Aims and scope
BMC Chemistry, formerly known as Chemistry Central Journal, is an open access, peer reviewed journal that publishes in the diverse field of chemistry, ranging from organic, inorganic and physical chemistry to medicinal and analytical contributions, as well as articles covering chemistry in the fields of environment and energy, materials and macromolecules, agriculture and food, and green and sustainable processes.
We are committed to supporting the community by welcoming content that evaluates fundamental concepts, highlights new developments, and promotes the application of chemical sciences in a broad range of research areas and industries. By providing an inclusive platform, we want to aid the advancement of chemical sciences and all associated research disciplines.
Editor
Tamara Hughes, BMC Series, UK
Assistant Editor
Kate Gaines, BMC Series, USA
Chair
Sang Ouk Kim, Korea Advanced Institute of Science and Technology
Trending Articles
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Articles
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Drying methodology effect on the phenolic content, antioxidant activity of Myrtus communis L. leaves ethanol extracts and soybean oil oxidative stability
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Synthesis, biological evaluation and docking studies of 1,2,4-oxadiazole linked 5-fluorouracil derivatives as anticancer agents
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Validated green spectrophotometric kinetic method for determination of Clindamycin Hydrochloride in capsules
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Rhodanine-3-acetamide derivatives as aldose and aldehyde reductase inhibitors to treat diabetic complications: synthesis, biological evaluation, molecular docking and simulation studies
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Chemistry in Second Life
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TiO2-graphene oxide nanocomposite as advanced photocatalytic materials
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Cacao seeds are a "Super Fruit": A comparative analysis of various fruit powders and products
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Transformation of PVP coated silver nanoparticles in a simulated wastewater treatment process and the effect on microbial communities
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Anthraquinonyl glycoside facilitates the standardization of graphene electrodes for the impedance detection of lectins
BMC Series blog
Featured articles
Figure 2
De novo design and bioactivity prediction of SARS-CoV-2 main protease inhibitors using recurrent neural network-based transfer learning
Santana & Silva-Jr developed a deep learning platform for de novo design of putative inhibitors of SARS-CoV-2 main protease. Among the top-20 predicted hits, they identified nine hits via molecular docking displaying binding poses and interactions similar to experimentally validated inhibitors.
photo by xandreaswork on Unsplash
Characterization of the key aroma compounds in three types of bagels by means of the sensomics approach
Lasekan et al evaluated the impact of cold fermentation time on bagel rolls, and key aroma-active compounds in the volatile fractions were sequentially characterized by an aroma extract dilution analysis, quantified by stable isotope dilution and analyzed by odor activity values respectively.
Graphical abstract
Relaxometric learning: a pattern recognition method for T2 relaxation curves based on machine learning supported by an analytical framework
Date et al describe a data mining method for NMR-based relaxometric data. Results suggest that relaxometric learning is a powerful and versatile alternative to conventional metabolomics approaches for evaluating fleshiness of chemical mixtures in food and for other biological and chemical research requiring a nondestructive, cost-effective, and time-saving method.
© Joachim
Characterization of polysaccharides from different species of brown seaweed using saccharide mapping and chromatographic analysis
In this study, Chen et al used HPLC, multi-angle laser light scattering, viscometry, refractive index detectors and FT-IR to discriminate polysaccharides from nine different species of brown algae. Results provide insights into the structure-function relationship of brown seaweed polysaccharides.
Get credit for your data!
Valuable data often go unpublished when they could be helping to progress science. Hence, the BMC Series introduced Data notes, a short article type allowing you to describe your data and publish them to make your data easier to find, cite and share.
You can publish your data in BMC Genomic Data (genomic, transcriptomic and high-throughput genotype data) or in BMC Research Notes (data from across all natural and clinical sciences).
More information about our unique article type can be found on the BMC Genomic Data and BMC Research Notes journal websites.
Welcome to BMC Chemistry
BMC Chemistry, formerly known as Chemistry Central Journal, is now part of the BMC series.
Chemistry Central Journal has served the chemistry community as a trusted open access resource for more than 10 years – and we are delighted to announce the next step on its journey. In January 2019 the journal has been renamed BMC Chemistry and now strengthens the BMC series footprint in the physical sciences by publishing quality articles and by pushing the boundaries of open chemistry.
For further information please refer to our blog and list of FAQs explaining this change in more detail.
BMC Series Focus Issues
(c) sankai - Getty Images - iStock
May: Understanding Mental Health
With Mental Health Awareness Month in May, the BMC Series presents a focus issue on ‘Understanding Mental Health’. We have brought together content to highlight research into understanding and improving mental health.
April: Our Changing Environment
In preparation for Earth Day on 22nd April, the BMC Series presents a focus issue on Our Changing Environment, highlighting research from across the journals on climate change, conservation, pollution, and the impact of environmental changes on human health and disease.
Annual Journal Metrics
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Speed
70 days to first decision for reviewed manuscripts only
63 days to first decision for all manuscripts
167 days from submission to acceptance
17 days from acceptance to publicationCitation Impact
For Chemistry Central Journal (former title)
2.493 - 2-year Impact Factor
2.837 - 5-year Impact Factor
1.261 - Source Normalized Impact per Paper (SNIP)
0.426 - SCImago Journal Rank (SJR)Usage
677,659 Downloads
92 Altmetric MentionsTransparency and Openness
TOP Factor Score - 9