The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Experimental observation of high thermal conductivity in boron arsenide
Abstract
Moving the heat aside with BAs: Thermal management becomes increasingly important as we decrease device size and increase computing power. Engineering materials with high thermal conductivity, such as boron arsenide (BAs), is hard because it is essential to avoid defects and impurities during synthesis, which would stop heat flow. Three different research groups have synthesized BAs with a thermal conductivity around 1000 watts per meter-kelvin: Kang et al. , Li et al. , and Tian et al. succeeded in synthesizing high-purity BAs with conductivities half that of diamond but more than double that of conventional metals (see the Perspective by Dames). The advance validates the search for high-thermal-conductivity materials and provides a new material that may be more easily integrated into semiconducting devices. Science , this issue p. 575 , p. 579 , p. 582 ; see also p. 549
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
Self-Consistent Equations Including Exchange and Correlation Effects
Kohn, W., & Sham, L. J. (1965) · Physical Review · doi:10.1103/physrev.140.a1133 · Cited by 64,135
Opportunities and challenges for a sustainable energy future
Chu, S., & Majumdar, A. (2012) · Nature · doi:10.1038/nature11475 · Cited by 12,550
Advanced capabilities for materials modelling with Q uantum ESPRESSO
Giannozzi, P., Andreussi, O., Brumme, T., Bunau, O., Buongiorno Nardelli, M., Calandra, M., Car, R., Cavazzoni, C., Ceresoli, D., Cococcioni, M., et al. (2017) · Journal of Physics: Condensed Matter · doi:10.1088/1361-648x/aa8f79 · Cited by 8,361
Self-citationThe chips are down for Moore’s law
Waldrop, M. M. (2016) · Nature · doi:10.1038/530144a · Cited by 2,397
United States Data Center Energy Usage Report
Lawrence Berkeley National Laboratory (LBNL), B., Shehabi, A., USDOE, Smith, S., Sartor, D., Brown, R., Herrlin, M., Koomey, J., Masanet, E., Horner, N., et al. (2016) · doi:10.2172/1372902 · Cited by 1,040
Heat transport in silicon from first-principles calculations
Esfarjani, K., Chen, G., & Stokes, H. T. (2011) · Physical Review B · doi:10.1103/physrevb.84.085204 · Cited by 759
Schmidt, A. J., Chen, X., & Chen, G. (2008) · Review of Scientific Instruments · doi:10.1063/1.3006335 · Cited by 655
Coherent Phonon Heat Conduction in Superlattices
Luckyanova, M. N., Garg, J., Esfarjani, K., Jandl, A., Bulsara, M. T., Schmidt, A. J., Minnich, A. J., Chen, S., Dresselhaus, M. S., Ren, Z., et al. (2012) · Science · doi:10.1126/science.1225549 · Cited by 630
Thermal Conductivity and Large Isotope Effect in GaN from First Principles
Lindsay, L., Broido, D. A., & Reinecke, T. L. (2012) · Physical Review Letters · doi:10.1103/physrevlett.109.095901 · Cited by 307
Mean free path spectra as a tool to understand thermal conductivity in bulk and nanostructures
Yang, F., & Dames, C. (2013) · Physical Review B · doi:10.1103/physrevb.87.035437 · Cited by 283
Cited by
Phonon-engineered extreme thermal conductivity materials
Qian, X., Zhou, J., & Chen, G. (2021) · Nature Materials · doi:10.1038/s41563-021-00918-3 · Cited by 837
Ultrahigh thermal conductivity in isotope-enriched cubic boron nitride
Chen, K., Song, B., Ravichandran, N. K., Zheng, Q., Chen, X., Lee, H., Sun, H., Li, S., Udalamatta Gamage, G. A. G., Tian, F., et al. (2020) · Science · doi:10.1126/science.aaz6149 · Cited by 336
Self-citation
Metadata
- Authors
- Kang, J. S., Li, M., Wu, H., Nguyen, H., & Hu, Y.
- Venue
- Science
- Published
- 2018-08-10
- Volume
- 361
- Issue
- 6402
- Pages
- 575-578
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2830336612
- Cited by
- 648
- References
- 11
- FWCI
- 20.15
- 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: Experimental observation of high thermal conductivity in boron arsenide. https://app.cochat.ai/papers/10.1126/science.aat5522
- The paper
- Kang, J. S., Li, M., Wu, H., Nguyen, H., & Hu, Y. (2018). Experimental observation of high thermal conductivity in boron arsenide. Science. https://doi.org/10.1126/science.aat5522
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.