The ISSN of Carbon is 00086223. An ISSN is an 8-digit code used to identify newspapers, journals, magazines and periodicals of all kinds and on all media–print and electronic.
Carbon - Subscription (non-OA) Journal
Carbon is a Subscription-based (non-OA) Journal. Publishers own the rights to the articles in their journals. Anyone who wants to read the articles should pay by individual or institution to access the articles. Anyone who wants to use the articles in any way must obtain permission from the publishers.
Carbon - Publisher
Carbon is published by Elsevier Ltd.,
which is located in the United Kingdom.
The Publication History of Carbon covers 1940, 1963-ongoing.
Carbon - Categories
Carbon is a peer-reviewed scientific journal.
The scope of Carbon covers
Chemistry (miscellaneous) (Q1), Materials Science (miscellaneous) (Q1).
The Impact Factor 2018 of Carbon is
7.466, which is just updated in 2019.
Compared with historical Impact Factor data, the Impact Factor 2018 of Carbon grew by
The Impact Factor Quartile of Carbon is
The Impact Factor (IF) or Journal Impact Factor (JIF) of an academic journal is a scientometric index that reflects the yearly average number of citations that recent articles published in a given journal received. It is frequently used as a proxy for the relative importance of a journal within its field; journals with higher impact factors are often deemed to be more important than those with lower ones. The Impact Factor measures the average number of citations received in a particular year (2018) by papers published in the journal during the two preceding years (2016-2017). Note that 2018 impact factors are reported in 2019; they cannot be calculated until all of the 2018 publications have been processed by the indexing agency.
Besides, 93% scientific research articles published by Carbon have received at least 1 citation in 2018. In addition to the 2-year Impact Factor, the 3-year Impact Factor and 5-year Impact Factor can provide further insights into the impact of Carbon.
Impact Factor Trend Prediction System provides an open, transparent, and straightforward platform to help academic researchers Predict future journal impact and performance through the wisdom of crowds. Impact Factor Trend Prediction System displays the exact community-driven Data without secret algorithms, hidden factors, or systematic delay.