The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
DIOPTAS: a program for reduction of two-dimensional X-ray diffraction data and data exploration
Abstract
The amount of data collected during synchrotron X-ray diffraction (XRD) experiments is constantly increasing. Most of the time, the data are collected with image detectors, which necessitates the use of image reduction/integration routines to extract structural information from measured XRD patterns. This step turns out to be a bottleneck in the data processing procedure due to a lack of suitable software packages. In particular, fast-running synchrotron experiments require online data reduction and analysis in real time so that experimental parameters can be adjusted interactively. Dioptas is a Python-based program for on-the-fly data processing and exploration of two-dimensional X-ray diffraction area detector data, specifically designed for the large amount of data collected at XRD beamlines at synchrotrons. Its fast data reduction algorithm and graphical data exploration capabilities make it ideal for online data processing during XRD experiments and batch post-processing of large numbers of images.
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.
Integrity signals
Registry
Cites
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.
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
Matplotlib: a 2D graphics environment
Hunter, J. D. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.55 · Cited by 39,249
Nika : software for two-dimensional data reduction
Ilavsky, J. (2012) · Journal of Applied Crystallography · doi:10.1107/s0021889812004037 · Cited by 923
Cited by
Superconductivity at 250 K in lanthanum hydride under high pressures
Drozdov, A. P., Kong, P. P., Minkov, V. S., Besedin, S. P., Kuzovnikov, M. A., Mozaffari, S., Balicas, L., Balakirev, F. F., Graf, D. E., Prakapenka, V. B., et al. (2019) · Nature · doi:10.1038/s41586-019-1201-8 · Cited by 1,633
Self-citationSignatures of superconductivity near 80 K in a nickelate under high pressure
Sun, H., Huo, M., Hu, X., Li, J., Liu, Z., Han, Y., Tang, L., Mao, Z., Yang, P., Wang, B., et al. (2023) · Nature · doi:10.1038/s41586-023-06408-7 · Cited by 746
Superconductivity up to 243 K in the yttrium-hydrogen system under high pressure
Kong, P., Minkov, V. S., Kuzovnikov, M. A., Drozdov, A. P., Besedin, S. P., Mozaffari, S., Balicas, L., Balakirev, F. F., Prakapenka, V. B., Chariton, S., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25372-2 · Cited by 528
Self-citationPolyoxometalated metal-organic framework superstructure for stable water oxidation
Yue, K., Lu, R., Gao, M., Song, F., Dai, Y., Xia, C., Mei, B., Dong, H., Qi, R., Zhang, D., et al. (2025) · Science · doi:10.1126/science.ads1466 · Cited by 322
High-pressure compressibility and vibrational properties of (Ca,Mn)CO 3
Liu, J., Caracas, R., Fan, D., Bobocioiu, E., Zhang, D., & Mao, W. L. (2016) · American Mineralogist · doi:10.2138/am-2016-5742 · Cited by 38
Metadata
- Authors
- Prescher, C., & Prakapenka, V. B.
- Venue
- High Pressure Research
- Publisher
- Informa UK Limited
- Published
- 2015-06-29
- Volume
- 35
- Issue
- 3
- Pages
- 223-230
- ISSN
- 0895-7959 (ISSN-L)
- 1477-2299
- OpenAlex
- W1531219050
- Cited by
- 1,981
- References
- 2
- FWCI
- 30.78
- Type
- journal article
- Language
- en
- Open access
- closed
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: DIOPTAS: a program for reduction of two-dimensional X-ray diffraction data and data exploration. https://app.cochat.ai/papers/10.1080/08957959.2015.1059835
- The paper
- Prescher, C., & Prakapenka, V. B. (2015). DIOPTAS: a program for reduction of two-dimensional X-ray diffraction data and data exploration. High Pressure Research. https://doi.org/10.1080/08957959.2015.1059835
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.
