| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Chemistry | 751 | 18 | 21 | 9 |
The main research concerns discussed in Journal of Laboratory Automation are Nanotechnology, Automation, Microfluidics, Chromatography and Laboratory automation. The journal dives deep in exploring the relationship between the study of Nanotechnology and Drug discovery. Journal of Laboratory Automation holds forums on Automation that merges themes from other disciplines such as Software, Embedded system and Throughput (business).
The in-depth study on Microfluidics also explores topics in the intersecting field of Biomedical engineering. Chromatography research discussed connects with the study of Analytical chemistry.
The journal papers primarily tackle Nanotechnology, Microfluidics, Biomedical engineering, Automation and Computational biology. While Nanotechnology is the focus of the journal papers, it also provides insights into the studies of Point of care, Fluorescence and Biochemical engineering. While the primary focus in the most cited articles is Automation, they also dissect topics surrounding Process engineering and Process (engineering) as a whole.
The journal primarily focuses on research topics in Humanities, Indonesian, Linguistics, Pedagogy and Higher education. Some problems in Humanities that were presented in it overlapped with concepts under Pragmatics, Charm (programming language), Meaning (non-linguistic) and Lyrics. The research on Indonesian tackled can also make contributions to studies in the areas of Meaning (linguistics), Contrastive analysis, Plural, Slang and Word formation.
The study on Linguistics presented is investigated in conjunction with research in Social media.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Journal of Laboratory Automation (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Journal of Laboratory Automation (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 62.50% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 0.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 83.33% of all publications and 16.67% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Fabian Barthels;Ulrich Barthels;Marvin Schwickert;Tanja Schirmeister
(2020)Hiroko Kudo;Kento Maejima;Yuki Hiruta;Daniel Citterio
(2020)Nicolás M. Morato;MyPhuong T. Le;Dylan T. Holden;R. Graham Cooks
(2021)E Enoch A W Councill;Nathanial B Axtell;Thy Truong;Yiran Liang
(2021)Malcolm A O'Neill;Ian Black;Breeanna Urbanowicz;Vivek Bharadwaj
(2020)Anna A. Popova;Sascha Dietrich;Wolfgang Huber;Wolfgang Huber;Markus Reischl
(2021)Asif Shajahan;Nitin T Supekar;Digantkumar Chapla;Christian Heiss
(2020)Peter J Smith;Peter J Smith;Malcolm A O'Neill;Jason Backe;Jason Backe;William S York;William S York
(2020)Anna A. Popova;Markus Reischl;Daniel Kazenmaier;Haijun Cui
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