Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 172

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Large-Scale Condensed Matter DFT Simulations: Performance and Capabilities of the CRYSTAL Code

Open access
Erba, A., Baima, J., Bush, I., Orlando, R., Dovesi, R.·2017·Journal of Chemical Theory and Computation

Abstract

Nowadays, the efficient exploitation of high-performance computing resources is crucial to extend the applicability of first-principles theoretical methods to the description of large, progressively more realistic molecular and condensed matter systems. This can be achieved only by devising effective parallelization strategies for the most time-consuming steps of a calculation, which requires some effort given the usual complexity of quantum-mechanical algorithms, particularly so if parallelization is to be extended to all properties and not just to the basic functionalities of the code. In this Article, the performance and capabilities of the massively parallel version of the Crystal17 package for first-principles calculations on solids are discussed. In particular, we present: (i) recent developments allowing for a further improvement of the code scalability (up to 32 768 cores); (ii) a quantitative analysis of the scaling and memory requirements of the code when running calculations with several thousands (up to about 14 000) of atoms per cell; (iii) a documentation of the high numerical size consistency of the code; and (iv) an overview of recent ab initio studies of several physical properties (structural, energetic, electronic, vibrational, spectroscopic, thermodynamic, elastic, piezoelectric, topological) of large systems investigated with the code.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acs.jctc.7b00687

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 172

Metadata

Authors
Erba, A., Baima, J., Bush, I., Orlando, R., & Dovesi, R.
Venue
Journal of Chemical Theory and Computation
Published
2017-09-19
Volume
13
Issue
10
Pages
5019-5027
ISSN
  • 1549-9618 (ISSN-L)
  • 1549-9626
OpenAlex
W2752435843
Cited by
172
References
1
FWCI
11.06
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Large-Scale Condensed Matter DFT Simulations: Performance and Capabilities of the CRYSTAL Code. https://app.cochat.ai/papers/10.1021/acs.jctc.7b00687
The paper
Erba, A., Baima, J., Bush, I., Orlando, R., & Dovesi, R. (2017). Large-Scale Condensed Matter DFT Simulations: Performance and Capabilities of the CRYSTAL Code. Journal of Chemical Theory and Computation. https://doi.org/10.1021/acs.jctc.7b00687

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.