The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Combinatorial and High-Throughput Screening of Materials Libraries: Review of State of the Art
Abstract
Rational materials design based on prior knowledge is attractive because it promises to avoid time-consuming synthesis and testing of numerous materials candidates. However with the increase of complexity of materials, the scientific ability for the rational materials design becomes progressively limited. As a result of this complexity, combinatorial and high-throughput (CHT) experimentation in materials science has been recognized as a new scientific approach to generate new knowledge. This review demonstrates the broad applicability of CHT experimentation technologies in discovery and optimization of new materials. We discuss general principles of CHT materials screening, followed by the detailed discussion of high-throughput materials characterization approaches, advances in data analysis/mining, and new materials developments facilitated by CHT experimentation. We critically analyze results of materials development in the areas most impacted by the CHT approaches, such as catalysis, electronic and functional materials, polymer-based industrial coatings, sensing materials, and biomaterials.
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
Computational high-throughput screening of electrocatalytic materials for hydrogen evolution
Greeley, J., Jaramillo, T. F., Bonde, J., Chorkendorff, I., & Nørskov, J. K. (2006) · Nature Materials · doi:10.1038/nmat1752 · Cited by 4,097
Belsky, A., Hellenbrandt, M., Karen, V. L., & Luksch, P. (2002) · Acta Crystallographica Section B Structural Science · doi:10.1107/s0108768102006948 · Cited by 1,379
Cited by
Rost, C. M., Sachet, E., Borman, T., Moballegh, A., Dickey, E. C., Hou, D., Jones, J. L., Curtarolo, S., & Maria, J.-P. (2015) · Nature Communications · doi:10.1038/ncomms9485 · Cited by 3,525
Accelerated exploration of multi-principal element alloys with solid solution phases
Senkov, O. N., Miller, J. D., Miracle, D. B., & Woodward, C. (2015) · Nature Communications · doi:10.1038/ncomms7529 · Cited by 871
Data‐Driven Materials Science: Status, Challenges, and Perspectives
Himanen, L., Geurts, A., Foster, A. S., & Rinke, P. (2019) · Advanced Science · doi:10.1002/advs.201900808 · Cited by 808
Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning
Kim, E., Huang, K., Saunders, A., McCallum, A., Ceder, G., & Olivetti, E. (2017) · Chemistry of Materials · doi:10.1021/acs.chemmater.7b03500 · Cited by 473
Rational Design of Flexible Two-Dimensional MXenes with Multiple Functionalities
Fu, Z., Wang, N., Legut, D., Si, C., Zhang, Q., Du, S., Germann, T. C., Francisco, J. S., & Zhang, R. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00348 · Cited by 396
Metadata
- Authors
- Potyrailo, R., Rajan, K., Stoewe, K., Takeuchi, I., Chisholm, B., & Lam, H.
- Venue
- ACS Combinatorial Science
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-08-31
- Volume
- 13
- Issue
- 6
- Pages
- 579-633
- ISSN
- 2156-8944 (ISSN-L)
- 2156-8952
- OpenAlex
- W2074497204
- Cited by
- 511
- References
- 2
- FWCI
- 13.17
- 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
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.