Archive for January, 2021

RSC paper mill retractions

Below is a list of papers retracted in connection with what we believe is a paper mill. Please see http://rsc.li/paper-mill-response for more information.

1. https://doi.org/10.1039/D1RA90011K
2. https://doi.org/10.1039/D1RA90018H
3. https://doi.org/10.1039/D1RA90019F
4. https://doi.org/10.1039/D1RA90023D
5. https://doi.org/10.1039/D1RA90020J
6. https://doi.org/10.1039/D1RA90015C
7. https://doi.org/10.1039/D1RA90013G
8. https://doi.org/10.1039/D1RA90006D
9. https://doi.org/10.1039/D1RA90007B
10. https://doi.org/10.1039/D1RA90010B
11. https://doi.org/10.1039/D1RA90008K
12. https://doi.org/10.1039/D1RA90012A
13. https://doi.org/10.1039/D1RA90014E
14. https://doi.org/10.1039/D1RA90016A
15. https://doi.org/10.1039/D1RA90017J
16. https://doi.org/10.1039/D1RA90021H
17. https://doi.org/10.1039/D1RA90022F
18. https://doi.org/10.1039/D1RA90024B
19. https://doi.org/10.1039/D1RA90025K
20. https://doi.org/10.1039/D1RA90026A
21. https://doi.org/10.1039/D1RA90027G
22. https://doi.org/10.1039/D1RA90028E
23. https://doi.org/10.1039/D1RA90030G
24. https://doi.org/10.1039/D1RA90031E
25. https://doi.org/10.1039/D1RA90046C
26. https://doi.org/10.1039/D1RA90033A
27. https://doi.org/10.1039/D1RA90034J
28. https://doi.org/10.1039/D1RA90035H
29. https://doi.org/10.1039/D1RA90032C
30. https://doi.org/10.1039/D1RA90036F
31. https://doi.org/10.1039/D1RA90037D
32. https://doi.org/10.1039/D1RA90038B
33. https://doi.org/10.1039/D1RA90039K
34. https://doi.org/10.1039/D1RA90040D
35. https://doi.org/10.1039/D1RA90047A
36. https://doi.org/10.1039/D1RA90048J
37. https://doi.org/10.1039/D1RA90049H
38. https://doi.org/10.1039/D1RA90050A
39. https://doi.org/10.1039/D1RA90051J
40. https://doi.org/10.1039/D1RA90052H
41. https://doi.org/10.1039/D1RA90041B
42. https://doi.org/10.1039/D1RA90042K
43. https://doi.org/10.1039/D1RA90043A
44. https://doi.org/10.1039/D1RA90044G
45. https://doi.org/10.1039/D1RA90045E
46. https://doi.org/10.1039/D1RA90054D
47. https://doi.org/10.1039/D1RA90055B
48. https://doi.org/10.1039/D1RA90056K
49. https://doi.org/10.1039/D1RA90057A
50. https://doi.org/10.1039/D1RA90058G
51. https://doi.org/10.1039/D1RA90059E
52. https://doi.org/10.1039/D1RA90060A
53. https://doi.org/10.1039/D1RA90061G
54. https://doi.org/10.1039/D1RA90062E
55. https://doi.org/10.1039/D1RA90063C
56. https://doi.org/10.1039/D1RA90064A
57. https://doi.org/10.1039/D1RA90065J
58. https://doi.org/10.1039/D1RA90071D
59. https://doi.org/10.1039/D1RA90072B
60. https://doi.org/10.1039/D1RA90073K
61. https://doi.org/10.1039/D1RA90074A
62. https://doi.org/10.1039/D1RA90075G
63. https://doi.org/10.1039/D1RA90076E
64. https://doi.org/10.1039/D1RA90066H
65. https://doi.org/10.1039/D1RA90067F
66. https://doi.org/10.1039/D1RA90068D
67. https://doi.org/10.1039/D1RA90069B
68. https://doi.org/10.1039/D1RA90070F
69. https://doi.org/10.1039/D1FO90004H
70. https://doi.org/10.1039/D1MD90001C

The associated Editorial published in RSC Advances can be found at the following url: https://doi.org/10.1039/D1RA90009A

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RSC Advances HOT articles – a feature interview with Siamac Fazli, Vsevolod A. Peshkov and Rustam Zhumagambetov

We are very pleased to introduce Siamac Fazli, Vsevolod A. Peshkov and Rustam Zhumagambetov, corresponding and first authors of the paper ‘cheML.io: an online database of ML-generated molecules‘. Their article has been very well received and handpicked by our reviewers and handling editors as one of our December HOT articles. The authors told us more about the work that went into this article and what they hope to achieve in the future. You can find out more about their article below and find more HOT articles in our online collection.

Meet the authors

Siamac Fazli received his B.Sc. Physics degree from the University of Exeter in 2002, his M.Sc. in Medical Neuroscience from Charité University Hospital Berlin, Germany in 2004 and his Ph.D. in Computer Science from the Technical University Berlin, Germany in 2011 under the supervision of Prof. Dr. Klaus-Robert Müller. From 2011-2013 he worked as a postdoctoral researcher in the Machine Learning Group at the Technical University Berlin, Germany. In 2013, he was appointed Assistant Professor at Korea University, Seoul, Rep. of Korea. From 2016 to 2017 he worked as a Group Leader at Fraunhofer Institute for Telecommunications, Berlin, Germany. In 2018, he joined the Computer Science Department at Nazarbazev University as an Associate Professor. His current research interests include machine learning, computational chemistry and neuroscience.

 

 

 

Dr. Vsevolod A. Peshkov received his Diploma in Chemistry in 2008 from Lomonosov Moscow State University with Prof. Nikolay V. Lukashev. In 2009, he joined the group of Prof. Erik V. Van der Eycken at the University of Leuven (KU Leuven) as a doctoral student. He defended his doctoral thesis entitled “Synthesis of nitrogen-containing medium-sized rings fused with benzene or indole through transition metal-catalyzed carbocyclizations” in 2013. He then spent one year at the University of Pittsburgh working on several medicinal chemistry projects under Prof. Peter Wipf and Prof. Donna Huryn’s direction. In September 2014, he began his independent career at Soochow University, China. In August 2018, he took on the position of Assistant Professor and Chemistry Graduate Program Director at Nazarbayev University, Kazakhstan. His research centers on a diversity-oriented synthesis (DOS) of complex heterocyclic molecules using multicomponent, one-pot and tandem strategies. In addition, his research group is active in design and synthesis of novel fluorescent organic materials and their optical properties assessment.

 

Rustam Zhumagambetov has received his BSc in Computer Science from the School of Science and Technology, Nazarbayev University, Kazakhstan in 2019. He is currently pursuing a Master’s degree and working as a research assistant in the Computer Science department of the School of Engineering and Digital Sciences, Nazarbayev University, Kazakhstan.

 

 

 

 

Could you briefly explain the focus of your article to the non-specialist (in one or two sentences only) and why it is of current interest?
The goal of our work was to implement, validate, and compare the molecular outputs of a number of recently established machine learning algorithms for de novo molecule generation. As a result of these efforts, we created a unified database of virtual molecules in browse-able format – cheML.io. While there exists a body of literature that targets the generation of novel molecules, the audience of these works appears to be not as broad as it could be particularly because not all the researchers from the chemistry community are able to readily implement the ML algorithms described therein. That is why we decided to create our database that allows a broader audience to testify how the rapidly growing field of ML technology can be utilized for the molecular generation and in turn for the hit identification.

How big an impact could your results potentially have?
We hope that our database may provide assistance to the researchers who are interested in the chemical and biological validation of ML-generated molecules.

In your opinion, what are the key design considerations for your study?
We wanted to achieve high molecular diversity by aggregating the outcome stemming from 10 different ML frameworks into a single database. Once the database was assembled, we wanted to
couple it with a user-friendly web interface, which would allow users to browse and retrieve the data in a fast and convenient manner. Finally, we decided to provide users with the opportunity to request the generation of new molecules that could be particularly useful when a specific search leads to insufficient results.

Which part of the work towards this paper proved to be most challenging?
The most challenging part was to implement the generation on demand feature. Nevertheless, we were able to come up with the suitable solution that involves utilization of case specific training
datasets assembled through a 3-stage procedure that takes into account the structural complexity of the input motif.

What aspect of your work are you most excited about at the moment?
The generation on demand feature will allow users to contribute to the expansion of our database. We will also attempt to establish a communication channel with the users by providing them with the possibility to leave their feedback and suggestions.

What is the next step? What work is planned?
We are currently working on the establishment of new ML algorithms for molecular generation that could enhance the generation on demand feature of our database.

 

cheML.io: an online database of ML-generated molecules
Rustam Zhumagambetov, Daniyar Kazbek, Mansur Shakipov, Daulet Maksut, Vsevolod A. Peshkov and Siamac Fazli
RSC Adv., 2020,10, 45189-45198
DOI: 10.1039/D0RA07820D, Paper

RSC Advances Royal Society of ChemistrySubmit to RSC Advances today! Check out our author guidelines for information on our article types or find out more about the advantages of publishing in a Royal Society of Chemistry journal.

Keep up to date with our latest HOT articles, Reviews, Collections & more by following us on Twitter. You can also keep informed by signing up to our E-Alerts.

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RSC Advances HOT articles – a feature interview with Hsiang-Lin Liu

We are very pleased to introduce Hsiang-Lin Liu, corresponding authors of the paper ‘Anomalous boron isotope effects on electronic structure and lattice dynamics of CuB2O4‘. His article has been very well received and handpicked by our reviewers and handling editors as one of our November HOT articles. Hsiang-Lin told us more about the work that went into this article and what he hope to achieve in the future. You can find out more about the author and his article below and find more HOT articles in our online collection.

Meet the author

Dr. Hsiang-Lin Liu received his Ph.D. in Physics from University of Florida, USA. He is now a Physics Professor at National Taiwan Normal University, Taiwan. He manages a research group with a broad range of projects, including work on optical spectroscopic studies of two-dimensional and strongly correlated electronic materials.

 

 

 

 

Could you briefly explain the focus of your article to the non-specialist (in one or two sentences only) and why it is of current interest?
We investigate the boron isotope effects of CuB2O4 using optical spectroscopy. The unusual isotope effects in CuB2O4 as well as its magnetoelectric and complex electric and optical coupling properties make it a very interesting material to study.

How big an impact could your results potentially have?
Previous studies on the isotope effects of superconducting materials had largely helped in understanding and classifying these materials’ properties that have a huge technological impact. We anticipate that our results will give more interest in the complex properties of CuB2O4 and encourage exploration on the theoretical aspects of its unusual behavior.

Could you explain the motivation behind this study?
High Tc superconductors which are mostly copper compounds have been known to exhibit large isotope effects particularly in its magnetic data. This motivates us to explore the discrepancy of the isotope boron effects in CuB2O4.

In your opinion, what are the key design considerations for your study?
The important aspect to consider in this study is the quality of the samples used. We particularly study the high quality large single crystals of CuB2O4 enriched with 10B and 11B isotopes.

Which part of the work towards this paper proved to be most challenging?
Describing the basis of the anomalous isotope effect found in the absorption spectra is challenging since studies on the isotope effects are scarce in literature and detailed theoretical studies on the electronic band structure for CuB2O4 is not yet available.

What aspect of your work are you most excited about at the moment?
Materials that exhibit close interplay between spin, charge, orbital, and lattice degrees of freedom show a lot of unusual properties and identifying the distinct optical signatures of these materials is very exciting. The prospects of optical isotope effects in identifying materials with unique characteristics present new and exciting possibilities.

What is the next step? What work is planned?
Currently, we are studying optical signatures of other multiferroic materials.

 

Anomalous boron isotope effects on electronic structure and lattice dynamics of CuB2O4
Rea Divina Mero, Chun-Hao Lai, Chao-Hung Du and Hsiang-Lin Liu
RSC Adv., 2020,10, 41891-41900
DOI: 10.1039/D0RA08200G, Paper

RSC Advances Royal Society of ChemistrySubmit to RSC Advances today! Check out our author guidelines for information on our article types or find out more about the advantages of publishing in a Royal Society of Chemistry journal.

Keep up to date with our latest HOT articles, Reviews, Collections & more by following us on Twitter. You can also keep informed by signing up to our E-Alerts.

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