Databases catalogue the corpus of research literature into scientific categories and report classes of bibliometric data such as the number of citations to articles, the number of authors, journals, funding agencies, institutes, references, etc. The number of articles and citations in a category are gauges of productivity and scientific impact but a quantitative basis to compare researchers between categories is limited. Here, we compile a list of bibliometric indicators for 236 science categories and citation rates of the 500 most cited articles of each category. The number of citations per paper vary by several orders of magnitude and are highest in multidisciplinary sciences, general internal medicine, and biochemistry and lowest in literature, poetry, and dance. A regression model demonstrates that citation rates to the top articles in each category increase with the square root of the number of articles in a category and decrease proportionately with the age of the references: articles in categories that cite recent research are also cited more frequently. The citation rate correlates positively with the number of funding agencies that finance the research. The category h-index correlates with the average number of cites to the top 500 ranked articles of each category (R2=0.997). Furthermore, only a few journals publish the top 500 cited articles in each category: four journals publish 60% (σ=±20%) of these and ten publish 81% (σ=±15%).

In this work, internal and external flows over superhydrophobic (SH) polytetrafluoroethylene (PTFE) were studied. The SH surface was fabricated by a one-step femtosecond laser micromachining process. The drag reduction ability of the textured surface was studied experimentally both in microscale and macroscale internal flows. The slip length, which indicates drag reduction in fluid flow, was determined in microscale fluid flow with a cone-and-plate rheometer, whereas a pressure channel setup was used for macroscale flow experiments. The textured PTFE surface reduced drag in both experiments yielding comparable slip lengths. Moreover, the experimentally obtained slip lengths correspond well to the result obtained applying a semianalytical model, which considers the solid fraction of the textured surface. In addition to the internal flow studies, we fabricated SH PTFE spheres to test their drag reduction abilities in an external flow experiment, where the terminal velocities of the falling spheres were measured. These experiments were conducted at three different Reynolds numbers in both viscous and inertial flow regimes with pure glycerol, a 30% glycerol solution, and water. Surprisingly, the drag on the SH spheres was higher than the measured drag on the non-SH spheres. We hypothesize that the increase in form drag outweighs the decrease in friction drag on the SH sphere. Thus, the overall drag increased. These experiments demonstrate that a superhydrophobic surface that reduces drag in internal flow might not reduce drag in external flow.

Artificial neural networks (ANNs) are one of the most powerful and versatile tools provided by artificial intelligence and they have now been exploited by chemical engineers for several decades in countless applications. ANNs are computational tools providing a minimalistic mathematical model of neural functions. Coupled with raw data and a learning algorithm, they can be applied to tasks such as modelling, classification, and prediction. Recently, their popularity has grown remarkably and they now constitute one of the most relevant research areas within the fields of artificial intelligence and machine learning. ANNs are large collections of simple classifiers called neurons. Chemical engineers apply them to model complex relationships, predict reactor performance, and to automate process controllers. ANNs can leverage their ability to learn and exploit large data sets, but they can also get stuck in local minima or overfit and are difficult to reverse engineer. In 2016 and 2017, ANNs were cited in 13 245 Web of Science (WoS) articles, 538 of which were in chemical engineering; the top WoS categories were electrical & electronic engineering (1615 occurrences) artificial intelligence (1253), and energy & fuels (980). The top 4 journals mentioning ANNs were Neural Computing & Applications (117), Neurocomputing (84), Energies (76), and Renewable & Sustainable Energy Reviews (76). In the near future, as larger data sets become available (and arduous to analyze), chemical engineers will be able to apply and leverage more sophisticated ANN architectures.

Chemical engineers operate industrial plants, design reactors and equipment, manage capital projects, estimate costs, project earnings, and drive efficiency through innovation while maintaining rigorous safety standards. The undergraduate curriculum includes mathematics, physics, chemistry, mechanics, biology, and management, much of which is common with other engineering departments. [1] However, chemical engineering research is more related to chemistry. Here, we show that chemical engineers cite journals in WoS' chemical engineering category most, followed by physical chemistry, energy & fuels, multi-disciplinary chemistry, environmental science, and multi-disciplinary materials science. According to a bibliometric analysis, the major research poles include materials, biotechnology, catalysis, environment, and thermodynamics. The 5 top cited journals in 2012 were Ind. Eng. Chem. Res., J. Membrane Sci., Chem. Eng. Sci., J. Hazard. Mater., and J. Catal., which are not the journals with the highest impact factors of the category. Can. J. Chem. Eng. was ranked third among the 32 classical chemical engineering journals after AIChE J. and Chem. Eng. Sci. and with respect to the ratio of the number of citations accrued until August 2017 to the number of articles they published in 2012. Chinese researchers have authored more articles than any other nation and they co-author research most with the USA and other Pacific Rim nations. Research collaborations between nations follow linguistic, geographical, and historical traditions.

Q7 We cite other researchers to recognize their contribution, educate, and establish the foundation of the research. References should balance recent breakthroughs with past contributions. Between 2011 and 2014, Nature published over 3200 articles and letters that referenced 113 000 papers. What is the average age of the references in these papers (the difference between the year Nature published the paper and the year the cited article was published)?[1] 4 6 bold-italic8 10 12

Q8What are the minimum requirements for co-authorship? [1,2] i) conceive and design the study (or parts of it) ii) collect and analyze data iii) interpret data iv) draft the article v) revise parts of it vi) approve the final version vii) agree to be accountable for the resultsOther combinations of correct answers:

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In the Excel file of the supplementary content "Top 10 Journals per Scientific Category", the category "Materials Science Coating Films" only has 7 journals but the calculations in this file included 10. So, all the attributions from line 1114 downwards are displaced by 3 lines. That is, the three top journals from "Dermatology" are included in "Materials Science Coating Films", then three journals from "Political Science" are in "Dermatology", etc. The authors apologize for the mistake. A corrected supplementary file is displayed below. This correction does not, in any way, compromise the findings of the study, either in terms of the methodology, results, or interpretations drawn from the data therein.