| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Materials Science | 417 | 31 | 113 | 16 |
| Engineering and Technology | 1184 | 25 | 30 | 5 |
The scientific interests tackled in the journal are Optoelectronics, Artificial intelligence, Composite material, Nanotechnology and Optics. The journal addresses concerns in Artificial intelligence which are intertwined with other disciplines, such as Computer vision and Pattern recognition.
The published papers investigate studies in Nanotechnology, Silicon, Taste, Composite material and Analytical chemistry. The most cited papers address concerns in Nanotechnology which are intertwined with other disciplines, such as Lithography, Fluorescence, LIGA, Microfabrication and Microstructure. The journal articles deal with Fluorescence in conjunction with Microthermal and similar fields in Optoelectronics.
The journal generally zeroes in on subjects such as Artificial intelligence, Computer vision, Optoelectronics, Control theory and Pattern recognition. The Artificial intelligence study tackling the subject of Deep learning is the focus of Sensors and Materials. Convolutional neural network is a focus of the Pattern recognition works in the journal.
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 Sensors and Materials (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 Sensors and Materials (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, 98.19% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 80.00% 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 0.00% of all publications and 20.00% 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.
Hiroyuki Fukushima;Masaki Akatsuka;Hiromi Kimura;Daichi Onoda
(2021)Go Okada;Kazuki Hirasawa;Takayuki Yanagida;Hidehito Nanto
(2021)Masaki Akatsuka;Hiromi Kimura;Daichi Onoda;Daiki Shiratori
(2021)Prom Kantuptim;Masaki Akatsuka;Daisuke Nakauchi;Takumi Kato
(2020)Masaki Akatsuka;Daisuke Nakauchi;Takumi Kato;Noriaki Kawaguchi
(2020)Pursuing a Materials Science degree opens many doors, but students often consider complementing their studies with other online programs. For those interested in a broad social impact, exploring msw programs can be a valuable addition, blending technical knowledge with social work expertise.
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Deciding on the right path also means understanding which areas have strong market demand. Reviewing the college majors connected to innovation and technology can help gauge future opportunities within and beyond Materials Science.
