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  • Deep learning models have gained popularity for chemical reaction outcome prediction due to their ability to learn representations directly from the molecular structure, whereas Gaussian processes provide reliable uncertainty estimates but are unable to learn representations from the data. Here, the authors combine the feature learning ability of neural networks with uncertainty quantification of Gaussian processes in a deep kernel learning framework to predict reaction outcomes.

    • Sukriti Singh
    • José Miguel Hernández-Lobato
    ArticleOpen Access
  • For atomically precise nanoparticle synthesis, it is crucial to understand hierarchical interactions during nanostructure formation. Here, the authors observe the crystal seed formation and simultaneous nanocrystal aggregation of ceria from aqueous solution in real time to understand hierarchically different intra- and interparticle interactions governing the particle shapes.

    • Noboru Aoyagi
    • Ryuhei Motokawa
    • Atsushi Ikeda-Ohno
    ArticleOpen Access
  • Voltage-gated sodium channel subtype Nav1.7 is a promising drug target associated with neuropathic pain disorder, however, the current Nav1.7 inhibitors show limited efficacy in clinical trials. More new molecular entities need to be discovered. Here, the authors report a selective Nav1.7 inhibitor by using carbenoid-involved reactions to construct an oxindole-based library, applying it to the scaffold-oriented virtual screening, and validating the hit compound in a clinically relevant model.

    • Jirong Shu
    • Yuwei Wang
    • Wenhao Hu
    ArticleOpen Access
  • Machine learning (ML) is a powerful tool in the field of drug discovery, with the continuous development of new models, however, rational selection of the most appropriate model based on the task remains challenging. Here, the authors explore the capabilities of classical ML algorithms and newer models over a range of dataset tasks and show an optimal zone for each model type, developing a predictive model to aid in the selection of a modeling method based on dataset size and diversity.

    • Scott H. Snyder
    • Patricia A. Vignaux
    • Sean Ekins
    ArticleOpen Access
  • In machine learning of molecular properties, adequate molecular representation is crucial, as minor structural changes result in significant differences in the activity of interest. Here, the authors use a lower-dimensional representation of a molecular manifold to embed electronic attributes and retain the chemical intuition of molecular interactions, invariant to translational and rational degrees of freedom of the molecular surface, to ease model complexities and facilitate generalization even with relatively small datasets.

    • Tonglei Li
    • Nicholas J. Huls
    • Peng Hou
    ArticleOpen Access
  • CRISPR-Cas proteins appear not only as a genome editing tool but also as a promising diagnostic tool to detect nucleic acid targets, however, most of the CRISPR-based biosensors rely on labelled reporters for signal acquisition. Here, the authors develop a label-free CRISPR-Cas12a-based sensing platform by using supercoiled plasmid DNA as ratiometric reporters, detecting ssDNA targets with a limit of detection of around 100 fM, and applying it to detect various virus samples.

    • Noor Mohammad
    • Logan Talton
    • Qingshan Wei
    ArticleOpen Access
    • The electrochemical Leaf (e-Leaf) is an emerging technology that addresses complex enzyme cascades nanoconfined within a porous conducting material—exploiting efficient electron tunneling and local NADP(H) recycling to transduce catalysis and electricity. Here, the authors describe how the e-Leaf was discovered, the steps in its development so far, and the outlook for future research and applications.

      • Bhavin Siritanaratkul
      • Clare F. Megarity
      • Fraser A. Armstrong
      PerspectiveOpen Access
    • Brønsted basicity can be greatly enhanced by the mechanical entanglement of two or more interlocked molecular subunits within catenanes and rotaxanes. Here, the authors discuss the development of such mechanically interlocked superbases, and outline challenges and opportunities for future directions of research.

      • Giorgio Capocasa
      • Federico Frateloreto
      • Stefano Di Stefano
      Review ArticleOpen Access
    • Molecular complexes with single-molecule magnet or qubit properties are great candidates for quantum information storage and processing, however, device implementation requires controlled surface deposition and property retention, which is a challenge. This Perspective gives a brief overview of molecular properties on a surface relevant for magnetic molecules and how they are affected by surface deposition, pointing out possible ways of overcoming the problems encountered so far.

      • Guillem Gabarró-Riera
      • E. Carolina Sañudo
      PerspectiveOpen Access
    • Combinatorial biosynthesis of natural products is a method to synthesize structurally diverse molecules with defined modifications. Here, the authors review the various approaches used for combinatorial biosynthesis of fungal natural products by engineering biosynthetic enzymes and pathways to generate novel molecules.

      • Elizabeth Skellam
      • Sanjeevan Rajendran
      • Lei Li
      Review ArticleOpen Access
    • Fluorescence resonance energy transfer (FRET) is one of the most important fluorescence mechanisms, with multi-step FRET systems enabling sequential energy transfer as seen in natural photosynthetic systems. Here, the authors review recent progress in exploiting discrete supramolecular assemblies to achieve multi-step FRET between donors and multiple acceptors.

      • Dengli Chen
      • Tangxin Xiao
      • Leyong Wang
      PerspectiveOpen Access
  • Extraterrestrial carbon gives insights into the origin of life and processes that took place billions of years ago in our solar system. Here, the authors provide an overview of what is known and of unanswered questions with a meteoritical focus.

    • Oliver Christ
    • Fabrizio Nestola
    • Matteo Alvaro
    CommentOpen Access
  • Rare-earth telluride clusters enable the construction of highly crystalline rare-earth tellurides, but a general route for preparing such clusters is lacking. Now, a facile reduction approach produces rare-earth clusters supported by (poly)tellurido ligands, including a tri-tellurido ligand with a three-center, four-electron bonding structure.

    • Chenyu Wang
    Research HighlightOpen Access
  • The chemical reduction of group 1 metal cations to their zero-valent species is challenging. Now, a bipyridine-stabilized borate anion joins the ranks of suitable reducing agents and also proves active in the two-electron reduction of CO2.

    • Johannes Kreutzer
    Research HighlightOpen Access
  • FAIR (findable, accessible, interoperable and reusable) data practices are necessary to expedite knowledge discovery, encourage collaboration, and optimise resource use, fostering a robust foundation for future scientific progress. Here, the authors explore the use of FAIR practices to advance materials chemistry research, examining key repositories, highlighting their role in sharing scientific data, and examining the accessibility of these approaches.

    • Konstantin Stracke
    • Jack D. Evans
    CommentOpen Access
  • Communications Chemistry is pleased to introduce a Collection of articles focused on organomediated polymerization. Here, the Guest Editors highlight the themes within and look towards the future of this research field.

    • Satoshi Honda
    • Karin Odelius
    • Haritz Sardon
    EditorialOpen Access
Circular carbon economy

Electrocatalytic CO2 reduction

The electrochemical reduction of carbon dioxide (CO2) is a key technology to combat global climate issues. By utilizing renewable energy, we can convert greenhouse gases into value-added commodity chemicals. While there has been a growing number of CO2 research in recent years, there are still many unanswered fundamental questions and engineering challenges. With this collection, we encourage scientists from different academic backgrounds to explore these remaining challenges in the CO2 electrochemical reduction reaction and provide a forum for the CO2 community to share their latest research results. We welcome all submission of original research articles, reviews and perspectives related to the theme of CO2 electrocatalytic reduction.


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