemRxiv preprint.
3
I suspect this would be very difficult to do with DFT. A spin liquid is a very subtle magnetic state and DFT, as a method, is not usually good at describing the magnetic states of a system. Spin liquids are fairly difficult to understand and characterize even using methods that are specialized for strongly-correlated magnetism (like DMRG or QMC).
Where DFT ...
2
I had the same doubt regarding the validity of my calculations. In some cases, it was astonishing how certain well-known quantities like the bandgap of Silicon could be easily underestimated by DFT. But as seen in most research papers on DFT calculations, there is a difference in experimental and predicted values. This depends on various factors including ...
1
Make a supercell of both the unit cells, so that they fit on top of each other.
1
There is an initiative from IBM called RoboRXN. It is a free web service for predicting chemical reactions.
From the IBM Research Blog recent post:
The magic behind the RXN for Chemistry is a state-of-the-art neural
machine learning translation method that can predict the most likely
outcome of a chemical reaction using neural machine translation
...
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